API tools faq
paste
Guest User

Untitled

a guest
Mar 22nd, 2018
203
0
Never
Add comment
Not a member of Pastebin yet? Sign Up, it unlocks many cool features!
text 1.86 MB | None | 0 0
raw download clone embed print report
  1. {
  2. "cells": [
  3. {
  4. "metadata": {},
  5. "cell_type": "markdown",
  6. "source": "# DLPAL"
  7. },
  8. {
  9. "metadata": {},
  10. "cell_type": "markdown",
  11. "source": "## Getting the data\n 1. Strategy Analyzer -> System_DLPALMinutePrinter\n \n 2. Change: a) Instrument b) Time Frame c) Start and End Date d) OOS Date\n \n 3. Output file is in \"C:\\Algos\\Backtest\\System_DLPALMinutePrinter\"\n \n 4. Move the file to \"C:\\Program Files\\DLPAL\\Data\""
  12. },
  13. {
  14. "metadata": {
  15. "trusted": true
  16. },
  17. "cell_type": "code",
  18. "source": "import os\nimport datetime\nimport pandas as pd\nimport numpy as np\nimport shutil\nimport glob\nimport itertools\nimport time\nimport random\nimport statistics\nfrom pathlib import Path\nfrom custom_dlpal import *\nfrom pathlib import Path\nfrom IPython.display import Image\nfrom IPython.core.display import HTML \n\n%run C:\\\\Users\\\\Workstation\\\\Desktop\\\\project-attribution\\\\custom_functions\\\\custom_gui.py\n%run C:\\\\Users\\\\Workstation\\\\Desktop\\\\project-attribution\\\\custom_functions\\\\custom_import.py\n%run C:\\\\Users\\\\Workstation\\\\Desktop\\\\project-attribution\\\\custom_functions\\\\custom_math.py\n%run custom_dlpal.py\n\nos.getcwd()",
  19. "execution_count": 6,
  20. "outputs": [
  21. {
  22. "output_type": "execute_result",
  23. "execution_count": 6,
  24. "data": {
  25. "text/plain": "'C:\\\\Users\\\\Workstation\\\\Desktop\\\\cxt-toolbox\\\\Current\\\\DLPAL Optimizer'"
  26. },
  27. "metadata": {}
  28. }
  29. ]
  30. },
  31. {
  32. "metadata": {},
  33. "cell_type": "markdown",
  34. "source": "## Copy and paste the input file name (without '.txt')\n## and move the .txt file to \"C:\\\\Program Files\\\\DLPAL\\\\Data\"\nBecause the need of admin access, so at the moment need to manually move it"
  35. },
  36. {
  37. "metadata": {
  38. "collapsed": true,
  39. "trusted": true
  40. },
  41. "cell_type": "code",
  42. "source": "# Edit\ninput_file_name = 'AMLP_M-60_20120103_20150930-10006558_20161212-10008675'",
  43. "execution_count": 7,
  44. "outputs": []
  45. },
  46. {
  47. "metadata": {
  48. "scrolled": true,
  49. "trusted": true
  50. },
  51. "cell_type": "code",
  52. "source": "# Run\n# Handle the case where the OOS date is wrongly input in Ninja\ninstrument = input_file_name.split(\"_\")[0]\ntime_frame = input_file_name.split(\"_\")[1]\nstart_date = input_file_name.split(\"_\")[2]\nstart_index = 10000001\nOOS_date = input_file_name.split(\"_\")[3].split(\"-\")[0]\nOOS_index = int(input_file_name.split(\"_\")[3].split(\"-\")[1])\nend_date = input_file_name.split(\"_\")[4].split(\"-\")[0]\nend_index = int(input_file_name.split(\"_\")[4].split(\"-\")[1])\n\nprint(\"Instrument:\",instrument,\" \",time_frame)\nprint(\"Start Date: \"+ start_date, \" Start Index: \", start_index)\nprint(\" End Date: \" + end_date, \" End Index: \", end_index)\nprint(\" OOS Date: \" + OOS_date, \" OOS Index: \", OOS_index)\n\n# Check your data directory\n# data_rel_path = os.path.relpath(\"C:\\\\Algos\\\\Backtest\\\\System_DLPALMinutePrinter\")\ndata_rel_path = os.path.relpath(\"C:\\\\Users\\\\Workstation\\\\Desktop\\\\cxt-toolbox\\\\Current\\\\DLPAL Optimizer\\\\Data\")\ntarget_rel_path = os.path.relpath(\"C:\\\\Program Files\\\\DLPAL6\\\\Data\")\n\ndata_file_path = data_rel_path+\"\\\\\"+input_file_name +\".txt\"\ntarget_file_path = target_rel_path+\"\\\\\"+instrument+\"_\"+time_frame +\".txt\"\n\nif Path(data_file_path).is_file():\n print(\"\\nData File Source Directory: \\n\", data_file_path)\n shutil.copy(data_file_path,target_file_path)\n print(\"\\nData File Moved to C:\\Program Files\\DLPAL4\\Data\")\n print(\"\\nFile Name: \",instrument+\"_\"+time_frame +\".txt\")\n",
  53. "execution_count": 8,
  54. "outputs": [
  55. {
  56. "output_type": "stream",
  57. "text": "Instrument: AMLP M-60\nStart Date: 20120103 Start Index: 10000001\n End Date: 20161212 End Index: 10008675\n OOS Date: 20150930 OOS Index: 10006558\n\nData File Source Directory: \n Data\\AMLP_M-60_20120103_20150930-10006558_20161212-10008675.txt\n\nData File Moved to C:\\Program Files\\DLPAL4\\Data\n\nFile Name: AMLP_M-60.txt\n",
  58. "name": "stdout"
  59. }
  60. ]
  61. },
  62. {
  63. "metadata": {},
  64. "cell_type": "markdown",
  65. "source": "## 1. Data Partition\n![Follow the Steps Here!](DLPAL_Instructions/Data_Partition.png)"
  66. },
  67. {
  68. "metadata": {},
  69. "cell_type": "markdown",
  70. "source": "## 2. T/S Files\n![Setting TP SL!](DLPAL_Instructions/Setting TP SL.png)"
  71. },
  72. {
  73. "metadata": {},
  74. "cell_type": "markdown",
  75. "source": "## 3. Mining (New Workspace)\nDo 5 first INSTEAD!!! Will change this image SOON!\n![Mining](DLPAL_Instructions/Mining.png)"
  76. },
  77. {
  78. "metadata": {},
  79. "cell_type": "markdown",
  80. "source": "## 4. Convert ALL the results to Ninja Code\n## 5. Save the Ninja Codes .txt file in \"C:\\Users\\Workstation\\Desktop\\cxt-toolbox\\Current\\DLPAL Optimizer\""
  81. },
  82. {
  83. "metadata": {
  84. "trusted": true
  85. },
  86. "cell_type": "code",
  87. "source": "# Edit\n# without '.txt'\nninja_code_file_name = \"AMLP_M5_12trs\"\n\nresult_directory = 'Results_Text_Files\\\\'+ninja_code_file_name\nall_tpsl = get_tpsl(result_directory)\nprint(\"TPSLs found:\",all_tpsl)",
  88. "execution_count": 91,
  89. "outputs": [
  90. {
  91. "name": "stdout",
  92. "output_type": "stream",
  93. "text": "TPSLs found: [[1, 1], [2, 2]]\n"
  94. }
  95. ]
  96. },
  97. {
  98. "metadata": {
  99. "trusted": true
  100. },
  101. "cell_type": "code",
  102. "source": "# Edit\nins_and_timeframe = ninja_code_file_name.split(\"_\")[0]+\"_\"+ninja_code_file_name.split(\"_\")[1]\ntpsl=[1,1]\n\n#=================================================================================================================\nLongRules, ShortRules, LongCount,ShortCount, TP, SL = generate_rules(result_directory,tpsl)\n\nall_rules_list, long_short_list, output_filename = writeOptimizationCode(ins_and_timeframe,LongRules, ShortRules, LongCount,ShortCount, TP, SL)\noutput_file = output_filename+\".cs\"\nninja_local_rel_path = os.path.relpath(\"C:\\\\Users\\\\Workstation\\\\Documents\\\\NinjaTrader 8\\\\bin\\\\Custom\\\\Strategies\")\n\n\nif Path(output_file).is_file():\n shutil.move(output_file,os.path.join(ninja_local_rel_path,output_file))\n print(\"\\nCS File Moved to C:\\\\Users\\\\Workstation\\\\Documents\\\\NinjaTrader 8\\\\bin\\\\Custom\\\\Strategies\")\n print(\"\\nFile Name: \",output_file)\n print(\"\\n[Note: The number in the file name is the upper limit of RuleNumber in Ninja]\")",
  103. "execution_count": 97,
  104. "outputs": [
  105. {
  106. "name": "stdout",
  107. "output_type": "stream",
  108. "text": "TPSL: [1, 1] --- Long Rules: 241, Short Rules: 159\n..\\..\\..\\..\\Documents\\NinjaTrader 8\\bin\\Custom\\Strategies\\cxt-strategies\\Miscellaneous\\System_DLPALOptimizer.cs\nFile exists\n----------------------------\nSuccessfully Created :DM_AMLP_M5_399_TP1_SL1.cs\n----------------------------\n\n\nCS File Moved to C:\\Users\\Workstation\\Documents\\NinjaTrader 8\\bin\\Custom\\Strategies\n\nFile Name: DM_AMLP_M5_399_TP1_SL1.cs\n\n[Note: The number in the file name is the upper limit of RuleNumber in Ninja]\n"
  109. }
  110. ]
  111. },
  112. {
  113. "metadata": {},
  114. "cell_type": "markdown",
  115. "source": "## 6. Open Ninja Strategy Analyzer and run the optimization of the strategy. \n## Change: Instrument, Time Frame, Period, TPSL, and Optimize from Rule = 0, to # appears in File Name\n## Make sure the Start Date and End Date cover the whole history available, not only the IS and OOS date in DLPAL\n## [come back when the optimization is done, could take up to few hours]\n![NinjaOptimization](DLPAL_Instructions/NinjaOptimization.png)"
  116. },
  117. {
  118. "metadata": {
  119. "trusted": true
  120. },
  121. "cell_type": "code",
  122. "source": "# Run\n\nopti_backtest_path=\"C:\\\\Algos\\\\Backtest\\\\\"+output_filename\nprint(\"Output Files are in: \",opti_backtest_path)\n\nColumns = ['Date', 'Model', 'Daily Return', 'Equity', 'Allocations', 'Attributions']\nTargetColName = 'Daily Return'\nSkipfooter = 1\n\nresult = glob.glob(opti_backtest_path + '\\\\*.csv')\n\ntry:\n os.remove(opti_backtest_path +'\\\\_Combine.cmd')\nexcept OSError:\n pass\n\nFileSwitch = np.repeat(True, len(result))\nWeights = 1\nLeverage = 1\n\ndf_list = DoFolderImport(opti_backtest_path, FileSwitch ,Columns,Skipfooter)\n",
  123. "execution_count": 8,
  124. "outputs": [
  125. {
  126. "name": "stdout",
  127. "output_type": "stream",
  128. "text": "Output Files are in: C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00000.csv with first row as headers\nAMLP-00000 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00001.csv with first row as headers\nAMLP-00001 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00002.csv with first row as headers\nAMLP-00002 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00003.csv with first row as headers\nAMLP-00003 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00004.csv with first row as headers\nAMLP-00004 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00005.csv with first row as headers\nAMLP-00005 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00006.csv with first row as headers\nAMLP-00006 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00007.csv with first row as headers\nAMLP-00007 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00008.csv with first row as headers\nAMLP-00008 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00009.csv with first row as headers\nAMLP-00009 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00010.csv with first row as headers\nAMLP-00010 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00011.csv with first row as headers\nAMLP-00011 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00012.csv with first row as headers\nAMLP-00012 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00013.csv with first row as headers\nAMLP-00013 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00014.csv with first row as headers\nAMLP-00014 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00015.csv with first row as headers\nAMLP-00015 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00016.csv with first row as headers\nAMLP-00016 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00017.csv with first row as headers\nAMLP-00017 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00018.csv with first row as headers\nAMLP-00018 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00019.csv with first row as headers\nAMLP-00019 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00020.csv with first row as headers\nAMLP-00020 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00021.csv with first row as headers\nAMLP-00021 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00022.csv with first row as headers\nAMLP-00022 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00023.csv with first row as headers\nAMLP-00023 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00024.csv with first row as headers\nAMLP-00024 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00025.csv with first row as headers\nAMLP-00025 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00026.csv with first row as headers\nAMLP-00026 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00027.csv with first row as headers\nAMLP-00027 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00028.csv with first row as headers\nAMLP-00028 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00029.csv with first row as headers\nAMLP-00029 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00030.csv with first row as headers\nAMLP-00030 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00031.csv with first row as headers\nAMLP-00031 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00032.csv with first row as headers\nAMLP-00032 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00033.csv with first row as headers\nAMLP-00033 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00034.csv with first row as headers\nAMLP-00034 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00035.csv with first row as headers\nAMLP-00035 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00036.csv with first row as headers\nAMLP-00036 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00037.csv with first row as headers\nAMLP-00037 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00038.csv with first row as headers\nAMLP-00038 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00039.csv with first row as headers\nAMLP-00039 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00040.csv with first row as headers\nAMLP-00040 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00041.csv with first row as headers\nAMLP-00041 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00042.csv with first row as headers\nAMLP-00042 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00043.csv with first row as headers\nAMLP-00043 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00044.csv with first row as headers\nAMLP-00044 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00045.csv with first row as headers\nAMLP-00045 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00046.csv with first row as headers\nAMLP-00046 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00047.csv with first row as headers\nAMLP-00047 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00048.csv with first row as headers\nAMLP-00048 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00049.csv with first row as headers\nAMLP-00049 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00050.csv with first row as headers\nAMLP-00050 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00051.csv with first row as headers\nAMLP-00051 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00052.csv with first row as headers\nAMLP-00052 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00053.csv with first row as headers\nAMLP-00053 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00054.csv with first row as headers\nAMLP-00054 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00055.csv with first row as headers\nAMLP-00055 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00056.csv with first row as headers\nAMLP-00056 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00057.csv with first row as headers\nAMLP-00057 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00058.csv with first row as headers\nAMLP-00058 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00059.csv with first row as headers\nAMLP-00059 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00060.csv with first row as headers\nAMLP-00060 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00061.csv with first row as headers\nAMLP-00061 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00062.csv with first row as headers\nAMLP-00062 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00063.csv with first row as headers\nAMLP-00063 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00064.csv with first row as headers\nAMLP-00064 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00065.csv with first row as headers\nAMLP-00065 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00066.csv with first row as headers\n"
  129. },
  130. {
  131. "name": "stdout",
  132. "output_type": "stream",
  133. "text": "AMLP-00066 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00067.csv with first row as headers\nAMLP-00067 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00068.csv with first row as headers\nAMLP-00068 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00069.csv with first row as headers\nAMLP-00069 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00070.csv with first row as headers\nAMLP-00070 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00071.csv with first row as headers\nAMLP-00071 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00072.csv with first row as headers\nAMLP-00072 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00073.csv with first row as headers\nAMLP-00073 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00074.csv with first row as headers\nAMLP-00074 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00075.csv with first row as headers\nAMLP-00075 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00076.csv with first row as headers\nAMLP-00076 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00077.csv with first row as headers\nAMLP-00077 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00078.csv with first row as headers\nAMLP-00078 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00079.csv with first row as headers\nAMLP-00079 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00080.csv with first row as headers\nAMLP-00080 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00081.csv with first row as headers\nAMLP-00081 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00082.csv with first row as headers\nAMLP-00082 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00083.csv with first row as headers\nAMLP-00083 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00084.csv with first row as headers\nAMLP-00084 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00085.csv with first row as headers\nAMLP-00085 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00086.csv with first row as headers\nAMLP-00086 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00087.csv with first row as headers\nAMLP-00087 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00088.csv with first row as headers\nAMLP-00088 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00089.csv with first row as headers\nAMLP-00089 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00090.csv with first row as headers\nAMLP-00090 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00091.csv with first row as headers\nAMLP-00091 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00092.csv with first row as headers\nAMLP-00092 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00093.csv with first row as headers\nAMLP-00093 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00094.csv with first row as headers\nAMLP-00094 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00095.csv with first row as headers\nAMLP-00095 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00096.csv with first row as headers\nAMLP-00096 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00097.csv with first row as headers\nAMLP-00097 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00098.csv with first row as headers\nAMLP-00098 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00099.csv with first row as headers\nAMLP-00099 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00100.csv with first row as headers\nAMLP-00100 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00101.csv with first row as headers\nAMLP-00101 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00102.csv with first row as headers\nAMLP-00102 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00103.csv with first row as headers\nAMLP-00103 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00104.csv with first row as headers\nAMLP-00104 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00105.csv with first row as headers\nAMLP-00105 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00106.csv with first row as headers\nAMLP-00106 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00107.csv with first row as headers\nAMLP-00107 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00108.csv with first row as headers\nAMLP-00108 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00109.csv with first row as headers\nAMLP-00109 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00110.csv with first row as headers\nAMLP-00110 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00111.csv with first row as headers\nAMLP-00111 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00112.csv with first row as headers\nAMLP-00112 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00113.csv with first row as headers\nAMLP-00113 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00114.csv with first row as headers\nAMLP-00114 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00115.csv with first row as headers\nAMLP-00115 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00116.csv with first row as headers\nAMLP-00116 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00117.csv with first row as headers\nAMLP-00117 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00118.csv with first row as headers\nAMLP-00118 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00119.csv with first row as headers\nAMLP-00119 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00120.csv with first row as headers\nAMLP-00120 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00121.csv with first row as headers\nAMLP-00121 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00122.csv with first row as headers\nAMLP-00122 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00123.csv with first row as headers\nAMLP-00123 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00124.csv with first row as headers\nAMLP-00124 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00125.csv with first row as headers\nAMLP-00125 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00126.csv with first row as headers\nAMLP-00126 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00127.csv with first row as headers\nAMLP-00127 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00128.csv with first row as headers\nAMLP-00128 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00129.csv with first row as headers\nAMLP-00129 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00130.csv with first row as headers\nAMLP-00130 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00131.csv with first row as headers\nAMLP-00131 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00132.csv with first row as headers\nAMLP-00132 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00133.csv with first row as headers\nAMLP-00133 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00134.csv with first row as headers\n"
  134. },
  135. {
  136. "name": "stdout",
  137. "output_type": "stream",
  138. "text": "AMLP-00134 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00135.csv with first row as headers\nAMLP-00135 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00136.csv with first row as headers\nAMLP-00136 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00137.csv with first row as headers\nAMLP-00137 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00138.csv with first row as headers\nAMLP-00138 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00139.csv with first row as headers\nAMLP-00139 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00140.csv with first row as headers\nAMLP-00140 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00141.csv with first row as headers\nAMLP-00141 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00142.csv with first row as headers\nAMLP-00142 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00143.csv with first row as headers\nAMLP-00143 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00144.csv with first row as headers\nAMLP-00144 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00145.csv with first row as headers\nAMLP-00145 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00146.csv with first row as headers\nAMLP-00146 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00147.csv with first row as headers\nAMLP-00147 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00148.csv with first row as headers\nAMLP-00148 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00149.csv with first row as headers\nAMLP-00149 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00150.csv with first row as headers\nAMLP-00150 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00151.csv with first row as headers\nAMLP-00151 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00152.csv with first row as headers\nAMLP-00152 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00153.csv with first row as headers\nAMLP-00153 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00154.csv with first row as headers\nAMLP-00154 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00155.csv with first row as headers\nAMLP-00155 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00156.csv with first row as headers\nAMLP-00156 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00157.csv with first row as headers\nAMLP-00157 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00158.csv with first row as headers\nAMLP-00158 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00159.csv with first row as headers\nAMLP-00159 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00160.csv with first row as headers\nAMLP-00160 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00161.csv with first row as headers\nAMLP-00161 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00162.csv with first row as headers\nAMLP-00162 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00163.csv with first row as headers\nAMLP-00163 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00164.csv with first row as headers\nAMLP-00164 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00165.csv with first row as headers\nAMLP-00165 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00166.csv with first row as headers\nAMLP-00166 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00167.csv with first row as headers\nAMLP-00167 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00168.csv with first row as headers\nAMLP-00168 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00169.csv with first row as headers\nAMLP-00169 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00170.csv with first row as headers\nAMLP-00170 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00171.csv with first row as headers\nAMLP-00171 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00172.csv with first row as headers\nAMLP-00172 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00173.csv with first row as headers\nAMLP-00173 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00174.csv with first row as headers\nAMLP-00174 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00175.csv with first row as headers\nAMLP-00175 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00176.csv with first row as headers\nAMLP-00176 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00177.csv with first row as headers\nAMLP-00177 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00178.csv with first row as headers\nAMLP-00178 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00179.csv with first row as headers\nAMLP-00179 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00180.csv with first row as headers\nAMLP-00180 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00181.csv with first row as headers\nAMLP-00181 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00182.csv with first row as headers\nAMLP-00182 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00183.csv with first row as headers\nAMLP-00183 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00184.csv with first row as headers\nAMLP-00184 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00185.csv with first row as headers\nAMLP-00185 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00186.csv with first row as headers\nAMLP-00186 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00187.csv with first row as headers\nAMLP-00187 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00188.csv with first row as headers\nAMLP-00188 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00189.csv with first row as headers\nAMLP-00189 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00190.csv with first row as headers\nAMLP-00190 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00191.csv with first row as headers\nAMLP-00191 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00192.csv with first row as headers\nAMLP-00192 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00193.csv with first row as headers\nAMLP-00193 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00194.csv with first row as headers\nAMLP-00194 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00195.csv with first row as headers\nAMLP-00195 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00196.csv with first row as headers\nAMLP-00196 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00197.csv with first row as headers\nAMLP-00197 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00198.csv with first row as headers\nAMLP-00198 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00199.csv with first row as headers\nAMLP-00199 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00200.csv with first row as headers\nAMLP-00200 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00201.csv with first row as headers\n"
  139. },
  140. {
  141. "name": "stdout",
  142. "output_type": "stream",
  143. "text": "AMLP-00201 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00202.csv with first row as headers\nAMLP-00202 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00203.csv with first row as headers\nAMLP-00203 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00204.csv with first row as headers\nAMLP-00204 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00205.csv with first row as headers\nAMLP-00205 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00206.csv with first row as headers\nAMLP-00206 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00207.csv with first row as headers\nAMLP-00207 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00208.csv with first row as headers\nAMLP-00208 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00209.csv with first row as headers\nAMLP-00209 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00210.csv with first row as headers\nAMLP-00210 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00211.csv with first row as headers\nAMLP-00211 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00212.csv with first row as headers\nAMLP-00212 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00213.csv with first row as headers\nAMLP-00213 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00214.csv with first row as headers\nAMLP-00214 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00215.csv with first row as headers\nAMLP-00215 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00216.csv with first row as headers\nAMLP-00216 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00217.csv with first row as headers\nAMLP-00217 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00218.csv with first row as headers\nAMLP-00218 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00219.csv with first row as headers\nAMLP-00219 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00220.csv with first row as headers\nAMLP-00220 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00221.csv with first row as headers\nAMLP-00221 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00222.csv with first row as headers\nAMLP-00222 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00223.csv with first row as headers\nAMLP-00223 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00224.csv with first row as headers\nAMLP-00224 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00225.csv with first row as headers\nAMLP-00225 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00226.csv with first row as headers\nAMLP-00226 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00227.csv with first row as headers\nAMLP-00227 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00228.csv with first row as headers\nAMLP-00228 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00229.csv with first row as headers\nAMLP-00229 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00230.csv with first row as headers\nAMLP-00230 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00231.csv with first row as headers\nAMLP-00231 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00232.csv with first row as headers\nAMLP-00232 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00233.csv with first row as headers\nAMLP-00233 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00234.csv with first row as headers\nAMLP-00234 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00235.csv with first row as headers\nAMLP-00235 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00236.csv with first row as headers\nAMLP-00236 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00237.csv with first row as headers\nAMLP-00237 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00238.csv with first row as headers\nAMLP-00238 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00239.csv with first row as headers\nAMLP-00239 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00240.csv with first row as headers\nAMLP-00240 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00241.csv with first row as headers\nAMLP-00241 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00242.csv with first row as headers\nAMLP-00242 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00243.csv with first row as headers\nAMLP-00243 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00244.csv with first row as headers\nAMLP-00244 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00245.csv with first row as headers\nAMLP-00245 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00246.csv with first row as headers\nAMLP-00246 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00247.csv with first row as headers\nAMLP-00247 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00248.csv with first row as headers\nAMLP-00248 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00249.csv with first row as headers\nAMLP-00249 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00250.csv with first row as headers\nAMLP-00250 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00251.csv with first row as headers\nAMLP-00251 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00252.csv with first row as headers\nAMLP-00252 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00253.csv with first row as headers\nAMLP-00253 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00254.csv with first row as headers\nAMLP-00254 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00255.csv with first row as headers\nAMLP-00255 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00256.csv with first row as headers\nAMLP-00256 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00257.csv with first row as headers\nAMLP-00257 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00258.csv with first row as headers\nAMLP-00258 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00259.csv with first row as headers\nAMLP-00259 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00260.csv with first row as headers\nAMLP-00260 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00261.csv with first row as headers\nAMLP-00261 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00262.csv with first row as headers\nAMLP-00262 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00263.csv with first row as headers\nAMLP-00263 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00264.csv with first row as headers\nAMLP-00264 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00265.csv with first row as headers\nAMLP-00265 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00266.csv with first row as headers\nAMLP-00266 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00267.csv with first row as headers\nAMLP-00267 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00268.csv with first row as headers\nAMLP-00268 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00269.csv with first row as headers\n"
  144. },
  145. {
  146. "name": "stdout",
  147. "output_type": "stream",
  148. "text": "AMLP-00269 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00270.csv with first row as headers\nAMLP-00270 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00271.csv with first row as headers\nAMLP-00271 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00272.csv with first row as headers\nAMLP-00272 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00273.csv with first row as headers\nAMLP-00273 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00274.csv with first row as headers\nAMLP-00274 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00275.csv with first row as headers\nAMLP-00275 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00276.csv with first row as headers\nAMLP-00276 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00277.csv with first row as headers\nAMLP-00277 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00278.csv with first row as headers\nAMLP-00278 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00279.csv with first row as headers\nAMLP-00279 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00280.csv with first row as headers\nAMLP-00280 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00281.csv with first row as headers\nAMLP-00281 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00282.csv with first row as headers\nAMLP-00282 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00283.csv with first row as headers\nAMLP-00283 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00284.csv with first row as headers\nAMLP-00284 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00285.csv with first row as headers\nAMLP-00285 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00286.csv with first row as headers\nAMLP-00286 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00287.csv with first row as headers\nAMLP-00287 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00288.csv with first row as headers\nAMLP-00288 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00289.csv with first row as headers\nAMLP-00289 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00290.csv with first row as headers\nAMLP-00290 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00291.csv with first row as headers\nAMLP-00291 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00292.csv with first row as headers\nAMLP-00292 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00293.csv with first row as headers\nAMLP-00293 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00294.csv with first row as headers\nAMLP-00294 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00295.csv with first row as headers\nAMLP-00295 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00296.csv with first row as headers\nAMLP-00296 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00297.csv with first row as headers\nAMLP-00297 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00298.csv with first row as headers\nAMLP-00298 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00299.csv with first row as headers\nAMLP-00299 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00300.csv with first row as headers\nAMLP-00300 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00301.csv with first row as headers\nAMLP-00301 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00302.csv with first row as headers\nAMLP-00302 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00303.csv with first row as headers\nAMLP-00303 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00304.csv with first row as headers\nAMLP-00304 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00305.csv with first row as headers\nAMLP-00305 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00306.csv with first row as headers\nAMLP-00306 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00307.csv with first row as headers\nAMLP-00307 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00308.csv with first row as headers\nAMLP-00308 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00309.csv with first row as headers\nAMLP-00309 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00310.csv with first row as headers\nAMLP-00310 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00311.csv with first row as headers\nAMLP-00311 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00312.csv with first row as headers\nAMLP-00312 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00313.csv with first row as headers\nAMLP-00313 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00314.csv with first row as headers\nAMLP-00314 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00315.csv with first row as headers\nAMLP-00315 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00316.csv with first row as headers\nAMLP-00316 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00317.csv with first row as headers\nAMLP-00317 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00318.csv with first row as headers\nAMLP-00318 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00319.csv with first row as headers\nAMLP-00319 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00320.csv with first row as headers\nAMLP-00320 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00321.csv with first row as headers\nAMLP-00321 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00322.csv with first row as headers\nAMLP-00322 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00323.csv with first row as headers\nAMLP-00323 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00324.csv with first row as headers\nAMLP-00324 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00325.csv with first row as headers\nAMLP-00325 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00326.csv with first row as headers\nAMLP-00326 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00327.csv with first row as headers\nAMLP-00327 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00328.csv with first row as headers\nAMLP-00328 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00329.csv with first row as headers\nAMLP-00329 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00330.csv with first row as headers\nAMLP-00330 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00331.csv with first row as headers\nAMLP-00331 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00332.csv with first row as headers\nAMLP-00332 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00333.csv with first row as headers\nAMLP-00333 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00334.csv with first row as headers\nAMLP-00334 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00335.csv with first row as headers\nAMLP-00335 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00336.csv with first row as headers\n"
  149. },
  150. {
  151. "name": "stdout",
  152. "output_type": "stream",
  153. "text": "AMLP-00336 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00337.csv with first row as headers\nAMLP-00337 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00338.csv with first row as headers\nAMLP-00338 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00339.csv with first row as headers\nAMLP-00339 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00340.csv with first row as headers\nAMLP-00340 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00341.csv with first row as headers\nAMLP-00341 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00342.csv with first row as headers\nAMLP-00342 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00343.csv with first row as headers\nAMLP-00343 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00344.csv with first row as headers\nAMLP-00344 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00345.csv with first row as headers\nAMLP-00345 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00346.csv with first row as headers\nAMLP-00346 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00347.csv with first row as headers\nAMLP-00347 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00348.csv with first row as headers\nAMLP-00348 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00349.csv with first row as headers\nAMLP-00349 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00350.csv with first row as headers\nAMLP-00350 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00351.csv with first row as headers\nAMLP-00351 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00352.csv with first row as headers\nAMLP-00352 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00353.csv with first row as headers\nAMLP-00353 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00354.csv with first row as headers\nAMLP-00354 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00355.csv with first row as headers\nAMLP-00355 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00356.csv with first row as headers\nAMLP-00356 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00357.csv with first row as headers\nAMLP-00357 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00358.csv with first row as headers\nAMLP-00358 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00359.csv with first row as headers\nAMLP-00359 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00360.csv with first row as headers\nAMLP-00360 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00361.csv with first row as headers\nAMLP-00361 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00362.csv with first row as headers\nAMLP-00362 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00363.csv with first row as headers\nAMLP-00363 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00364.csv with first row as headers\nAMLP-00364 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00365.csv with first row as headers\nAMLP-00365 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00366.csv with first row as headers\nAMLP-00366 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00367.csv with first row as headers\nAMLP-00367 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00368.csv with first row as headers\nAMLP-00368 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00369.csv with first row as headers\nAMLP-00369 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00370.csv with first row as headers\nAMLP-00370 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00371.csv with first row as headers\nAMLP-00371 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00372.csv with first row as headers\nAMLP-00372 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00373.csv with first row as headers\nAMLP-00373 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00374.csv with first row as headers\nAMLP-00374 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00375.csv with first row as headers\nAMLP-00375 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00376.csv with first row as headers\nAMLP-00376 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00377.csv with first row as headers\nAMLP-00377 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00378.csv with first row as headers\nAMLP-00378 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00379.csv with first row as headers\nAMLP-00379 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00380.csv with first row as headers\nAMLP-00380 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00381.csv with first row as headers\nAMLP-00381 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00382.csv with first row as headers\nAMLP-00382 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00383.csv with first row as headers\nAMLP-00383 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00384.csv with first row as headers\nAMLP-00384 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00385.csv with first row as headers\nAMLP-00385 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00386.csv with first row as headers\nAMLP-00386 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00387.csv with first row as headers\nAMLP-00387 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00388.csv with first row as headers\nAMLP-00388 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00389.csv with first row as headers\nAMLP-00389 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00390.csv with first row as headers\nAMLP-00390 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00391.csv with first row as headers\nAMLP-00391 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00392.csv with first row as headers\nAMLP-00392 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00393.csv with first row as headers\nAMLP-00393 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00394.csv with first row as headers\nAMLP-00394 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00395.csv with first row as headers\nAMLP-00395 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00396.csv with first row as headers\nAMLP-00396 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00397.csv with first row as headers\nAMLP-00397 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00398.csv with first row as headers\nAMLP-00398 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00399.csv with first row as headers\nAMLP-00399 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00400.csv with first row as headers\nAMLP-00400 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00401.csv with first row as headers\nAMLP-00401 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00402.csv with first row as headers\nAMLP-00402 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00403.csv with first row as headers\nAMLP-00403 has been imported!\n"
  154. },
  155. {
  156. "name": "stdout",
  157. "output_type": "stream",
  158. "text": "Importing C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00404.csv with first row as headers\nAMLP-00404 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00405.csv with first row as headers\nAMLP-00405 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00406.csv with first row as headers\nAMLP-00406 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00407.csv with first row as headers\nAMLP-00407 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00408.csv with first row as headers\nAMLP-00408 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00409.csv with first row as headers\nAMLP-00409 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00410.csv with first row as headers\nAMLP-00410 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00411.csv with first row as headers\nAMLP-00411 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00412.csv with first row as headers\nAMLP-00412 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00413.csv with first row as headers\nAMLP-00413 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00414.csv with first row as headers\nAMLP-00414 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00415.csv with first row as headers\nAMLP-00415 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00416.csv with first row as headers\nAMLP-00416 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00417.csv with first row as headers\nAMLP-00417 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00418.csv with first row as headers\nAMLP-00418 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00419.csv with first row as headers\nAMLP-00419 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00420.csv with first row as headers\nAMLP-00420 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00421.csv with first row as headers\nAMLP-00421 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00422.csv with first row as headers\nAMLP-00422 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00423.csv with first row as headers\nAMLP-00423 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00424.csv with first row as headers\nAMLP-00424 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00425.csv with first row as headers\nAMLP-00425 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00426.csv with first row as headers\nAMLP-00426 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00427.csv with first row as headers\nAMLP-00427 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00428.csv with first row as headers\nAMLP-00428 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00429.csv with first row as headers\nAMLP-00429 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00430.csv with first row as headers\nAMLP-00430 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00431.csv with first row as headers\nAMLP-00431 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00432.csv with first row as headers\nAMLP-00432 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00433.csv with first row as headers\nAMLP-00433 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00434.csv with first row as headers\nAMLP-00434 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00435.csv with first row as headers\nAMLP-00435 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00436.csv with first row as headers\nAMLP-00436 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00437.csv with first row as headers\nAMLP-00437 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00438.csv with first row as headers\nAMLP-00438 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00439.csv with first row as headers\nAMLP-00439 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00440.csv with first row as headers\nAMLP-00440 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00441.csv with first row as headers\nAMLP-00441 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00442.csv with first row as headers\nAMLP-00442 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00443.csv with first row as headers\nAMLP-00443 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00444.csv with first row as headers\nAMLP-00444 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00445.csv with first row as headers\nAMLP-00445 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00446.csv with first row as headers\nAMLP-00446 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00447.csv with first row as headers\nAMLP-00447 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00448.csv with first row as headers\nAMLP-00448 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00449.csv with first row as headers\nAMLP-00449 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00450.csv with first row as headers\nAMLP-00450 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00451.csv with first row as headers\nAMLP-00451 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00452.csv with first row as headers\nAMLP-00452 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00453.csv with first row as headers\nAMLP-00453 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00454.csv with first row as headers\nAMLP-00454 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00455.csv with first row as headers\nAMLP-00455 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00456.csv with first row as headers\nAMLP-00456 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00457.csv with first row as headers\nAMLP-00457 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00458.csv with first row as headers\nAMLP-00458 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00459.csv with first row as headers\nAMLP-00459 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00460.csv with first row as headers\nAMLP-00460 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00461.csv with first row as headers\nAMLP-00461 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00462.csv with first row as headers\nAMLP-00462 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00463.csv with first row as headers\nAMLP-00463 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00464.csv with first row as headers\nAMLP-00464 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00465.csv with first row as headers\nAMLP-00465 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00466.csv with first row as headers\nAMLP-00466 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00467.csv with first row as headers\nAMLP-00467 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00468.csv with first row as headers\nAMLP-00468 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00469.csv with first row as headers\nAMLP-00469 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00470.csv with first row as headers\nAMLP-00470 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00471.csv with first row as headers\n"
  159. },
  160. {
  161. "name": "stdout",
  162. "output_type": "stream",
  163. "text": "AMLP-00471 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00472.csv with first row as headers\nAMLP-00472 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00473.csv with first row as headers\nAMLP-00473 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00474.csv with first row as headers\nAMLP-00474 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00475.csv with first row as headers\nAMLP-00475 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00476.csv with first row as headers\nAMLP-00476 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00477.csv with first row as headers\nAMLP-00477 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00478.csv with first row as headers\nAMLP-00478 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00479.csv with first row as headers\nAMLP-00479 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00480.csv with first row as headers\nAMLP-00480 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00481.csv with first row as headers\nAMLP-00481 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00482.csv with first row as headers\nAMLP-00482 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00483.csv with first row as headers\nAMLP-00483 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00484.csv with first row as headers\nAMLP-00484 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00485.csv with first row as headers\nAMLP-00485 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00486.csv with first row as headers\nAMLP-00486 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00487.csv with first row as headers\nAMLP-00487 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00488.csv with first row as headers\nAMLP-00488 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00489.csv with first row as headers\nAMLP-00489 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00490.csv with first row as headers\nAMLP-00490 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00491.csv with first row as headers\nAMLP-00491 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00492.csv with first row as headers\nAMLP-00492 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00493.csv with first row as headers\nAMLP-00493 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00494.csv with first row as headers\nAMLP-00494 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00495.csv with first row as headers\nAMLP-00495 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00496.csv with first row as headers\nAMLP-00496 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00497.csv with first row as headers\nAMLP-00497 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00498.csv with first row as headers\nAMLP-00498 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00499.csv with first row as headers\nAMLP-00499 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00500.csv with first row as headers\nAMLP-00500 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00501.csv with first row as headers\nAMLP-00501 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00502.csv with first row as headers\nAMLP-00502 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00503.csv with first row as headers\nAMLP-00503 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00504.csv with first row as headers\nAMLP-00504 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00505.csv with first row as headers\nAMLP-00505 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00506.csv with first row as headers\nAMLP-00506 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00507.csv with first row as headers\nAMLP-00507 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00508.csv with first row as headers\nAMLP-00508 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00509.csv with first row as headers\nAMLP-00509 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00510.csv with first row as headers\nAMLP-00510 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00511.csv with first row as headers\nAMLP-00511 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00512.csv with first row as headers\nAMLP-00512 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00513.csv with first row as headers\nAMLP-00513 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00514.csv with first row as headers\nAMLP-00514 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00515.csv with first row as headers\nAMLP-00515 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00516.csv with first row as headers\nAMLP-00516 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00517.csv with first row as headers\nAMLP-00517 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00518.csv with first row as headers\nAMLP-00518 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00519.csv with first row as headers\nAMLP-00519 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00520.csv with first row as headers\nAMLP-00520 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00521.csv with first row as headers\nAMLP-00521 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00522.csv with first row as headers\nAMLP-00522 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00523.csv with first row as headers\nAMLP-00523 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00524.csv with first row as headers\nAMLP-00524 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00525.csv with first row as headers\nAMLP-00525 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00526.csv with first row as headers\nAMLP-00526 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00527.csv with first row as headers\nAMLP-00527 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00528.csv with first row as headers\nAMLP-00528 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00529.csv with first row as headers\nAMLP-00529 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00530.csv with first row as headers\nAMLP-00530 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00531.csv with first row as headers\nAMLP-00531 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00532.csv with first row as headers\nAMLP-00532 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00533.csv with first row as headers\nAMLP-00533 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00534.csv with first row as headers\nAMLP-00534 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00535.csv with first row as headers\nAMLP-00535 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00536.csv with first row as headers\nAMLP-00536 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00537.csv with first row as headers\nAMLP-00537 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00538.csv with first row as headers\nAMLP-00538 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00539.csv with first row as headers\n"
  164. },
  165. {
  166. "name": "stdout",
  167. "output_type": "stream",
  168. "text": "AMLP-00539 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00540.csv with first row as headers\nAMLP-00540 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00541.csv with first row as headers\nAMLP-00541 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00542.csv with first row as headers\nAMLP-00542 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00543.csv with first row as headers\nAMLP-00543 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00544.csv with first row as headers\nAMLP-00544 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00545.csv with first row as headers\nAMLP-00545 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00546.csv with first row as headers\nAMLP-00546 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00547.csv with first row as headers\nAMLP-00547 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00548.csv with first row as headers\nAMLP-00548 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00549.csv with first row as headers\nAMLP-00549 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00550.csv with first row as headers\nAMLP-00550 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00551.csv with first row as headers\nAMLP-00551 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00552.csv with first row as headers\nAMLP-00552 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00553.csv with first row as headers\nAMLP-00553 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00554.csv with first row as headers\nAMLP-00554 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00555.csv with first row as headers\nAMLP-00555 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00556.csv with first row as headers\nAMLP-00556 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00557.csv with first row as headers\nAMLP-00557 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00558.csv with first row as headers\nAMLP-00558 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00559.csv with first row as headers\nAMLP-00559 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00560.csv with first row as headers\nAMLP-00560 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00561.csv with first row as headers\nAMLP-00561 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00562.csv with first row as headers\nAMLP-00562 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00563.csv with first row as headers\nAMLP-00563 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00564.csv with first row as headers\nAMLP-00564 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00565.csv with first row as headers\nAMLP-00565 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00566.csv with first row as headers\nAMLP-00566 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00567.csv with first row as headers\nAMLP-00567 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00568.csv with first row as headers\nAMLP-00568 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00569.csv with first row as headers\nAMLP-00569 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00570.csv with first row as headers\nAMLP-00570 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00571.csv with first row as headers\nAMLP-00571 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00572.csv with first row as headers\nAMLP-00572 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00573.csv with first row as headers\nAMLP-00573 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00574.csv with first row as headers\nAMLP-00574 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00575.csv with first row as headers\nAMLP-00575 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00576.csv with first row as headers\nAMLP-00576 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00577.csv with first row as headers\nAMLP-00577 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00578.csv with first row as headers\nAMLP-00578 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00579.csv with first row as headers\nAMLP-00579 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00580.csv with first row as headers\nAMLP-00580 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00581.csv with first row as headers\nAMLP-00581 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00582.csv with first row as headers\nAMLP-00582 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00583.csv with first row as headers\nAMLP-00583 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00584.csv with first row as headers\nAMLP-00584 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00585.csv with first row as headers\nAMLP-00585 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00586.csv with first row as headers\nAMLP-00586 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00587.csv with first row as headers\nAMLP-00587 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00588.csv with first row as headers\nAMLP-00588 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00589.csv with first row as headers\nAMLP-00589 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00590.csv with first row as headers\nAMLP-00590 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00591.csv with first row as headers\nAMLP-00591 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00592.csv with first row as headers\nAMLP-00592 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00593.csv with first row as headers\nAMLP-00593 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00594.csv with first row as headers\nAMLP-00594 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00595.csv with first row as headers\nAMLP-00595 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00596.csv with first row as headers\nAMLP-00596 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00597.csv with first row as headers\nAMLP-00597 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00598.csv with first row as headers\nAMLP-00598 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00599.csv with first row as headers\nAMLP-00599 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00600.csv with first row as headers\nAMLP-00600 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00601.csv with first row as headers\nAMLP-00601 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00602.csv with first row as headers\nAMLP-00602 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00603.csv with first row as headers\nAMLP-00603 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00604.csv with first row as headers\nAMLP-00604 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00605.csv with first row as headers\nAMLP-00605 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00606.csv with first row as headers\n"
  169. },
  170. {
  171. "name": "stdout",
  172. "output_type": "stream",
  173. "text": "AMLP-00606 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00607.csv with first row as headers\nAMLP-00607 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00608.csv with first row as headers\nAMLP-00608 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00609.csv with first row as headers\nAMLP-00609 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00610.csv with first row as headers\nAMLP-00610 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00611.csv with first row as headers\nAMLP-00611 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00612.csv with first row as headers\nAMLP-00612 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00613.csv with first row as headers\nAMLP-00613 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00614.csv with first row as headers\nAMLP-00614 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00615.csv with first row as headers\nAMLP-00615 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00616.csv with first row as headers\nAMLP-00616 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00617.csv with first row as headers\nAMLP-00617 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00618.csv with first row as headers\nAMLP-00618 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00619.csv with first row as headers\nAMLP-00619 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00620.csv with first row as headers\nAMLP-00620 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00621.csv with first row as headers\nAMLP-00621 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00622.csv with first row as headers\nAMLP-00622 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00623.csv with first row as headers\nAMLP-00623 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00624.csv with first row as headers\nAMLP-00624 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00625.csv with first row as headers\nAMLP-00625 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00626.csv with first row as headers\nAMLP-00626 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00627.csv with first row as headers\nAMLP-00627 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00628.csv with first row as headers\nAMLP-00628 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00629.csv with first row as headers\nAMLP-00629 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00630.csv with first row as headers\nAMLP-00630 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00631.csv with first row as headers\nAMLP-00631 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00632.csv with first row as headers\nAMLP-00632 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00633.csv with first row as headers\nAMLP-00633 has been imported!\nImporting C:\\Algos\\Backtest\\DM_AMLP_M60_634_TP2_SL2\\AMLP-00634.csv with first row as headers\nAMLP-00634 has been imported!\n"
  174. }
  175. ]
  176. },
  177. {
  178. "metadata": {},
  179. "cell_type": "markdown",
  180. "source": "# Filtering Based on Thresholds and Ranking Methodology Below IN DLPAL Period\nWhen you do ranking, make sure you have already filtered out the ones with too low IS and OOS1 Nonflat\nThe ranking formula: \n\nLet $a =$ IS NonflatPCT,$\\quad$ $b =$ OOS1 NonflatPCT,$\\quad\\quad$ $n=a+b$\n$$Score = 100 \\left[ \\frac{a(\\text{SharpeIS}) + b(\\text{SharpeOOS1})}{n} + \\text{SharpeDLPAL}\\left( 1-{\\frac{|\\text{ SharpeIS}-\\text{SharpeOOS1 }|}{2}} \\right)\\right] $$\nHigher weights on higher nonflat, deviation small doesn't mean higher rank all the time, relative to the\n\"goodness\" of Sharpe\n\nChoose Top 50: top = 50\n\nDoes not take care of things when the difference of Sharpes is more than 2. It will only affect the case when for e.g. Sharpe IS = 2, Sharpe OOS1 = 4, Score will be 0, or even larger difference will give negative score."
  181. },
  182. {
  183. "metadata": {
  184. "trusted": true
  185. },
  186. "cell_type": "code",
  187. "source": "# Run\n\n##Following codes are the conversion of datetime string to datetime object for the use below\nninja_start_date = df_list[0].iloc[0,0].to_pydatetime()\nninja_end_date = df_list[0].iloc[len(df_list[0])-1,0].to_pydatetime()\nstart_date = datetime.datetime.strptime(start_date,'%Y%m%d')\nend_date = datetime.datetime.strptime(end_date,'%Y%m%d')\nOOS_date = datetime.datetime.strptime(OOS_date,'%Y%m%d')\n\nprint(\"\\nNinja Start Date :\",ninja_start_date.date())\nprint(\"Ninja End Date: \",ninja_end_date.date())\nprint(\"DLPAL Start Date: \", start_date.date())\nprint(\"DLPAL End Date: \" , end_date.date())\nprint(\"DLPAL OOS Date: \", OOS_date.date())\n\n#======================================= If you get TypeError ===================================================\n# You can only compile this once, because after compiling, your current start_date, end_date, OOS_date becomes \n# a datetime object, and hence cannot be converted to datetime object and you will get the following error\n# TypeError: strptime() argument 1 must be str, not datetime.datetime\n# Just ignore it if the dates are stored correctly. If not, go back to the top, under the section:\n# \"Copy and paste the input file name (without '.txt')\"\n# Compile once, and come back here to compile again, it will be refreshed and get the right dates\n#================================================================================================================",
  188. "execution_count": 9,
  189. "outputs": [
  190. {
  191. "name": "stdout",
  192. "output_type": "stream",
  193. "text": "\nNinja Start Date : 2010-08-26\nNinja End Date: 2018-02-28\nDLPAL Start Date: 2012-01-03\nDLPAL End Date: 2016-12-12\nDLPAL OOS Date: 2015-09-30\n"
  194. }
  195. ]
  196. },
  197. {
  198. "metadata": {
  199. "trusted": true
  200. },
  201. "cell_type": "code",
  202. "source": "fdf=SharpeMatrix(df_list, long_short_list, ninja_start_date, ninja_end_date, start_date, OOS_date,end_date)\n\n# Run [This cell runs the calculation of a huge Sharpe matrices]\n\n\n# Uncomment the following lines of codes if you want to see the complete story without filtering in DLPAL period\n# You may change the sorting method. This df gives you the sharpe for IS and OOS period in DLPAL\n# Sharpe DLPAL is the sharpe for the combined IS and OOS in DLPAL\n# Hence, you shouldn't cheat by looking at the complete sharpe matrix fdf first.\n# Use this to decide the rules to choose and analyze on fdf\n\n# with pd.option_context('display.max_rows', None, 'display.max_columns', None):\n# display(fdf[['Name','Direction','Sharpe DLPAL','SharpeIS','SharpeOOS1','IS NonflatPCT','OOS1 NonflatPCT','IS Nonflat', 'OOS1 Nonflat']].sort_values(by='SharpeOOS1',ascending = False).style.apply(highlight_max, subset=['Sharpe DLPAL','SharpeIS','SharpeOOS1']))",
  203. "execution_count": 10,
  204. "outputs": [
  205. {
  206. "name": "stdout",
  207. "output_type": "stream",
  208. "text": "Total Trading Days: 1890 \n | IS Trading Days: 941 | OOS1 Trading Days: 303 | OOS2 Trading Days: 341 | OOS3 Trading Days: 305\nTime to calculate the Sharpe DataFrame: 15.189059257507324\n"
  209. }
  210. ]
  211. },
  212. {
  213. "metadata": {
  214. "trusted": true
  215. },
  216. "cell_type": "code",
  217. "source": "# Edit\n#======================================= Fixed Threshold Filtering, edit below ===================================\n\nIS_sharpe_threshold = 0.2\nOOS_sharpe_threshold = 0.2\noverall_sharpe_threshold = 0.2\nIS_nonflatPCT_threshold = 1\nOOS1_nonflatPCT_threshold = 1\ntop = 10\n\n#======================================= No Need to Edit [Unless you want to sort differently======================\nfiltered = fdf[(fdf['Sharpe']>overall_sharpe_threshold) & \n (fdf['SharpeIS']>IS_sharpe_threshold) & \n (fdf['SharpeOOS1']>OOS_sharpe_threshold) & \n (fdf['IS NonflatPCT']>IS_nonflatPCT_threshold) &\n (fdf['OOS1 NonflatPCT']>OOS1_nonflatPCT_threshold)\n ].sort_values(by='SharpeOOS1',ascending=False)\n\nranking_df = Rank(filtered)\ntop_ranking = ranking_df.head(top)\n\nprint(\"The Top Ranked Rules without separation of Longs and Shorts in DLPAL Period\")\nwith pd.option_context('display.max_rows', None, 'display.max_columns', None):\n if len(ranking_df)!=0:\n display(top_ranking.reindex(columns=['Name','Direction','Sharpe DLPAL','SharpeIS','SharpeOOS1','IS Nonflat',\n 'OOS1 Nonflat','IS NonflatPCT','OOS1 NonflatPCT','Score','Rank'])\n .style.apply(highlight_max, subset=['Sharpe DLPAL','SharpeIS','SharpeOOS1','IS Nonflat',\n 'OOS1 Nonflat','IS NonflatPCT','OOS1 NonflatPCT','Score']))\n else:\n print(\"No Rule satisfies the given threshold, please loosen your threshold\")\n#================================================================================================================\nlist_IS = [x for x in top_ranking.index]",
  218. "execution_count": 98,
  219. "outputs": [
  220. {
  221. "name": "stdout",
  222. "output_type": "stream",
  223. "text": "The Top Ranked Rules without separation of Longs and Shorts in DLPAL Period\n"
  224. },
  225. {
  226. "data": {
  227. "text/html": "<style type=\"text/css\" >\n #T_f95b6842_2697_11e8_b574_002683143c82row0_col9 {\n background-color: lightgreen;\n } #T_f95b6842_2697_11e8_b574_002683143c82row2_col2 {\n background-color: lightgreen;\n } #T_f95b6842_2697_11e8_b574_002683143c82row2_col4 {\n background-color: lightgreen;\n } #T_f95b6842_2697_11e8_b574_002683143c82row3_col3 {\n background-color: lightgreen;\n } #T_f95b6842_2697_11e8_b574_002683143c82row6_col5 {\n background-color: lightgreen;\n } #T_f95b6842_2697_11e8_b574_002683143c82row6_col6 {\n background-color: lightgreen;\n } #T_f95b6842_2697_11e8_b574_002683143c82row6_col7 {\n background-color: lightgreen;\n } #T_f95b6842_2697_11e8_b574_002683143c82row6_col8 {\n background-color: lightgreen;\n }</style> \n<table id=\"T_f95b6842_2697_11e8_b574_002683143c82\" > \n<thead> <tr> \n <th class=\"blank level0\" ></th> \n <th class=\"col_heading level0 col0\" >Name</th> \n <th class=\"col_heading level0 col1\" >Direction</th> \n <th class=\"col_heading level0 col2\" >Sharpe DLPAL</th> \n <th class=\"col_heading level0 col3\" >SharpeIS</th> \n <th class=\"col_heading level0 col4\" >SharpeOOS1</th> \n <th class=\"col_heading level0 col5\" >IS Nonflat</th> \n <th class=\"col_heading level0 col6\" >OOS1 Nonflat</th> \n <th class=\"col_heading level0 col7\" >IS NonflatPCT</th> \n <th class=\"col_heading level0 col8\" >OOS1 NonflatPCT</th> \n <th class=\"col_heading level0 col9\" >Score</th> \n <th class=\"col_heading level0 col10\" >Rank</th> \n </tr></thead> \n<tbody> <tr> \n <th id=\"T_f95b6842_2697_11e8_b574_002683143c82level0_row0\" class=\"row_heading level0 row0\" >308</th> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row0_col0\" class=\"data row0 col0\" >AMLP-00308</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row0_col1\" class=\"data row0 col1\" >Short</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row0_col2\" class=\"data row0 col2\" >1.35871</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row0_col3\" class=\"data row0 col3\" >1.46855</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row0_col4\" class=\"data row0 col4\" >1.39443</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row0_col5\" class=\"data row0 col5\" >402</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row0_col6\" class=\"data row0 col6\" >82</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row0_col7\" class=\"data row0 col7\" >42.7205</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row0_col8\" class=\"data row0 col8\" >27.0627</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row0_col9\" class=\"data row0 col9\" >274.816</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row0_col10\" class=\"data row0 col10\" >1</td> \n </tr> <tr> \n <th id=\"T_f95b6842_2697_11e8_b574_002683143c82level0_row1\" class=\"row_heading level0 row1\" >225</th> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row1_col0\" class=\"data row1 col0\" >AMLP-00225</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row1_col1\" class=\"data row1 col1\" >Short</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row1_col2\" class=\"data row1 col2\" >1.56957</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row1_col3\" class=\"data row1 col3\" >1.41899</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row1_col4\" class=\"data row1 col4\" >1.99355</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row1_col5\" class=\"data row1 col5\" >240</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row1_col6\" class=\"data row1 col6\" >31</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row1_col7\" class=\"data row1 col7\" >25.5048</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row1_col8\" class=\"data row1 col8\" >10.231</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row1_col9\" class=\"data row1 col9\" >270.215</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row1_col10\" class=\"data row1 col10\" >2</td> \n </tr> <tr> \n <th id=\"T_f95b6842_2697_11e8_b574_002683143c82level0_row2\" class=\"row_heading level0 row2\" >400</th> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row2_col0\" class=\"data row2 col0\" >AMLP-00400</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row2_col1\" class=\"data row2 col1\" >Short</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row2_col2\" class=\"data row2 col2\" >1.57834</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row2_col3\" class=\"data row2 col3\" >1.36003</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row2_col4\" class=\"data row2 col4\" >2.24782</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row2_col5\" class=\"data row2 col5\" >565</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row2_col6\" class=\"data row2 col6\" >144</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row2_col7\" class=\"data row2 col7\" >60.0425</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row2_col8\" class=\"data row2 col8\" >47.5248</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row2_col9\" class=\"data row2 col9\" >262.999</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row2_col10\" class=\"data row2 col10\" >3</td> \n </tr> <tr> \n <th id=\"T_f95b6842_2697_11e8_b574_002683143c82level0_row3\" class=\"row_heading level0 row3\" >309</th> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row3_col0\" class=\"data row3 col0\" >AMLP-00309</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row3_col1\" class=\"data row3 col1\" >Short</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row3_col2\" class=\"data row3 col2\" >1.42406</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row3_col3\" class=\"data row3 col3\" >1.6667</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row3_col4\" class=\"data row3 col4\" >1.21351</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row3_col5\" class=\"data row3 col5\" >408</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row3_col6\" class=\"data row3 col6\" >109</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row3_col7\" class=\"data row3 col7\" >43.3581</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row3_col8\" class=\"data row3 col8\" >35.9736</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row3_col9\" class=\"data row3 col9\" >256.258</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row3_col10\" class=\"data row3 col10\" >4</td> \n </tr> <tr> \n <th id=\"T_f95b6842_2697_11e8_b574_002683143c82level0_row4\" class=\"row_heading level0 row4\" >593</th> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row4_col0\" class=\"data row4 col0\" >AMLP-00593</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row4_col1\" class=\"data row4 col1\" >Short</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row4_col2\" class=\"data row4 col2\" >1.28768</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row4_col3\" class=\"data row4 col3\" >1.21113</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row4_col4\" class=\"data row4 col4\" >1.69598</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row4_col5\" class=\"data row4 col5\" >92</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row4_col6\" class=\"data row4 col6\" >20</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row4_col7\" class=\"data row4 col7\" >9.77683</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row4_col8\" class=\"data row4 col8\" >6.60066</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row4_col9\" class=\"data row4 col9\" >238.206</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row4_col10\" class=\"data row4 col10\" >5</td> \n </tr> <tr> \n <th id=\"T_f95b6842_2697_11e8_b574_002683143c82level0_row5\" class=\"row_heading level0 row5\" >572</th> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row5_col0\" class=\"data row5 col0\" >AMLP-00572</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row5_col1\" class=\"data row5 col1\" >Short</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row5_col2\" class=\"data row5 col2\" >1.21831</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row5_col3\" class=\"data row5 col3\" >1.19308</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row5_col4\" class=\"data row5 col4\" >1.34484</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row5_col5\" class=\"data row5 col5\" >326</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row5_col6\" class=\"data row5 col6\" >49</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row5_col7\" class=\"data row5 col7\" >34.644</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row5_col8\" class=\"data row5 col8\" >16.1716</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row5_col9\" class=\"data row5 col9\" >236.724</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row5_col10\" class=\"data row5 col10\" >6</td> \n </tr> <tr> \n <th id=\"T_f95b6842_2697_11e8_b574_002683143c82level0_row6\" class=\"row_heading level0 row6\" >219</th> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row6_col0\" class=\"data row6 col0\" >AMLP-00219</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row6_col1\" class=\"data row6 col1\" >Short</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row6_col2\" class=\"data row6 col2\" >1.14611</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row6_col3\" class=\"data row6 col3\" >1.17921</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row6_col4\" class=\"data row6 col4\" >1.24937</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row6_col5\" class=\"data row6 col5\" >656</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row6_col6\" class=\"data row6 col6\" >158</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row6_col7\" class=\"data row6 col7\" >69.7131</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row6_col8\" class=\"data row6 col8\" >52.1452</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row6_col9\" class=\"data row6 col9\" >231.514</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row6_col10\" class=\"data row6 col10\" >7</td> \n </tr> <tr> \n <th id=\"T_f95b6842_2697_11e8_b574_002683143c82level0_row7\" class=\"row_heading level0 row7\" >217</th> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row7_col0\" class=\"data row7 col0\" >AMLP-00217</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row7_col1\" class=\"data row7 col1\" >Short</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row7_col2\" class=\"data row7 col2\" >1.26689</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row7_col3\" class=\"data row7 col3\" >1.41057</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row7_col4\" class=\"data row7 col4\" >0.986359</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row7_col5\" class=\"data row7 col5\" >268</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row7_col6\" class=\"data row7 col6\" >43</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row7_col7\" class=\"data row7 col7\" >28.4803</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row7_col8\" class=\"data row7 col8\" >14.1914</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row7_col9\" class=\"data row7 col9\" >226.766</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row7_col10\" class=\"data row7 col10\" >8</td> \n </tr> <tr> \n <th id=\"T_f95b6842_2697_11e8_b574_002683143c82level0_row8\" class=\"row_heading level0 row8\" >239</th> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row8_col0\" class=\"data row8 col0\" >AMLP-00239</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row8_col1\" class=\"data row8 col1\" >Short</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row8_col2\" class=\"data row8 col2\" >1.18526</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row8_col3\" class=\"data row8 col3\" >1.35224</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row8_col4\" class=\"data row8 col4\" >1.05443</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row8_col5\" class=\"data row8 col5\" >433</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row8_col6\" class=\"data row8 col6\" >130</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row8_col7\" class=\"data row8 col7\" >46.0149</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row8_col8\" class=\"data row8 col8\" >42.9043</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row8_col9\" class=\"data row8 col9\" >221.731</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row8_col10\" class=\"data row8 col10\" >9</td> \n </tr> <tr> \n <th id=\"T_f95b6842_2697_11e8_b574_002683143c82level0_row9\" class=\"row_heading level0 row9\" >315</th> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row9_col0\" class=\"data row9 col0\" >AMLP-00315</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row9_col1\" class=\"data row9 col1\" >Short</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row9_col2\" class=\"data row9 col2\" >1.20312</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row9_col3\" class=\"data row9 col3\" >1.08614</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row9_col4\" class=\"data row9 col4\" >1.60983</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row9_col5\" class=\"data row9 col5\" >544</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row9_col6\" class=\"data row9 col6\" >148</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row9_col7\" class=\"data row9 col7\" >57.8108</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row9_col8\" class=\"data row9 col8\" >48.8449</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row9_col9\" class=\"data row9 col9\" >221.406</td> \n <td id=\"T_f95b6842_2697_11e8_b574_002683143c82row9_col10\" class=\"data row9 col10\" >10</td> \n </tr></tbody> \n</table> ",
  228. "text/plain": "<pandas.io.formats.style.Styler at 0x288d33a3518>"
  229. },
  230. "metadata": {},
  231. "output_type": "display_data"
  232. }
  233. ]
  234. },
  235. {
  236. "metadata": {},
  237. "cell_type": "markdown",
  238. "source": "# Separating Long and Short Rules and Rank Them in DLPAL Period"
  239. },
  240. {
  241. "metadata": {
  242. "trusted": true
  243. },
  244. "cell_type": "code",
  245. "source": "# Edit\ntop_long = 10\ntop_short = 20\n\n#================================================================================================================\nlong_rules = filtered.loc[filtered['Direction']=='Long']\nshort_rules = filtered.loc[filtered['Direction']=='Short']\nprint('[After applying crude Sharpe filter] The Ranking of Long and Short separately')\nrank_long_dlpal_period = Rank(long_rules).head(top_long)\nrank_short_dlpal_period = Rank(short_rules).head(top_short)\n\nwith pd.option_context('display.max_rows', None, 'display.max_columns', None):\n if len(rank_long_dlpal_period)!=0:\n display(rank_long_dlpal_period[['Name','Direction','Sharpe DLPAL','SharpeIS','SharpeOOS1','IS Nonflat', \n 'OOS1 Nonflat','IS NonflatPCT','OOS1 NonflatPCT','Score','Rank']]\n .style.apply(highlight_max, subset=['Sharpe DLPAL','SharpeIS','SharpeOOS1','IS Nonflat',\n 'OOS1 Nonflat','IS NonflatPCT','OOS1 NonflatPCT','Score']))\n else:\n print(\"No Long Rules\")\n if len(rank_short_dlpal_period)!=0:\n display(rank_short_dlpal_period[['Name','Direction','Sharpe DLPAL','SharpeIS','SharpeOOS1','IS Nonflat', \n 'OOS1 Nonflat','IS NonflatPCT','OOS1 NonflatPCT','Score','Rank']]\n .style.apply(highlight_max, subset=['Sharpe DLPAL','SharpeIS','SharpeOOS1','IS Nonflat',\n 'OOS1 Nonflat','IS NonflatPCT','OOS1 NonflatPCT','Score']))\n else:\n print(\"No Long Rules\")\n\nlong_indices_dlpal_period = [x for x in rank_long_dlpal_period.index]\nshort_indices_dlpal_period = [x for x in rank_short_dlpal_period.index]\n\nprint(\"Long Indices: \", long_indices_dlpal_period)\nprint(\"Short Indices: \", short_indices_dlpal_period)",
  246. "execution_count": 102,
  247. "outputs": [
  248. {
  249. "name": "stdout",
  250. "output_type": "stream",
  251. "text": "[After applying crude Sharpe filter] The Ranking of Long and Short separately\n"
  252. },
  253. {
  254. "data": {
  255. "text/html": "<style type=\"text/css\" >\n #T_6f453d38_2698_11e8_93c6_002683143c82row0_col2 {\n background-color: lightgreen;\n } #T_6f453d38_2698_11e8_93c6_002683143c82row0_col3 {\n background-color: lightgreen;\n } #T_6f453d38_2698_11e8_93c6_002683143c82row0_col9 {\n background-color: lightgreen;\n } #T_6f453d38_2698_11e8_93c6_002683143c82row2_col4 {\n background-color: lightgreen;\n } #T_6f453d38_2698_11e8_93c6_002683143c82row5_col5 {\n background-color: lightgreen;\n } #T_6f453d38_2698_11e8_93c6_002683143c82row5_col7 {\n background-color: lightgreen;\n } #T_6f453d38_2698_11e8_93c6_002683143c82row8_col5 {\n background-color: lightgreen;\n } #T_6f453d38_2698_11e8_93c6_002683143c82row8_col6 {\n background-color: lightgreen;\n } #T_6f453d38_2698_11e8_93c6_002683143c82row8_col7 {\n background-color: lightgreen;\n } #T_6f453d38_2698_11e8_93c6_002683143c82row8_col8 {\n background-color: lightgreen;\n }</style> \n<table id=\"T_6f453d38_2698_11e8_93c6_002683143c82\" > \n<thead> <tr> \n <th class=\"blank level0\" ></th> \n <th class=\"col_heading level0 col0\" >Name</th> \n <th class=\"col_heading level0 col1\" >Direction</th> \n <th class=\"col_heading level0 col2\" >Sharpe DLPAL</th> \n <th class=\"col_heading level0 col3\" >SharpeIS</th> \n <th class=\"col_heading level0 col4\" >SharpeOOS1</th> \n <th class=\"col_heading level0 col5\" >IS Nonflat</th> \n <th class=\"col_heading level0 col6\" >OOS1 Nonflat</th> \n <th class=\"col_heading level0 col7\" >IS NonflatPCT</th> \n <th class=\"col_heading level0 col8\" >OOS1 NonflatPCT</th> \n <th class=\"col_heading level0 col9\" >Score</th> \n <th class=\"col_heading level0 col10\" >Rank</th> \n </tr></thead> \n<tbody> <tr> \n <th id=\"T_6f453d38_2698_11e8_93c6_002683143c82level0_row0\" class=\"row_heading level0 row0\" >167</th> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row0_col0\" class=\"data row0 col0\" >AMLP-00167</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row0_col1\" class=\"data row0 col1\" >Long</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row0_col2\" class=\"data row0 col2\" >1.06059</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row0_col3\" class=\"data row0 col3\" >1.74023</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row0_col4\" class=\"data row0 col4\" >0.211354</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row0_col5\" class=\"data row0 col5\" >123</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row0_col6\" class=\"data row0 col6\" >9</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row0_col7\" class=\"data row0 col7\" >13.0712</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row0_col8\" class=\"data row0 col8\" >2.9703</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row0_col9\" class=\"data row0 col9\" >170.697</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row0_col10\" class=\"data row0 col10\" >1</td> \n </tr> <tr> \n <th id=\"T_6f453d38_2698_11e8_93c6_002683143c82level0_row1\" class=\"row_heading level0 row1\" >116</th> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row1_col0\" class=\"data row1 col0\" >AMLP-00116</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row1_col1\" class=\"data row1 col1\" >Long</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row1_col2\" class=\"data row1 col2\" >0.960279</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row1_col3\" class=\"data row1 col3\" >1.22829</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row1_col4\" class=\"data row1 col4\" >0.544062</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row1_col5\" class=\"data row1 col5\" >105</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row1_col6\" class=\"data row1 col6\" >14</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row1_col7\" class=\"data row1 col7\" >11.1583</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row1_col8\" class=\"data row1 col8\" >4.62046</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row1_col9\" class=\"data row1 col9\" >165.968</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row1_col10\" class=\"data row1 col10\" >2</td> \n </tr> <tr> \n <th id=\"T_6f453d38_2698_11e8_93c6_002683143c82level0_row2\" class=\"row_heading level0 row2\" >136</th> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row2_col0\" class=\"data row2 col0\" >AMLP-00136</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row2_col1\" class=\"data row2 col1\" >Long</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row2_col2\" class=\"data row2 col2\" >0.835845</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row2_col3\" class=\"data row2 col3\" >0.426769</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row2_col4\" class=\"data row2 col4\" >1.78973</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row2_col5\" class=\"data row2 col5\" >128</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row2_col6\" class=\"data row2 col6\" >39</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row2_col7\" class=\"data row2 col7\" >13.6026</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row2_col8\" class=\"data row2 col8\" >12.8713</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row2_col9\" class=\"data row2 col9\" >135.566</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row2_col10\" class=\"data row2 col10\" >3</td> \n </tr> <tr> \n <th id=\"T_6f453d38_2698_11e8_93c6_002683143c82level0_row3\" class=\"row_heading level0 row3\" >102</th> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row3_col0\" class=\"data row3 col0\" >AMLP-00102</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row3_col1\" class=\"data row3 col1\" >Long</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row3_col2\" class=\"data row3 col2\" >0.89269</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row3_col3\" class=\"data row3 col3\" >0.549812</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row3_col4\" class=\"data row3 col4\" >1.65078</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row3_col5\" class=\"data row3 col5\" >190</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row3_col6\" class=\"data row3 col6\" >29</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row3_col7\" class=\"data row3 col7\" >20.1913</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row3_col8\" class=\"data row3 col8\" >9.57096</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row3_col9\" class=\"data row3 col9\" >130.514</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row3_col10\" class=\"data row3 col10\" >4</td> \n </tr> <tr> \n <th id=\"T_6f453d38_2698_11e8_93c6_002683143c82level0_row4\" class=\"row_heading level0 row4\" >117</th> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row4_col0\" class=\"data row4 col0\" >AMLP-00117</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row4_col1\" class=\"data row4 col1\" >Long</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row4_col2\" class=\"data row4 col2\" >0.66066</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row4_col3\" class=\"data row4 col3\" >0.917875</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row4_col4\" class=\"data row4 col4\" >0.303365</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row4_col5\" class=\"data row4 col5\" >169</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row4_col6\" class=\"data row4 col6\" >21</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row4_col7\" class=\"data row4 col7\" >17.9596</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row4_col8\" class=\"data row4 col8\" >6.93069</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row4_col9\" class=\"data row4 col9\" >120.443</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row4_col10\" class=\"data row4 col10\" >5</td> \n </tr> <tr> \n <th id=\"T_6f453d38_2698_11e8_93c6_002683143c82level0_row5\" class=\"row_heading level0 row5\" >181</th> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row5_col0\" class=\"data row5 col0\" >AMLP-00181</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row5_col1\" class=\"data row5 col1\" >Long</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row5_col2\" class=\"data row5 col2\" >0.635567</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row5_col3\" class=\"data row5 col3\" >0.523548</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row5_col4\" class=\"data row5 col4\" >0.94728</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row5_col5\" class=\"data row5 col5\" >218</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row5_col6\" class=\"data row5 col6\" >18</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row5_col7\" class=\"data row5 col7\" >23.1668</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row5_col8\" class=\"data row5 col8\" >5.94059</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row5_col9\" class=\"data row5 col9\" >111.094</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row5_col10\" class=\"data row5 col10\" >6</td> \n </tr> <tr> \n <th id=\"T_6f453d38_2698_11e8_93c6_002683143c82level0_row6\" class=\"row_heading level0 row6\" >176</th> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row6_col0\" class=\"data row6 col0\" >AMLP-00176</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row6_col1\" class=\"data row6 col1\" >Long</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row6_col2\" class=\"data row6 col2\" >0.482804</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row6_col3\" class=\"data row6 col3\" >0.535422</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row6_col4\" class=\"data row6 col4\" >0.633621</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row6_col5\" class=\"data row6 col5\" >73</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row6_col6\" class=\"data row6 col6\" >38</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row6_col7\" class=\"data row6 col7\" >7.7577</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row6_col8\" class=\"data row6 col8\" >12.5413</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row6_col9\" class=\"data row6 col9\" >105.519</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row6_col10\" class=\"data row6 col10\" >7</td> \n </tr> <tr> \n <th id=\"T_6f453d38_2698_11e8_93c6_002683143c82level0_row7\" class=\"row_heading level0 row7\" >68</th> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row7_col0\" class=\"data row7 col0\" >AMLP-00068</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row7_col1\" class=\"data row7 col1\" >Long</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row7_col2\" class=\"data row7 col2\" >0.612095</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row7_col3\" class=\"data row7 col3\" >0.768052</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row7_col4\" class=\"data row7 col4\" >0.201999</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row7_col5\" class=\"data row7 col5\" >134</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row7_col6\" class=\"data row7 col6\" >24</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row7_col7\" class=\"data row7 col7\" >14.2402</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row7_col8\" class=\"data row7 col8\" >7.92079</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row7_col9\" class=\"data row7 col9\" >100.459</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row7_col10\" class=\"data row7 col10\" >8</td> \n </tr> <tr> \n <th id=\"T_6f453d38_2698_11e8_93c6_002683143c82level0_row8\" class=\"row_heading level0 row8\" >7</th> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row8_col0\" class=\"data row8 col0\" >AMLP-00007</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row8_col1\" class=\"data row8 col1\" >Long</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row8_col2\" class=\"data row8 col2\" >0.554116</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row8_col3\" class=\"data row8 col3\" >0.326679</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row8_col4\" class=\"data row8 col4\" >1.002</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row8_col5\" class=\"data row8 col5\" >218</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row8_col6\" class=\"data row8 col6\" >57</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row8_col7\" class=\"data row8 col7\" >23.1668</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row8_col8\" class=\"data row8 col8\" >18.8119</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row8_col9\" class=\"data row8 col9\" >99.6322</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row8_col10\" class=\"data row8 col10\" >9</td> \n </tr> <tr> \n <th id=\"T_6f453d38_2698_11e8_93c6_002683143c82level0_row9\" class=\"row_heading level0 row9\" >180</th> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row9_col0\" class=\"data row9 col0\" >AMLP-00180</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row9_col1\" class=\"data row9 col1\" >Long</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row9_col2\" class=\"data row9 col2\" >0.507569</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row9_col3\" class=\"data row9 col3\" >0.41752</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row9_col4\" class=\"data row9 col4\" >0.749201</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row9_col5\" class=\"data row9 col5\" >132</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row9_col6\" class=\"data row9 col6\" >36</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row9_col7\" class=\"data row9 col7\" >14.0276</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row9_col8\" class=\"data row9 col8\" >11.8812</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row9_col9\" class=\"data row9 col9\" >99.3015</td> \n <td id=\"T_6f453d38_2698_11e8_93c6_002683143c82row9_col10\" class=\"data row9 col10\" >10</td> \n </tr></tbody> \n</table> ",
  256. "text/plain": "<pandas.io.formats.style.Styler at 0x288d16f1518>"
  257. },
  258. "metadata": {},
  259. "output_type": "display_data"
  260. },
  261. {
  262. "data": {
  263. "text/html": "<style type=\"text/css\" >\n #T_6f5b9d58_2698_11e8_bb7f_002683143c82row0_col9 {\n background-color: lightgreen;\n } #T_6f5b9d58_2698_11e8_bb7f_002683143c82row2_col2 {\n background-color: lightgreen;\n } #T_6f5b9d58_2698_11e8_bb7f_002683143c82row2_col4 {\n background-color: lightgreen;\n } #T_6f5b9d58_2698_11e8_bb7f_002683143c82row3_col3 {\n background-color: lightgreen;\n } #T_6f5b9d58_2698_11e8_bb7f_002683143c82row6_col5 {\n background-color: lightgreen;\n } #T_6f5b9d58_2698_11e8_bb7f_002683143c82row6_col6 {\n background-color: lightgreen;\n } #T_6f5b9d58_2698_11e8_bb7f_002683143c82row6_col7 {\n background-color: lightgreen;\n } #T_6f5b9d58_2698_11e8_bb7f_002683143c82row6_col8 {\n background-color: lightgreen;\n }</style> \n<table id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82\" > \n<thead> <tr> \n <th class=\"blank level0\" ></th> \n <th class=\"col_heading level0 col0\" >Name</th> \n <th class=\"col_heading level0 col1\" >Direction</th> \n <th class=\"col_heading level0 col2\" >Sharpe DLPAL</th> \n <th class=\"col_heading level0 col3\" >SharpeIS</th> \n <th class=\"col_heading level0 col4\" >SharpeOOS1</th> \n <th class=\"col_heading level0 col5\" >IS Nonflat</th> \n <th class=\"col_heading level0 col6\" >OOS1 Nonflat</th> \n <th class=\"col_heading level0 col7\" >IS NonflatPCT</th> \n <th class=\"col_heading level0 col8\" >OOS1 NonflatPCT</th> \n <th class=\"col_heading level0 col9\" >Score</th> \n <th class=\"col_heading level0 col10\" >Rank</th> \n </tr></thead> \n<tbody> <tr> \n <th id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82level0_row0\" class=\"row_heading level0 row0\" >308</th> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row0_col0\" class=\"data row0 col0\" >AMLP-00308</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row0_col1\" class=\"data row0 col1\" >Short</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row0_col2\" class=\"data row0 col2\" >1.35871</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row0_col3\" class=\"data row0 col3\" >1.46855</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row0_col4\" class=\"data row0 col4\" >1.39443</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row0_col5\" class=\"data row0 col5\" >402</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row0_col6\" class=\"data row0 col6\" >82</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row0_col7\" class=\"data row0 col7\" >42.7205</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row0_col8\" class=\"data row0 col8\" >27.0627</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row0_col9\" class=\"data row0 col9\" >274.816</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row0_col10\" class=\"data row0 col10\" >1</td> \n </tr> <tr> \n <th id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82level0_row1\" class=\"row_heading level0 row1\" >225</th> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row1_col0\" class=\"data row1 col0\" >AMLP-00225</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row1_col1\" class=\"data row1 col1\" >Short</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row1_col2\" class=\"data row1 col2\" >1.56957</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row1_col3\" class=\"data row1 col3\" >1.41899</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row1_col4\" class=\"data row1 col4\" >1.99355</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row1_col5\" class=\"data row1 col5\" >240</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row1_col6\" class=\"data row1 col6\" >31</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row1_col7\" class=\"data row1 col7\" >25.5048</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row1_col8\" class=\"data row1 col8\" >10.231</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row1_col9\" class=\"data row1 col9\" >270.215</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row1_col10\" class=\"data row1 col10\" >2</td> \n </tr> <tr> \n <th id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82level0_row2\" class=\"row_heading level0 row2\" >400</th> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row2_col0\" class=\"data row2 col0\" >AMLP-00400</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row2_col1\" class=\"data row2 col1\" >Short</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row2_col2\" class=\"data row2 col2\" >1.57834</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row2_col3\" class=\"data row2 col3\" >1.36003</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row2_col4\" class=\"data row2 col4\" >2.24782</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row2_col5\" class=\"data row2 col5\" >565</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row2_col6\" class=\"data row2 col6\" >144</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row2_col7\" class=\"data row2 col7\" >60.0425</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row2_col8\" class=\"data row2 col8\" >47.5248</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row2_col9\" class=\"data row2 col9\" >262.999</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row2_col10\" class=\"data row2 col10\" >3</td> \n </tr> <tr> \n <th id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82level0_row3\" class=\"row_heading level0 row3\" >309</th> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row3_col0\" class=\"data row3 col0\" >AMLP-00309</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row3_col1\" class=\"data row3 col1\" >Short</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row3_col2\" class=\"data row3 col2\" >1.42406</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row3_col3\" class=\"data row3 col3\" >1.6667</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row3_col4\" class=\"data row3 col4\" >1.21351</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row3_col5\" class=\"data row3 col5\" >408</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row3_col6\" class=\"data row3 col6\" >109</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row3_col7\" class=\"data row3 col7\" >43.3581</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row3_col8\" class=\"data row3 col8\" >35.9736</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row3_col9\" class=\"data row3 col9\" >256.258</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row3_col10\" class=\"data row3 col10\" >4</td> \n </tr> <tr> \n <th id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82level0_row4\" class=\"row_heading level0 row4\" >593</th> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row4_col0\" class=\"data row4 col0\" >AMLP-00593</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row4_col1\" class=\"data row4 col1\" >Short</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row4_col2\" class=\"data row4 col2\" >1.28768</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row4_col3\" class=\"data row4 col3\" >1.21113</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row4_col4\" class=\"data row4 col4\" >1.69598</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row4_col5\" class=\"data row4 col5\" >92</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row4_col6\" class=\"data row4 col6\" >20</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row4_col7\" class=\"data row4 col7\" >9.77683</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row4_col8\" class=\"data row4 col8\" >6.60066</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row4_col9\" class=\"data row4 col9\" >238.206</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row4_col10\" class=\"data row4 col10\" >5</td> \n </tr> <tr> \n <th id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82level0_row5\" class=\"row_heading level0 row5\" >572</th> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row5_col0\" class=\"data row5 col0\" >AMLP-00572</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row5_col1\" class=\"data row5 col1\" >Short</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row5_col2\" class=\"data row5 col2\" >1.21831</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row5_col3\" class=\"data row5 col3\" >1.19308</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row5_col4\" class=\"data row5 col4\" >1.34484</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row5_col5\" class=\"data row5 col5\" >326</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row5_col6\" class=\"data row5 col6\" >49</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row5_col7\" class=\"data row5 col7\" >34.644</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row5_col8\" class=\"data row5 col8\" >16.1716</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row5_col9\" class=\"data row5 col9\" >236.724</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row5_col10\" class=\"data row5 col10\" >6</td> \n </tr> <tr> \n <th id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82level0_row6\" class=\"row_heading level0 row6\" >219</th> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row6_col0\" class=\"data row6 col0\" >AMLP-00219</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row6_col1\" class=\"data row6 col1\" >Short</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row6_col2\" class=\"data row6 col2\" >1.14611</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row6_col3\" class=\"data row6 col3\" >1.17921</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row6_col4\" class=\"data row6 col4\" >1.24937</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row6_col5\" class=\"data row6 col5\" >656</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row6_col6\" class=\"data row6 col6\" >158</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row6_col7\" class=\"data row6 col7\" >69.7131</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row6_col8\" class=\"data row6 col8\" >52.1452</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row6_col9\" class=\"data row6 col9\" >231.514</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row6_col10\" class=\"data row6 col10\" >7</td> \n </tr> <tr> \n <th id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82level0_row7\" class=\"row_heading level0 row7\" >217</th> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row7_col0\" class=\"data row7 col0\" >AMLP-00217</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row7_col1\" class=\"data row7 col1\" >Short</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row7_col2\" class=\"data row7 col2\" >1.26689</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row7_col3\" class=\"data row7 col3\" >1.41057</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row7_col4\" class=\"data row7 col4\" >0.986359</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row7_col5\" class=\"data row7 col5\" >268</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row7_col6\" class=\"data row7 col6\" >43</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row7_col7\" class=\"data row7 col7\" >28.4803</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row7_col8\" class=\"data row7 col8\" >14.1914</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row7_col9\" class=\"data row7 col9\" >226.766</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row7_col10\" class=\"data row7 col10\" >8</td> \n </tr> <tr> \n <th id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82level0_row8\" class=\"row_heading level0 row8\" >239</th> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row8_col0\" class=\"data row8 col0\" >AMLP-00239</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row8_col1\" class=\"data row8 col1\" >Short</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row8_col2\" class=\"data row8 col2\" >1.18526</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row8_col3\" class=\"data row8 col3\" >1.35224</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row8_col4\" class=\"data row8 col4\" >1.05443</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row8_col5\" class=\"data row8 col5\" >433</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row8_col6\" class=\"data row8 col6\" >130</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row8_col7\" class=\"data row8 col7\" >46.0149</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row8_col8\" class=\"data row8 col8\" >42.9043</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row8_col9\" class=\"data row8 col9\" >221.731</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row8_col10\" class=\"data row8 col10\" >9</td> \n </tr> <tr> \n <th id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82level0_row9\" class=\"row_heading level0 row9\" >315</th> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row9_col0\" class=\"data row9 col0\" >AMLP-00315</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row9_col1\" class=\"data row9 col1\" >Short</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row9_col2\" class=\"data row9 col2\" >1.20312</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row9_col3\" class=\"data row9 col3\" >1.08614</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row9_col4\" class=\"data row9 col4\" >1.60983</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row9_col5\" class=\"data row9 col5\" >544</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row9_col6\" class=\"data row9 col6\" >148</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row9_col7\" class=\"data row9 col7\" >57.8108</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row9_col8\" class=\"data row9 col8\" >48.8449</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row9_col9\" class=\"data row9 col9\" >221.406</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row9_col10\" class=\"data row9 col10\" >10</td> \n </tr> <tr> \n <th id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82level0_row10\" class=\"row_heading level0 row10\" >238</th> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row10_col0\" class=\"data row10 col0\" >AMLP-00238</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row10_col1\" class=\"data row10 col1\" >Short</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row10_col2\" class=\"data row10 col2\" >1.07772</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row10_col3\" class=\"data row10 col3\" >1.09151</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row10_col4\" class=\"data row10 col4\" >1.23263</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row10_col5\" class=\"data row10 col5\" >157</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row10_col6\" class=\"data row10 col6\" >66</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row10_col7\" class=\"data row10 col7\" >16.6844</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row10_col8\" class=\"data row10 col8\" >21.7822</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row10_col9\" class=\"data row10 col9\" >217.31</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row10_col10\" class=\"data row10 col10\" >11</td> \n </tr> <tr> \n <th id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82level0_row11\" class=\"row_heading level0 row11\" >293</th> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row11_col0\" class=\"data row11 col0\" >AMLP-00293</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row11_col1\" class=\"data row11 col1\" >Short</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row11_col2\" class=\"data row11 col2\" >1.08154</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row11_col3\" class=\"data row11 col3\" >1.19524</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row11_col4\" class=\"data row11 col4\" >1.04553</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row11_col5\" class=\"data row11 col5\" >464</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row11_col6\" class=\"data row11 col6\" >88</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row11_col7\" class=\"data row11 col7\" >49.3092</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row11_col8\" class=\"data row11 col8\" >29.0429</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row11_col9\" class=\"data row11 col9\" >214.033</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row11_col10\" class=\"data row11 col10\" >12</td> \n </tr> <tr> \n <th id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82level0_row12\" class=\"row_heading level0 row12\" >234</th> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row12_col0\" class=\"data row12 col0\" >AMLP-00234</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row12_col1\" class=\"data row12 col1\" >Short</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row12_col2\" class=\"data row12 col2\" >1.07936</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row12_col3\" class=\"data row12 col3\" >1.05607</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row12_col4\" class=\"data row12 col4\" >1.22691</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row12_col5\" class=\"data row12 col5\" >391</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row12_col6\" class=\"data row12 col6\" >74</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row12_col7\" class=\"data row12 col7\" >41.5515</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row12_col8\" class=\"data row12 col8\" >24.4224</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row12_col9\" class=\"data row12 col9\" >210.647</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row12_col10\" class=\"data row12 col10\" >13</td> \n </tr> <tr> \n <th id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82level0_row13\" class=\"row_heading level0 row13\" >208</th> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row13_col0\" class=\"data row13 col0\" >AMLP-00208</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row13_col1\" class=\"data row13 col1\" >Short</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row13_col2\" class=\"data row13 col2\" >1.06286</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row13_col3\" class=\"data row13 col3\" >1.04042</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row13_col4\" class=\"data row13 col4\" >1.24914</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row13_col5\" class=\"data row13 col5\" >552</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row13_col6\" class=\"data row13 col6\" >115</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row13_col7\" class=\"data row13 col7\" >58.661</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row13_col8\" class=\"data row13 col8\" >37.9538</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row13_col9\" class=\"data row13 col9\" >207.435</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row13_col10\" class=\"data row13 col10\" >14</td> \n </tr> <tr> \n <th id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82level0_row14\" class=\"row_heading level0 row14\" >437</th> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row14_col0\" class=\"data row14 col0\" >AMLP-00437</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row14_col1\" class=\"data row14 col1\" >Short</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row14_col2\" class=\"data row14 col2\" >0.989368</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row14_col3\" class=\"data row14 col3\" >1.05864</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row14_col4\" class=\"data row14 col4\" >1.11701</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row14_col5\" class=\"data row14 col5\" >61</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row14_col6\" class=\"data row14 col6\" >32</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row14_col7\" class=\"data row14 col7\" >6.48247</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row14_col8\" class=\"data row14 col8\" >10.5611</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row14_col9\" class=\"data row14 col9\" >205.53</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row14_col10\" class=\"data row14 col10\" >15</td> \n </tr> <tr> \n <th id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82level0_row15\" class=\"row_heading level0 row15\" >388</th> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row15_col0\" class=\"data row15 col0\" >AMLP-00388</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row15_col1\" class=\"data row15 col1\" >Short</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row15_col2\" class=\"data row15 col2\" >1.04408</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row15_col3\" class=\"data row15 col3\" >0.97659</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row15_col4\" class=\"data row15 col4\" >1.25593</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row15_col5\" class=\"data row15 col5\" >67</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row15_col6\" class=\"data row15 col6\" >21</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row15_col7\" class=\"data row15 col7\" >7.12009</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row15_col8\" class=\"data row15 col8\" >6.93069</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row15_col9\" class=\"data row15 col9\" >201.263</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row15_col10\" class=\"data row15 col10\" >16</td> \n </tr> <tr> \n <th id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82level0_row16\" class=\"row_heading level0 row16\" >601</th> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row16_col0\" class=\"data row16 col0\" >AMLP-00601</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row16_col1\" class=\"data row16 col1\" >Short</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row16_col2\" class=\"data row16 col2\" >1.03058</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row16_col3\" class=\"data row16 col3\" >1.18111</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row16_col4\" class=\"data row16 col4\" >0.910108</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row16_col5\" class=\"data row16 col5\" >99</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row16_col6\" class=\"data row16 col6\" >13</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row16_col7\" class=\"data row16 col7\" >10.5207</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row16_col8\" class=\"data row16 col8\" >4.29043</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row16_col9\" class=\"data row16 col9\" >199.354</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row16_col10\" class=\"data row16 col10\" >17</td> \n </tr> <tr> \n <th id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82level0_row17\" class=\"row_heading level0 row17\" >361</th> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row17_col0\" class=\"data row17 col0\" >AMLP-00361</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row17_col1\" class=\"data row17 col1\" >Short</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row17_col2\" class=\"data row17 col2\" >0.976257</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row17_col3\" class=\"data row17 col3\" >1.02172</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row17_col4\" class=\"data row17 col4\" >1.06405</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row17_col5\" class=\"data row17 col5\" >447</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row17_col6\" class=\"data row17 col6\" >84</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row17_col7\" class=\"data row17 col7\" >47.5027</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row17_col8\" class=\"data row17 col8\" >27.7228</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row17_col9\" class=\"data row17 col9\" >199.292</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row17_col10\" class=\"data row17 col10\" >18</td> \n </tr> <tr> \n <th id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82level0_row18\" class=\"row_heading level0 row18\" >377</th> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row18_col0\" class=\"data row18 col0\" >AMLP-00377</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row18_col1\" class=\"data row18 col1\" >Short</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row18_col2\" class=\"data row18 col2\" >1.11862</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row18_col3\" class=\"data row18 col3\" >1.16087</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row18_col4\" class=\"data row18 col4\" >1.92685</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row18_col5\" class=\"data row18 col5\" >106</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row18_col6\" class=\"data row18 col6\" >7</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row18_col7\" class=\"data row18 col7\" >11.2646</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row18_col8\" class=\"data row18 col8\" >2.31023</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row18_col9\" class=\"data row18 col9\" >198.142</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row18_col10\" class=\"data row18 col10\" >19</td> \n </tr> <tr> \n <th id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82level0_row19\" class=\"row_heading level0 row19\" >245</th> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row19_col0\" class=\"data row19 col0\" >AMLP-00245</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row19_col1\" class=\"data row19 col1\" >Short</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row19_col2\" class=\"data row19 col2\" >1.17501</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row19_col3\" class=\"data row19 col3\" >0.796623</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row19_col4\" class=\"data row19 col4\" >2.22672</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row19_col5\" class=\"data row19 col5\" >141</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row19_col6\" class=\"data row19 col6\" >57</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row19_col7\" class=\"data row19 col7\" >14.9841</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row19_col8\" class=\"data row19 col8\" >18.8119</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row19_col9\" class=\"data row19 col9\" >192.748</td> \n <td id=\"T_6f5b9d58_2698_11e8_bb7f_002683143c82row19_col10\" class=\"data row19 col10\" >20</td> \n </tr></tbody> \n</table> ",
  264. "text/plain": "<pandas.io.formats.style.Styler at 0x288d16f1dd8>"
  265. },
  266. "metadata": {},
  267. "output_type": "display_data"
  268. },
  269. {
  270. "name": "stdout",
  271. "output_type": "stream",
  272. "text": "Long Indices: [167, 116, 136, 102, 117, 181, 176, 68, 7, 180]\nShort Indices: [308, 225, 400, 309, 593, 572, 219, 217, 239, 315, 238, 293, 234, 208, 437, 388, 601, 361, 377, 245]\n"
  273. }
  274. ]
  275. },
  276. {
  277. "metadata": {},
  278. "cell_type": "markdown",
  279. "source": "# The Following Rank the Rules in Outer Period [Outside of DLPAL Period]\nMethodology: Let $a =$ OOS2 NonflatPCT,$\\quad b=$ OOS3 NonflatPCT $\\quad\\quad n=a+b$\n$$Score\\text{ } Outer = 100 \\left[ \\frac{a(\\text{SharpeOOS2}) + b(\\text{SharpeOOS3})}{n} + \\text{SharpeOOS2N3}\\left( 1-{\\frac{|\\text{ SharpeOOS2}-\\text{SharpeOOS3 }|}{2}} \\right)\\right] $$\nHigher weights on higher nonflat, deviation small doesn't mean higher rank all the time, relative to the\n\"goodness\" of Sharpe"
  280. },
  281. {
  282. "metadata": {
  283. "trusted": true
  284. },
  285. "cell_type": "code",
  286. "source": "outer_rank = Rank_outer_period(long_rules).head(top)\n\nprint(\"The ranking without separation of Longs and Shorts\")\nwith pd.option_context('display.max_rows', None, 'display.max_columns', None):\n display(outer_rank[['Name','Direction','Sharpe','SharpeOOS2','SharpeIS','SharpeOOS1','SharpeOOS3',\n 'OOS2 NonflatPCT','IS NonflatPCT', 'OOS1 NonflatPCT','OOS3 NonflatPCT',\n 'Score Outer','Rank Outer']]\n .style.apply(highlight_max, subset = ['Sharpe','SharpeOOS2','SharpeIS','SharpeOOS1','SharpeOOS3',\n 'OOS2 NonflatPCT','IS NonflatPCT', 'OOS1 NonflatPCT','OOS3 NonflatPCT',\n 'Score Outer']))",
  287. "execution_count": 13,
  288. "outputs": [
  289. {
  290. "name": "stdout",
  291. "output_type": "stream",
  292. "text": "The ranking without separation of Longs and Shorts\n"
  293. },
  294. {
  295. "data": {
  296. "text/html": "<style type=\"text/css\" >\n #T_ceb0d52e_2683_11e8_9f33_002683143c82row0_col2 {\n background-color: lightgreen;\n } #T_ceb0d52e_2683_11e8_9f33_002683143c82row0_col3 {\n background-color: lightgreen;\n } #T_ceb0d52e_2683_11e8_9f33_002683143c82row0_col11 {\n background-color: lightgreen;\n } #T_ceb0d52e_2683_11e8_9f33_002683143c82row1_col6 {\n background-color: lightgreen;\n } #T_ceb0d52e_2683_11e8_9f33_002683143c82row1_col7 {\n background-color: lightgreen;\n } #T_ceb0d52e_2683_11e8_9f33_002683143c82row1_col8 {\n background-color: lightgreen;\n } #T_ceb0d52e_2683_11e8_9f33_002683143c82row1_col9 {\n background-color: lightgreen;\n } #T_ceb0d52e_2683_11e8_9f33_002683143c82row2_col5 {\n background-color: lightgreen;\n } #T_ceb0d52e_2683_11e8_9f33_002683143c82row6_col4 {\n background-color: lightgreen;\n } #T_ceb0d52e_2683_11e8_9f33_002683143c82row8_col10 {\n background-color: lightgreen;\n }</style> \n<table id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82\" > \n<thead> <tr> \n <th class=\"blank level0\" ></th> \n <th class=\"col_heading level0 col0\" >Name</th> \n <th class=\"col_heading level0 col1\" >Direction</th> \n <th class=\"col_heading level0 col2\" >Sharpe</th> \n <th class=\"col_heading level0 col3\" >SharpeOOS2</th> \n <th class=\"col_heading level0 col4\" >SharpeIS</th> \n <th class=\"col_heading level0 col5\" >SharpeOOS1</th> \n <th class=\"col_heading level0 col6\" >SharpeOOS3</th> \n <th class=\"col_heading level0 col7\" >OOS2 NonflatPCT</th> \n <th class=\"col_heading level0 col8\" >IS NonflatPCT</th> \n <th class=\"col_heading level0 col9\" >OOS1 NonflatPCT</th> \n <th class=\"col_heading level0 col10\" >OOS3 NonflatPCT</th> \n <th class=\"col_heading level0 col11\" >Score Outer</th> \n <th class=\"col_heading level0 col12\" >Rank Outer</th> \n </tr></thead> \n<tbody> <tr> \n <th id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82level0_row0\" class=\"row_heading level0 row0\" >116</th> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row0_col0\" class=\"data row0 col0\" >AMLP-00116</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row0_col1\" class=\"data row0 col1\" >Long</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row0_col2\" class=\"data row0 col2\" >1.06485</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row0_col3\" class=\"data row0 col3\" >2.15526</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row0_col4\" class=\"data row0 col4\" >1.22829</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row0_col5\" class=\"data row0 col5\" >0.544062</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row0_col6\" class=\"data row0 col6\" >0.565165</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row0_col7\" class=\"data row0 col7\" >9.97067</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row0_col8\" class=\"data row0 col8\" >11.1583</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row0_col9\" class=\"data row0 col9\" >4.62046</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row0_col10\" class=\"data row0 col10\" >4.2623</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row0_col11\" class=\"data row0 col11\" >195.719</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row0_col12\" class=\"data row0 col12\" >1</td> \n </tr> <tr> \n <th id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82level0_row1\" class=\"row_heading level0 row1\" >106</th> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row1_col0\" class=\"data row1 col0\" >AMLP-00106</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row1_col1\" class=\"data row1 col1\" >Long</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row1_col2\" class=\"data row1 col2\" >0.465545</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row1_col3\" class=\"data row1 col3\" >0.550931</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row1_col4\" class=\"data row1 col4\" >0.231968</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row1_col5\" class=\"data row1 col5\" >0.565743</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row1_col6\" class=\"data row1 col6\" >1.41557</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row1_col7\" class=\"data row1 col7\" >33.1378</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row1_col8\" class=\"data row1 col8\" >42.1892</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row1_col9\" class=\"data row1 col9\" >25.4125</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row1_col10\" class=\"data row1 col10\" >18.0328</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row1_col11\" class=\"data row1 col11\" >140.829</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row1_col12\" class=\"data row1 col12\" >2</td> \n </tr> <tr> \n <th id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82level0_row2\" class=\"row_heading level0 row2\" >136</th> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row2_col0\" class=\"data row2 col0\" >AMLP-00136</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row2_col1\" class=\"data row2 col1\" >Long</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row2_col2\" class=\"data row2 col2\" >0.74644</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row2_col3\" class=\"data row2 col3\" >0.91652</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row2_col4\" class=\"data row2 col4\" >0.426769</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row2_col5\" class=\"data row2 col5\" >1.78973</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row2_col6\" class=\"data row2 col6\" >0.110357</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row2_col7\" class=\"data row2 col7\" >29.6188</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row2_col8\" class=\"data row2 col8\" >13.6026</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row2_col9\" class=\"data row2 col9\" >12.8713</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row2_col10\" class=\"data row2 col10\" >11.8033</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row2_col11\" class=\"data row2 col11\" >102.911</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row2_col12\" class=\"data row2 col12\" >3</td> \n </tr> <tr> \n <th id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82level0_row3\" class=\"row_heading level0 row3\" >105</th> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row3_col0\" class=\"data row3 col0\" >AMLP-00105</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row3_col1\" class=\"data row3 col1\" >Long</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row3_col2\" class=\"data row3 col2\" >0.252906</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row3_col3\" class=\"data row3 col3\" >1.57112</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row3_col4\" class=\"data row3 col4\" >0.314378</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row3_col5\" class=\"data row3 col5\" >0.341573</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row3_col6\" class=\"data row3 col6\" >-0.839421</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row3_col7\" class=\"data row3 col7\" >9.67742</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row3_col8\" class=\"data row3 col8\" >15.1966</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row3_col9\" class=\"data row3 col9\" >3.30033</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row3_col10\" class=\"data row3 col10\" >3.27869</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row3_col11\" class=\"data row3 col11\" >94.5818</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row3_col12\" class=\"data row3 col12\" >4</td> \n </tr> <tr> \n <th id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82level0_row4\" class=\"row_heading level0 row4\" >102</th> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row4_col0\" class=\"data row4 col0\" >AMLP-00102</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row4_col1\" class=\"data row4 col1\" >Long</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row4_col2\" class=\"data row4 col2\" >0.800721</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row4_col3\" class=\"data row4 col3\" >1.61167</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row4_col4\" class=\"data row4 col4\" >0.549812</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row4_col5\" class=\"data row4 col5\" >1.65078</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row4_col6\" class=\"data row4 col6\" >-0.21009</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row4_col7\" class=\"data row4 col7\" >2.93255</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row4_col8\" class=\"data row4 col8\" >20.1913</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row4_col9\" class=\"data row4 col9\" >9.57096</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row4_col10\" class=\"data row4 col10\" >3.27869</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row4_col11\" class=\"data row4 col11\" >70.5087</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row4_col12\" class=\"data row4 col12\" >5</td> \n </tr> <tr> \n <th id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82level0_row5\" class=\"row_heading level0 row5\" >14</th> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row5_col0\" class=\"data row5 col0\" >AMLP-00014</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row5_col1\" class=\"data row5 col1\" >Long</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row5_col2\" class=\"data row5 col2\" >0.44971</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row5_col3\" class=\"data row5 col3\" >0.748313</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row5_col4\" class=\"data row5 col4\" >0.233512</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row5_col5\" class=\"data row5 col5\" >1.01724</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row5_col6\" class=\"data row5 col6\" >0.0980198</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row5_col7\" class=\"data row5 col7\" >17.8886</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row5_col8\" class=\"data row5 col8\" >15.3029</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row5_col9\" class=\"data row5 col9\" >12.5413</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row5_col10\" class=\"data row5 col10\" >16.3934</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row5_col11\" class=\"data row5 col11\" >69.8102</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row5_col12\" class=\"data row5 col12\" >6</td> \n </tr> <tr> \n <th id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82level0_row6\" class=\"row_heading level0 row6\" >167</th> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row6_col0\" class=\"data row6 col0\" >AMLP-00167</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row6_col1\" class=\"data row6 col1\" >Long</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row6_col2\" class=\"data row6 col2\" >0.848278</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row6_col3\" class=\"data row6 col3\" >0.540776</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row6_col4\" class=\"data row6 col4\" >1.74023</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row6_col5\" class=\"data row6 col5\" >0.211354</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row6_col6\" class=\"data row6 col6\" >-0.103539</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row6_col7\" class=\"data row6 col7\" >2.6393</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row6_col8\" class=\"data row6 col8\" >13.0712</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row6_col9\" class=\"data row6 col9\" >2.9703</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row6_col10\" class=\"data row6 col10\" >3.93443</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row6_col11\" class=\"data row6 col11\" >31.0066</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row6_col12\" class=\"data row6 col12\" >7</td> \n </tr> <tr> \n <th id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82level0_row7\" class=\"row_heading level0 row7\" >180</th> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row7_col0\" class=\"data row7 col0\" >AMLP-00180</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row7_col1\" class=\"data row7 col1\" >Long</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row7_col2\" class=\"data row7 col2\" >0.354959</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row7_col3\" class=\"data row7 col3\" >0.24949</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row7_col4\" class=\"data row7 col4\" >0.41752</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row7_col5\" class=\"data row7 col5\" >0.749201</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row7_col6\" class=\"data row7 col6\" >-0.52751</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row7_col7\" class=\"data row7 col7\" >17.3021</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row7_col8\" class=\"data row7 col8\" >14.0276</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row7_col9\" class=\"data row7 col9\" >11.8812</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row7_col10\" class=\"data row7 col10\" >1.96721</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row7_col11\" class=\"data row7 col11\" >13.596</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row7_col12\" class=\"data row7 col12\" >8</td> \n </tr> <tr> \n <th id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82level0_row8\" class=\"row_heading level0 row8\" >61</th> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row8_col0\" class=\"data row8 col0\" >AMLP-00061</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row8_col1\" class=\"data row8 col1\" >Long</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row8_col2\" class=\"data row8 col2\" >0.486624</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row8_col3\" class=\"data row8 col3\" >-0.113525</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row8_col4\" class=\"data row8 col4\" >0.373884</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row8_col5\" class=\"data row8 col5\" >1.69339</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row8_col6\" class=\"data row8 col6\" >0.132679</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row8_col7\" class=\"data row8 col7\" >6.74487</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row8_col8\" class=\"data row8 col8\" >19.1286</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row8_col9\" class=\"data row8 col9\" >5.28053</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row8_col10\" class=\"data row8 col10\" >19.6721</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row8_col11\" class=\"data row8 col11\" >7.60196</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row8_col12\" class=\"data row8 col12\" >9</td> \n </tr> <tr> \n <th id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82level0_row9\" class=\"row_heading level0 row9\" >173</th> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row9_col0\" class=\"data row9 col0\" >AMLP-00173</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row9_col1\" class=\"data row9 col1\" >Long</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row9_col2\" class=\"data row9 col2\" >0.228576</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row9_col3\" class=\"data row9 col3\" >1.06741</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row9_col4\" class=\"data row9 col4\" >0.372413</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row9_col5\" class=\"data row9 col5\" >0.383954</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row9_col6\" class=\"data row9 col6\" >-0.504906</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row9_col7\" class=\"data row9 col7\" >2.34604</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row9_col8\" class=\"data row9 col8\" >11.796</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row9_col9\" class=\"data row9 col9\" >4.9505</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row9_col10\" class=\"data row9 col10\" >12.459</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row9_col11\" class=\"data row9 col11\" >-27.8523</td> \n <td id=\"T_ceb0d52e_2683_11e8_9f33_002683143c82row9_col12\" class=\"data row9 col12\" >10</td> \n </tr></tbody> \n</table> ",
  297. "text/plain": "<pandas.io.formats.style.Styler at 0x288c7ed0940>"
  298. },
  299. "metadata": {},
  300. "output_type": "display_data"
  301. }
  302. ]
  303. },
  304. {
  305. "metadata": {
  306. "trusted": true
  307. },
  308. "cell_type": "code",
  309. "source": "rank_long_outer_period = Rank_outer_period(long_rules).head(top)\nrank_short_outer_period = Rank_outer_period(short_rules).head(top)\n\nprint(\"Longs and Shorts Seperated in Outer Period [OOS2 and OOS3]\")\nwith pd.option_context('display.max_rows', None, 'display.max_columns', None):\n display(rank_long_outer_period[['Name','Direction','Sharpe','SharpeOOS2','SharpeIS','SharpeOOS1','SharpeOOS3',\n 'OOS2 NonflatPCT','IS NonflatPCT', 'OOS1 NonflatPCT','OOS3 NonflatPCT',\n 'Score Outer','Rank Outer']]\n .style.apply(highlight_max, subset = ['Sharpe','SharpeOOS2','SharpeIS','SharpeOOS1','SharpeOOS3',\n 'OOS2 NonflatPCT','IS NonflatPCT', 'OOS1 NonflatPCT','OOS3 NonflatPCT',\n 'Score Outer']))\n display(rank_short_outer_period[['Name','Direction','Sharpe','SharpeOOS2','SharpeIS','SharpeOOS1','SharpeOOS3',\n 'OOS2 NonflatPCT','IS NonflatPCT', 'OOS1 NonflatPCT','OOS3 NonflatPCT',\n 'Score Outer','Rank Outer']]\n .style.apply(highlight_max, subset = ['Sharpe','SharpeOOS2','SharpeIS','SharpeOOS1','SharpeOOS3',\n 'OOS2 NonflatPCT','IS NonflatPCT', 'OOS1 NonflatPCT','OOS3 NonflatPCT',\n 'Score Outer']))\n\nlong_indices_outer_period = [x for x in rank_long_outer_period.index]\nshort_indices_outer_period = [x for x in rank_short_outer_period.index]",
  310. "execution_count": 103,
  311. "outputs": [
  312. {
  313. "name": "stdout",
  314. "output_type": "stream",
  315. "text": "Longs and Shorts Seperated in Outer Period [OOS2 and OOS3]\n"
  316. },
  317. {
  318. "data": {
  319. "text/html": "<style type=\"text/css\" >\n #T_80c60aba_2698_11e8_87ea_002683143c82row0_col2 {\n background-color: lightgreen;\n } #T_80c60aba_2698_11e8_87ea_002683143c82row0_col3 {\n background-color: lightgreen;\n } #T_80c60aba_2698_11e8_87ea_002683143c82row0_col11 {\n background-color: lightgreen;\n } #T_80c60aba_2698_11e8_87ea_002683143c82row1_col6 {\n background-color: lightgreen;\n } #T_80c60aba_2698_11e8_87ea_002683143c82row1_col7 {\n background-color: lightgreen;\n } #T_80c60aba_2698_11e8_87ea_002683143c82row1_col8 {\n background-color: lightgreen;\n } #T_80c60aba_2698_11e8_87ea_002683143c82row1_col9 {\n background-color: lightgreen;\n } #T_80c60aba_2698_11e8_87ea_002683143c82row2_col5 {\n background-color: lightgreen;\n } #T_80c60aba_2698_11e8_87ea_002683143c82row6_col4 {\n background-color: lightgreen;\n } #T_80c60aba_2698_11e8_87ea_002683143c82row8_col10 {\n background-color: lightgreen;\n }</style> \n<table id=\"T_80c60aba_2698_11e8_87ea_002683143c82\" > \n<thead> <tr> \n <th class=\"blank level0\" ></th> \n <th class=\"col_heading level0 col0\" >Name</th> \n <th class=\"col_heading level0 col1\" >Direction</th> \n <th class=\"col_heading level0 col2\" >Sharpe</th> \n <th class=\"col_heading level0 col3\" >SharpeOOS2</th> \n <th class=\"col_heading level0 col4\" >SharpeIS</th> \n <th class=\"col_heading level0 col5\" >SharpeOOS1</th> \n <th class=\"col_heading level0 col6\" >SharpeOOS3</th> \n <th class=\"col_heading level0 col7\" >OOS2 NonflatPCT</th> \n <th class=\"col_heading level0 col8\" >IS NonflatPCT</th> \n <th class=\"col_heading level0 col9\" >OOS1 NonflatPCT</th> \n <th class=\"col_heading level0 col10\" >OOS3 NonflatPCT</th> \n <th class=\"col_heading level0 col11\" >Score Outer</th> \n <th class=\"col_heading level0 col12\" >Rank Outer</th> \n </tr></thead> \n<tbody> <tr> \n <th id=\"T_80c60aba_2698_11e8_87ea_002683143c82level0_row0\" class=\"row_heading level0 row0\" >116</th> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row0_col0\" class=\"data row0 col0\" >AMLP-00116</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row0_col1\" class=\"data row0 col1\" >Long</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row0_col2\" class=\"data row0 col2\" >1.06485</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row0_col3\" class=\"data row0 col3\" >2.15526</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row0_col4\" class=\"data row0 col4\" >1.22829</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row0_col5\" class=\"data row0 col5\" >0.544062</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row0_col6\" class=\"data row0 col6\" >0.565165</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row0_col7\" class=\"data row0 col7\" >9.97067</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row0_col8\" class=\"data row0 col8\" >11.1583</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row0_col9\" class=\"data row0 col9\" >4.62046</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row0_col10\" class=\"data row0 col10\" >4.2623</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row0_col11\" class=\"data row0 col11\" >195.719</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row0_col12\" class=\"data row0 col12\" >1</td> \n </tr> <tr> \n <th id=\"T_80c60aba_2698_11e8_87ea_002683143c82level0_row1\" class=\"row_heading level0 row1\" >106</th> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row1_col0\" class=\"data row1 col0\" >AMLP-00106</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row1_col1\" class=\"data row1 col1\" >Long</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row1_col2\" class=\"data row1 col2\" >0.465545</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row1_col3\" class=\"data row1 col3\" >0.550931</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row1_col4\" class=\"data row1 col4\" >0.231968</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row1_col5\" class=\"data row1 col5\" >0.565743</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row1_col6\" class=\"data row1 col6\" >1.41557</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row1_col7\" class=\"data row1 col7\" >33.1378</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row1_col8\" class=\"data row1 col8\" >42.1892</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row1_col9\" class=\"data row1 col9\" >25.4125</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row1_col10\" class=\"data row1 col10\" >18.0328</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row1_col11\" class=\"data row1 col11\" >140.829</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row1_col12\" class=\"data row1 col12\" >2</td> \n </tr> <tr> \n <th id=\"T_80c60aba_2698_11e8_87ea_002683143c82level0_row2\" class=\"row_heading level0 row2\" >136</th> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row2_col0\" class=\"data row2 col0\" >AMLP-00136</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row2_col1\" class=\"data row2 col1\" >Long</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row2_col2\" class=\"data row2 col2\" >0.74644</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row2_col3\" class=\"data row2 col3\" >0.91652</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row2_col4\" class=\"data row2 col4\" >0.426769</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row2_col5\" class=\"data row2 col5\" >1.78973</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row2_col6\" class=\"data row2 col6\" >0.110357</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row2_col7\" class=\"data row2 col7\" >29.6188</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row2_col8\" class=\"data row2 col8\" >13.6026</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row2_col9\" class=\"data row2 col9\" >12.8713</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row2_col10\" class=\"data row2 col10\" >11.8033</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row2_col11\" class=\"data row2 col11\" >102.911</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row2_col12\" class=\"data row2 col12\" >3</td> \n </tr> <tr> \n <th id=\"T_80c60aba_2698_11e8_87ea_002683143c82level0_row3\" class=\"row_heading level0 row3\" >105</th> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row3_col0\" class=\"data row3 col0\" >AMLP-00105</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row3_col1\" class=\"data row3 col1\" >Long</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row3_col2\" class=\"data row3 col2\" >0.252906</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row3_col3\" class=\"data row3 col3\" >1.57112</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row3_col4\" class=\"data row3 col4\" >0.314378</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row3_col5\" class=\"data row3 col5\" >0.341573</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row3_col6\" class=\"data row3 col6\" >-0.839421</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row3_col7\" class=\"data row3 col7\" >9.67742</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row3_col8\" class=\"data row3 col8\" >15.1966</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row3_col9\" class=\"data row3 col9\" >3.30033</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row3_col10\" class=\"data row3 col10\" >3.27869</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row3_col11\" class=\"data row3 col11\" >94.5818</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row3_col12\" class=\"data row3 col12\" >4</td> \n </tr> <tr> \n <th id=\"T_80c60aba_2698_11e8_87ea_002683143c82level0_row4\" class=\"row_heading level0 row4\" >102</th> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row4_col0\" class=\"data row4 col0\" >AMLP-00102</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row4_col1\" class=\"data row4 col1\" >Long</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row4_col2\" class=\"data row4 col2\" >0.800721</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row4_col3\" class=\"data row4 col3\" >1.61167</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row4_col4\" class=\"data row4 col4\" >0.549812</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row4_col5\" class=\"data row4 col5\" >1.65078</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row4_col6\" class=\"data row4 col6\" >-0.21009</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row4_col7\" class=\"data row4 col7\" >2.93255</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row4_col8\" class=\"data row4 col8\" >20.1913</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row4_col9\" class=\"data row4 col9\" >9.57096</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row4_col10\" class=\"data row4 col10\" >3.27869</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row4_col11\" class=\"data row4 col11\" >70.5087</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row4_col12\" class=\"data row4 col12\" >5</td> \n </tr> <tr> \n <th id=\"T_80c60aba_2698_11e8_87ea_002683143c82level0_row5\" class=\"row_heading level0 row5\" >14</th> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row5_col0\" class=\"data row5 col0\" >AMLP-00014</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row5_col1\" class=\"data row5 col1\" >Long</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row5_col2\" class=\"data row5 col2\" >0.44971</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row5_col3\" class=\"data row5 col3\" >0.748313</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row5_col4\" class=\"data row5 col4\" >0.233512</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row5_col5\" class=\"data row5 col5\" >1.01724</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row5_col6\" class=\"data row5 col6\" >0.0980198</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row5_col7\" class=\"data row5 col7\" >17.8886</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row5_col8\" class=\"data row5 col8\" >15.3029</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row5_col9\" class=\"data row5 col9\" >12.5413</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row5_col10\" class=\"data row5 col10\" >16.3934</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row5_col11\" class=\"data row5 col11\" >69.8102</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row5_col12\" class=\"data row5 col12\" >6</td> \n </tr> <tr> \n <th id=\"T_80c60aba_2698_11e8_87ea_002683143c82level0_row6\" class=\"row_heading level0 row6\" >167</th> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row6_col0\" class=\"data row6 col0\" >AMLP-00167</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row6_col1\" class=\"data row6 col1\" >Long</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row6_col2\" class=\"data row6 col2\" >0.848278</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row6_col3\" class=\"data row6 col3\" >0.540776</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row6_col4\" class=\"data row6 col4\" >1.74023</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row6_col5\" class=\"data row6 col5\" >0.211354</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row6_col6\" class=\"data row6 col6\" >-0.103539</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row6_col7\" class=\"data row6 col7\" >2.6393</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row6_col8\" class=\"data row6 col8\" >13.0712</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row6_col9\" class=\"data row6 col9\" >2.9703</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row6_col10\" class=\"data row6 col10\" >3.93443</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row6_col11\" class=\"data row6 col11\" >31.0066</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row6_col12\" class=\"data row6 col12\" >7</td> \n </tr> <tr> \n <th id=\"T_80c60aba_2698_11e8_87ea_002683143c82level0_row7\" class=\"row_heading level0 row7\" >180</th> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row7_col0\" class=\"data row7 col0\" >AMLP-00180</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row7_col1\" class=\"data row7 col1\" >Long</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row7_col2\" class=\"data row7 col2\" >0.354959</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row7_col3\" class=\"data row7 col3\" >0.24949</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row7_col4\" class=\"data row7 col4\" >0.41752</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row7_col5\" class=\"data row7 col5\" >0.749201</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row7_col6\" class=\"data row7 col6\" >-0.52751</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row7_col7\" class=\"data row7 col7\" >17.3021</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row7_col8\" class=\"data row7 col8\" >14.0276</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row7_col9\" class=\"data row7 col9\" >11.8812</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row7_col10\" class=\"data row7 col10\" >1.96721</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row7_col11\" class=\"data row7 col11\" >13.596</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row7_col12\" class=\"data row7 col12\" >8</td> \n </tr> <tr> \n <th id=\"T_80c60aba_2698_11e8_87ea_002683143c82level0_row8\" class=\"row_heading level0 row8\" >61</th> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row8_col0\" class=\"data row8 col0\" >AMLP-00061</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row8_col1\" class=\"data row8 col1\" >Long</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row8_col2\" class=\"data row8 col2\" >0.486624</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row8_col3\" class=\"data row8 col3\" >-0.113525</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row8_col4\" class=\"data row8 col4\" >0.373884</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row8_col5\" class=\"data row8 col5\" >1.69339</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row8_col6\" class=\"data row8 col6\" >0.132679</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row8_col7\" class=\"data row8 col7\" >6.74487</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row8_col8\" class=\"data row8 col8\" >19.1286</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row8_col9\" class=\"data row8 col9\" >5.28053</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row8_col10\" class=\"data row8 col10\" >19.6721</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row8_col11\" class=\"data row8 col11\" >7.60196</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row8_col12\" class=\"data row8 col12\" >9</td> \n </tr> <tr> \n <th id=\"T_80c60aba_2698_11e8_87ea_002683143c82level0_row9\" class=\"row_heading level0 row9\" >173</th> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row9_col0\" class=\"data row9 col0\" >AMLP-00173</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row9_col1\" class=\"data row9 col1\" >Long</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row9_col2\" class=\"data row9 col2\" >0.228576</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row9_col3\" class=\"data row9 col3\" >1.06741</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row9_col4\" class=\"data row9 col4\" >0.372413</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row9_col5\" class=\"data row9 col5\" >0.383954</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row9_col6\" class=\"data row9 col6\" >-0.504906</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row9_col7\" class=\"data row9 col7\" >2.34604</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row9_col8\" class=\"data row9 col8\" >11.796</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row9_col9\" class=\"data row9 col9\" >4.9505</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row9_col10\" class=\"data row9 col10\" >12.459</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row9_col11\" class=\"data row9 col11\" >-27.8523</td> \n <td id=\"T_80c60aba_2698_11e8_87ea_002683143c82row9_col12\" class=\"data row9 col12\" >10</td> \n </tr></tbody> \n</table> ",
  320. "text/plain": "<pandas.io.formats.style.Styler at 0x288d33a3e10>"
  321. },
  322. "metadata": {},
  323. "output_type": "display_data"
  324. },
  325. {
  326. "data": {
  327. "text/html": "<style type=\"text/css\" >\n #T_80d08110_2698_11e8_ab6b_002683143c82row0_col11 {\n background-color: lightgreen;\n } #T_80d08110_2698_11e8_ab6b_002683143c82row1_col3 {\n background-color: lightgreen;\n } #T_80d08110_2698_11e8_ab6b_002683143c82row2_col5 {\n background-color: lightgreen;\n } #T_80d08110_2698_11e8_ab6b_002683143c82row3_col7 {\n background-color: lightgreen;\n } #T_80d08110_2698_11e8_ab6b_002683143c82row4_col6 {\n background-color: lightgreen;\n } #T_80d08110_2698_11e8_ab6b_002683143c82row4_col8 {\n background-color: lightgreen;\n } #T_80d08110_2698_11e8_ab6b_002683143c82row6_col9 {\n background-color: lightgreen;\n } #T_80d08110_2698_11e8_ab6b_002683143c82row6_col10 {\n background-color: lightgreen;\n } #T_80d08110_2698_11e8_ab6b_002683143c82row8_col2 {\n background-color: lightgreen;\n } #T_80d08110_2698_11e8_ab6b_002683143c82row8_col4 {\n background-color: lightgreen;\n }</style> \n<table id=\"T_80d08110_2698_11e8_ab6b_002683143c82\" > \n<thead> <tr> \n <th class=\"blank level0\" ></th> \n <th class=\"col_heading level0 col0\" >Name</th> \n <th class=\"col_heading level0 col1\" >Direction</th> \n <th class=\"col_heading level0 col2\" >Sharpe</th> \n <th class=\"col_heading level0 col3\" >SharpeOOS2</th> \n <th class=\"col_heading level0 col4\" >SharpeIS</th> \n <th class=\"col_heading level0 col5\" >SharpeOOS1</th> \n <th class=\"col_heading level0 col6\" >SharpeOOS3</th> \n <th class=\"col_heading level0 col7\" >OOS2 NonflatPCT</th> \n <th class=\"col_heading level0 col8\" >IS NonflatPCT</th> \n <th class=\"col_heading level0 col9\" >OOS1 NonflatPCT</th> \n <th class=\"col_heading level0 col10\" >OOS3 NonflatPCT</th> \n <th class=\"col_heading level0 col11\" >Score Outer</th> \n <th class=\"col_heading level0 col12\" >Rank Outer</th> \n </tr></thead> \n<tbody> <tr> \n <th id=\"T_80d08110_2698_11e8_ab6b_002683143c82level0_row0\" class=\"row_heading level0 row0\" >259</th> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row0_col0\" class=\"data row0 col0\" >AMLP-00259</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row0_col1\" class=\"data row0 col1\" >Short</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row0_col2\" class=\"data row0 col2\" >0.787243</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row0_col3\" class=\"data row0 col3\" >1.33681</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row0_col4\" class=\"data row0 col4\" >0.763324</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row0_col5\" class=\"data row0 col5\" >0.349801</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row0_col6\" class=\"data row0 col6\" >1.78016</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row0_col7\" class=\"data row0 col7\" >2.05279</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row0_col8\" class=\"data row0 col8\" >12.9649</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row0_col9\" class=\"data row0 col9\" >7.92079</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row0_col10\" class=\"data row0 col10\" >13.7705</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row0_col11\" class=\"data row0 col11\" >283.594</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row0_col12\" class=\"data row0 col12\" >1</td> \n </tr> <tr> \n <th id=\"T_80d08110_2698_11e8_ab6b_002683143c82level0_row1\" class=\"row_heading level0 row1\" >266</th> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row1_col0\" class=\"data row1 col0\" >AMLP-00266</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row1_col1\" class=\"data row1 col1\" >Short</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row1_col2\" class=\"data row1 col2\" >0.834933</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row1_col3\" class=\"data row1 col3\" >2.06168</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row1_col4\" class=\"data row1 col4\" >0.647193</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row1_col5\" class=\"data row1 col5\" >0.553638</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row1_col6\" class=\"data row1 col6\" >1.40344</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row1_col7\" class=\"data row1 col7\" >6.45161</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row1_col8\" class=\"data row1 col8\" >24.7609</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row1_col9\" class=\"data row1 col9\" >6.60066</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row1_col10\" class=\"data row1 col10\" >11.4754</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row1_col11\" class=\"data row1 col11\" >272.906</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row1_col12\" class=\"data row1 col12\" >2</td> \n </tr> <tr> \n <th id=\"T_80d08110_2698_11e8_ab6b_002683143c82level0_row2\" class=\"row_heading level0 row2\" >452</th> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row2_col0\" class=\"data row2 col0\" >AMLP-00452</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row2_col1\" class=\"data row2 col1\" >Short</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row2_col2\" class=\"data row2 col2\" >1.15453</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row2_col3\" class=\"data row2 col3\" >0.825182</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row2_col4\" class=\"data row2 col4\" >0.430815</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row2_col5\" class=\"data row2 col5\" >2.29227</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row2_col6\" class=\"data row2 col6\" >2.30203</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row2_col7\" class=\"data row2 col7\" >2.34604</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row2_col8\" class=\"data row2 col8\" >15.0903</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row2_col9\" class=\"data row2 col9\" >11.8812</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row2_col10\" class=\"data row2 col10\" >10.4918</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row2_col11\" class=\"data row2 col11\" >246.571</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row2_col12\" class=\"data row2 col12\" >3</td> \n </tr> <tr> \n <th id=\"T_80d08110_2698_11e8_ab6b_002683143c82level0_row3\" class=\"row_heading level0 row3\" >436</th> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row3_col0\" class=\"data row3 col0\" >AMLP-00436</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row3_col1\" class=\"data row3 col1\" >Short</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row3_col2\" class=\"data row3 col2\" >0.836929</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row3_col3\" class=\"data row3 col3\" >1.48231</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row3_col4\" class=\"data row3 col4\" >1.02157</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row3_col5\" class=\"data row3 col5\" >0.211024</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row3_col6\" class=\"data row3 col6\" >1.14762</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row3_col7\" class=\"data row3 col7\" >21.1144</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row3_col8\" class=\"data row3 col8\" >19.6599</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row3_col9\" class=\"data row3 col9\" >14.1914</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row3_col10\" class=\"data row3 col10\" >20.3279</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row3_col11\" class=\"data row3 col11\" >242.653</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row3_col12\" class=\"data row3 col12\" >4</td> \n </tr> <tr> \n <th id=\"T_80d08110_2698_11e8_ab6b_002683143c82level0_row4\" class=\"row_heading level0 row4\" >222</th> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row4_col0\" class=\"data row4 col0\" >AMLP-00222</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row4_col1\" class=\"data row4 col1\" >Short</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row4_col2\" class=\"data row4 col2\" >1.19414</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row4_col3\" class=\"data row4 col3\" >0.846204</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row4_col4\" class=\"data row4 col4\" >0.789453</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row4_col5\" class=\"data row4 col5\" >1.50983</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row4_col6\" class=\"data row4 col6\" >2.47584</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row4_col7\" class=\"data row4 col7\" >14.3695</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row4_col8\" class=\"data row4 col8\" >41.7641</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row4_col9\" class=\"data row4 col9\" >20.462</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row4_col10\" class=\"data row4 col10\" >39.3443</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row4_col11\" class=\"data row4 col11\" >236.18</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row4_col12\" class=\"data row4 col12\" >5</td> \n </tr> <tr> \n <th id=\"T_80d08110_2698_11e8_ab6b_002683143c82level0_row5\" class=\"row_heading level0 row5\" >378</th> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row5_col0\" class=\"data row5 col0\" >AMLP-00378</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row5_col1\" class=\"data row5 col1\" >Short</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row5_col2\" class=\"data row5 col2\" >0.834929</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row5_col3\" class=\"data row5 col3\" >1.26233</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row5_col4\" class=\"data row5 col4\" >0.754882</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row5_col5\" class=\"data row5 col5\" >0.866047</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row5_col6\" class=\"data row5 col6\" >1.0889</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row5_col7\" class=\"data row5 col7\" >8.79765</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row5_col8\" class=\"data row5 col8\" >11.3709</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row5_col9\" class=\"data row5 col9\" >18.8119</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row5_col10\" class=\"data row5 col10\" >7.21311</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row5_col11\" class=\"data row5 col11\" >224.78</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row5_col12\" class=\"data row5 col12\" >6</td> \n </tr> <tr> \n <th id=\"T_80d08110_2698_11e8_ab6b_002683143c82level0_row6\" class=\"row_heading level0 row6\" >430</th> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row6_col0\" class=\"data row6 col0\" >AMLP-00430</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row6_col1\" class=\"data row6 col1\" >Short</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row6_col2\" class=\"data row6 col2\" >0.973192</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row6_col3\" class=\"data row6 col3\" >0.526758</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row6_col4\" class=\"data row6 col4\" >0.805348</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row6_col5\" class=\"data row6 col5\" >1.15563</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row6_col6\" class=\"data row6 col6\" >1.8474</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row6_col7\" class=\"data row6 col7\" >3.51906</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row6_col8\" class=\"data row6 col8\" >24.3358</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row6_col9\" class=\"data row6 col9\" >30.033</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row6_col10\" class=\"data row6 col10\" >43.9344</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row6_col11\" class=\"data row6 col11\" >217.405</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row6_col12\" class=\"data row6 col12\" >7</td> \n </tr> <tr> \n <th id=\"T_80d08110_2698_11e8_ab6b_002683143c82level0_row7\" class=\"row_heading level0 row7\" >299</th> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row7_col0\" class=\"data row7 col0\" >AMLP-00299</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row7_col1\" class=\"data row7 col1\" >Short</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row7_col2\" class=\"data row7 col2\" >0.92645</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row7_col3\" class=\"data row7 col3\" >1.15068</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row7_col4\" class=\"data row7 col4\" >0.71865</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row7_col5\" class=\"data row7 col5\" >1.41257</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row7_col6\" class=\"data row7 col6\" >1.04961</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row7_col7\" class=\"data row7 col7\" >9.67742</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row7_col8\" class=\"data row7 col8\" >10.2019</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row7_col9\" class=\"data row7 col9\" >6.27063</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row7_col10\" class=\"data row7 col10\" >5.57377</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row7_col11\" class=\"data row7 col11\" >216.144</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row7_col12\" class=\"data row7 col12\" >8</td> \n </tr> <tr> \n <th id=\"T_80d08110_2698_11e8_ab6b_002683143c82level0_row8\" class=\"row_heading level0 row8\" >593</th> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row8_col0\" class=\"data row8 col0\" >AMLP-00593</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row8_col1\" class=\"data row8 col1\" >Short</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row8_col2\" class=\"data row8 col2\" >1.24594</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row8_col3\" class=\"data row8 col3\" >1.38126</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row8_col4\" class=\"data row8 col4\" >1.21113</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row8_col5\" class=\"data row8 col5\" >1.69598</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row8_col6\" class=\"data row8 col6\" >0.980526</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row8_col7\" class=\"data row8 col7\" >3.51906</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row8_col8\" class=\"data row8 col8\" >9.77683</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row8_col9\" class=\"data row8 col9\" >6.60066</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row8_col10\" class=\"data row8 col10\" >7.21311</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row8_col11\" class=\"data row8 col11\" >207.578</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row8_col12\" class=\"data row8 col12\" >9</td> \n </tr> <tr> \n <th id=\"T_80d08110_2698_11e8_ab6b_002683143c82level0_row9\" class=\"row_heading level0 row9\" >389</th> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row9_col0\" class=\"data row9 col0\" >AMLP-00389</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row9_col1\" class=\"data row9 col1\" >Short</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row9_col2\" class=\"data row9 col2\" >0.772885</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row9_col3\" class=\"data row9 col3\" >0.993081</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row9_col4\" class=\"data row9 col4\" >0.597508</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row9_col5\" class=\"data row9 col5\" >0.954034</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row9_col6\" class=\"data row9 col6\" >1.06669</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row9_col7\" class=\"data row9 col7\" >2.05279</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row9_col8\" class=\"data row9 col8\" >15.9405</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row9_col9\" class=\"data row9 col9\" >11.8812</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row9_col10\" class=\"data row9 col10\" >16.0656</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row9_col11\" class=\"data row9 col11\" >204.464</td> \n <td id=\"T_80d08110_2698_11e8_ab6b_002683143c82row9_col12\" class=\"data row9 col12\" >10</td> \n </tr></tbody> \n</table> ",
  328. "text/plain": "<pandas.io.formats.style.Styler at 0x288d1c91dd8>"
  329. },
  330. "metadata": {},
  331. "output_type": "display_data"
  332. }
  333. ]
  334. },
  335. {
  336. "metadata": {
  337. "trusted": true
  338. },
  339. "cell_type": "code",
  340. "source": "# This compares the longs/shorts in top list during DLPAL and Outer Period\nsame_long = [x for x in np.intersect1d(long_indices_dlpal_period,long_indices_outer_period)]\nlong_remove=[x for x in rank_long_dlpal_period.index if x not in rank_short_dlpal_period.index]\nsame_short = [x for x in np.intersect1d(short_indices_dlpal_period,short_indices_outer_period)]\nshort_remove=[x for x in rank_short_dlpal_period.index if x not in rank_short_outer_period.index]\nprint(\"=========================================================================================================\")\nprint(\"Long Rules :\",long_indices_dlpal_period,\"\\n\",len(same_long), \" out of \",top_long, \" are in both list: \",\n \"same_long = \",same_long)\nprint(\"List of indices that are in DLPAL top list but not in Outer top list: \\n\", \"long_remove = \",\n long_remove,\"\\n [Consider Removing for inconsistency]\")\nprint(\"=========================================================================================================\")\nprint(\"Short Rules :\",short_indices_dlpal_period,\"\\n\",len(same_short), \" out of \",top_short, \" are in both list \",\n \"same_short = \",same_short)\nprint(\"List of indices that are in DLPAL top list but not in Outer top list: \\n\", \"short_remove = \",\n short_remove,\"\\n [Consider Removing for inconsistency]\")\nprint(\"=========================================================================================================\")\n",
  341. "execution_count": 104,
  342. "outputs": [
  343. {
  344. "name": "stdout",
  345. "output_type": "stream",
  346. "text": "=========================================================================================================\nLong Rules : [167, 116, 136, 102, 117, 181, 176, 68, 7, 180] \n 5 out of 10 are in both list: same_long = [102, 116, 136, 167, 180]\nList of indices that are in DLPAL top list but not in Outer top list: \n long_remove = [167, 116, 136, 102, 117, 181, 176, 68, 7, 180] \n [Consider Removing for inconsistency]\n=========================================================================================================\nShort Rules : [308, 225, 400, 309, 593, 572, 219, 217, 239, 315, 238, 293, 234, 208, 437, 388, 601, 361, 377, 245] \n 1 out of 20 are in both list same_short = [593]\nList of indices that are in DLPAL top list but not in Outer top list: \n short_remove = [308, 225, 400, 309, 572, 219, 217, 239, 315, 238, 293, 234, 208, 437, 388, 601, 361, 377, 245] \n [Consider Removing for inconsistency]\n=========================================================================================================\n"
  347. }
  348. ]
  349. },
  350. {
  351. "metadata": {},
  352. "cell_type": "markdown",
  353. "source": "# Manual Filtration [Try Reduce to less than 20 Rules for Multisignal]\n- Copy the indices above and paste it below\n- Drop the rules that you don't want\n- keep the number of rules low (<10), so that we can check the sharpe for each of the combination\n- chosen rule = n ===> combinations (excluding singleton) = 2^n -(n+1)"
  354. },
  355. {
  356. "metadata": {
  357. "trusted": true
  358. },
  359. "cell_type": "code",
  360. "source": "# Edit\n\n# Manual copy/paste/editing\n# chosen = [167,593,225]\n\n# if you want intersection of the coincide lists of longs/shorts:\nchosen = list_IS+same_long\n\n#======================================= No Need to Edit ========================================================\nfinal = ranking_df.loc[chosen]\n\nwith pd.option_context('display.max_rows', None, 'display.max_columns', None):\n display(final[['Name','Direction','Sharpe','SharpeOOS2','SharpeIS','SharpeOOS1','SharpeOOS3',\n 'OOS2 NonflatPCT','IS NonflatPCT', 'OOS1 NonflatPCT','OOS3 NonflatPCT',\n 'Score','Rank']].sort_values(by = 'Rank')\n .style.apply(highlight_max, subset = ['Sharpe','SharpeOOS2','SharpeIS','SharpeOOS1','SharpeOOS3',\n 'OOS2 NonflatPCT','IS NonflatPCT', 'OOS1 NonflatPCT','OOS3 NonflatPCT',\n 'Score']))\n\nchosen = [i for i in final.index]\nprint(\"Chosen Rules are chosen =: \",chosen)\nprint(\"Total Rules in chosen : \",len(chosen))\n#================================================================================================================",
  361. "execution_count": 122,
  362. "outputs": [
  363. {
  364. "data": {
  365. "text/html": "<style type=\"text/css\" >\n #T_fa1bbd94_269a_11e8_8e49_002683143c82row0_col11 {\n background-color: lightgreen;\n } #T_fa1bbd94_269a_11e8_8e49_002683143c82row2_col2 {\n background-color: lightgreen;\n } #T_fa1bbd94_269a_11e8_8e49_002683143c82row2_col5 {\n background-color: lightgreen;\n } #T_fa1bbd94_269a_11e8_8e49_002683143c82row6_col6 {\n background-color: lightgreen;\n } #T_fa1bbd94_269a_11e8_8e49_002683143c82row6_col7 {\n background-color: lightgreen;\n } #T_fa1bbd94_269a_11e8_8e49_002683143c82row6_col8 {\n background-color: lightgreen;\n } #T_fa1bbd94_269a_11e8_8e49_002683143c82row6_col9 {\n background-color: lightgreen;\n } #T_fa1bbd94_269a_11e8_8e49_002683143c82row6_col10 {\n background-color: lightgreen;\n } #T_fa1bbd94_269a_11e8_8e49_002683143c82row10_col4 {\n background-color: lightgreen;\n } #T_fa1bbd94_269a_11e8_8e49_002683143c82row11_col3 {\n background-color: lightgreen;\n }</style> \n<table id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82\" > \n<thead> <tr> \n <th class=\"blank level0\" ></th> \n <th class=\"col_heading level0 col0\" >Name</th> \n <th class=\"col_heading level0 col1\" >Direction</th> \n <th class=\"col_heading level0 col2\" >Sharpe</th> \n <th class=\"col_heading level0 col3\" >SharpeOOS2</th> \n <th class=\"col_heading level0 col4\" >SharpeIS</th> \n <th class=\"col_heading level0 col5\" >SharpeOOS1</th> \n <th class=\"col_heading level0 col6\" >SharpeOOS3</th> \n <th class=\"col_heading level0 col7\" >OOS2 NonflatPCT</th> \n <th class=\"col_heading level0 col8\" >IS NonflatPCT</th> \n <th class=\"col_heading level0 col9\" >OOS1 NonflatPCT</th> \n <th class=\"col_heading level0 col10\" >OOS3 NonflatPCT</th> \n <th class=\"col_heading level0 col11\" >Score</th> \n <th class=\"col_heading level0 col12\" >Rank</th> \n </tr></thead> \n<tbody> <tr> \n <th id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82level0_row0\" class=\"row_heading level0 row0\" >308</th> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row0_col0\" class=\"data row0 col0\" >AMLP-00308</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row0_col1\" class=\"data row0 col1\" >Short</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row0_col2\" class=\"data row0 col2\" >1.06911</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row0_col3\" class=\"data row0 col3\" >-0.0979969</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row0_col4\" class=\"data row0 col4\" >1.46855</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row0_col5\" class=\"data row0 col5\" >1.39443</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row0_col6\" class=\"data row0 col6\" >0.855515</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row0_col7\" class=\"data row0 col7\" >49.5601</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row0_col8\" class=\"data row0 col8\" >42.7205</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row0_col9\" class=\"data row0 col9\" >27.0627</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row0_col10\" class=\"data row0 col10\" >37.0492</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row0_col11\" class=\"data row0 col11\" >274.816</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row0_col12\" class=\"data row0 col12\" >1</td> \n </tr> <tr> \n <th id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82level0_row1\" class=\"row_heading level0 row1\" >225</th> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row1_col0\" class=\"data row1 col0\" >AMLP-00225</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row1_col1\" class=\"data row1 col1\" >Short</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row1_col2\" class=\"data row1 col2\" >1.05564</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row1_col3\" class=\"data row1 col3\" >-1.66068</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row1_col4\" class=\"data row1 col4\" >1.41899</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row1_col5\" class=\"data row1 col5\" >1.99355</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row1_col6\" class=\"data row1 col6\" >1.2018</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row1_col7\" class=\"data row1 col7\" >26.9795</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row1_col8\" class=\"data row1 col8\" >25.5048</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row1_col9\" class=\"data row1 col9\" >10.231</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row1_col10\" class=\"data row1 col10\" >31.4754</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row1_col11\" class=\"data row1 col11\" >270.215</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row1_col12\" class=\"data row1 col12\" >2</td> \n </tr> <tr> \n <th id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82level0_row2\" class=\"row_heading level0 row2\" >400</th> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row2_col0\" class=\"data row2 col0\" >AMLP-00400</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row2_col1\" class=\"data row2 col1\" >Short</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row2_col2\" class=\"data row2 col2\" >1.29844</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row2_col3\" class=\"data row2 col3\" >0.00571472</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row2_col4\" class=\"data row2 col4\" >1.36003</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row2_col5\" class=\"data row2 col5\" >2.24782</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row2_col6\" class=\"data row2 col6\" >1.3035</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row2_col7\" class=\"data row2 col7\" >51.9062</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row2_col8\" class=\"data row2 col8\" >60.0425</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row2_col9\" class=\"data row2 col9\" >47.5248</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row2_col10\" class=\"data row2 col10\" >60</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row2_col11\" class=\"data row2 col11\" >262.999</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row2_col12\" class=\"data row2 col12\" >3</td> \n </tr> <tr> \n <th id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82level0_row3\" class=\"row_heading level0 row3\" >309</th> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row3_col0\" class=\"data row3 col0\" >AMLP-00309</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row3_col1\" class=\"data row3 col1\" >Short</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row3_col2\" class=\"data row3 col2\" >0.936359</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row3_col3\" class=\"data row3 col3\" >-0.94381</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row3_col4\" class=\"data row3 col4\" >1.6667</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row3_col5\" class=\"data row3 col5\" >1.21351</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row3_col6\" class=\"data row3 col6\" >0.336139</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row3_col7\" class=\"data row3 col7\" >47.2141</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row3_col8\" class=\"data row3 col8\" >43.3581</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row3_col9\" class=\"data row3 col9\" >35.9736</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row3_col10\" class=\"data row3 col10\" >37.0492</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row3_col11\" class=\"data row3 col11\" >256.258</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row3_col12\" class=\"data row3 col12\" >4</td> \n </tr> <tr> \n <th id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82level0_row4\" class=\"row_heading level0 row4\" >593</th> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row4_col0\" class=\"data row4 col0\" >AMLP-00593</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row4_col1\" class=\"data row4 col1\" >Short</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row4_col2\" class=\"data row4 col2\" >1.24594</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row4_col3\" class=\"data row4 col3\" >1.38126</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row4_col4\" class=\"data row4 col4\" >1.21113</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row4_col5\" class=\"data row4 col5\" >1.69598</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row4_col6\" class=\"data row4 col6\" >0.980526</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row4_col7\" class=\"data row4 col7\" >3.51906</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row4_col8\" class=\"data row4 col8\" >9.77683</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row4_col9\" class=\"data row4 col9\" >6.60066</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row4_col10\" class=\"data row4 col10\" >7.21311</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row4_col11\" class=\"data row4 col11\" >238.206</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row4_col12\" class=\"data row4 col12\" >5</td> \n </tr> <tr> \n <th id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82level0_row5\" class=\"row_heading level0 row5\" >572</th> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row5_col0\" class=\"data row5 col0\" >AMLP-00572</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row5_col1\" class=\"data row5 col1\" >Short</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row5_col2\" class=\"data row5 col2\" >0.787532</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row5_col3\" class=\"data row5 col3\" >-0.879235</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row5_col4\" class=\"data row5 col4\" >1.19308</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row5_col5\" class=\"data row5 col5\" >1.34484</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row5_col6\" class=\"data row5 col6\" >-0.0838823</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row5_col7\" class=\"data row5 col7\" >23.1672</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row5_col8\" class=\"data row5 col8\" >34.644</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row5_col9\" class=\"data row5 col9\" >16.1716</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row5_col10\" class=\"data row5 col10\" >9.83607</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row5_col11\" class=\"data row5 col11\" >236.724</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row5_col12\" class=\"data row5 col12\" >6</td> \n </tr> <tr> \n <th id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82level0_row6\" class=\"row_heading level0 row6\" >219</th> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row6_col0\" class=\"data row6 col0\" >AMLP-00219</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row6_col1\" class=\"data row6 col1\" >Short</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row6_col2\" class=\"data row6 col2\" >0.925657</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row6_col3\" class=\"data row6 col3\" >-0.854148</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row6_col4\" class=\"data row6 col4\" >1.17921</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row6_col5\" class=\"data row6 col5\" >1.24937</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row6_col6\" class=\"data row6 col6\" >1.47986</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row6_col7\" class=\"data row6 col7\" >60.4106</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row6_col8\" class=\"data row6 col8\" >69.7131</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row6_col9\" class=\"data row6 col9\" >52.1452</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row6_col10\" class=\"data row6 col10\" >67.8689</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row6_col11\" class=\"data row6 col11\" >231.514</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row6_col12\" class=\"data row6 col12\" >7</td> \n </tr> <tr> \n <th id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82level0_row7\" class=\"row_heading level0 row7\" >217</th> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row7_col0\" class=\"data row7 col0\" >AMLP-00217</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row7_col1\" class=\"data row7 col1\" >Short</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row7_col2\" class=\"data row7 col2\" >1.07588</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row7_col3\" class=\"data row7 col3\" >0.40379</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row7_col4\" class=\"data row7 col4\" >1.41057</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row7_col5\" class=\"data row7 col5\" >0.986359</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row7_col6\" class=\"data row7 col6\" >0.898823</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row7_col7\" class=\"data row7 col7\" >17.5953</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row7_col8\" class=\"data row7 col8\" >28.4803</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row7_col9\" class=\"data row7 col9\" >14.1914</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row7_col10\" class=\"data row7 col10\" >8.85246</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row7_col11\" class=\"data row7 col11\" >226.766</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row7_col12\" class=\"data row7 col12\" >8</td> \n </tr> <tr> \n <th id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82level0_row8\" class=\"row_heading level0 row8\" >239</th> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row8_col0\" class=\"data row8 col0\" >AMLP-00239</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row8_col1\" class=\"data row8 col1\" >Short</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row8_col2\" class=\"data row8 col2\" >0.572721</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row8_col3\" class=\"data row8 col3\" >-1.44806</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row8_col4\" class=\"data row8 col4\" >1.35224</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row8_col5\" class=\"data row8 col5\" >1.05443</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row8_col6\" class=\"data row8 col6\" >-0.342582</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row8_col7\" class=\"data row8 col7\" >44.868</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row8_col8\" class=\"data row8 col8\" >46.0149</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row8_col9\" class=\"data row8 col9\" >42.9043</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row8_col10\" class=\"data row8 col10\" >41.3115</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row8_col11\" class=\"data row8 col11\" >221.731</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row8_col12\" class=\"data row8 col12\" >9</td> \n </tr> <tr> \n <th id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82level0_row9\" class=\"row_heading level0 row9\" >315</th> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row9_col0\" class=\"data row9 col0\" >AMLP-00315</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row9_col1\" class=\"data row9 col1\" >Short</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row9_col2\" class=\"data row9 col2\" >0.71129</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row9_col3\" class=\"data row9 col3\" >-0.883046</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row9_col4\" class=\"data row9 col4\" >1.08614</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row9_col5\" class=\"data row9 col5\" >1.60983</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row9_col6\" class=\"data row9 col6\" >-0.227734</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row9_col7\" class=\"data row9 col7\" >45.7478</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row9_col8\" class=\"data row9 col8\" >57.8108</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row9_col9\" class=\"data row9 col9\" >48.8449</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row9_col10\" class=\"data row9 col10\" >43.6066</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row9_col11\" class=\"data row9 col11\" >221.406</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row9_col12\" class=\"data row9 col12\" >10</td> \n </tr> <tr> \n <th id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82level0_row10\" class=\"row_heading level0 row10\" >167</th> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row10_col0\" class=\"data row10 col0\" >AMLP-00167</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row10_col1\" class=\"data row10 col1\" >Long</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row10_col2\" class=\"data row10 col2\" >0.848278</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row10_col3\" class=\"data row10 col3\" >0.540776</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row10_col4\" class=\"data row10 col4\" >1.74023</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row10_col5\" class=\"data row10 col5\" >0.211354</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row10_col6\" class=\"data row10 col6\" >-0.103539</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row10_col7\" class=\"data row10 col7\" >2.6393</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row10_col8\" class=\"data row10 col8\" >13.0712</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row10_col9\" class=\"data row10 col9\" >2.9703</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row10_col10\" class=\"data row10 col10\" >3.93443</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row10_col11\" class=\"data row10 col11\" >170.697</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row10_col12\" class=\"data row10 col12\" >41</td> \n </tr> <tr> \n <th id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82level0_row11\" class=\"row_heading level0 row11\" >116</th> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row11_col0\" class=\"data row11 col0\" >AMLP-00116</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row11_col1\" class=\"data row11 col1\" >Long</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row11_col2\" class=\"data row11 col2\" >1.06485</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row11_col3\" class=\"data row11 col3\" >2.15526</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row11_col4\" class=\"data row11 col4\" >1.22829</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row11_col5\" class=\"data row11 col5\" >0.544062</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row11_col6\" class=\"data row11 col6\" >0.565165</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row11_col7\" class=\"data row11 col7\" >9.97067</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row11_col8\" class=\"data row11 col8\" >11.1583</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row11_col9\" class=\"data row11 col9\" >4.62046</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row11_col10\" class=\"data row11 col10\" >4.2623</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row11_col11\" class=\"data row11 col11\" >165.968</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row11_col12\" class=\"data row11 col12\" >48</td> \n </tr> <tr> \n <th id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82level0_row12\" class=\"row_heading level0 row12\" >136</th> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row12_col0\" class=\"data row12 col0\" >AMLP-00136</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row12_col1\" class=\"data row12 col1\" >Long</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row12_col2\" class=\"data row12 col2\" >0.74644</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row12_col3\" class=\"data row12 col3\" >0.91652</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row12_col4\" class=\"data row12 col4\" >0.426769</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row12_col5\" class=\"data row12 col5\" >1.78973</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row12_col6\" class=\"data row12 col6\" >0.110357</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row12_col7\" class=\"data row12 col7\" >29.6188</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row12_col8\" class=\"data row12 col8\" >13.6026</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row12_col9\" class=\"data row12 col9\" >12.8713</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row12_col10\" class=\"data row12 col10\" >11.8033</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row12_col11\" class=\"data row12 col11\" >135.566</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row12_col12\" class=\"data row12 col12\" >107</td> \n </tr> <tr> \n <th id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82level0_row13\" class=\"row_heading level0 row13\" >102</th> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row13_col0\" class=\"data row13 col0\" >AMLP-00102</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row13_col1\" class=\"data row13 col1\" >Long</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row13_col2\" class=\"data row13 col2\" >0.800721</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row13_col3\" class=\"data row13 col3\" >1.61167</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row13_col4\" class=\"data row13 col4\" >0.549812</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row13_col5\" class=\"data row13 col5\" >1.65078</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row13_col6\" class=\"data row13 col6\" >-0.21009</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row13_col7\" class=\"data row13 col7\" >2.93255</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row13_col8\" class=\"data row13 col8\" >20.1913</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row13_col9\" class=\"data row13 col9\" >9.57096</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row13_col10\" class=\"data row13 col10\" >3.27869</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row13_col11\" class=\"data row13 col11\" >130.514</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row13_col12\" class=\"data row13 col12\" >121</td> \n </tr> <tr> \n <th id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82level0_row14\" class=\"row_heading level0 row14\" >180</th> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row14_col0\" class=\"data row14 col0\" >AMLP-00180</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row14_col1\" class=\"data row14 col1\" >Long</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row14_col2\" class=\"data row14 col2\" >0.354959</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row14_col3\" class=\"data row14 col3\" >0.24949</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row14_col4\" class=\"data row14 col4\" >0.41752</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row14_col5\" class=\"data row14 col5\" >0.749201</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row14_col6\" class=\"data row14 col6\" >-0.52751</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row14_col7\" class=\"data row14 col7\" >17.3021</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row14_col8\" class=\"data row14 col8\" >14.0276</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row14_col9\" class=\"data row14 col9\" >11.8812</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row14_col10\" class=\"data row14 col10\" >1.96721</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row14_col11\" class=\"data row14 col11\" >99.3015</td> \n <td id=\"T_fa1bbd94_269a_11e8_8e49_002683143c82row14_col12\" class=\"data row14 col12\" >188</td> \n </tr></tbody> \n</table> ",
  366. "text/plain": "<pandas.io.formats.style.Styler at 0x288d1723400>"
  367. },
  368. "metadata": {},
  369. "output_type": "display_data"
  370. },
  371. {
  372. "name": "stdout",
  373. "output_type": "stream",
  374. "text": "Chosen Rules are chosen =: [308, 225, 400, 309, 593, 572, 219, 217, 239, 315, 102, 116, 136, 167, 180]\nTotal Rules in chosen : 15\n"
  375. }
  376. ]
  377. },
  378. {
  379. "metadata": {},
  380. "cell_type": "markdown",
  381. "source": "# Final Final Filter: Correlation Threshold\nIf correlation of 2 rules exceed a certain threshold, compare the rank of them, remove the lower ranked rule."
  382. },
  383. {
  384. "metadata": {
  385. "collapsed": true,
  386. "trusted": true
  387. },
  388. "cell_type": "code",
  389. "source": "#=======================================Import Benchmark==========================================================\nt0=time.time()\ndf_bench = DoImportBenchmark('BenchmarkReturns.csv', 'SPY', '1/1/1990', '3/1/2018',Output=[False, True])\ndisplay(df_bench.head())\nt1=time.time()\nprint('Time for Benchmark Import: ', t1-t0)\n\n#==========================Combine the chosen rules and check correlation=========================================\nt0=time.time()\ndf_combine_chosen, metric_dict_chosen = DoCombine([df_list[i] for i in chosen],df_bench, np.ones(len(chosen)) , 1, OOS_Date = OOS_date, Start_Date = start_date, End_Date = end_date,Opti=False,Metrics=False)\nt1=time.time()\nprint('Time for DoCombine calculation: ', t1-t0)\n",
  390. "execution_count": null,
  391. "outputs": []
  392. },
  393. {
  394. "metadata": {
  395. "trusted": true
  396. },
  397. "cell_type": "code",
  398. "source": "# Edit\ncross_corr_threshold = 0.5\n\n#=================================Correlation Matrix Cleaning=====================================================\ncorr_chosen = DoCorrMatrix(df_combine_chosen)\n\ncorr_copy = corr_chosen.drop(['Combined Return','Benchmark Returns'],axis=1) #drop columns\ncorr_copy = corr_copy.drop(['Combined Return','Benchmark Returns']).values #drop rows and conver to ndarray\n# display(corr_copy)\n\ncorr_mat = pd.DataFrame(data=corr_copy,index = chosen,columns = chosen)\n\ncorr_mat_display = corr_mat.copy()\ncorr_mat_display.columns = [str(i)+\"_\"+final.loc[i]['Direction'][0] for i in chosen]\ncorr_mat_display.index = [str(i)+\"_\"+final.loc[i]['Direction'][0] for i in chosen]\nwith pd.option_context('display.max_rows', None, 'display.max_columns', None):\n display(corr_mat_display)\n\nto_remove = []\nprint(\"========================================================================================\")\nfor rule1 in chosen:\n for rule2 in chosen:\n if abs(corr_mat[rule1][rule2])>cross_corr_threshold and corr_mat[rule1][rule2]!=1:\n \n if chosen.index(rule2)>chosen.index(rule1):\n to_remove.append(rule2)\n print(\"Corr \",rule1,\"(Index =\",chosen.index(rule1),\") and \", rule2,\"(Index = \",\n chosen.index(rule2),\") Corr = \", corr_mat[rule1][rule2],\" [Remove \",rule2,\"]\")\nprint(\"========================================================================================\")\nprint(\"Rules to Be Removed: \",to_remove)\n\n\n\nchosen = [x for x in chosen if x not in to_remove]\nprint(\"Final Chosen Rules are chosen = \",[str(i)+\"_\"+final.loc[i]['Direction'][0] for i in chosen])\n\n\nprint(\"========================================================================================\")\nwith pd.option_context('display.max_rows', None, 'display.max_columns', None):\n display(ranking_df.loc[chosen][['Name','Direction','Sharpe','SharpeOOS2','SharpeIS','SharpeOOS1','SharpeOOS3',\n 'OOS2 NonflatPCT','IS NonflatPCT', 'OOS1 NonflatPCT','OOS3 NonflatPCT',\n 'Score','Rank']].sort_values(by = 'Rank')\n .style.apply(highlight_max, subset = ['Sharpe','SharpeOOS2','SharpeIS','SharpeOOS1','SharpeOOS3',\n 'OOS2 NonflatPCT','IS NonflatPCT', 'OOS1 NonflatPCT','OOS3 NonflatPCT',\n 'Score']))\n\nnum_long=0\nnum_short=0\nfor i in chosen:\n if final.loc[i]['Direction'][0]=='L':\n num_long=num_long+1\n elif final.loc[i]['Direction'][0]=='S':\n num_short=num_short+1\nprint(\"Total Rules in chosen : \",len(chosen))\nprint(\"Long Rules: \",num_long,\" , Short Rules: \",num_short)",
  399. "execution_count": 123,
  400. "outputs": [
  401. {
  402. "data": {
  403. "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Date</th>\n <th>SPY</th>\n <th>CumuRet</th>\n <th>Drawdown</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>1990-01-03</td>\n <td>0.0</td>\n <td>0.0</td>\n <td>0.0</td>\n </tr>\n <tr>\n <th>1</th>\n <td>1990-01-04</td>\n <td>0.0</td>\n <td>0.0</td>\n <td>0.0</td>\n </tr>\n <tr>\n <th>2</th>\n <td>1990-01-05</td>\n <td>0.0</td>\n <td>0.0</td>\n <td>0.0</td>\n </tr>\n <tr>\n <th>3</th>\n <td>1990-01-08</td>\n <td>0.0</td>\n <td>0.0</td>\n <td>0.0</td>\n </tr>\n <tr>\n <th>4</th>\n <td>1990-01-09</td>\n <td>0.0</td>\n <td>0.0</td>\n <td>0.0</td>\n </tr>\n </tbody>\n</table>\n</div>",
  404. "text/plain": " Date SPY CumuRet Drawdown\n0 1990-01-03 0.0 0.0 0.0\n1 1990-01-04 0.0 0.0 0.0\n2 1990-01-05 0.0 0.0 0.0\n3 1990-01-08 0.0 0.0 0.0\n4 1990-01-09 0.0 0.0 0.0"
  405. },
  406. "metadata": {},
  407. "output_type": "display_data"
  408. },
  409. {
  410. "name": "stdout",
  411. "output_type": "stream",
  412. "text": "Time for Benchmark Import: 18.047520637512207\nTime for DoCombine calculation: 63.68720769882202\n"
  413. },
  414. {
  415. "data": {
  416. "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>308_S</th>\n <th>225_S</th>\n <th>400_S</th>\n <th>309_S</th>\n <th>593_S</th>\n <th>572_S</th>\n <th>219_S</th>\n <th>217_S</th>\n <th>239_S</th>\n <th>315_S</th>\n <th>102_L</th>\n <th>116_L</th>\n <th>136_L</th>\n <th>167_L</th>\n <th>180_L</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>308_S</th>\n <td>1.000000</td>\n <td>0.267735</td>\n <td>0.299823</td>\n <td>0.897567</td>\n <td>0.225816</td>\n <td>0.257763</td>\n <td>0.407094</td>\n <td>0.293781</td>\n <td>0.218422</td>\n <td>0.337018</td>\n <td>-0.141843</td>\n <td>-0.081885</td>\n <td>-0.118087</td>\n <td>-0.059871</td>\n <td>-0.149151</td>\n </tr>\n <tr>\n <th>225_S</th>\n <td>0.267735</td>\n <td>1.000000</td>\n <td>0.290214</td>\n <td>0.267196</td>\n <td>0.188555</td>\n <td>0.258819</td>\n <td>0.444873</td>\n <td>0.425105</td>\n <td>0.386754</td>\n <td>0.295560</td>\n <td>-0.152056</td>\n <td>-0.118801</td>\n <td>-0.133723</td>\n <td>-0.090817</td>\n <td>-0.041008</td>\n </tr>\n <tr>\n <th>400_S</th>\n <td>0.299823</td>\n <td>0.290214</td>\n <td>1.000000</td>\n <td>0.328346</td>\n <td>0.132780</td>\n <td>0.289773</td>\n <td>0.423755</td>\n <td>0.303202</td>\n <td>0.435471</td>\n <td>0.448725</td>\n <td>-0.224446</td>\n <td>-0.209175</td>\n <td>-0.195597</td>\n <td>-0.162405</td>\n <td>-0.159151</td>\n </tr>\n <tr>\n <th>309_S</th>\n <td>0.897567</td>\n <td>0.267196</td>\n <td>0.328346</td>\n <td>1.000000</td>\n <td>0.253456</td>\n <td>0.276563</td>\n <td>0.441494</td>\n <td>0.307497</td>\n <td>0.239615</td>\n <td>0.353589</td>\n <td>-0.137033</td>\n <td>-0.088426</td>\n <td>-0.162929</td>\n <td>-0.025463</td>\n <td>-0.180867</td>\n </tr>\n <tr>\n <th>593_S</th>\n <td>0.225816</td>\n <td>0.188555</td>\n <td>0.132780</td>\n <td>0.253456</td>\n <td>1.000000</td>\n <td>0.131378</td>\n <td>0.419870</td>\n <td>0.198588</td>\n <td>0.160496</td>\n <td>0.139231</td>\n <td>-0.075380</td>\n <td>-0.040566</td>\n <td>-0.117782</td>\n <td>-0.005188</td>\n <td>-0.080293</td>\n </tr>\n <tr>\n <th>572_S</th>\n <td>0.257763</td>\n <td>0.258819</td>\n <td>0.289773</td>\n <td>0.276563</td>\n <td>0.131378</td>\n <td>1.000000</td>\n <td>0.323389</td>\n <td>0.207476</td>\n <td>0.370065</td>\n <td>0.415199</td>\n <td>-0.199249</td>\n <td>-0.089447</td>\n <td>-0.168461</td>\n <td>-0.131845</td>\n <td>-0.247725</td>\n </tr>\n <tr>\n <th>219_S</th>\n <td>0.407094</td>\n <td>0.444873</td>\n <td>0.423755</td>\n <td>0.441494</td>\n <td>0.419870</td>\n <td>0.323389</td>\n <td>1.000000</td>\n <td>0.475290</td>\n <td>0.415926</td>\n <td>0.441697</td>\n <td>-0.336145</td>\n <td>-0.131257</td>\n <td>-0.219401</td>\n <td>-0.094161</td>\n <td>-0.183254</td>\n </tr>\n <tr>\n <th>217_S</th>\n <td>0.293781</td>\n <td>0.425105</td>\n <td>0.303202</td>\n <td>0.307497</td>\n <td>0.198588</td>\n <td>0.207476</td>\n <td>0.475290</td>\n <td>1.000000</td>\n <td>0.263553</td>\n <td>0.315807</td>\n <td>-0.208161</td>\n <td>-0.085742</td>\n <td>-0.156201</td>\n <td>-0.105520</td>\n <td>-0.116900</td>\n </tr>\n <tr>\n <th>239_S</th>\n <td>0.218422</td>\n <td>0.386754</td>\n <td>0.435471</td>\n <td>0.239615</td>\n <td>0.160496</td>\n <td>0.370065</td>\n <td>0.415926</td>\n <td>0.263553</td>\n <td>1.000000</td>\n <td>0.704866</td>\n <td>-0.135854</td>\n <td>-0.154207</td>\n <td>-0.202654</td>\n <td>-0.139016</td>\n <td>-0.113611</td>\n </tr>\n <tr>\n <th>315_S</th>\n <td>0.337018</td>\n <td>0.295560</td>\n <td>0.448725</td>\n <td>0.353589</td>\n <td>0.139231</td>\n <td>0.415199</td>\n <td>0.441697</td>\n <td>0.315807</td>\n <td>0.704866</td>\n <td>1.000000</td>\n <td>-0.197577</td>\n <td>-0.214212</td>\n <td>-0.207958</td>\n <td>-0.161237</td>\n <td>-0.169146</td>\n </tr>\n <tr>\n <th>102_L</th>\n <td>-0.141843</td>\n <td>-0.152056</td>\n <td>-0.224446</td>\n <td>-0.137033</td>\n <td>-0.075380</td>\n <td>-0.199249</td>\n <td>-0.336145</td>\n <td>-0.208161</td>\n <td>-0.135854</td>\n <td>-0.197577</td>\n <td>1.000000</td>\n <td>0.184881</td>\n <td>0.125566</td>\n <td>0.075000</td>\n <td>0.162561</td>\n </tr>\n <tr>\n <th>116_L</th>\n <td>-0.081885</td>\n <td>-0.118801</td>\n <td>-0.209175</td>\n <td>-0.088426</td>\n <td>-0.040566</td>\n <td>-0.089447</td>\n <td>-0.131257</td>\n <td>-0.085742</td>\n <td>-0.154207</td>\n <td>-0.214212</td>\n <td>0.184881</td>\n <td>1.000000</td>\n <td>0.190304</td>\n <td>0.030145</td>\n <td>0.037742</td>\n </tr>\n <tr>\n <th>136_L</th>\n <td>-0.118087</td>\n <td>-0.133723</td>\n <td>-0.195597</td>\n <td>-0.162929</td>\n <td>-0.117782</td>\n <td>-0.168461</td>\n <td>-0.219401</td>\n <td>-0.156201</td>\n <td>-0.202654</td>\n <td>-0.207958</td>\n <td>0.125566</td>\n <td>0.190304</td>\n <td>1.000000</td>\n <td>0.033851</td>\n <td>0.212233</td>\n </tr>\n <tr>\n <th>167_L</th>\n <td>-0.059871</td>\n <td>-0.090817</td>\n <td>-0.162405</td>\n <td>-0.025463</td>\n <td>-0.005188</td>\n <td>-0.131845</td>\n <td>-0.094161</td>\n <td>-0.105520</td>\n <td>-0.139016</td>\n <td>-0.161237</td>\n <td>0.075000</td>\n <td>0.030145</td>\n <td>0.033851</td>\n <td>1.000000</td>\n <td>0.054146</td>\n </tr>\n <tr>\n <th>180_L</th>\n <td>-0.149151</td>\n <td>-0.041008</td>\n <td>-0.159151</td>\n <td>-0.180867</td>\n <td>-0.080293</td>\n <td>-0.247725</td>\n <td>-0.183254</td>\n <td>-0.116900</td>\n <td>-0.113611</td>\n <td>-0.169146</td>\n <td>0.162561</td>\n <td>0.037742</td>\n <td>0.212233</td>\n <td>0.054146</td>\n <td>1.000000</td>\n </tr>\n </tbody>\n</table>\n</div>",
  417. "text/plain": " 308_S 225_S 400_S 309_S 593_S 572_S 219_S \\\n308_S 1.000000 0.267735 0.299823 0.897567 0.225816 0.257763 0.407094 \n225_S 0.267735 1.000000 0.290214 0.267196 0.188555 0.258819 0.444873 \n400_S 0.299823 0.290214 1.000000 0.328346 0.132780 0.289773 0.423755 \n309_S 0.897567 0.267196 0.328346 1.000000 0.253456 0.276563 0.441494 \n593_S 0.225816 0.188555 0.132780 0.253456 1.000000 0.131378 0.419870 \n572_S 0.257763 0.258819 0.289773 0.276563 0.131378 1.000000 0.323389 \n219_S 0.407094 0.444873 0.423755 0.441494 0.419870 0.323389 1.000000 \n217_S 0.293781 0.425105 0.303202 0.307497 0.198588 0.207476 0.475290 \n239_S 0.218422 0.386754 0.435471 0.239615 0.160496 0.370065 0.415926 \n315_S 0.337018 0.295560 0.448725 0.353589 0.139231 0.415199 0.441697 \n102_L -0.141843 -0.152056 -0.224446 -0.137033 -0.075380 -0.199249 -0.336145 \n116_L -0.081885 -0.118801 -0.209175 -0.088426 -0.040566 -0.089447 -0.131257 \n136_L -0.118087 -0.133723 -0.195597 -0.162929 -0.117782 -0.168461 -0.219401 \n167_L -0.059871 -0.090817 -0.162405 -0.025463 -0.005188 -0.131845 -0.094161 \n180_L -0.149151 -0.041008 -0.159151 -0.180867 -0.080293 -0.247725 -0.183254 \n\n 217_S 239_S 315_S 102_L 116_L 136_L 167_L \\\n308_S 0.293781 0.218422 0.337018 -0.141843 -0.081885 -0.118087 -0.059871 \n225_S 0.425105 0.386754 0.295560 -0.152056 -0.118801 -0.133723 -0.090817 \n400_S 0.303202 0.435471 0.448725 -0.224446 -0.209175 -0.195597 -0.162405 \n309_S 0.307497 0.239615 0.353589 -0.137033 -0.088426 -0.162929 -0.025463 \n593_S 0.198588 0.160496 0.139231 -0.075380 -0.040566 -0.117782 -0.005188 \n572_S 0.207476 0.370065 0.415199 -0.199249 -0.089447 -0.168461 -0.131845 \n219_S 0.475290 0.415926 0.441697 -0.336145 -0.131257 -0.219401 -0.094161 \n217_S 1.000000 0.263553 0.315807 -0.208161 -0.085742 -0.156201 -0.105520 \n239_S 0.263553 1.000000 0.704866 -0.135854 -0.154207 -0.202654 -0.139016 \n315_S 0.315807 0.704866 1.000000 -0.197577 -0.214212 -0.207958 -0.161237 \n102_L -0.208161 -0.135854 -0.197577 1.000000 0.184881 0.125566 0.075000 \n116_L -0.085742 -0.154207 -0.214212 0.184881 1.000000 0.190304 0.030145 \n136_L -0.156201 -0.202654 -0.207958 0.125566 0.190304 1.000000 0.033851 \n167_L -0.105520 -0.139016 -0.161237 0.075000 0.030145 0.033851 1.000000 \n180_L -0.116900 -0.113611 -0.169146 0.162561 0.037742 0.212233 0.054146 \n\n 180_L \n308_S -0.149151 \n225_S -0.041008 \n400_S -0.159151 \n309_S -0.180867 \n593_S -0.080293 \n572_S -0.247725 \n219_S -0.183254 \n217_S -0.116900 \n239_S -0.113611 \n315_S -0.169146 \n102_L 0.162561 \n116_L 0.037742 \n136_L 0.212233 \n167_L 0.054146 \n180_L 1.000000 "
  418. },
  419. "metadata": {},
  420. "output_type": "display_data"
  421. },
  422. {
  423. "name": "stdout",
  424. "output_type": "stream",
  425. "text": "========================================================================================\nCorr 308 (Index = 0 ) and 309 (Index = 3 ) Corr = 0.8975666207439275 [Remove 309 ]\nCorr 239 (Index = 8 ) and 315 (Index = 9 ) Corr = 0.7048657658110283 [Remove 315 ]\n========================================================================================\nRules to Be Removed: [309, 315]\nFinal Chosen Rules are chosen = ['308_S', '225_S', '400_S', '593_S', '572_S', '219_S', '217_S', '239_S', '102_L', '116_L', '136_L', '167_L', '180_L']\n========================================================================================\n"
  426. },
  427. {
  428. "data": {
  429. "text/html": "<style type=\"text/css\" >\n #T_2ddfb0d8_269b_11e8_89ce_002683143c82row0_col11 {\n background-color: lightgreen;\n } #T_2ddfb0d8_269b_11e8_89ce_002683143c82row2_col2 {\n background-color: lightgreen;\n } #T_2ddfb0d8_269b_11e8_89ce_002683143c82row2_col5 {\n background-color: lightgreen;\n } #T_2ddfb0d8_269b_11e8_89ce_002683143c82row5_col6 {\n background-color: lightgreen;\n } #T_2ddfb0d8_269b_11e8_89ce_002683143c82row5_col7 {\n background-color: lightgreen;\n } #T_2ddfb0d8_269b_11e8_89ce_002683143c82row5_col8 {\n background-color: lightgreen;\n } #T_2ddfb0d8_269b_11e8_89ce_002683143c82row5_col9 {\n background-color: lightgreen;\n } #T_2ddfb0d8_269b_11e8_89ce_002683143c82row5_col10 {\n background-color: lightgreen;\n } #T_2ddfb0d8_269b_11e8_89ce_002683143c82row8_col4 {\n background-color: lightgreen;\n } #T_2ddfb0d8_269b_11e8_89ce_002683143c82row9_col3 {\n background-color: lightgreen;\n }</style> \n<table id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82\" > \n<thead> <tr> \n <th class=\"blank level0\" ></th> \n <th class=\"col_heading level0 col0\" >Name</th> \n <th class=\"col_heading level0 col1\" >Direction</th> \n <th class=\"col_heading level0 col2\" >Sharpe</th> \n <th class=\"col_heading level0 col3\" >SharpeOOS2</th> \n <th class=\"col_heading level0 col4\" >SharpeIS</th> \n <th class=\"col_heading level0 col5\" >SharpeOOS1</th> \n <th class=\"col_heading level0 col6\" >SharpeOOS3</th> \n <th class=\"col_heading level0 col7\" >OOS2 NonflatPCT</th> \n <th class=\"col_heading level0 col8\" >IS NonflatPCT</th> \n <th class=\"col_heading level0 col9\" >OOS1 NonflatPCT</th> \n <th class=\"col_heading level0 col10\" >OOS3 NonflatPCT</th> \n <th class=\"col_heading level0 col11\" >Score</th> \n <th class=\"col_heading level0 col12\" >Rank</th> \n </tr></thead> \n<tbody> <tr> \n <th id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82level0_row0\" class=\"row_heading level0 row0\" >308</th> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row0_col0\" class=\"data row0 col0\" >AMLP-00308</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row0_col1\" class=\"data row0 col1\" >Short</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row0_col2\" class=\"data row0 col2\" >1.06911</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row0_col3\" class=\"data row0 col3\" >-0.0979969</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row0_col4\" class=\"data row0 col4\" >1.46855</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row0_col5\" class=\"data row0 col5\" >1.39443</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row0_col6\" class=\"data row0 col6\" >0.855515</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row0_col7\" class=\"data row0 col7\" >49.5601</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row0_col8\" class=\"data row0 col8\" >42.7205</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row0_col9\" class=\"data row0 col9\" >27.0627</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row0_col10\" class=\"data row0 col10\" >37.0492</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row0_col11\" class=\"data row0 col11\" >274.816</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row0_col12\" class=\"data row0 col12\" >1</td> \n </tr> <tr> \n <th id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82level0_row1\" class=\"row_heading level0 row1\" >225</th> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row1_col0\" class=\"data row1 col0\" >AMLP-00225</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row1_col1\" class=\"data row1 col1\" >Short</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row1_col2\" class=\"data row1 col2\" >1.05564</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row1_col3\" class=\"data row1 col3\" >-1.66068</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row1_col4\" class=\"data row1 col4\" >1.41899</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row1_col5\" class=\"data row1 col5\" >1.99355</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row1_col6\" class=\"data row1 col6\" >1.2018</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row1_col7\" class=\"data row1 col7\" >26.9795</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row1_col8\" class=\"data row1 col8\" >25.5048</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row1_col9\" class=\"data row1 col9\" >10.231</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row1_col10\" class=\"data row1 col10\" >31.4754</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row1_col11\" class=\"data row1 col11\" >270.215</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row1_col12\" class=\"data row1 col12\" >2</td> \n </tr> <tr> \n <th id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82level0_row2\" class=\"row_heading level0 row2\" >400</th> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row2_col0\" class=\"data row2 col0\" >AMLP-00400</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row2_col1\" class=\"data row2 col1\" >Short</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row2_col2\" class=\"data row2 col2\" >1.29844</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row2_col3\" class=\"data row2 col3\" >0.00571472</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row2_col4\" class=\"data row2 col4\" >1.36003</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row2_col5\" class=\"data row2 col5\" >2.24782</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row2_col6\" class=\"data row2 col6\" >1.3035</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row2_col7\" class=\"data row2 col7\" >51.9062</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row2_col8\" class=\"data row2 col8\" >60.0425</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row2_col9\" class=\"data row2 col9\" >47.5248</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row2_col10\" class=\"data row2 col10\" >60</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row2_col11\" class=\"data row2 col11\" >262.999</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row2_col12\" class=\"data row2 col12\" >3</td> \n </tr> <tr> \n <th id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82level0_row3\" class=\"row_heading level0 row3\" >593</th> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row3_col0\" class=\"data row3 col0\" >AMLP-00593</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row3_col1\" class=\"data row3 col1\" >Short</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row3_col2\" class=\"data row3 col2\" >1.24594</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row3_col3\" class=\"data row3 col3\" >1.38126</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row3_col4\" class=\"data row3 col4\" >1.21113</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row3_col5\" class=\"data row3 col5\" >1.69598</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row3_col6\" class=\"data row3 col6\" >0.980526</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row3_col7\" class=\"data row3 col7\" >3.51906</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row3_col8\" class=\"data row3 col8\" >9.77683</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row3_col9\" class=\"data row3 col9\" >6.60066</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row3_col10\" class=\"data row3 col10\" >7.21311</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row3_col11\" class=\"data row3 col11\" >238.206</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row3_col12\" class=\"data row3 col12\" >5</td> \n </tr> <tr> \n <th id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82level0_row4\" class=\"row_heading level0 row4\" >572</th> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row4_col0\" class=\"data row4 col0\" >AMLP-00572</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row4_col1\" class=\"data row4 col1\" >Short</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row4_col2\" class=\"data row4 col2\" >0.787532</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row4_col3\" class=\"data row4 col3\" >-0.879235</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row4_col4\" class=\"data row4 col4\" >1.19308</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row4_col5\" class=\"data row4 col5\" >1.34484</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row4_col6\" class=\"data row4 col6\" >-0.0838823</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row4_col7\" class=\"data row4 col7\" >23.1672</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row4_col8\" class=\"data row4 col8\" >34.644</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row4_col9\" class=\"data row4 col9\" >16.1716</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row4_col10\" class=\"data row4 col10\" >9.83607</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row4_col11\" class=\"data row4 col11\" >236.724</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row4_col12\" class=\"data row4 col12\" >6</td> \n </tr> <tr> \n <th id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82level0_row5\" class=\"row_heading level0 row5\" >219</th> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row5_col0\" class=\"data row5 col0\" >AMLP-00219</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row5_col1\" class=\"data row5 col1\" >Short</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row5_col2\" class=\"data row5 col2\" >0.925657</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row5_col3\" class=\"data row5 col3\" >-0.854148</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row5_col4\" class=\"data row5 col4\" >1.17921</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row5_col5\" class=\"data row5 col5\" >1.24937</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row5_col6\" class=\"data row5 col6\" >1.47986</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row5_col7\" class=\"data row5 col7\" >60.4106</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row5_col8\" class=\"data row5 col8\" >69.7131</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row5_col9\" class=\"data row5 col9\" >52.1452</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row5_col10\" class=\"data row5 col10\" >67.8689</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row5_col11\" class=\"data row5 col11\" >231.514</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row5_col12\" class=\"data row5 col12\" >7</td> \n </tr> <tr> \n <th id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82level0_row6\" class=\"row_heading level0 row6\" >217</th> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row6_col0\" class=\"data row6 col0\" >AMLP-00217</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row6_col1\" class=\"data row6 col1\" >Short</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row6_col2\" class=\"data row6 col2\" >1.07588</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row6_col3\" class=\"data row6 col3\" >0.40379</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row6_col4\" class=\"data row6 col4\" >1.41057</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row6_col5\" class=\"data row6 col5\" >0.986359</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row6_col6\" class=\"data row6 col6\" >0.898823</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row6_col7\" class=\"data row6 col7\" >17.5953</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row6_col8\" class=\"data row6 col8\" >28.4803</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row6_col9\" class=\"data row6 col9\" >14.1914</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row6_col10\" class=\"data row6 col10\" >8.85246</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row6_col11\" class=\"data row6 col11\" >226.766</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row6_col12\" class=\"data row6 col12\" >8</td> \n </tr> <tr> \n <th id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82level0_row7\" class=\"row_heading level0 row7\" >239</th> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row7_col0\" class=\"data row7 col0\" >AMLP-00239</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row7_col1\" class=\"data row7 col1\" >Short</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row7_col2\" class=\"data row7 col2\" >0.572721</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row7_col3\" class=\"data row7 col3\" >-1.44806</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row7_col4\" class=\"data row7 col4\" >1.35224</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row7_col5\" class=\"data row7 col5\" >1.05443</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row7_col6\" class=\"data row7 col6\" >-0.342582</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row7_col7\" class=\"data row7 col7\" >44.868</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row7_col8\" class=\"data row7 col8\" >46.0149</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row7_col9\" class=\"data row7 col9\" >42.9043</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row7_col10\" class=\"data row7 col10\" >41.3115</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row7_col11\" class=\"data row7 col11\" >221.731</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row7_col12\" class=\"data row7 col12\" >9</td> \n </tr> <tr> \n <th id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82level0_row8\" class=\"row_heading level0 row8\" >167</th> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row8_col0\" class=\"data row8 col0\" >AMLP-00167</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row8_col1\" class=\"data row8 col1\" >Long</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row8_col2\" class=\"data row8 col2\" >0.848278</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row8_col3\" class=\"data row8 col3\" >0.540776</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row8_col4\" class=\"data row8 col4\" >1.74023</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row8_col5\" class=\"data row8 col5\" >0.211354</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row8_col6\" class=\"data row8 col6\" >-0.103539</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row8_col7\" class=\"data row8 col7\" >2.6393</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row8_col8\" class=\"data row8 col8\" >13.0712</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row8_col9\" class=\"data row8 col9\" >2.9703</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row8_col10\" class=\"data row8 col10\" >3.93443</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row8_col11\" class=\"data row8 col11\" >170.697</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row8_col12\" class=\"data row8 col12\" >41</td> \n </tr> <tr> \n <th id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82level0_row9\" class=\"row_heading level0 row9\" >116</th> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row9_col0\" class=\"data row9 col0\" >AMLP-00116</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row9_col1\" class=\"data row9 col1\" >Long</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row9_col2\" class=\"data row9 col2\" >1.06485</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row9_col3\" class=\"data row9 col3\" >2.15526</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row9_col4\" class=\"data row9 col4\" >1.22829</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row9_col5\" class=\"data row9 col5\" >0.544062</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row9_col6\" class=\"data row9 col6\" >0.565165</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row9_col7\" class=\"data row9 col7\" >9.97067</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row9_col8\" class=\"data row9 col8\" >11.1583</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row9_col9\" class=\"data row9 col9\" >4.62046</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row9_col10\" class=\"data row9 col10\" >4.2623</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row9_col11\" class=\"data row9 col11\" >165.968</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row9_col12\" class=\"data row9 col12\" >48</td> \n </tr> <tr> \n <th id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82level0_row10\" class=\"row_heading level0 row10\" >136</th> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row10_col0\" class=\"data row10 col0\" >AMLP-00136</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row10_col1\" class=\"data row10 col1\" >Long</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row10_col2\" class=\"data row10 col2\" >0.74644</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row10_col3\" class=\"data row10 col3\" >0.91652</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row10_col4\" class=\"data row10 col4\" >0.426769</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row10_col5\" class=\"data row10 col5\" >1.78973</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row10_col6\" class=\"data row10 col6\" >0.110357</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row10_col7\" class=\"data row10 col7\" >29.6188</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row10_col8\" class=\"data row10 col8\" >13.6026</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row10_col9\" class=\"data row10 col9\" >12.8713</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row10_col10\" class=\"data row10 col10\" >11.8033</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row10_col11\" class=\"data row10 col11\" >135.566</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row10_col12\" class=\"data row10 col12\" >107</td> \n </tr> <tr> \n <th id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82level0_row11\" class=\"row_heading level0 row11\" >102</th> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row11_col0\" class=\"data row11 col0\" >AMLP-00102</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row11_col1\" class=\"data row11 col1\" >Long</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row11_col2\" class=\"data row11 col2\" >0.800721</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row11_col3\" class=\"data row11 col3\" >1.61167</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row11_col4\" class=\"data row11 col4\" >0.549812</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row11_col5\" class=\"data row11 col5\" >1.65078</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row11_col6\" class=\"data row11 col6\" >-0.21009</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row11_col7\" class=\"data row11 col7\" >2.93255</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row11_col8\" class=\"data row11 col8\" >20.1913</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row11_col9\" class=\"data row11 col9\" >9.57096</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row11_col10\" class=\"data row11 col10\" >3.27869</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row11_col11\" class=\"data row11 col11\" >130.514</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row11_col12\" class=\"data row11 col12\" >121</td> \n </tr> <tr> \n <th id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82level0_row12\" class=\"row_heading level0 row12\" >180</th> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row12_col0\" class=\"data row12 col0\" >AMLP-00180</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row12_col1\" class=\"data row12 col1\" >Long</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row12_col2\" class=\"data row12 col2\" >0.354959</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row12_col3\" class=\"data row12 col3\" >0.24949</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row12_col4\" class=\"data row12 col4\" >0.41752</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row12_col5\" class=\"data row12 col5\" >0.749201</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row12_col6\" class=\"data row12 col6\" >-0.52751</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row12_col7\" class=\"data row12 col7\" >17.3021</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row12_col8\" class=\"data row12 col8\" >14.0276</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row12_col9\" class=\"data row12 col9\" >11.8812</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row12_col10\" class=\"data row12 col10\" >1.96721</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row12_col11\" class=\"data row12 col11\" >99.3015</td> \n <td id=\"T_2ddfb0d8_269b_11e8_89ce_002683143c82row12_col12\" class=\"data row12 col12\" >188</td> \n </tr></tbody> \n</table> ",
  430. "text/plain": "<pandas.io.formats.style.Styler at 0x288d16f5390>"
  431. },
  432. "metadata": {},
  433. "output_type": "display_data"
  434. },
  435. {
  436. "name": "stdout",
  437. "output_type": "stream",
  438. "text": "Total Rules in chosen : 13\nLong Rules: 5 , Short Rules: 8\n"
  439. }
  440. ]
  441. },
  442. {
  443. "metadata": {},
  444. "cell_type": "markdown",
  445. "source": "# Get all combinations to form ONE Multisignal strategy for this Instrument and TimeFrame"
  446. },
  447. {
  448. "metadata": {
  449. "trusted": true
  450. },
  451. "cell_type": "code",
  452. "source": "print(chosen)\nchosen = [x for x in chosen if x!=180]\nprint(chosen)",
  453. "execution_count": 125,
  454. "outputs": [
  455. {
  456. "name": "stdout",
  457. "output_type": "stream",
  458. "text": "[308, 225, 400, 593, 572, 219, 217, 239, 102, 116, 136, 167, 180]\n[308, 225, 400, 593, 572, 219, 217, 239, 102, 116, 136, 167]\n"
  459. }
  460. ]
  461. },
  462. {
  463. "metadata": {
  464. "trusted": true
  465. },
  466. "cell_type": "code",
  467. "source": "# Run\nprint(chosen)\n\n# Sample run of 4083 combinations takes 84 seconds\n# if Memory Error, reduce the number of rules in Chosen\nprint(\"Rules= \",[str(i)+\"_\"+final.loc[i]['Direction'][0] for i in chosen])\nall_combi = GetRulesCombinations(chosen)\nprint(\"Total Combination = \", len(all_combi))\n\nt0 = time.time()\ncombi_array=[]\nsharpe_array=[]\nnum_long_array=[]\nnum_short_array=[]\n\n# print(\"Combi | Sharpe\")\nfor combi in all_combi:\n\n combi_array.append(combi)\n\n num_long = 0\n num_short = 0\n for i in combi:\n if final.loc[i]['Direction'][0]=='L':\n num_long=num_long+1\n elif final.loc[i]['Direction'][0]=='S':\n num_short=num_short+1\n num_long_array.append(num_long)\n num_short_array.append(num_short)\n \n new_df = pd.DataFrame()\n new_df['Date']=df_list[0]['Date']\n for df in [df_list[x] for x in combi]:\n new_df[df.name]=df['Daily Return']\n new_df['Daily Return']=new_df[[x for x in new_df.columns if x != 'Date']].sum(axis=1)\n new_df['Daily Return']=new_df['Daily Return']/len(combi)\n combined_ret_df = new_df[['Date','Daily Return']]\n sharpe=get_sharpe(combined_ret_df)\n sharpe_array.append(sharpe)\n \nt1 = time.time()\ndf_allcombi = pd.DataFrame({'Combinations':combi_array,'Sharpe':sharpe_array,'LongRules':num_long_array,\n 'ShortRules':num_short_array})\ndf_allcombi = df_allcombi.sort_values(by=\"Sharpe\",ascending =False)\ndf_allcombi['Combi Index']=range(len(df_allcombi))\ndf_allcombi=df_allcombi.set_index('Combi Index')\n\nprint(\"Run Time:\",t1-t0, \"Seconds\")\n\nwith pd.option_context('display.max_rows', None, 'display.max_columns', None):\n display(df_allcombi[['Combinations', 'Sharpe','LongRules','ShortRules']])",
  468. "execution_count": 126,
  469. "outputs": [
  470. {
  471. "name": "stdout",
  472. "output_type": "stream",
  473. "text": "[308, 225, 400, 593, 572, 219, 217, 239, 102, 116, 136, 167]\nRules= ['308_S', '225_S', '400_S', '593_S', '572_S', '219_S', '217_S', '239_S', '102_L', '116_L', '136_L', '167_L']\nTotal Combination = 4083\nRun Time: 84.15065383911133 Seconds\n"
  474. },
  475. {
  476. "data": {
  477. "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Combinations</th>\n <th>Sharpe</th>\n <th>LongRules</th>\n <th>ShortRules</th>\n </tr>\n <tr>\n <th>Combi Index</th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>[400, 593, 217, 102, 116, 136, 167]</td>\n <td>2.720188</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1</th>\n <td>[225, 400, 593, 102, 116, 136, 167]</td>\n <td>2.705898</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2</th>\n <td>[400, 593, 572, 217, 102, 116, 136, 167]</td>\n <td>2.686970</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3</th>\n <td>[400, 593, 572, 102, 116, 136, 167]</td>\n <td>2.686759</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4</th>\n <td>[400, 593, 102, 116, 136, 167]</td>\n <td>2.677788</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>5</th>\n <td>[225, 400, 593, 572, 102, 116, 136, 167]</td>\n <td>2.660203</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>6</th>\n <td>[225, 400, 593, 217, 102, 116, 136, 167]</td>\n <td>2.653306</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>7</th>\n <td>[225, 400, 593, 572, 217, 102, 116, 136, 167]</td>\n <td>2.607421</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>8</th>\n <td>[400, 217, 102, 116, 136, 167]</td>\n <td>2.577118</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>9</th>\n <td>[593, 572, 217, 102, 116, 136, 167]</td>\n <td>2.565216</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>10</th>\n <td>[400, 572, 217, 102, 116, 136, 167]</td>\n <td>2.563370</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>11</th>\n <td>[225, 400, 102, 116, 136, 167]</td>\n <td>2.551190</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>12</th>\n <td>[225, 400, 217, 102, 116, 136, 167]</td>\n <td>2.544877</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>13</th>\n <td>[225, 593, 572, 217, 102, 116, 136, 167]</td>\n <td>2.539767</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>14</th>\n <td>[308, 400, 593, 217, 102, 116, 136, 167]</td>\n <td>2.531614</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>15</th>\n <td>[308, 225, 400, 593, 102, 116, 136, 167]</td>\n <td>2.529843</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>16</th>\n <td>[225, 400, 572, 102, 116, 136, 167]</td>\n <td>2.525656</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>17</th>\n <td>[308, 400, 593, 102, 116, 136, 167]</td>\n <td>2.524993</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>18</th>\n <td>[400, 593, 217, 102, 116, 136]</td>\n <td>2.518334</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>19</th>\n <td>[225, 400, 593, 102, 116, 136]</td>\n <td>2.511185</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>20</th>\n <td>[400, 593, 217, 102, 136, 167]</td>\n <td>2.510557</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>21</th>\n <td>[225, 400, 572, 217, 102, 116, 136, 167]</td>\n <td>2.506984</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>22</th>\n <td>[308, 400, 593, 572, 102, 116, 136, 167]</td>\n <td>2.502865</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>23</th>\n <td>[308, 400, 593, 572, 217, 102, 116, 136, 167]</td>\n <td>2.500339</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>24</th>\n <td>[308, 225, 400, 593, 217, 102, 116, 136, 167]</td>\n <td>2.496539</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>25</th>\n <td>[225, 593, 572, 102, 116, 136, 167]</td>\n <td>2.496199</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>26</th>\n <td>[225, 593, 217, 102, 116, 136, 167]</td>\n <td>2.495892</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>27</th>\n <td>[400, 572, 102, 116, 136, 167]</td>\n <td>2.495542</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>28</th>\n <td>[225, 400, 593, 102, 136, 167]</td>\n <td>2.491610</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>29</th>\n <td>[308, 225, 400, 593, 572, 102, 116, 136, 167]</td>\n <td>2.489900</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>30</th>\n <td>[400, 593, 102, 116, 136]</td>\n <td>2.487189</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>31</th>\n <td>[400, 593, 572, 217, 102, 116, 136]</td>\n <td>2.484959</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>32</th>\n <td>[400, 593, 572, 217, 102, 136, 167]</td>\n <td>2.483792</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>33</th>\n <td>[400, 593, 572, 102, 116, 136]</td>\n <td>2.480400</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>34</th>\n <td>[400, 593, 217, 102, 116, 167]</td>\n <td>2.478921</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>35</th>\n <td>[225, 400, 593, 102, 116, 167]</td>\n <td>2.476664</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>36</th>\n <td>[400, 593, 572, 102, 136, 167]</td>\n <td>2.473321</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>37</th>\n <td>[225, 400, 593, 116, 136, 167]</td>\n <td>2.468986</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>38</th>\n <td>[400, 593, 102, 136, 167]</td>\n <td>2.467252</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>39</th>\n <td>[400, 593, 116, 136, 167]</td>\n <td>2.465253</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>40</th>\n <td>[225, 400, 593, 217, 102, 116, 136]</td>\n <td>2.464879</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>41</th>\n <td>[400, 593, 217, 116, 136, 167]</td>\n <td>2.464664</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>42</th>\n <td>[225, 400, 593, 572, 102, 116, 136]</td>\n <td>2.464032</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>43</th>\n <td>[308, 225, 400, 593, 572, 217, 102, 116, 136, ...</td>\n <td>2.460709</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>44</th>\n <td>[400, 593, 102, 116, 167]</td>\n <td>2.457251</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>45</th>\n <td>[225, 400, 593, 217, 102, 136, 167]</td>\n <td>2.454269</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>46</th>\n <td>[225, 400, 593, 572, 102, 136, 167]</td>\n <td>2.453891</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>47</th>\n <td>[308, 400, 217, 102, 116, 136, 167]</td>\n <td>2.434522</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>48</th>\n <td>[400, 102, 116, 136, 167]</td>\n <td>2.434434</td>\n <td>4</td>\n <td>1</td>\n </tr>\n <tr>\n <th>49</th>\n <td>[400, 593, 572, 217, 102, 116, 167]</td>\n <td>2.432925</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>50</th>\n <td>[308, 593, 572, 217, 102, 116, 136, 167]</td>\n <td>2.432502</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>51</th>\n <td>[225, 400, 593, 217, 102, 116, 167]</td>\n <td>2.428590</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>52</th>\n <td>[308, 225, 400, 102, 116, 136, 167]</td>\n <td>2.428539</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>53</th>\n <td>[400, 593, 572, 116, 136, 167]</td>\n <td>2.426876</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>54</th>\n <td>[400, 593, 572, 102, 116, 167]</td>\n <td>2.426089</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>55</th>\n <td>[225, 400, 593, 572, 217, 102, 116, 136]</td>\n <td>2.424517</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>56</th>\n <td>[593, 217, 102, 116, 136, 167]</td>\n <td>2.421183</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>57</th>\n <td>[225, 400, 593, 572, 217, 102, 136, 167]</td>\n <td>2.419173</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>58</th>\n <td>[400, 593, 572, 217, 116, 136, 167]</td>\n <td>2.418623</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>59</th>\n <td>[225, 400, 593, 572, 102, 116, 167]</td>\n <td>2.415783</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>60</th>\n <td>[308, 225, 400, 217, 102, 116, 136, 167]</td>\n <td>2.415490</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>61</th>\n <td>[308, 225, 593, 217, 102, 116, 136, 167]</td>\n <td>2.414755</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>62</th>\n <td>[308, 225, 593, 572, 217, 102, 116, 136, 167]</td>\n <td>2.414030</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>63</th>\n <td>[308, 400, 572, 217, 102, 116, 136, 167]</td>\n <td>2.409487</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>64</th>\n <td>[225, 400, 593, 217, 116, 136, 167]</td>\n <td>2.409265</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>65</th>\n <td>[308, 225, 593, 572, 102, 116, 136, 167]</td>\n <td>2.407014</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>66</th>\n <td>[225, 400, 593, 572, 116, 136, 167]</td>\n <td>2.406138</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>67</th>\n <td>[308, 593, 217, 102, 116, 136, 167]</td>\n <td>2.401655</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>68</th>\n <td>[593, 572, 217, 102, 136, 167]</td>\n <td>2.398830</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>69</th>\n <td>[308, 225, 400, 572, 102, 116, 136, 167]</td>\n <td>2.394522</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>70</th>\n <td>[225, 572, 217, 102, 116, 136, 167]</td>\n <td>2.392434</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>71</th>\n <td>[308, 400, 102, 116, 136, 167]</td>\n <td>2.390099</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>72</th>\n <td>[400, 593, 217, 239, 102, 116, 136, 167]</td>\n <td>2.387871</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>73</th>\n <td>[308, 225, 593, 102, 116, 136, 167]</td>\n <td>2.385140</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>74</th>\n <td>[308, 400, 572, 102, 116, 136, 167]</td>\n <td>2.382973</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>75</th>\n <td>[308, 225, 400, 572, 217, 102, 116, 136, 167]</td>\n <td>2.382493</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>76</th>\n <td>[225, 400, 593, 572, 217, 102, 116, 167]</td>\n <td>2.380709</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>77</th>\n <td>[593, 572, 217, 102, 116, 136]</td>\n <td>2.369744</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>78</th>\n <td>[308, 225, 400, 593, 102, 116, 136]</td>\n <td>2.369537</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>79</th>\n <td>[308, 400, 593, 217, 102, 116, 136]</td>\n <td>2.368855</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>80</th>\n <td>[400, 593, 219, 102, 116, 136, 167]</td>\n <td>2.368734</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>81</th>\n <td>[225, 400, 593, 572, 217, 116, 136, 167]</td>\n <td>2.363019</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>82</th>\n <td>[225, 593, 102, 116, 136, 167]</td>\n <td>2.362896</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>83</th>\n <td>[225, 593, 572, 217, 102, 136, 167]</td>\n <td>2.359048</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>84</th>\n <td>[308, 400, 593, 102, 116, 136]</td>\n <td>2.357948</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>85</th>\n <td>[400, 217, 102, 116, 136]</td>\n <td>2.356903</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>86</th>\n <td>[308, 400, 593, 217, 102, 136, 167]</td>\n <td>2.354747</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>87</th>\n <td>[308, 593, 572, 102, 116, 136, 167]</td>\n <td>2.353576</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>88</th>\n <td>[400, 217, 102, 136, 167]</td>\n <td>2.352880</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>89</th>\n <td>[572, 217, 102, 116, 136, 167]</td>\n <td>2.352845</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>90</th>\n <td>[593, 572, 217, 102, 116, 167]</td>\n <td>2.350716</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>91</th>\n <td>[308, 225, 400, 593, 102, 136, 167]</td>\n <td>2.349383</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>92</th>\n <td>[225, 593, 572, 217, 102, 116, 136]</td>\n <td>2.347418</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>93</th>\n <td>[400, 593, 572, 217, 239, 102, 116, 136, 167]</td>\n <td>2.347043</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>94</th>\n <td>[400, 572, 217, 102, 136, 167]</td>\n <td>2.345758</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>95</th>\n <td>[308, 225, 400, 593, 217, 102, 116, 136]</td>\n <td>2.345284</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>96</th>\n <td>[400, 572, 217, 102, 116, 136]</td>\n <td>2.343262</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>97</th>\n <td>[225, 400, 593, 217, 239, 102, 116, 136, 167]</td>\n <td>2.342601</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>98</th>\n <td>[400, 593, 572, 219, 102, 116, 136, 167]</td>\n <td>2.342369</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>99</th>\n <td>[308, 400, 593, 572, 217, 102, 116, 136]</td>\n <td>2.341743</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>100</th>\n <td>[225, 400, 217, 102, 116, 136]</td>\n <td>2.339735</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>101</th>\n <td>[225, 400, 593, 219, 102, 116, 136, 167]</td>\n <td>2.339673</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>102</th>\n <td>[225, 400, 102, 116, 136]</td>\n <td>2.339648</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>103</th>\n <td>[400, 593, 219, 217, 102, 116, 136, 167]</td>\n <td>2.339263</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>104</th>\n <td>[400, 217, 102, 116, 167]</td>\n <td>2.337173</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>105</th>\n <td>[308, 400, 593, 572, 102, 116, 136]</td>\n <td>2.335948</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>106</th>\n <td>[308, 400, 593, 102, 136, 167]</td>\n <td>2.335613</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>107</th>\n <td>[308, 225, 400, 593, 572, 102, 116, 136]</td>\n <td>2.333519</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>108</th>\n <td>[308, 400, 593, 572, 217, 102, 136, 167]</td>\n <td>2.332582</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>109</th>\n <td>[308, 225, 400, 593, 217, 102, 136, 167]</td>\n <td>2.331666</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>110</th>\n <td>[225, 400, 217, 102, 136, 167]</td>\n <td>2.331114</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>111</th>\n <td>[593, 572, 217, 116, 136, 167]</td>\n <td>2.330560</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>112</th>\n <td>[225, 400, 593, 239, 102, 116, 136, 167]</td>\n <td>2.329481</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>113</th>\n <td>[400, 593, 239, 102, 116, 136, 167]</td>\n <td>2.329251</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>114</th>\n <td>[593, 572, 102, 116, 136, 167]</td>\n <td>2.329008</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>115</th>\n <td>[225, 400, 102, 116, 167]</td>\n <td>2.326799</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>116</th>\n <td>[308, 225, 400, 593, 102, 116, 167]</td>\n <td>2.324378</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>117</th>\n <td>[225, 593, 572, 102, 136, 167]</td>\n <td>2.323503</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>118</th>\n <td>[225, 593, 572, 217, 102, 116, 167]</td>\n <td>2.322624</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>119</th>\n <td>[308, 400, 593, 217, 102, 116, 167]</td>\n <td>2.322179</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>120</th>\n <td>[225, 400, 102, 136, 167]</td>\n <td>2.321749</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>121</th>\n <td>[593, 217, 239, 102, 116, 136, 167]</td>\n <td>2.321594</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>122</th>\n <td>[308, 400, 593, 572, 102, 136, 167]</td>\n <td>2.321514</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>123</th>\n <td>[225, 593, 217, 102, 136, 167]</td>\n <td>2.320093</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>124</th>\n <td>[308, 225, 400, 593, 572, 102, 136, 167]</td>\n <td>2.319592</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>125</th>\n <td>[593, 572, 217, 239, 102, 116, 136, 167]</td>\n <td>2.317479</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>126</th>\n <td>[400, 593, 572, 219, 217, 102, 116, 136, 167]</td>\n <td>2.316782</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>127</th>\n <td>[308, 225, 400, 593, 116, 136, 167]</td>\n <td>2.316549</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>128</th>\n <td>[225, 593, 217, 102, 116, 167]</td>\n <td>2.316339</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>129</th>\n <td>[225, 400, 217, 102, 116, 167]</td>\n <td>2.315622</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>130</th>\n <td>[308, 225, 400, 593, 572, 217, 102, 116, 136]</td>\n <td>2.314922</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>131</th>\n <td>[308, 225, 572, 217, 102, 116, 136, 167]</td>\n <td>2.314761</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>132</th>\n <td>[225, 593, 217, 102, 116, 136]</td>\n <td>2.314048</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>133</th>\n <td>[225, 400, 572, 102, 116, 136]</td>\n <td>2.312733</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>134</th>\n <td>[225, 593, 572, 102, 116, 136]</td>\n <td>2.312411</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>135</th>\n <td>[308, 400, 593, 217, 239, 102, 116, 136, 167]</td>\n <td>2.311238</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>136</th>\n <td>[308, 400, 593, 217, 116, 136, 167]</td>\n <td>2.311123</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>137</th>\n <td>[400, 217, 116, 136, 167]</td>\n <td>2.310622</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>138</th>\n <td>[225, 217, 102, 116, 136, 167]</td>\n <td>2.310002</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>139</th>\n <td>[225, 400, 593, 572, 219, 102, 116, 136, 167]</td>\n <td>2.309497</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>140</th>\n <td>[225, 400, 572, 217, 102, 116, 136]</td>\n <td>2.308930</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>141</th>\n <td>[308, 572, 217, 102, 116, 136, 167]</td>\n <td>2.308234</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>142</th>\n <td>[225, 400, 116, 136, 167]</td>\n <td>2.307549</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>143</th>\n <td>[308, 400, 593, 102, 116, 167]</td>\n <td>2.307477</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>144</th>\n <td>[308, 400, 593, 116, 136, 167]</td>\n <td>2.305973</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>145</th>\n <td>[225, 400, 572, 217, 102, 136, 167]</td>\n <td>2.305593</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>146</th>\n <td>[308, 225, 400, 593, 572, 217, 102, 136, 167]</td>\n <td>2.305311</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>147</th>\n <td>[225, 400, 593, 572, 217, 239, 102, 116, 136, ...</td>\n <td>2.304782</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>148</th>\n <td>[308, 225, 400, 593, 217, 102, 116, 167]</td>\n <td>2.304768</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>149</th>\n <td>[225, 400, 572, 102, 136, 167]</td>\n <td>2.304758</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>150</th>\n <td>[308, 225, 217, 102, 116, 136, 167]</td>\n <td>2.304136</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>151</th>\n <td>[400, 572, 217, 102, 116, 167]</td>\n <td>2.302926</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>152</th>\n <td>[225, 593, 572, 102, 116, 167]</td>\n <td>2.301777</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>153</th>\n <td>[400, 593, 572, 239, 102, 116, 136, 167]</td>\n <td>2.301744</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>154</th>\n <td>[225, 400, 593, 219, 217, 102, 116, 136, 167]</td>\n <td>2.298320</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>155</th>\n <td>[225, 593, 572, 217, 116, 136, 167]</td>\n <td>2.296965</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>156</th>\n <td>[400, 593, 217, 102, 136]</td>\n <td>2.296866</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>157</th>\n <td>[308, 400, 593, 572, 217, 102, 116, 167]</td>\n <td>2.292399</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>158</th>\n <td>[225, 400, 593, 572, 239, 102, 116, 136, 167]</td>\n <td>2.291723</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>159</th>\n <td>[400, 219, 102, 116, 136, 167]</td>\n <td>2.291196</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>160</th>\n <td>[308, 225, 400, 593, 217, 116, 136, 167]</td>\n <td>2.291087</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>161</th>\n <td>[225, 593, 572, 116, 136, 167]</td>\n <td>2.290158</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>162</th>\n <td>[225, 593, 217, 239, 102, 116, 136, 167]</td>\n <td>2.289624</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>163</th>\n <td>[225, 593, 217, 116, 136, 167]</td>\n <td>2.287367</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>164</th>\n <td>[225, 400, 217, 116, 136, 167]</td>\n <td>2.286910</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>165</th>\n <td>[308, 225, 400, 593, 572, 102, 116, 167]</td>\n <td>2.285602</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>166</th>\n <td>[225, 400, 593, 102, 136]</td>\n <td>2.284091</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>167</th>\n <td>[308, 400, 593, 239, 102, 116, 136, 167]</td>\n <td>2.283750</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>168</th>\n <td>[308, 225, 400, 593, 217, 239, 102, 116, 136, ...</td>\n <td>2.283475</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>169</th>\n <td>[308, 400, 593, 572, 217, 116, 136, 167]</td>\n <td>2.281444</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>170</th>\n <td>[308, 400, 593, 572, 102, 116, 167]</td>\n <td>2.280681</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>171</th>\n <td>[593, 217, 102, 116, 167]</td>\n <td>2.280215</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>172</th>\n <td>[308, 225, 400, 593, 239, 102, 116, 136, 167]</td>\n <td>2.279368</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>173</th>\n <td>[400, 572, 217, 116, 136, 167]</td>\n <td>2.279351</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>174</th>\n <td>[308, 400, 593, 572, 217, 239, 102, 116, 136, ...</td>\n <td>2.277324</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>175</th>\n <td>[225, 400, 572, 102, 116, 167]</td>\n <td>2.277280</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>176</th>\n <td>[308, 225, 400, 593, 572, 116, 136, 167]</td>\n <td>2.277127</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>177</th>\n <td>[308, 400, 593, 572, 116, 136, 167]</td>\n <td>2.276774</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>178</th>\n <td>[225, 400, 593, 572, 219, 217, 102, 116, 136, ...</td>\n <td>2.276153</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>179</th>\n <td>[400, 593, 572, 217, 102, 136]</td>\n <td>2.275224</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>180</th>\n <td>[593, 572, 219, 102, 116, 136, 167]</td>\n <td>2.274362</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>181</th>\n <td>[308, 593, 217, 239, 102, 116, 136, 167]</td>\n <td>2.273618</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>182</th>\n <td>[308, 225, 572, 102, 116, 136, 167]</td>\n <td>2.273416</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>183</th>\n <td>[593, 572, 219, 217, 102, 116, 136, 167]</td>\n <td>2.273299</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>184</th>\n <td>[225, 400, 572, 217, 102, 116, 167]</td>\n <td>2.272822</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>185</th>\n <td>[308, 225, 400, 593, 572, 217, 102, 116, 167]</td>\n <td>2.272668</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>186</th>\n <td>[593, 217, 102, 136, 167]</td>\n <td>2.272380</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>187</th>\n <td>[225, 593, 572, 217, 239, 102, 116, 136, 167]</td>\n <td>2.272303</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>188</th>\n <td>[400, 219, 217, 102, 116, 136, 167]</td>\n <td>2.271875</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>189</th>\n <td>[400, 572, 102, 116, 136]</td>\n <td>2.271759</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>190</th>\n <td>[225, 400, 219, 102, 116, 136, 167]</td>\n <td>2.270309</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>191</th>\n <td>[225, 400, 593, 102, 116]</td>\n <td>2.268882</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>192</th>\n <td>[400, 572, 102, 136, 167]</td>\n <td>2.268047</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>193</th>\n <td>[400, 593, 217, 102, 116]</td>\n <td>2.266655</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>194</th>\n <td>[308, 593, 572, 217, 102, 136, 167]</td>\n <td>2.264980</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>195</th>\n <td>[308, 593, 572, 217, 102, 116, 136]</td>\n <td>2.264680</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>196</th>\n <td>[400, 572, 219, 102, 116, 136, 167]</td>\n <td>2.264048</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>197</th>\n <td>[308, 593, 102, 116, 136, 167]</td>\n <td>2.260859</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>198</th>\n <td>[225, 400, 593, 217, 102, 136]</td>\n <td>2.260355</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>199</th>\n <td>[308, 225, 400, 593, 572, 217, 116, 136, 167]</td>\n <td>2.259792</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>200</th>\n <td>[593, 217, 116, 136, 167]</td>\n <td>2.259144</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>201</th>\n <td>[225, 572, 102, 116, 136, 167]</td>\n <td>2.259068</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>202</th>\n <td>[225, 400, 572, 116, 136, 167]</td>\n <td>2.258898</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>203</th>\n <td>[593, 219, 217, 102, 116, 136, 167]</td>\n <td>2.258862</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>204</th>\n <td>[308, 400, 217, 102, 116, 136]</td>\n <td>2.258812</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>205</th>\n <td>[308, 400, 593, 219, 102, 116, 136, 167]</td>\n <td>2.258097</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>206</th>\n <td>[225, 400, 593, 116, 136]</td>\n <td>2.257570</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>207</th>\n <td>[308, 225, 593, 217, 102, 116, 136]</td>\n <td>2.256475</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>208</th>\n <td>[225, 593, 572, 219, 102, 116, 136, 167]</td>\n <td>2.256283</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>209</th>\n <td>[308, 225, 593, 572, 217, 102, 116, 136]</td>\n <td>2.256102</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>210</th>\n <td>[308, 225, 400, 102, 116, 136]</td>\n <td>2.255699</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>211</th>\n <td>[400, 593, 102, 136]</td>\n <td>2.254031</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>212</th>\n <td>[308, 217, 102, 116, 136, 167]</td>\n <td>2.253227</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>213</th>\n <td>[593, 217, 102, 116, 136]</td>\n <td>2.253096</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>214</th>\n <td>[308, 225, 400, 217, 102, 116, 136]</td>\n <td>2.252940</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>215</th>\n <td>[308, 593, 572, 217, 239, 102, 116, 136, 167]</td>\n <td>2.252815</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>216</th>\n <td>[308, 225, 593, 572, 217, 102, 136, 167]</td>\n <td>2.252589</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>217</th>\n <td>[400, 593, 572, 102, 136]</td>\n <td>2.252439</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>218</th>\n <td>[308, 400, 593, 572, 239, 102, 116, 136, 167]</td>\n <td>2.252337</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>219</th>\n <td>[308, 225, 400, 593, 572, 217, 239, 102, 116, ...</td>\n <td>2.251783</td>\n <td>4</td>\n <td>7</td>\n </tr>\n <tr>\n <th>220</th>\n <td>[225, 593, 219, 102, 116, 136, 167]</td>\n <td>2.251335</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>221</th>\n <td>[225, 400, 593, 572, 102, 136]</td>\n <td>2.250618</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>222</th>\n <td>[400, 217, 239, 102, 116, 136, 167]</td>\n <td>2.249583</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>223</th>\n <td>[400, 593, 217, 116, 136]</td>\n <td>2.249361</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>224</th>\n <td>[308, 225, 593, 217, 239, 102, 116, 136, 167]</td>\n <td>2.249284</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>225</th>\n <td>[400, 572, 219, 217, 102, 116, 136, 167]</td>\n <td>2.248856</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>226</th>\n <td>[308, 225, 400, 593, 219, 102, 116, 136, 167]</td>\n <td>2.248730</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>227</th>\n <td>[308, 225, 593, 217, 102, 136, 167]</td>\n <td>2.248527</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>228</th>\n <td>[225, 400, 572, 217, 116, 136, 167]</td>\n <td>2.247976</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>229</th>\n <td>[308, 400, 593, 219, 217, 102, 116, 136, 167]</td>\n <td>2.246897</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>230</th>\n <td>[225, 593, 102, 116, 167]</td>\n <td>2.246520</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>231</th>\n <td>[308, 400, 217, 102, 136, 167]</td>\n <td>2.245420</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>232</th>\n <td>[308, 225, 400, 593, 572, 239, 102, 116, 136, ...</td>\n <td>2.245051</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>233</th>\n <td>[308, 225, 593, 572, 102, 116, 136]</td>\n <td>2.244043</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>234</th>\n <td>[400, 593, 116, 136]</td>\n <td>2.243982</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>235</th>\n <td>[400, 593, 102, 116]</td>\n <td>2.241564</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>236</th>\n <td>[308, 225, 400, 217, 102, 136, 167]</td>\n <td>2.239686</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>237</th>\n <td>[308, 400, 593, 572, 219, 102, 116, 136, 167]</td>\n <td>2.239225</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>238</th>\n <td>[308, 593, 217, 102, 116, 136]</td>\n <td>2.239225</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>239</th>\n <td>[308, 400, 572, 217, 102, 116, 136]</td>\n <td>2.239046</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>240</th>\n <td>[225, 400, 572, 219, 102, 116, 136, 167]</td>\n <td>2.238627</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>241</th>\n <td>[400, 593, 217, 102, 167]</td>\n <td>2.237901</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>242</th>\n <td>[400, 572, 102, 116, 167]</td>\n <td>2.237875</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>243</th>\n <td>[225, 593, 116, 136, 167]</td>\n <td>2.237124</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>244</th>\n <td>[308, 225, 593, 572, 102, 136, 167]</td>\n <td>2.236733</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>245</th>\n <td>[225, 400, 593, 217, 102, 116]</td>\n <td>2.236478</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>246</th>\n <td>[593, 219, 102, 116, 136, 167]</td>\n <td>2.235798</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>247</th>\n <td>[308, 225, 400, 102, 136, 167]</td>\n <td>2.235464</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>248</th>\n <td>[225, 400, 219, 217, 102, 116, 136, 167]</td>\n <td>2.234376</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>249</th>\n <td>[308, 593, 217, 102, 136, 167]</td>\n <td>2.233850</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>250</th>\n <td>[225, 400, 593, 572, 217, 102, 136]</td>\n <td>2.233732</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>251</th>\n <td>[400, 102, 116, 167]</td>\n <td>2.232358</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>252</th>\n <td>[225, 593, 572, 219, 217, 102, 116, 136, 167]</td>\n <td>2.231657</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>253</th>\n <td>[308, 400, 572, 217, 102, 136, 167]</td>\n <td>2.230854</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>254</th>\n <td>[225, 593, 219, 217, 102, 116, 136, 167]</td>\n <td>2.230281</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>255</th>\n <td>[308, 400, 593, 572, 219, 217, 102, 116, 136, ...</td>\n <td>2.230276</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>256</th>\n <td>[225, 400, 593, 102, 167]</td>\n <td>2.228935</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>257</th>\n <td>[400, 593, 572, 217, 102, 116]</td>\n <td>2.228703</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>258</th>\n <td>[308, 225, 593, 102, 116, 136]</td>\n <td>2.228656</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>259</th>\n <td>[225, 400, 217, 239, 102, 116, 136, 167]</td>\n <td>2.227941</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>260</th>\n <td>[400, 102, 116, 136]</td>\n <td>2.227912</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>261</th>\n <td>[400, 572, 116, 136, 167]</td>\n <td>2.227651</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>262</th>\n <td>[308, 225, 400, 593, 219, 217, 102, 116, 136, ...</td>\n <td>2.227173</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>263</th>\n <td>[308, 225, 102, 116, 136, 167]</td>\n <td>2.227035</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>264</th>\n <td>[308, 225, 400, 593, 572, 219, 102, 116, 136, ...</td>\n <td>2.226914</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>265</th>\n <td>[308, 225, 400, 572, 102, 116, 136]</td>\n <td>2.226689</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>266</th>\n <td>[308, 225, 400, 572, 217, 102, 116, 136]</td>\n <td>2.226657</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>267</th>\n <td>[308, 225, 593, 217, 102, 116, 167]</td>\n <td>2.226193</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>268</th>\n <td>[400, 116, 136, 167]</td>\n <td>2.225774</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>269</th>\n <td>[308, 225, 593, 572, 217, 239, 102, 116, 136, ...</td>\n <td>2.225771</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>270</th>\n <td>[308, 593, 572, 217, 102, 116, 167]</td>\n <td>2.221343</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>271</th>\n <td>[400, 572, 217, 239, 102, 116, 136, 167]</td>\n <td>2.220788</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>272</th>\n <td>[400, 593, 217, 136, 167]</td>\n <td>2.220235</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>273</th>\n <td>[308, 400, 217, 102, 116, 167]</td>\n <td>2.218515</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>274</th>\n <td>[308, 225, 593, 239, 102, 116, 136, 167]</td>\n <td>2.218166</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>275</th>\n <td>[308, 225, 593, 572, 217, 102, 116, 167]</td>\n <td>2.217863</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>276</th>\n <td>[308, 225, 400, 572, 217, 102, 136, 167]</td>\n <td>2.217617</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>277</th>\n <td>[308, 225, 400, 102, 116, 167]</td>\n <td>2.217590</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>278</th>\n <td>[225, 400, 593, 136, 167]</td>\n <td>2.217063</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>279</th>\n <td>[308, 225, 400, 217, 102, 116, 167]</td>\n <td>2.217000</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>280</th>\n <td>[225, 400, 593, 116, 167]</td>\n <td>2.216807</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>281</th>\n <td>[225, 593, 572, 239, 102, 116, 136, 167]</td>\n <td>2.216337</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>282</th>\n <td>[225, 400, 593, 217, 116, 136]</td>\n <td>2.215648</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>283</th>\n <td>[225, 400, 593, 572, 102, 116]</td>\n <td>2.215323</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>284</th>\n <td>[308, 225, 593, 102, 136, 167]</td>\n <td>2.213891</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>285</th>\n <td>[308, 225, 400, 572, 102, 136, 167]</td>\n <td>2.213166</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>286</th>\n <td>[308, 400, 217, 239, 102, 116, 136, 167]</td>\n <td>2.212705</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>287</th>\n <td>[400, 593, 572, 217, 116, 136]</td>\n <td>2.212227</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>288</th>\n <td>[225, 400, 572, 219, 217, 102, 116, 136, 167]</td>\n <td>2.212029</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>289</th>\n <td>[225, 400, 593, 217, 102, 167]</td>\n <td>2.211868</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>290</th>\n <td>[400, 593, 572, 217, 102, 167]</td>\n <td>2.210591</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>291</th>\n <td>[400, 102, 136, 167]</td>\n <td>2.210323</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>292</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 102, 116, ...</td>\n <td>2.209953</td>\n <td>4</td>\n <td>7</td>\n </tr>\n <tr>\n <th>293</th>\n <td>[308, 400, 102, 116, 136]</td>\n <td>2.209900</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>294</th>\n <td>[225, 593, 239, 102, 116, 136, 167]</td>\n <td>2.208720</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>295</th>\n <td>[308, 593, 217, 102, 116, 167]</td>\n <td>2.208539</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>296</th>\n <td>[225, 593, 102, 116, 136]</td>\n <td>2.208064</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>297</th>\n <td>[308, 225, 593, 217, 116, 136, 167]</td>\n <td>2.207953</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>298</th>\n <td>[400, 593, 572, 102, 116]</td>\n <td>2.207611</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>299</th>\n <td>[308, 593, 572, 217, 116, 136, 167]</td>\n <td>2.207359</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>300</th>\n <td>[225, 593, 102, 136, 167]</td>\n <td>2.206437</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>301</th>\n <td>[400, 593, 217, 116, 167]</td>\n <td>2.205428</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>302</th>\n <td>[308, 225, 400, 116, 136, 167]</td>\n <td>2.204000</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>303</th>\n <td>[308, 225, 593, 572, 102, 116, 167]</td>\n <td>2.203942</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>304</th>\n <td>[400, 593, 572, 116, 136]</td>\n <td>2.203790</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>305</th>\n <td>[308, 400, 572, 102, 116, 136]</td>\n <td>2.203340</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>306</th>\n <td>[225, 400, 593, 572, 116, 136]</td>\n <td>2.203026</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>307</th>\n <td>[308, 225, 593, 102, 116, 167]</td>\n <td>2.202017</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>308</th>\n <td>[308, 400, 217, 116, 136, 167]</td>\n <td>2.201455</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>309</th>\n <td>[400, 593, 116, 167]</td>\n <td>2.201297</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>310</th>\n <td>[400, 593, 217, 239, 102, 116, 136]</td>\n <td>2.201072</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>311</th>\n <td>[308, 225, 593, 572, 217, 116, 136, 167]</td>\n <td>2.201031</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>312</th>\n <td>[225, 572, 217, 102, 136, 167]</td>\n <td>2.200572</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>313</th>\n <td>[308, 225, 593, 572, 239, 102, 116, 136, 167]</td>\n <td>2.199680</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>314</th>\n <td>[572, 219, 217, 102, 116, 136, 167]</td>\n <td>2.199069</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>315</th>\n <td>[225, 400, 593, 572, 217, 102, 116]</td>\n <td>2.198722</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>316</th>\n <td>[308, 225, 400, 217, 116, 136, 167]</td>\n <td>2.198333</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>317</th>\n <td>[225, 400, 572, 217, 239, 102, 116, 136, 167]</td>\n <td>2.197712</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>318</th>\n <td>[308, 225, 400, 217, 239, 102, 116, 136, 167]</td>\n <td>2.197554</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>319</th>\n <td>[308, 593, 217, 116, 136, 167]</td>\n <td>2.194212</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>320</th>\n <td>[308, 400, 572, 217, 102, 116, 167]</td>\n <td>2.193956</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>321</th>\n <td>[308, 225, 593, 572, 116, 136, 167]</td>\n <td>2.193903</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>322</th>\n <td>[400, 593, 572, 217, 136, 167]</td>\n <td>2.193849</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>323</th>\n <td>[400, 593, 219, 102, 116, 136]</td>\n <td>2.193278</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>324</th>\n <td>[308, 225, 593, 116, 136, 167]</td>\n <td>2.192902</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>325</th>\n <td>[400, 593, 136, 167]</td>\n <td>2.192217</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>326</th>\n <td>[400, 593, 102, 167]</td>\n <td>2.191150</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>327</th>\n <td>[225, 400, 593, 217, 136, 167]</td>\n <td>2.190834</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>328</th>\n <td>[308, 593, 239, 102, 116, 136, 167]</td>\n <td>2.190734</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>329</th>\n <td>[308, 593, 572, 239, 102, 116, 136, 167]</td>\n <td>2.190152</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>330</th>\n <td>[308, 400, 572, 102, 136, 167]</td>\n <td>2.189594</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>331</th>\n <td>[225, 400, 593, 572, 102, 167]</td>\n <td>2.189358</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>332</th>\n <td>[308, 593, 572, 102, 116, 136]</td>\n <td>2.188851</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>333</th>\n <td>[308, 400, 219, 102, 116, 136, 167]</td>\n <td>2.188674</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>334</th>\n <td>[308, 400, 593, 217, 102, 136]</td>\n <td>2.188118</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>335</th>\n <td>[593, 572, 102, 136, 167]</td>\n <td>2.187933</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>336</th>\n <td>[308, 400, 102, 136, 167]</td>\n <td>2.187604</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>337</th>\n <td>[308, 225, 400, 572, 217, 102, 116, 167]</td>\n <td>2.187602</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>338</th>\n <td>[308, 225, 400, 219, 102, 116, 136, 167]</td>\n <td>2.186656</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>339</th>\n <td>[308, 400, 219, 217, 102, 116, 136, 167]</td>\n <td>2.185868</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>340</th>\n <td>[400, 593, 217, 239, 102, 136, 167]</td>\n <td>2.185252</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>341</th>\n <td>[308, 225, 400, 593, 102, 136]</td>\n <td>2.184740</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>342</th>\n <td>[308, 593, 572, 102, 136, 167]</td>\n <td>2.184099</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>343</th>\n <td>[308, 400, 572, 217, 239, 102, 116, 136, 167]</td>\n <td>2.183807</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>344</th>\n <td>[308, 593, 572, 219, 217, 102, 116, 136, 167]</td>\n <td>2.183533</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>345</th>\n <td>[308, 225, 400, 572, 102, 116, 167]</td>\n <td>2.183478</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>346</th>\n <td>[572, 219, 102, 116, 136, 167]</td>\n <td>2.183138</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>347</th>\n <td>[225, 572, 217, 102, 116, 136]</td>\n <td>2.182002</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>348</th>\n <td>[225, 400, 593, 572, 217, 102, 167]</td>\n <td>2.181830</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>349</th>\n <td>[593, 572, 116, 136, 167]</td>\n <td>2.181302</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>350</th>\n <td>[593, 572, 239, 102, 116, 136, 167]</td>\n <td>2.181098</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>351</th>\n <td>[308, 593, 219, 217, 102, 116, 136, 167]</td>\n <td>2.180767</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>352</th>\n <td>[572, 217, 102, 136, 167]</td>\n <td>2.180764</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>353</th>\n <td>[219, 217, 102, 116, 136, 167]</td>\n <td>2.180408</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>354</th>\n <td>[225, 400, 593, 572, 217, 116, 136]</td>\n <td>2.179980</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>355</th>\n <td>[225, 400, 239, 102, 116, 136, 167]</td>\n <td>2.179876</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>356</th>\n <td>[308, 225, 593, 219, 102, 116, 136, 167]</td>\n <td>2.179490</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>357</th>\n <td>[593, 572, 217, 102, 136]</td>\n <td>2.179034</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>358</th>\n <td>[225, 400, 593, 219, 102, 116, 136]</td>\n <td>2.178827</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>359</th>\n <td>[308, 225, 400, 593, 217, 102, 136]</td>\n <td>2.178707</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>360</th>\n <td>[308, 400, 572, 217, 116, 136, 167]</td>\n <td>2.178139</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>361</th>\n <td>[225, 400, 593, 217, 116, 167]</td>\n <td>2.177669</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>362</th>\n <td>[400, 593, 219, 217, 102, 116, 136]</td>\n <td>2.177334</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>363</th>\n <td>[400, 593, 572, 102, 167]</td>\n <td>2.177294</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>364</th>\n <td>[225, 572, 217, 102, 116, 167]</td>\n <td>2.177094</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>365</th>\n <td>[225, 400, 593, 572, 136, 167]</td>\n <td>2.176748</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>366</th>\n <td>[308, 593, 572, 219, 102, 116, 136, 167]</td>\n <td>2.176209</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>367</th>\n <td>[308, 225, 593, 572, 219, 102, 116, 136, 167]</td>\n <td>2.175828</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>368</th>\n <td>[225, 572, 219, 102, 116, 136, 167]</td>\n <td>2.175802</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>369</th>\n <td>[225, 400, 593, 217, 239, 102, 116, 136]</td>\n <td>2.175259</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>370</th>\n <td>[308, 225, 400, 239, 102, 116, 136, 167]</td>\n <td>2.174948</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>371</th>\n <td>[593, 572, 102, 116, 167]</td>\n <td>2.174591</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>372</th>\n <td>[400, 593, 572, 219, 102, 116, 136]</td>\n <td>2.172958</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>373</th>\n <td>[400, 593, 572, 136, 167]</td>\n <td>2.172927</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>374</th>\n <td>[308, 400, 593, 572, 217, 102, 136]</td>\n <td>2.172034</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>375</th>\n <td>[400, 593, 572, 217, 239, 102, 116, 136]</td>\n <td>2.170807</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>376</th>\n <td>[308, 225, 400, 572, 217, 116, 136, 167]</td>\n <td>2.170672</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>377</th>\n <td>[308, 225, 400, 219, 217, 102, 116, 136, 167]</td>\n <td>2.170431</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>378</th>\n <td>[308, 225, 593, 219, 217, 102, 116, 136, 167]</td>\n <td>2.170370</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>379</th>\n <td>[308, 225, 400, 572, 116, 136, 167]</td>\n <td>2.170329</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>380</th>\n <td>[308, 400, 572, 219, 102, 116, 136, 167]</td>\n <td>2.170261</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>381</th>\n <td>[308, 400, 102, 116, 167]</td>\n <td>2.169806</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>382</th>\n <td>[308, 400, 572, 219, 217, 102, 116, 136, 167]</td>\n <td>2.169559</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>383</th>\n <td>[308, 225, 400, 572, 217, 239, 102, 116, 136, ...</td>\n <td>2.169306</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>384</th>\n <td>[225, 219, 102, 116, 136, 167]</td>\n <td>2.168190</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>385</th>\n <td>[400, 593, 219, 102, 136, 167]</td>\n <td>2.168060</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>386</th>\n <td>[308, 225, 593, 572, 219, 217, 102, 116, 136, ...</td>\n <td>2.166577</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>387</th>\n <td>[308, 593, 219, 102, 116, 136, 167]</td>\n <td>2.165621</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>388</th>\n <td>[308, 572, 102, 116, 136, 167]</td>\n <td>2.165222</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>389</th>\n <td>[308, 225, 400, 572, 219, 102, 116, 136, 167]</td>\n <td>2.164623</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>390</th>\n <td>[593, 572, 102, 116, 136]</td>\n <td>2.164414</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>391</th>\n <td>[225, 400, 593, 572, 217, 136, 167]</td>\n <td>2.162902</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>392</th>\n <td>[400, 593, 572, 219, 217, 102, 116, 136]</td>\n <td>2.161780</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>393</th>\n <td>[308, 400, 116, 136, 167]</td>\n <td>2.161599</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>394</th>\n <td>[308, 400, 593, 217, 239, 102, 116, 136]</td>\n <td>2.161274</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>395</th>\n <td>[308, 225, 400, 593, 102, 116]</td>\n <td>2.161186</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>396</th>\n <td>[308, 225, 400, 593, 572, 102, 136]</td>\n <td>2.160970</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>397</th>\n <td>[400, 593, 572, 217, 116, 167]</td>\n <td>2.160817</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>398</th>\n <td>[400, 593, 217, 239, 116, 136, 167]</td>\n <td>2.160537</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>399</th>\n <td>[308, 400, 593, 102, 136]</td>\n <td>2.160490</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>400</th>\n <td>[400, 593, 219, 217, 102, 136, 167]</td>\n <td>2.160338</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>401</th>\n <td>[225, 400, 593, 217, 239, 102, 136, 167]</td>\n <td>2.160319</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>402</th>\n <td>[400, 593, 572, 217, 239, 102, 136, 167]</td>\n <td>2.160197</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>403</th>\n <td>[225, 572, 219, 217, 102, 116, 136, 167]</td>\n <td>2.159763</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>404</th>\n <td>[308, 225, 400, 593, 572, 217, 102, 136]</td>\n <td>2.158962</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>405</th>\n <td>[308, 400, 593, 217, 102, 116]</td>\n <td>2.157751</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>406</th>\n <td>[308, 400, 239, 102, 116, 136, 167]</td>\n <td>2.157584</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>407</th>\n <td>[225, 400, 593, 219, 102, 136, 167]</td>\n <td>2.156935</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>408</th>\n <td>[225, 400, 572, 239, 102, 116, 136, 167]</td>\n <td>2.156410</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>409</th>\n <td>[225, 219, 217, 102, 116, 136, 167]</td>\n <td>2.156241</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>410</th>\n <td>[400, 593, 217, 239, 102, 116, 167]</td>\n <td>2.156163</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>411</th>\n <td>[225, 400, 593, 572, 219, 102, 116, 136]</td>\n <td>2.155700</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>412</th>\n <td>[400, 593, 572, 219, 102, 136, 167]</td>\n <td>2.155325</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>413</th>\n <td>[308, 400, 572, 102, 116, 167]</td>\n <td>2.154775</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>414</th>\n <td>[572, 217, 102, 116, 167]</td>\n <td>2.154620</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>415</th>\n <td>[225, 400, 593, 572, 116, 167]</td>\n <td>2.154039</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>416</th>\n <td>[308, 225, 400, 593, 217, 102, 116]</td>\n <td>2.153768</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>417</th>\n <td>[308, 225, 400, 572, 219, 217, 102, 116, 136, ...</td>\n <td>2.153418</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>418</th>\n <td>[225, 593, 572, 217, 102, 136]</td>\n <td>2.152933</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>419</th>\n <td>[225, 400, 593, 219, 217, 102, 116, 136]</td>\n <td>2.151566</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>420</th>\n <td>[308, 225, 400, 593, 116, 136]</td>\n <td>2.151448</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>421</th>\n <td>[308, 400, 593, 572, 102, 136]</td>\n <td>2.149819</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>422</th>\n <td>[400, 593, 572, 219, 217, 102, 136, 167]</td>\n <td>2.149518</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>423</th>\n <td>[225, 400, 593, 239, 102, 116, 136]</td>\n <td>2.149212</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>424</th>\n <td>[308, 217, 239, 102, 116, 136, 167]</td>\n <td>2.148394</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>425</th>\n <td>[225, 400, 593, 572, 217, 239, 102, 116, 136]</td>\n <td>2.147143</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>426</th>\n <td>[308, 593, 572, 102, 116, 167]</td>\n <td>2.146784</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>427</th>\n <td>[225, 217, 102, 116, 167]</td>\n <td>2.146740</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>428</th>\n <td>[308, 225, 400, 593, 217, 239, 102, 116, 136]</td>\n <td>2.146527</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>429</th>\n <td>[308, 225, 400, 572, 239, 102, 116, 136, 167]</td>\n <td>2.146500</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>430</th>\n <td>[400, 593, 572, 116, 167]</td>\n <td>2.145754</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>431</th>\n <td>[308, 400, 593, 217, 239, 102, 136, 167]</td>\n <td>2.145550</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>432</th>\n <td>[308, 400, 572, 116, 136, 167]</td>\n <td>2.145388</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>433</th>\n <td>[308, 400, 593, 217, 116, 136]</td>\n <td>2.145077</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>434</th>\n <td>[572, 217, 239, 102, 116, 136, 167]</td>\n <td>2.144777</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>435</th>\n <td>[308, 225, 217, 239, 102, 116, 136, 167]</td>\n <td>2.144262</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>436</th>\n <td>[308, 593, 572, 116, 136, 167]</td>\n <td>2.144214</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>437</th>\n <td>[308, 225, 572, 217, 102, 116, 136]</td>\n <td>2.143902</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>438</th>\n <td>[308, 225, 572, 217, 102, 136, 167]</td>\n <td>2.142517</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>439</th>\n <td>[225, 400, 593, 572, 219, 102, 136, 167]</td>\n <td>2.139573</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>440</th>\n <td>[308, 225, 400, 593, 217, 116, 136]</td>\n <td>2.139140</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>441</th>\n <td>[572, 217, 102, 116, 136]</td>\n <td>2.139133</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>442</th>\n <td>[225, 572, 217, 116, 136, 167]</td>\n <td>2.137901</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>443</th>\n <td>[308, 572, 217, 239, 102, 116, 136, 167]</td>\n <td>2.137466</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>444</th>\n <td>[225, 400, 593, 572, 217, 116, 167]</td>\n <td>2.137397</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>445</th>\n <td>[225, 400, 593, 217, 239, 102, 116, 167]</td>\n <td>2.137169</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>446</th>\n <td>[225, 400, 593, 572, 217, 239, 102, 136, 167]</td>\n <td>2.136356</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>447</th>\n <td>[225, 400, 593, 572, 219, 217, 102, 116, 136]</td>\n <td>2.136047</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>448</th>\n <td>[225, 400, 593, 219, 217, 102, 136, 167]</td>\n <td>2.136021</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>449</th>\n <td>[308, 400, 572, 239, 102, 116, 136, 167]</td>\n <td>2.135960</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>450</th>\n <td>[308, 400, 593, 572, 217, 239, 102, 116, 136]</td>\n <td>2.135096</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>451</th>\n <td>[308, 400, 593, 572, 217, 102, 116]</td>\n <td>2.135031</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>452</th>\n <td>[225, 400, 593, 217, 239, 116, 136, 167]</td>\n <td>2.134633</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>453</th>\n <td>[225, 217, 239, 102, 116, 136, 167]</td>\n <td>2.134433</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>454</th>\n <td>[400, 239, 102, 116, 136, 167]</td>\n <td>2.134154</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>455</th>\n <td>[225, 572, 217, 239, 102, 116, 136, 167]</td>\n <td>2.133859</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>456</th>\n <td>[308, 400, 593, 217, 102, 167]</td>\n <td>2.133741</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>457</th>\n <td>[308, 400, 593, 102, 116]</td>\n <td>2.133486</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>458</th>\n <td>[308, 225, 400, 593, 217, 102, 167]</td>\n <td>2.132777</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>459</th>\n <td>[400, 593, 239, 102, 116, 136]</td>\n <td>2.132591</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>460</th>\n <td>[308, 225, 217, 102, 116, 136]</td>\n <td>2.132448</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>461</th>\n <td>[308, 225, 400, 593, 239, 102, 116, 136]</td>\n <td>2.132442</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>462</th>\n <td>[400, 572, 239, 102, 116, 136, 167]</td>\n <td>2.132256</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>463</th>\n <td>[308, 225, 400, 593, 217, 239, 102, 136, 167]</td>\n <td>2.132080</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>464</th>\n <td>[308, 225, 400, 593, 102, 167]</td>\n <td>2.131481</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>465</th>\n <td>[219, 102, 116, 136, 167]</td>\n <td>2.131075</td>\n <td>4</td>\n <td>1</td>\n </tr>\n <tr>\n <th>466</th>\n <td>[593, 572, 217, 102, 116]</td>\n <td>2.130640</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>467</th>\n <td>[308, 572, 217, 102, 136, 167]</td>\n <td>2.129723</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>468</th>\n <td>[308, 225, 400, 593, 572, 102, 116]</td>\n <td>2.129514</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>469</th>\n <td>[308, 400, 593, 116, 136]</td>\n <td>2.129058</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>470</th>\n <td>[308, 225, 400, 593, 572, 217, 102, 116]</td>\n <td>2.128897</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>471</th>\n <td>[400, 593, 219, 102, 116, 167]</td>\n <td>2.128166</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>472</th>\n <td>[225, 400, 593, 239, 102, 136, 167]</td>\n <td>2.127439</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>473</th>\n <td>[308, 225, 572, 217, 239, 102, 116, 136, 167]</td>\n <td>2.126843</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>474</th>\n <td>[308, 225, 217, 102, 136, 167]</td>\n <td>2.126550</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>475</th>\n <td>[593, 572, 217, 102, 167]</td>\n <td>2.126512</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>476</th>\n <td>[217, 102, 116, 136, 167]</td>\n <td>2.126242</td>\n <td>4</td>\n <td>1</td>\n </tr>\n <tr>\n <th>477</th>\n <td>[308, 572, 217, 102, 116, 136]</td>\n <td>2.125874</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>478</th>\n <td>[225, 400, 593, 219, 102, 116, 167]</td>\n <td>2.125376</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>479</th>\n <td>[400, 593, 572, 217, 239, 116, 136, 167]</td>\n <td>2.124762</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>480</th>\n <td>[225, 217, 102, 136, 167]</td>\n <td>2.124616</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>481</th>\n <td>[308, 400, 593, 239, 102, 116, 136]</td>\n <td>2.124541</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>482</th>\n <td>[225, 400, 593, 572, 219, 217, 102, 136, 167]</td>\n <td>2.124256</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>483</th>\n <td>[400, 593, 572, 217, 239, 102, 116, 167]</td>\n <td>2.123879</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>484</th>\n <td>[400, 593, 219, 217, 102, 116, 167]</td>\n <td>2.123357</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>485</th>\n <td>[308, 400, 593, 572, 217, 239, 102, 136, 167]</td>\n <td>2.123251</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>486</th>\n <td>[308, 400, 593, 572, 217, 116, 136]</td>\n <td>2.122837</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>487</th>\n <td>[308, 225, 400, 593, 572, 217, 239, 102, 116, ...</td>\n <td>2.121861</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>488</th>\n <td>[308, 225, 400, 593, 136, 167]</td>\n <td>2.121472</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>489</th>\n <td>[225, 400, 593, 572, 239, 102, 116, 136]</td>\n <td>2.121256</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>490</th>\n <td>[308, 400, 593, 217, 136, 167]</td>\n <td>2.120870</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>491</th>\n <td>[400, 593, 219, 217, 239, 102, 116, 136, 167]</td>\n <td>2.119997</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>492</th>\n <td>[308, 225, 400, 593, 572, 116, 136]</td>\n <td>2.119572</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>493</th>\n <td>[225, 400, 217, 102, 136]</td>\n <td>2.118817</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>494</th>\n <td>[225, 593, 217, 102, 136]</td>\n <td>2.118621</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>495</th>\n <td>[225, 593, 572, 217, 102, 116]</td>\n <td>2.118337</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>496</th>\n <td>[308, 225, 400, 593, 217, 136, 167]</td>\n <td>2.118034</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>497</th>\n <td>[217, 239, 102, 116, 136, 167]</td>\n <td>2.118021</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>498</th>\n <td>[308, 225, 400, 593, 219, 102, 116, 136]</td>\n <td>2.117863</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>499</th>\n <td>[308, 400, 593, 217, 239, 116, 136, 167]</td>\n <td>2.117782</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>500</th>\n <td>[308, 400, 593, 217, 239, 102, 116, 167]</td>\n <td>2.117512</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>501</th>\n <td>[308, 400, 593, 572, 217, 102, 167]</td>\n <td>2.117446</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>502</th>\n <td>[308, 400, 593, 219, 102, 116, 136]</td>\n <td>2.117090</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>503</th>\n <td>[400, 572, 217, 102, 136]</td>\n <td>2.117062</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>504</th>\n <td>[400, 217, 102, 136]</td>\n <td>2.116898</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>505</th>\n <td>[225, 593, 572, 102, 136]</td>\n <td>2.115813</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>506</th>\n <td>[308, 400, 593, 219, 217, 102, 116, 136]</td>\n <td>2.115701</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>507</th>\n <td>[593, 217, 239, 102, 116, 136]</td>\n <td>2.115664</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>508</th>\n <td>[572, 217, 116, 136, 167]</td>\n <td>2.115607</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>509</th>\n <td>[308, 572, 219, 217, 102, 116, 136, 167]</td>\n <td>2.115378</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>510</th>\n <td>[308, 225, 400, 593, 572, 217, 116, 136]</td>\n <td>2.115302</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>511</th>\n <td>[225, 400, 593, 239, 116, 136, 167]</td>\n <td>2.115282</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>512</th>\n <td>[593, 572, 217, 239, 102, 116, 136]</td>\n <td>2.115066</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>513</th>\n <td>[593, 572, 217, 239, 102, 136, 167]</td>\n <td>2.114737</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>514</th>\n <td>[593, 239, 102, 116, 136, 167]</td>\n <td>2.113986</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>515</th>\n <td>[400, 593, 572, 239, 102, 116, 136]</td>\n <td>2.113698</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>516</th>\n <td>[308, 225, 400, 593, 239, 102, 136, 167]</td>\n <td>2.113098</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>517</th>\n <td>[225, 593, 217, 102, 116]</td>\n <td>2.113059</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>518</th>\n <td>[308, 225, 400, 593, 572, 217, 102, 167]</td>\n <td>2.112926</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>519</th>\n <td>[308, 225, 217, 102, 116, 167]</td>\n <td>2.112707</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>520</th>\n <td>[308, 225, 572, 217, 102, 116, 167]</td>\n <td>2.112434</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>521</th>\n <td>[308, 400, 593, 572, 102, 116]</td>\n <td>2.111825</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>522</th>\n <td>[225, 217, 102, 116, 136]</td>\n <td>2.111635</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>523</th>\n <td>[308, 593, 102, 116, 136]</td>\n <td>2.110894</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>524</th>\n <td>[308, 225, 400, 593, 572, 217, 239, 102, 136, ...</td>\n <td>2.110584</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>525</th>\n <td>[308, 219, 217, 102, 116, 136, 167]</td>\n <td>2.110462</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>526</th>\n <td>[593, 217, 239, 102, 136, 167]</td>\n <td>2.110017</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>527</th>\n <td>[400, 593, 572, 219, 102, 116, 167]</td>\n <td>2.109048</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>528</th>\n <td>[308, 225, 400, 593, 217, 239, 102, 116, 167]</td>\n <td>2.108890</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>529</th>\n <td>[225, 593, 572, 217, 102, 167]</td>\n <td>2.108503</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>530</th>\n <td>[400, 593, 572, 219, 217, 102, 116, 167]</td>\n <td>2.108398</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>531</th>\n <td>[225, 400, 593, 239, 102, 116, 167]</td>\n <td>2.108396</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>532</th>\n <td>[400, 593, 239, 102, 136, 167]</td>\n <td>2.107869</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>533</th>\n <td>[308, 225, 400, 593, 572, 102, 167]</td>\n <td>2.107613</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>534</th>\n <td>[225, 400, 593, 572, 217, 239, 102, 116, 167]</td>\n <td>2.107595</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>535</th>\n <td>[308, 225, 219, 102, 116, 136, 167]</td>\n <td>2.107374</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>536</th>\n <td>[400, 593, 219, 116, 136, 167]</td>\n <td>2.106799</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>537</th>\n <td>[225, 400, 593, 219, 217, 102, 116, 167]</td>\n <td>2.106742</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>538</th>\n <td>[308, 225, 400, 593, 116, 167]</td>\n <td>2.106459</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>539</th>\n <td>[593, 572, 217, 116, 136]</td>\n <td>2.106441</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>540</th>\n <td>[308, 225, 400, 593, 219, 217, 102, 116, 136]</td>\n <td>2.106050</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>541</th>\n <td>[308, 225, 219, 217, 102, 116, 136, 167]</td>\n <td>2.105916</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>542</th>\n <td>[225, 400, 593, 572, 239, 102, 136, 167]</td>\n <td>2.105863</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>543</th>\n <td>[308, 593, 217, 239, 102, 116, 136]</td>\n <td>2.105856</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>544</th>\n <td>[308, 225, 400, 593, 572, 239, 102, 116, 136]</td>\n <td>2.105626</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>545</th>\n <td>[308, 400, 593, 572, 116, 136]</td>\n <td>2.105606</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>546</th>\n <td>[308, 225, 400, 593, 217, 239, 116, 136, 167]</td>\n <td>2.105452</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>547</th>\n <td>[400, 593, 239, 116, 136, 167]</td>\n <td>2.105292</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>548</th>\n <td>[308, 400, 593, 572, 217, 136, 167]</td>\n <td>2.105104</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>549</th>\n <td>[308, 225, 572, 219, 102, 116, 136, 167]</td>\n <td>2.104995</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>550</th>\n <td>[225, 400, 217, 102, 116]</td>\n <td>2.104554</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>551</th>\n <td>[225, 400, 572, 217, 102, 136]</td>\n <td>2.104290</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>552</th>\n <td>[308, 400, 593, 572, 219, 217, 102, 116, 136]</td>\n <td>2.104253</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>553</th>\n <td>[225, 400, 593, 219, 116, 136, 167]</td>\n <td>2.103798</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>554</th>\n <td>[225, 400, 593, 572, 217, 239, 116, 136, 167]</td>\n <td>2.103641</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>555</th>\n <td>[308, 400, 593, 572, 219, 102, 116, 136]</td>\n <td>2.103419</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>556</th>\n <td>[308, 225, 572, 219, 217, 102, 116, 136, 167]</td>\n <td>2.103319</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>557</th>\n <td>[225, 400, 593, 572, 219, 102, 116, 167]</td>\n <td>2.103056</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>558</th>\n <td>[308, 400, 593, 239, 102, 136, 167]</td>\n <td>2.102751</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>559</th>\n <td>[400, 593, 572, 219, 217, 239, 102, 116, 136, ...</td>\n <td>2.102336</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>560</th>\n <td>[400, 593, 219, 239, 102, 116, 136, 167]</td>\n <td>2.101766</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>561</th>\n <td>[593, 572, 217, 136, 167]</td>\n <td>2.101744</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>562</th>\n <td>[400, 217, 102, 116]</td>\n <td>2.101587</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>563</th>\n <td>[593, 217, 239, 116, 136, 167]</td>\n <td>2.101368</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>564</th>\n <td>[308, 225, 400, 593, 572, 219, 102, 116, 136]</td>\n <td>2.101362</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>565</th>\n <td>[225, 593, 217, 239, 102, 116, 136]</td>\n <td>2.101351</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>566</th>\n <td>[308, 400, 593, 572, 239, 102, 116, 136]</td>\n <td>2.100685</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>567</th>\n <td>[308, 400, 593, 219, 217, 102, 136, 167]</td>\n <td>2.099963</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>568</th>\n <td>[308, 225, 400, 593, 217, 116, 167]</td>\n <td>2.099843</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>569</th>\n <td>[225, 400, 593, 219, 217, 239, 102, 116, 136, ...</td>\n <td>2.099833</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>570</th>\n <td>[400, 593, 219, 217, 116, 136, 167]</td>\n <td>2.099832</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>571</th>\n <td>[225, 217, 116, 136, 167]</td>\n <td>2.099567</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>572</th>\n <td>[308, 400, 593, 217, 116, 167]</td>\n <td>2.099339</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>573</th>\n <td>[308, 225, 400, 593, 572, 217, 136, 167]</td>\n <td>2.099228</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>574</th>\n <td>[593, 572, 219, 217, 102, 116, 136]</td>\n <td>2.099080</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>575</th>\n <td>[308, 225, 400, 593, 219, 102, 136, 167]</td>\n <td>2.099072</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>576</th>\n <td>[308, 400, 593, 102, 167]</td>\n <td>2.098293</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>577</th>\n <td>[308, 225, 400, 593, 572, 136, 167]</td>\n <td>2.097492</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>578</th>\n <td>[400, 593, 572, 239, 102, 136, 167]</td>\n <td>2.097280</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>579</th>\n <td>[308, 225, 572, 102, 116, 136]</td>\n <td>2.096814</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>580</th>\n <td>[225, 400, 102, 116]</td>\n <td>2.096659</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>581</th>\n <td>[400, 219, 102, 116, 136]</td>\n <td>2.096445</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>582</th>\n <td>[308, 593, 102, 136, 167]</td>\n <td>2.096044</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>583</th>\n <td>[308, 400, 593, 219, 102, 136, 167]</td>\n <td>2.095909</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>584</th>\n <td>[308, 225, 593, 217, 239, 102, 116, 136]</td>\n <td>2.095742</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>585</th>\n <td>[308, 572, 219, 102, 116, 136, 167]</td>\n <td>2.095689</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>586</th>\n <td>[225, 400, 593, 219, 239, 102, 116, 136, 167]</td>\n <td>2.094579</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>587</th>\n <td>[400, 219, 217, 102, 116, 136]</td>\n <td>2.094057</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>588</th>\n <td>[225, 400, 219, 102, 116, 136]</td>\n <td>2.093727</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>589</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 102, 116, ...</td>\n <td>2.093720</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>590</th>\n <td>[225, 593, 217, 102, 167]</td>\n <td>2.093450</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>591</th>\n <td>[308, 400, 593, 136, 167]</td>\n <td>2.093344</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>592</th>\n <td>[225, 400, 102, 136]</td>\n <td>2.093275</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>593</th>\n <td>[308, 593, 217, 239, 102, 136, 167]</td>\n <td>2.093226</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>594</th>\n <td>[308, 225, 400, 593, 239, 116, 136, 167]</td>\n <td>2.092823</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>595</th>\n <td>[308, 572, 217, 102, 116, 167]</td>\n <td>2.092497</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>596</th>\n <td>[593, 572, 219, 217, 102, 136, 167]</td>\n <td>2.092424</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>597</th>\n <td>[225, 593, 572, 102, 116]</td>\n <td>2.092021</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>598</th>\n <td>[225, 593, 217, 239, 102, 136, 167]</td>\n <td>2.091903</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>599</th>\n <td>[308, 400, 593, 572, 219, 217, 102, 136, 167]</td>\n <td>2.091887</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>600</th>\n <td>[308, 400, 593, 572, 217, 239, 102, 116, 167]</td>\n <td>2.091792</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>601</th>\n <td>[308, 225, 572, 102, 136, 167]</td>\n <td>2.091706</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>602</th>\n <td>[308, 225, 400, 593, 219, 217, 102, 136, 167]</td>\n <td>2.091689</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>603</th>\n <td>[225, 593, 572, 217, 239, 102, 116, 136]</td>\n <td>2.091559</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>604</th>\n <td>[225, 400, 593, 572, 219, 217, 102, 116, 167]</td>\n <td>2.091513</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>605</th>\n <td>[308, 593, 572, 217, 239, 102, 116, 136]</td>\n <td>2.091305</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>606</th>\n <td>[308, 400, 593, 219, 217, 239, 102, 116, 136, ...</td>\n <td>2.091270</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>607</th>\n <td>[308, 225, 400, 593, 572, 239, 102, 136, 167]</td>\n <td>2.090803</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>608</th>\n <td>[308, 225, 400, 593, 239, 102, 116, 167]</td>\n <td>2.090783</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>609</th>\n <td>[225, 593, 572, 217, 116, 136]</td>\n <td>2.090780</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>610</th>\n <td>[308, 593, 116, 136, 167]</td>\n <td>2.090586</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>611</th>\n <td>[308, 400, 593, 572, 217, 239, 116, 136, 167]</td>\n <td>2.090387</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>612</th>\n <td>[308, 593, 102, 116, 167]</td>\n <td>2.090099</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>613</th>\n <td>[400, 593, 572, 219, 116, 136, 167]</td>\n <td>2.089899</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>614</th>\n <td>[593, 572, 219, 102, 116, 136]</td>\n <td>2.089537</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>615</th>\n <td>[308, 225, 593, 572, 217, 102, 136]</td>\n <td>2.089429</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>616</th>\n <td>[308, 225, 572, 217, 116, 136, 167]</td>\n <td>2.089053</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>617</th>\n <td>[308, 593, 572, 217, 102, 136]</td>\n <td>2.087797</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>618</th>\n <td>[400, 593, 572, 219, 217, 116, 136, 167]</td>\n <td>2.087495</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>619</th>\n <td>[308, 400, 593, 572, 219, 102, 136, 167]</td>\n <td>2.087114</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>620</th>\n <td>[308, 400, 593, 572, 102, 167]</td>\n <td>2.086814</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>621</th>\n <td>[225, 593, 572, 217, 239, 102, 136, 167]</td>\n <td>2.086615</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>622</th>\n <td>[308, 225, 400, 593, 572, 219, 102, 136, 167]</td>\n <td>2.086497</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>623</th>\n <td>[308, 225, 217, 116, 136, 167]</td>\n <td>2.086180</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>624</th>\n <td>[400, 593, 239, 102, 116, 167]</td>\n <td>2.086178</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>625</th>\n <td>[593, 217, 239, 102, 116, 167]</td>\n <td>2.085636</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>626</th>\n <td>[225, 593, 572, 219, 102, 116, 136]</td>\n <td>2.085181</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>627</th>\n <td>[308, 400, 593, 239, 116, 136, 167]</td>\n <td>2.084752</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>628</th>\n <td>[308, 400, 593, 572, 239, 102, 136, 167]</td>\n <td>2.084548</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>629</th>\n <td>[225, 400, 593, 219, 217, 116, 136, 167]</td>\n <td>2.084493</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>630</th>\n <td>[308, 225, 400, 593, 572, 217, 239, 102, 116, ...</td>\n <td>2.084488</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>631</th>\n <td>[225, 400, 593, 572, 219, 217, 239, 102, 116, ...</td>\n <td>2.083848</td>\n <td>4</td>\n <td>7</td>\n </tr>\n <tr>\n <th>632</th>\n <td>[400, 593, 572, 219, 239, 102, 116, 136, 167]</td>\n <td>2.083836</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>633</th>\n <td>[225, 400, 593, 572, 219, 116, 136, 167]</td>\n <td>2.083814</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>634</th>\n <td>[308, 593, 572, 217, 239, 102, 136, 167]</td>\n <td>2.083174</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>635</th>\n <td>[308, 225, 593, 217, 239, 102, 136, 167]</td>\n <td>2.083150</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>636</th>\n <td>[225, 572, 102, 116, 167]</td>\n <td>2.082763</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>637</th>\n <td>[225, 400, 572, 102, 136]</td>\n <td>2.082625</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>638</th>\n <td>[593, 219, 217, 102, 116, 136]</td>\n <td>2.082404</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>639</th>\n <td>[308, 225, 593, 217, 102, 136]</td>\n <td>2.082178</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>640</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 102, 136, ...</td>\n <td>2.082138</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>641</th>\n <td>[308, 225, 239, 102, 116, 136, 167]</td>\n <td>2.081237</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>642</th>\n <td>[225, 593, 217, 116, 136]</td>\n <td>2.081126</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>643</th>\n <td>[225, 400, 593, 572, 239, 116, 136, 167]</td>\n <td>2.080720</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>644</th>\n <td>[308, 219, 102, 116, 136, 167]</td>\n <td>2.080550</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>645</th>\n <td>[225, 593, 572, 217, 136, 167]</td>\n <td>2.080451</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>646</th>\n <td>[308, 225, 400, 593, 572, 217, 239, 116, 136, ...</td>\n <td>2.080310</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>647</th>\n <td>[308, 400, 593, 572, 136, 167]</td>\n <td>2.080304</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>648</th>\n <td>[400, 572, 219, 217, 102, 116, 136]</td>\n <td>2.080140</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>649</th>\n <td>[308, 225, 400, 593, 219, 217, 239, 102, 116, ...</td>\n <td>2.080032</td>\n <td>4</td>\n <td>7</td>\n </tr>\n <tr>\n <th>650</th>\n <td>[593, 217, 102, 116]</td>\n <td>2.079443</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>651</th>\n <td>[593, 572, 217, 239, 116, 136, 167]</td>\n <td>2.079313</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>652</th>\n <td>[225, 400, 217, 102, 167]</td>\n <td>2.079258</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>653</th>\n <td>[308, 225, 593, 572, 217, 239, 102, 116, 136]</td>\n <td>2.079048</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>654</th>\n <td>[400, 572, 217, 102, 116]</td>\n <td>2.078555</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>655</th>\n <td>[225, 593, 219, 102, 116, 136]</td>\n <td>2.078506</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>656</th>\n <td>[225, 400, 593, 572, 239, 102, 116, 167]</td>\n <td>2.077919</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>657</th>\n <td>[593, 572, 219, 102, 136, 167]</td>\n <td>2.077815</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>658</th>\n <td>[400, 572, 219, 102, 116, 136]</td>\n <td>2.077717</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>659</th>\n <td>[308, 400, 593, 116, 167]</td>\n <td>2.077381</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>660</th>\n <td>[308, 400, 593, 219, 239, 102, 116, 136, 167]</td>\n <td>2.077263</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>661</th>\n <td>[400, 219, 217, 102, 136, 167]</td>\n <td>2.076952</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>662</th>\n <td>[308, 217, 102, 116, 136]</td>\n <td>2.076824</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>663</th>\n <td>[225, 572, 102, 136, 167]</td>\n <td>2.076640</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>664</th>\n <td>[308, 400, 593, 239, 102, 116, 167]</td>\n <td>2.076549</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>665</th>\n <td>[593, 217, 102, 136]</td>\n <td>2.076472</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>666</th>\n <td>[308, 400, 593, 572, 219, 217, 239, 102, 116, ...</td>\n <td>2.076146</td>\n <td>4</td>\n <td>7</td>\n </tr>\n <tr>\n <th>667</th>\n <td>[225, 400, 593, 572, 219, 239, 102, 116, 136, ...</td>\n <td>2.076115</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>668</th>\n <td>[308, 400, 593, 572, 217, 116, 167]</td>\n <td>2.076106</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>669</th>\n <td>[225, 593, 572, 116, 136]</td>\n <td>2.075975</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>670</th>\n <td>[593, 572, 217, 116, 167]</td>\n <td>2.075860</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>671</th>\n <td>[308, 225, 400, 593, 572, 217, 116, 167]</td>\n <td>2.075308</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>672</th>\n <td>[308, 225, 400, 593, 219, 239, 102, 116, 136, ...</td>\n <td>2.075283</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>673</th>\n <td>[225, 400, 219, 217, 102, 116, 136]</td>\n <td>2.075090</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>674</th>\n <td>[308, 225, 400, 217, 102, 136]</td>\n <td>2.075020</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>675</th>\n <td>[225, 400, 572, 217, 102, 116]</td>\n <td>2.074980</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>676</th>\n <td>[308, 225, 572, 239, 102, 116, 136, 167]</td>\n <td>2.074832</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>677</th>\n <td>[225, 400, 217, 116, 136]</td>\n <td>2.074761</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>678</th>\n <td>[308, 217, 102, 136, 167]</td>\n <td>2.074746</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>679</th>\n <td>[225, 593, 572, 219, 217, 102, 116, 136]</td>\n <td>2.074339</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>680</th>\n <td>[400, 593, 572, 239, 116, 136, 167]</td>\n <td>2.074275</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>681</th>\n <td>[225, 400, 116, 136]</td>\n <td>2.073706</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>682</th>\n <td>[308, 225, 400, 593, 572, 116, 167]</td>\n <td>2.073667</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>683</th>\n <td>[225, 593, 217, 239, 116, 136, 167]</td>\n <td>2.073072</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>684</th>\n <td>[225, 593, 217, 239, 102, 116, 167]</td>\n <td>2.072637</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>685</th>\n <td>[225, 593, 572, 219, 102, 136, 167]</td>\n <td>2.072372</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>686</th>\n <td>[225, 593, 217, 116, 167]</td>\n <td>2.072345</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>687</th>\n <td>[225, 593, 572, 102, 167]</td>\n <td>2.072223</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>688</th>\n <td>[400, 217, 116, 136]</td>\n <td>2.072198</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>689</th>\n <td>[400, 217, 102, 167]</td>\n <td>2.072103</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>690</th>\n <td>[593, 572, 217, 239, 102, 116, 167]</td>\n <td>2.071947</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>691</th>\n <td>[308, 225, 400, 593, 219, 102, 116, 167]</td>\n <td>2.071706</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>692</th>\n <td>[225, 400, 593, 572, 219, 217, 116, 136, 167]</td>\n <td>2.071618</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>693</th>\n <td>[225, 593, 116, 167]</td>\n <td>2.071516</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>694</th>\n <td>[225, 400, 572, 219, 102, 116, 136]</td>\n <td>2.071334</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>695</th>\n <td>[593, 219, 217, 239, 102, 116, 136, 167]</td>\n <td>2.070955</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>696</th>\n <td>[225, 400, 219, 102, 136, 167]</td>\n <td>2.070927</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>697</th>\n <td>[308, 572, 217, 116, 136, 167]</td>\n <td>2.070371</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>698</th>\n <td>[308, 225, 593, 572, 217, 239, 102, 136, 167]</td>\n <td>2.070132</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>699</th>\n <td>[400, 219, 102, 136, 167]</td>\n <td>2.070050</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>700</th>\n <td>[593, 219, 217, 102, 136, 167]</td>\n <td>2.070042</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>701</th>\n <td>[308, 400, 593, 219, 217, 102, 116, 167]</td>\n <td>2.069445</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>702</th>\n <td>[400, 572, 219, 217, 102, 136, 167]</td>\n <td>2.068225</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>703</th>\n <td>[225, 593, 219, 217, 102, 116, 136]</td>\n <td>2.068196</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>704</th>\n <td>[308, 225, 572, 102, 116, 167]</td>\n <td>2.067597</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>705</th>\n <td>[308, 593, 217, 239, 116, 136, 167]</td>\n <td>2.067594</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>706</th>\n <td>[308, 225, 400, 593, 219, 217, 102, 116, 167]</td>\n <td>2.066179</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>707</th>\n <td>[225, 593, 572, 219, 217, 102, 136, 167]</td>\n <td>2.065863</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>708</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 239, 102, ...</td>\n <td>2.065747</td>\n <td>4</td>\n <td>8</td>\n </tr>\n <tr>\n <th>709</th>\n <td>[308, 400, 217, 102, 136]</td>\n <td>2.064813</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>710</th>\n <td>[593, 217, 116, 167]</td>\n <td>2.064361</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>711</th>\n <td>[308, 225, 400, 593, 572, 239, 102, 116, 167]</td>\n <td>2.064244</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>712</th>\n <td>[308, 225, 400, 593, 572, 239, 116, 136, 167]</td>\n <td>2.064234</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>713</th>\n <td>[593, 572, 219, 217, 239, 102, 116, 136, 167]</td>\n <td>2.064042</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>714</th>\n <td>[308, 225, 593, 572, 102, 136]</td>\n <td>2.064000</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>715</th>\n <td>[308, 400, 593, 219, 102, 116, 167]</td>\n <td>2.063217</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>716</th>\n <td>[308, 593, 217, 239, 102, 116, 167]</td>\n <td>2.063176</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>717</th>\n <td>[400, 593, 572, 239, 102, 116, 167]</td>\n <td>2.063139</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>718</th>\n <td>[308, 217, 102, 116, 167]</td>\n <td>2.062170</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>719</th>\n <td>[308, 400, 593, 572, 219, 239, 102, 116, 136, ...</td>\n <td>2.061259</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>720</th>\n <td>[593, 217, 102, 167]</td>\n <td>2.061122</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>721</th>\n <td>[225, 400, 572, 219, 217, 102, 116, 136]</td>\n <td>2.061121</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>722</th>\n <td>[308, 225, 400, 572, 217, 102, 136]</td>\n <td>2.061082</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>723</th>\n <td>[225, 593, 217, 136, 167]</td>\n <td>2.060963</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>724</th>\n <td>[400, 572, 217, 102, 167]</td>\n <td>2.060905</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>725</th>\n <td>[308, 225, 593, 217, 102, 116]</td>\n <td>2.060751</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>726</th>\n <td>[225, 593, 102, 116]</td>\n <td>2.060642</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>727</th>\n <td>[225, 593, 572, 217, 116, 167]</td>\n <td>2.060450</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>728</th>\n <td>[400, 572, 219, 102, 136, 167]</td>\n <td>2.060028</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>729</th>\n <td>[225, 400, 219, 217, 102, 136, 167]</td>\n <td>2.059329</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>730</th>\n <td>[308, 225, 593, 217, 239, 102, 116, 167]</td>\n <td>2.059190</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>731</th>\n <td>[308, 400, 593, 572, 219, 217, 102, 116, 167]</td>\n <td>2.059083</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>732</th>\n <td>[308, 225, 400, 593, 572, 219, 239, 102, 116, ...</td>\n <td>2.058866</td>\n <td>4</td>\n <td>7</td>\n </tr>\n <tr>\n <th>733</th>\n <td>[225, 572, 102, 116, 136]</td>\n <td>2.058344</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>734</th>\n <td>[225, 593, 219, 102, 136, 167]</td>\n <td>2.058321</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>735</th>\n <td>[225, 400, 572, 217, 102, 167]</td>\n <td>2.058177</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>736</th>\n <td>[308, 593, 217, 102, 136]</td>\n <td>2.058044</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>737</th>\n <td>[308, 400, 572, 217, 102, 136]</td>\n <td>2.057974</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>738</th>\n <td>[308, 225, 102, 116, 136]</td>\n <td>2.057559</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>739</th>\n <td>[225, 400, 572, 102, 116]</td>\n <td>2.057526</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>740</th>\n <td>[308, 400, 593, 572, 239, 116, 136, 167]</td>\n <td>2.057460</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>741</th>\n <td>[308, 225, 400, 102, 136]</td>\n <td>2.057137</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>742</th>\n <td>[308, 225, 593, 572, 217, 102, 116]</td>\n <td>2.057062</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>743</th>\n <td>[593, 219, 102, 116, 136]</td>\n <td>2.056873</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>744</th>\n <td>[308, 225, 593, 217, 239, 116, 136, 167]</td>\n <td>2.056821</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>745</th>\n <td>[308, 225, 400, 593, 572, 219, 102, 116, 167]</td>\n <td>2.056471</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>746</th>\n <td>[308, 225, 400, 593, 219, 116, 136, 167]</td>\n <td>2.056236</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>747</th>\n <td>[308, 225, 593, 239, 102, 116, 136]</td>\n <td>2.055956</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>748</th>\n <td>[225, 593, 572, 136, 167]</td>\n <td>2.055704</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>749</th>\n <td>[225, 593, 219, 217, 102, 136, 167]</td>\n <td>2.055269</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>750</th>\n <td>[225, 593, 572, 217, 239, 102, 116, 167]</td>\n <td>2.055039</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>751</th>\n <td>[225, 400, 572, 219, 102, 136, 167]</td>\n <td>2.055022</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>752</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 102, 116, ...</td>\n <td>2.054621</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>753</th>\n <td>[308, 225, 400, 217, 102, 116]</td>\n <td>2.054249</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>754</th>\n <td>[225, 572, 116, 136, 167]</td>\n <td>2.054154</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>755</th>\n <td>[225, 400, 102, 167]</td>\n <td>2.053993</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>756</th>\n <td>[400, 572, 217, 116, 136]</td>\n <td>2.053195</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>757</th>\n <td>[593, 217, 116, 136]</td>\n <td>2.052970</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>758</th>\n <td>[308, 400, 593, 572, 239, 102, 116, 167]</td>\n <td>2.052968</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>759</th>\n <td>[308, 400, 593, 219, 217, 116, 136, 167]</td>\n <td>2.052733</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>760</th>\n <td>[225, 593, 572, 116, 167]</td>\n <td>2.052701</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>761</th>\n <td>[308, 400, 217, 239, 102, 116, 136]</td>\n <td>2.052559</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>762</th>\n <td>[225, 593, 572, 217, 239, 116, 136, 167]</td>\n <td>2.052466</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>763</th>\n <td>[308, 400, 593, 572, 116, 167]</td>\n <td>2.052169</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>764</th>\n <td>[308, 225, 400, 217, 239, 102, 116, 136]</td>\n <td>2.052137</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>765</th>\n <td>[308, 400, 593, 572, 219, 102, 116, 167]</td>\n <td>2.051223</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>766</th>\n <td>[225, 400, 116, 167]</td>\n <td>2.050679</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>767</th>\n <td>[308, 225, 572, 116, 136, 167]</td>\n <td>2.049893</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>768</th>\n <td>[308, 225, 400, 593, 219, 217, 116, 136, 167]</td>\n <td>2.049842</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>769</th>\n <td>[225, 400, 572, 217, 116, 136]</td>\n <td>2.049501</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>770</th>\n <td>[225, 400, 572, 219, 217, 102, 136, 167]</td>\n <td>2.049439</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>771</th>\n <td>[225, 400, 217, 136, 167]</td>\n <td>2.049252</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>772</th>\n <td>[225, 400, 217, 239, 102, 116, 136]</td>\n <td>2.048797</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>773</th>\n <td>[225, 593, 219, 217, 239, 102, 116, 136, 167]</td>\n <td>2.048793</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>774</th>\n <td>[308, 225, 102, 116, 167]</td>\n <td>2.048477</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>775</th>\n <td>[400, 217, 239, 102, 116, 136]</td>\n <td>2.048217</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>776</th>\n <td>[308, 400, 593, 219, 116, 136, 167]</td>\n <td>2.048194</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>777</th>\n <td>[308, 593, 219, 217, 239, 102, 116, 136, 167]</td>\n <td>2.047857</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>778</th>\n <td>[308, 593, 572, 217, 239, 116, 136, 167]</td>\n <td>2.047046</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>779</th>\n <td>[308, 593, 572, 217, 102, 116]</td>\n <td>2.046599</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>780</th>\n <td>[225, 400, 217, 116, 167]</td>\n <td>2.046583</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>781</th>\n <td>[225, 593, 116, 136]</td>\n <td>2.046219</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>782</th>\n <td>[308, 593, 572, 217, 239, 102, 116, 167]</td>\n <td>2.045995</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>783</th>\n <td>[308, 225, 400, 219, 102, 116, 136]</td>\n <td>2.045747</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>784</th>\n <td>[308, 400, 219, 217, 102, 116, 136]</td>\n <td>2.044640</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>785</th>\n <td>[308, 225, 102, 136, 167]</td>\n <td>2.044411</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>786</th>\n <td>[400, 217, 116, 167]</td>\n <td>2.043971</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>787</th>\n <td>[308, 400, 593, 572, 219, 217, 116, 136, 167]</td>\n <td>2.043785</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>788</th>\n <td>[308, 593, 572, 219, 217, 102, 116, 136]</td>\n <td>2.043512</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>789</th>\n <td>[308, 225, 593, 102, 136]</td>\n <td>2.043379</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>790</th>\n <td>[308, 225, 593, 572, 239, 102, 116, 136]</td>\n <td>2.043197</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>791</th>\n <td>[308, 225, 593, 572, 217, 102, 167]</td>\n <td>2.042878</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>792</th>\n <td>[225, 102, 116, 136, 167]</td>\n <td>2.042865</td>\n <td>4</td>\n <td>1</td>\n </tr>\n <tr>\n <th>793</th>\n <td>[308, 225, 400, 572, 102, 136]</td>\n <td>2.042544</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>794</th>\n <td>[400, 217, 136, 167]</td>\n <td>2.042313</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>795</th>\n <td>[308, 225, 400, 593, 572, 219, 116, 136, 167]</td>\n <td>2.042252</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>796</th>\n <td>[225, 400, 219, 102, 116, 167]</td>\n <td>2.042048</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>797</th>\n <td>[593, 572, 219, 217, 102, 116, 167]</td>\n <td>2.041759</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>798</th>\n <td>[225, 593, 572, 219, 217, 239, 102, 116, 136, ...</td>\n <td>2.041539</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>799</th>\n <td>[400, 219, 217, 102, 116, 167]</td>\n <td>2.041508</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>800</th>\n <td>[308, 225, 593, 217, 116, 136]</td>\n <td>2.041016</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>801</th>\n <td>[308, 225, 400, 219, 217, 102, 116, 136]</td>\n <td>2.040987</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>802</th>\n <td>[308, 225, 593, 572, 217, 239, 102, 116, 167]</td>\n <td>2.040658</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>803</th>\n <td>[308, 225, 400, 102, 116]</td>\n <td>2.040444</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>804</th>\n <td>[308, 225, 593, 217, 102, 167]</td>\n <td>2.040225</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>805</th>\n <td>[308, 400, 217, 102, 116]</td>\n <td>2.040018</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>806</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 116, 136, ...</td>\n <td>2.039642</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>807</th>\n <td>[308, 593, 572, 219, 217, 239, 102, 116, 136, ...</td>\n <td>2.039280</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>808</th>\n <td>[308, 225, 593, 572, 217, 116, 136]</td>\n <td>2.039137</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>809</th>\n <td>[308, 225, 593, 572, 219, 217, 102, 116, 136]</td>\n <td>2.037850</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>810</th>\n <td>[308, 217, 116, 136, 167]</td>\n <td>2.037581</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>811</th>\n <td>[308, 225, 400, 217, 239, 102, 136, 167]</td>\n <td>2.037520</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>812</th>\n <td>[308, 225, 593, 239, 102, 136, 167]</td>\n <td>2.037363</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>813</th>\n <td>[308, 400, 593, 572, 219, 116, 136, 167]</td>\n <td>2.037324</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>814</th>\n <td>[308, 225, 593, 219, 217, 102, 116, 136]</td>\n <td>2.037238</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>815</th>\n <td>[308, 225, 593, 219, 217, 239, 102, 116, 136, ...</td>\n <td>2.037097</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>816</th>\n <td>[308, 225, 593, 572, 219, 102, 116, 136]</td>\n <td>2.037025</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>817</th>\n <td>[308, 225, 593, 572, 217, 239, 116, 136, 167]</td>\n <td>2.036888</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>818</th>\n <td>[308, 593, 219, 217, 102, 116, 136]</td>\n <td>2.036875</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>819</th>\n <td>[308, 225, 593, 219, 102, 116, 136]</td>\n <td>2.036850</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>820</th>\n <td>[225, 400, 572, 116, 136]</td>\n <td>2.036708</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>821</th>\n <td>[308, 400, 217, 239, 102, 136, 167]</td>\n <td>2.036689</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>822</th>\n <td>[400, 219, 217, 239, 102, 116, 136, 167]</td>\n <td>2.036544</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>823</th>\n <td>[308, 400, 219, 102, 116, 136]</td>\n <td>2.035737</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>824</th>\n <td>[400, 572, 217, 136, 167]</td>\n <td>2.035187</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>825</th>\n <td>[593, 219, 102, 136, 167]</td>\n <td>2.035026</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>826</th>\n <td>[308, 225, 400, 217, 116, 136]</td>\n <td>2.034805</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>827</th>\n <td>[308, 400, 572, 219, 217, 102, 116, 136]</td>\n <td>2.034722</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>828</th>\n <td>[308, 572, 239, 102, 116, 136, 167]</td>\n <td>2.034419</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>829</th>\n <td>[225, 400, 217, 239, 102, 136, 167]</td>\n <td>2.033931</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>830</th>\n <td>[593, 217, 136, 167]</td>\n <td>2.033902</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>831</th>\n <td>[308, 225, 400, 572, 217, 102, 116]</td>\n <td>2.033770</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>832</th>\n <td>[400, 219, 102, 116, 167]</td>\n <td>2.033109</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>833</th>\n <td>[308, 593, 572, 219, 217, 102, 136, 167]</td>\n <td>2.033027</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>834</th>\n <td>[308, 400, 572, 217, 239, 102, 116, 136]</td>\n <td>2.032896</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>835</th>\n <td>[308, 593, 217, 102, 116]</td>\n <td>2.032839</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>836</th>\n <td>[400, 217, 239, 102, 136, 167]</td>\n <td>2.032685</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>837</th>\n <td>[308, 225, 593, 572, 102, 116]</td>\n <td>2.032601</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>838</th>\n <td>[308, 225, 400, 217, 102, 167]</td>\n <td>2.032492</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>839</th>\n <td>[225, 400, 572, 217, 136, 167]</td>\n <td>2.032462</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>840</th>\n <td>[400, 572, 217, 239, 102, 116, 136]</td>\n <td>2.032322</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>841</th>\n <td>[308, 225, 400, 572, 217, 239, 102, 116, 136]</td>\n <td>2.032130</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>842</th>\n <td>[308, 593, 572, 217, 102, 167]</td>\n <td>2.031997</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>843</th>\n <td>[225, 400, 219, 217, 102, 116, 167]</td>\n <td>2.031744</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>844</th>\n <td>[225, 400, 572, 102, 167]</td>\n <td>2.030894</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>845</th>\n <td>[308, 593, 572, 217, 116, 136]</td>\n <td>2.030656</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>846</th>\n <td>[308, 225, 593, 102, 116]</td>\n <td>2.030644</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>847</th>\n <td>[225, 400, 136, 167]</td>\n <td>2.030587</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>848</th>\n <td>[308, 225, 400, 572, 219, 102, 116, 136]</td>\n <td>2.030302</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>849</th>\n <td>[308, 225, 593, 572, 239, 102, 136, 167]</td>\n <td>2.030237</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>850</th>\n <td>[225, 400, 572, 217, 239, 102, 116, 136]</td>\n <td>2.030152</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>851</th>\n <td>[308, 225, 400, 572, 219, 217, 102, 116, 136]</td>\n <td>2.029870</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>852</th>\n <td>[225, 593, 572, 219, 102, 116, 167]</td>\n <td>2.029728</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>853</th>\n <td>[308, 225, 116, 136, 167]</td>\n <td>2.029676</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>854</th>\n <td>[593, 219, 217, 102, 116, 167]</td>\n <td>2.029313</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>855</th>\n <td>[225, 593, 219, 239, 102, 116, 136, 167]</td>\n <td>2.028557</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>856</th>\n <td>[308, 400, 219, 217, 102, 136, 167]</td>\n <td>2.028489</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>857</th>\n <td>[308, 225, 593, 572, 219, 217, 239, 102, 116, ...</td>\n <td>2.028179</td>\n <td>4</td>\n <td>7</td>\n </tr>\n <tr>\n <th>858</th>\n <td>[225, 593, 572, 219, 217, 102, 116, 167]</td>\n <td>2.027938</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>859</th>\n <td>[400, 572, 219, 217, 102, 116, 167]</td>\n <td>2.027580</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>860</th>\n <td>[308, 225, 593, 572, 219, 217, 102, 136, 167]</td>\n <td>2.027505</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>861</th>\n <td>[225, 593, 219, 102, 116, 167]</td>\n <td>2.027312</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>862</th>\n <td>[308, 593, 572, 219, 102, 116, 136]</td>\n <td>2.026628</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>863</th>\n <td>[308, 225, 400, 219, 217, 102, 136, 167]</td>\n <td>2.026269</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>864</th>\n <td>[593, 572, 219, 239, 102, 116, 136, 167]</td>\n <td>2.026218</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>865</th>\n <td>[308, 225, 400, 219, 102, 136, 167]</td>\n <td>2.026173</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>866</th>\n <td>[593, 219, 239, 102, 116, 136, 167]</td>\n <td>2.025501</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>867</th>\n <td>[400, 572, 102, 136]</td>\n <td>2.025330</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>868</th>\n <td>[308, 225, 400, 116, 136]</td>\n <td>2.024964</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>869</th>\n <td>[308, 225, 593, 572, 217, 136, 167]</td>\n <td>2.024761</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>870</th>\n <td>[225, 572, 239, 102, 116, 136, 167]</td>\n <td>2.024743</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>871</th>\n <td>[225, 593, 572, 239, 102, 116, 136]</td>\n <td>2.024734</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>872</th>\n <td>[225, 593, 219, 217, 102, 116, 167]</td>\n <td>2.024560</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>873</th>\n <td>[308, 400, 572, 217, 102, 116]</td>\n <td>2.024435</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>874</th>\n <td>[225, 593, 102, 136]</td>\n <td>2.024409</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>875</th>\n <td>[308, 225, 593, 239, 116, 136, 167]</td>\n <td>2.024065</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>876</th>\n <td>[308, 400, 572, 219, 102, 116, 136]</td>\n <td>2.023967</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>877</th>\n <td>[225, 400, 219, 217, 239, 102, 116, 136, 167]</td>\n <td>2.023963</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>878</th>\n <td>[308, 225, 593, 219, 217, 102, 136, 167]</td>\n <td>2.023596</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>879</th>\n <td>[308, 225, 593, 219, 239, 102, 116, 136, 167]</td>\n <td>2.023265</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>880</th>\n <td>[308, 225, 593, 572, 219, 102, 136, 167]</td>\n <td>2.022988</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>881</th>\n <td>[308, 400, 219, 217, 239, 102, 116, 136, 167]</td>\n <td>2.022761</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>882</th>\n <td>[225, 593, 572, 219, 239, 102, 116, 136, 167]</td>\n <td>2.022439</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>883</th>\n <td>[308, 593, 219, 217, 102, 136, 167]</td>\n <td>2.022319</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>884</th>\n <td>[308, 400, 572, 219, 217, 102, 136, 167]</td>\n <td>2.022254</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>885</th>\n <td>[400, 572, 217, 239, 102, 136, 167]</td>\n <td>2.022201</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>886</th>\n <td>[308, 102, 116, 136, 167]</td>\n <td>2.021872</td>\n <td>4</td>\n <td>1</td>\n </tr>\n <tr>\n <th>887</th>\n <td>[400, 572, 219, 217, 239, 102, 116, 136, 167]</td>\n <td>2.021680</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>888</th>\n <td>[308, 400, 217, 116, 136]</td>\n <td>2.021441</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>889</th>\n <td>[308, 400, 572, 217, 239, 102, 136, 167]</td>\n <td>2.021121</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>890</th>\n <td>[308, 225, 400, 572, 217, 239, 102, 136, 167]</td>\n <td>2.020852</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>891</th>\n <td>[308, 593, 572, 239, 102, 116, 136]</td>\n <td>2.020843</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>892</th>\n <td>[225, 593, 102, 167]</td>\n <td>2.020364</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>893</th>\n <td>[593, 572, 219, 102, 116, 167]</td>\n <td>2.020324</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>894</th>\n <td>[308, 225, 593, 572, 116, 136]</td>\n <td>2.020299</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>895</th>\n <td>[308, 225, 593, 217, 136, 167]</td>\n <td>2.020277</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>896</th>\n <td>[217, 102, 116, 167]</td>\n <td>2.019812</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>897</th>\n <td>[225, 400, 572, 219, 102, 116, 167]</td>\n <td>2.019804</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>898</th>\n <td>[225, 400, 572, 217, 239, 102, 136, 167]</td>\n <td>2.019615</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>899</th>\n <td>[308, 225, 593, 116, 136]</td>\n <td>2.018672</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>900</th>\n <td>[308, 593, 219, 239, 102, 116, 136, 167]</td>\n <td>2.018480</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>901</th>\n <td>[308, 593, 239, 102, 116, 136]</td>\n <td>2.018449</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>902</th>\n <td>[308, 225, 400, 239, 102, 116, 136]</td>\n <td>2.018394</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>903</th>\n <td>[400, 593, 217, 102]</td>\n <td>2.018174</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>904</th>\n <td>[308, 225, 400, 572, 219, 217, 102, 136, 167]</td>\n <td>2.018159</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>905</th>\n <td>[308, 225, 593, 219, 102, 136, 167]</td>\n <td>2.017911</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>906</th>\n <td>[225, 400, 572, 219, 217, 102, 116, 167]</td>\n <td>2.017589</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>907</th>\n <td>[308, 225, 400, 572, 217, 102, 167]</td>\n <td>2.017508</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>908</th>\n <td>[225, 400, 593, 217, 102]</td>\n <td>2.017311</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>909</th>\n <td>[308, 225, 400, 217, 239, 102, 116, 167]</td>\n <td>2.017187</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>910</th>\n <td>[308, 225, 593, 239, 102, 116, 167]</td>\n <td>2.017176</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>911</th>\n <td>[308, 225, 400, 219, 217, 239, 102, 116, 136, ...</td>\n <td>2.016959</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>912</th>\n <td>[225, 400, 217, 239, 102, 116, 167]</td>\n <td>2.016295</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>913</th>\n <td>[308, 225, 400, 572, 217, 116, 136]</td>\n <td>2.016292</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>914</th>\n <td>[308, 593, 217, 116, 136]</td>\n <td>2.015957</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>915</th>\n <td>[308, 593, 572, 217, 136, 167]</td>\n <td>2.015807</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>916</th>\n <td>[308, 225, 400, 572, 102, 116]</td>\n <td>2.015421</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>917</th>\n <td>[308, 225, 400, 572, 219, 102, 136, 167]</td>\n <td>2.015074</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>918</th>\n <td>[308, 400, 217, 102, 167]</td>\n <td>2.015021</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>919</th>\n <td>[225, 593, 572, 239, 102, 136, 167]</td>\n <td>2.014908</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>920</th>\n <td>[400, 572, 219, 102, 116, 167]</td>\n <td>2.014691</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>921</th>\n <td>[225, 593, 239, 102, 116, 136]</td>\n <td>2.014324</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>922</th>\n <td>[308, 593, 219, 102, 116, 136]</td>\n <td>2.014059</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>923</th>\n <td>[308, 225, 593, 572, 219, 239, 102, 116, 136, ...</td>\n <td>2.013773</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>924</th>\n <td>[225, 400, 219, 116, 136, 167]</td>\n <td>2.013659</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>925</th>\n <td>[308, 400, 219, 102, 136, 167]</td>\n <td>2.013543</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>926</th>\n <td>[225, 400, 572, 217, 116, 167]</td>\n <td>2.013278</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>927</th>\n <td>[308, 225, 400, 217, 136, 167]</td>\n <td>2.012944</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>928</th>\n <td>[225, 400, 593, 102]</td>\n <td>2.012428</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>929</th>\n <td>[308, 239, 102, 116, 136, 167]</td>\n <td>2.012399</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>930</th>\n <td>[308, 593, 572, 219, 239, 102, 116, 136, 167]</td>\n <td>2.012312</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>931</th>\n <td>[308, 400, 217, 239, 102, 116, 167]</td>\n <td>2.012264</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>932</th>\n <td>[593, 572, 219, 217, 116, 136, 167]</td>\n <td>2.011899</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>933</th>\n <td>[308, 593, 572, 219, 102, 136, 167]</td>\n <td>2.011672</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>934</th>\n <td>[400, 217, 239, 102, 116, 167]</td>\n <td>2.011286</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>935</th>\n <td>[308, 225, 400, 217, 239, 116, 136, 167]</td>\n <td>2.011255</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>936</th>\n <td>[400, 572, 217, 116, 167]</td>\n <td>2.011175</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>937</th>\n <td>[308, 225, 593, 572, 102, 167]</td>\n <td>2.011135</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>938</th>\n <td>[400, 217, 239, 116, 136, 167]</td>\n <td>2.011082</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>939</th>\n <td>[400, 219, 217, 116, 136, 167]</td>\n <td>2.011059</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>940</th>\n <td>[225, 400, 572, 219, 217, 239, 102, 116, 136, ...</td>\n <td>2.010357</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>941</th>\n <td>[225, 400, 217, 239, 116, 136, 167]</td>\n <td>2.009936</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>942</th>\n <td>[308, 593, 217, 102, 167]</td>\n <td>2.009876</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>943</th>\n <td>[225, 593, 239, 116, 136, 167]</td>\n <td>2.009770</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>944</th>\n <td>[225, 400, 572, 136, 167]</td>\n <td>2.009763</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>945</th>\n <td>[308, 400, 217, 239, 116, 136, 167]</td>\n <td>2.009697</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>946</th>\n <td>[308, 400, 572, 219, 217, 239, 102, 116, 136, ...</td>\n <td>2.009307</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>947</th>\n <td>[308, 225, 400, 102, 167]</td>\n <td>2.009011</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>948</th>\n <td>[308, 225, 593, 217, 116, 167]</td>\n <td>2.008273</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>949</th>\n <td>[308, 593, 572, 239, 102, 136, 167]</td>\n <td>2.007638</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>950</th>\n <td>[308, 400, 572, 217, 116, 136]</td>\n <td>2.007529</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>951</th>\n <td>[308, 400, 572, 219, 102, 136, 167]</td>\n <td>2.007243</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>952</th>\n <td>[308, 400, 572, 217, 102, 167]</td>\n <td>2.006546</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>953</th>\n <td>[225, 400, 219, 239, 102, 116, 136, 167]</td>\n <td>2.006505</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>954</th>\n <td>[225, 593, 136, 167]</td>\n <td>2.004972</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>955</th>\n <td>[572, 219, 217, 102, 116, 136]</td>\n <td>2.004627</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>956</th>\n <td>[308, 225, 593, 572, 239, 116, 136, 167]</td>\n <td>2.004293</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>957</th>\n <td>[225, 400, 219, 217, 116, 136, 167]</td>\n <td>2.004161</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>958</th>\n <td>[308, 225, 400, 219, 239, 102, 116, 136, 167]</td>\n <td>2.004125</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>959</th>\n <td>[308, 225, 400, 572, 219, 217, 239, 102, 116, ...</td>\n <td>2.004105</td>\n <td>4</td>\n <td>7</td>\n </tr>\n <tr>\n <th>960</th>\n <td>[308, 400, 572, 102, 136]</td>\n <td>2.003940</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>961</th>\n <td>[308, 593, 572, 102, 136]</td>\n <td>2.003821</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>962</th>\n <td>[400, 593, 572, 217, 102]</td>\n <td>2.003481</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>963</th>\n <td>[400, 219, 116, 136, 167]</td>\n <td>2.002985</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>964</th>\n <td>[225, 593, 572, 219, 116, 136, 167]</td>\n <td>2.002500</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>965</th>\n <td>[308, 225, 400, 219, 217, 102, 116, 167]</td>\n <td>2.001698</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>966</th>\n <td>[593, 102, 116, 136, 167]</td>\n <td>2.001374</td>\n <td>4</td>\n <td>1</td>\n </tr>\n <tr>\n <th>967</th>\n <td>[308, 225, 593, 572, 239, 102, 116, 167]</td>\n <td>2.001350</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>968</th>\n <td>[400, 572, 219, 217, 116, 136, 167]</td>\n <td>2.001286</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>969</th>\n <td>[400, 219, 239, 102, 116, 136, 167]</td>\n <td>2.001160</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>970</th>\n <td>[308, 225, 593, 572, 217, 116, 167]</td>\n <td>2.001011</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>971</th>\n <td>[308, 225, 400, 572, 116, 136]</td>\n <td>2.000898</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>972</th>\n <td>[572, 219, 217, 102, 136, 167]</td>\n <td>2.000731</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>973</th>\n <td>[225, 593, 572, 219, 217, 116, 136, 167]</td>\n <td>2.000707</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>974</th>\n <td>[308, 225, 400, 219, 102, 116, 167]</td>\n <td>2.000158</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>975</th>\n <td>[308, 225, 400, 572, 217, 136, 167]</td>\n <td>1.999921</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>976</th>\n <td>[225, 400, 593, 572, 217, 102]</td>\n <td>1.999607</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>977</th>\n <td>[308, 225, 400, 217, 116, 167]</td>\n <td>1.999379</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>978</th>\n <td>[308, 225, 400, 572, 239, 102, 116, 136]</td>\n <td>1.998875</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>979</th>\n <td>[308, 400, 219, 217, 102, 116, 167]</td>\n <td>1.998828</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>980</th>\n <td>[308, 225, 400, 239, 102, 136, 167]</td>\n <td>1.998573</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>981</th>\n <td>[308, 225, 593, 572, 136, 167]</td>\n <td>1.998563</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>982</th>\n <td>[308, 225, 593, 102, 167]</td>\n <td>1.998491</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>983</th>\n <td>[225, 400, 572, 116, 167]</td>\n <td>1.998075</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>984</th>\n <td>[308, 593, 239, 102, 136, 167]</td>\n <td>1.998039</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>985</th>\n <td>[308, 400, 219, 239, 102, 116, 136, 167]</td>\n <td>1.997985</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>986</th>\n <td>[225, 593, 572, 239, 116, 136, 167]</td>\n <td>1.997810</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>987</th>\n <td>[400, 593, 217, 136]</td>\n <td>1.997722</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>988</th>\n <td>[400, 593, 219, 217, 102, 136]</td>\n <td>1.997119</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>989</th>\n <td>[225, 400, 593, 136]</td>\n <td>1.997103</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>990</th>\n <td>[308, 400, 102, 136]</td>\n <td>1.997080</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>991</th>\n <td>[308, 225, 400, 572, 217, 239, 102, 116, 167]</td>\n <td>1.996861</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>992</th>\n <td>[400, 593, 217, 239, 102, 136]</td>\n <td>1.996777</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>993</th>\n <td>[400, 572, 102, 116]</td>\n <td>1.996767</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>994</th>\n <td>[225, 593, 239, 102, 136, 167]</td>\n <td>1.996644</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>995</th>\n <td>[225, 400, 593, 116]</td>\n <td>1.996529</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>996</th>\n <td>[308, 225, 593, 572, 219, 217, 102, 116, 167]</td>\n <td>1.996335</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>997</th>\n <td>[308, 400, 217, 136, 167]</td>\n <td>1.996262</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>998</th>\n <td>[308, 225, 593, 219, 217, 102, 116, 167]</td>\n <td>1.996117</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>999</th>\n <td>[225, 593, 219, 116, 136, 167]</td>\n <td>1.995726</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1000</th>\n <td>[308, 225, 400, 593, 217, 239, 102, 136]</td>\n <td>1.995714</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1001</th>\n <td>[308, 400, 593, 217, 239, 102, 136]</td>\n <td>1.995489</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1002</th>\n <td>[593, 219, 102, 116, 167]</td>\n <td>1.995314</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1003</th>\n <td>[225, 400, 572, 219, 116, 136, 167]</td>\n <td>1.995306</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1004</th>\n <td>[225, 400, 593, 217, 136]</td>\n <td>1.995009</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1005</th>\n <td>[225, 400, 572, 217, 239, 102, 116, 167]</td>\n <td>1.994711</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1006</th>\n <td>[593, 219, 217, 116, 136, 167]</td>\n <td>1.994677</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1007</th>\n <td>[308, 593, 572, 219, 217, 102, 116, 167]</td>\n <td>1.994589</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1008</th>\n <td>[225, 400, 593, 219, 102, 136]</td>\n <td>1.994461</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1009</th>\n <td>[400, 593, 572, 219, 217, 102, 136]</td>\n <td>1.994441</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1010</th>\n <td>[593, 572, 102, 136]</td>\n <td>1.993777</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1011</th>\n <td>[308, 593, 239, 116, 136, 167]</td>\n <td>1.993654</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1012</th>\n <td>[225, 400, 572, 219, 217, 116, 136, 167]</td>\n <td>1.993443</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1013</th>\n <td>[225, 593, 219, 217, 116, 136, 167]</td>\n <td>1.993346</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1014</th>\n <td>[308, 225, 400, 136, 167]</td>\n <td>1.993304</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1015</th>\n <td>[225, 400, 593, 217, 239, 102, 136]</td>\n <td>1.993083</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1016</th>\n <td>[308, 593, 219, 102, 136, 167]</td>\n <td>1.992861</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1017</th>\n <td>[308, 225, 400, 572, 102, 167]</td>\n <td>1.992753</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1018</th>\n <td>[308, 593, 217, 136, 167]</td>\n <td>1.992669</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1019</th>\n <td>[400, 102, 116]</td>\n <td>1.992542</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1020</th>\n <td>[593, 572, 219, 116, 136, 167]</td>\n <td>1.992251</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1021</th>\n <td>[308, 400, 572, 217, 239, 102, 116, 167]</td>\n <td>1.992233</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1022</th>\n <td>[225, 400, 572, 219, 239, 102, 116, 136, 167]</td>\n <td>1.991386</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1023</th>\n <td>[225, 593, 239, 102, 116, 167]</td>\n <td>1.991366</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1024</th>\n <td>[308, 225, 400, 572, 219, 217, 102, 116, 167]</td>\n <td>1.991205</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1025</th>\n <td>[400, 572, 217, 239, 102, 116, 167]</td>\n <td>1.991012</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1026</th>\n <td>[308, 225, 400, 572, 217, 239, 116, 136, 167]</td>\n <td>1.990526</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1027</th>\n <td>[308, 400, 572, 219, 217, 102, 116, 167]</td>\n <td>1.989846</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1028</th>\n <td>[308, 225, 400, 572, 219, 239, 102, 116, 136, ...</td>\n <td>1.989568</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1029</th>\n <td>[308, 400, 572, 217, 136, 167]</td>\n <td>1.989481</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1030</th>\n <td>[225, 400, 593, 219, 217, 102, 136]</td>\n <td>1.989220</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1031</th>\n <td>[308, 225, 593, 219, 102, 116, 167]</td>\n <td>1.988997</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1032</th>\n <td>[400, 572, 219, 116, 136, 167]</td>\n <td>1.988917</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1033</th>\n <td>[308, 225, 593, 572, 219, 102, 116, 167]</td>\n <td>1.988789</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1034</th>\n <td>[308, 593, 219, 217, 102, 116, 167]</td>\n <td>1.988499</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1035</th>\n <td>[308, 400, 572, 217, 239, 116, 136, 167]</td>\n <td>1.988357</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1036</th>\n <td>[400, 593, 219, 102, 136]</td>\n <td>1.988278</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1037</th>\n <td>[225, 593, 572, 239, 102, 116, 167]</td>\n <td>1.988233</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1038</th>\n <td>[400, 572, 217, 239, 116, 136, 167]</td>\n <td>1.988045</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1039</th>\n <td>[400, 572, 219, 239, 102, 116, 136, 167]</td>\n <td>1.987969</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1040</th>\n <td>[225, 400, 572, 217, 239, 116, 136, 167]</td>\n <td>1.987555</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1041</th>\n <td>[308, 400, 239, 102, 116, 136]</td>\n <td>1.987190</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1042</th>\n <td>[225, 572, 219, 217, 102, 116, 136]</td>\n <td>1.986863</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1043</th>\n <td>[225, 400, 239, 102, 116, 136]</td>\n <td>1.986426</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1044</th>\n <td>[308, 593, 572, 217, 116, 167]</td>\n <td>1.986326</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1045</th>\n <td>[308, 572, 102, 116, 136]</td>\n <td>1.986198</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1046</th>\n <td>[308, 225, 593, 136, 167]</td>\n <td>1.986079</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1047</th>\n <td>[308, 225, 400, 572, 219, 102, 116, 167]</td>\n <td>1.985826</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1048</th>\n <td>[308, 225, 593, 116, 167]</td>\n <td>1.985775</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1049</th>\n <td>[308, 225, 400, 116, 167]</td>\n <td>1.985772</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1050</th>\n <td>[225, 400, 593, 572, 219, 102, 136]</td>\n <td>1.985486</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1051</th>\n <td>[225, 400, 593, 572, 102]</td>\n <td>1.985361</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1052</th>\n <td>[225, 572, 219, 102, 116, 136]</td>\n <td>1.985332</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1053</th>\n <td>[400, 593, 572, 217, 136]</td>\n <td>1.984831</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1054</th>\n <td>[225, 400, 593, 572, 219, 217, 102, 136]</td>\n <td>1.984765</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1055</th>\n <td>[308, 400, 572, 219, 239, 102, 116, 136, 167]</td>\n <td>1.984503</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1056</th>\n <td>[308, 572, 102, 136, 167]</td>\n <td>1.984280</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1057</th>\n <td>[400, 593, 217, 116]</td>\n <td>1.984280</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1058</th>\n <td>[400, 593, 572, 217, 239, 102, 136]</td>\n <td>1.984047</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1059</th>\n <td>[400, 593, 572, 219, 102, 136]</td>\n <td>1.984045</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1060</th>\n <td>[308, 225, 400, 572, 239, 102, 136, 167]</td>\n <td>1.983873</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1061</th>\n <td>[308, 593, 572, 239, 116, 136, 167]</td>\n <td>1.983552</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1062</th>\n <td>[225, 400, 593, 217, 116]</td>\n <td>1.983315</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1063</th>\n <td>[219, 217, 102, 116, 136]</td>\n <td>1.982320</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1064</th>\n <td>[308, 400, 219, 102, 116, 167]</td>\n <td>1.982274</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1065</th>\n <td>[308, 225, 400, 219, 217, 116, 136, 167]</td>\n <td>1.982113</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1066</th>\n <td>[400, 572, 116, 136]</td>\n <td>1.981829</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1067</th>\n <td>[308, 400, 593, 572, 217, 239, 102, 136]</td>\n <td>1.981628</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1068</th>\n <td>[308, 225, 400, 593, 572, 217, 239, 102, 136]</td>\n <td>1.981622</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1069</th>\n <td>[308, 225, 400, 593, 217, 102]</td>\n <td>1.981478</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1070</th>\n <td>[225, 239, 102, 116, 136, 167]</td>\n <td>1.981152</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1071</th>\n <td>[308, 400, 217, 116, 167]</td>\n <td>1.980965</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1072</th>\n <td>[308, 225, 400, 219, 116, 136, 167]</td>\n <td>1.980827</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1073</th>\n <td>[308, 225, 400, 239, 102, 116, 167]</td>\n <td>1.980532</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1074</th>\n <td>[308, 593, 217, 116, 167]</td>\n <td>1.980225</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1075</th>\n <td>[308, 400, 102, 116]</td>\n <td>1.979984</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1076</th>\n <td>[308, 225, 400, 239, 116, 136, 167]</td>\n <td>1.979850</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1077</th>\n <td>[225, 400, 593, 572, 217, 136]</td>\n <td>1.979820</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1078</th>\n <td>[225, 400, 593, 572, 217, 239, 102, 136]</td>\n <td>1.979700</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1079</th>\n <td>[400, 116, 136]</td>\n <td>1.979643</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1080</th>\n <td>[225, 572, 219, 217, 102, 136, 167]</td>\n <td>1.979633</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1081</th>\n <td>[308, 225, 400, 572, 217, 116, 167]</td>\n <td>1.979123</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1082</th>\n <td>[308, 225, 217, 239, 102, 116, 136]</td>\n <td>1.978737</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1083</th>\n <td>[308, 400, 219, 217, 116, 136, 167]</td>\n <td>1.978201</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1084</th>\n <td>[308, 225, 593, 572, 116, 167]</td>\n <td>1.978145</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1085</th>\n <td>[308, 225, 400, 572, 136, 167]</td>\n <td>1.978063</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1086</th>\n <td>[400, 593, 219, 217, 239, 102, 116, 136]</td>\n <td>1.977239</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1087</th>\n <td>[308, 225, 593, 572, 219, 217, 116, 136, 167]</td>\n <td>1.977189</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1088</th>\n <td>[225, 219, 217, 102, 116, 136]</td>\n <td>1.976652</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1089</th>\n <td>[593, 572, 116, 136]</td>\n <td>1.975194</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1090</th>\n <td>[572, 219, 102, 116, 136]</td>\n <td>1.975096</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1091</th>\n <td>[308, 593, 239, 102, 116, 167]</td>\n <td>1.975033</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1092</th>\n <td>[593, 572, 239, 102, 116, 136]</td>\n <td>1.974913</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1093</th>\n <td>[308, 225, 593, 219, 217, 116, 136, 167]</td>\n <td>1.974887</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1094</th>\n <td>[225, 400, 572, 239, 102, 116, 136]</td>\n <td>1.974870</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1095</th>\n <td>[225, 219, 102, 116, 136]</td>\n <td>1.974845</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1096</th>\n <td>[308, 400, 572, 239, 102, 116, 136]</td>\n <td>1.974752</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1097</th>\n <td>[308, 593, 572, 219, 217, 116, 136, 167]</td>\n <td>1.974613</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1098</th>\n <td>[308, 225, 400, 593, 217, 239, 102, 116]</td>\n <td>1.974551</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1099</th>\n <td>[400, 102, 136]</td>\n <td>1.974319</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1100</th>\n <td>[217, 116, 136, 167]</td>\n <td>1.974142</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1101</th>\n <td>[225, 572, 219, 102, 136, 167]</td>\n <td>1.973910</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1102</th>\n <td>[219, 217, 239, 102, 116, 136, 167]</td>\n <td>1.973775</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1103</th>\n <td>[308, 225, 400, 572, 219, 217, 116, 136, 167]</td>\n <td>1.973517</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1104</th>\n <td>[593, 572, 102, 116]</td>\n <td>1.973424</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1105</th>\n <td>[308, 400, 593, 219, 217, 239, 102, 116, 136]</td>\n <td>1.972431</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1106</th>\n <td>[219, 217, 102, 136, 167]</td>\n <td>1.972429</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1107</th>\n <td>[308, 593, 572, 239, 102, 116, 167]</td>\n <td>1.972427</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1108</th>\n <td>[225, 400, 593, 217, 239, 102, 116]</td>\n <td>1.972372</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1109</th>\n <td>[308, 400, 572, 219, 102, 116, 167]</td>\n <td>1.972021</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1110</th>\n <td>[308, 400, 572, 102, 116]</td>\n <td>1.971958</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1111</th>\n <td>[400, 593, 217, 239, 116, 136]</td>\n <td>1.971796</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1112</th>\n <td>[225, 572, 217, 102, 136]</td>\n <td>1.971706</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1113</th>\n <td>[308, 400, 572, 219, 217, 116, 136, 167]</td>\n <td>1.971321</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1114</th>\n <td>[308, 225, 400, 593, 219, 217, 102, 136]</td>\n <td>1.970918</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1115</th>\n <td>[400, 593, 217, 239, 102, 116]</td>\n <td>1.970817</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1116</th>\n <td>[572, 219, 217, 239, 102, 116, 136, 167]</td>\n <td>1.970731</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1117</th>\n <td>[225, 400, 593, 219, 217, 239, 102, 116, 136]</td>\n <td>1.970482</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1118</th>\n <td>[308, 225, 400, 593, 219, 217, 239, 102, 116, ...</td>\n <td>1.970431</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1119</th>\n <td>[225, 400, 593, 572, 136]</td>\n <td>1.970349</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1120</th>\n <td>[308, 225, 593, 572, 219, 116, 136, 167]</td>\n <td>1.970344</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1121</th>\n <td>[308, 219, 217, 239, 102, 116, 136, 167]</td>\n <td>1.970172</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1122</th>\n <td>[308, 400, 593, 217, 239, 102, 116]</td>\n <td>1.969980</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1123</th>\n <td>[308, 225, 400, 593, 217, 239, 116, 136]</td>\n <td>1.969855</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1124</th>\n <td>[308, 225, 572, 217, 239, 102, 116, 136]</td>\n <td>1.969832</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1125</th>\n <td>[308, 225, 400, 593, 572, 217, 102]</td>\n <td>1.969648</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1126</th>\n <td>[308, 593, 572, 219, 102, 116, 167]</td>\n <td>1.969497</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1127</th>\n <td>[308, 400, 116, 136]</td>\n <td>1.968674</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1128</th>\n <td>[308, 400, 593, 219, 217, 102, 136]</td>\n <td>1.968621</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1129</th>\n <td>[308, 225, 593, 219, 116, 136, 167]</td>\n <td>1.968519</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1130</th>\n <td>[308, 225, 400, 572, 219, 116, 136, 167]</td>\n <td>1.968440</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1131</th>\n <td>[308, 400, 593, 217, 239, 116, 136]</td>\n <td>1.968343</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1132</th>\n <td>[217, 102, 136, 167]</td>\n <td>1.968134</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1133</th>\n <td>[308, 225, 400, 593, 219, 102, 136]</td>\n <td>1.967902</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1134</th>\n <td>[225, 400, 593, 217, 239, 116, 136]</td>\n <td>1.967804</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1135</th>\n <td>[593, 572, 239, 102, 136, 167]</td>\n <td>1.967737</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1136</th>\n <td>[308, 400, 593, 217, 102]</td>\n <td>1.967482</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1137</th>\n <td>[400, 593, 572, 219, 217, 239, 102, 116, 136]</td>\n <td>1.967437</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1138</th>\n <td>[400, 116, 167]</td>\n <td>1.967380</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1139</th>\n <td>[308, 593, 572, 102, 116]</td>\n <td>1.966836</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1140</th>\n <td>[572, 219, 102, 136, 167]</td>\n <td>1.966804</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1141</th>\n <td>[593, 572, 116, 167]</td>\n <td>1.966787</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1142</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 102, 136]</td>\n <td>1.966560</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1143</th>\n <td>[308, 225, 217, 239, 102, 136, 167]</td>\n <td>1.966461</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1144</th>\n <td>[308, 593, 219, 217, 116, 136, 167]</td>\n <td>1.966258</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1145</th>\n <td>[308, 400, 593, 572, 219, 217, 102, 136]</td>\n <td>1.966227</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1146</th>\n <td>[308, 217, 239, 102, 116, 136]</td>\n <td>1.966009</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1147</th>\n <td>[308, 225, 400, 593, 102]</td>\n <td>1.966002</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1148</th>\n <td>[308, 225, 400, 593, 217, 136]</td>\n <td>1.965897</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1149</th>\n <td>[308, 225, 400, 593, 239, 102, 136]</td>\n <td>1.965851</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1150</th>\n <td>[308, 225, 219, 217, 239, 102, 116, 136, 167]</td>\n <td>1.965772</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1151</th>\n <td>[400, 572, 102, 167]</td>\n <td>1.965707</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1152</th>\n <td>[225, 400, 593, 219, 102, 116]</td>\n <td>1.965626</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1153</th>\n <td>[308, 225, 572, 217, 102, 136]</td>\n <td>1.964980</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1154</th>\n <td>[308, 400, 239, 102, 136, 167]</td>\n <td>1.964835</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1155</th>\n <td>[225, 219, 217, 102, 136, 167]</td>\n <td>1.964666</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1156</th>\n <td>[308, 225, 572, 219, 217, 102, 116, 136]</td>\n <td>1.964571</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1157</th>\n <td>[308, 400, 572, 217, 116, 167]</td>\n <td>1.964479</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1158</th>\n <td>[225, 400, 239, 102, 136, 167]</td>\n <td>1.964303</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1159</th>\n <td>[308, 572, 219, 217, 239, 102, 116, 136, 167]</td>\n <td>1.963697</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1160</th>\n <td>[400, 593, 219, 217, 102, 116]</td>\n <td>1.963466</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1161</th>\n <td>[308, 572, 217, 239, 102, 116, 136]</td>\n <td>1.963286</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1162</th>\n <td>[308, 572, 219, 217, 102, 116, 136]</td>\n <td>1.963025</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1163</th>\n <td>[308, 400, 593, 572, 219, 217, 239, 102, 116, ...</td>\n <td>1.962938</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1164</th>\n <td>[593, 219, 116, 136, 167]</td>\n <td>1.962768</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1165</th>\n <td>[593, 572, 239, 116, 136, 167]</td>\n <td>1.962750</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1166</th>\n <td>[308, 400, 219, 116, 136, 167]</td>\n <td>1.962647</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1167</th>\n <td>[225, 400, 593, 219, 217, 102, 116]</td>\n <td>1.962528</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1168</th>\n <td>[308, 225, 219, 217, 102, 116, 136]</td>\n <td>1.961496</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1169</th>\n <td>[308, 225, 572, 217, 239, 102, 136, 167]</td>\n <td>1.961379</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1170</th>\n <td>[225, 400, 593, 572, 219, 217, 239, 102, 116, ...</td>\n <td>1.961232</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1171</th>\n <td>[308, 225, 400, 593, 572, 219, 102, 136]</td>\n <td>1.961200</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1172</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 239, 102, ...</td>\n <td>1.961110</td>\n <td>3</td>\n <td>8</td>\n </tr>\n <tr>\n <th>1173</th>\n <td>[308, 593, 572, 116, 136]</td>\n <td>1.960892</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1174</th>\n <td>[400, 593, 219, 217, 239, 102, 136, 167]</td>\n <td>1.960586</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1175</th>\n <td>[225, 102, 116, 167]</td>\n <td>1.960488</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1176</th>\n <td>[308, 572, 102, 116, 167]</td>\n <td>1.960441</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1177</th>\n <td>[308, 225, 400, 572, 239, 102, 116, 167]</td>\n <td>1.960398</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1178</th>\n <td>[225, 219, 217, 239, 102, 116, 136, 167]</td>\n <td>1.960397</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1179</th>\n <td>[308, 400, 572, 116, 136]</td>\n <td>1.960250</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1180</th>\n <td>[308, 400, 593, 572, 217, 102]</td>\n <td>1.959686</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1181</th>\n <td>[225, 400, 572, 239, 102, 136, 167]</td>\n <td>1.959483</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1182</th>\n <td>[308, 225, 400, 572, 116, 167]</td>\n <td>1.959026</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1183</th>\n <td>[308, 225, 572, 219, 217, 239, 102, 116, 136, ...</td>\n <td>1.958718</td>\n <td>4</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1184</th>\n <td>[308, 400, 572, 239, 102, 136, 167]</td>\n <td>1.958435</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1185</th>\n <td>[308, 225, 400, 572, 239, 116, 136, 167]</td>\n <td>1.958002</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1186</th>\n <td>[400, 593, 116]</td>\n <td>1.957963</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1187</th>\n <td>[308, 225, 400, 593, 572, 217, 239, 102, 116]</td>\n <td>1.957780</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1188</th>\n <td>[308, 593, 219, 102, 116, 167]</td>\n <td>1.957768</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1189</th>\n <td>[308, 400, 593, 219, 217, 239, 102, 136, 167]</td>\n <td>1.957510</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1190</th>\n <td>[308, 225, 400, 593, 219, 239, 102, 116, 136]</td>\n <td>1.957507</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1191</th>\n <td>[225, 400, 593, 572, 217, 116]</td>\n <td>1.957225</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1192</th>\n <td>[400, 593, 572, 219, 217, 102, 116]</td>\n <td>1.957139</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1193</th>\n <td>[308, 225, 400, 593, 219, 217, 239, 102, 136, ...</td>\n <td>1.956830</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1194</th>\n <td>[225, 572, 219, 217, 239, 102, 116, 136, 167]</td>\n <td>1.956611</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1195</th>\n <td>[225, 400, 239, 116, 136, 167]</td>\n <td>1.956463</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1196</th>\n <td>[593, 572, 136, 167]</td>\n <td>1.956184</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1197</th>\n <td>[308, 572, 217, 239, 102, 136, 167]</td>\n <td>1.956015</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1198</th>\n <td>[400, 593, 102]</td>\n <td>1.955895</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1199</th>\n <td>[308, 225, 400, 593, 217, 239, 102, 167]</td>\n <td>1.955731</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1200</th>\n <td>[400, 593, 572, 217, 116]</td>\n <td>1.955631</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1201</th>\n <td>[225, 400, 593, 219, 217, 239, 102, 136, 167]</td>\n <td>1.955456</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1202</th>\n <td>[308, 225, 400, 593, 572, 217, 136]</td>\n <td>1.955325</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1203</th>\n <td>[225, 219, 102, 136, 167]</td>\n <td>1.955096</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1204</th>\n <td>[225, 400, 593, 572, 219, 217, 102, 116]</td>\n <td>1.954931</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1205</th>\n <td>[593, 572, 102, 167]</td>\n <td>1.954471</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1206</th>\n <td>[308, 225, 572, 219, 217, 102, 136, 167]</td>\n <td>1.954454</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1207</th>\n <td>[308, 400, 572, 219, 116, 136, 167]</td>\n <td>1.954379</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1208</th>\n <td>[400, 593, 572, 219, 217, 239, 102, 136, 167]</td>\n <td>1.954308</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1209</th>\n <td>[308, 225, 400, 593, 136]</td>\n <td>1.954210</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1210</th>\n <td>[308, 217, 239, 102, 136, 167]</td>\n <td>1.954097</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1211</th>\n <td>[308, 225, 572, 219, 102, 116, 136]</td>\n <td>1.954060</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1212</th>\n <td>[225, 400, 239, 102, 116, 167]</td>\n <td>1.953999</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1213</th>\n <td>[225, 400, 593, 572, 217, 239, 102, 116]</td>\n <td>1.953926</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1214</th>\n <td>[225, 400, 593, 219, 239, 102, 116, 136]</td>\n <td>1.953909</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1215</th>\n <td>[308, 400, 593, 219, 102, 136]</td>\n <td>1.953605</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1216</th>\n <td>[308, 400, 593, 217, 136]</td>\n <td>1.953121</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1217</th>\n <td>[308, 572, 219, 217, 102, 136, 167]</td>\n <td>1.953053</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1218</th>\n <td>[308, 400, 593, 572, 217, 239, 102, 116]</td>\n <td>1.953020</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1219</th>\n <td>[308, 219, 217, 102, 116, 136]</td>\n <td>1.952858</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1220</th>\n <td>[308, 225, 400, 593, 572, 217, 239, 116, 136]</td>\n <td>1.952597</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1221</th>\n <td>[225, 400, 593, 572, 219, 102, 116]</td>\n <td>1.952277</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1222</th>\n <td>[308, 225, 400, 593, 572, 239, 102, 136]</td>\n <td>1.951806</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1223</th>\n <td>[400, 593, 572, 217, 239, 102, 116]</td>\n <td>1.951711</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1224</th>\n <td>[400, 593, 219, 102, 116]</td>\n <td>1.951678</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1225</th>\n <td>[308, 225, 219, 102, 116, 136]</td>\n <td>1.951212</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1226</th>\n <td>[308, 593, 572, 219, 116, 136, 167]</td>\n <td>1.951211</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1227</th>\n <td>[308, 400, 593, 572, 219, 102, 136]</td>\n <td>1.950943</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1228</th>\n <td>[400, 593, 136]</td>\n <td>1.950893</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1229</th>\n <td>[308, 225, 400, 593, 217, 239, 136, 167]</td>\n <td>1.950885</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1230</th>\n <td>[308, 225, 400, 593, 572, 102]</td>\n <td>1.950860</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1231</th>\n <td>[308, 400, 593, 572, 219, 217, 239, 102, 136, ...</td>\n <td>1.950660</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1232</th>\n <td>[225, 400, 593, 217, 239, 102, 167]</td>\n <td>1.950368</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1233</th>\n <td>[400, 572, 136, 167]</td>\n <td>1.950226</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1234</th>\n <td>[225, 400, 593, 572, 116]</td>\n <td>1.950151</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1235</th>\n <td>[308, 400, 593, 572, 217, 239, 116, 136]</td>\n <td>1.950111</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1236</th>\n <td>[400, 593, 572, 217, 239, 116, 136]</td>\n <td>1.950048</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1237</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 239, 102, ...</td>\n <td>1.949717</td>\n <td>3</td>\n <td>8</td>\n </tr>\n <tr>\n <th>1238</th>\n <td>[308, 400, 593, 219, 239, 102, 116, 136]</td>\n <td>1.949644</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1239</th>\n <td>[308, 400, 239, 116, 136, 167]</td>\n <td>1.949485</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1240</th>\n <td>[308, 225, 400, 593, 217, 116]</td>\n <td>1.949411</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1241</th>\n <td>[225, 572, 217, 102, 116]</td>\n <td>1.949399</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1242</th>\n <td>[572, 219, 217, 102, 116, 167]</td>\n <td>1.949321</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1243</th>\n <td>[400, 593, 572, 102]</td>\n <td>1.949123</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1244</th>\n <td>[225, 400, 593, 572, 219, 217, 239, 102, 136, ...</td>\n <td>1.949062</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1245</th>\n <td>[308, 572, 116, 136, 167]</td>\n <td>1.948662</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1246</th>\n <td>[308, 400, 593, 217, 239, 102, 167]</td>\n <td>1.948625</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1247</th>\n <td>[225, 400, 593, 572, 217, 239, 116, 136]</td>\n <td>1.948417</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1248</th>\n <td>[225, 400, 593, 217, 167]</td>\n <td>1.948222</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1249</th>\n <td>[308, 225, 219, 217, 102, 136, 167]</td>\n <td>1.947798</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1250</th>\n <td>[308, 225, 400, 593, 219, 217, 102, 116]</td>\n <td>1.947340</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1251</th>\n <td>[308, 225, 217, 239, 102, 116, 167]</td>\n <td>1.947211</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1252</th>\n <td>[308, 400, 593, 217, 239, 136, 167]</td>\n <td>1.946752</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1253</th>\n <td>[308, 225, 400, 593, 572, 219, 239, 102, 116, ...</td>\n <td>1.946735</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1254</th>\n <td>[400, 593, 219, 239, 102, 116, 136]</td>\n <td>1.946721</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1255</th>\n <td>[308, 400, 593, 572, 217, 136]</td>\n <td>1.946228</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1256</th>\n <td>[308, 400, 572, 102, 167]</td>\n <td>1.945986</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1257</th>\n <td>[400, 593, 217, 239, 136, 167]</td>\n <td>1.945771</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1258</th>\n <td>[225, 400, 593, 217, 239, 136, 167]</td>\n <td>1.945568</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1259</th>\n <td>[308, 225, 400, 593, 239, 116, 136]</td>\n <td>1.945527</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1260</th>\n <td>[308, 225, 400, 593, 239, 102, 116]</td>\n <td>1.945514</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1261</th>\n <td>[400, 593, 217, 239, 102, 167]</td>\n <td>1.945190</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1262</th>\n <td>[225, 400, 593, 239, 102, 136]</td>\n <td>1.945121</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1263</th>\n <td>[308, 400, 239, 102, 116, 167]</td>\n <td>1.944380</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1264</th>\n <td>[308, 225, 217, 102, 136]</td>\n <td>1.944366</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1265</th>\n <td>[572, 102, 116, 136, 167]</td>\n <td>1.944024</td>\n <td>4</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1266</th>\n <td>[225, 400, 593, 219, 116, 136]</td>\n <td>1.943569</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1267</th>\n <td>[593, 116, 136, 167]</td>\n <td>1.943258</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1268</th>\n <td>[225, 400, 593, 572, 219, 239, 102, 116, 136]</td>\n <td>1.943224</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1269</th>\n <td>[593, 239, 116, 136, 167]</td>\n <td>1.943037</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1270</th>\n <td>[308, 593, 572, 102, 167]</td>\n <td>1.942758</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1271</th>\n <td>[308, 225, 400, 593, 572, 217, 239, 102, 167]</td>\n <td>1.942636</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1272</th>\n <td>[308, 225, 400, 593, 219, 102, 116]</td>\n <td>1.942613</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1273</th>\n <td>[225, 572, 219, 217, 102, 116, 167]</td>\n <td>1.942569</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1274</th>\n <td>[308, 400, 102, 167]</td>\n <td>1.942483</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1275</th>\n <td>[225, 572, 217, 102, 167]</td>\n <td>1.942220</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1276</th>\n <td>[400, 593, 572, 219, 102, 116]</td>\n <td>1.942044</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1277</th>\n <td>[308, 400, 593, 239, 102, 136]</td>\n <td>1.941816</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1278</th>\n <td>[225, 400, 593, 219, 217, 102, 167]</td>\n <td>1.941631</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1279</th>\n <td>[308, 225, 217, 239, 116, 136, 167]</td>\n <td>1.941220</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1280</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 102, 116]</td>\n <td>1.941125</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1281</th>\n <td>[308, 225, 219, 239, 102, 116, 136, 167]</td>\n <td>1.940978</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1282</th>\n <td>[225, 400, 593, 167]</td>\n <td>1.940937</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1283</th>\n <td>[308, 225, 400, 593, 219, 239, 102, 136, 167]</td>\n <td>1.940604</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1284</th>\n <td>[308, 225, 400, 593, 116]</td>\n <td>1.940526</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1285</th>\n <td>[308, 400, 593, 219, 217, 102, 116]</td>\n <td>1.940475</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1286</th>\n <td>[400, 572, 116, 167]</td>\n <td>1.940352</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1287</th>\n <td>[225, 400, 593, 219, 217, 116, 136]</td>\n <td>1.940314</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1288</th>\n <td>[400, 593, 572, 136]</td>\n <td>1.940254</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1289</th>\n <td>[217, 102, 116, 136]</td>\n <td>1.940133</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1290</th>\n <td>[308, 225, 572, 219, 102, 136, 167]</td>\n <td>1.940018</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1291</th>\n <td>[308, 400, 593, 572, 219, 239, 102, 116, 136]</td>\n <td>1.939930</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1292</th>\n <td>[400, 593, 219, 217, 116, 136]</td>\n <td>1.939715</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1293</th>\n <td>[400, 593, 217, 167]</td>\n <td>1.939679</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1294</th>\n <td>[308, 225, 400, 593, 572, 136]</td>\n <td>1.939398</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1295</th>\n <td>[400, 593, 219, 217, 102, 167]</td>\n <td>1.939293</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1296</th>\n <td>[400, 593, 572, 219, 217, 102, 167]</td>\n <td>1.938602</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1297</th>\n <td>[225, 572, 217, 239, 102, 116, 136]</td>\n <td>1.938467</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1298</th>\n <td>[308, 219, 217, 102, 136, 167]</td>\n <td>1.938428</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1299</th>\n <td>[225, 400, 593, 572, 219, 217, 102, 167]</td>\n <td>1.938391</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1300</th>\n <td>[400, 102, 167]</td>\n <td>1.938372</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1301</th>\n <td>[400, 593, 572, 219, 239, 102, 116, 136]</td>\n <td>1.937614</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1302</th>\n <td>[308, 593, 219, 116, 136, 167]</td>\n <td>1.937573</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1303</th>\n <td>[225, 400, 572, 239, 102, 116, 167]</td>\n <td>1.937516</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1304</th>\n <td>[308, 225, 400, 593, 572, 217, 239, 136, 167]</td>\n <td>1.937348</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1305</th>\n <td>[308, 225, 572, 217, 102, 116]</td>\n <td>1.937288</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1306</th>\n <td>[225, 400, 593, 572, 217, 239, 102, 167]</td>\n <td>1.937088</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1307</th>\n <td>[225, 400, 593, 219, 102, 167]</td>\n <td>1.936953</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1308</th>\n <td>[225, 219, 217, 102, 116, 167]</td>\n <td>1.936789</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1309</th>\n <td>[225, 400, 572, 239, 116, 136, 167]</td>\n <td>1.936598</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1310</th>\n <td>[308, 593, 572, 136, 167]</td>\n <td>1.936428</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1311</th>\n <td>[308, 400, 593, 572, 217, 239, 102, 167]</td>\n <td>1.936267</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1312</th>\n <td>[400, 593, 572, 219, 217, 116, 136]</td>\n <td>1.936126</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1313</th>\n <td>[308, 400, 593, 572, 219, 217, 102, 116]</td>\n <td>1.936006</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1314</th>\n <td>[308, 225, 400, 593, 219, 217, 239, 102, 116, ...</td>\n <td>1.935669</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1315</th>\n <td>[593, 572, 239, 102, 116, 167]</td>\n <td>1.935544</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1316</th>\n <td>[225, 400, 593, 572, 239, 102, 136]</td>\n <td>1.935170</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1317</th>\n <td>[308, 572, 217, 102, 136]</td>\n <td>1.935142</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1318</th>\n <td>[225, 400, 593, 572, 219, 217, 116, 136]</td>\n <td>1.935108</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1319</th>\n <td>[308, 225, 572, 217, 239, 102, 116, 167]</td>\n <td>1.935044</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1320</th>\n <td>[225, 572, 217, 239, 102, 136, 167]</td>\n <td>1.934848</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1321</th>\n <td>[225, 400, 593, 219, 239, 102, 136, 167]</td>\n <td>1.934427</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1322</th>\n <td>[593, 102, 116, 167]</td>\n <td>1.934333</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1323</th>\n <td>[572, 217, 102, 136]</td>\n <td>1.934305</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1324</th>\n <td>[308, 225, 400, 593, 217, 239, 116, 167]</td>\n <td>1.934087</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1325</th>\n <td>[308, 225, 572, 219, 239, 102, 116, 136, 167]</td>\n <td>1.934080</td>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1326</th>\n <td>[219, 217, 102, 116, 167]</td>\n <td>1.934069</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1327</th>\n <td>[308, 400, 572, 136, 167]</td>\n <td>1.933999</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1328</th>\n <td>[308, 225, 400, 593, 572, 217, 116]</td>\n <td>1.933642</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1329</th>\n <td>[308, 400, 593, 217, 116]</td>\n <td>1.933590</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1330</th>\n <td>[308, 225, 400, 593, 572, 219, 102, 116]</td>\n <td>1.933500</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1331</th>\n <td>[308, 400, 593, 572, 217, 239, 136, 167]</td>\n <td>1.933208</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1332</th>\n <td>[400, 593, 572, 217, 239, 102, 167]</td>\n <td>1.932892</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1333</th>\n <td>[308, 225, 400, 593, 572, 219, 239, 102, 136, ...</td>\n <td>1.932773</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1334</th>\n <td>[225, 400, 593, 572, 219, 116, 136]</td>\n <td>1.932727</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1335</th>\n <td>[225, 572, 219, 102, 116, 167]</td>\n <td>1.932670</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1336</th>\n <td>[308, 400, 572, 239, 116, 136, 167]</td>\n <td>1.932634</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1337</th>\n <td>[308, 400, 593, 219, 217, 239, 102, 116, 167]</td>\n <td>1.932632</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1338</th>\n <td>[308, 400, 593, 572, 239, 102, 136]</td>\n <td>1.932510</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1339</th>\n <td>[400, 593, 219, 217, 239, 102, 116, 167]</td>\n <td>1.932426</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1340</th>\n <td>[225, 400, 593, 219, 217, 239, 102, 116, 167]</td>\n <td>1.932362</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1341</th>\n <td>[225, 400, 593, 572, 217, 167]</td>\n <td>1.931749</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1342</th>\n <td>[308, 225, 219, 102, 136, 167]</td>\n <td>1.931659</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1343</th>\n <td>[219, 102, 116, 136]</td>\n <td>1.931569</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1344</th>\n <td>[308, 572, 219, 102, 116, 136]</td>\n <td>1.931531</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1345</th>\n <td>[225, 400, 593, 239, 116, 136]</td>\n <td>1.931437</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1346</th>\n <td>[225, 400, 593, 572, 217, 239, 136, 167]</td>\n <td>1.931430</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1347</th>\n <td>[400, 572, 239, 102, 116, 136]</td>\n <td>1.931292</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1348</th>\n <td>[308, 225, 217, 102, 116]</td>\n <td>1.931052</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1349</th>\n <td>[400, 593, 572, 217, 239, 136, 167]</td>\n <td>1.931012</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1350</th>\n <td>[308, 225, 400, 593, 219, 217, 116, 136]</td>\n <td>1.930899</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1351</th>\n <td>[308, 400, 572, 239, 102, 116, 167]</td>\n <td>1.930891</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1352</th>\n <td>[225, 400, 593, 217, 239, 116, 167]</td>\n <td>1.930870</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1353</th>\n <td>[308, 217, 239, 116, 136, 167]</td>\n <td>1.930776</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1354</th>\n <td>[308, 400, 593, 219, 239, 102, 136, 167]</td>\n <td>1.930748</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1355</th>\n <td>[308, 400, 136, 167]</td>\n <td>1.930699</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1356</th>\n <td>[308, 217, 239, 102, 116, 167]</td>\n <td>1.930414</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1357</th>\n <td>[225, 400, 593, 572, 219, 102, 167]</td>\n <td>1.930281</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1358</th>\n <td>[225, 219, 102, 116, 167]</td>\n <td>1.929621</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1359</th>\n <td>[308, 225, 400, 593, 219, 217, 102, 167]</td>\n <td>1.929599</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1360</th>\n <td>[400, 593, 219, 116, 136]</td>\n <td>1.929208</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1361</th>\n <td>[225, 217, 239, 102, 116, 136]</td>\n <td>1.929088</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1362</th>\n <td>[225, 116, 136, 167]</td>\n <td>1.928273</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1363</th>\n <td>[308, 225, 572, 217, 239, 116, 136, 167]</td>\n <td>1.928182</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1364</th>\n <td>[225, 400, 593, 239, 102, 116]</td>\n <td>1.928092</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1365</th>\n <td>[400, 593, 217, 239, 116, 167]</td>\n <td>1.927817</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1366</th>\n <td>[225, 400, 593, 572, 219, 239, 102, 136, 167]</td>\n <td>1.927738</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1367</th>\n <td>[308, 225, 400, 593, 572, 239, 102, 116]</td>\n <td>1.927619</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1368</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 239, 102, ...</td>\n <td>1.927371</td>\n <td>3</td>\n <td>8</td>\n </tr>\n <tr>\n <th>1369</th>\n <td>[308, 225, 593, 217, 239, 102, 136]</td>\n <td>1.927084</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1370</th>\n <td>[308, 225, 400, 593, 219, 217, 239, 116, 136, ...</td>\n <td>1.926872</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1371</th>\n <td>[308, 400, 593, 217, 239, 116, 167]</td>\n <td>1.926760</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1372</th>\n <td>[308, 225, 400, 593, 219, 116, 136]</td>\n <td>1.926737</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1373</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 102, 167]</td>\n <td>1.926470</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1374</th>\n <td>[308, 593, 102, 136]</td>\n <td>1.926228</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1375</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 116, 136]</td>\n <td>1.926083</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1376</th>\n <td>[308, 225, 400, 593, 572, 239, 116, 136]</td>\n <td>1.926010</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1377</th>\n <td>[572, 217, 239, 102, 136, 167]</td>\n <td>1.925971</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1378</th>\n <td>[308, 400, 116, 167]</td>\n <td>1.925438</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1379</th>\n <td>[308, 219, 239, 102, 116, 136, 167]</td>\n <td>1.925196</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1380</th>\n <td>[400, 593, 572, 217, 167]</td>\n <td>1.925141</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1381</th>\n <td>[308, 400, 593, 572, 219, 239, 102, 136, 167]</td>\n <td>1.924616</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1382</th>\n <td>[308, 400, 593, 572, 219, 217, 239, 102, 116, ...</td>\n <td>1.924557</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1383</th>\n <td>[308, 400, 593, 219, 217, 239, 116, 136, 167]</td>\n <td>1.924541</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1384</th>\n <td>[400, 593, 219, 239, 102, 136, 167]</td>\n <td>1.924492</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1385</th>\n <td>[400, 136, 167]</td>\n <td>1.924262</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1386</th>\n <td>[400, 593, 572, 219, 217, 239, 102, 116, 167]</td>\n <td>1.924065</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1387</th>\n <td>[225, 400, 593, 572, 219, 217, 239, 102, 116, ...</td>\n <td>1.924034</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1388</th>\n <td>[308, 225, 572, 219, 217, 102, 116, 167]</td>\n <td>1.923816</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1389</th>\n <td>[572, 217, 239, 102, 116, 136]</td>\n <td>1.923760</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1390</th>\n <td>[308, 400, 593, 219, 217, 116, 136]</td>\n <td>1.923487</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1391</th>\n <td>[308, 400, 593, 219, 102, 116]</td>\n <td>1.923396</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1392</th>\n <td>[308, 225, 572, 217, 102, 167]</td>\n <td>1.923384</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1393</th>\n <td>[308, 400, 593, 239, 116, 136]</td>\n <td>1.923161</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1394</th>\n <td>[308, 572, 217, 239, 102, 116, 167]</td>\n <td>1.922802</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1395</th>\n <td>[308, 225, 400, 593, 217, 167]</td>\n <td>1.922791</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1396</th>\n <td>[308, 572, 219, 239, 102, 116, 136, 167]</td>\n <td>1.922783</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1397</th>\n <td>[400, 593, 219, 217, 239, 116, 136, 167]</td>\n <td>1.922675</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1398</th>\n <td>[308, 225, 593, 572, 217, 239, 102, 136]</td>\n <td>1.922290</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1399</th>\n <td>[400, 239, 102, 116, 136]</td>\n <td>1.922271</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1400</th>\n <td>[400, 593, 572, 219, 116, 136]</td>\n <td>1.922148</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1401</th>\n <td>[225, 219, 239, 102, 116, 136, 167]</td>\n <td>1.921969</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1402</th>\n <td>[225, 400, 593, 219, 217, 239, 116, 136, 167]</td>\n <td>1.921655</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1403</th>\n <td>[308, 225, 219, 217, 102, 116, 167]</td>\n <td>1.921607</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1404</th>\n <td>[225, 572, 219, 239, 102, 116, 136, 167]</td>\n <td>1.921337</td>\n <td>4</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1405</th>\n <td>[308, 225, 400, 593, 239, 102, 167]</td>\n <td>1.921027</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1406</th>\n <td>[225, 217, 239, 102, 136, 167]</td>\n <td>1.920957</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1407</th>\n <td>[308, 225, 400, 593, 239, 136, 167]</td>\n <td>1.920728</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1408</th>\n <td>[308, 400, 593, 572, 219, 217, 116, 136]</td>\n <td>1.920513</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1409</th>\n <td>[308, 400, 593, 219, 217, 102, 167]</td>\n <td>1.920513</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1410</th>\n <td>[400, 593, 572, 219, 239, 102, 136, 167]</td>\n <td>1.920447</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1411</th>\n <td>[308, 572, 217, 239, 116, 136, 167]</td>\n <td>1.920288</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1412</th>\n <td>[308, 593, 217, 239, 102, 136]</td>\n <td>1.920120</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1413</th>\n <td>[308, 400, 593, 572, 217, 116]</td>\n <td>1.920036</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1414</th>\n <td>[308, 400, 593, 572, 219, 217, 102, 167]</td>\n <td>1.919832</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1415</th>\n <td>[308, 225, 400, 593, 219, 102, 167]</td>\n <td>1.919812</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1416</th>\n <td>[225, 400, 593, 219, 217, 136, 167]</td>\n <td>1.919431</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1417</th>\n <td>[308, 225, 400, 593, 572, 219, 116, 136]</td>\n <td>1.918980</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1418</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 239, 116, ...</td>\n <td>1.918950</td>\n <td>3</td>\n <td>8</td>\n </tr>\n <tr>\n <th>1419</th>\n <td>[308, 400, 593, 102]</td>\n <td>1.918909</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1420</th>\n <td>[308, 593, 572, 217, 239, 102, 136]</td>\n <td>1.918804</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1421</th>\n <td>[225, 217, 102, 116]</td>\n <td>1.918793</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1422</th>\n <td>[225, 400, 593, 572, 219, 217, 136, 167]</td>\n <td>1.918540</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1423</th>\n <td>[308, 225, 400, 593, 219, 239, 102, 116, 167]</td>\n <td>1.918533</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1424</th>\n <td>[308, 400, 593, 239, 102, 116]</td>\n <td>1.917949</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1425</th>\n <td>[308, 400, 593, 572, 219, 102, 116]</td>\n <td>1.917911</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1426</th>\n <td>[308, 593, 102, 116]</td>\n <td>1.917848</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1427</th>\n <td>[308, 225, 400, 593, 572, 116]</td>\n <td>1.917830</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1428</th>\n <td>[572, 239, 102, 116, 136, 167]</td>\n <td>1.917790</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1429</th>\n <td>[400, 593, 572, 219, 217, 136, 167]</td>\n <td>1.917537</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1430</th>\n <td>[308, 225, 400, 593, 572, 217, 239, 116, 167]</td>\n <td>1.917480</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1431</th>\n <td>[400, 593, 219, 102, 167]</td>\n <td>1.917185</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1432</th>\n <td>[308, 572, 219, 102, 136, 167]</td>\n <td>1.916774</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1433</th>\n <td>[308, 400, 593, 572, 219, 217, 239, 116, 136, ...</td>\n <td>1.916693</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1434</th>\n <td>[400, 593, 572, 219, 102, 167]</td>\n <td>1.916534</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1435</th>\n <td>[400, 593, 572, 116]</td>\n <td>1.915745</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1436</th>\n <td>[400, 593, 219, 217, 136, 167]</td>\n <td>1.915541</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1437</th>\n <td>[308, 400, 593, 572, 102]</td>\n <td>1.915412</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1438</th>\n <td>[308, 225, 400, 593, 572, 219, 102, 167]</td>\n <td>1.915039</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1439</th>\n <td>[400, 572, 239, 102, 136, 167]</td>\n <td>1.914934</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1440</th>\n <td>[225, 400, 593, 219, 136, 167]</td>\n <td>1.914920</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1441</th>\n <td>[308, 593, 116, 136]</td>\n <td>1.914726</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1442</th>\n <td>[400, 593, 572, 219, 217, 239, 116, 136, 167]</td>\n <td>1.914647</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1443</th>\n <td>[308, 572, 219, 217, 102, 116, 167]</td>\n <td>1.914646</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1444</th>\n <td>[308, 225, 593, 219, 217, 239, 102, 116, 136]</td>\n <td>1.914326</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1445</th>\n <td>[593, 239, 102, 116, 136]</td>\n <td>1.914234</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1446</th>\n <td>[225, 400, 593, 572, 219, 217, 239, 116, 136, ...</td>\n <td>1.913895</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1447</th>\n <td>[308, 593, 572, 116, 167]</td>\n <td>1.913873</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1448</th>\n <td>[308, 593, 219, 217, 239, 102, 116, 136]</td>\n <td>1.913524</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1449</th>\n <td>[308, 219, 102, 116, 136]</td>\n <td>1.913330</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1450</th>\n <td>[308, 225, 400, 593, 219, 217, 136, 167]</td>\n <td>1.913159</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1451</th>\n <td>[308, 225, 572, 217, 116, 136]</td>\n <td>1.913029</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1452</th>\n <td>[308, 225, 400, 593, 572, 217, 167]</td>\n <td>1.912793</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1453</th>\n <td>[225, 400, 593, 572, 167]</td>\n <td>1.912585</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1454</th>\n <td>[225, 217, 239, 102, 116, 167]</td>\n <td>1.912571</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1455</th>\n <td>[593, 572, 219, 217, 102, 136]</td>\n <td>1.912536</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1456</th>\n <td>[308, 400, 572, 116, 167]</td>\n <td>1.912443</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1457</th>\n <td>[219, 102, 136, 167]</td>\n <td>1.911624</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1458</th>\n <td>[308, 225, 400, 593, 219, 239, 116, 136, 167]</td>\n <td>1.911415</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1459</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 136, 167]</td>\n <td>1.911409</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1460</th>\n <td>[308, 593, 572, 219, 217, 239, 102, 116, 136]</td>\n <td>1.911286</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1461</th>\n <td>[308, 400, 593, 136]</td>\n <td>1.911090</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1462</th>\n <td>[308, 225, 593, 572, 219, 217, 239, 102, 116, ...</td>\n <td>1.911055</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1463</th>\n <td>[225, 400, 593, 572, 217, 239, 116, 167]</td>\n <td>1.911037</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1464</th>\n <td>[225, 400, 593, 572, 219, 136, 167]</td>\n <td>1.910703</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1465</th>\n <td>[225, 400, 593, 219, 239, 102, 116, 167]</td>\n <td>1.910620</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1466</th>\n <td>[225, 400, 593, 572, 239, 116, 136]</td>\n <td>1.910375</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1467</th>\n <td>[225, 400, 593, 572, 239, 102, 116]</td>\n <td>1.910242</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1468</th>\n <td>[308, 225, 217, 102, 167]</td>\n <td>1.910146</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1469</th>\n <td>[225, 572, 217, 239, 102, 116, 167]</td>\n <td>1.910005</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1470</th>\n <td>[308, 400, 593, 572, 217, 239, 116, 167]</td>\n <td>1.909574</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1471</th>\n <td>[572, 219, 239, 102, 116, 136, 167]</td>\n <td>1.909380</td>\n <td>4</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1472</th>\n <td>[572, 219, 217, 116, 136, 167]</td>\n <td>1.909264</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1473</th>\n <td>[308, 225, 400, 593, 572, 219, 239, 102, 116, ...</td>\n <td>1.909176</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1474</th>\n <td>[572, 217, 102, 167]</td>\n <td>1.908868</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1475</th>\n <td>[572, 219, 102, 116, 167]</td>\n <td>1.908788</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1476</th>\n <td>[225, 572, 217, 116, 136]</td>\n <td>1.908765</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1477</th>\n <td>[308, 225, 400, 593, 572, 239, 102, 167]</td>\n <td>1.908323</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1478</th>\n <td>[225, 572, 219, 217, 116, 136, 167]</td>\n <td>1.908025</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1479</th>\n <td>[593, 572, 219, 217, 239, 102, 116, 136]</td>\n <td>1.907877</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1480</th>\n <td>[308, 400, 593, 219, 116, 136]</td>\n <td>1.907642</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1481</th>\n <td>[400, 593, 572, 239, 102, 136]</td>\n <td>1.906944</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1482</th>\n <td>[225, 217, 239, 116, 136, 167]</td>\n <td>1.906857</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1483</th>\n <td>[308, 225, 572, 239, 102, 116, 136]</td>\n <td>1.906723</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1484</th>\n <td>[308, 400, 593, 572, 136]</td>\n <td>1.906718</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1485</th>\n <td>[308, 225, 572, 219, 102, 116, 167]</td>\n <td>1.906627</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1486</th>\n <td>[572, 217, 102, 116]</td>\n <td>1.906524</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1487</th>\n <td>[308, 225, 400, 593, 572, 239, 136, 167]</td>\n <td>1.906519</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1488</th>\n <td>[593, 219, 217, 239, 102, 116, 136]</td>\n <td>1.906101</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1489</th>\n <td>[308, 400, 593, 572, 239, 116, 136]</td>\n <td>1.906007</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1490</th>\n <td>[225, 593, 572, 219, 217, 102, 136]</td>\n <td>1.905952</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1491</th>\n <td>[400, 593, 572, 217, 239, 116, 167]</td>\n <td>1.905728</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1492</th>\n <td>[308, 219, 217, 102, 116, 167]</td>\n <td>1.905660</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1493</th>\n <td>[308, 225, 239, 102, 116, 136]</td>\n <td>1.905573</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1494</th>\n <td>[308, 225, 400, 593, 239, 116, 167]</td>\n <td>1.905537</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1495</th>\n <td>[400, 593, 239, 102, 136]</td>\n <td>1.905436</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1496</th>\n <td>[308, 225, 593, 217, 239, 102, 116]</td>\n <td>1.905201</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1497</th>\n <td>[308, 225, 219, 102, 116, 167]</td>\n <td>1.904839</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1498</th>\n <td>[308, 400, 593, 219, 239, 102, 116, 167]</td>\n <td>1.904839</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1499</th>\n <td>[308, 400, 593, 572, 219, 217, 136, 167]</td>\n <td>1.904306</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1500</th>\n <td>[593, 572, 217, 239, 102, 136]</td>\n <td>1.904007</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1501</th>\n <td>[308, 225, 400, 593, 219, 136, 167]</td>\n <td>1.903927</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1502</th>\n <td>[308, 400, 593, 572, 239, 102, 116]</td>\n <td>1.903856</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1503</th>\n <td>[308, 225, 400, 593, 167]</td>\n <td>1.903564</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1504</th>\n <td>[308, 400, 593, 219, 217, 136, 167]</td>\n <td>1.903511</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1505</th>\n <td>[308, 400, 593, 572, 219, 116, 136]</td>\n <td>1.903464</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1506</th>\n <td>[308, 225, 217, 116, 136]</td>\n <td>1.903142</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1507</th>\n <td>[308, 225, 572, 102, 136]</td>\n <td>1.902446</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1508</th>\n <td>[225, 572, 217, 239, 116, 136, 167]</td>\n <td>1.902407</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1509</th>\n <td>[225, 593, 572, 217, 239, 102, 136]</td>\n <td>1.902360</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1510</th>\n <td>[225, 400, 593, 219, 239, 116, 136, 167]</td>\n <td>1.902262</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1511</th>\n <td>[308, 225, 400, 593, 572, 219, 239, 116, 136, ...</td>\n <td>1.902141</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1512</th>\n <td>[308, 400, 593, 217, 167]</td>\n <td>1.902083</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1513</th>\n <td>[400, 239, 116, 136, 167]</td>\n <td>1.901725</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1514</th>\n <td>[225, 593, 572, 219, 217, 239, 102, 116, 136]</td>\n <td>1.901669</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1515</th>\n <td>[225, 400, 593, 572, 219, 239, 102, 116, 167]</td>\n <td>1.901299</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1516</th>\n <td>[225, 593, 219, 217, 239, 102, 116, 136]</td>\n <td>1.901274</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1517</th>\n <td>[308, 225, 400, 219, 217, 239, 102, 116, 136]</td>\n <td>1.901154</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1518</th>\n <td>[225, 217, 102, 167]</td>\n <td>1.901083</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1519</th>\n <td>[308, 225, 593, 217, 239, 116, 136]</td>\n <td>1.900887</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1520</th>\n <td>[225, 572, 217, 136, 167]</td>\n <td>1.900624</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1521</th>\n <td>[308, 225, 572, 219, 217, 116, 136, 167]</td>\n <td>1.900552</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1522</th>\n <td>[308, 225, 593, 219, 217, 239, 102, 136, 167]</td>\n <td>1.900499</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1523</th>\n <td>[308, 225, 400, 593, 572, 219, 136, 167]</td>\n <td>1.900493</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1524</th>\n <td>[225, 400, 593, 239, 136, 167]</td>\n <td>1.900400</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1525</th>\n <td>[308, 572, 217, 102, 116]</td>\n <td>1.900319</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1526</th>\n <td>[219, 239, 102, 116, 136, 167]</td>\n <td>1.900113</td>\n <td>4</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1527</th>\n <td>[225, 400, 219, 217, 102, 136]</td>\n <td>1.899976</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1528</th>\n <td>[308, 225, 593, 572, 219, 217, 239, 102, 136, ...</td>\n <td>1.899888</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1529</th>\n <td>[225, 217, 102, 136]</td>\n <td>1.899884</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1530</th>\n <td>[400, 593, 239, 116, 136]</td>\n <td>1.899423</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1531</th>\n <td>[308, 593, 572, 219, 217, 239, 102, 136, 167]</td>\n <td>1.899409</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1532</th>\n <td>[400, 572, 219, 217, 102, 136]</td>\n <td>1.899399</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1533</th>\n <td>[225, 400, 572, 219, 217, 102, 136]</td>\n <td>1.899279</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1534</th>\n <td>[308, 400, 593, 219, 239, 116, 136, 167]</td>\n <td>1.899166</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1535</th>\n <td>[225, 400, 593, 219, 217, 116, 167]</td>\n <td>1.899084</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1536</th>\n <td>[308, 225, 572, 217, 136, 167]</td>\n <td>1.898858</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1537</th>\n <td>[308, 593, 219, 217, 239, 102, 136, 167]</td>\n <td>1.898395</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1538</th>\n <td>[593, 239, 102, 116, 167]</td>\n <td>1.897991</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1539</th>\n <td>[308, 225, 593, 572, 219, 217, 102, 136]</td>\n <td>1.897873</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1540</th>\n <td>[225, 400, 593, 239, 102, 167]</td>\n <td>1.897619</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1541</th>\n <td>[400, 219, 217, 102, 136]</td>\n <td>1.897439</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1542</th>\n <td>[308, 225, 400, 219, 217, 102, 136]</td>\n <td>1.897244</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1543</th>\n <td>[400, 239, 102, 136, 167]</td>\n <td>1.897172</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1544</th>\n <td>[308, 400, 593, 219, 102, 167]</td>\n <td>1.897168</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1545</th>\n <td>[308, 400, 593, 572, 219, 102, 167]</td>\n <td>1.897123</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1546</th>\n <td>[308, 400, 593, 572, 219, 239, 102, 116, 167]</td>\n <td>1.897044</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1547</th>\n <td>[225, 593, 217, 239, 102, 136]</td>\n <td>1.896702</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1548</th>\n <td>[400, 593, 572, 219, 136, 167]</td>\n <td>1.896567</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1549</th>\n <td>[308, 400, 219, 217, 239, 102, 116, 136]</td>\n <td>1.896456</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1550</th>\n <td>[308, 400, 593, 116]</td>\n <td>1.896365</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1551</th>\n <td>[593, 239, 102, 136, 167]</td>\n <td>1.896306</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1552</th>\n <td>[593, 572, 219, 217, 239, 102, 136, 167]</td>\n <td>1.896251</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1553</th>\n <td>[308, 400, 593, 572, 217, 167]</td>\n <td>1.896103</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1554</th>\n <td>[225, 219, 217, 116, 136, 167]</td>\n <td>1.895942</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1555</th>\n <td>[400, 572, 239, 116, 136, 167]</td>\n <td>1.895788</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1556</th>\n <td>[225, 572, 219, 116, 136, 167]</td>\n <td>1.895638</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1557</th>\n <td>[400, 593, 219, 239, 102, 116, 167]</td>\n <td>1.895555</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1558</th>\n <td>[308, 225, 593, 572, 217, 239, 102, 116]</td>\n <td>1.895475</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1559</th>\n <td>[308, 225, 400, 572, 219, 217, 102, 136]</td>\n <td>1.895379</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1560</th>\n <td>[308, 225, 219, 217, 116, 136, 167]</td>\n <td>1.895285</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1561</th>\n <td>[225, 593, 572, 219, 102, 136]</td>\n <td>1.895143</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1562</th>\n <td>[400, 593, 219, 136, 167]</td>\n <td>1.894684</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1563</th>\n <td>[225, 400, 593, 572, 219, 217, 116, 167]</td>\n <td>1.894519</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1564</th>\n <td>[225, 572, 217, 116, 167]</td>\n <td>1.894493</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1565</th>\n <td>[225, 400, 593, 219, 116, 167]</td>\n <td>1.894372</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1566</th>\n <td>[308, 400, 593, 239, 136, 167]</td>\n <td>1.894235</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1567</th>\n <td>[572, 217, 239, 116, 136, 167]</td>\n <td>1.894157</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1568</th>\n <td>[308, 225, 400, 572, 219, 217, 239, 102, 116, ...</td>\n <td>1.894063</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1569</th>\n <td>[308, 225, 400, 593, 219, 217, 116, 167]</td>\n <td>1.894009</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1570</th>\n <td>[308, 225, 572, 239, 102, 136, 167]</td>\n <td>1.893969</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1571</th>\n <td>[308, 593, 217, 239, 116, 136]</td>\n <td>1.893866</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1572</th>\n <td>[225, 593, 572, 217, 102]</td>\n <td>1.893750</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1573</th>\n <td>[225, 400, 593, 572, 219, 239, 116, 136, 167]</td>\n <td>1.893035</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1574</th>\n <td>[572, 217, 239, 102, 116, 167]</td>\n <td>1.892985</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1575</th>\n <td>[308, 225, 400, 217, 239, 102, 136]</td>\n <td>1.892764</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1576</th>\n <td>[308, 593, 217, 239, 102, 116]</td>\n <td>1.892545</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1577</th>\n <td>[225, 400, 219, 102, 136]</td>\n <td>1.892200</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1578</th>\n <td>[308, 219, 102, 136, 167]</td>\n <td>1.891421</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1579</th>\n <td>[308, 400, 593, 572, 219, 239, 116, 136, 167]</td>\n <td>1.891132</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1580</th>\n <td>[217, 239, 102, 116, 136]</td>\n <td>1.891017</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1581</th>\n <td>[308, 593, 572, 219, 217, 102, 136]</td>\n <td>1.890932</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1582</th>\n <td>[308, 225, 593, 219, 239, 102, 116, 136]</td>\n <td>1.890858</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1583</th>\n <td>[225, 400, 593, 239, 116, 167]</td>\n <td>1.890666</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1584</th>\n <td>[400, 593, 219, 217, 116, 167]</td>\n <td>1.890495</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1585</th>\n <td>[225, 593, 572, 219, 217, 239, 102, 136, 167]</td>\n <td>1.890383</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1586</th>\n <td>[308, 225, 593, 572, 217, 239, 116, 136]</td>\n <td>1.890184</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1587</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 116, 167]</td>\n <td>1.890074</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1588</th>\n <td>[593, 219, 217, 239, 102, 136, 167]</td>\n <td>1.890072</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1589</th>\n <td>[308, 225, 400, 593, 572, 167]</td>\n <td>1.889924</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1590</th>\n <td>[308, 400, 572, 219, 217, 239, 102, 116, 136]</td>\n <td>1.889654</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1591</th>\n <td>[308, 400, 593, 239, 102, 167]</td>\n <td>1.889546</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1592</th>\n <td>[308, 572, 219, 217, 116, 136, 167]</td>\n <td>1.889529</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1593</th>\n <td>[400, 593, 219, 239, 116, 136, 167]</td>\n <td>1.889467</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1594</th>\n <td>[217, 239, 116, 136, 167]</td>\n <td>1.889416</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1595</th>\n <td>[400, 572, 239, 102, 116, 167]</td>\n <td>1.889327</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1596</th>\n <td>[593, 217, 239, 102, 136]</td>\n <td>1.889248</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1597</th>\n <td>[225, 217, 116, 167]</td>\n <td>1.888861</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1598</th>\n <td>[308, 225, 593, 219, 217, 102, 136]</td>\n <td>1.888634</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1599</th>\n <td>[400, 593, 572, 219, 239, 102, 116, 167]</td>\n <td>1.888479</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1600</th>\n <td>[225, 593, 219, 217, 102, 136]</td>\n <td>1.888460</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1601</th>\n <td>[400, 239, 102, 116, 167]</td>\n <td>1.888268</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1602</th>\n <td>[217, 239, 102, 136, 167]</td>\n <td>1.888044</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1603</th>\n <td>[400, 593, 572, 219, 217, 116, 167]</td>\n <td>1.888032</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1604</th>\n <td>[308, 400, 572, 219, 217, 102, 136]</td>\n <td>1.887847</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1605</th>\n <td>[308, 225, 593, 572, 219, 239, 102, 116, 136]</td>\n <td>1.887634</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1606</th>\n <td>[225, 400, 593, 572, 239, 102, 167]</td>\n <td>1.887590</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1607</th>\n <td>[225, 400, 593, 572, 239, 136, 167]</td>\n <td>1.887417</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1608</th>\n <td>[225, 400, 572, 219, 102, 136]</td>\n <td>1.887349</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1609</th>\n <td>[308, 225, 400, 219, 217, 239, 102, 136, 167]</td>\n <td>1.887176</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1610</th>\n <td>[308, 400, 219, 217, 102, 136]</td>\n <td>1.887077</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1611</th>\n <td>[308, 225, 400, 593, 572, 239, 116, 167]</td>\n <td>1.886958</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1612</th>\n <td>[308, 225, 239, 102, 136, 167]</td>\n <td>1.886808</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1613</th>\n <td>[225, 593, 219, 217, 239, 102, 136, 167]</td>\n <td>1.886502</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1614</th>\n <td>[308, 572, 217, 102, 167]</td>\n <td>1.886411</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1615</th>\n <td>[225, 400, 219, 217, 239, 102, 116, 136]</td>\n <td>1.886034</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1616</th>\n <td>[400, 593, 239, 102, 116]</td>\n <td>1.885936</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1617</th>\n <td>[219, 217, 116, 136, 167]</td>\n <td>1.885506</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1618</th>\n <td>[308, 225, 593, 217, 239, 102, 167]</td>\n <td>1.885200</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1619</th>\n <td>[308, 593, 572, 217, 239, 102, 116]</td>\n <td>1.885037</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1620</th>\n <td>[225, 400, 593, 572, 219, 116, 167]</td>\n <td>1.884950</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1621</th>\n <td>[308, 225, 400, 219, 102, 136]</td>\n <td>1.884886</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1622</th>\n <td>[308, 225, 400, 572, 217, 239, 102, 136]</td>\n <td>1.884770</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1623</th>\n <td>[225, 219, 116, 136, 167]</td>\n <td>1.884390</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1624</th>\n <td>[593, 219, 217, 102, 136]</td>\n <td>1.884162</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1625</th>\n <td>[308, 225, 400, 593, 219, 116, 167]</td>\n <td>1.884110</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1626</th>\n <td>[308, 400, 593, 572, 239, 136, 167]</td>\n <td>1.883903</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1627</th>\n <td>[593, 572, 217, 102]</td>\n <td>1.883775</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1628</th>\n <td>[308, 593, 572, 217, 239, 116, 136]</td>\n <td>1.883679</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1629</th>\n <td>[400, 593, 572, 239, 116, 136]</td>\n <td>1.883522</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1630</th>\n <td>[308, 593, 116, 167]</td>\n <td>1.883508</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1631</th>\n <td>[308, 225, 572, 219, 116, 136, 167]</td>\n <td>1.883171</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1632</th>\n <td>[400, 219, 217, 239, 102, 116, 136]</td>\n <td>1.883013</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1633</th>\n <td>[308, 400, 593, 572, 219, 136, 167]</td>\n <td>1.882623</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1634</th>\n <td>[308, 225, 400, 572, 219, 217, 239, 102, 136, ...</td>\n <td>1.882446</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1635</th>\n <td>[308, 400, 593, 572, 239, 102, 167]</td>\n <td>1.882052</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1636</th>\n <td>[400, 593, 167]</td>\n <td>1.882047</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1637</th>\n <td>[308, 225, 217, 136, 167]</td>\n <td>1.881969</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1638</th>\n <td>[400, 593, 572, 219, 239, 116, 136, 167]</td>\n <td>1.881894</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1639</th>\n <td>[308, 225, 593, 572, 219, 102, 136]</td>\n <td>1.881880</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1640</th>\n <td>[308, 400, 593, 219, 136, 167]</td>\n <td>1.881368</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1641</th>\n <td>[308, 400, 593, 572, 116]</td>\n <td>1.881251</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1642</th>\n <td>[308, 400, 219, 217, 239, 102, 136, 167]</td>\n <td>1.881076</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1643</th>\n <td>[308, 225, 400, 572, 219, 102, 136]</td>\n <td>1.881052</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1644</th>\n <td>[217, 239, 102, 116, 167]</td>\n <td>1.881004</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1645</th>\n <td>[308, 400, 593, 219, 217, 116, 167]</td>\n <td>1.880989</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1646</th>\n <td>[593, 572, 219, 102, 136]</td>\n <td>1.880847</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1647</th>\n <td>[308, 217, 102, 136]</td>\n <td>1.880675</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1648</th>\n <td>[308, 225, 593, 217, 239, 136, 167]</td>\n <td>1.880671</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1649</th>\n <td>[308, 225, 572, 217, 116, 167]</td>\n <td>1.880495</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1650</th>\n <td>[225, 400, 572, 219, 217, 239, 102, 116, 136]</td>\n <td>1.880431</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1651</th>\n <td>[308, 225, 593, 572, 217, 239, 102, 167]</td>\n <td>1.880235</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1652</th>\n <td>[308, 593, 102, 167]</td>\n <td>1.879581</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1653</th>\n <td>[308, 225, 572, 102, 116]</td>\n <td>1.879449</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1654</th>\n <td>[225, 593, 217, 239, 102, 116]</td>\n <td>1.879291</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1655</th>\n <td>[308, 400, 593, 572, 219, 217, 116, 167]</td>\n <td>1.879256</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1656</th>\n <td>[219, 102, 116, 167]</td>\n <td>1.879071</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1657</th>\n <td>[308, 225, 400, 219, 239, 102, 116, 136]</td>\n <td>1.879051</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1658</th>\n <td>[308, 225, 217, 116, 167]</td>\n <td>1.879013</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1659</th>\n <td>[308, 225, 593, 572, 217, 102]</td>\n <td>1.878659</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1660</th>\n <td>[308, 225, 219, 116, 136, 167]</td>\n <td>1.878007</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1661</th>\n <td>[308, 225, 400, 593, 572, 219, 116, 167]</td>\n <td>1.877799</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1662</th>\n <td>[400, 572, 219, 217, 239, 102, 116, 136]</td>\n <td>1.877722</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1663</th>\n <td>[308, 225, 239, 116, 136, 167]</td>\n <td>1.877433</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1664</th>\n <td>[308, 400, 572, 219, 217, 239, 102, 136, 167]</td>\n <td>1.877120</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1665</th>\n <td>[308, 225, 593, 219, 217, 239, 102, 116, 167]</td>\n <td>1.877004</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1666</th>\n <td>[308, 219, 217, 116, 136, 167]</td>\n <td>1.876960</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1667</th>\n <td>[308, 400, 593, 239, 116, 167]</td>\n <td>1.876811</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1668</th>\n <td>[400, 593, 572, 239, 102, 116]</td>\n <td>1.876610</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1669</th>\n <td>[308, 400, 217, 239, 102, 136]</td>\n <td>1.876380</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1670</th>\n <td>[308, 572, 217, 116, 136]</td>\n <td>1.876313</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1671</th>\n <td>[225, 593, 217, 239, 116, 136]</td>\n <td>1.876261</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1672</th>\n <td>[593, 217, 239, 116, 136]</td>\n <td>1.876180</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1673</th>\n <td>[308, 593, 136, 167]</td>\n <td>1.875618</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1674</th>\n <td>[225, 593, 219, 102, 136]</td>\n <td>1.875263</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1675</th>\n <td>[225, 400, 219, 217, 102, 116]</td>\n <td>1.875225</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1676</th>\n <td>[308, 572, 219, 102, 116, 167]</td>\n <td>1.874971</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1677</th>\n <td>[308, 593, 219, 217, 102, 136]</td>\n <td>1.874852</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1678</th>\n <td>[308, 225, 593, 572, 217, 239, 136, 167]</td>\n <td>1.874806</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1679</th>\n <td>[308, 225, 400, 219, 217, 102, 116]</td>\n <td>1.874774</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1680</th>\n <td>[308, 593, 572, 219, 239, 102, 116, 136]</td>\n <td>1.874665</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1681</th>\n <td>[308, 225, 400, 217, 239, 102, 116]</td>\n <td>1.874496</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1682</th>\n <td>[308, 225, 593, 572, 219, 217, 239, 102, 116, ...</td>\n <td>1.874473</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1683</th>\n <td>[308, 225, 239, 102, 116, 167]</td>\n <td>1.874402</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1684</th>\n <td>[225, 593, 572, 217, 239, 102, 116]</td>\n <td>1.874177</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1685</th>\n <td>[308, 593, 219, 239, 102, 116, 136]</td>\n <td>1.874124</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1686</th>\n <td>[308, 225, 593, 572, 219, 239, 102, 136, 167]</td>\n <td>1.873393</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1687</th>\n <td>[308, 225, 593, 219, 239, 102, 136, 167]</td>\n <td>1.872903</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1688</th>\n <td>[225, 593, 217, 102]</td>\n <td>1.871851</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1689</th>\n <td>[225, 593, 572, 219, 217, 102, 116]</td>\n <td>1.871453</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1690</th>\n <td>[308, 225, 593, 219, 102, 136]</td>\n <td>1.871332</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1691</th>\n <td>[225, 102, 136, 167]</td>\n <td>1.871321</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1692</th>\n <td>[400, 572, 219, 102, 136]</td>\n <td>1.871212</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1693</th>\n <td>[308, 225, 400, 572, 219, 239, 102, 116, 136]</td>\n <td>1.871155</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1694</th>\n <td>[308, 400, 572, 217, 239, 102, 136]</td>\n <td>1.870887</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1695</th>\n <td>[308, 225, 593, 572, 239, 102, 136]</td>\n <td>1.870723</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1696</th>\n <td>[308, 225, 400, 572, 219, 217, 102, 116]</td>\n <td>1.870699</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1697</th>\n <td>[225, 400, 572, 219, 217, 102, 116]</td>\n <td>1.870656</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1698</th>\n <td>[308, 593, 217, 239, 136, 167]</td>\n <td>1.870601</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1699</th>\n <td>[225, 400, 219, 217, 239, 102, 136, 167]</td>\n <td>1.870592</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1700</th>\n <td>[308, 225, 572, 239, 102, 116, 167]</td>\n <td>1.870155</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1701</th>\n <td>[225, 593, 572, 219, 239, 102, 116, 136]</td>\n <td>1.869971</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1702</th>\n <td>[308, 593, 219, 217, 239, 102, 116, 167]</td>\n <td>1.869768</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1703</th>\n <td>[308, 225, 572, 239, 116, 136, 167]</td>\n <td>1.869686</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1704</th>\n <td>[308, 593, 217, 239, 102, 167]</td>\n <td>1.869626</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1705</th>\n <td>[308, 225, 593, 239, 102, 136]</td>\n <td>1.869612</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1706</th>\n <td>[400, 593, 219, 116, 167]</td>\n <td>1.869550</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1707</th>\n <td>[308, 225, 400, 217, 102]</td>\n <td>1.869347</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1708</th>\n <td>[400, 219, 102, 136]</td>\n <td>1.869340</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1709</th>\n <td>[308, 225, 593, 572, 219, 217, 102, 116]</td>\n <td>1.869141</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1710</th>\n <td>[225, 102, 116, 136]</td>\n <td>1.869046</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1711</th>\n <td>[225, 593, 572, 217, 239, 116, 136]</td>\n <td>1.869010</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1712</th>\n <td>[225, 400, 593, 572, 239, 116, 167]</td>\n <td>1.868855</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1713</th>\n <td>[308, 593, 572, 219, 217, 239, 102, 116, 167]</td>\n <td>1.868702</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1714</th>\n <td>[308, 225, 593, 217, 102]</td>\n <td>1.868636</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1715</th>\n <td>[593, 572, 217, 239, 116, 136]</td>\n <td>1.868457</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1716</th>\n <td>[225, 217, 116, 136]</td>\n <td>1.868383</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1717</th>\n <td>[308, 593, 572, 217, 239, 102, 167]</td>\n <td>1.868317</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1718</th>\n <td>[400, 593, 572, 167]</td>\n <td>1.868206</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1719</th>\n <td>[225, 400, 572, 219, 217, 239, 102, 136, 167]</td>\n <td>1.868054</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1720</th>\n <td>[225, 593, 219, 239, 102, 116, 136]</td>\n <td>1.867706</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1721</th>\n <td>[308, 217, 102, 116]</td>\n <td>1.867603</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1722</th>\n <td>[308, 225, 400, 217, 239, 116, 136]</td>\n <td>1.867322</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1723</th>\n <td>[572, 219, 116, 136, 167]</td>\n <td>1.867110</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1724</th>\n <td>[308, 225, 400, 219, 217, 239, 102, 116, 167]</td>\n <td>1.867005</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1725</th>\n <td>[308, 593, 572, 217, 239, 136, 167]</td>\n <td>1.866774</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1726</th>\n <td>[593, 217, 239, 102, 116]</td>\n <td>1.866564</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1727</th>\n <td>[308, 225, 593, 219, 217, 239, 116, 136, 167]</td>\n <td>1.866449</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1728</th>\n <td>[593, 572, 219, 217, 102, 116]</td>\n <td>1.866383</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1729</th>\n <td>[225, 400, 219, 102, 116]</td>\n <td>1.866281</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1730</th>\n <td>[400, 219, 217, 239, 102, 136, 167]</td>\n <td>1.865853</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1731</th>\n <td>[400, 219, 217, 102, 116]</td>\n <td>1.865742</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1732</th>\n <td>[593, 572, 217, 239, 102, 116]</td>\n <td>1.865713</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1733</th>\n <td>[225, 400, 217, 102]</td>\n <td>1.864899</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1734</th>\n <td>[308, 225, 593, 217, 239, 116, 167]</td>\n <td>1.864840</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1735</th>\n <td>[400, 593, 572, 219, 116, 167]</td>\n <td>1.864760</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1736</th>\n <td>[308, 225, 593, 572, 219, 217, 239, 116, 136, ...</td>\n <td>1.864461</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1737</th>\n <td>[400, 572, 219, 217, 239, 102, 136, 167]</td>\n <td>1.864376</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1738</th>\n <td>[308, 225, 400, 572, 217, 102]</td>\n <td>1.864242</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1739</th>\n <td>[225, 593, 572, 217, 136]</td>\n <td>1.864108</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1740</th>\n <td>[572, 217, 136, 167]</td>\n <td>1.863795</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1741</th>\n <td>[308, 225, 593, 219, 217, 102, 116]</td>\n <td>1.863228</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1742</th>\n <td>[308, 225, 400, 572, 217, 239, 102, 116]</td>\n <td>1.863130</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1743</th>\n <td>[400, 572, 219, 217, 102, 116]</td>\n <td>1.863109</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1744</th>\n <td>[572, 217, 116, 136]</td>\n <td>1.863066</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1745</th>\n <td>[593, 102, 116, 136]</td>\n <td>1.863009</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1746</th>\n <td>[593, 116, 167]</td>\n <td>1.862428</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1747</th>\n <td>[308, 572, 217, 136, 167]</td>\n <td>1.862032</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1748</th>\n <td>[572, 217, 116, 167]</td>\n <td>1.861815</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1749</th>\n <td>[400, 593, 239, 136, 167]</td>\n <td>1.861608</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1750</th>\n <td>[308, 400, 219, 239, 102, 116, 136]</td>\n <td>1.861607</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1751</th>\n <td>[308, 225, 400, 219, 239, 102, 136, 167]</td>\n <td>1.861523</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1752</th>\n <td>[225, 593, 572, 219, 217, 239, 102, 116, 167]</td>\n <td>1.861477</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1753</th>\n <td>[308, 102, 116, 167]</td>\n <td>1.861146</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1754</th>\n <td>[308, 225, 400, 219, 102, 116]</td>\n <td>1.861133</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1755</th>\n <td>[225, 593, 219, 217, 239, 102, 116, 167]</td>\n <td>1.861007</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1756</th>\n <td>[308, 400, 593, 572, 239, 116, 167]</td>\n <td>1.860994</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1757</th>\n <td>[593, 102, 136, 167]</td>\n <td>1.860974</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1758</th>\n <td>[308, 225, 400, 572, 219, 217, 239, 102, 116, ...</td>\n <td>1.860862</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1759</th>\n <td>[308, 400, 572, 219, 102, 136]</td>\n <td>1.860482</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1760</th>\n <td>[225, 593, 219, 217, 102, 116]</td>\n <td>1.860301</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1761</th>\n <td>[308, 593, 219, 217, 239, 116, 136, 167]</td>\n <td>1.860185</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1762</th>\n <td>[308, 400, 219, 217, 102, 116]</td>\n <td>1.860040</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1763</th>\n <td>[225, 400, 572, 217, 102]</td>\n <td>1.859971</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1764</th>\n <td>[308, 225, 593, 572, 217, 136]</td>\n <td>1.859583</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1765</th>\n <td>[308, 225, 572, 116, 136]</td>\n <td>1.859435</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1766</th>\n <td>[308, 593, 572, 219, 217, 239, 116, 136, 167]</td>\n <td>1.859429</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1767</th>\n <td>[593, 572, 219, 217, 239, 102, 116, 167]</td>\n <td>1.859415</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1768</th>\n <td>[308, 593, 572, 219, 239, 102, 136, 167]</td>\n <td>1.859068</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1769</th>\n <td>[308, 225, 102, 116]</td>\n <td>1.859022</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1770</th>\n <td>[308, 400, 219, 102, 136]</td>\n <td>1.858956</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1771</th>\n <td>[308, 219, 102, 116, 167]</td>\n <td>1.858624</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1772</th>\n <td>[308, 400, 572, 219, 217, 102, 116]</td>\n <td>1.858307</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1773</th>\n <td>[225, 593, 572, 217, 239, 102, 167]</td>\n <td>1.858287</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1774</th>\n <td>[308, 400, 593, 219, 116, 167]</td>\n <td>1.858169</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1775</th>\n <td>[308, 593, 572, 219, 102, 136]</td>\n <td>1.857674</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1776</th>\n <td>[308, 225, 572, 102, 167]</td>\n <td>1.857577</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1777</th>\n <td>[308, 400, 219, 217, 239, 102, 116, 167]</td>\n <td>1.857242</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1778</th>\n <td>[308, 102, 116, 136]</td>\n <td>1.857171</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1779</th>\n <td>[593, 219, 217, 239, 102, 116, 167]</td>\n <td>1.857156</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1780</th>\n <td>[308, 225, 400, 572, 219, 239, 102, 136, 167]</td>\n <td>1.856812</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1781</th>\n <td>[400, 593, 572, 239, 136, 167]</td>\n <td>1.856799</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1782</th>\n <td>[593, 572, 219, 239, 102, 116, 136]</td>\n <td>1.856534</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1783</th>\n <td>[308, 225, 102, 136]</td>\n <td>1.856499</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1784</th>\n <td>[225, 593, 217, 239, 102, 167]</td>\n <td>1.856489</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1785</th>\n <td>[308, 225, 400, 219, 217, 239, 116, 136, 167]</td>\n <td>1.856379</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1786</th>\n <td>[308, 225, 400, 219, 217, 102, 167]</td>\n <td>1.856237</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1787</th>\n <td>[225, 593, 572, 219, 102, 116]</td>\n <td>1.856042</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1788</th>\n <td>[308, 400, 593, 572, 219, 116, 167]</td>\n <td>1.855960</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1789</th>\n <td>[225, 400, 572, 219, 102, 116]</td>\n <td>1.855838</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1790</th>\n <td>[308, 225, 400, 572, 217, 239, 116, 136]</td>\n <td>1.855824</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1791</th>\n <td>[308, 400, 572, 219, 239, 102, 116, 136]</td>\n <td>1.855696</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1792</th>\n <td>[308, 225, 400, 572, 219, 217, 102, 167]</td>\n <td>1.855555</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1793</th>\n <td>[308, 593, 572, 219, 217, 102, 116]</td>\n <td>1.855545</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1794</th>\n <td>[225, 400, 219, 239, 102, 116, 136]</td>\n <td>1.855482</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1795</th>\n <td>[308, 225, 400, 219, 217, 116, 136]</td>\n <td>1.855245</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1796</th>\n <td>[308, 225, 400, 217, 239, 102, 167]</td>\n <td>1.855034</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1797</th>\n <td>[593, 572, 217, 136]</td>\n <td>1.854979</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1798</th>\n <td>[225, 593, 572, 219, 217, 102, 167]</td>\n <td>1.854956</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1799</th>\n <td>[225, 400, 217, 239, 102, 136]</td>\n <td>1.854857</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1800</th>\n <td>[225, 593, 572, 219, 239, 102, 136, 167]</td>\n <td>1.854708</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1801</th>\n <td>[308, 225, 593, 239, 116, 136]</td>\n <td>1.854678</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1802</th>\n <td>[308, 400, 217, 239, 102, 116]</td>\n <td>1.854549</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1803</th>\n <td>[308, 225, 400, 572, 219, 102, 116]</td>\n <td>1.854362</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1804</th>\n <td>[308, 225, 593, 572, 219, 217, 102, 167]</td>\n <td>1.854076</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1805</th>\n <td>[308, 593, 219, 239, 102, 136, 167]</td>\n <td>1.853867</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1806</th>\n <td>[225, 400, 572, 219, 217, 102, 167]</td>\n <td>1.853528</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1807</th>\n <td>[308, 225, 593, 572, 217, 239, 116, 167]</td>\n <td>1.853431</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1808</th>\n <td>[225, 400, 219, 217, 102, 167]</td>\n <td>1.853222</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1809</th>\n <td>[225, 400, 572, 217, 239, 102, 136]</td>\n <td>1.853179</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1810</th>\n <td>[225, 593, 217, 239, 136, 167]</td>\n <td>1.853127</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1811</th>\n <td>[308, 225, 400, 572, 219, 217, 116, 136]</td>\n <td>1.853088</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1812</th>\n <td>[225, 593, 572, 217, 239, 136, 167]</td>\n <td>1.852939</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1813</th>\n <td>[308, 400, 572, 219, 217, 239, 102, 116, 167]</td>\n <td>1.851793</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1814</th>\n <td>[400, 593, 239, 116, 167]</td>\n <td>1.851675</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1815</th>\n <td>[593, 572, 217, 239, 136, 167]</td>\n <td>1.851470</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1816</th>\n <td>[308, 572, 239, 102, 116, 136]</td>\n <td>1.851368</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1817</th>\n <td>[308, 400, 593, 167]</td>\n <td>1.851263</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1818</th>\n <td>[308, 593, 217, 239, 116, 167]</td>\n <td>1.851074</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1819</th>\n <td>[308, 225, 593, 239, 102, 116]</td>\n <td>1.850985</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1820</th>\n <td>[308, 225, 400, 572, 219, 217, 239, 116, 136, ...</td>\n <td>1.850853</td>\n <td>3</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1821</th>\n <td>[308, 572, 219, 116, 136, 167]</td>\n <td>1.850510</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1822</th>\n <td>[400, 593, 572, 239, 102, 167]</td>\n <td>1.850397</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1823</th>\n <td>[308, 225, 593, 572, 219, 102, 116]</td>\n <td>1.850300</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1824</th>\n <td>[308, 593, 572, 217, 102]</td>\n <td>1.850234</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1825</th>\n <td>[308, 400, 217, 239, 116, 136]</td>\n <td>1.850021</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1826</th>\n <td>[308, 116, 136, 167]</td>\n <td>1.849993</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1827</th>\n <td>[308, 225, 593, 572, 219, 217, 116, 136]</td>\n <td>1.849941</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1828</th>\n <td>[225, 400, 572, 219, 239, 102, 116, 136]</td>\n <td>1.849814</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1829</th>\n <td>[225, 217, 136, 167]</td>\n <td>1.849579</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1830</th>\n <td>[593, 217, 239, 136, 167]</td>\n <td>1.849249</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1831</th>\n <td>[400, 593, 239, 102, 167]</td>\n <td>1.849200</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1832</th>\n <td>[225, 400, 219, 217, 239, 102, 116, 167]</td>\n <td>1.849155</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1833</th>\n <td>[308, 225, 400, 217, 136]</td>\n <td>1.849147</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1834</th>\n <td>[225, 593, 572, 219, 217, 239, 116, 136, 167]</td>\n <td>1.848956</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1835</th>\n <td>[593, 572, 217, 239, 102, 167]</td>\n <td>1.848899</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1836</th>\n <td>[308, 225, 593, 219, 239, 102, 116, 167]</td>\n <td>1.848561</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1837</th>\n <td>[308, 400, 593, 572, 167]</td>\n <td>1.848344</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1838</th>\n <td>[308, 225, 400, 593, 219, 217, 239, 102, 136]</td>\n <td>1.848237</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1839</th>\n <td>[593, 572, 219, 217, 102, 167]</td>\n <td>1.848183</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1840</th>\n <td>[225, 400, 219, 217, 116, 136]</td>\n <td>1.848030</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1841</th>\n <td>[593, 572, 219, 217, 239, 116, 136, 167]</td>\n <td>1.847885</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1842</th>\n <td>[308, 225, 400, 217, 239, 136, 167]</td>\n <td>1.847715</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1843</th>\n <td>[308, 225, 400, 572, 217, 239, 102, 167]</td>\n <td>1.847613</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1844</th>\n <td>[225, 593, 219, 217, 239, 116, 136, 167]</td>\n <td>1.847596</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1845</th>\n <td>[308, 225, 593, 217, 136]</td>\n <td>1.847327</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1846</th>\n <td>[593, 219, 239, 102, 116, 136]</td>\n <td>1.847245</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1847</th>\n <td>[225, 593, 219, 239, 102, 136, 167]</td>\n <td>1.847237</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1848</th>\n <td>[225, 572, 102, 116]</td>\n <td>1.847216</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1849</th>\n <td>[308, 400, 219, 217, 239, 116, 136, 167]</td>\n <td>1.847053</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1850</th>\n <td>[225, 400, 572, 219, 217, 116, 136]</td>\n <td>1.846876</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1851</th>\n <td>[308, 225, 593, 572, 219, 239, 102, 116, 167]</td>\n <td>1.846448</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1852</th>\n <td>[225, 593, 217, 116]</td>\n <td>1.846395</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1853</th>\n <td>[593, 219, 217, 102, 116]</td>\n <td>1.846373</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1854</th>\n <td>[308, 225, 400, 572, 217, 136]</td>\n <td>1.846210</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1855</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 239, 102, ...</td>\n <td>1.846168</td>\n <td>2</td>\n <td>8</td>\n </tr>\n <tr>\n <th>1856</th>\n <td>[225, 593, 572, 217, 116]</td>\n <td>1.846087</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1857</th>\n <td>[225, 593, 219, 102, 116]</td>\n <td>1.846086</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1858</th>\n <td>[593, 219, 217, 239, 116, 136, 167]</td>\n <td>1.845138</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1859</th>\n <td>[308, 400, 572, 217, 239, 102, 116]</td>\n <td>1.845000</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1860</th>\n <td>[308, 225, 593, 572, 239, 116, 136]</td>\n <td>1.844849</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1861</th>\n <td>[225, 593, 217, 239, 116, 167]</td>\n <td>1.844703</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1862</th>\n <td>[308, 225, 593, 572, 239, 102, 116]</td>\n <td>1.844412</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1863</th>\n <td>[308, 225, 593, 219, 102, 116]</td>\n <td>1.844402</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1864</th>\n <td>[225, 593, 572, 219, 217, 116, 136]</td>\n <td>1.844391</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1865</th>\n <td>[308, 217, 102, 167]</td>\n <td>1.844321</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1866</th>\n <td>[225, 572, 102, 136]</td>\n <td>1.844299</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1867</th>\n <td>[308, 225, 593, 219, 217, 102, 167]</td>\n <td>1.844288</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1868</th>\n <td>[225, 400, 572, 219, 217, 239, 102, 116, 167]</td>\n <td>1.844253</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1869</th>\n <td>[400, 572, 219, 217, 102, 167]</td>\n <td>1.843820</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1870</th>\n <td>[308, 102, 136, 167]</td>\n <td>1.843650</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1871</th>\n <td>[308, 593, 219, 217, 102, 116]</td>\n <td>1.843513</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1872</th>\n <td>[308, 400, 572, 219, 217, 239, 116, 136, 167]</td>\n <td>1.842116</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1873</th>\n <td>[308, 400, 219, 239, 102, 136, 167]</td>\n <td>1.841918</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1874</th>\n <td>[308, 225, 593, 219, 217, 116, 136]</td>\n <td>1.841868</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1875</th>\n <td>[308, 225, 400, 239, 102, 136]</td>\n <td>1.841582</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1876</th>\n <td>[308, 225, 400, 219, 116, 136]</td>\n <td>1.841541</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1877</th>\n <td>[308, 400, 572, 219, 217, 102, 167]</td>\n <td>1.841522</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1878</th>\n <td>[308, 225, 400, 219, 239, 102, 116, 167]</td>\n <td>1.840814</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1879</th>\n <td>[308, 225, 593, 219, 239, 116, 136, 167]</td>\n <td>1.840353</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1880</th>\n <td>[308, 217, 116, 136]</td>\n <td>1.840231</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1881</th>\n <td>[308, 225, 400, 572, 217, 239, 136, 167]</td>\n <td>1.840204</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1882</th>\n <td>[593, 217, 239, 102, 167]</td>\n <td>1.840150</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1883</th>\n <td>[308, 593, 572, 217, 239, 116, 167]</td>\n <td>1.840145</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1884</th>\n <td>[308, 572, 217, 116, 167]</td>\n <td>1.840031</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1885</th>\n <td>[400, 219, 217, 102, 167]</td>\n <td>1.840012</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1886</th>\n <td>[593, 572, 219, 239, 102, 136, 167]</td>\n <td>1.839928</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1887</th>\n <td>[308, 400, 572, 219, 239, 102, 136, 167]</td>\n <td>1.839920</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1888</th>\n <td>[308, 400, 572, 219, 217, 116, 136]</td>\n <td>1.839745</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1889</th>\n <td>[593, 217, 239, 116, 167]</td>\n <td>1.839693</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1890</th>\n <td>[308, 400, 572, 217, 239, 116, 136]</td>\n <td>1.839617</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1891</th>\n <td>[308, 400, 593, 219, 217, 239, 102, 136]</td>\n <td>1.839587</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1892</th>\n <td>[225, 400, 217, 239, 102, 116]</td>\n <td>1.839538</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1893</th>\n <td>[400, 219, 217, 239, 102, 116, 167]</td>\n <td>1.839530</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1894</th>\n <td>[308, 400, 219, 217, 116, 136]</td>\n <td>1.839309</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1895</th>\n <td>[225, 593, 116]</td>\n <td>1.839211</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1896</th>\n <td>[308, 400, 219, 217, 102, 167]</td>\n <td>1.839033</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1897</th>\n <td>[225, 593, 572, 102]</td>\n <td>1.838909</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1898</th>\n <td>[308, 593, 572, 219, 217, 102, 167]</td>\n <td>1.838904</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1899</th>\n <td>[308, 400, 593, 572, 219, 217, 239, 102, 136]</td>\n <td>1.838527</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1900</th>\n <td>[308, 572, 239, 102, 136, 167]</td>\n <td>1.838521</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1901</th>\n <td>[308, 225, 593, 572, 219, 239, 116, 136, 167]</td>\n <td>1.838318</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1902</th>\n <td>[225, 593, 219, 217, 102, 167]</td>\n <td>1.838093</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1903</th>\n <td>[308, 225, 593, 572, 217, 116]</td>\n <td>1.838059</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1904</th>\n <td>[308, 225, 400, 572, 219, 217, 136, 167]</td>\n <td>1.837932</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1905</th>\n <td>[225, 400, 219, 116, 136]</td>\n <td>1.837767</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1906</th>\n <td>[593, 219, 102, 136]</td>\n <td>1.837302</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1907</th>\n <td>[308, 225, 572, 136, 167]</td>\n <td>1.837249</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1908</th>\n <td>[308, 225, 400, 217, 116]</td>\n <td>1.837191</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1909</th>\n <td>[400, 572, 219, 217, 116, 136]</td>\n <td>1.837071</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1910</th>\n <td>[308, 225, 116, 136]</td>\n <td>1.836971</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1911</th>\n <td>[308, 225, 400, 219, 102, 167]</td>\n <td>1.836960</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1912</th>\n <td>[308, 225, 400, 572, 219, 116, 136]</td>\n <td>1.836813</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1913</th>\n <td>[308, 225, 400, 219, 217, 136, 167]</td>\n <td>1.836728</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1914</th>\n <td>[308, 225, 400, 572, 239, 102, 136]</td>\n <td>1.836710</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1915</th>\n <td>[225, 593, 217, 136]</td>\n <td>1.836660</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1916</th>\n <td>[308, 400, 572, 217, 102]</td>\n <td>1.836488</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1917</th>\n <td>[593, 572, 219, 217, 116, 136]</td>\n <td>1.836363</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1918</th>\n <td>[308, 225, 593, 217, 116]</td>\n <td>1.836292</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1919</th>\n <td>[400, 219, 102, 116]</td>\n <td>1.836047</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1920</th>\n <td>[225, 400, 219, 217, 239, 116, 136, 167]</td>\n <td>1.835858</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1921</th>\n <td>[400, 219, 217, 116, 136]</td>\n <td>1.835494</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1922</th>\n <td>[400, 572, 219, 217, 239, 102, 116, 167]</td>\n <td>1.835433</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1923</th>\n <td>[225, 400, 219, 102, 167]</td>\n <td>1.835353</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1924</th>\n <td>[308, 593, 572, 219, 217, 116, 136]</td>\n <td>1.835309</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1925</th>\n <td>[225, 400, 219, 239, 102, 136, 167]</td>\n <td>1.835212</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1926</th>\n <td>[308, 225, 400, 572, 219, 102, 167]</td>\n <td>1.835071</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1927</th>\n <td>[308, 225, 593, 572, 219, 217, 136, 167]</td>\n <td>1.834828</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1928</th>\n <td>[400, 593, 572, 239, 116, 167]</td>\n <td>1.834670</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1929</th>\n <td>[308, 225, 219, 217, 239, 102, 116, 136]</td>\n <td>1.834273</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1930</th>\n <td>[308, 593, 219, 102, 136]</td>\n <td>1.834268</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1931</th>\n <td>[308, 225, 400, 572, 219, 239, 102, 116, 167]</td>\n <td>1.834249</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1932</th>\n <td>[308, 400, 217, 102]</td>\n <td>1.834159</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1933</th>\n <td>[225, 400, 217, 136]</td>\n <td>1.834127</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1934</th>\n <td>[308, 225, 572, 219, 217, 239, 102, 116, 136]</td>\n <td>1.834085</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1935</th>\n <td>[308, 225, 400, 217, 239, 116, 167]</td>\n <td>1.833982</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1936</th>\n <td>[225, 400, 572, 219, 239, 102, 136, 167]</td>\n <td>1.833902</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1937</th>\n <td>[225, 400, 572, 217, 136]</td>\n <td>1.833858</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1938</th>\n <td>[400, 572, 217, 239, 102, 136]</td>\n <td>1.833767</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1939</th>\n <td>[400, 219, 239, 102, 116, 136]</td>\n <td>1.833175</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1940</th>\n <td>[225, 400, 572, 219, 102, 167]</td>\n <td>1.832662</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1941</th>\n <td>[400, 572, 217, 102]</td>\n <td>1.832616</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1942</th>\n <td>[225, 593, 572, 217, 239, 116, 167]</td>\n <td>1.832541</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1943</th>\n <td>[225, 593, 572, 219, 102, 167]</td>\n <td>1.832409</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1944</th>\n <td>[308, 400, 217, 239, 102, 167]</td>\n <td>1.832371</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1945</th>\n <td>[225, 400, 217, 116]</td>\n <td>1.832241</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1946</th>\n <td>[308, 593, 572, 239, 102, 136]</td>\n <td>1.832236</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1947</th>\n <td>[308, 593, 572, 217, 136]</td>\n <td>1.832199</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1948</th>\n <td>[308, 225, 593, 572, 102]</td>\n <td>1.832177</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1949</th>\n <td>[225, 400, 572, 219, 217, 239, 116, 136, 167]</td>\n <td>1.831922</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1950</th>\n <td>[308, 225, 400, 219, 239, 116, 136, 167]</td>\n <td>1.831670</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1951</th>\n <td>[308, 225, 593, 572, 219, 116, 136]</td>\n <td>1.831428</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1952</th>\n <td>[225, 400, 572, 219, 116, 136]</td>\n <td>1.831346</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1953</th>\n <td>[225, 400, 572, 217, 239, 102, 116]</td>\n <td>1.831319</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1954</th>\n <td>[225, 400, 217, 239, 116, 136]</td>\n <td>1.831181</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1955</th>\n <td>[400, 572, 219, 239, 102, 116, 136]</td>\n <td>1.831021</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1956</th>\n <td>[400, 572, 219, 102, 116]</td>\n <td>1.830807</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1957</th>\n <td>[308, 219, 116, 136, 167]</td>\n <td>1.830520</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1958</th>\n <td>[308, 400, 219, 102, 116]</td>\n <td>1.830431</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1959</th>\n <td>[308, 225, 593, 572, 219, 102, 167]</td>\n <td>1.830428</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1960</th>\n <td>[593, 572, 217, 116]</td>\n <td>1.830390</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1961</th>\n <td>[225, 400, 572, 219, 217, 136, 167]</td>\n <td>1.829726</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1962</th>\n <td>[225, 572, 102, 167]</td>\n <td>1.829468</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1963</th>\n <td>[225, 593, 219, 217, 116, 136]</td>\n <td>1.829134</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1964</th>\n <td>[400, 217, 239, 102, 136]</td>\n <td>1.829133</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1965</th>\n <td>[308, 225, 400, 102]</td>\n <td>1.828904</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1966</th>\n <td>[308, 225, 400, 593, 219, 217, 239, 102, 116]</td>\n <td>1.828764</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1967</th>\n <td>[308, 400, 572, 219, 102, 116]</td>\n <td>1.828459</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1968</th>\n <td>[225, 593, 572, 219, 116, 136]</td>\n <td>1.828297</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1969</th>\n <td>[225, 400, 593, 572, 219, 217, 239, 102, 136]</td>\n <td>1.827859</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1970</th>\n <td>[308, 400, 572, 217, 239, 102, 167]</td>\n <td>1.827796</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1971</th>\n <td>[225, 593, 572, 219, 217, 136, 167]</td>\n <td>1.827785</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1972</th>\n <td>[308, 225, 400, 572, 217, 116]</td>\n <td>1.827709</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1973</th>\n <td>[308, 400, 217, 239, 136, 167]</td>\n <td>1.827610</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1974</th>\n <td>[593, 572, 219, 102, 116]</td>\n <td>1.827397</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1975</th>\n <td>[225, 400, 593, 219, 217, 239, 102, 136]</td>\n <td>1.827354</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1976</th>\n <td>[219, 116, 136, 167]</td>\n <td>1.827027</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1977</th>\n <td>[400, 219, 217, 239, 116, 136, 167]</td>\n <td>1.826700</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1978</th>\n <td>[308, 593, 572, 219, 239, 102, 116, 167]</td>\n <td>1.826502</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1979</th>\n <td>[308, 572, 219, 217, 239, 102, 116, 136]</td>\n <td>1.826412</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1980</th>\n <td>[308, 225, 593, 239, 136, 167]</td>\n <td>1.826293</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1981</th>\n <td>[308, 225, 572, 116, 167]</td>\n <td>1.826175</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1982</th>\n <td>[400, 217, 102]</td>\n <td>1.826118</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1983</th>\n <td>[225, 400, 219, 217, 136, 167]</td>\n <td>1.826076</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1984</th>\n <td>[593, 217, 102]</td>\n <td>1.825738</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1985</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 239, 102, ...</td>\n <td>1.825555</td>\n <td>2</td>\n <td>8</td>\n </tr>\n <tr>\n <th>1986</th>\n <td>[308, 225, 400, 239, 102, 116]</td>\n <td>1.825478</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1987</th>\n <td>[308, 225, 400, 572, 219, 239, 116, 136, 167]</td>\n <td>1.825458</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1988</th>\n <td>[308, 219, 217, 239, 102, 116, 136]</td>\n <td>1.824933</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1989</th>\n <td>[308, 225, 102, 167]</td>\n <td>1.824821</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1990</th>\n <td>[308, 239, 102, 116, 136]</td>\n <td>1.824431</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>1991</th>\n <td>[308, 593, 219, 239, 102, 116, 167]</td>\n <td>1.824317</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1992</th>\n <td>[225, 593, 572, 219, 239, 102, 116, 167]</td>\n <td>1.824159</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1993</th>\n <td>[593, 572, 217, 239, 116, 167]</td>\n <td>1.824138</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1994</th>\n <td>[308, 225, 593, 572, 239, 136, 167]</td>\n <td>1.823928</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1995</th>\n <td>[308, 225, 400, 572, 102]</td>\n <td>1.823817</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>1996</th>\n <td>[308, 225, 593, 572, 239, 102, 167]</td>\n <td>1.823765</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1997</th>\n <td>[593, 219, 239, 102, 136, 167]</td>\n <td>1.823756</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>1998</th>\n <td>[308, 225, 400, 593, 219, 239, 102, 136]</td>\n <td>1.823645</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>1999</th>\n <td>[400, 572, 219, 217, 239, 116, 136, 167]</td>\n <td>1.823431</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2000</th>\n <td>[308, 225, 593, 219, 116, 136]</td>\n <td>1.823298</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2001</th>\n <td>[308, 225, 593, 239, 102, 167]</td>\n <td>1.823117</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2002</th>\n <td>[308, 400, 572, 219, 217, 136, 167]</td>\n <td>1.822937</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2003</th>\n <td>[308, 225, 593, 219, 217, 136, 167]</td>\n <td>1.822912</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2004</th>\n <td>[308, 225, 572, 219, 217, 239, 102, 136, 167]</td>\n <td>1.822771</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2005</th>\n <td>[308, 225, 400, 239, 116, 136]</td>\n <td>1.822688</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2006</th>\n <td>[225, 400, 572, 217, 239, 116, 136]</td>\n <td>1.822680</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2007</th>\n <td>[308, 225, 400, 593, 217, 239, 102]</td>\n <td>1.822680</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2008</th>\n <td>[308, 225, 400, 572, 217, 239, 116, 167]</td>\n <td>1.822672</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2009</th>\n <td>[308, 593, 217, 102]</td>\n <td>1.822541</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2010</th>\n <td>[308, 400, 572, 217, 239, 136, 167]</td>\n <td>1.822264</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2011</th>\n <td>[225, 572, 116, 167]</td>\n <td>1.821992</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2012</th>\n <td>[308, 593, 219, 217, 102, 167]</td>\n <td>1.821970</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2013</th>\n <td>[225, 593, 219, 239, 102, 116, 167]</td>\n <td>1.821680</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2014</th>\n <td>[308, 225, 400, 593, 572, 219, 239, 102, 136]</td>\n <td>1.821634</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2015</th>\n <td>[308, 593, 219, 217, 116, 136]</td>\n <td>1.820856</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2016</th>\n <td>[400, 593, 572, 219, 217, 239, 102, 136]</td>\n <td>1.820780</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2017</th>\n <td>[593, 219, 217, 102, 167]</td>\n <td>1.820409</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2018</th>\n <td>[308, 225, 219, 217, 239, 102, 136, 167]</td>\n <td>1.820090</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2019</th>\n <td>[308, 593, 572, 219, 239, 116, 136, 167]</td>\n <td>1.820060</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2020</th>\n <td>[308, 225, 400, 593, 219, 217, 239, 116, 136]</td>\n <td>1.819579</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2021</th>\n <td>[308, 225, 400, 219, 217, 116, 167]</td>\n <td>1.819033</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2022</th>\n <td>[308, 225, 116, 167]</td>\n <td>1.818955</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2023</th>\n <td>[400, 593, 219, 217, 239, 102, 136]</td>\n <td>1.818861</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2024</th>\n <td>[308, 225, 593, 219, 102, 167]</td>\n <td>1.818753</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2025</th>\n <td>[225, 593, 572, 217, 167]</td>\n <td>1.818744</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2026</th>\n <td>[593, 217, 116]</td>\n <td>1.818694</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2027</th>\n <td>[308, 593, 572, 219, 102, 116]</td>\n <td>1.818634</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2028</th>\n <td>[308, 593, 572, 219, 217, 136, 167]</td>\n <td>1.818592</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2029</th>\n <td>[308, 400, 572, 217, 136]</td>\n <td>1.818478</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2030</th>\n <td>[308, 593, 219, 239, 116, 136, 167]</td>\n <td>1.818372</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2031</th>\n <td>[308, 400, 219, 217, 136, 167]</td>\n <td>1.818316</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2032</th>\n <td>[593, 572, 219, 217, 136, 167]</td>\n <td>1.817976</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2033</th>\n <td>[400, 572, 219, 217, 136, 167]</td>\n <td>1.817737</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2034</th>\n <td>[308, 217, 116, 167]</td>\n <td>1.817710</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2035</th>\n <td>[225, 593, 572, 136]</td>\n <td>1.817697</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2036</th>\n <td>[308, 225, 400, 572, 219, 217, 116, 167]</td>\n <td>1.817648</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2037</th>\n <td>[308, 572, 239, 116, 136, 167]</td>\n <td>1.817591</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2038</th>\n <td>[308, 400, 219, 239, 102, 116, 167]</td>\n <td>1.817557</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2039</th>\n <td>[308, 225, 400, 572, 219, 136, 167]</td>\n <td>1.817513</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2040</th>\n <td>[225, 400, 572, 217, 116]</td>\n <td>1.817471</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2041</th>\n <td>[308, 225, 593, 572, 136]</td>\n <td>1.817413</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2042</th>\n <td>[308, 225, 400, 593, 572, 217, 239, 102]</td>\n <td>1.817399</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2043</th>\n <td>[308, 225, 400, 219, 136, 167]</td>\n <td>1.817399</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2044</th>\n <td>[225, 572, 239, 102, 116, 136]</td>\n <td>1.817040</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2045</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 239, 116, ...</td>\n <td>1.816816</td>\n <td>2</td>\n <td>8</td>\n </tr>\n <tr>\n <th>2046</th>\n <td>[308, 400, 593, 219, 217, 239, 102, 116]</td>\n <td>1.816794</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2047</th>\n <td>[225, 400, 217, 239, 102, 167]</td>\n <td>1.816757</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2048</th>\n <td>[308, 225, 400, 593, 217, 239, 136]</td>\n <td>1.816682</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2049</th>\n <td>[308, 217, 136, 167]</td>\n <td>1.816527</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2050</th>\n <td>[308, 225, 400, 572, 239, 102, 116]</td>\n <td>1.815672</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2051</th>\n <td>[308, 593, 239, 102, 136]</td>\n <td>1.815464</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2052</th>\n <td>[308, 225, 593, 572, 217, 167]</td>\n <td>1.815454</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2053</th>\n <td>[225, 593, 572, 239, 102, 136]</td>\n <td>1.815177</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2054</th>\n <td>[308, 225, 593, 239, 116, 167]</td>\n <td>1.815002</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2055</th>\n <td>[308, 225, 572, 219, 217, 102, 136]</td>\n <td>1.814572</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2056</th>\n <td>[308, 400, 593, 572, 219, 217, 239, 102, 116]</td>\n <td>1.814559</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2057</th>\n <td>[308, 572, 219, 217, 239, 102, 136, 167]</td>\n <td>1.814412</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2058</th>\n <td>[308, 225, 593, 102]</td>\n <td>1.814383</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2059</th>\n <td>[225, 593, 572, 219, 239, 116, 136, 167]</td>\n <td>1.814332</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2060</th>\n <td>[225, 400, 572, 217, 239, 102, 167]</td>\n <td>1.814090</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2061</th>\n <td>[308, 400, 217, 136]</td>\n <td>1.814036</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2062</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 102]</td>\n <td>1.814008</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2063</th>\n <td>[225, 400, 219, 239, 102, 116, 167]</td>\n <td>1.813817</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2064</th>\n <td>[225, 593, 572, 116]</td>\n <td>1.813648</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2065</th>\n <td>[225, 593, 219, 116, 136]</td>\n <td>1.813515</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2066</th>\n <td>[308, 400, 572, 219, 239, 102, 116, 167]</td>\n <td>1.813488</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2067</th>\n <td>[225, 572, 116, 136]</td>\n <td>1.813442</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2068</th>\n <td>[400, 572, 219, 239, 102, 136, 167]</td>\n <td>1.813333</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2069</th>\n <td>[308, 225, 400, 593, 219, 217, 239, 102, 167]</td>\n <td>1.812943</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2070</th>\n <td>[225, 593, 219, 102, 167]</td>\n <td>1.812795</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2071</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 239, 102, ...</td>\n <td>1.812107</td>\n <td>2</td>\n <td>8</td>\n </tr>\n <tr>\n <th>2072</th>\n <td>[225, 593, 219, 239, 116, 136, 167]</td>\n <td>1.811779</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2073</th>\n <td>[225, 400, 102]</td>\n <td>1.811683</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2074</th>\n <td>[308, 225, 400, 572, 239, 116, 136]</td>\n <td>1.811655</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2075</th>\n <td>[308, 225, 593, 572, 219, 217, 116, 167]</td>\n <td>1.811640</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2076</th>\n <td>[308, 225, 400, 593, 219, 217, 102]</td>\n <td>1.811618</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2077</th>\n <td>[308, 400, 217, 239, 116, 167]</td>\n <td>1.811527</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2078</th>\n <td>[308, 225, 593, 572, 219, 136, 167]</td>\n <td>1.811505</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2079</th>\n <td>[308, 225, 400, 136]</td>\n <td>1.811458</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2080</th>\n <td>[593, 219, 217, 116, 136]</td>\n <td>1.811220</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2081</th>\n <td>[308, 225, 400, 593, 572, 217, 239, 136]</td>\n <td>1.811195</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2082</th>\n <td>[400, 217, 239, 102, 116]</td>\n <td>1.810680</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2083</th>\n <td>[572, 102, 116, 167]</td>\n <td>1.810616</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2084</th>\n <td>[308, 572, 239, 102, 116, 167]</td>\n <td>1.810459</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2085</th>\n <td>[308, 400, 572, 219, 116, 136]</td>\n <td>1.810404</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2086</th>\n <td>[308, 400, 219, 116, 136]</td>\n <td>1.810195</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2087</th>\n <td>[217, 116, 167]</td>\n <td>1.810169</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2088</th>\n <td>[400, 219, 239, 102, 136, 167]</td>\n <td>1.809902</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2089</th>\n <td>[400, 219, 217, 136, 167]</td>\n <td>1.809816</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2090</th>\n <td>[308, 400, 219, 239, 116, 136, 167]</td>\n <td>1.809588</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2091</th>\n <td>[308, 219, 217, 239, 102, 136, 167]</td>\n <td>1.809395</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2092</th>\n <td>[225, 400, 572, 219, 239, 102, 116, 167]</td>\n <td>1.809212</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2093</th>\n <td>[308, 225, 400, 217, 167]</td>\n <td>1.809041</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2094</th>\n <td>[225, 400, 219, 217, 116, 167]</td>\n <td>1.808269</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2095</th>\n <td>[225, 400, 217, 239, 136, 167]</td>\n <td>1.808178</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2096</th>\n <td>[225, 400, 572, 219, 136, 167]</td>\n <td>1.808176</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2097</th>\n <td>[308, 400, 593, 219, 217, 239, 116, 136]</td>\n <td>1.808111</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2098</th>\n <td>[225, 572, 239, 102, 136, 167]</td>\n <td>1.807950</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2099</th>\n <td>[308, 225, 400, 572, 136]</td>\n <td>1.807903</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2100</th>\n <td>[308, 593, 239, 116, 136]</td>\n <td>1.807760</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2101</th>\n <td>[225, 400, 572, 219, 217, 116, 167]</td>\n <td>1.807415</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2102</th>\n <td>[308, 593, 572, 239, 116, 136]</td>\n <td>1.807394</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2103</th>\n <td>[225, 400, 219, 136, 167]</td>\n <td>1.806960</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2104</th>\n <td>[400, 217, 239, 116, 136]</td>\n <td>1.806949</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2105</th>\n <td>[225, 593, 219, 217, 136, 167]</td>\n <td>1.806895</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2106</th>\n <td>[400, 572, 217, 239, 102, 116]</td>\n <td>1.806667</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2107</th>\n <td>[308, 400, 572, 219, 102, 167]</td>\n <td>1.806590</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2108</th>\n <td>[225, 400, 593, 219, 217, 239, 102, 116]</td>\n <td>1.806453</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2109</th>\n <td>[308, 239, 116, 136, 167]</td>\n <td>1.806445</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2110</th>\n <td>[225, 400, 572, 102]</td>\n <td>1.806380</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2111</th>\n <td>[308, 400, 593, 572, 219, 217, 239, 116, 136]</td>\n <td>1.806215</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2112</th>\n <td>[308, 225, 400, 572, 217, 167]</td>\n <td>1.805988</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2113</th>\n <td>[225, 572, 219, 217, 239, 102, 116, 136]</td>\n <td>1.805985</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2114</th>\n <td>[308, 225, 593, 217, 167]</td>\n <td>1.805606</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2115</th>\n <td>[308, 400, 572, 219, 239, 116, 136, 167]</td>\n <td>1.805588</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2116</th>\n <td>[400, 572, 217, 136]</td>\n <td>1.805472</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2117</th>\n <td>[308, 593, 572, 217, 116]</td>\n <td>1.805326</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2118</th>\n <td>[225, 400, 572, 217, 239, 136, 167]</td>\n <td>1.805303</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2119</th>\n <td>[400, 219, 116, 136]</td>\n <td>1.805130</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2120</th>\n <td>[225, 400, 593, 572, 219, 217, 239, 102, 116]</td>\n <td>1.805122</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2121</th>\n <td>[308, 225, 400, 116]</td>\n <td>1.804942</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2122</th>\n <td>[225, 116, 167]</td>\n <td>1.804745</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2123</th>\n <td>[400, 572, 219, 116, 136]</td>\n <td>1.804626</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2124</th>\n <td>[225, 593, 572, 219, 136, 167]</td>\n <td>1.804571</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2125</th>\n <td>[308, 400, 593, 572, 219, 239, 102, 136]</td>\n <td>1.804142</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2126</th>\n <td>[308, 225, 593, 572, 239, 116, 167]</td>\n <td>1.804057</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2127</th>\n <td>[308, 239, 102, 136, 167]</td>\n <td>1.803849</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2128</th>\n <td>[225, 593, 217, 167]</td>\n <td>1.803799</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2129</th>\n <td>[308, 225, 400, 593, 219, 217, 239, 136, 167]</td>\n <td>1.803714</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2130</th>\n <td>[308, 400, 593, 219, 239, 102, 136]</td>\n <td>1.803658</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2131</th>\n <td>[400, 572, 219, 102, 167]</td>\n <td>1.803645</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2132</th>\n <td>[308, 225, 593, 219, 217, 116, 167]</td>\n <td>1.803479</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2133</th>\n <td>[308, 225, 400, 593, 219, 239, 102, 116]</td>\n <td>1.803418</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2134</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 239, 136, ...</td>\n <td>1.803329</td>\n <td>2</td>\n <td>8</td>\n </tr>\n <tr>\n <th>2135</th>\n <td>[225, 572, 219, 217, 102, 136]</td>\n <td>1.803309</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2136</th>\n <td>[225, 400, 593, 572, 219, 217, 102]</td>\n <td>1.803133</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2137</th>\n <td>[308, 225, 572, 217, 239, 102, 136]</td>\n <td>1.802975</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2138</th>\n <td>[225, 400, 116]</td>\n <td>1.802895</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2139</th>\n <td>[308, 593, 217, 136]</td>\n <td>1.802794</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2140</th>\n <td>[225, 400, 219, 239, 116, 136, 167]</td>\n <td>1.802517</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2141</th>\n <td>[308, 225, 136, 167]</td>\n <td>1.802344</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2142</th>\n <td>[308, 400, 219, 102, 167]</td>\n <td>1.802336</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2143</th>\n <td>[308, 400, 593, 217, 239, 102]</td>\n <td>1.802047</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2144</th>\n <td>[225, 593, 572, 219, 217, 116, 167]</td>\n <td>1.801700</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2145</th>\n <td>[308, 225, 400, 593, 217, 239, 116]</td>\n <td>1.801637</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2146</th>\n <td>[308, 400, 572, 217, 239, 116, 167]</td>\n <td>1.801530</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2147</th>\n <td>[308, 593, 219, 102, 116]</td>\n <td>1.801267</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2148</th>\n <td>[400, 572, 217, 239, 116, 136]</td>\n <td>1.801148</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2149</th>\n <td>[308, 225, 219, 217, 102, 136]</td>\n <td>1.801041</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2150</th>\n <td>[593, 572, 219, 239, 102, 116, 167]</td>\n <td>1.800941</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2151</th>\n <td>[308, 400, 217, 116]</td>\n <td>1.800597</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2152</th>\n <td>[572, 219, 217, 239, 102, 116, 136]</td>\n <td>1.800469</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2153</th>\n <td>[225, 219, 217, 239, 102, 116, 136]</td>\n <td>1.800071</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2154</th>\n <td>[308, 593, 572, 239, 102, 116]</td>\n <td>1.800064</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2155</th>\n <td>[308, 225, 400, 593, 572, 219, 239, 102, 116]</td>\n <td>1.799960</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2156</th>\n <td>[308, 225, 400, 239, 102, 167]</td>\n <td>1.799941</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2157</th>\n <td>[308, 400, 593, 572, 219, 217, 239, 102, 167]</td>\n <td>1.799816</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2158</th>\n <td>[308, 225, 400, 219, 116, 167]</td>\n <td>1.799609</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2159</th>\n <td>[593, 572, 219, 102, 167]</td>\n <td>1.799603</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2160</th>\n <td>[308, 593, 572, 219, 116, 136]</td>\n <td>1.799506</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2161</th>\n <td>[308, 593, 219, 217, 136, 167]</td>\n <td>1.799273</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2162</th>\n <td>[308, 400, 593, 219, 217, 239, 102, 167]</td>\n <td>1.799192</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2163</th>\n <td>[225, 400, 217, 239, 116, 167]</td>\n <td>1.799070</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2164</th>\n <td>[308, 225, 593, 136]</td>\n <td>1.799031</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2165</th>\n <td>[308, 400, 572, 219, 217, 116, 167]</td>\n <td>1.799005</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2166</th>\n <td>[308, 225, 572, 219, 239, 102, 116, 136]</td>\n <td>1.799003</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2167</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 136]</td>\n <td>1.798916</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2168</th>\n <td>[308, 400, 593, 572, 217, 239, 102]</td>\n <td>1.798847</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2169</th>\n <td>[308, 225, 593, 572, 116]</td>\n <td>1.798623</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2170</th>\n <td>[225, 400, 572, 219, 239, 116, 136, 167]</td>\n <td>1.798471</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2171</th>\n <td>[308, 400, 593, 217, 239, 136]</td>\n <td>1.798410</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2172</th>\n <td>[572, 219, 217, 102, 136]</td>\n <td>1.798378</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2173</th>\n <td>[225, 400, 593, 219, 217, 102]</td>\n <td>1.798344</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2174</th>\n <td>[593, 219, 102, 116]</td>\n <td>1.798335</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2175</th>\n <td>[225, 593, 102]</td>\n <td>1.798258</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2176</th>\n <td>[308, 225, 593, 116]</td>\n <td>1.798247</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2177</th>\n <td>[308, 225, 572, 219, 217, 239, 102, 116, 167]</td>\n <td>1.798215</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2178</th>\n <td>[400, 219, 102, 167]</td>\n <td>1.798117</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2179</th>\n <td>[308, 225, 219, 239, 102, 116, 136]</td>\n <td>1.798051</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2180</th>\n <td>[308, 572, 219, 217, 102, 136]</td>\n <td>1.798028</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2181</th>\n <td>[593, 572, 219, 116, 136]</td>\n <td>1.797892</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2182</th>\n <td>[308, 225, 219, 217, 239, 102, 116, 167]</td>\n <td>1.797832</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2183</th>\n <td>[308, 225, 217, 239, 102, 136]</td>\n <td>1.797749</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2184</th>\n <td>[308, 400, 593, 572, 219, 217, 102]</td>\n <td>1.797658</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2185</th>\n <td>[308, 225, 593, 219, 136, 167]</td>\n <td>1.797635</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2186</th>\n <td>[308, 400, 219, 217, 116, 167]</td>\n <td>1.797428</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2187</th>\n <td>[593, 572, 217, 167]</td>\n <td>1.797302</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2188</th>\n <td>[308, 225, 400, 239, 136, 167]</td>\n <td>1.796844</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2189</th>\n <td>[308, 400, 572, 239, 102, 136]</td>\n <td>1.796699</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2190</th>\n <td>[225, 572, 239, 116, 136, 167]</td>\n <td>1.796411</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2191</th>\n <td>[308, 400, 572, 217, 116]</td>\n <td>1.796379</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2192</th>\n <td>[308, 225, 400, 572, 219, 116, 167]</td>\n <td>1.796233</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2193</th>\n <td>[225, 593, 572, 239, 116, 136]</td>\n <td>1.796186</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2194</th>\n <td>[225, 400, 593, 572, 219, 239, 102, 136]</td>\n <td>1.796069</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2195</th>\n <td>[308, 593, 572, 219, 102, 167]</td>\n <td>1.795980</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2196</th>\n <td>[308, 225, 400, 572, 239, 102, 167]</td>\n <td>1.795761</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2197</th>\n <td>[400, 217, 116]</td>\n <td>1.795695</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2198</th>\n <td>[308, 225, 400, 593, 219, 239, 116, 136]</td>\n <td>1.795631</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2199</th>\n <td>[225, 400, 593, 219, 217, 239, 116, 136]</td>\n <td>1.795251</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2200</th>\n <td>[225, 593, 239, 116, 136]</td>\n <td>1.795239</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2201</th>\n <td>[308, 225, 400, 593, 219, 217, 136]</td>\n <td>1.795111</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2202</th>\n <td>[225, 572, 136, 167]</td>\n <td>1.794788</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2203</th>\n <td>[225, 572, 219, 217, 239, 102, 136, 167]</td>\n <td>1.794714</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2204</th>\n <td>[225, 400, 593, 219, 239, 102, 136]</td>\n <td>1.794605</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2205</th>\n <td>[225, 400, 593, 572, 219, 217, 239, 116, 136]</td>\n <td>1.794591</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2206</th>\n <td>[225, 400, 217, 167]</td>\n <td>1.794567</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2207</th>\n <td>[308, 400, 593, 572, 217, 239, 136]</td>\n <td>1.794407</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2208</th>\n <td>[572, 116, 136, 167]</td>\n <td>1.794143</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2209</th>\n <td>[593, 572, 219, 239, 116, 136, 167]</td>\n <td>1.793916</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2210</th>\n <td>[400, 217, 136]</td>\n <td>1.793885</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2211</th>\n <td>[308, 593, 239, 102, 116]</td>\n <td>1.793856</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2212</th>\n <td>[400, 593, 219, 217, 239, 102, 116]</td>\n <td>1.793535</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2213</th>\n <td>[217, 102, 116]</td>\n <td>1.793522</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2214</th>\n <td>[400, 593, 572, 219, 217, 239, 102, 116]</td>\n <td>1.793488</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2215</th>\n <td>[308, 225, 400, 593, 572, 217, 239, 116]</td>\n <td>1.793285</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2216</th>\n <td>[225, 572, 239, 102, 116, 167]</td>\n <td>1.792899</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2217</th>\n <td>[308, 225, 400, 593, 572, 219, 102]</td>\n <td>1.792885</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2218</th>\n <td>[308, 225, 400, 593, 572, 219, 239, 116, 136]</td>\n <td>1.792381</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2219</th>\n <td>[593, 217, 136]</td>\n <td>1.792332</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2220</th>\n <td>[308, 400, 239, 102, 136]</td>\n <td>1.792247</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2221</th>\n <td>[308, 239, 102, 116, 167]</td>\n <td>1.792216</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2222</th>\n <td>[308, 400, 593, 219, 217, 102]</td>\n <td>1.792125</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2223</th>\n <td>[219, 217, 239, 102, 116, 136]</td>\n <td>1.791915</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2224</th>\n <td>[308, 225, 400, 572, 239, 136, 167]</td>\n <td>1.791554</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2225</th>\n <td>[308, 400, 593, 572, 219, 217, 239, 136, 167]</td>\n <td>1.791415</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2226</th>\n <td>[225, 593, 572, 239, 102, 116]</td>\n <td>1.791199</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2227</th>\n <td>[308, 225, 400, 593, 219, 102]</td>\n <td>1.791177</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2228</th>\n <td>[308, 225, 400, 572, 116]</td>\n <td>1.791097</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2229</th>\n <td>[593, 219, 239, 102, 116, 167]</td>\n <td>1.791067</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2230</th>\n <td>[308, 593, 217, 116]</td>\n <td>1.790944</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2231</th>\n <td>[225, 400, 572, 217, 167]</td>\n <td>1.790775</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2232</th>\n <td>[308, 593, 572, 219, 217, 116, 167]</td>\n <td>1.790526</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2233</th>\n <td>[308, 400, 593, 219, 217, 239, 136, 167]</td>\n <td>1.790440</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2234</th>\n <td>[225, 400, 219, 116, 167]</td>\n <td>1.790270</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2235</th>\n <td>[400, 572, 219, 217, 116, 167]</td>\n <td>1.790081</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2236</th>\n <td>[225, 400, 593, 572, 219, 217, 239, 102, 167]</td>\n <td>1.790063</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2237</th>\n <td>[572, 219, 217, 239, 102, 136, 167]</td>\n <td>1.789063</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2238</th>\n <td>[225, 400, 572, 217, 239, 116, 167]</td>\n <td>1.788957</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2239</th>\n <td>[308, 400, 572, 219, 136, 167]</td>\n <td>1.788507</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2240</th>\n <td>[400, 593, 572, 219, 217, 102]</td>\n <td>1.788362</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2241</th>\n <td>[225, 400, 593, 219, 217, 239, 102, 167]</td>\n <td>1.788256</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2242</th>\n <td>[225, 593, 239, 102, 136]</td>\n <td>1.787978</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2243</th>\n <td>[225, 593, 219, 217, 116, 167]</td>\n <td>1.787848</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2244</th>\n <td>[400, 219, 217, 116, 167]</td>\n <td>1.787766</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2245</th>\n <td>[400, 572, 217, 239, 102, 167]</td>\n <td>1.787377</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2246</th>\n <td>[308, 225, 400, 593, 219, 217, 239, 116, 167]</td>\n <td>1.787311</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2247</th>\n <td>[225, 400, 593, 217, 239, 102]</td>\n <td>1.787087</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2248</th>\n <td>[308, 225, 593, 572, 219, 116, 167]</td>\n <td>1.786939</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2249</th>\n <td>[308, 225, 572, 219, 217, 102, 116]</td>\n <td>1.786671</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2250</th>\n <td>[308, 225, 572, 219, 102, 136]</td>\n <td>1.786117</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2251</th>\n <td>[308, 225, 400, 239, 116, 167]</td>\n <td>1.786064</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2252</th>\n <td>[308, 225, 572, 219, 217, 239, 116, 136, 167]</td>\n <td>1.785989</td>\n <td>3</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2253</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 239, 116, ...</td>\n <td>1.785563</td>\n <td>2</td>\n <td>8</td>\n </tr>\n <tr>\n <th>2254</th>\n <td>[225, 400, 593, 572, 217, 239, 102]</td>\n <td>1.785381</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2255</th>\n <td>[593, 219, 239, 116, 136, 167]</td>\n <td>1.785194</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2256</th>\n <td>[593, 219, 217, 136, 167]</td>\n <td>1.785172</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2257</th>\n <td>[400, 572, 217, 116]</td>\n <td>1.785126</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2258</th>\n <td>[225, 219, 217, 239, 102, 136, 167]</td>\n <td>1.785034</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2259</th>\n <td>[308, 572, 102, 136]</td>\n <td>1.784944</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2260</th>\n <td>[225, 400, 136]</td>\n <td>1.784880</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2261</th>\n <td>[225, 400, 572, 219, 116, 167]</td>\n <td>1.784865</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2262</th>\n <td>[308, 225, 219, 217, 239, 116, 136, 167]</td>\n <td>1.784667</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2263</th>\n <td>[308, 572, 219, 217, 239, 102, 116, 167]</td>\n <td>1.784454</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2264</th>\n <td>[308, 225, 572, 219, 239, 102, 136, 167]</td>\n <td>1.784388</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2265</th>\n <td>[593, 572, 219, 217, 116, 167]</td>\n <td>1.784063</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2266</th>\n <td>[308, 225, 400, 593, 219, 239, 102, 167]</td>\n <td>1.784046</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2267</th>\n <td>[400, 217, 239, 102, 167]</td>\n <td>1.784024</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2268</th>\n <td>[400, 219, 239, 102, 116, 167]</td>\n <td>1.783897</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2269</th>\n <td>[308, 225, 400, 593, 572, 219, 239, 102, 167]</td>\n <td>1.783724</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2270</th>\n <td>[400, 593, 572, 219, 217, 239, 116, 136]</td>\n <td>1.783420</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2271</th>\n <td>[225, 400, 593, 572, 219, 217, 136]</td>\n <td>1.783408</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2272</th>\n <td>[400, 572, 219, 239, 102, 116, 167]</td>\n <td>1.783403</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2273</th>\n <td>[308, 593, 572, 239, 136, 167]</td>\n <td>1.783368</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2274</th>\n <td>[308, 225, 593, 572, 219, 217, 239, 102, 136]</td>\n <td>1.783167</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2275</th>\n <td>[225, 400, 572, 136]</td>\n <td>1.783156</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2276</th>\n <td>[400, 593, 219, 217, 239, 116, 136]</td>\n <td>1.782954</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2277</th>\n <td>[225, 593, 239, 102, 116]</td>\n <td>1.782759</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2278</th>\n <td>[593, 116, 136]</td>\n <td>1.782259</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2279</th>\n <td>[239, 102, 116, 136, 167]</td>\n <td>1.782246</td>\n <td>4</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2280</th>\n <td>[308, 400, 219, 136, 167]</td>\n <td>1.782110</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2281</th>\n <td>[308, 400, 593, 572, 219, 217, 136]</td>\n <td>1.781981</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2282</th>\n <td>[308, 219, 217, 239, 102, 116, 167]</td>\n <td>1.781960</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2283</th>\n <td>[400, 572, 217, 239, 136, 167]</td>\n <td>1.781640</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2284</th>\n <td>[308, 400, 593, 217, 239, 116]</td>\n <td>1.780623</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2285</th>\n <td>[308, 225, 217, 239, 102, 116]</td>\n <td>1.780561</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2286</th>\n <td>[225, 400, 593, 217, 239, 136]</td>\n <td>1.780454</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2287</th>\n <td>[225, 400, 593, 572, 219, 102]</td>\n <td>1.780346</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2288</th>\n <td>[225, 593, 219, 136, 167]</td>\n <td>1.780262</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2289</th>\n <td>[308, 400, 593, 219, 239, 102, 116]</td>\n <td>1.780014</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2290</th>\n <td>[217, 102, 167]</td>\n <td>1.779951</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2291</th>\n <td>[400, 217, 239, 136, 167]</td>\n <td>1.779904</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2292</th>\n <td>[308, 593, 219, 116, 136]</td>\n <td>1.779878</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2293</th>\n <td>[400, 593, 219, 217, 102]</td>\n <td>1.779633</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2294</th>\n <td>[225, 400, 593, 572, 219, 217, 239, 136, 167]</td>\n <td>1.779481</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2295</th>\n <td>[572, 102, 136, 167]</td>\n <td>1.779446</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2296</th>\n <td>[308, 225, 572, 217, 239, 102, 116]</td>\n <td>1.779442</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2297</th>\n <td>[308, 225, 400, 593, 217, 239, 167]</td>\n <td>1.779427</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2298</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 116]</td>\n <td>1.779386</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2299</th>\n <td>[308, 225, 219, 239, 102, 136, 167]</td>\n <td>1.779349</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2300</th>\n <td>[308, 593, 572, 217, 167]</td>\n <td>1.778949</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2301</th>\n <td>[308, 400, 593, 572, 219, 239, 102, 116]</td>\n <td>1.778936</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2302</th>\n <td>[225, 219, 217, 102, 136]</td>\n <td>1.778620</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2303</th>\n <td>[308, 225, 593, 219, 116, 167]</td>\n <td>1.778354</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2304</th>\n <td>[225, 400, 593, 572, 217, 239, 136]</td>\n <td>1.778330</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2305</th>\n <td>[308, 572, 217, 239, 102, 136]</td>\n <td>1.778220</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2306</th>\n <td>[308, 225, 400, 593, 572, 219, 136]</td>\n <td>1.778087</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2307</th>\n <td>[308, 225, 593, 219, 217, 239, 102, 136]</td>\n <td>1.777739</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2308</th>\n <td>[308, 225, 400, 593, 219, 217, 116]</td>\n <td>1.777635</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2309</th>\n <td>[225, 400, 572, 239, 102, 136]</td>\n <td>1.777595</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2310</th>\n <td>[400, 572, 219, 136, 167]</td>\n <td>1.777440</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2311</th>\n <td>[225, 400, 593, 219, 102]</td>\n <td>1.777158</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2312</th>\n <td>[308, 225, 219, 217, 102, 116]</td>\n <td>1.777144</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2313</th>\n <td>[225, 400, 593, 219, 217, 239, 136, 167]</td>\n <td>1.776998</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2314</th>\n <td>[225, 593, 572, 219, 116, 167]</td>\n <td>1.776940</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2315</th>\n <td>[308, 593, 572, 219, 136, 167]</td>\n <td>1.776756</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2316</th>\n <td>[400, 593, 572, 219, 217, 239, 102, 167]</td>\n <td>1.776746</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2317</th>\n <td>[225, 593, 136]</td>\n <td>1.776543</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2318</th>\n <td>[308, 225, 400, 593, 239, 102]</td>\n <td>1.776478</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2319</th>\n <td>[308, 593, 572, 239, 102, 167]</td>\n <td>1.776472</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2320</th>\n <td>[225, 400, 593, 219, 217, 136]</td>\n <td>1.776246</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2321</th>\n <td>[308, 225, 400, 593, 219, 239, 136, 167]</td>\n <td>1.776175</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2322</th>\n <td>[308, 219, 217, 102, 136]</td>\n <td>1.776093</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2323</th>\n <td>[308, 225, 400, 593, 572, 219, 239, 136, 167]</td>\n <td>1.776079</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2324</th>\n <td>[308, 400, 239, 116, 136]</td>\n <td>1.775959</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2325</th>\n <td>[308, 593, 219, 217, 116, 167]</td>\n <td>1.775862</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2326</th>\n <td>[219, 217, 239, 102, 136, 167]</td>\n <td>1.775722</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2327</th>\n <td>[308, 225, 400, 572, 239, 116, 167]</td>\n <td>1.775267</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2328</th>\n <td>[400, 593, 572, 219, 239, 102, 136]</td>\n <td>1.775139</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2329</th>\n <td>[308, 225, 400, 593, 572, 217, 239, 167]</td>\n <td>1.775127</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2330</th>\n <td>[308, 225, 400, 593, 219, 136]</td>\n <td>1.774941</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2331</th>\n <td>[225, 239, 116, 136, 167]</td>\n <td>1.774932</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2332</th>\n <td>[225, 572, 219, 102, 136]</td>\n <td>1.774918</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2333</th>\n <td>[308, 400, 593, 219, 217, 136]</td>\n <td>1.774896</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2334</th>\n <td>[400, 219, 239, 116, 136, 167]</td>\n <td>1.774365</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2335</th>\n <td>[308, 225, 400, 593, 239, 136]</td>\n <td>1.774295</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2336</th>\n <td>[308, 572, 219, 239, 102, 116, 136]</td>\n <td>1.774105</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2337</th>\n <td>[308, 400, 239, 102, 116]</td>\n <td>1.774062</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2338</th>\n <td>[593, 102, 116]</td>\n <td>1.774045</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2339</th>\n <td>[400, 572, 219, 239, 116, 136, 167]</td>\n <td>1.773923</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2340</th>\n <td>[308, 225, 400, 572, 219, 217, 239, 102, 136]</td>\n <td>1.773639</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2341</th>\n <td>[308, 593, 239, 136, 167]</td>\n <td>1.773587</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2342</th>\n <td>[225, 400, 572, 116]</td>\n <td>1.773429</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2343</th>\n <td>[308, 400, 593, 219, 239, 116, 136]</td>\n <td>1.773354</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2344</th>\n <td>[308, 225, 400, 593, 217]</td>\n <td>1.773350</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2345</th>\n <td>[308, 400, 593, 572, 217, 239, 116]</td>\n <td>1.773254</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2346</th>\n <td>[225, 400, 593, 219, 239, 102, 116]</td>\n <td>1.773194</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2347</th>\n <td>[400, 593, 219, 217, 239, 102, 167]</td>\n <td>1.772876</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2348</th>\n <td>[308, 225, 400, 593, 572, 239, 102]</td>\n <td>1.772872</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2349</th>\n <td>[308, 572, 219, 217, 239, 116, 136, 167]</td>\n <td>1.772588</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2350</th>\n <td>[308, 225, 217, 239, 116, 136]</td>\n <td>1.772567</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2351</th>\n <td>[308, 225, 400, 593, 572, 217]</td>\n <td>1.772543</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2352</th>\n <td>[308, 225, 400, 219, 217, 239, 102, 136]</td>\n <td>1.772526</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2353</th>\n <td>[308, 400, 593, 572, 219, 239, 116, 136]</td>\n <td>1.772230</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2354</th>\n <td>[225, 400, 593, 572, 219, 239, 102, 116]</td>\n <td>1.772202</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2355</th>\n <td>[308, 400, 572, 239, 102, 116]</td>\n <td>1.772171</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2356</th>\n <td>[225, 593, 572, 239, 136, 167]</td>\n <td>1.772009</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2357</th>\n <td>[308, 400, 572, 239, 116, 136]</td>\n <td>1.771473</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2358</th>\n <td>[308, 593, 572, 219, 217, 239, 102, 136]</td>\n <td>1.771428</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2359</th>\n <td>[308, 400, 593, 219, 217, 239, 116, 167]</td>\n <td>1.771425</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2360</th>\n <td>[308, 400, 572, 217, 167]</td>\n <td>1.771292</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2361</th>\n <td>[308, 225, 572, 219, 217, 102, 167]</td>\n <td>1.771099</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2362</th>\n <td>[308, 593, 219, 102, 167]</td>\n <td>1.771098</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2363</th>\n <td>[308, 225, 572, 217, 239, 116, 136]</td>\n <td>1.771067</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2364</th>\n <td>[308, 400, 593, 572, 219, 217, 239, 116, 167]</td>\n <td>1.770922</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2365</th>\n <td>[308, 225, 219, 102, 136]</td>\n <td>1.770273</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2366</th>\n <td>[225, 572, 219, 217, 102, 116]</td>\n <td>1.770199</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2367</th>\n <td>[593, 572, 219, 136, 167]</td>\n <td>1.769904</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2368</th>\n <td>[400, 217, 239, 116, 167]</td>\n <td>1.769733</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2369</th>\n <td>[400, 593, 219, 239, 102, 136]</td>\n <td>1.769625</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2370</th>\n <td>[308, 225, 400, 593, 572, 239, 136]</td>\n <td>1.769594</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2371</th>\n <td>[308, 219, 217, 239, 116, 136, 167]</td>\n <td>1.769302</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2372</th>\n <td>[225, 400, 239, 102, 136]</td>\n <td>1.768225</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2373</th>\n <td>[225, 239, 102, 116, 136]</td>\n <td>1.767987</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2374</th>\n <td>[225, 400, 593, 217, 239, 116]</td>\n <td>1.767784</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2375</th>\n <td>[308, 219, 239, 102, 116, 136]</td>\n <td>1.767771</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2376</th>\n <td>[225, 593, 572, 239, 102, 167]</td>\n <td>1.767439</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2377</th>\n <td>[225, 572, 219, 217, 239, 102, 116, 167]</td>\n <td>1.767330</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2378</th>\n <td>[400, 219, 136, 167]</td>\n <td>1.767323</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2379</th>\n <td>[400, 593, 572, 219, 217, 136]</td>\n <td>1.767270</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2380</th>\n <td>[308, 400, 217, 167]</td>\n <td>1.766937</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2381</th>\n <td>[400, 593, 572, 219, 217, 239, 136, 167]</td>\n <td>1.766600</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2382</th>\n <td>[225, 593, 572, 167]</td>\n <td>1.766183</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2383</th>\n <td>[308, 225, 593, 572, 167]</td>\n <td>1.765894</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2384</th>\n <td>[225, 593, 239, 116, 167]</td>\n <td>1.765349</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2385</th>\n <td>[308, 225, 400, 167]</td>\n <td>1.765152</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2386</th>\n <td>[308, 217, 239, 102, 136]</td>\n <td>1.764776</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2387</th>\n <td>[308, 400, 593, 572, 219, 102]</td>\n <td>1.764253</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2388</th>\n <td>[225, 239, 102, 116, 167]</td>\n <td>1.763977</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2389</th>\n <td>[225, 400, 593, 219, 239, 116, 136]</td>\n <td>1.763878</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2390</th>\n <td>[308, 225, 572, 217, 239, 102, 167]</td>\n <td>1.763864</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2391</th>\n <td>[225, 593, 219, 116, 167]</td>\n <td>1.763755</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2392</th>\n <td>[308, 225, 572, 219, 217, 116, 136]</td>\n <td>1.763579</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2393</th>\n <td>[308, 400, 572, 219, 116, 167]</td>\n <td>1.763451</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2394</th>\n <td>[308, 593, 219, 217, 239, 102, 136]</td>\n <td>1.763406</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2395</th>\n <td>[593, 219, 116, 136]</td>\n <td>1.763330</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2396</th>\n <td>[225, 400, 593, 572, 219, 239, 116, 136]</td>\n <td>1.763188</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2397</th>\n <td>[308, 572, 219, 217, 102, 116]</td>\n <td>1.763139</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2398</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 167]</td>\n <td>1.762410</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2399</th>\n <td>[400, 593, 572, 217, 239, 102]</td>\n <td>1.762372</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2400</th>\n <td>[400, 593, 219, 217, 239, 136, 167]</td>\n <td>1.762198</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2401</th>\n <td>[225, 219, 217, 239, 102, 116, 167]</td>\n <td>1.761874</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2402</th>\n <td>[225, 400, 593, 572, 219, 217, 116]</td>\n <td>1.761840</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2403</th>\n <td>[400, 572, 217, 239, 116, 167]</td>\n <td>1.761760</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2404</th>\n <td>[308, 225, 400, 572, 167]</td>\n <td>1.761668</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2405</th>\n <td>[308, 593, 239, 116, 167]</td>\n <td>1.761546</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2406</th>\n <td>[308, 400, 219, 116, 167]</td>\n <td>1.761335</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2407</th>\n <td>[308, 572, 102, 116]</td>\n <td>1.761018</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2408</th>\n <td>[308, 400, 593, 572, 219, 239, 102, 167]</td>\n <td>1.760895</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2409</th>\n <td>[308, 225, 400, 593, 239, 116]</td>\n <td>1.760831</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2410</th>\n <td>[593, 219, 217, 116, 167]</td>\n <td>1.760755</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2411</th>\n <td>[308, 593, 239, 102, 167]</td>\n <td>1.760634</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2412</th>\n <td>[219, 217, 102, 136]</td>\n <td>1.760613</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2413</th>\n <td>[225, 400, 593, 572, 219, 136]</td>\n <td>1.760554</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2414</th>\n <td>[225, 400, 593, 572, 217, 239, 116]</td>\n <td>1.760460</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2415</th>\n <td>[400, 593, 217, 239, 102]</td>\n <td>1.760442</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2416</th>\n <td>[225, 400, 593, 572, 219, 217, 239, 116, 167]</td>\n <td>1.760438</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2417</th>\n <td>[225, 400, 593, 219, 217, 239, 116, 167]</td>\n <td>1.760112</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2418</th>\n <td>[308, 225, 593, 572, 219, 217, 239, 102, 116]</td>\n <td>1.759895</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2419</th>\n <td>[308, 400, 572, 102]</td>\n <td>1.759841</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2420</th>\n <td>[308, 225, 217, 239, 102, 167]</td>\n <td>1.759799</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2421</th>\n <td>[593, 217, 167]</td>\n <td>1.759619</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2422</th>\n <td>[308, 225, 400, 593, 219, 239, 116, 167]</td>\n <td>1.759542</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2423</th>\n <td>[225, 400, 239, 102, 116]</td>\n <td>1.759535</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2424</th>\n <td>[308, 593, 572, 239, 116, 167]</td>\n <td>1.759489</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2425</th>\n <td>[308, 400, 593, 572, 219, 217, 116]</td>\n <td>1.759164</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2426</th>\n <td>[225, 593, 239, 136, 167]</td>\n <td>1.758781</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2427</th>\n <td>[308, 225, 572, 219, 239, 102, 116, 167]</td>\n <td>1.758699</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2428</th>\n <td>[308, 400, 572, 219, 217, 239, 102, 136]</td>\n <td>1.758698</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2429</th>\n <td>[225, 400, 572, 239, 102, 116]</td>\n <td>1.758566</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2430</th>\n <td>[225, 400, 239, 116, 136]</td>\n <td>1.758286</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2431</th>\n <td>[400, 593, 572, 217, 239, 136]</td>\n <td>1.758183</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2432</th>\n <td>[308, 400, 593, 219, 239, 102, 167]</td>\n <td>1.758142</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2433</th>\n <td>[225, 400, 593, 219, 217, 116]</td>\n <td>1.758078</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2434</th>\n <td>[308, 572, 219, 239, 102, 136, 167]</td>\n <td>1.758068</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2435</th>\n <td>[400, 593, 217, 239, 136]</td>\n <td>1.757909</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2436</th>\n <td>[308, 225, 400, 593, 572, 219, 239, 116, 167]</td>\n <td>1.757709</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2437</th>\n <td>[225, 593, 572, 239, 116, 167]</td>\n <td>1.757466</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2438</th>\n <td>[308, 225, 400, 593, 572, 219, 116]</td>\n <td>1.757415</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2439</th>\n <td>[308, 225, 400, 593, 219, 217, 167]</td>\n <td>1.757400</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2440</th>\n <td>[308, 225, 219, 217, 102, 167]</td>\n <td>1.757219</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2441</th>\n <td>[308, 400, 593, 219, 102]</td>\n <td>1.757147</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2442</th>\n <td>[308, 225, 400, 593, 219, 116]</td>\n <td>1.756939</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2443</th>\n <td>[308, 225, 219, 239, 102, 116, 167]</td>\n <td>1.756845</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2444</th>\n <td>[593, 219, 102, 167]</td>\n <td>1.756536</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2445</th>\n <td>[308, 225, 593, 219, 217, 239, 102, 116]</td>\n <td>1.756267</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2446</th>\n <td>[308, 400, 219, 217, 239, 102, 136]</td>\n <td>1.755830</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2447</th>\n <td>[400, 593, 219, 217, 136]</td>\n <td>1.755759</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2448</th>\n <td>[308, 225, 572, 219, 102, 116]</td>\n <td>1.755694</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2449</th>\n <td>[225, 572, 219, 239, 102, 116, 136]</td>\n <td>1.755687</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2450</th>\n <td>[308, 225, 572, 217, 239, 136, 167]</td>\n <td>1.755344</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2451</th>\n <td>[308, 400, 593, 217, 239, 167]</td>\n <td>1.754969</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2452</th>\n <td>[225, 400, 572, 239, 116, 136]</td>\n <td>1.754942</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2453</th>\n <td>[225, 400, 593, 219, 136]</td>\n <td>1.754765</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2454</th>\n <td>[308, 400, 593, 219, 217, 116]</td>\n <td>1.754434</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2455</th>\n <td>[225, 400, 593, 217]</td>\n <td>1.754426</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2456</th>\n <td>[308, 225, 400, 219, 217, 239, 102, 116]</td>\n <td>1.754160</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2457</th>\n <td>[308, 400, 593, 572, 219, 239, 136, 167]</td>\n <td>1.754089</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2458</th>\n <td>[308, 225, 400, 572, 219, 217, 239, 102, 116]</td>\n <td>1.753910</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2459</th>\n <td>[225, 593, 167]</td>\n <td>1.753595</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2460</th>\n <td>[572, 219, 217, 239, 102, 116, 167]</td>\n <td>1.753577</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2461</th>\n <td>[225, 219, 217, 102, 116]</td>\n <td>1.753547</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2462</th>\n <td>[225, 400, 593, 572, 219, 239, 102, 167]</td>\n <td>1.753440</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2463</th>\n <td>[225, 400, 593, 572, 217]</td>\n <td>1.753395</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2464</th>\n <td>[572, 102, 116, 136]</td>\n <td>1.753367</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2465</th>\n <td>[308, 593, 217, 167]</td>\n <td>1.753324</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2466</th>\n <td>[225, 572, 219, 217, 102, 167]</td>\n <td>1.753264</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2467</th>\n <td>[400, 572, 217, 167]</td>\n <td>1.752880</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2468</th>\n <td>[308, 400, 593, 572, 217, 239, 167]</td>\n <td>1.752749</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2469</th>\n <td>[572, 219, 217, 102, 116]</td>\n <td>1.752430</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2470</th>\n <td>[308, 225, 400, 593, 572, 239, 116]</td>\n <td>1.752107</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2471</th>\n <td>[308, 225, 217, 239, 136, 167]</td>\n <td>1.751587</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2472</th>\n <td>[225, 572, 219, 217, 239, 116, 136, 167]</td>\n <td>1.751535</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2473</th>\n <td>[308, 400, 593, 219, 239, 136, 167]</td>\n <td>1.751344</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2474</th>\n <td>[308, 225, 593, 167]</td>\n <td>1.751304</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2475</th>\n <td>[225, 102, 116]</td>\n <td>1.751196</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2476</th>\n <td>[308, 225, 219, 217, 116, 136]</td>\n <td>1.750941</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2477</th>\n <td>[225, 593, 572, 219, 217, 239, 102, 136]</td>\n <td>1.750702</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2478</th>\n <td>[225, 239, 102, 136, 167]</td>\n <td>1.750532</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2479</th>\n <td>[225, 400, 593, 219, 239, 102, 167]</td>\n <td>1.750091</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2480</th>\n <td>[308, 593, 219, 136, 167]</td>\n <td>1.749637</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2481</th>\n <td>[308, 400, 572, 239, 102, 167]</td>\n <td>1.749606</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2482</th>\n <td>[308, 225, 593, 572, 219, 217, 239, 116, 136]</td>\n <td>1.749459</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2483</th>\n <td>[400, 593, 572, 219, 102]</td>\n <td>1.749437</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2484</th>\n <td>[308, 400, 593, 572, 219, 136]</td>\n <td>1.749271</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2485</th>\n <td>[308, 593, 572, 102]</td>\n <td>1.748872</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2486</th>\n <td>[308, 572, 217, 239, 102, 116]</td>\n <td>1.748663</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2487</th>\n <td>[308, 400, 572, 239, 136, 167]</td>\n <td>1.748612</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2488</th>\n <td>[400, 572, 219, 116, 167]</td>\n <td>1.748502</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2489</th>\n <td>[308, 225, 572, 219, 239, 116, 136, 167]</td>\n <td>1.748093</td>\n <td>3</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2490</th>\n <td>[308, 225, 572, 219, 217, 136, 167]</td>\n <td>1.747954</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2491</th>\n <td>[225, 593, 239, 102, 167]</td>\n <td>1.747338</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2492</th>\n <td>[400, 219, 116, 167]</td>\n <td>1.747160</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2493</th>\n <td>[308, 225, 593, 572, 219, 239, 102, 136]</td>\n <td>1.747138</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2494</th>\n <td>[308, 593, 572, 219, 116, 167]</td>\n <td>1.747086</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2495</th>\n <td>[400, 217, 167]</td>\n <td>1.746866</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2496</th>\n <td>[225, 219, 102, 136]</td>\n <td>1.746834</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2497</th>\n <td>[308, 572, 219, 102, 136]</td>\n <td>1.746722</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2498</th>\n <td>[308, 219, 239, 102, 136, 167]</td>\n <td>1.746532</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2499</th>\n <td>[400, 593, 572, 219, 239, 102, 116]</td>\n <td>1.746480</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2500</th>\n <td>[308, 219, 217, 102, 116]</td>\n <td>1.746138</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2501</th>\n <td>[308, 572, 219, 217, 102, 167]</td>\n <td>1.745873</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2502</th>\n <td>[308, 225, 219, 239, 116, 136, 167]</td>\n <td>1.745716</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2503</th>\n <td>[308, 400, 572, 136]</td>\n <td>1.745687</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2504</th>\n <td>[308, 225, 593, 572, 219, 217, 239, 102, 167]</td>\n <td>1.745682</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2505</th>\n <td>[308, 400, 239, 136, 167]</td>\n <td>1.745681</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2506</th>\n <td>[217, 102, 136]</td>\n <td>1.745624</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2507</th>\n <td>[308, 225, 219, 102, 116]</td>\n <td>1.745622</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2508</th>\n <td>[308, 400, 102]</td>\n <td>1.745526</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2509</th>\n <td>[308, 572, 116, 136]</td>\n <td>1.745474</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2510</th>\n <td>[593, 572, 239, 102, 136]</td>\n <td>1.745267</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2511</th>\n <td>[219, 217, 239, 102, 116, 167]</td>\n <td>1.745214</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2512</th>\n <td>[225, 219, 239, 102, 116, 136]</td>\n <td>1.745191</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2513</th>\n <td>[308, 225, 593, 219, 217, 239, 116, 136]</td>\n <td>1.745180</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2514</th>\n <td>[225, 219, 217, 239, 116, 136, 167]</td>\n <td>1.744460</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2515</th>\n <td>[225, 400, 593, 572, 219, 239, 136, 167]</td>\n <td>1.744335</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2516</th>\n <td>[308, 400, 239, 102, 167]</td>\n <td>1.744313</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2517</th>\n <td>[400, 593, 572, 219, 217, 239, 116, 167]</td>\n <td>1.743992</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2518</th>\n <td>[308, 225, 572, 217, 102]</td>\n <td>1.743777</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2519</th>\n <td>[400, 593, 219, 239, 102, 116]</td>\n <td>1.743757</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2520</th>\n <td>[308, 225, 400, 572, 219, 217, 239, 116, 136]</td>\n <td>1.743637</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2521</th>\n <td>[308, 572, 217, 239, 116, 136]</td>\n <td>1.743624</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2522</th>\n <td>[308, 217, 239, 102, 116]</td>\n <td>1.743555</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2523</th>\n <td>[308, 593, 572, 219, 217, 239, 102, 116]</td>\n <td>1.743448</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2524</th>\n <td>[308, 225, 400, 219, 217, 239, 116, 136]</td>\n <td>1.743202</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2525</th>\n <td>[400, 593, 217, 239, 116]</td>\n <td>1.742603</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2526</th>\n <td>[400, 593, 219, 217, 239, 116, 167]</td>\n <td>1.742018</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2527</th>\n <td>[225, 400, 593, 572, 219, 217, 167]</td>\n <td>1.741871</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2528</th>\n <td>[225, 400, 167]</td>\n <td>1.741131</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2529</th>\n <td>[308, 400, 593, 572, 217]</td>\n <td>1.741020</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2530</th>\n <td>[400, 593, 572, 219, 217, 116]</td>\n <td>1.740973</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2531</th>\n <td>[308, 225, 217, 239, 116, 167]</td>\n <td>1.740806</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2532</th>\n <td>[572, 219, 102, 136]</td>\n <td>1.740737</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2533</th>\n <td>[308, 400, 593, 219, 136]</td>\n <td>1.740689</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2534</th>\n <td>[225, 400, 593, 219, 239, 136, 167]</td>\n <td>1.740654</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2535</th>\n <td>[308, 217, 239, 116, 136]</td>\n <td>1.740531</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2536</th>\n <td>[225, 400, 593, 217, 239, 167]</td>\n <td>1.740498</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2537</th>\n <td>[308, 400, 593, 572, 219, 217, 167]</td>\n <td>1.740179</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2538</th>\n <td>[225, 572, 219, 239, 102, 136, 167]</td>\n <td>1.740124</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2539</th>\n <td>[308, 225, 400, 572, 219, 217, 239, 102, 167]</td>\n <td>1.740061</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2540</th>\n <td>[225, 400, 572, 219, 217, 239, 102, 136]</td>\n <td>1.739764</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2541</th>\n <td>[308, 225, 593, 219, 239, 102, 136]</td>\n <td>1.739673</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2542</th>\n <td>[217, 116, 136]</td>\n <td>1.739624</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2543</th>\n <td>[308, 225, 400, 572, 219, 239, 102, 136]</td>\n <td>1.739530</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2544</th>\n <td>[593, 572, 219, 217, 239, 102, 136]</td>\n <td>1.739383</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2545</th>\n <td>[225, 400, 593, 572, 217, 239, 167]</td>\n <td>1.739080</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2546</th>\n <td>[308, 225, 593, 219, 217, 239, 102, 167]</td>\n <td>1.739073</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2547</th>\n <td>[308, 593, 572, 136]</td>\n <td>1.738954</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2548</th>\n <td>[400, 593, 219, 102]</td>\n <td>1.738832</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2549</th>\n <td>[400, 593, 572, 219, 239, 116, 136]</td>\n <td>1.738711</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2550</th>\n <td>[225, 593, 219, 217, 239, 102, 136]</td>\n <td>1.738352</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2551</th>\n <td>[572, 219, 217, 239, 116, 136, 167]</td>\n <td>1.738019</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2552</th>\n <td>[308, 572, 219, 217, 116, 136]</td>\n <td>1.738018</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2553</th>\n <td>[225, 572, 219, 102, 116]</td>\n <td>1.737794</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2554</th>\n <td>[308, 225, 400, 219, 217, 239, 102, 167]</td>\n <td>1.737753</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2555</th>\n <td>[225, 400, 593, 572, 219, 116]</td>\n <td>1.737604</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2556</th>\n <td>[308, 225, 572, 217, 239, 116, 167]</td>\n <td>1.737505</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2557</th>\n <td>[308, 225, 400, 219, 239, 102, 136]</td>\n <td>1.737385</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2558</th>\n <td>[308, 225, 400, 593]</td>\n <td>1.737362</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2559</th>\n <td>[308, 593, 219, 217, 239, 102, 116]</td>\n <td>1.737345</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2560</th>\n <td>[225, 400, 593, 219, 116]</td>\n <td>1.736545</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2561</th>\n <td>[308, 400, 593, 217]</td>\n <td>1.736441</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2562</th>\n <td>[308, 572, 102, 167]</td>\n <td>1.736394</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2563</th>\n <td>[225, 572, 219, 217, 116, 136]</td>\n <td>1.736363</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2564</th>\n <td>[308, 225, 400, 593, 572, 219, 167]</td>\n <td>1.736338</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2565</th>\n <td>[400, 593, 572, 217, 239, 116]</td>\n <td>1.736281</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2566</th>\n <td>[308, 225, 400, 572, 219, 217, 102]</td>\n <td>1.736244</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2567</th>\n <td>[400, 593, 219, 239, 116, 136]</td>\n <td>1.736134</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2568</th>\n <td>[308, 400, 572, 219, 217, 239, 102, 116]</td>\n <td>1.735684</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2569</th>\n <td>[593, 572, 239, 116, 136]</td>\n <td>1.735577</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2570</th>\n <td>[308, 225, 593, 572, 219, 217, 239, 136, 167]</td>\n <td>1.735189</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2571</th>\n <td>[225, 400, 572, 239, 102, 167]</td>\n <td>1.735185</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2572</th>\n <td>[308, 225, 593, 572, 217, 239, 102]</td>\n <td>1.735018</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2573</th>\n <td>[225, 572, 217, 239, 102, 136]</td>\n <td>1.734996</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2574</th>\n <td>[308, 225, 400, 593, 572]</td>\n <td>1.734856</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2575</th>\n <td>[308, 225, 572, 219, 102, 167]</td>\n <td>1.734764</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2576</th>\n <td>[308, 400, 219, 217, 239, 102, 116]</td>\n <td>1.734255</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2577</th>\n <td>[308, 400, 239, 116, 167]</td>\n <td>1.734141</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2578</th>\n <td>[225, 400, 219, 217, 239, 102, 136]</td>\n <td>1.734124</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2579</th>\n <td>[572, 219, 217, 102, 167]</td>\n <td>1.733858</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2580</th>\n <td>[593, 572, 219, 116, 167]</td>\n <td>1.733717</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2581</th>\n <td>[308, 400, 593, 572, 239, 102]</td>\n <td>1.733644</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2582</th>\n <td>[400, 593, 219, 217, 116]</td>\n <td>1.733534</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2583</th>\n <td>[308, 593, 572, 219, 217, 239, 116, 136]</td>\n <td>1.733495</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2584</th>\n <td>[225, 400, 593, 219, 217, 167]</td>\n <td>1.733435</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2585</th>\n <td>[308, 400, 593, 572, 239, 136]</td>\n <td>1.733314</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2586</th>\n <td>[225, 400, 572, 167]</td>\n <td>1.733282</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2587</th>\n <td>[308, 400, 593, 572, 219, 239, 116, 167]</td>\n <td>1.732932</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2588</th>\n <td>[308, 400, 593, 239, 136]</td>\n <td>1.732609</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2589</th>\n <td>[308, 225, 400, 593, 239, 167]</td>\n <td>1.732368</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2590</th>\n <td>[308, 400, 593, 219, 239, 116, 167]</td>\n <td>1.732139</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2591</th>\n <td>[308, 225, 572, 219, 116, 136]</td>\n <td>1.732019</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2592</th>\n <td>[308, 572, 217, 239, 102, 167]</td>\n <td>1.731559</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2593</th>\n <td>[308, 400, 593, 219, 217, 167]</td>\n <td>1.731427</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2594</th>\n <td>[308, 225, 400, 593, 219, 167]</td>\n <td>1.731300</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2595</th>\n <td>[225, 400, 572, 239, 136, 167]</td>\n <td>1.731264</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2596</th>\n <td>[308, 225, 219, 217, 136, 167]</td>\n <td>1.731018</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2597</th>\n <td>[593, 136, 167]</td>\n <td>1.730742</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2598</th>\n <td>[308, 400, 593, 239, 102]</td>\n <td>1.730741</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2599</th>\n <td>[308, 400, 136]</td>\n <td>1.730694</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2600</th>\n <td>[308, 225, 400, 219, 217, 102]</td>\n <td>1.730317</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2601</th>\n <td>[308, 225, 593, 217, 239, 102]</td>\n <td>1.730115</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2602</th>\n <td>[225, 219, 217, 102, 167]</td>\n <td>1.730025</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2603</th>\n <td>[308, 400, 572, 239, 116, 167]</td>\n <td>1.729962</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2604</th>\n <td>[308, 225, 400, 572, 219, 217, 239, 136, 167]</td>\n <td>1.729753</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2605</th>\n <td>[308, 225, 400, 593, 572, 239, 167]</td>\n <td>1.729364</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2606</th>\n <td>[400, 593, 572, 219, 136]</td>\n <td>1.728865</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2607</th>\n <td>[219, 217, 239, 116, 136, 167]</td>\n <td>1.728204</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2608</th>\n <td>[308, 225, 593, 572, 217, 239, 136]</td>\n <td>1.728181</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2609</th>\n <td>[308, 225, 593, 219, 217, 239, 136, 167]</td>\n <td>1.727923</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2610</th>\n <td>[308, 593, 572, 219, 217, 239, 102, 167]</td>\n <td>1.727741</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2611</th>\n <td>[225, 400, 239, 102, 167]</td>\n <td>1.727692</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2612</th>\n <td>[308, 593, 219, 217, 239, 116, 136]</td>\n <td>1.726901</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2613</th>\n <td>[308, 593, 219, 116, 167]</td>\n <td>1.726876</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2614</th>\n <td>[308, 572, 219, 239, 102, 116, 167]</td>\n <td>1.726792</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2615</th>\n <td>[308, 225, 400, 219, 217, 239, 136, 167]</td>\n <td>1.726761</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2616</th>\n <td>[308, 400, 572, 116]</td>\n <td>1.726751</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2617</th>\n <td>[308, 225, 593, 572, 219, 217, 102]</td>\n <td>1.726707</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2618</th>\n <td>[308, 572, 217, 239, 136, 167]</td>\n <td>1.726325</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2619</th>\n <td>[308, 400, 116]</td>\n <td>1.726209</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2620</th>\n <td>[308, 225, 572, 219, 217, 116, 167]</td>\n <td>1.726147</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2621</th>\n <td>[225, 400, 239, 136, 167]</td>\n <td>1.725891</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2622</th>\n <td>[308, 400, 572, 219, 217, 239, 116, 136]</td>\n <td>1.725579</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2623</th>\n <td>[219, 217, 102, 116]</td>\n <td>1.725533</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2624</th>\n <td>[400, 593, 572, 219, 239, 102, 167]</td>\n <td>1.725214</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2625</th>\n <td>[308, 400, 593, 572, 219, 116]</td>\n <td>1.725103</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2626</th>\n <td>[225, 400, 593, 572, 219, 239, 116, 167]</td>\n <td>1.724842</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2627</th>\n <td>[225, 593, 572, 219, 217, 239, 102, 116]</td>\n <td>1.724724</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2628</th>\n <td>[225, 400, 239, 116, 167]</td>\n <td>1.724698</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2629</th>\n <td>[593, 102, 167]</td>\n <td>1.724361</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2630</th>\n <td>[225, 400, 593, 219, 239, 116, 167]</td>\n <td>1.724048</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2631</th>\n <td>[217, 136, 167]</td>\n <td>1.724034</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2632</th>\n <td>[225, 219, 239, 102, 136, 167]</td>\n <td>1.723835</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2633</th>\n <td>[308, 225, 593, 217, 239, 136]</td>\n <td>1.723762</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2634</th>\n <td>[308, 400, 219, 217, 239, 116, 136]</td>\n <td>1.723523</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2635</th>\n <td>[308, 219, 217, 102, 167]</td>\n <td>1.723248</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2636</th>\n <td>[225, 219, 102, 116]</td>\n <td>1.723069</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2637</th>\n <td>[593, 219, 217, 239, 102, 136]</td>\n <td>1.722977</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2638</th>\n <td>[308, 225, 593, 572, 219, 239, 102, 116]</td>\n <td>1.722569</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2639</th>\n <td>[572, 219, 239, 102, 116, 136]</td>\n <td>1.722510</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2640</th>\n <td>[308, 225, 572, 239, 102, 136]</td>\n <td>1.722070</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2641</th>\n <td>[400, 572, 219, 217, 239, 102, 136]</td>\n <td>1.722027</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2642</th>\n <td>[593, 219, 136, 167]</td>\n <td>1.721478</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2643</th>\n <td>[225, 400, 593, 572, 239, 102]</td>\n <td>1.721199</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2644</th>\n <td>[308, 572, 219, 217, 136, 167]</td>\n <td>1.720665</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2645</th>\n <td>[308, 593, 572, 219, 239, 102, 136]</td>\n <td>1.720521</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2646</th>\n <td>[400, 593, 572, 217]</td>\n <td>1.720501</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2647</th>\n <td>[308, 400, 572, 219, 217, 239, 102, 167]</td>\n <td>1.720448</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2648</th>\n <td>[308, 572, 136, 167]</td>\n <td>1.720406</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2649</th>\n <td>[308, 225, 217, 102]</td>\n <td>1.720208</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2650</th>\n <td>[308, 400, 593, 219, 116]</td>\n <td>1.719689</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2651</th>\n <td>[308, 217, 239, 102, 167]</td>\n <td>1.719623</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2652</th>\n <td>[225, 572, 219, 217, 136, 167]</td>\n <td>1.719271</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2653</th>\n <td>[308, 225, 400, 572, 219, 239, 102, 116]</td>\n <td>1.719031</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2654</th>\n <td>[308, 219, 239, 102, 116, 167]</td>\n <td>1.719026</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2655</th>\n <td>[308, 225, 400, 572, 219, 217, 136]</td>\n <td>1.718727</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2656</th>\n <td>[225, 400, 572, 239, 116, 167]</td>\n <td>1.718677</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2657</th>\n <td>[308, 225, 400, 219, 239, 102, 116]</td>\n <td>1.718650</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2658</th>\n <td>[225, 400, 593, 572, 239, 136]</td>\n <td>1.718590</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2659</th>\n <td>[308, 225, 572, 217, 136]</td>\n <td>1.718563</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2660</th>\n <td>[225, 400, 572, 219, 217, 239, 102, 116]</td>\n <td>1.718427</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2661</th>\n <td>[308, 225, 219, 116, 136]</td>\n <td>1.718349</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2662</th>\n <td>[400, 593, 572, 219, 217, 167]</td>\n <td>1.718058</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2663</th>\n <td>[308, 225, 219, 102, 167]</td>\n <td>1.717946</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2664</th>\n <td>[308, 593, 219, 217, 239, 102, 167]</td>\n <td>1.717934</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2665</th>\n <td>[308, 593, 572, 219, 217, 239, 136, 167]</td>\n <td>1.717705</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2666</th>\n <td>[308, 593, 572, 116]</td>\n <td>1.717652</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2667</th>\n <td>[308, 572, 219, 239, 116, 136, 167]</td>\n <td>1.717500</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2668</th>\n <td>[308, 225, 593, 219, 239, 102, 116]</td>\n <td>1.717496</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2669</th>\n <td>[225, 400, 593, 239, 102]</td>\n <td>1.717436</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2670</th>\n <td>[400, 593, 572, 219, 239, 136, 167]</td>\n <td>1.717296</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2671</th>\n <td>[308, 400, 593, 239, 116]</td>\n <td>1.717277</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2672</th>\n <td>[308, 219, 217, 116, 136]</td>\n <td>1.717273</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2673</th>\n <td>[400, 593, 219, 239, 102, 167]</td>\n <td>1.716952</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2674</th>\n <td>[225, 400, 593, 239, 136]</td>\n <td>1.716941</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2675</th>\n <td>[225, 400, 593]</td>\n <td>1.716887</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2676</th>\n <td>[308, 217, 239, 136, 167]</td>\n <td>1.716245</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2677</th>\n <td>[400, 593, 217]</td>\n <td>1.715979</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2678</th>\n <td>[308, 400, 219, 217, 239, 102, 167]</td>\n <td>1.715912</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2679</th>\n <td>[593, 572, 239, 102, 116]</td>\n <td>1.715782</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2680</th>\n <td>[308, 225, 593, 572, 219, 217, 239, 116, 167]</td>\n <td>1.715663</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2681</th>\n <td>[308, 225, 400, 572, 217, 239, 102]</td>\n <td>1.715545</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2682</th>\n <td>[225, 593, 219, 217, 239, 102, 116]</td>\n <td>1.715512</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2683</th>\n <td>[400, 593, 219, 136]</td>\n <td>1.715395</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2684</th>\n <td>[225, 400, 219, 217, 239, 102, 116]</td>\n <td>1.715035</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2685</th>\n <td>[308, 219, 102, 136]</td>\n <td>1.714484</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2686</th>\n <td>[308, 225, 400, 217, 239, 102]</td>\n <td>1.713807</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2687</th>\n <td>[308, 225, 219, 217, 116, 167]</td>\n <td>1.713742</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2688</th>\n <td>[308, 225, 593, 572, 219, 239, 116, 136]</td>\n <td>1.713666</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2689</th>\n <td>[225, 572, 217, 239, 102, 116]</td>\n <td>1.713549</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2690</th>\n <td>[400, 219, 217, 239, 102, 136]</td>\n <td>1.713541</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2691</th>\n <td>[225, 219, 217, 116, 136]</td>\n <td>1.713358</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2692</th>\n <td>[593, 572, 116]</td>\n <td>1.713018</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2693</th>\n <td>[308, 225, 400, 572, 219, 217, 239, 116, 167]</td>\n <td>1.713005</td>\n <td>2</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2694</th>\n <td>[308, 400, 593, 572, 239, 116]</td>\n <td>1.712993</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2695</th>\n <td>[572, 219, 217, 116, 136]</td>\n <td>1.712891</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2696</th>\n <td>[225, 572, 219, 102, 167]</td>\n <td>1.712708</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2697</th>\n <td>[593, 572, 102]</td>\n <td>1.712437</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2698</th>\n <td>[308, 400, 572, 219, 239, 102, 136]</td>\n <td>1.712087</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2699</th>\n <td>[308, 572, 116, 167]</td>\n <td>1.712038</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2700</th>\n <td>[225, 572, 219, 239, 102, 116, 167]</td>\n <td>1.711970</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2701</th>\n <td>[225, 593, 572, 219, 217, 239, 116, 136]</td>\n <td>1.711657</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2702</th>\n <td>[308, 225, 400, 219, 217, 239, 116, 167]</td>\n <td>1.711621</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2703</th>\n <td>[225, 400, 593, 572, 219, 167]</td>\n <td>1.711599</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2704</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 239, 102]</td>\n <td>1.711557</td>\n <td>1</td>\n <td>8</td>\n </tr>\n <tr>\n <th>2705</th>\n <td>[400, 593, 572, 217, 239, 167]</td>\n <td>1.711463</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2706</th>\n <td>[400, 572, 102]</td>\n <td>1.711239</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2707</th>\n <td>[400, 572, 239, 102, 136]</td>\n <td>1.711053</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2708</th>\n <td>[308, 225, 572, 219, 136, 167]</td>\n <td>1.711053</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2709</th>\n <td>[308, 400, 572, 219, 217, 102]</td>\n <td>1.711031</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2710</th>\n <td>[308, 225, 400, 219, 217, 136]</td>\n <td>1.710894</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2711</th>\n <td>[225, 116, 136]</td>\n <td>1.710847</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2712</th>\n <td>[308, 225, 593, 219, 217, 239, 116, 167]</td>\n <td>1.710515</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2713</th>\n <td>[308, 225, 593, 219, 217, 102]</td>\n <td>1.710488</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2714</th>\n <td>[308, 400, 572, 219, 217, 239, 136, 167]</td>\n <td>1.710292</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2715</th>\n <td>[308, 225, 593, 217, 239, 116]</td>\n <td>1.709798</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2716</th>\n <td>[400, 593, 217, 239, 167]</td>\n <td>1.709776</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2717</th>\n <td>[308, 225, 400, 572, 219, 239, 116, 136]</td>\n <td>1.709737</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2718</th>\n <td>[308, 219, 239, 116, 136, 167]</td>\n <td>1.709731</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2719</th>\n <td>[308, 225, 593, 572, 217, 239, 116]</td>\n <td>1.709171</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2720</th>\n <td>[225, 102, 167]</td>\n <td>1.709144</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2721</th>\n <td>[400, 593, 219, 239, 136, 167]</td>\n <td>1.709108</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2722</th>\n <td>[225, 400, 593, 239, 116]</td>\n <td>1.708873</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2723</th>\n <td>[308, 225, 400, 219, 239, 116, 136]</td>\n <td>1.708870</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2724</th>\n <td>[225, 593, 572, 219, 217, 239, 102, 167]</td>\n <td>1.708835</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2725</th>\n <td>[225, 400, 593, 572]</td>\n <td>1.708666</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2726</th>\n <td>[308, 572, 219, 102, 116]</td>\n <td>1.708564</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2727</th>\n <td>[308, 225, 593, 219, 239, 116, 136]</td>\n <td>1.708314</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2728</th>\n <td>[225, 400, 572, 219, 217, 102]</td>\n <td>1.708178</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2729</th>\n <td>[593, 239, 116, 136]</td>\n <td>1.707673</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2730</th>\n <td>[308, 225, 593, 572, 219, 217, 136]</td>\n <td>1.707463</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2731</th>\n <td>[308, 593, 219, 239, 102, 136]</td>\n <td>1.707396</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2732</th>\n <td>[308, 593, 219, 217, 239, 136, 167]</td>\n <td>1.707386</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2733</th>\n <td>[593, 572, 239, 136, 167]</td>\n <td>1.707289</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2734</th>\n <td>[308, 225, 400, 593, 219, 217, 239, 102]</td>\n <td>1.707285</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2735</th>\n <td>[308, 225, 400, 572, 217, 239, 136]</td>\n <td>1.707262</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2736</th>\n <td>[593, 572, 136]</td>\n <td>1.707125</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2737</th>\n <td>[225, 217, 239, 102, 136]</td>\n <td>1.706561</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2738</th>\n <td>[593, 572, 219, 217, 239, 102, 116]</td>\n <td>1.706506</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2739</th>\n <td>[308, 593, 572, 217, 239, 102]</td>\n <td>1.706142</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2740</th>\n <td>[308, 400, 219, 239, 102, 136]</td>\n <td>1.706131</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2741</th>\n <td>[225, 400, 572, 219, 217, 239, 116, 136]</td>\n <td>1.705803</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2742</th>\n <td>[572, 219, 239, 102, 136, 167]</td>\n <td>1.705643</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2743</th>\n <td>[308, 225, 400, 217, 239, 136]</td>\n <td>1.705364</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2744</th>\n <td>[308, 400, 219, 217, 239, 136, 167]</td>\n <td>1.705121</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2745</th>\n <td>[308, 225, 593, 572, 219, 239, 102, 167]</td>\n <td>1.704822</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2746</th>\n <td>[308, 225, 400, 572, 219, 102]</td>\n <td>1.704551</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2747</th>\n <td>[400, 593, 219, 217, 167]</td>\n <td>1.704519</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2748</th>\n <td>[308, 572, 217, 239, 116, 167]</td>\n <td>1.704284</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2749</th>\n <td>[308, 225, 239, 102, 136]</td>\n <td>1.704034</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2750</th>\n <td>[308, 217, 239, 116, 167]</td>\n <td>1.703632</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2751</th>\n <td>[225, 400, 593, 219, 167]</td>\n <td>1.703423</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2752</th>\n <td>[225, 572, 217, 239, 116, 136]</td>\n <td>1.703370</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2753</th>\n <td>[225, 400, 572, 219, 217, 239, 102, 167]</td>\n <td>1.702876</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2754</th>\n <td>[225, 400, 593, 572, 239, 116]</td>\n <td>1.702600</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2755</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 239, 136]</td>\n <td>1.702495</td>\n <td>1</td>\n <td>8</td>\n </tr>\n <tr>\n <th>2756</th>\n <td>[308, 225, 572, 217, 116]</td>\n <td>1.702416</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2757</th>\n <td>[308, 593, 572, 217, 239, 136]</td>\n <td>1.702322</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2758</th>\n <td>[308, 225, 400, 572, 219, 239, 102, 167]</td>\n <td>1.702210</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2759</th>\n <td>[225, 219, 239, 102, 116, 167]</td>\n <td>1.702075</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2760</th>\n <td>[593, 219, 116, 167]</td>\n <td>1.701628</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2761</th>\n <td>[225, 593, 219, 217, 239, 116, 136]</td>\n <td>1.701383</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2762</th>\n <td>[225, 400, 219, 217, 239, 116, 136]</td>\n <td>1.701352</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2763</th>\n <td>[225, 593, 572, 219, 239, 102, 136]</td>\n <td>1.701322</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2764</th>\n <td>[308, 400, 593, 572, 219, 167]</td>\n <td>1.701137</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2765</th>\n <td>[219, 239, 102, 116, 136]</td>\n <td>1.700994</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2766</th>\n <td>[308, 400, 219, 217, 102]</td>\n <td>1.700922</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2767</th>\n <td>[308, 225, 572, 239, 102, 116]</td>\n <td>1.700884</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2768</th>\n <td>[225, 572, 219, 116, 136]</td>\n <td>1.700766</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2769</th>\n <td>[400, 593, 572, 219, 116]</td>\n <td>1.700720</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2770</th>\n <td>[308, 225, 400, 572, 219, 217, 116]</td>\n <td>1.700384</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2771</th>\n <td>[225, 572, 217, 102]</td>\n <td>1.699809</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2772</th>\n <td>[225, 217, 239, 102, 116]</td>\n <td>1.699510</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2773</th>\n <td>[308, 593, 572, 219, 217, 102]</td>\n <td>1.698844</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2774</th>\n <td>[308, 225, 572, 219, 217, 239, 102, 136]</td>\n <td>1.698598</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2775</th>\n <td>[308, 225, 400, 219, 102]</td>\n <td>1.698457</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2776</th>\n <td>[308, 225, 400, 219, 239, 102, 167]</td>\n <td>1.698409</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2777</th>\n <td>[225, 572, 219, 239, 116, 136, 167]</td>\n <td>1.698369</td>\n <td>3</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2778</th>\n <td>[593, 102, 136]</td>\n <td>1.697831</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2779</th>\n <td>[225, 400, 219, 217, 102]</td>\n <td>1.697821</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2780</th>\n <td>[308, 225, 572, 239, 116, 136]</td>\n <td>1.697766</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2781</th>\n <td>[308, 225, 400, 593, 219, 217, 239, 136]</td>\n <td>1.697707</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2782</th>\n <td>[219, 217, 102, 167]</td>\n <td>1.697680</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2783</th>\n <td>[225, 572, 217, 239, 102, 167]</td>\n <td>1.697442</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2784</th>\n <td>[225, 593, 572, 219, 217, 102]</td>\n <td>1.697375</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2785</th>\n <td>[400, 572, 219, 217, 239, 102, 116]</td>\n <td>1.696311</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2786</th>\n <td>[225, 400, 219, 217, 239, 102, 167]</td>\n <td>1.696077</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2787</th>\n <td>[308, 225, 593, 572, 219, 239, 136, 167]</td>\n <td>1.695824</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2788</th>\n <td>[308, 593, 217, 239, 102]</td>\n <td>1.695759</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2789</th>\n <td>[225, 593, 572, 219, 217, 239, 136, 167]</td>\n <td>1.695686</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2790</th>\n <td>[225, 572, 219, 217, 116, 167]</td>\n <td>1.695664</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2791</th>\n <td>[308, 225, 593, 219, 239, 102, 167]</td>\n <td>1.695622</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2792</th>\n <td>[225, 593, 219, 217, 239, 102, 167]</td>\n <td>1.695532</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2793</th>\n <td>[308, 225, 400, 219, 217, 116]</td>\n <td>1.694988</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2794</th>\n <td>[308, 593, 572, 219, 217, 239, 116, 167]</td>\n <td>1.694486</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2795</th>\n <td>[308, 219, 217, 136, 167]</td>\n <td>1.694367</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2796</th>\n <td>[400, 593, 572, 219, 239, 116, 167]</td>\n <td>1.694210</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2797</th>\n <td>[572, 217, 239, 102, 136]</td>\n <td>1.694055</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2798</th>\n <td>[572, 219, 217, 136, 167]</td>\n <td>1.694020</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2799</th>\n <td>[308, 572, 219, 217, 116, 167]</td>\n <td>1.694002</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2800</th>\n <td>[593, 572, 219, 217, 239, 116, 136]</td>\n <td>1.693984</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2801</th>\n <td>[225, 400, 572, 219, 239, 102, 136]</td>\n <td>1.693752</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2802</th>\n <td>[308, 593, 217, 239, 136]</td>\n <td>1.693736</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2803</th>\n <td>[593, 219, 217, 239, 102, 116]</td>\n <td>1.693627</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2804</th>\n <td>[308, 225, 400, 217, 239, 116]</td>\n <td>1.693379</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2805</th>\n <td>[400, 593, 219, 116]</td>\n <td>1.693195</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2806</th>\n <td>[308, 225, 239, 102, 116]</td>\n <td>1.692970</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2807</th>\n <td>[308, 225, 400, 572, 219, 239, 136, 167]</td>\n <td>1.692857</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2808</th>\n <td>[308, 225, 239, 116, 136]</td>\n <td>1.692482</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2809</th>\n <td>[308, 400, 572, 219, 217, 136]</td>\n <td>1.692450</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2810</th>\n <td>[572, 239, 102, 116, 136]</td>\n <td>1.692078</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2811</th>\n <td>[308, 400, 572, 167]</td>\n <td>1.691806</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2812</th>\n <td>[308, 225, 400, 572, 217, 239, 116]</td>\n <td>1.691741</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2813</th>\n <td>[400, 572, 136]</td>\n <td>1.691242</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2814</th>\n <td>[400, 572, 239, 116, 136]</td>\n <td>1.691153</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2815</th>\n <td>[308, 400, 593, 572, 219, 217, 239, 102]</td>\n <td>1.691138</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2816</th>\n <td>[308, 593, 572, 219, 239, 102, 116]</td>\n <td>1.690956</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2817</th>\n <td>[308, 400, 572, 219, 217, 239, 116, 167]</td>\n <td>1.690940</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2818</th>\n <td>[308, 225, 217, 136]</td>\n <td>1.690864</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2819</th>\n <td>[308, 225, 219, 136, 167]</td>\n <td>1.690723</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2820</th>\n <td>[308, 225, 593, 572, 219, 102]</td>\n <td>1.690712</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2821</th>\n <td>[593, 572, 239, 116, 167]</td>\n <td>1.690570</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2822</th>\n <td>[400, 219, 217, 239, 102, 116]</td>\n <td>1.690312</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2823</th>\n <td>[225, 400, 572, 219, 217, 239, 136, 167]</td>\n <td>1.690207</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2824</th>\n <td>[225, 217, 239, 116, 136]</td>\n <td>1.690162</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2825</th>\n <td>[572, 239, 116, 136, 167]</td>\n <td>1.690113</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2826</th>\n <td>[308, 400, 593, 219, 167]</td>\n <td>1.689978</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2827</th>\n <td>[225, 219, 217, 136, 167]</td>\n <td>1.689810</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2828</th>\n <td>[400, 593, 219, 239, 116, 167]</td>\n <td>1.689430</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2829</th>\n <td>[400, 572, 239, 102, 116]</td>\n <td>1.689121</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2830</th>\n <td>[308, 225, 593, 219, 217, 136]</td>\n <td>1.689054</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2831</th>\n <td>[308, 225, 593, 572, 217, 239, 167]</td>\n <td>1.689034</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2832</th>\n <td>[593, 572, 219, 217, 239, 102, 167]</td>\n <td>1.688699</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2833</th>\n <td>[308, 225, 219, 217, 239, 102, 136]</td>\n <td>1.688577</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2834</th>\n <td>[308, 225, 400, 219, 239, 136, 167]</td>\n <td>1.688559</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2835</th>\n <td>[308, 225, 572, 219, 116, 167]</td>\n <td>1.688461</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2836</th>\n <td>[308, 225, 217, 116]</td>\n <td>1.688458</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2837</th>\n <td>[308, 400, 572, 219, 239, 102, 116]</td>\n <td>1.688227</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2838</th>\n <td>[400, 116]</td>\n <td>1.688150</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2839</th>\n <td>[593, 572, 239, 102, 167]</td>\n <td>1.688139</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2840</th>\n <td>[308, 400, 219, 217, 239, 116, 167]</td>\n <td>1.687548</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2841</th>\n <td>[225, 219, 239, 116, 136, 167]</td>\n <td>1.687538</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2842</th>\n <td>[572, 219, 102, 116]</td>\n <td>1.687509</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2843</th>\n <td>[225, 572, 217, 239, 136, 167]</td>\n <td>1.687052</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2844</th>\n <td>[308, 400, 593, 572, 239, 167]</td>\n <td>1.686887</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2845</th>\n <td>[308, 225, 400, 572, 219, 136]</td>\n <td>1.686880</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2846</th>\n <td>[308, 593, 219, 217, 239, 116, 167]</td>\n <td>1.686547</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2847</th>\n <td>[308, 225, 593, 572, 219, 217, 116]</td>\n <td>1.686425</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2848</th>\n <td>[308, 225, 593, 219, 239, 136, 167]</td>\n <td>1.686312</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2849</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 239, 116]</td>\n <td>1.686246</td>\n <td>1</td>\n <td>8</td>\n </tr>\n <tr>\n <th>2850</th>\n <td>[225, 219, 102, 167]</td>\n <td>1.685975</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2851</th>\n <td>[308, 593, 102]</td>\n <td>1.685838</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2852</th>\n <td>[572, 239, 102, 136, 167]</td>\n <td>1.685377</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2853</th>\n <td>[225, 400, 219, 239, 102, 136]</td>\n <td>1.685173</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2854</th>\n <td>[225, 400, 572, 219, 217, 136]</td>\n <td>1.684791</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2855</th>\n <td>[308, 572, 217, 102]</td>\n <td>1.684746</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2856</th>\n <td>[308, 400, 593, 219, 217, 239, 102]</td>\n <td>1.684606</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2857</th>\n <td>[308, 572, 219, 102, 167]</td>\n <td>1.684460</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2858</th>\n <td>[308, 400, 219, 239, 102, 116]</td>\n <td>1.684226</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2859</th>\n <td>[308, 225, 593, 217, 239, 167]</td>\n <td>1.684031</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2860</th>\n <td>[308, 219, 102, 116]</td>\n <td>1.683972</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2861</th>\n <td>[225, 593, 219, 239, 102, 136]</td>\n <td>1.683872</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2862</th>\n <td>[308, 593, 116]</td>\n <td>1.683870</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2863</th>\n <td>[308, 400, 593, 239, 167]</td>\n <td>1.683779</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2864</th>\n <td>[400, 572, 219, 217, 239, 116, 136]</td>\n <td>1.683760</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2865</th>\n <td>[308, 572, 219, 116, 136]</td>\n <td>1.683431</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2866</th>\n <td>[308, 593, 572, 219, 239, 116, 136]</td>\n <td>1.683326</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2867</th>\n <td>[400, 572, 116]</td>\n <td>1.683107</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2868</th>\n <td>[219, 102, 136]</td>\n <td>1.683057</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2869</th>\n <td>[308, 225, 400, 593, 219, 217, 239, 116]</td>\n <td>1.682776</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2870</th>\n <td>[308, 225, 400, 572, 219, 217, 167]</td>\n <td>1.682696</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2871</th>\n <td>[225, 400, 219, 217, 239, 136, 167]</td>\n <td>1.682351</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2872</th>\n <td>[308, 400, 593, 572, 219, 217, 239, 136]</td>\n <td>1.682304</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2873</th>\n <td>[308, 400, 572, 217, 239, 102]</td>\n <td>1.682086</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2874</th>\n <td>[225, 593, 219, 217, 239, 136, 167]</td>\n <td>1.681313</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2875</th>\n <td>[400, 572, 219, 217, 102]</td>\n <td>1.680574</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2876</th>\n <td>[308, 593, 219, 239, 102, 116]</td>\n <td>1.680540</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2877</th>\n <td>[593, 219, 217, 239, 116, 136]</td>\n <td>1.680285</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2878</th>\n <td>[308, 400, 219, 217, 136]</td>\n <td>1.680144</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2879</th>\n <td>[308, 400, 572, 219, 239, 116, 136]</td>\n <td>1.679557</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2880</th>\n <td>[308, 225, 572, 239, 102, 167]</td>\n <td>1.679461</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2881</th>\n <td>[400, 572, 219, 217, 239, 102, 167]</td>\n <td>1.678947</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2882</th>\n <td>[308, 593, 572, 217, 239, 116]</td>\n <td>1.678805</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2883</th>\n <td>[308, 225, 400, 219, 136]</td>\n <td>1.678690</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2884</th>\n <td>[593, 239, 116, 167]</td>\n <td>1.678671</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2885</th>\n <td>[308, 225, 572, 217, 167]</td>\n <td>1.678668</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2886</th>\n <td>[308, 593, 572, 219, 217, 136]</td>\n <td>1.678356</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2887</th>\n <td>[400, 239, 116, 136]</td>\n <td>1.677898</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2888</th>\n <td>[400, 239, 102, 136]</td>\n <td>1.677894</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2889</th>\n <td>[308, 593, 572, 167]</td>\n <td>1.677664</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2890</th>\n <td>[308, 593, 136]</td>\n <td>1.677555</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2891</th>\n <td>[225, 219, 116, 136]</td>\n <td>1.677208</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2892</th>\n <td>[308, 572, 219, 217, 239, 102, 136]</td>\n <td>1.677116</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2893</th>\n <td>[308, 400, 167]</td>\n <td>1.677099</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2894</th>\n <td>[219, 217, 116, 136]</td>\n <td>1.677073</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2895</th>\n <td>[308, 400, 593, 572]</td>\n <td>1.676956</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2896</th>\n <td>[400, 219, 217, 239, 116, 136]</td>\n <td>1.676752</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2897</th>\n <td>[308, 593, 217, 239, 116]</td>\n <td>1.676566</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2898</th>\n <td>[308, 225, 572, 219, 217, 239, 102, 116]</td>\n <td>1.676391</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2899</th>\n <td>[219, 239, 102, 136, 167]</td>\n <td>1.676317</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2900</th>\n <td>[225, 593, 572, 217, 239, 102]</td>\n <td>1.676191</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2901</th>\n <td>[308, 225, 572, 239, 136, 167]</td>\n <td>1.676064</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2902</th>\n <td>[593, 572, 219, 217, 239, 136, 167]</td>\n <td>1.676050</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2903</th>\n <td>[225, 217, 239, 102, 167]</td>\n <td>1.675867</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2904</th>\n <td>[308, 225, 400, 572, 219, 239, 116, 167]</td>\n <td>1.675821</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2905</th>\n <td>[308, 225, 400, 593, 572, 219, 239, 102]</td>\n <td>1.675754</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2906</th>\n <td>[308, 400, 217, 239, 102]</td>\n <td>1.675704</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2907</th>\n <td>[308, 225, 593, 572, 219, 239, 116, 167]</td>\n <td>1.675704</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2908</th>\n <td>[225, 572, 219, 136, 167]</td>\n <td>1.675583</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2909</th>\n <td>[308, 400, 593, 219, 217, 239, 136]</td>\n <td>1.675317</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2910</th>\n <td>[308, 400, 219, 239, 116, 136]</td>\n <td>1.675274</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2911</th>\n <td>[308, 400, 572, 217, 239, 136]</td>\n <td>1.675185</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2912</th>\n <td>[225, 219, 217, 116, 167]</td>\n <td>1.675154</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2913</th>\n <td>[225, 593, 572, 219, 217, 239, 116, 167]</td>\n <td>1.674787</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2914</th>\n <td>[308, 225, 219, 116, 167]</td>\n <td>1.674724</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2915</th>\n <td>[308, 593, 219, 217, 102]</td>\n <td>1.674712</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2916</th>\n <td>[225, 400, 593, 572, 239, 167]</td>\n <td>1.674576</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2917</th>\n <td>[225, 593, 572, 219, 239, 102, 116]</td>\n <td>1.674038</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2918</th>\n <td>[593, 116]</td>\n <td>1.673801</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2919</th>\n <td>[308, 225, 400, 219, 217, 167]</td>\n <td>1.673698</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2920</th>\n <td>[225, 572, 217, 239, 116, 167]</td>\n <td>1.673698</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2921</th>\n <td>[308, 225, 400, 219, 239, 116, 167]</td>\n <td>1.673609</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2922</th>\n <td>[308, 219, 217, 116, 167]</td>\n <td>1.673428</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2923</th>\n <td>[308, 593, 219, 239, 116, 136]</td>\n <td>1.673079</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2924</th>\n <td>[308, 225, 400, 572, 217, 239, 167]</td>\n <td>1.672974</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2925</th>\n <td>[225, 400, 593, 572, 219, 217, 239, 102]</td>\n <td>1.672862</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2926</th>\n <td>[225, 400, 572, 219, 217, 239, 116, 167]</td>\n <td>1.672742</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2927</th>\n <td>[225, 400, 593, 239, 167]</td>\n <td>1.671875</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2928</th>\n <td>[225, 400, 572, 219, 239, 102, 116]</td>\n <td>1.671833</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2929</th>\n <td>[572, 239, 102, 116, 167]</td>\n <td>1.671628</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2930</th>\n <td>[308, 225, 593, 219, 102]</td>\n <td>1.671543</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2931</th>\n <td>[308, 225, 593, 219, 217, 116]</td>\n <td>1.671476</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2932</th>\n <td>[308, 225, 593, 572, 219, 136]</td>\n <td>1.671449</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2933</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 239, 167]</td>\n <td>1.671203</td>\n <td>1</td>\n <td>8</td>\n </tr>\n <tr>\n <th>2934</th>\n <td>[225, 400, 219, 217, 136]</td>\n <td>1.671123</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2935</th>\n <td>[225, 593, 219, 217, 102]</td>\n <td>1.670974</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2936</th>\n <td>[308, 400, 572, 219, 217, 116]</td>\n <td>1.670956</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2937</th>\n <td>[308, 593, 572, 219, 239, 102, 167]</td>\n <td>1.670936</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2938</th>\n <td>[593, 239, 102, 116]</td>\n <td>1.670866</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2939</th>\n <td>[400, 239, 102, 116]</td>\n <td>1.670565</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2940</th>\n <td>[593, 239, 102, 136]</td>\n <td>1.670565</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2941</th>\n <td>[225, 593, 572, 219, 217, 136]</td>\n <td>1.670499</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2942</th>\n <td>[593, 219, 217, 239, 102, 167]</td>\n <td>1.670463</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2943</th>\n <td>[400, 102]</td>\n <td>1.670436</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2944</th>\n <td>[308, 225, 400, 217, 239, 167]</td>\n <td>1.670232</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2945</th>\n <td>[308, 225, 400, 593, 219, 239, 102]</td>\n <td>1.670092</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2946</th>\n <td>[400, 593, 572, 219, 167]</td>\n <td>1.670048</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2947</th>\n <td>[225, 400, 572, 219, 102]</td>\n <td>1.669700</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2948</th>\n <td>[593, 572, 219, 217, 102]</td>\n <td>1.669494</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2949</th>\n <td>[308, 400, 572, 219, 239, 102, 167]</td>\n <td>1.669455</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2950</th>\n <td>[572, 219, 239, 102, 116, 167]</td>\n <td>1.669302</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2951</th>\n <td>[308, 400, 217, 239, 136]</td>\n <td>1.669147</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2952</th>\n <td>[308, 225, 593, 219, 239, 116, 167]</td>\n <td>1.669015</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2953</th>\n <td>[225, 217, 239, 116, 167]</td>\n <td>1.668750</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2954</th>\n <td>[400, 219, 217, 239, 102, 167]</td>\n <td>1.668642</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2955</th>\n <td>[308, 225, 219, 217, 239, 102, 116]</td>\n <td>1.668533</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2956</th>\n <td>[225, 593, 572, 217, 239, 136]</td>\n <td>1.668450</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2957</th>\n <td>[308, 102, 116]</td>\n <td>1.667828</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2958</th>\n <td>[308, 225, 593, 572, 219, 217, 167]</td>\n <td>1.667814</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2959</th>\n <td>[308, 225, 400, 572, 219, 116]</td>\n <td>1.667785</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2960</th>\n <td>[308, 400, 593]</td>\n <td>1.667691</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2961</th>\n <td>[308, 225, 400, 593, 572, 219, 239, 136]</td>\n <td>1.667614</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2962</th>\n <td>[225, 136, 167]</td>\n <td>1.667583</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2963</th>\n <td>[225, 400, 219, 217, 239, 116, 167]</td>\n <td>1.667488</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2964</th>\n <td>[593, 572, 219, 239, 102, 136]</td>\n <td>1.667417</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2965</th>\n <td>[400, 593, 572, 239, 136]</td>\n <td>1.666419</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2966</th>\n <td>[225, 400, 219, 239, 102, 116]</td>\n <td>1.666336</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2967</th>\n <td>[400, 572, 219, 217, 239, 136, 167]</td>\n <td>1.666324</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2968</th>\n <td>[225, 217, 239, 136, 167]</td>\n <td>1.666170</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2969</th>\n <td>[572, 217, 239, 102, 116]</td>\n <td>1.665637</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2970</th>\n <td>[308, 225, 593, 572, 239, 102]</td>\n <td>1.665345</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2971</th>\n <td>[308, 225, 400, 593, 219, 217, 239, 167]</td>\n <td>1.665261</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2972</th>\n <td>[225, 400, 572, 219, 217, 116]</td>\n <td>1.665140</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2973</th>\n <td>[400, 219, 217, 102]</td>\n <td>1.664471</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2974</th>\n <td>[225, 593, 219, 217, 239, 116, 167]</td>\n <td>1.664032</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2975</th>\n <td>[225, 400, 593, 219, 217, 239, 102]</td>\n <td>1.664010</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2976</th>\n <td>[400, 593, 572, 239, 102]</td>\n <td>1.663944</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2977</th>\n <td>[308, 225, 572, 219, 217, 239, 116, 136]</td>\n <td>1.663820</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2978</th>\n <td>[308, 400, 593, 572, 219, 217, 239, 116]</td>\n <td>1.663670</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2979</th>\n <td>[308, 225, 239, 102, 167]</td>\n <td>1.663531</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2980</th>\n <td>[400, 572, 239, 136, 167]</td>\n <td>1.663523</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2981</th>\n <td>[308, 400, 572, 219, 102]</td>\n <td>1.663505</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2982</th>\n <td>[308, 219, 217, 239, 102, 136]</td>\n <td>1.663299</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2983</th>\n <td>[308, 593, 572, 219, 239, 136, 167]</td>\n <td>1.663156</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2984</th>\n <td>[308, 225, 593, 572, 239, 136]</td>\n <td>1.663123</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2985</th>\n <td>[225, 593, 572, 219, 239, 116, 136]</td>\n <td>1.663061</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2986</th>\n <td>[308, 225, 400, 219, 116]</td>\n <td>1.662834</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2987</th>\n <td>[572, 219, 217, 116, 167]</td>\n <td>1.662549</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2988</th>\n <td>[308, 225, 239, 136, 167]</td>\n <td>1.662513</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2989</th>\n <td>[400, 572, 239, 102, 167]</td>\n <td>1.661993</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2990</th>\n <td>[225, 400, 593, 572, 219, 217, 239, 136]</td>\n <td>1.661943</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>2991</th>\n <td>[572, 217, 239, 116, 136]</td>\n <td>1.661831</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2992</th>\n <td>[225, 102, 136]</td>\n <td>1.661728</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>2993</th>\n <td>[308, 225, 572, 219, 217, 239, 102, 167]</td>\n <td>1.661689</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2994</th>\n <td>[308, 225, 400, 593, 219, 239, 136]</td>\n <td>1.661610</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>2995</th>\n <td>[308, 225, 572, 239, 116, 167]</td>\n <td>1.661569</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2996</th>\n <td>[308, 400, 219, 217, 116]</td>\n <td>1.661489</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2997</th>\n <td>[308, 400, 219, 239, 102, 167]</td>\n <td>1.661235</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2998</th>\n <td>[225, 593, 219, 239, 102, 116]</td>\n <td>1.661080</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>2999</th>\n <td>[593, 239, 136, 167]</td>\n <td>1.660881</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3000</th>\n <td>[308, 400, 572, 219, 239, 136, 167]</td>\n <td>1.660693</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3001</th>\n <td>[225, 400, 572, 219, 239, 116, 136]</td>\n <td>1.660418</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3002</th>\n <td>[225, 400, 219, 102]</td>\n <td>1.659448</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3003</th>\n <td>[308, 572, 219, 136, 167]</td>\n <td>1.659249</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3004</th>\n <td>[308, 225, 239, 116, 167]</td>\n <td>1.659230</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3005</th>\n <td>[308, 225, 572, 102]</td>\n <td>1.659163</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3006</th>\n <td>[225, 593, 217, 239, 102]</td>\n <td>1.659145</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3007</th>\n <td>[308, 572, 217, 136]</td>\n <td>1.658682</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3008</th>\n <td>[308, 400, 593, 219, 217, 239, 116]</td>\n <td>1.658114</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3009</th>\n <td>[572, 219, 239, 116, 136, 167]</td>\n <td>1.657736</td>\n <td>3</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3010</th>\n <td>[572, 219, 102, 167]</td>\n <td>1.657586</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3011</th>\n <td>[400, 572, 219, 239, 102, 136]</td>\n <td>1.657442</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3012</th>\n <td>[225, 572, 217, 136]</td>\n <td>1.657367</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3013</th>\n <td>[308, 400, 572, 217, 239, 116]</td>\n <td>1.657018</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3014</th>\n <td>[593, 219, 217, 239, 136, 167]</td>\n <td>1.656959</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3015</th>\n <td>[308, 225, 400, 572, 217]</td>\n <td>1.656182</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3016</th>\n <td>[225, 400, 219, 217, 116]</td>\n <td>1.655636</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3017</th>\n <td>[308, 593, 572, 217, 239, 167]</td>\n <td>1.655562</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3018</th>\n <td>[308, 225, 217, 167]</td>\n <td>1.655379</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3019</th>\n <td>[308, 400, 217, 239, 116]</td>\n <td>1.655276</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3020</th>\n <td>[308, 593, 219, 239, 102, 167]</td>\n <td>1.655275</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3021</th>\n <td>[400, 219, 217, 239, 136, 167]</td>\n <td>1.655002</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3022</th>\n <td>[225, 593, 572, 219, 102]</td>\n <td>1.654929</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3023</th>\n <td>[308, 225, 219, 217, 239, 116, 136]</td>\n <td>1.654916</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3024</th>\n <td>[400, 572, 219, 217, 136]</td>\n <td>1.654829</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3025</th>\n <td>[308, 219, 116, 136]</td>\n <td>1.654720</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3026</th>\n <td>[225, 400, 219, 239, 116, 136]</td>\n <td>1.654146</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3027</th>\n <td>[400, 593, 239, 136]</td>\n <td>1.653522</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3028</th>\n <td>[308, 225, 593, 239, 136]</td>\n <td>1.653384</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3029</th>\n <td>[308, 225, 593, 239, 102]</td>\n <td>1.653332</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3030</th>\n <td>[225, 593, 572, 219, 239, 102, 167]</td>\n <td>1.653264</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3031</th>\n <td>[308, 225, 400, 593, 572, 219, 217]</td>\n <td>1.653034</td>\n <td>0</td>\n <td>7</td>\n </tr>\n <tr>\n <th>3032</th>\n <td>[308, 593, 572, 219, 217, 116]</td>\n <td>1.653013</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3033</th>\n <td>[225, 400, 572, 217, 239, 102]</td>\n <td>1.652948</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3034</th>\n <td>[400, 593, 219, 167]</td>\n <td>1.652862</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3035</th>\n <td>[308, 225, 400, 593, 572, 217, 239]</td>\n <td>1.652837</td>\n <td>0</td>\n <td>7</td>\n </tr>\n <tr>\n <th>3036</th>\n <td>[308, 102, 136]</td>\n <td>1.652757</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3037</th>\n <td>[225, 593, 217, 239, 136]</td>\n <td>1.652495</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3038</th>\n <td>[225, 572, 217, 116]</td>\n <td>1.652454</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3039</th>\n <td>[308, 225, 400, 572, 239, 102]</td>\n <td>1.652333</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3040</th>\n <td>[225, 400, 593, 219, 217, 239, 136]</td>\n <td>1.652323</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3041</th>\n <td>[225, 400, 572, 219, 239, 102, 167]</td>\n <td>1.652309</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3042</th>\n <td>[308, 400, 219, 239, 136, 167]</td>\n <td>1.652159</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3043</th>\n <td>[308, 116, 136]</td>\n <td>1.652116</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3044</th>\n <td>[225, 572, 219, 116, 167]</td>\n <td>1.651839</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3045</th>\n <td>[308, 593, 219, 217, 136]</td>\n <td>1.651696</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3046</th>\n <td>[308, 400, 572, 219, 217, 167]</td>\n <td>1.651058</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3047</th>\n <td>[225, 593, 572, 217, 239, 116]</td>\n <td>1.651036</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3048</th>\n <td>[308, 225, 400, 593, 572, 219, 239, 116]</td>\n <td>1.650925</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>3049</th>\n <td>[308, 225, 593, 572, 217]</td>\n <td>1.650901</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3050</th>\n <td>[308, 219, 102, 167]</td>\n <td>1.650816</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3051</th>\n <td>[308, 225, 219, 217, 239, 102, 167]</td>\n <td>1.650562</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3052</th>\n <td>[219, 102, 116]</td>\n <td>1.650226</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3053</th>\n <td>[308, 572, 219, 217, 239, 102, 116]</td>\n <td>1.650208</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3054</th>\n <td>[308, 400, 219, 102]</td>\n <td>1.650168</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3055</th>\n <td>[593, 572, 219, 217, 239, 116, 167]</td>\n <td>1.650017</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3056</th>\n <td>[308, 225, 593, 219, 136]</td>\n <td>1.649900</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3057</th>\n <td>[400, 572, 239, 116, 167]</td>\n <td>1.649790</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3058</th>\n <td>[225, 593, 219, 239, 116, 136]</td>\n <td>1.649656</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3059</th>\n <td>[400, 136]</td>\n <td>1.649393</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3060</th>\n <td>[308, 225, 593, 572, 219, 116]</td>\n <td>1.649252</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3061</th>\n <td>[308, 225, 572, 219, 239, 102, 136]</td>\n <td>1.649141</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3062</th>\n <td>[219, 217, 136, 167]</td>\n <td>1.649113</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3063</th>\n <td>[308, 225, 572, 219, 217, 239, 136, 167]</td>\n <td>1.649062</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3064</th>\n <td>[308, 225, 400, 593, 217, 239]</td>\n <td>1.648869</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3065</th>\n <td>[572, 217, 239, 102, 167]</td>\n <td>1.648707</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3066</th>\n <td>[308, 225, 593, 219, 217, 167]</td>\n <td>1.648633</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3067</th>\n <td>[219, 239, 102, 116, 167]</td>\n <td>1.648342</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3068</th>\n <td>[400, 593, 572, 219, 217, 239, 102]</td>\n <td>1.647977</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3069</th>\n <td>[308, 225, 400, 217]</td>\n <td>1.647962</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3070</th>\n <td>[308, 572, 239, 102, 136]</td>\n <td>1.647705</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3071</th>\n <td>[400, 593, 572, 239, 116]</td>\n <td>1.647624</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3072</th>\n <td>[308, 593, 219, 239, 136, 167]</td>\n <td>1.647591</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3073</th>\n <td>[225, 593, 572, 219, 217, 116]</td>\n <td>1.647393</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3074</th>\n <td>[308, 400, 593, 572, 219, 217, 239, 167]</td>\n <td>1.647051</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>3075</th>\n <td>[593, 572, 167]</td>\n <td>1.646795</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3076</th>\n <td>[308, 225, 400, 572, 239, 136]</td>\n <td>1.646646</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3077</th>\n <td>[308, 225, 400, 593, 219, 239, 116]</td>\n <td>1.646585</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3078</th>\n <td>[400, 593, 239, 102]</td>\n <td>1.646484</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3079</th>\n <td>[225, 217, 102]</td>\n <td>1.646078</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3080</th>\n <td>[308, 593, 217, 239, 167]</td>\n <td>1.645698</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3081</th>\n <td>[225, 593, 217, 239, 116]</td>\n <td>1.645680</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3082</th>\n <td>[308, 225, 400, 239, 102]</td>\n <td>1.645636</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3083</th>\n <td>[308, 225, 593, 572, 239, 116]</td>\n <td>1.645626</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3084</th>\n <td>[308, 225, 400, 572, 219, 167]</td>\n <td>1.645618</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3085</th>\n <td>[400, 572, 219, 217, 239, 116, 167]</td>\n <td>1.645557</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3086</th>\n <td>[400, 593, 239, 116]</td>\n <td>1.645501</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3087</th>\n <td>[225, 400, 572, 219, 136]</td>\n <td>1.645321</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3088</th>\n <td>[308, 400, 572, 219, 136]</td>\n <td>1.645077</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3089</th>\n <td>[225, 400, 593, 572, 219, 217, 239, 116]</td>\n <td>1.644860</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>3090</th>\n <td>[572, 219, 116, 136]</td>\n <td>1.644733</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3091</th>\n <td>[572, 217, 239, 136, 167]</td>\n <td>1.644706</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3092</th>\n <td>[225, 572, 219, 217, 239, 102, 136]</td>\n <td>1.644299</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3093</th>\n <td>[225, 400, 572, 219, 217, 167]</td>\n <td>1.644179</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3094</th>\n <td>[308, 400, 593, 572, 219, 239, 102]</td>\n <td>1.643993</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3095</th>\n <td>[308, 116, 167]</td>\n <td>1.643963</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3096</th>\n <td>[308, 225, 593, 239, 116]</td>\n <td>1.643588</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3097</th>\n <td>[225, 400, 572, 217, 239, 136]</td>\n <td>1.642860</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3098</th>\n <td>[308, 225, 400, 593, 219, 217]</td>\n <td>1.642259</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3099</th>\n <td>[308, 593, 572, 219, 102]</td>\n <td>1.642222</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3100</th>\n <td>[225, 593, 572, 219, 239, 136, 167]</td>\n <td>1.642145</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3101</th>\n <td>[400, 219, 239, 102, 136]</td>\n <td>1.642054</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3102</th>\n <td>[225, 400, 219, 239, 102, 167]</td>\n <td>1.642027</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3103</th>\n <td>[225, 400, 217, 239, 102]</td>\n <td>1.641727</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3104</th>\n <td>[308, 400, 572, 219, 239, 116, 167]</td>\n <td>1.641098</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3105</th>\n <td>[217, 239, 102, 136]</td>\n <td>1.640917</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3106</th>\n <td>[225, 400, 572, 219, 239, 136, 167]</td>\n <td>1.640816</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3107</th>\n <td>[400, 239, 116, 167]</td>\n <td>1.640782</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3108</th>\n <td>[308, 225, 400, 239, 136]</td>\n <td>1.640599</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3109</th>\n <td>[225, 219, 136, 167]</td>\n <td>1.640330</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3110</th>\n <td>[225, 593, 219, 217, 136]</td>\n <td>1.639999</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3111</th>\n <td>[593, 219, 239, 102, 136]</td>\n <td>1.639643</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3112</th>\n <td>[593, 572, 219, 217, 136]</td>\n <td>1.639337</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3113</th>\n <td>[308, 572, 217, 116]</td>\n <td>1.639285</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3114</th>\n <td>[308, 593, 572, 219, 239, 116, 167]</td>\n <td>1.639278</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3115</th>\n <td>[308, 219, 217, 239, 102, 116]</td>\n <td>1.638740</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3116</th>\n <td>[308, 400, 593, 219, 217, 239, 167]</td>\n <td>1.638509</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3117</th>\n <td>[400, 239, 136, 167]</td>\n <td>1.638331</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3118</th>\n <td>[593, 572, 217, 239, 102]</td>\n <td>1.638045</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3119</th>\n <td>[308, 572, 219, 217, 239, 116, 136]</td>\n <td>1.637731</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3120</th>\n <td>[225, 400, 593, 219, 217, 239, 116]</td>\n <td>1.637303</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3121</th>\n <td>[400, 593, 572, 219, 217, 239, 136]</td>\n <td>1.637261</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3122</th>\n <td>[400, 219, 217, 239, 116, 167]</td>\n <td>1.637245</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3123</th>\n <td>[308, 400, 219, 217, 167]</td>\n <td>1.637080</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3124</th>\n <td>[219, 239, 116, 136, 167]</td>\n <td>1.636932</td>\n <td>3</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3125</th>\n <td>[308, 225, 219, 217, 239, 136, 167]</td>\n <td>1.636891</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3126</th>\n <td>[308, 225, 572, 136]</td>\n <td>1.636661</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3127</th>\n <td>[308, 400, 593, 572, 219, 239, 136]</td>\n <td>1.636460</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3128</th>\n <td>[593, 572, 217, 239, 136]</td>\n <td>1.636158</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3129</th>\n <td>[217, 239, 116, 136]</td>\n <td>1.636119</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3130</th>\n <td>[308, 400, 572, 217, 239, 167]</td>\n <td>1.635742</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3131</th>\n <td>[400, 593, 219, 217, 239, 102]</td>\n <td>1.635639</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3132</th>\n <td>[308, 225, 400, 219, 167]</td>\n <td>1.635517</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3133</th>\n <td>[308, 225, 219, 239, 102, 136]</td>\n <td>1.635354</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3134</th>\n <td>[593, 219, 217, 239, 116, 167]</td>\n <td>1.635221</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3135</th>\n <td>[308, 400, 219, 239, 116, 167]</td>\n <td>1.634960</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3136</th>\n <td>[217, 239, 102, 116]</td>\n <td>1.634729</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3137</th>\n <td>[400, 219, 217, 136]</td>\n <td>1.634578</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3138</th>\n <td>[308, 225, 400, 572, 219, 217, 239, 102]</td>\n <td>1.634523</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>3139</th>\n <td>[308, 400, 593, 219, 239, 102]</td>\n <td>1.634331</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3140</th>\n <td>[225, 593, 219, 239, 102, 167]</td>\n <td>1.634248</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3141</th>\n <td>[400, 593, 572]</td>\n <td>1.633889</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3142</th>\n <td>[308, 572, 219, 217, 239, 102, 167]</td>\n <td>1.633881</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3143</th>\n <td>[308, 225, 572, 219, 217, 102]</td>\n <td>1.633694</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3144</th>\n <td>[308, 217, 102]</td>\n <td>1.633403</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3145</th>\n <td>[308, 225, 400, 593, 572, 219, 239, 167]</td>\n <td>1.632966</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>3146</th>\n <td>[593, 572, 219, 239, 102, 116]</td>\n <td>1.632798</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3147</th>\n <td>[308, 225, 593, 219, 116]</td>\n <td>1.632497</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3148</th>\n <td>[308, 225, 400, 572, 239, 116]</td>\n <td>1.632452</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3149</th>\n <td>[400, 239, 102, 167]</td>\n <td>1.632083</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3150</th>\n <td>[308, 225, 593, 572, 219, 217, 239, 102]</td>\n <td>1.631887</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>3151</th>\n <td>[308, 593, 572, 219, 217, 167]</td>\n <td>1.631859</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3152</th>\n <td>[308, 572, 219, 116, 167]</td>\n <td>1.631817</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3153</th>\n <td>[400, 572, 167]</td>\n <td>1.631735</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3154</th>\n <td>[225, 219, 116, 167]</td>\n <td>1.631697</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3155</th>\n <td>[308, 225, 400, 239, 116]</td>\n <td>1.631462</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3156</th>\n <td>[225, 400, 217, 239, 136]</td>\n <td>1.631379</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3157</th>\n <td>[400, 572, 219, 239, 102, 116]</td>\n <td>1.631139</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3158</th>\n <td>[225, 400, 219, 136]</td>\n <td>1.631059</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3159</th>\n <td>[308, 225, 572, 219, 217, 239, 116, 167]</td>\n <td>1.630839</td>\n <td>2</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3160</th>\n <td>[593, 219, 217, 102]</td>\n <td>1.630741</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3161</th>\n <td>[400, 572, 219, 217, 116]</td>\n <td>1.630738</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3162</th>\n <td>[308, 593, 219, 217, 116]</td>\n <td>1.630580</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3163</th>\n <td>[219, 217, 116, 167]</td>\n <td>1.630196</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3164</th>\n <td>[225, 400, 219, 239, 136, 167]</td>\n <td>1.629740</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3165</th>\n <td>[308, 225, 593, 217]</td>\n <td>1.629685</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3166</th>\n <td>[225, 400, 219, 217, 167]</td>\n <td>1.629406</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3167</th>\n <td>[308, 400, 219, 136]</td>\n <td>1.629400</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3168</th>\n <td>[225, 400, 572, 217, 239, 116]</td>\n <td>1.629023</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3169</th>\n <td>[308, 400, 217, 239, 167]</td>\n <td>1.628383</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3170</th>\n <td>[572, 217, 239, 116, 167]</td>\n <td>1.627734</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3171</th>\n <td>[225, 400, 593, 572, 219, 217, 239, 167]</td>\n <td>1.627646</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>3172</th>\n <td>[225, 217, 116]</td>\n <td>1.627412</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3173</th>\n <td>[308, 593, 219, 239, 116, 167]</td>\n <td>1.627038</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3174</th>\n <td>[308, 225, 572, 116]</td>\n <td>1.626938</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3175</th>\n <td>[225, 593, 572, 217, 239, 167]</td>\n <td>1.626886</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3176</th>\n <td>[572, 217, 102]</td>\n <td>1.626875</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3177</th>\n <td>[225, 593, 572, 219, 136]</td>\n <td>1.626785</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3178</th>\n <td>[308, 102, 167]</td>\n <td>1.626656</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3179</th>\n <td>[308, 400, 593, 219, 239, 136]</td>\n <td>1.626624</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3180</th>\n <td>[593, 239, 102, 167]</td>\n <td>1.626371</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3181</th>\n <td>[308, 225, 400, 219, 217, 239, 102]</td>\n <td>1.626309</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3182</th>\n <td>[308, 225, 572, 219, 239, 102, 116]</td>\n <td>1.626072</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3183</th>\n <td>[225, 400, 593, 572, 219, 239, 102]</td>\n <td>1.626014</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3184</th>\n <td>[308, 572, 239, 116, 136]</td>\n <td>1.625719</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3185</th>\n <td>[308, 225, 400, 593, 219, 239, 167]</td>\n <td>1.625379</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3186</th>\n <td>[308, 219, 217, 239, 116, 136]</td>\n <td>1.625276</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3187</th>\n <td>[308, 225, 593, 572, 219, 167]</td>\n <td>1.625171</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3188</th>\n <td>[225, 593, 572, 219, 217, 167]</td>\n <td>1.625104</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3189</th>\n <td>[400, 593]</td>\n <td>1.625097</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3190</th>\n <td>[225, 400, 572, 219, 116]</td>\n <td>1.625066</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3191</th>\n <td>[400, 593, 219, 217, 239, 136]</td>\n <td>1.624227</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3192</th>\n <td>[225, 400, 217, 239, 116]</td>\n <td>1.624108</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3193</th>\n <td>[308, 225, 400, 572, 219, 217, 239, 136]</td>\n <td>1.623985</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>3194</th>\n <td>[225, 593, 219, 102]</td>\n <td>1.623939</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3195</th>\n <td>[225, 219, 217, 239, 102, 136]</td>\n <td>1.623875</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3196</th>\n <td>[593, 572, 219, 239, 116, 136]</td>\n <td>1.623811</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3197</th>\n <td>[225, 572, 217, 167]</td>\n <td>1.623579</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3198</th>\n <td>[308, 593, 167]</td>\n <td>1.623575</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3199</th>\n <td>[225, 400, 572, 219, 239, 116, 167]</td>\n <td>1.623477</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3200</th>\n <td>[225, 593, 219, 217, 116]</td>\n <td>1.623244</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3201</th>\n <td>[308, 572, 239, 102, 116]</td>\n <td>1.622771</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3202</th>\n <td>[308, 400, 572, 219, 116]</td>\n <td>1.622759</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3203</th>\n <td>[225, 593, 219, 239, 136, 167]</td>\n <td>1.622622</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3204</th>\n <td>[308, 593, 572, 219, 136]</td>\n <td>1.622265</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3205</th>\n <td>[308, 219, 136, 167]</td>\n <td>1.621587</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3206</th>\n <td>[308, 400, 593, 572, 219, 217]</td>\n <td>1.621378</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3207</th>\n <td>[308, 572, 219, 217, 239, 136, 167]</td>\n <td>1.621322</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3208</th>\n <td>[308, 225, 219, 217, 239, 116, 167]</td>\n <td>1.621196</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3209</th>\n <td>[225, 593, 572, 219, 239, 116, 167]</td>\n <td>1.621063</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3210</th>\n <td>[308, 225, 593, 572, 219, 217, 239, 136]</td>\n <td>1.621021</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>3211</th>\n <td>[400, 572, 219, 239, 116, 136]</td>\n <td>1.620523</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3212</th>\n <td>[225, 572, 219, 217, 239, 102, 116]</td>\n <td>1.620165</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3213</th>\n <td>[400, 572, 219, 102]</td>\n <td>1.619520</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3214</th>\n <td>[400, 219, 239, 102, 116]</td>\n <td>1.619386</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3215</th>\n <td>[308, 225, 593, 572, 239, 167]</td>\n <td>1.619061</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3216</th>\n <td>[308, 225, 593, 219, 217, 239, 102]</td>\n <td>1.618847</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3217</th>\n <td>[308, 400, 593, 572, 217, 239]</td>\n <td>1.618408</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3218</th>\n <td>[308, 219, 217, 239, 102, 167]</td>\n <td>1.618291</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3219</th>\n <td>[572, 219, 217, 239, 102, 136]</td>\n <td>1.617873</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3220</th>\n <td>[308, 225, 102]</td>\n <td>1.617447</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3221</th>\n <td>[308, 400, 593, 572, 219, 239, 116]</td>\n <td>1.617366</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3222</th>\n <td>[308, 225, 400, 593, 572, 219]</td>\n <td>1.617187</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3223</th>\n <td>[400, 593, 572, 219, 217, 239, 116]</td>\n <td>1.617159</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3224</th>\n <td>[225, 400, 219, 116]</td>\n <td>1.616813</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3225</th>\n <td>[225, 400, 593, 219, 217, 239, 167]</td>\n <td>1.616798</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3226</th>\n <td>[217, 239, 116, 167]</td>\n <td>1.616456</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3227</th>\n <td>[225, 400, 593, 572, 219, 239, 136]</td>\n <td>1.616243</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3228</th>\n <td>[225, 400, 219, 239, 116, 167]</td>\n <td>1.615961</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3229</th>\n <td>[400, 219, 217, 116]</td>\n <td>1.615607</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3230</th>\n <td>[308, 225, 219, 239, 102, 116]</td>\n <td>1.615229</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3231</th>\n <td>[308, 225, 400, 219, 217, 239, 136]</td>\n <td>1.615025</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3232</th>\n <td>[308, 225, 572, 219, 239, 116, 136]</td>\n <td>1.614739</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3233</th>\n <td>[572, 219, 136, 167]</td>\n <td>1.614576</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3234</th>\n <td>[400, 593, 572, 239, 167]</td>\n <td>1.614287</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3235</th>\n <td>[225, 400, 593, 219, 239, 102]</td>\n <td>1.614146</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3236</th>\n <td>[593, 217, 239, 136]</td>\n <td>1.613179</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3237</th>\n <td>[593, 572, 217, 239, 116]</td>\n <td>1.613048</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3238</th>\n <td>[225, 593, 217, 239, 167]</td>\n <td>1.612555</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3239</th>\n <td>[308, 225, 219, 217, 102]</td>\n <td>1.611533</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3240</th>\n <td>[308, 572, 217, 167]</td>\n <td>1.611280</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3241</th>\n <td>[225, 400, 593, 572, 219, 217]</td>\n <td>1.611023</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3242</th>\n <td>[308, 400, 219, 116]</td>\n <td>1.611006</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3243</th>\n <td>[308, 225, 572, 219, 217, 136]</td>\n <td>1.610786</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3244</th>\n <td>[308, 400, 593, 217, 239]</td>\n <td>1.610672</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3245</th>\n <td>[593, 219, 239, 102, 116]</td>\n <td>1.610510</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3246</th>\n <td>[593, 217, 239, 102]</td>\n <td>1.610354</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3247</th>\n <td>[308, 136, 167]</td>\n <td>1.610103</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3248</th>\n <td>[593, 572, 219, 217, 116]</td>\n <td>1.609479</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3249</th>\n <td>[308, 400, 593, 219, 239, 116]</td>\n <td>1.609395</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3250</th>\n <td>[308, 593, 219, 102]</td>\n <td>1.609298</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3251</th>\n <td>[400, 572, 219, 239, 102, 167]</td>\n <td>1.608881</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3252</th>\n <td>[308, 225, 400, 572, 219, 217, 239, 116]</td>\n <td>1.608842</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>3253</th>\n <td>[308, 225, 400, 572, 239, 167]</td>\n <td>1.608838</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3254</th>\n <td>[593, 572, 219, 239, 102, 167]</td>\n <td>1.608720</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3255</th>\n <td>[308, 225, 593, 239, 167]</td>\n <td>1.608387</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3256</th>\n <td>[400, 219, 239, 116, 136]</td>\n <td>1.608324</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3257</th>\n <td>[308, 572, 219, 239, 102, 136]</td>\n <td>1.608219</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3258</th>\n <td>[308, 225, 572, 217, 239, 102]</td>\n <td>1.608153</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3259</th>\n <td>[217, 239, 136, 167]</td>\n <td>1.608067</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3260</th>\n <td>[308, 225, 572, 219, 239, 102, 167]</td>\n <td>1.607530</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3261</th>\n <td>[308, 225, 593, 219, 217, 239, 136]</td>\n <td>1.607223</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3262</th>\n <td>[217, 239, 102, 167]</td>\n <td>1.607204</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3263</th>\n <td>[308, 225, 116]</td>\n <td>1.606914</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3264</th>\n <td>[225, 400, 572, 217, 239, 167]</td>\n <td>1.606866</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3265</th>\n <td>[225, 593, 219, 239, 116, 167]</td>\n <td>1.606716</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3266</th>\n <td>[400, 572, 219, 217, 167]</td>\n <td>1.606467</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3267</th>\n <td>[400, 593, 219, 217, 239, 116]</td>\n <td>1.606449</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3268</th>\n <td>[308, 400, 593, 219, 217]</td>\n <td>1.605983</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3269</th>\n <td>[308, 400, 572, 219, 217, 239, 102]</td>\n <td>1.605819</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3270</th>\n <td>[593, 217, 239, 116]</td>\n <td>1.605413</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3271</th>\n <td>[308, 225, 400, 593, 219]</td>\n <td>1.605157</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3272</th>\n <td>[400, 572, 217, 239, 102]</td>\n <td>1.604891</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3273</th>\n <td>[308, 219, 217, 239, 136, 167]</td>\n <td>1.604732</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3274</th>\n <td>[308, 400, 572, 217]</td>\n <td>1.604231</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3275</th>\n <td>[308, 217, 116]</td>\n <td>1.604065</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3276</th>\n <td>[308, 593, 219, 217, 167]</td>\n <td>1.604007</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3277</th>\n <td>[225, 572, 219, 217, 239, 116, 136]</td>\n <td>1.603982</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3278</th>\n <td>[225, 400, 593, 219, 239, 136]</td>\n <td>1.603854</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3279</th>\n <td>[225, 572, 219, 217, 239, 102, 167]</td>\n <td>1.603668</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3280</th>\n <td>[225, 219, 217, 239, 102, 116]</td>\n <td>1.603640</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3281</th>\n <td>[308, 593, 572, 239, 136]</td>\n <td>1.603383</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3282</th>\n <td>[308, 225, 593, 572, 219, 217, 239, 116]</td>\n <td>1.603376</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>3283</th>\n <td>[308, 225, 219, 239, 116, 136]</td>\n <td>1.603147</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3284</th>\n <td>[308, 593, 572, 219, 217, 239, 102]</td>\n <td>1.603050</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3285</th>\n <td>[308, 219, 116, 167]</td>\n <td>1.602995</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3286</th>\n <td>[308, 217, 136]</td>\n <td>1.602910</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3287</th>\n <td>[225, 593, 572, 219, 116]</td>\n <td>1.602432</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3288</th>\n <td>[308, 239, 102, 136]</td>\n <td>1.602357</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3289</th>\n <td>[308, 225, 593, 219, 167]</td>\n <td>1.602107</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3290</th>\n <td>[593, 219, 239, 116, 136]</td>\n <td>1.601998</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3291</th>\n <td>[239, 116, 136, 167]</td>\n <td>1.601875</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3292</th>\n <td>[400, 167]</td>\n <td>1.601789</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3293</th>\n <td>[308, 225, 400, 239, 167]</td>\n <td>1.601610</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3294</th>\n <td>[219, 102, 167]</td>\n <td>1.601502</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3295</th>\n <td>[308, 225, 400, 219, 217, 239, 116]</td>\n <td>1.601438</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3296</th>\n <td>[308, 572, 239, 136, 167]</td>\n <td>1.600643</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3297</th>\n <td>[308, 239, 116, 136]</td>\n <td>1.600619</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3298</th>\n <td>[308, 593, 572, 239, 102]</td>\n <td>1.600224</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3299</th>\n <td>[400, 593, 239, 167]</td>\n <td>1.599682</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3300</th>\n <td>[308, 572, 219, 217, 239, 116, 167]</td>\n <td>1.599540</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3301</th>\n <td>[593, 572, 219, 239, 136, 167]</td>\n <td>1.599487</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3302</th>\n <td>[225, 400, 593, 572, 219, 239, 116]</td>\n <td>1.598946</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3303</th>\n <td>[400, 219, 102]</td>\n <td>1.598313</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3304</th>\n <td>[572, 116, 167]</td>\n <td>1.598259</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3305</th>\n <td>[308, 225, 572, 217, 239, 136]</td>\n <td>1.598256</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3306</th>\n <td>[225, 593, 572, 217]</td>\n <td>1.598193</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3307</th>\n <td>[308, 572, 239, 102, 167]</td>\n <td>1.598138</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3308</th>\n <td>[400, 572, 219, 239, 136, 167]</td>\n <td>1.598129</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3309</th>\n <td>[593, 572, 219, 102]</td>\n <td>1.597868</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3310</th>\n <td>[400, 593, 572, 219, 217, 239, 167]</td>\n <td>1.597801</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3311</th>\n <td>[225, 400, 572, 219, 167]</td>\n <td>1.597384</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3312</th>\n <td>[308, 400, 572, 219, 167]</td>\n <td>1.597363</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3313</th>\n <td>[308, 400, 593, 572, 219, 239, 167]</td>\n <td>1.597304</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3314</th>\n <td>[225, 400, 572, 217]</td>\n <td>1.597070</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3315</th>\n <td>[400, 572, 217, 239, 136]</td>\n <td>1.596880</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3316</th>\n <td>[308, 225, 400, 593, 572, 239]</td>\n <td>1.596327</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3317</th>\n <td>[308, 225, 572, 219, 239, 136, 167]</td>\n <td>1.596109</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3318</th>\n <td>[308, 593, 572, 219, 116]</td>\n <td>1.595548</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3319</th>\n <td>[225, 400, 217, 239, 167]</td>\n <td>1.595540</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3320</th>\n <td>[308, 400, 572, 219, 217, 239, 136]</td>\n <td>1.595282</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3321</th>\n <td>[593, 219, 217, 136]</td>\n <td>1.595276</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3322</th>\n <td>[219, 116, 136]</td>\n <td>1.595036</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3323</th>\n <td>[308, 225, 400, 572]</td>\n <td>1.594500</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3324</th>\n <td>[225, 593, 219, 217, 167]</td>\n <td>1.594478</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3325</th>\n <td>[308, 400, 219, 217, 239, 102]</td>\n <td>1.594330</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3326</th>\n <td>[225, 400, 593, 219, 217]</td>\n <td>1.594067</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3327</th>\n <td>[308, 593, 572, 217]</td>\n <td>1.593501</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3328</th>\n <td>[308, 225, 400, 572, 219, 217, 239, 167]</td>\n <td>1.593291</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>3329</th>\n <td>[400, 572, 219, 136]</td>\n <td>1.593069</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3330</th>\n <td>[308, 572, 219, 217, 102]</td>\n <td>1.592995</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3331</th>\n <td>[308, 593, 572, 219, 217, 239, 136]</td>\n <td>1.592403</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3332</th>\n <td>[308, 225, 219, 239, 102, 167]</td>\n <td>1.592072</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3333</th>\n <td>[225, 217, 136]</td>\n <td>1.592023</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3334</th>\n <td>[308, 239, 102, 116]</td>\n <td>1.591831</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3335</th>\n <td>[308, 225, 572, 167]</td>\n <td>1.591702</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3336</th>\n <td>[308, 225, 217, 239, 102]</td>\n <td>1.591675</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3337</th>\n <td>[308, 225, 136]</td>\n <td>1.591656</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3338</th>\n <td>[308, 225, 593, 219, 217, 239, 116]</td>\n <td>1.591594</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3339</th>\n <td>[308, 400, 572, 239, 102]</td>\n <td>1.591578</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3340</th>\n <td>[308, 225, 572, 219, 217, 116]</td>\n <td>1.591351</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3341</th>\n <td>[225, 400, 593, 572, 217, 239]</td>\n <td>1.591290</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3342</th>\n <td>[400, 219, 239, 102, 167]</td>\n <td>1.590940</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3343</th>\n <td>[219, 217, 239, 102, 136]</td>\n <td>1.590841</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3344</th>\n <td>[225, 593, 219, 136]</td>\n <td>1.590705</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3345</th>\n <td>[225, 572, 239, 102, 136]</td>\n <td>1.589859</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3346</th>\n <td>[225, 400, 593, 219, 239, 116]</td>\n <td>1.589287</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3347</th>\n <td>[308, 225, 400, 593, 239]</td>\n <td>1.589281</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3348</th>\n <td>[308, 225, 400, 572, 219, 239, 102]</td>\n <td>1.588380</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3349</th>\n <td>[308, 400, 572, 239, 136]</td>\n <td>1.588329</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3350</th>\n <td>[225, 572, 219, 217, 239, 136, 167]</td>\n <td>1.587400</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3351</th>\n <td>[572, 219, 217, 239, 102, 116]</td>\n <td>1.586934</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3352</th>\n <td>[308, 225, 593, 572, 219, 217, 239, 167]</td>\n <td>1.586838</td>\n <td>1</td>\n <td>7</td>\n </tr>\n <tr>\n <th>3353</th>\n <td>[308, 593, 219, 136]</td>\n <td>1.586751</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3354</th>\n <td>[308, 400, 217]</td>\n <td>1.586480</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3355</th>\n <td>[308, 219, 239, 102, 136]</td>\n <td>1.586311</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3356</th>\n <td>[308, 219, 217, 239, 116, 167]</td>\n <td>1.585848</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3357</th>\n <td>[225, 219, 217, 239, 116, 136]</td>\n <td>1.585678</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3358</th>\n <td>[308, 593, 219, 217, 239, 102]</td>\n <td>1.585584</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3359</th>\n <td>[308, 225, 219, 217, 136]</td>\n <td>1.585534</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3360</th>\n <td>[308, 400, 593, 219, 239, 167]</td>\n <td>1.585357</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3361</th>\n <td>[400, 593, 572, 219, 239, 102]</td>\n <td>1.584796</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3362</th>\n <td>[400, 219, 217, 167]</td>\n <td>1.584291</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3363</th>\n <td>[308, 572, 239, 116, 167]</td>\n <td>1.584277</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3364</th>\n <td>[593, 572, 217, 239, 167]</td>\n <td>1.584013</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3365</th>\n <td>[400, 217, 239, 102]</td>\n <td>1.583940</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3366</th>\n <td>[308, 225, 400]</td>\n <td>1.583738</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3367</th>\n <td>[308, 225, 400, 219, 217, 239, 167]</td>\n <td>1.583219</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3368</th>\n <td>[593, 572, 219, 217, 167]</td>\n <td>1.583214</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3369</th>\n <td>[308, 400, 219, 217, 239, 136]</td>\n <td>1.583053</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3370</th>\n <td>[400, 593, 219, 217, 239, 167]</td>\n <td>1.582965</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3371</th>\n <td>[308, 225, 572, 217, 239, 116]</td>\n <td>1.582863</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3372</th>\n <td>[572, 219, 116, 167]</td>\n <td>1.582799</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3373</th>\n <td>[225, 219, 217, 239, 102, 167]</td>\n <td>1.582592</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3374</th>\n <td>[308, 593, 572, 239, 116]</td>\n <td>1.582493</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3375</th>\n <td>[308, 225, 572, 219, 102]</td>\n <td>1.582187</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3376</th>\n <td>[308, 225, 217, 239, 136]</td>\n <td>1.581609</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3377</th>\n <td>[308, 225, 593, 572, 219, 239, 102]</td>\n <td>1.581378</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3378</th>\n <td>[308, 225, 593, 572]</td>\n <td>1.581242</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3379</th>\n <td>[225, 400, 219, 167]</td>\n <td>1.580825</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3380</th>\n <td>[225, 400, 217]</td>\n <td>1.580671</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3381</th>\n <td>[400, 572, 217, 239, 116]</td>\n <td>1.580383</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3382</th>\n <td>[308, 572, 219, 239, 102, 116]</td>\n <td>1.580333</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3383</th>\n <td>[225, 400, 593, 217, 239]</td>\n <td>1.580135</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3384</th>\n <td>[225, 217, 167]</td>\n <td>1.579880</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3385</th>\n <td>[308, 225, 219, 239, 136, 167]</td>\n <td>1.579878</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3386</th>\n <td>[400, 219, 239, 136, 167]</td>\n <td>1.579682</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3387</th>\n <td>[308, 593, 239, 136]</td>\n <td>1.579672</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3388</th>\n <td>[225, 572, 219, 217, 102]</td>\n <td>1.579398</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3389</th>\n <td>[308, 400, 219, 167]</td>\n <td>1.578997</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3390</th>\n <td>[225, 400, 572, 219, 217, 239, 102]</td>\n <td>1.578995</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3391</th>\n <td>[308, 225, 400, 572, 219, 239, 136]</td>\n <td>1.578576</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3392</th>\n <td>[593, 219, 239, 102, 167]</td>\n <td>1.578194</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3393</th>\n <td>[308, 400, 572, 219, 217, 239, 116]</td>\n <td>1.577917</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3394</th>\n <td>[225, 400, 593, 572, 219, 239, 167]</td>\n <td>1.577829</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3395</th>\n <td>[308, 225, 572, 219, 239, 116, 167]</td>\n <td>1.577786</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3396</th>\n <td>[572, 217, 136]</td>\n <td>1.577744</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3397</th>\n <td>[400, 572, 219, 239, 116, 167]</td>\n <td>1.577698</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3398</th>\n <td>[308, 225, 400, 219, 239, 102]</td>\n <td>1.577535</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3399</th>\n <td>[225, 572, 239, 102, 116]</td>\n <td>1.577166</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3400</th>\n <td>[400, 217, 239, 136]</td>\n <td>1.576633</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3401</th>\n <td>[225, 593, 219, 116]</td>\n <td>1.576183</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3402</th>\n <td>[400, 593, 572, 219, 239, 136]</td>\n <td>1.575817</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3403</th>\n <td>[225, 572, 239, 116, 136]</td>\n <td>1.575729</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3404</th>\n <td>[572, 217, 116]</td>\n <td>1.575679</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3405</th>\n <td>[572, 102, 116]</td>\n <td>1.575160</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3406</th>\n <td>[308, 593, 219, 217, 239, 136]</td>\n <td>1.574255</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3407</th>\n <td>[593, 219, 217, 116]</td>\n <td>1.573797</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3408</th>\n <td>[308, 400, 239, 102]</td>\n <td>1.573513</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3409</th>\n <td>[593, 572, 219, 239, 116, 167]</td>\n <td>1.573300</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3410</th>\n <td>[225, 572, 219, 239, 102, 136]</td>\n <td>1.573278</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3411</th>\n <td>[308, 225, 400, 593, 572, 219, 217, 239]</td>\n <td>1.573273</td>\n <td>0</td>\n <td>8</td>\n </tr>\n <tr>\n <th>3412</th>\n <td>[225, 593, 572, 219, 217, 239, 102]</td>\n <td>1.572985</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3413</th>\n <td>[400, 593, 572, 219, 217]</td>\n <td>1.572788</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3414</th>\n <td>[308, 225, 217, 239, 116]</td>\n <td>1.572627</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3415</th>\n <td>[308, 400, 572, 239, 116]</td>\n <td>1.572300</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3416</th>\n <td>[308, 400, 239, 136]</td>\n <td>1.571877</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3417</th>\n <td>[308, 225, 593, 219, 217, 239, 167]</td>\n <td>1.571876</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3418</th>\n <td>[308, 225, 572, 219, 217, 167]</td>\n <td>1.571766</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3419</th>\n <td>[308, 225, 593, 572, 219, 239, 136]</td>\n <td>1.571679</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3420</th>\n <td>[308, 593, 239, 102]</td>\n <td>1.571611</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3421</th>\n <td>[308, 593, 572, 219, 217, 239, 116]</td>\n <td>1.571575</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3422</th>\n <td>[225, 593, 572, 219, 167]</td>\n <td>1.571398</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3423</th>\n <td>[308, 400, 593, 572, 219]</td>\n <td>1.571301</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3424</th>\n <td>[572, 219, 217, 239, 116, 136]</td>\n <td>1.570528</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3425</th>\n <td>[308, 225, 219, 217, 116]</td>\n <td>1.570274</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3426</th>\n <td>[308, 572, 219, 239, 116, 136]</td>\n <td>1.569849</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3427</th>\n <td>[593, 219, 239, 136, 167]</td>\n <td>1.569268</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3428</th>\n <td>[308, 593, 239, 116]</td>\n <td>1.569236</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3429</th>\n <td>[239, 102, 116, 167]</td>\n <td>1.569142</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3430</th>\n <td>[400, 217, 239, 116]</td>\n <td>1.568826</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3431</th>\n <td>[225, 572, 219, 217, 239, 116, 167]</td>\n <td>1.568694</td>\n <td>2</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3432</th>\n <td>[572, 219, 217, 239, 102, 167]</td>\n <td>1.568325</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3433</th>\n <td>[400, 572, 219, 116]</td>\n <td>1.568237</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3434</th>\n <td>[308, 572, 219, 217, 136]</td>\n <td>1.567882</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3435</th>\n <td>[308, 593, 572, 219, 167]</td>\n <td>1.567486</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3436</th>\n <td>[308, 400, 219, 217, 239, 116]</td>\n <td>1.567411</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3437</th>\n <td>[308, 225, 400, 219, 239, 136]</td>\n <td>1.567111</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3438</th>\n <td>[593, 572, 219, 136]</td>\n <td>1.567030</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3439</th>\n <td>[400, 219, 136]</td>\n <td>1.566916</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3440</th>\n <td>[308, 225, 400, 572, 219, 217]</td>\n <td>1.566893</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3441</th>\n <td>[400, 593, 219, 239, 102]</td>\n <td>1.566289</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3442</th>\n <td>[308, 593, 219, 116]</td>\n <td>1.566187</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3443</th>\n <td>[225, 400, 572, 219, 217, 239, 136]</td>\n <td>1.566087</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3444</th>\n <td>[225, 400, 593, 572, 219]</td>\n <td>1.565927</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3445</th>\n <td>[225, 593, 572, 239, 136]</td>\n <td>1.565566</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3446</th>\n <td>[225, 593, 572, 239, 102]</td>\n <td>1.565474</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3447</th>\n <td>[308, 225, 219, 239, 116, 167]</td>\n <td>1.565003</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3448</th>\n <td>[225, 219, 217, 239, 136, 167]</td>\n <td>1.564552</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3449</th>\n <td>[308, 225, 593, 219, 239, 102]</td>\n <td>1.564463</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3450</th>\n <td>[219, 217, 239, 102, 116]</td>\n <td>1.564421</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3451</th>\n <td>[308, 239, 136, 167]</td>\n <td>1.564179</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3452</th>\n <td>[225, 400, 219, 217, 239, 102]</td>\n <td>1.563858</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3453</th>\n <td>[308, 239, 116, 167]</td>\n <td>1.563849</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3454</th>\n <td>[225, 400, 593, 219, 239, 167]</td>\n <td>1.563651</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3455</th>\n <td>[400, 219, 239, 116, 167]</td>\n <td>1.563582</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3456</th>\n <td>[225, 593, 217]</td>\n <td>1.563419</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3457</th>\n <td>[308, 225, 400, 572, 219, 239, 116]</td>\n <td>1.563320</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3458</th>\n <td>[308, 217, 167]</td>\n <td>1.562668</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3459</th>\n <td>[593, 217, 239, 167]</td>\n <td>1.562623</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3460</th>\n <td>[308, 400, 239, 116]</td>\n <td>1.562313</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3461</th>\n <td>[308, 225, 400, 593, 219, 217, 239]</td>\n <td>1.562135</td>\n <td>0</td>\n <td>7</td>\n </tr>\n <tr>\n <th>3462</th>\n <td>[308, 225, 572, 217, 239, 167]</td>\n <td>1.561856</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3463</th>\n <td>[308, 219, 239, 102, 116]</td>\n <td>1.561842</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3464</th>\n <td>[308, 400, 572, 219, 217, 239, 167]</td>\n <td>1.560670</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3465</th>\n <td>[308, 219, 217, 102]</td>\n <td>1.560600</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3466</th>\n <td>[225, 593, 572, 219, 217, 239, 136]</td>\n <td>1.559375</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3467</th>\n <td>[308, 572, 219, 239, 102, 167]</td>\n <td>1.559262</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3468</th>\n <td>[225, 572, 102]</td>\n <td>1.559188</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3469</th>\n <td>[308, 225, 572, 219, 136]</td>\n <td>1.558363</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3470</th>\n <td>[239, 102, 116, 136]</td>\n <td>1.557658</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3471</th>\n <td>[225, 400, 572, 239, 102]</td>\n <td>1.557626</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3472</th>\n <td>[572, 102, 167]</td>\n <td>1.557563</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3473</th>\n <td>[400, 593, 219, 239, 136]</td>\n <td>1.557059</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3474</th>\n <td>[308, 239, 102, 167]</td>\n <td>1.556410</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3475</th>\n <td>[308, 572, 217, 239, 102]</td>\n <td>1.555784</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3476</th>\n <td>[308, 593, 219, 217, 239, 116]</td>\n <td>1.555684</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3477</th>\n <td>[400, 593, 572, 219, 239, 116]</td>\n <td>1.555549</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3478</th>\n <td>[308, 225, 219, 102]</td>\n <td>1.555133</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3479</th>\n <td>[308, 593, 217]</td>\n <td>1.554979</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3480</th>\n <td>[400, 572, 217, 239, 167]</td>\n <td>1.554539</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3481</th>\n <td>[308, 225, 167]</td>\n <td>1.554346</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3482</th>\n <td>[308, 225, 593, 219, 239, 136]</td>\n <td>1.554259</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3483</th>\n <td>[308, 225, 400, 219, 239, 116]</td>\n <td>1.553855</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3484</th>\n <td>[308, 225, 593, 572, 219, 239, 116]</td>\n <td>1.553657</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3485</th>\n <td>[225, 593, 572, 239, 116]</td>\n <td>1.553572</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3486</th>\n <td>[308, 225, 593]</td>\n <td>1.553305</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3487</th>\n <td>[308, 593, 572, 219, 217, 239, 167]</td>\n <td>1.553018</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3488</th>\n <td>[225, 572, 239, 102, 167]</td>\n <td>1.552402</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3489</th>\n <td>[308, 400, 593, 219]</td>\n <td>1.552093</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3490</th>\n <td>[572, 219, 217, 239, 136, 167]</td>\n <td>1.551786</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3491</th>\n <td>[225, 400, 572, 239, 136]</td>\n <td>1.551270</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3492</th>\n <td>[572, 116, 136]</td>\n <td>1.551097</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3493</th>\n <td>[308, 225, 400, 219, 217]</td>\n <td>1.551014</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3494</th>\n <td>[308, 219, 239, 116, 136]</td>\n <td>1.550962</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3495</th>\n <td>[308, 593, 572, 239, 167]</td>\n <td>1.550959</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3496</th>\n <td>[225, 400, 572, 219, 217, 239, 116]</td>\n <td>1.550697</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3497</th>\n <td>[225, 572, 239, 136, 167]</td>\n <td>1.550537</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3498</th>\n <td>[225, 593, 219, 217, 239, 102]</td>\n <td>1.550374</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3499</th>\n <td>[225, 219, 217, 239, 116, 167]</td>\n <td>1.550302</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3500</th>\n <td>[400, 219, 116]</td>\n <td>1.549909</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3501</th>\n <td>[225, 400, 219, 217, 239, 136]</td>\n <td>1.549813</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3502</th>\n <td>[593, 219, 239, 116, 167]</td>\n <td>1.549647</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3503</th>\n <td>[400, 593, 219, 217]</td>\n <td>1.548882</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3504</th>\n <td>[225, 572, 219, 239, 102, 116]</td>\n <td>1.548774</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3505</th>\n <td>[308, 572, 219, 239, 136, 167]</td>\n <td>1.548633</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3506</th>\n <td>[572, 102, 136]</td>\n <td>1.548336</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3507</th>\n <td>[308, 572, 217, 239, 136]</td>\n <td>1.548191</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3508</th>\n <td>[225, 572, 239, 116, 167]</td>\n <td>1.547540</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3509</th>\n <td>[308, 400, 219, 217, 239, 167]</td>\n <td>1.546911</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3510</th>\n <td>[225, 400, 593, 219]</td>\n <td>1.546745</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3511</th>\n <td>[219, 136, 167]</td>\n <td>1.546606</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3512</th>\n <td>[225, 572, 219, 217, 136]</td>\n <td>1.546278</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3513</th>\n <td>[219, 217, 239, 116, 136]</td>\n <td>1.546203</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3514</th>\n <td>[308, 225, 219, 217, 167]</td>\n <td>1.545880</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3515</th>\n <td>[308, 225, 593, 572, 217, 239]</td>\n <td>1.545696</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3516</th>\n <td>[308, 400, 572, 219, 239, 102]</td>\n <td>1.545521</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3517</th>\n <td>[308, 225, 217, 239, 167]</td>\n <td>1.545375</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3518</th>\n <td>[308, 400, 572, 239, 167]</td>\n <td>1.545104</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3519</th>\n <td>[400, 593, 572, 217, 239]</td>\n <td>1.544963</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3520</th>\n <td>[308, 225, 400, 572, 219, 239, 167]</td>\n <td>1.544667</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3521</th>\n <td>[308, 572, 219, 217, 116]</td>\n <td>1.544306</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3522</th>\n <td>[308, 225, 400, 572, 217, 239]</td>\n <td>1.544141</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3523</th>\n <td>[225, 219, 239, 102, 136]</td>\n <td>1.543694</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3524</th>\n <td>[225, 572, 116]</td>\n <td>1.543480</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3525</th>\n <td>[593, 219, 102]</td>\n <td>1.543129</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3526</th>\n <td>[308, 225, 593, 572, 219, 217]</td>\n <td>1.543004</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3527</th>\n <td>[225, 219, 217, 102]</td>\n <td>1.542747</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3528</th>\n <td>[400, 572, 219, 217, 239, 102]</td>\n <td>1.541892</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3529</th>\n <td>[308, 400, 593, 572, 219, 217, 239]</td>\n <td>1.541278</td>\n <td>0</td>\n <td>7</td>\n </tr>\n <tr>\n <th>3530</th>\n <td>[225, 400, 572, 239, 116]</td>\n <td>1.541106</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3531</th>\n <td>[225, 593, 572, 219, 217, 239, 116]</td>\n <td>1.540992</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3532</th>\n <td>[308, 225, 572, 219, 217, 239, 102]</td>\n <td>1.540744</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3533</th>\n <td>[308, 400, 593, 572, 239]</td>\n <td>1.540498</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3534</th>\n <td>[572, 217, 167]</td>\n <td>1.540291</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3535</th>\n <td>[400, 593, 219, 239, 116]</td>\n <td>1.540000</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3536</th>\n <td>[219, 217, 239, 102, 167]</td>\n <td>1.539717</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3537</th>\n <td>[225, 593, 239, 116]</td>\n <td>1.539542</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3538</th>\n <td>[308, 225, 593, 219, 239, 116]</td>\n <td>1.538892</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3539</th>\n <td>[239, 102, 136, 167]</td>\n <td>1.538786</td>\n <td>3</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3540</th>\n <td>[219, 116, 167]</td>\n <td>1.538507</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3541</th>\n <td>[593, 219, 217, 167]</td>\n <td>1.538473</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3542</th>\n <td>[308, 225, 572, 219, 116]</td>\n <td>1.538415</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3543</th>\n <td>[225, 400, 219, 217, 239, 116]</td>\n <td>1.536908</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3544</th>\n <td>[593, 572, 219, 217, 239, 102]</td>\n <td>1.536213</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3545</th>\n <td>[308, 400, 572, 219, 239, 136]</td>\n <td>1.536063</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3546</th>\n <td>[225, 593, 219, 217, 239, 136]</td>\n <td>1.535540</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3547</th>\n <td>[308, 593, 572, 219, 239, 102]</td>\n <td>1.535290</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3548</th>\n <td>[400, 572, 219, 167]</td>\n <td>1.535169</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3549</th>\n <td>[225, 239, 116, 136]</td>\n <td>1.535145</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3550</th>\n <td>[593, 572, 219, 116]</td>\n <td>1.535140</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3551</th>\n <td>[308, 219, 239, 102, 167]</td>\n <td>1.534797</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3552</th>\n <td>[593, 572, 217]</td>\n <td>1.534248</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3553</th>\n <td>[400, 217, 239, 167]</td>\n <td>1.534200</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3554</th>\n <td>[225, 572, 219, 239, 116, 136]</td>\n <td>1.534116</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3555</th>\n <td>[225, 593, 219, 167]</td>\n <td>1.534103</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3556</th>\n <td>[308, 225, 593, 572, 219, 239, 167]</td>\n <td>1.533313</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3557</th>\n <td>[308, 593, 219, 217, 239, 167]</td>\n <td>1.533144</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3558</th>\n <td>[225, 400, 239, 102]</td>\n <td>1.533121</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3559</th>\n <td>[225, 593, 239, 136]</td>\n <td>1.533034</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3560</th>\n <td>[225, 400, 572, 219, 217, 239, 167]</td>\n <td>1.532834</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3561</th>\n <td>[572, 136, 167]</td>\n <td>1.532803</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3562</th>\n <td>[572, 219, 217, 102]</td>\n <td>1.532239</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3563</th>\n <td>[308, 225, 400, 217, 239]</td>\n <td>1.531704</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3564</th>\n <td>[308, 219, 217, 136]</td>\n <td>1.531676</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3565</th>\n <td>[308, 225, 400, 219, 239, 167]</td>\n <td>1.531659</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3566</th>\n <td>[400, 593, 572, 219, 239, 167]</td>\n <td>1.531432</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3567</th>\n <td>[225, 239, 102, 116]</td>\n <td>1.530975</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3568</th>\n <td>[593, 167]</td>\n <td>1.530806</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3569</th>\n <td>[225, 116]</td>\n <td>1.530784</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3570</th>\n <td>[308, 593, 219, 167]</td>\n <td>1.529803</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3571</th>\n <td>[308, 572, 217, 239, 116]</td>\n <td>1.529429</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3572</th>\n <td>[308, 225, 593, 217, 239]</td>\n <td>1.529192</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3573</th>\n <td>[308, 400, 219, 239, 102]</td>\n <td>1.528987</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3574</th>\n <td>[400, 572, 219, 217, 239, 136]</td>\n <td>1.528804</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3575</th>\n <td>[308, 217, 239, 102]</td>\n <td>1.528367</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3576</th>\n <td>[572, 219, 217, 239, 116, 167]</td>\n <td>1.528298</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3577</th>\n <td>[225, 400, 239, 136]</td>\n <td>1.527928</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3578</th>\n <td>[225, 400, 239, 116]</td>\n <td>1.527918</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3579</th>\n <td>[308, 225, 572, 219, 217, 239, 136]</td>\n <td>1.527825</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3580</th>\n <td>[225, 593, 239, 102]</td>\n <td>1.527772</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3581</th>\n <td>[308, 225, 219, 136]</td>\n <td>1.527601</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3582</th>\n <td>[308, 225, 400, 593, 572, 219, 239]</td>\n <td>1.527598</td>\n <td>0</td>\n <td>7</td>\n </tr>\n <tr>\n <th>3583</th>\n <td>[400, 572, 217]</td>\n <td>1.527145</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3584</th>\n <td>[400, 593, 217, 239]</td>\n <td>1.527106</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3585</th>\n <td>[308, 400, 239, 167]</td>\n <td>1.527005</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3586</th>\n <td>[225, 572, 219, 239, 102, 167]</td>\n <td>1.526889</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3587</th>\n <td>[308, 572, 219, 239, 116, 167]</td>\n <td>1.526883</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3588</th>\n <td>[308, 400, 593, 219, 217, 239]</td>\n <td>1.526659</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3589</th>\n <td>[308, 593, 572, 219, 239, 136]</td>\n <td>1.526415</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3590</th>\n <td>[225, 572, 219, 217, 116]</td>\n <td>1.526021</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3591</th>\n <td>[308, 593, 239, 167]</td>\n <td>1.525647</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3592</th>\n <td>[308, 400, 593, 239]</td>\n <td>1.525313</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3593</th>\n <td>[225, 219, 239, 102, 116]</td>\n <td>1.524965</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3594</th>\n <td>[308, 400, 572, 219, 217]</td>\n <td>1.524417</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3595</th>\n <td>[593, 136]</td>\n <td>1.523855</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3596</th>\n <td>[308, 219, 239, 136, 167]</td>\n <td>1.523705</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3597</th>\n <td>[593, 572, 219, 217, 239, 136]</td>\n <td>1.522698</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3598</th>\n <td>[225, 239, 116, 167]</td>\n <td>1.521952</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3599</th>\n <td>[308, 572, 219, 217, 167]</td>\n <td>1.521828</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3600</th>\n <td>[308, 225, 219, 217, 239, 102]</td>\n <td>1.521808</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3601</th>\n <td>[225, 593, 572, 219, 217, 239, 167]</td>\n <td>1.521741</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3602</th>\n <td>[308, 217, 239, 136]</td>\n <td>1.521731</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3603</th>\n <td>[219, 217, 239, 136, 167]</td>\n <td>1.521348</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3604</th>\n <td>[400, 219, 217, 239, 102]</td>\n <td>1.521308</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3605</th>\n <td>[225, 593, 219, 217, 239, 116]</td>\n <td>1.520548</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3606</th>\n <td>[593, 102]</td>\n <td>1.519465</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3607</th>\n <td>[225, 572, 136]</td>\n <td>1.519230</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3608</th>\n <td>[225, 593, 572, 239, 167]</td>\n <td>1.519207</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3609</th>\n <td>[308, 400, 219, 239, 136]</td>\n <td>1.519011</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3610</th>\n <td>[308, 400, 572, 219, 239, 116]</td>\n <td>1.518675</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3611</th>\n <td>[225, 239, 102, 136]</td>\n <td>1.518538</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3612</th>\n <td>[308, 225, 400, 572, 219]</td>\n <td>1.518510</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3613</th>\n <td>[308, 572, 102]</td>\n <td>1.517505</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3614</th>\n <td>[225, 400, 572, 219, 239, 102]</td>\n <td>1.516821</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3615</th>\n <td>[217, 116]</td>\n <td>1.516507</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3616</th>\n <td>[308, 225, 593, 219, 217]</td>\n <td>1.516456</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3617</th>\n <td>[225, 400, 219, 217, 239, 167]</td>\n <td>1.515465</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3618</th>\n <td>[572, 219, 239, 102, 136]</td>\n <td>1.514983</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3619</th>\n <td>[308, 225, 593, 219, 239, 167]</td>\n <td>1.514166</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3620</th>\n <td>[308, 572, 219, 102]</td>\n <td>1.514050</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3621</th>\n <td>[225, 400, 593, 572, 219, 217, 239]</td>\n <td>1.513973</td>\n <td>0</td>\n <td>7</td>\n </tr>\n <tr>\n <th>3622</th>\n <td>[308, 225, 400, 593, 219, 239]</td>\n <td>1.513806</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3623</th>\n <td>[308, 225, 219, 116]</td>\n <td>1.513632</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3624</th>\n <td>[308, 219, 217, 116]</td>\n <td>1.513303</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3625</th>\n <td>[308, 225, 572, 219, 167]</td>\n <td>1.512669</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3626</th>\n <td>[225, 572, 219, 102]</td>\n <td>1.512423</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3627</th>\n <td>[225, 572, 219, 239, 136, 167]</td>\n <td>1.512098</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3628</th>\n <td>[225, 400, 572, 239, 167]</td>\n <td>1.511956</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3629</th>\n <td>[308, 225, 572, 219, 217, 239, 116]</td>\n <td>1.511636</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3630</th>\n <td>[308, 217, 239, 116]</td>\n <td>1.511407</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3631</th>\n <td>[225, 400, 593, 572, 239]</td>\n <td>1.510904</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3632</th>\n <td>[400, 572, 219, 217, 239, 116]</td>\n <td>1.510728</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3633</th>\n <td>[308, 593, 219, 239, 102]</td>\n <td>1.510436</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3634</th>\n <td>[400, 593, 219, 239, 167]</td>\n <td>1.510102</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3635</th>\n <td>[225, 219, 239, 116, 136]</td>\n <td>1.508943</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3636</th>\n <td>[308, 225, 572, 239, 102]</td>\n <td>1.508227</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3637</th>\n <td>[225, 400, 572]</td>\n <td>1.508175</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3638</th>\n <td>[308, 225, 219, 217, 239, 136]</td>\n <td>1.507748</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3639</th>\n <td>[225, 593, 572]</td>\n <td>1.507266</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3640</th>\n <td>[400, 593, 572, 219]</td>\n <td>1.507189</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3641</th>\n <td>[400, 219, 217, 239, 136]</td>\n <td>1.507039</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3642</th>\n <td>[593, 219, 217, 239, 102]</td>\n <td>1.506237</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3643</th>\n <td>[308, 219, 239, 116, 167]</td>\n <td>1.506118</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3644</th>\n <td>[593, 219, 136]</td>\n <td>1.505917</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3645</th>\n <td>[308, 593, 572, 219, 239, 116]</td>\n <td>1.505208</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3646</th>\n <td>[400, 219, 167]</td>\n <td>1.505170</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3647</th>\n <td>[308, 400, 572]</td>\n <td>1.505096</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3648</th>\n <td>[308, 572, 217, 239, 167]</td>\n <td>1.504992</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3649</th>\n <td>[225, 400, 572, 219, 239, 136]</td>\n <td>1.504746</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3650</th>\n <td>[225, 400, 572, 219, 217]</td>\n <td>1.503983</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3651</th>\n <td>[308, 400, 219, 239, 116]</td>\n <td>1.503918</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3652</th>\n <td>[225, 219, 217, 136]</td>\n <td>1.503448</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3653</th>\n <td>[102, 116, 136, 167]</td>\n <td>1.503368</td>\n <td>4</td>\n <td>0</td>\n </tr>\n <tr>\n <th>3654</th>\n <td>[219, 217, 239, 116, 167]</td>\n <td>1.503327</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3655</th>\n <td>[225, 593, 572, 219, 239, 102]</td>\n <td>1.503326</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3656</th>\n <td>[308, 225, 572, 239, 136]</td>\n <td>1.502331</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3657</th>\n <td>[308, 400, 219, 217]</td>\n <td>1.502295</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3658</th>\n <td>[225, 572, 219, 217, 167]</td>\n <td>1.502259</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3659</th>\n <td>[308, 593, 219, 239, 136]</td>\n <td>1.501335</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3660</th>\n <td>[217, 102]</td>\n <td>1.500246</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3661</th>\n <td>[308, 572, 219, 217, 239, 102]</td>\n <td>1.500241</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3662</th>\n <td>[593, 572, 219, 217, 239, 116]</td>\n <td>1.500071</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3663</th>\n <td>[308, 225, 400, 219]</td>\n <td>1.499800</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3664</th>\n <td>[225, 572, 217, 239, 102]</td>\n <td>1.499327</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3665</th>\n <td>[308, 225, 572, 217]</td>\n <td>1.498324</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3666</th>\n <td>[308, 400, 572, 219, 239, 167]</td>\n <td>1.497747</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3667</th>\n <td>[308, 572, 136]</td>\n <td>1.497511</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3668</th>\n <td>[225, 593, 219, 217, 239, 167]</td>\n <td>1.496853</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3669</th>\n <td>[593, 572, 219, 167]</td>\n <td>1.496719</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3670</th>\n <td>[225, 239, 136, 167]</td>\n <td>1.496340</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3671</th>\n <td>[225, 400, 219, 239, 102]</td>\n <td>1.496203</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3672</th>\n <td>[225, 219, 239, 102, 167]</td>\n <td>1.496148</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3673</th>\n <td>[225, 400, 593, 219, 217, 239]</td>\n <td>1.495916</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3674</th>\n <td>[308, 593, 572, 217, 239]</td>\n <td>1.494450</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3675</th>\n <td>[308, 225, 572, 219, 217, 239, 167]</td>\n <td>1.494402</td>\n <td>1</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3676</th>\n <td>[400, 217]</td>\n <td>1.494315</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3677</th>\n <td>[225, 572, 219, 239, 116, 167]</td>\n <td>1.494234</td>\n <td>2</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3678</th>\n <td>[308, 593, 572, 219, 217]</td>\n <td>1.494160</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3679</th>\n <td>[308, 225, 219, 217, 239, 116]</td>\n <td>1.493968</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3680</th>\n <td>[308, 400, 572, 217, 239]</td>\n <td>1.493373</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3681</th>\n <td>[225, 239, 102, 167]</td>\n <td>1.493249</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3682</th>\n <td>[572, 219, 217, 136]</td>\n <td>1.493239</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3683</th>\n <td>[225, 400, 593, 239]</td>\n <td>1.492119</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3684</th>\n <td>[400, 219, 217, 239, 116]</td>\n <td>1.491843</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3685</th>\n <td>[593, 219, 217, 239, 136]</td>\n <td>1.491560</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3686</th>\n <td>[225, 219, 217, 116]</td>\n <td>1.491243</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3687</th>\n <td>[225, 593, 572, 219, 239, 136]</td>\n <td>1.491185</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3688</th>\n <td>[308, 225, 400, 572, 219, 217, 239]</td>\n <td>1.490629</td>\n <td>0</td>\n <td>7</td>\n </tr>\n <tr>\n <th>3689</th>\n <td>[400, 572, 219, 217, 239, 167]</td>\n <td>1.490535</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3690</th>\n <td>[225, 572, 167]</td>\n <td>1.490350</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3691</th>\n <td>[308, 225, 572, 239, 116]</td>\n <td>1.490213</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3692</th>\n <td>[308, 572, 116]</td>\n <td>1.490053</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3693</th>\n <td>[225, 400, 572, 219, 239, 116]</td>\n <td>1.489730</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3694</th>\n <td>[225, 593, 239, 167]</td>\n <td>1.489500</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3695</th>\n <td>[225, 400, 239, 167]</td>\n <td>1.488982</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3696</th>\n <td>[308, 572, 219, 136]</td>\n <td>1.488314</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3697</th>\n <td>[593, 219, 116]</td>\n <td>1.488078</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3698</th>\n <td>[225, 400]</td>\n <td>1.487270</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3699</th>\n <td>[308, 572, 219, 217, 239, 136]</td>\n <td>1.487147</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3700</th>\n <td>[308, 225, 593, 572, 219]</td>\n <td>1.487129</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3701</th>\n <td>[225, 572, 217, 239, 136]</td>\n <td>1.486612</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3702</th>\n <td>[308, 219, 217, 167]</td>\n <td>1.484509</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3703</th>\n <td>[572, 219, 239, 102, 116]</td>\n <td>1.483722</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3704</th>\n <td>[308, 593, 219, 239, 116]</td>\n <td>1.483232</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3705</th>\n <td>[308, 400, 593, 572, 219, 239]</td>\n <td>1.483163</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3706</th>\n <td>[225, 400, 219, 239, 136]</td>\n <td>1.483137</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3707</th>\n <td>[308, 593, 572, 219, 239, 167]</td>\n <td>1.482001</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3708</th>\n <td>[308, 225, 219, 167]</td>\n <td>1.480440</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3709</th>\n <td>[225, 219, 239, 136, 167]</td>\n <td>1.479955</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3710</th>\n <td>[219, 217, 102]</td>\n <td>1.478911</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3711</th>\n <td>[308, 400, 219, 239, 167]</td>\n <td>1.478606</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3712</th>\n <td>[225, 400, 219, 217]</td>\n <td>1.478583</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3713</th>\n <td>[308, 217, 239, 167]</td>\n <td>1.478345</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3714</th>\n <td>[593, 572, 219, 217, 239, 167]</td>\n <td>1.477911</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3715</th>\n <td>[308, 225, 239, 102]</td>\n <td>1.477257</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3716</th>\n <td>[400, 593, 219]</td>\n <td>1.476457</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3717</th>\n <td>[225, 593]</td>\n <td>1.476378</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3718</th>\n <td>[225, 572, 217, 239, 116]</td>\n <td>1.476141</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3719</th>\n <td>[593, 217]</td>\n <td>1.475654</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3720</th>\n <td>[225, 572, 219, 136]</td>\n <td>1.475632</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3721</th>\n <td>[308, 225, 593, 572, 219, 217, 239]</td>\n <td>1.475614</td>\n <td>0</td>\n <td>7</td>\n </tr>\n <tr>\n <th>3722</th>\n <td>[308, 225, 572, 219, 239, 102]</td>\n <td>1.475347</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3723</th>\n <td>[308, 219, 217, 239, 102]</td>\n <td>1.475040</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3724</th>\n <td>[308, 225, 400, 219, 217, 239]</td>\n <td>1.474545</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3725</th>\n <td>[308, 400, 217, 239]</td>\n <td>1.474051</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3726</th>\n <td>[308, 400]</td>\n <td>1.473833</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3727</th>\n <td>[308, 225, 219, 217, 239, 167]</td>\n <td>1.473233</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3728</th>\n <td>[400, 593, 572, 219, 217, 239]</td>\n <td>1.473046</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3729</th>\n <td>[225, 593, 572, 219, 239, 116]</td>\n <td>1.472944</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3730</th>\n <td>[593, 219, 217, 239, 116]</td>\n <td>1.472938</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3731</th>\n <td>[308, 225, 239, 136]</td>\n <td>1.472813</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3732</th>\n <td>[225, 593, 219, 239, 102]</td>\n <td>1.472629</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3733</th>\n <td>[225, 400, 219, 239, 116]</td>\n <td>1.471483</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3734</th>\n <td>[225, 593, 572, 219, 217]</td>\n <td>1.470929</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3735</th>\n <td>[308, 225, 239, 116]</td>\n <td>1.470743</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3736</th>\n <td>[572, 219, 239, 116, 136]</td>\n <td>1.470161</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3737</th>\n <td>[308, 593, 572]</td>\n <td>1.470025</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3738</th>\n <td>[308, 593, 217, 239]</td>\n <td>1.469893</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3739</th>\n <td>[219, 239, 102, 136]</td>\n <td>1.468945</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3740</th>\n <td>[225, 219, 239, 116, 167]</td>\n <td>1.468678</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3741</th>\n <td>[308, 219, 102]</td>\n <td>1.468474</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3742</th>\n <td>[308, 572, 219, 217, 239, 116]</td>\n <td>1.467999</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3743</th>\n <td>[308, 225, 400, 572, 239]</td>\n <td>1.467952</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3744</th>\n <td>[225, 219, 102]</td>\n <td>1.467748</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3745</th>\n <td>[225, 400, 572, 219, 239, 167]</td>\n <td>1.467694</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3746</th>\n <td>[593, 572, 239, 136]</td>\n <td>1.467519</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3747</th>\n <td>[400, 219, 217, 239, 167]</td>\n <td>1.467105</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3748</th>\n <td>[572, 219, 217, 116]</td>\n <td>1.466572</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3749</th>\n <td>[308, 572, 219, 116]</td>\n <td>1.464283</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3750</th>\n <td>[308, 400, 593, 219, 239]</td>\n <td>1.463906</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3751</th>\n <td>[308, 225, 572, 219, 239, 136]</td>\n <td>1.463280</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3752</th>\n <td>[308, 225, 572, 239, 167]</td>\n <td>1.462248</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3753</th>\n <td>[400, 572, 239, 102]</td>\n <td>1.461571</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3754</th>\n <td>[308, 219, 217, 239, 136]</td>\n <td>1.460764</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3755</th>\n <td>[308, 225, 593, 572, 239]</td>\n <td>1.460547</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3756</th>\n <td>[225, 219, 217, 167]</td>\n <td>1.459829</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3757</th>\n <td>[225, 593, 219, 239, 136]</td>\n <td>1.459630</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3758</th>\n <td>[308, 225, 217]</td>\n <td>1.459132</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3759</th>\n <td>[400, 572, 239, 136]</td>\n <td>1.459032</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3760</th>\n <td>[400, 572, 219, 239, 102]</td>\n <td>1.458373</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3761</th>\n <td>[572, 219, 239, 102, 167]</td>\n <td>1.458056</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3762</th>\n <td>[308, 400, 572, 219]</td>\n <td>1.457659</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3763</th>\n <td>[225, 572, 219, 217, 239, 102]</td>\n <td>1.457541</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3764</th>\n <td>[308, 593, 219, 217]</td>\n <td>1.457478</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3765</th>\n <td>[225, 217, 239, 102]</td>\n <td>1.457344</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3766</th>\n <td>[593, 572, 239, 102]</td>\n <td>1.456249</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3767</th>\n <td>[225, 572, 219, 116]</td>\n <td>1.455633</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3768</th>\n <td>[308, 225, 593, 219]</td>\n <td>1.454724</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3769</th>\n <td>[308, 593, 219, 239, 167]</td>\n <td>1.454419</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3770</th>\n <td>[593, 572, 239, 116]</td>\n <td>1.453944</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3771</th>\n <td>[225, 400, 593, 572, 219, 239]</td>\n <td>1.453893</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3772</th>\n <td>[308, 225, 593, 219, 217, 239]</td>\n <td>1.453823</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3773</th>\n <td>[225, 572, 217, 239, 167]</td>\n <td>1.450741</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3774</th>\n <td>[308, 225, 219, 239, 102]</td>\n <td>1.450206</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3775</th>\n <td>[225, 400, 572, 217, 239]</td>\n <td>1.450031</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3776</th>\n <td>[400, 593, 219, 217, 239]</td>\n <td>1.449413</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3777</th>\n <td>[308, 400, 572, 219, 217, 239]</td>\n <td>1.449227</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3778</th>\n <td>[400, 572, 219, 217]</td>\n <td>1.449093</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3779</th>\n <td>[308, 225, 400, 239]</td>\n <td>1.448632</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3780</th>\n <td>[308, 572, 219, 217, 239, 167]</td>\n <td>1.448536</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3781</th>\n <td>[400, 572, 239, 116]</td>\n <td>1.448408</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3782</th>\n <td>[225, 593, 572, 219, 239, 167]</td>\n <td>1.448314</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3783</th>\n <td>[225, 217, 239, 116]</td>\n <td>1.447771</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3784</th>\n <td>[308, 225, 572, 219, 239, 116]</td>\n <td>1.447237</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3785</th>\n <td>[400, 572, 219, 239, 136]</td>\n <td>1.446623</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3786</th>\n <td>[308, 572, 167]</td>\n <td>1.446335</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3787</th>\n <td>[225, 593, 572, 217, 239]</td>\n <td>1.446242</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3788</th>\n <td>[225, 593, 219, 239, 116]</td>\n <td>1.446167</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3789</th>\n <td>[217, 167]</td>\n <td>1.446102</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3790</th>\n <td>[219, 239, 102, 116]</td>\n <td>1.445051</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3791</th>\n <td>[593, 219, 217, 239, 167]</td>\n <td>1.444875</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3792</th>\n <td>[225, 400, 219, 239, 167]</td>\n <td>1.444470</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3793</th>\n <td>[308, 219, 217, 239, 116]</td>\n <td>1.444376</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3794</th>\n <td>[225, 102]</td>\n <td>1.444307</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3795</th>\n <td>[225, 217, 239, 136]</td>\n <td>1.444261</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3796</th>\n <td>[572, 219, 239, 136, 167]</td>\n <td>1.444250</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3797</th>\n <td>[225, 572, 219, 217, 239, 136]</td>\n <td>1.440981</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3798</th>\n <td>[593, 572, 219, 239, 102]</td>\n <td>1.439500</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3799</th>\n <td>[225, 400, 572, 219]</td>\n <td>1.439417</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3800</th>\n <td>[572, 239, 102, 136]</td>\n <td>1.438465</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3801</th>\n <td>[308, 219, 136]</td>\n <td>1.438248</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3802</th>\n <td>[572, 219, 217, 167]</td>\n <td>1.438072</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3803</th>\n <td>[308, 225, 572, 219, 217]</td>\n <td>1.437320</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3804</th>\n <td>[308, 225, 219, 239, 136]</td>\n <td>1.437154</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3805</th>\n <td>[572, 239, 116, 136]</td>\n <td>1.437055</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3806</th>\n <td>[308, 225, 593, 239]</td>\n <td>1.435216</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3807</th>\n <td>[217, 136]</td>\n <td>1.434696</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3808</th>\n <td>[308, 572, 219, 167]</td>\n <td>1.433858</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3809</th>\n <td>[308, 225, 400, 572, 219, 239]</td>\n <td>1.433666</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3810</th>\n <td>[308, 225, 239, 167]</td>\n <td>1.433025</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3811</th>\n <td>[593, 219, 167]</td>\n <td>1.433022</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3812</th>\n <td>[308, 593, 572, 219, 217, 239]</td>\n <td>1.431059</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3813</th>\n <td>[219, 217, 136]</td>\n <td>1.430961</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3814</th>\n <td>[219, 239, 116, 136]</td>\n <td>1.430763</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3815</th>\n <td>[225, 400, 593, 219, 239]</td>\n <td>1.430760</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3816</th>\n <td>[400, 593, 572, 239]</td>\n <td>1.429313</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3817</th>\n <td>[400, 572, 219, 239, 116]</td>\n <td>1.429217</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3818</th>\n <td>[308, 400, 219]</td>\n <td>1.428976</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3819</th>\n <td>[225, 593, 219, 217]</td>\n <td>1.428621</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3820</th>\n <td>[593, 572, 219, 239, 136]</td>\n <td>1.428477</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3821</th>\n <td>[308, 400, 219, 217, 239]</td>\n <td>1.428291</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3822</th>\n <td>[400, 219, 239, 102]</td>\n <td>1.427569</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3823</th>\n <td>[572, 239, 102, 116]</td>\n <td>1.427056</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3824</th>\n <td>[308, 225, 572, 219, 239, 167]</td>\n <td>1.425872</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3825</th>\n <td>[225, 572, 219, 217, 239, 116]</td>\n <td>1.425010</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3826</th>\n <td>[225, 219, 217, 239, 102]</td>\n <td>1.424668</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3827</th>\n <td>[308, 225, 219, 239, 116]</td>\n <td>1.424360</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3828</th>\n <td>[225, 400, 217, 239]</td>\n <td>1.423555</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3829</th>\n <td>[572, 219, 102]</td>\n <td>1.422657</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3830</th>\n <td>[572, 219, 239, 116, 167]</td>\n <td>1.422171</td>\n <td>2</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3831</th>\n <td>[308, 219, 116]</td>\n <td>1.422102</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3832</th>\n <td>[225, 219, 136]</td>\n <td>1.422003</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3833</th>\n <td>[225, 572, 219, 167]</td>\n <td>1.421586</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3834</th>\n <td>[225, 167]</td>\n <td>1.421551</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3835</th>\n <td>[308, 219, 217, 239, 167]</td>\n <td>1.420457</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3836</th>\n <td>[102, 116, 167]</td>\n <td>1.419267</td>\n <td>3</td>\n <td>0</td>\n </tr>\n <tr>\n <th>3837</th>\n <td>[219, 217, 116]</td>\n <td>1.415349</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3838</th>\n <td>[225, 219, 116]</td>\n <td>1.415312</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3839</th>\n <td>[593, 239, 116]</td>\n <td>1.415080</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3840</th>\n <td>[572, 217, 239, 102]</td>\n <td>1.415065</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3841</th>\n <td>[225, 593, 219, 239, 167]</td>\n <td>1.414995</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3842</th>\n <td>[400, 219, 239, 136]</td>\n <td>1.414950</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3843</th>\n <td>[400, 239, 116]</td>\n <td>1.414700</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3844</th>\n <td>[308, 593, 572, 219]</td>\n <td>1.414263</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3845</th>\n <td>[400, 572, 239, 167]</td>\n <td>1.413660</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3846</th>\n <td>[400, 219, 217]</td>\n <td>1.413364</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3847</th>\n <td>[308, 225, 400, 219, 239]</td>\n <td>1.413322</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3848</th>\n <td>[225, 400, 572, 219, 217, 239]</td>\n <td>1.412867</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3849</th>\n <td>[308, 572, 219, 239, 102]</td>\n <td>1.412534</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3850</th>\n <td>[225, 593, 217, 239]</td>\n <td>1.412475</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3851</th>\n <td>[225, 217, 239, 167]</td>\n <td>1.412256</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3852</th>\n <td>[308, 225, 593, 572, 219, 239]</td>\n <td>1.412101</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3853</th>\n <td>[308, 116]</td>\n <td>1.411406</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3854</th>\n <td>[400, 239, 136]</td>\n <td>1.411099</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3855</th>\n <td>[400, 239, 102]</td>\n <td>1.410651</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3856</th>\n <td>[593, 572, 239, 167]</td>\n <td>1.410415</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3857</th>\n <td>[219, 239, 102, 167]</td>\n <td>1.409657</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3858</th>\n <td>[572, 239, 116, 167]</td>\n <td>1.408650</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3859</th>\n <td>[225, 400, 219]</td>\n <td>1.408384</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3860</th>\n <td>[308, 225, 572, 217, 239]</td>\n <td>1.408163</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3861</th>\n <td>[593, 572, 219, 217]</td>\n <td>1.407299</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3862</th>\n <td>[572, 239, 136, 167]</td>\n <td>1.407068</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3863</th>\n <td>[572, 217, 239, 136]</td>\n <td>1.406320</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3864</th>\n <td>[225, 219, 217, 239, 136]</td>\n <td>1.406200</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3865</th>\n <td>[593, 572, 219, 239, 116]</td>\n <td>1.406163</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3866</th>\n <td>[308, 572, 239, 102]</td>\n <td>1.405249</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3867</th>\n <td>[225, 572, 219, 217, 239, 167]</td>\n <td>1.404802</td>\n <td>1</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3868</th>\n <td>[308, 572, 217]</td>\n <td>1.404083</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3869</th>\n <td>[400, 572, 219, 239, 167]</td>\n <td>1.403907</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3870</th>\n <td>[308, 572, 239, 136]</td>\n <td>1.403643</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3871</th>\n <td>[308, 593, 219, 217, 239]</td>\n <td>1.402845</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3872</th>\n <td>[572, 219, 217, 239, 102]</td>\n <td>1.402108</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3873</th>\n <td>[308, 225, 219, 217]</td>\n <td>1.401936</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3874</th>\n <td>[308, 593]</td>\n <td>1.401907</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3875</th>\n <td>[308, 102]</td>\n <td>1.401624</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3876</th>\n <td>[400, 219, 239, 116]</td>\n <td>1.401624</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3877</th>\n <td>[308, 572, 219, 239, 136]</td>\n <td>1.400824</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3878</th>\n <td>[593, 239, 136]</td>\n <td>1.398582</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3879</th>\n <td>[308, 225, 219, 239, 167]</td>\n <td>1.398085</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3880</th>\n <td>[572, 239, 102, 167]</td>\n <td>1.397739</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3881</th>\n <td>[116, 136, 167]</td>\n <td>1.396639</td>\n <td>3</td>\n <td>0</td>\n </tr>\n <tr>\n <th>3882</th>\n <td>[225, 593, 572, 219]</td>\n <td>1.395155</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3883</th>\n <td>[219, 239, 136, 167]</td>\n <td>1.394967</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3884</th>\n <td>[400, 593, 572, 219, 239]</td>\n <td>1.394747</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3885</th>\n <td>[225, 219, 217, 239, 116]</td>\n <td>1.394408</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3886</th>\n <td>[593, 219, 239, 102]</td>\n <td>1.394112</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3887</th>\n <td>[400, 593, 239]</td>\n <td>1.393917</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3888</th>\n <td>[572, 217, 239, 116]</td>\n <td>1.393516</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3889</th>\n <td>[225, 136]</td>\n <td>1.392220</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3890</th>\n <td>[308, 572, 239, 116]</td>\n <td>1.390316</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3891</th>\n <td>[225, 593, 572, 219, 217, 239]</td>\n <td>1.389369</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3892</th>\n <td>[308, 400, 572, 239]</td>\n <td>1.388975</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3893</th>\n <td>[225, 400, 219, 217, 239]</td>\n <td>1.386948</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3894</th>\n <td>[308, 225, 572]</td>\n <td>1.385070</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3895</th>\n <td>[572, 219, 217, 239, 136]</td>\n <td>1.384873</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3896</th>\n <td>[308, 225, 593, 219, 239]</td>\n <td>1.384452</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3897</th>\n <td>[593, 219, 239, 136]</td>\n <td>1.382719</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3898</th>\n <td>[308, 572, 219, 239, 116]</td>\n <td>1.382041</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3899</th>\n <td>[219, 239, 116, 167]</td>\n <td>1.381607</td>\n <td>2</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3900</th>\n <td>[308, 219, 167]</td>\n <td>1.381500</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3901</th>\n <td>[308, 136]</td>\n <td>1.379457</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3902</th>\n <td>[572, 219, 136]</td>\n <td>1.379126</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3903</th>\n <td>[308, 225, 217, 239]</td>\n <td>1.377155</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3904</th>\n <td>[593, 572, 219, 239, 167]</td>\n <td>1.377074</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3905</th>\n <td>[308, 400, 572, 219, 239]</td>\n <td>1.376758</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3906</th>\n <td>[400, 572, 217, 239]</td>\n <td>1.376349</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3907</th>\n <td>[308, 225, 572, 219, 217, 239]</td>\n <td>1.376327</td>\n <td>0</td>\n <td>6</td>\n </tr>\n <tr>\n <th>3908</th>\n <td>[308, 219, 239, 102]</td>\n <td>1.375993</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3909</th>\n <td>[219, 217, 167]</td>\n <td>1.375580</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3910</th>\n <td>[593, 239, 102]</td>\n <td>1.374495</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3911</th>\n <td>[225, 572, 217]</td>\n <td>1.372381</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3912</th>\n <td>[308, 593, 572, 239]</td>\n <td>1.372066</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3913</th>\n <td>[593, 572, 217, 239]</td>\n <td>1.371845</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3914</th>\n <td>[308, 572, 219, 217]</td>\n <td>1.371617</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3915</th>\n <td>[400, 219, 239, 167]</td>\n <td>1.369862</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3916</th>\n <td>[225, 219, 217, 239, 167]</td>\n <td>1.369226</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3917</th>\n <td>[400, 572]</td>\n <td>1.367319</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3918</th>\n <td>[225, 219, 167]</td>\n <td>1.367174</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3919</th>\n <td>[593, 219, 239, 116]</td>\n <td>1.366407</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3920</th>\n <td>[400, 239, 167]</td>\n <td>1.366362</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3921</th>\n <td>[572, 219, 217, 239, 116]</td>\n <td>1.365207</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3922</th>\n <td>[308, 593, 219]</td>\n <td>1.365164</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3923</th>\n <td>[225, 572, 219, 239, 102]</td>\n <td>1.363804</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3924</th>\n <td>[308, 219, 239, 136]</td>\n <td>1.363434</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3925</th>\n <td>[572, 217, 239, 167]</td>\n <td>1.362554</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3926</th>\n <td>[400, 593, 219, 239]</td>\n <td>1.362312</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3927</th>\n <td>[308, 225, 572, 219]</td>\n <td>1.361895</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3928</th>\n <td>[400, 572, 219, 217, 239]</td>\n <td>1.357931</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3929</th>\n <td>[219, 217, 239, 102]</td>\n <td>1.357794</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3930</th>\n <td>[308, 572, 219, 239, 167]</td>\n <td>1.357478</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3931</th>\n <td>[308, 572, 239, 167]</td>\n <td>1.356857</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3932</th>\n <td>[400, 572, 219]</td>\n <td>1.355849</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3933</th>\n <td>[308, 400, 239]</td>\n <td>1.355763</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3934</th>\n <td>[225, 593, 219, 217, 239]</td>\n <td>1.354396</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3935</th>\n <td>[572, 219, 116]</td>\n <td>1.352621</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3936</th>\n <td>[308, 400, 219, 239]</td>\n <td>1.348708</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3937</th>\n <td>[308, 219, 239, 116]</td>\n <td>1.348562</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3938</th>\n <td>[308, 593, 572, 219, 239]</td>\n <td>1.348372</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3939</th>\n <td>[225, 572, 219, 239, 136]</td>\n <td>1.348111</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3940</th>\n <td>[217, 239, 116]</td>\n <td>1.348020</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3941</th>\n <td>[308, 239, 116]</td>\n <td>1.347995</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3942</th>\n <td>[593, 219, 217]</td>\n <td>1.347250</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3943</th>\n <td>[308, 239, 136]</td>\n <td>1.347097</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3944</th>\n <td>[308, 225, 219, 217, 239]</td>\n <td>1.346846</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3945</th>\n <td>[593, 239, 167]</td>\n <td>1.345906</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3946</th>\n <td>[217, 239, 102]</td>\n <td>1.345428</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3947</th>\n <td>[308, 239, 102]</td>\n <td>1.345027</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3948</th>\n <td>[219, 102]</td>\n <td>1.344321</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3949</th>\n <td>[308, 167]</td>\n <td>1.342292</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3950</th>\n <td>[593, 572]</td>\n <td>1.341895</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3951</th>\n <td>[572, 219, 217, 239, 167]</td>\n <td>1.341711</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3952</th>\n <td>[225, 593, 219]</td>\n <td>1.341477</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3953</th>\n <td>[217, 239, 136]</td>\n <td>1.339042</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3954</th>\n <td>[219, 217, 239, 136]</td>\n <td>1.338408</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3955</th>\n <td>[225, 400, 572, 239]</td>\n <td>1.337085</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3956</th>\n <td>[225, 400, 572, 219, 239]</td>\n <td>1.336019</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3957</th>\n <td>[400, 217, 239]</td>\n <td>1.335754</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3958</th>\n <td>[308, 217]</td>\n <td>1.334933</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3959</th>\n <td>[225, 572, 219, 239, 116]</td>\n <td>1.333353</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3960</th>\n <td>[225, 572, 219, 217]</td>\n <td>1.332536</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3961</th>\n <td>[308, 572, 217, 239]</td>\n <td>1.330104</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3962</th>\n <td>[225, 572, 239, 102]</td>\n <td>1.330085</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3963</th>\n <td>[239, 116, 136]</td>\n <td>1.329372</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3964</th>\n <td>[593, 572, 219, 217, 239]</td>\n <td>1.329183</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3965</th>\n <td>[593, 219, 239, 167]</td>\n <td>1.328305</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3966</th>\n <td>[239, 116, 167]</td>\n <td>1.328076</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3967</th>\n <td>[308, 593, 239]</td>\n <td>1.327795</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3968</th>\n <td>[308, 225]</td>\n <td>1.326018</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3969</th>\n <td>[219, 217, 239, 116]</td>\n <td>1.323865</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3970</th>\n <td>[400, 219, 217, 239]</td>\n <td>1.323737</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3971</th>\n <td>[225, 572, 239, 136]</td>\n <td>1.323430</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3972</th>\n <td>[116, 167]</td>\n <td>1.323295</td>\n <td>2</td>\n <td>0</td>\n </tr>\n <tr>\n <th>3973</th>\n <td>[225, 572, 239, 116]</td>\n <td>1.322502</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3974</th>\n <td>[593, 217, 239]</td>\n <td>1.322279</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3975</th>\n <td>[308, 219, 217]</td>\n <td>1.322177</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3976</th>\n <td>[308, 572, 219, 217, 239]</td>\n <td>1.317927</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3977</th>\n <td>[308, 219, 239, 167]</td>\n <td>1.317594</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3978</th>\n <td>[225, 219, 239, 102]</td>\n <td>1.317471</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3979</th>\n <td>[308, 225, 219]</td>\n <td>1.316771</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3980</th>\n <td>[225, 593, 572, 239]</td>\n <td>1.313573</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3981</th>\n <td>[102, 116, 136]</td>\n <td>1.312975</td>\n <td>3</td>\n <td>0</td>\n </tr>\n <tr>\n <th>3982</th>\n <td>[308, 593, 219, 239]</td>\n <td>1.310192</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3983</th>\n <td>[572, 219, 167]</td>\n <td>1.309107</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3984</th>\n <td>[225, 572, 219, 239, 167]</td>\n <td>1.307230</td>\n <td>1</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3985</th>\n <td>[239, 102, 116]</td>\n <td>1.307101</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>3986</th>\n <td>[400, 219]</td>\n <td>1.306500</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3987</th>\n <td>[102, 136, 167]</td>\n <td>1.303011</td>\n <td>3</td>\n <td>0</td>\n </tr>\n <tr>\n <th>3988</th>\n <td>[225, 400, 219, 239]</td>\n <td>1.301825</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>3989</th>\n <td>[225, 593, 572, 219, 239]</td>\n <td>1.301182</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3990</th>\n <td>[217, 239, 167]</td>\n <td>1.300997</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3991</th>\n <td>[308, 239, 167]</td>\n <td>1.300712</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3992</th>\n <td>[225, 219, 239, 136]</td>\n <td>1.299985</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3993</th>\n <td>[308, 225, 572, 219, 239]</td>\n <td>1.296107</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3994</th>\n <td>[225, 217]</td>\n <td>1.294878</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3995</th>\n <td>[225, 400, 239]</td>\n <td>1.293949</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3996</th>\n <td>[219, 217, 239, 167]</td>\n <td>1.293595</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3997</th>\n <td>[593, 572, 219]</td>\n <td>1.292522</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3998</th>\n <td>[225, 219, 239, 116]</td>\n <td>1.291312</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>3999</th>\n <td>[308, 225, 572, 239]</td>\n <td>1.290446</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>4000</th>\n <td>[219, 136]</td>\n <td>1.287069</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>4001</th>\n <td>[225, 572, 239, 167]</td>\n <td>1.285988</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4002</th>\n <td>[572, 116]</td>\n <td>1.284576</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>4003</th>\n <td>[308, 217, 239]</td>\n <td>1.283784</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4004</th>\n <td>[593, 219, 217, 239]</td>\n <td>1.282947</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>4005</th>\n <td>[219, 116]</td>\n <td>1.280944</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>4006</th>\n <td>[308, 219, 217, 239]</td>\n <td>1.279298</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>4007</th>\n <td>[239, 102, 136]</td>\n <td>1.278831</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>4008</th>\n <td>[239, 136, 167]</td>\n <td>1.278779</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>4009</th>\n <td>[225, 219, 217]</td>\n <td>1.273669</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4010</th>\n <td>[572, 219, 239, 102]</td>\n <td>1.270827</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4011</th>\n <td>[225, 239, 116]</td>\n <td>1.264636</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4012</th>\n <td>[308, 572, 219]</td>\n <td>1.263453</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4013</th>\n <td>[225, 572, 219, 217, 239]</td>\n <td>1.262644</td>\n <td>0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>4014</th>\n <td>[239, 102, 167]</td>\n <td>1.259024</td>\n <td>2</td>\n <td>1</td>\n </tr>\n <tr>\n <th>4015</th>\n <td>[572, 102]</td>\n <td>1.257862</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>4016</th>\n <td>[225, 219, 239, 167]</td>\n <td>1.257693</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4017</th>\n <td>[308, 225, 219, 239]</td>\n <td>1.257549</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>4018</th>\n <td>[400, 572, 219, 239]</td>\n <td>1.257338</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>4019</th>\n <td>[225, 593, 239]</td>\n <td>1.256648</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4020</th>\n <td>[572, 219, 239, 136]</td>\n <td>1.255254</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4021</th>\n <td>[225, 593, 219, 239]</td>\n <td>1.254484</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>4022</th>\n <td>[225, 572, 217, 239]</td>\n <td>1.253987</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>4023</th>\n <td>[225, 239, 102]</td>\n <td>1.244785</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4024</th>\n <td>[308, 225, 239]</td>\n <td>1.241564</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4025</th>\n <td>[225, 239, 136]</td>\n <td>1.240733</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4026</th>\n <td>[572, 219, 217]</td>\n <td>1.239719</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4027</th>\n <td>[572, 219, 239, 116]</td>\n <td>1.237578</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4028</th>\n <td>[572, 217]</td>\n <td>1.225138</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4029</th>\n <td>[225, 572, 219]</td>\n <td>1.222448</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4030</th>\n <td>[572, 136]</td>\n <td>1.221922</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>4031</th>\n <td>[225, 219, 217, 239]</td>\n <td>1.214239</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>4032</th>\n <td>[219, 167]</td>\n <td>1.214021</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>4033</th>\n <td>[400, 572, 239]</td>\n <td>1.213903</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4034</th>\n <td>[308, 572, 219, 239]</td>\n <td>1.212752</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>4035</th>\n <td>[225, 239, 167]</td>\n <td>1.210190</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4036</th>\n <td>[593, 572, 219, 239]</td>\n <td>1.210073</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>4037</th>\n <td>[400, 219, 239]</td>\n <td>1.208980</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4038</th>\n <td>[308, 572]</td>\n <td>1.206602</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4039</th>\n <td>[572, 219, 239, 167]</td>\n <td>1.206341</td>\n <td>1</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4040</th>\n <td>[572, 167]</td>\n <td>1.206226</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>4041</th>\n <td>[593, 219]</td>\n <td>1.205971</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4042</th>\n <td>[219, 239, 102]</td>\n <td>1.200929</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4043</th>\n <td>[308, 219]</td>\n <td>1.193416</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4044</th>\n <td>[102, 116]</td>\n <td>1.190801</td>\n <td>2</td>\n <td>0</td>\n </tr>\n <tr>\n <th>4045</th>\n <td>[225, 217, 239]</td>\n <td>1.189271</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4046</th>\n <td>[219, 239, 136]</td>\n <td>1.183604</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4047</th>\n <td>[572, 219, 217, 239]</td>\n <td>1.179769</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>4048</th>\n <td>[225, 572]</td>\n <td>1.179115</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4049</th>\n <td>[219, 239, 116]</td>\n <td>1.173958</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4050</th>\n <td>[593, 572, 239]</td>\n <td>1.166241</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4051</th>\n <td>[308, 572, 239]</td>\n <td>1.159678</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4052</th>\n <td>[116, 136]</td>\n <td>1.159043</td>\n <td>2</td>\n <td>0</td>\n </tr>\n <tr>\n <th>4053</th>\n <td>[308, 219, 239]</td>\n <td>1.158597</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4054</th>\n <td>[219, 217]</td>\n <td>1.152890</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4055</th>\n <td>[225, 572, 219, 239]</td>\n <td>1.147189</td>\n <td>0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>4056</th>\n <td>[593, 219, 239]</td>\n <td>1.143013</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4057</th>\n <td>[225, 219]</td>\n <td>1.141725</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4058</th>\n <td>[572, 239, 116]</td>\n <td>1.140662</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4059</th>\n <td>[400, 239]</td>\n <td>1.138507</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4060</th>\n <td>[572, 239, 136]</td>\n <td>1.136570</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4061</th>\n <td>[572, 239, 102]</td>\n <td>1.136379</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4062</th>\n <td>[102, 167]</td>\n <td>1.134207</td>\n <td>2</td>\n <td>0</td>\n </tr>\n <tr>\n <th>4063</th>\n <td>[219, 239, 167]</td>\n <td>1.132073</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4064</th>\n <td>[572, 217, 239]</td>\n <td>1.126306</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4065</th>\n <td>[219, 217, 239]</td>\n <td>1.113772</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4066</th>\n <td>[136, 167]</td>\n <td>1.100145</td>\n <td>2</td>\n <td>0</td>\n </tr>\n <tr>\n <th>4067</th>\n <td>[572, 239, 167]</td>\n <td>1.093898</td>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4068</th>\n <td>[225, 219, 239]</td>\n <td>1.079517</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4069</th>\n <td>[308, 239]</td>\n <td>1.075236</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4070</th>\n <td>[572, 219]</td>\n <td>1.068853</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4071</th>\n <td>[102, 136]</td>\n <td>1.060123</td>\n <td>2</td>\n <td>0</td>\n </tr>\n <tr>\n <th>4072</th>\n <td>[593, 239]</td>\n <td>1.059879</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4073</th>\n <td>[225, 572, 239]</td>\n <td>1.058020</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4074</th>\n <td>[217, 239]</td>\n <td>1.022142</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4075</th>\n <td>[572, 219, 239]</td>\n <td>1.021043</td>\n <td>0</td>\n <td>3</td>\n </tr>\n <tr>\n <th>4076</th>\n <td>[239, 116]</td>\n <td>1.010654</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>4077</th>\n <td>[239, 136]</td>\n <td>0.965136</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>4078</th>\n <td>[239, 102]</td>\n <td>0.959413</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>4079</th>\n <td>[225, 239]</td>\n <td>0.941099</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4080</th>\n <td>[239, 167]</td>\n <td>0.934426</td>\n <td>1</td>\n <td>1</td>\n </tr>\n <tr>\n <th>4081</th>\n <td>[219, 239]</td>\n <td>0.919083</td>\n <td>0</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4082</th>\n <td>[572, 239]</td>\n <td>0.813601</td>\n <td>0</td>\n <td>2</td>\n </tr>\n </tbody>\n</table>\n</div>",
  478. "text/plain": " Combinations Sharpe \\\nCombi Index \n0 [400, 593, 217, 102, 116, 136, 167] 2.720188 \n1 [225, 400, 593, 102, 116, 136, 167] 2.705898 \n2 [400, 593, 572, 217, 102, 116, 136, 167] 2.686970 \n3 [400, 593, 572, 102, 116, 136, 167] 2.686759 \n4 [400, 593, 102, 116, 136, 167] 2.677788 \n5 [225, 400, 593, 572, 102, 116, 136, 167] 2.660203 \n6 [225, 400, 593, 217, 102, 116, 136, 167] 2.653306 \n7 [225, 400, 593, 572, 217, 102, 116, 136, 167] 2.607421 \n8 [400, 217, 102, 116, 136, 167] 2.577118 \n9 [593, 572, 217, 102, 116, 136, 167] 2.565216 \n10 [400, 572, 217, 102, 116, 136, 167] 2.563370 \n11 [225, 400, 102, 116, 136, 167] 2.551190 \n12 [225, 400, 217, 102, 116, 136, 167] 2.544877 \n13 [225, 593, 572, 217, 102, 116, 136, 167] 2.539767 \n14 [308, 400, 593, 217, 102, 116, 136, 167] 2.531614 \n15 [308, 225, 400, 593, 102, 116, 136, 167] 2.529843 \n16 [225, 400, 572, 102, 116, 136, 167] 2.525656 \n17 [308, 400, 593, 102, 116, 136, 167] 2.524993 \n18 [400, 593, 217, 102, 116, 136] 2.518334 \n19 [225, 400, 593, 102, 116, 136] 2.511185 \n20 [400, 593, 217, 102, 136, 167] 2.510557 \n21 [225, 400, 572, 217, 102, 116, 136, 167] 2.506984 \n22 [308, 400, 593, 572, 102, 116, 136, 167] 2.502865 \n23 [308, 400, 593, 572, 217, 102, 116, 136, 167] 2.500339 \n24 [308, 225, 400, 593, 217, 102, 116, 136, 167] 2.496539 \n25 [225, 593, 572, 102, 116, 136, 167] 2.496199 \n26 [225, 593, 217, 102, 116, 136, 167] 2.495892 \n27 [400, 572, 102, 116, 136, 167] 2.495542 \n28 [225, 400, 593, 102, 136, 167] 2.491610 \n29 [308, 225, 400, 593, 572, 102, 116, 136, 167] 2.489900 \n30 [400, 593, 102, 116, 136] 2.487189 \n31 [400, 593, 572, 217, 102, 116, 136] 2.484959 \n32 [400, 593, 572, 217, 102, 136, 167] 2.483792 \n33 [400, 593, 572, 102, 116, 136] 2.480400 \n34 [400, 593, 217, 102, 116, 167] 2.478921 \n35 [225, 400, 593, 102, 116, 167] 2.476664 \n36 [400, 593, 572, 102, 136, 167] 2.473321 \n37 [225, 400, 593, 116, 136, 167] 2.468986 \n38 [400, 593, 102, 136, 167] 2.467252 \n39 [400, 593, 116, 136, 167] 2.465253 \n40 [225, 400, 593, 217, 102, 116, 136] 2.464879 \n41 [400, 593, 217, 116, 136, 167] 2.464664 \n42 [225, 400, 593, 572, 102, 116, 136] 2.464032 \n43 [308, 225, 400, 593, 572, 217, 102, 116, 136, ... 2.460709 \n44 [400, 593, 102, 116, 167] 2.457251 \n45 [225, 400, 593, 217, 102, 136, 167] 2.454269 \n46 [225, 400, 593, 572, 102, 136, 167] 2.453891 \n47 [308, 400, 217, 102, 116, 136, 167] 2.434522 \n48 [400, 102, 116, 136, 167] 2.434434 \n49 [400, 593, 572, 217, 102, 116, 167] 2.432925 \n50 [308, 593, 572, 217, 102, 116, 136, 167] 2.432502 \n51 [225, 400, 593, 217, 102, 116, 167] 2.428590 \n52 [308, 225, 400, 102, 116, 136, 167] 2.428539 \n53 [400, 593, 572, 116, 136, 167] 2.426876 \n54 [400, 593, 572, 102, 116, 167] 2.426089 \n55 [225, 400, 593, 572, 217, 102, 116, 136] 2.424517 \n56 [593, 217, 102, 116, 136, 167] 2.421183 \n57 [225, 400, 593, 572, 217, 102, 136, 167] 2.419173 \n58 [400, 593, 572, 217, 116, 136, 167] 2.418623 \n59 [225, 400, 593, 572, 102, 116, 167] 2.415783 \n60 [308, 225, 400, 217, 102, 116, 136, 167] 2.415490 \n61 [308, 225, 593, 217, 102, 116, 136, 167] 2.414755 \n62 [308, 225, 593, 572, 217, 102, 116, 136, 167] 2.414030 \n63 [308, 400, 572, 217, 102, 116, 136, 167] 2.409487 \n64 [225, 400, 593, 217, 116, 136, 167] 2.409265 \n65 [308, 225, 593, 572, 102, 116, 136, 167] 2.407014 \n66 [225, 400, 593, 572, 116, 136, 167] 2.406138 \n67 [308, 593, 217, 102, 116, 136, 167] 2.401655 \n68 [593, 572, 217, 102, 136, 167] 2.398830 \n69 [308, 225, 400, 572, 102, 116, 136, 167] 2.394522 \n70 [225, 572, 217, 102, 116, 136, 167] 2.392434 \n71 [308, 400, 102, 116, 136, 167] 2.390099 \n72 [400, 593, 217, 239, 102, 116, 136, 167] 2.387871 \n73 [308, 225, 593, 102, 116, 136, 167] 2.385140 \n74 [308, 400, 572, 102, 116, 136, 167] 2.382973 \n75 [308, 225, 400, 572, 217, 102, 116, 136, 167] 2.382493 \n76 [225, 400, 593, 572, 217, 102, 116, 167] 2.380709 \n77 [593, 572, 217, 102, 116, 136] 2.369744 \n78 [308, 225, 400, 593, 102, 116, 136] 2.369537 \n79 [308, 400, 593, 217, 102, 116, 136] 2.368855 \n80 [400, 593, 219, 102, 116, 136, 167] 2.368734 \n81 [225, 400, 593, 572, 217, 116, 136, 167] 2.363019 \n82 [225, 593, 102, 116, 136, 167] 2.362896 \n83 [225, 593, 572, 217, 102, 136, 167] 2.359048 \n84 [308, 400, 593, 102, 116, 136] 2.357948 \n85 [400, 217, 102, 116, 136] 2.356903 \n86 [308, 400, 593, 217, 102, 136, 167] 2.354747 \n87 [308, 593, 572, 102, 116, 136, 167] 2.353576 \n88 [400, 217, 102, 136, 167] 2.352880 \n89 [572, 217, 102, 116, 136, 167] 2.352845 \n90 [593, 572, 217, 102, 116, 167] 2.350716 \n91 [308, 225, 400, 593, 102, 136, 167] 2.349383 \n92 [225, 593, 572, 217, 102, 116, 136] 2.347418 \n93 [400, 593, 572, 217, 239, 102, 116, 136, 167] 2.347043 \n94 [400, 572, 217, 102, 136, 167] 2.345758 \n95 [308, 225, 400, 593, 217, 102, 116, 136] 2.345284 \n96 [400, 572, 217, 102, 116, 136] 2.343262 \n97 [225, 400, 593, 217, 239, 102, 116, 136, 167] 2.342601 \n98 [400, 593, 572, 219, 102, 116, 136, 167] 2.342369 \n99 [308, 400, 593, 572, 217, 102, 116, 136] 2.341743 \n100 [225, 400, 217, 102, 116, 136] 2.339735 \n101 [225, 400, 593, 219, 102, 116, 136, 167] 2.339673 \n102 [225, 400, 102, 116, 136] 2.339648 \n103 [400, 593, 219, 217, 102, 116, 136, 167] 2.339263 \n104 [400, 217, 102, 116, 167] 2.337173 \n105 [308, 400, 593, 572, 102, 116, 136] 2.335948 \n106 [308, 400, 593, 102, 136, 167] 2.335613 \n107 [308, 225, 400, 593, 572, 102, 116, 136] 2.333519 \n108 [308, 400, 593, 572, 217, 102, 136, 167] 2.332582 \n109 [308, 225, 400, 593, 217, 102, 136, 167] 2.331666 \n110 [225, 400, 217, 102, 136, 167] 2.331114 \n111 [593, 572, 217, 116, 136, 167] 2.330560 \n112 [225, 400, 593, 239, 102, 116, 136, 167] 2.329481 \n113 [400, 593, 239, 102, 116, 136, 167] 2.329251 \n114 [593, 572, 102, 116, 136, 167] 2.329008 \n115 [225, 400, 102, 116, 167] 2.326799 \n116 [308, 225, 400, 593, 102, 116, 167] 2.324378 \n117 [225, 593, 572, 102, 136, 167] 2.323503 \n118 [225, 593, 572, 217, 102, 116, 167] 2.322624 \n119 [308, 400, 593, 217, 102, 116, 167] 2.322179 \n120 [225, 400, 102, 136, 167] 2.321749 \n121 [593, 217, 239, 102, 116, 136, 167] 2.321594 \n122 [308, 400, 593, 572, 102, 136, 167] 2.321514 \n123 [225, 593, 217, 102, 136, 167] 2.320093 \n124 [308, 225, 400, 593, 572, 102, 136, 167] 2.319592 \n125 [593, 572, 217, 239, 102, 116, 136, 167] 2.317479 \n126 [400, 593, 572, 219, 217, 102, 116, 136, 167] 2.316782 \n127 [308, 225, 400, 593, 116, 136, 167] 2.316549 \n128 [225, 593, 217, 102, 116, 167] 2.316339 \n129 [225, 400, 217, 102, 116, 167] 2.315622 \n130 [308, 225, 400, 593, 572, 217, 102, 116, 136] 2.314922 \n131 [308, 225, 572, 217, 102, 116, 136, 167] 2.314761 \n132 [225, 593, 217, 102, 116, 136] 2.314048 \n133 [225, 400, 572, 102, 116, 136] 2.312733 \n134 [225, 593, 572, 102, 116, 136] 2.312411 \n135 [308, 400, 593, 217, 239, 102, 116, 136, 167] 2.311238 \n136 [308, 400, 593, 217, 116, 136, 167] 2.311123 \n137 [400, 217, 116, 136, 167] 2.310622 \n138 [225, 217, 102, 116, 136, 167] 2.310002 \n139 [225, 400, 593, 572, 219, 102, 116, 136, 167] 2.309497 \n140 [225, 400, 572, 217, 102, 116, 136] 2.308930 \n141 [308, 572, 217, 102, 116, 136, 167] 2.308234 \n142 [225, 400, 116, 136, 167] 2.307549 \n143 [308, 400, 593, 102, 116, 167] 2.307477 \n144 [308, 400, 593, 116, 136, 167] 2.305973 \n145 [225, 400, 572, 217, 102, 136, 167] 2.305593 \n146 [308, 225, 400, 593, 572, 217, 102, 136, 167] 2.305311 \n147 [225, 400, 593, 572, 217, 239, 102, 116, 136, ... 2.304782 \n148 [308, 225, 400, 593, 217, 102, 116, 167] 2.304768 \n149 [225, 400, 572, 102, 136, 167] 2.304758 \n150 [308, 225, 217, 102, 116, 136, 167] 2.304136 \n151 [400, 572, 217, 102, 116, 167] 2.302926 \n152 [225, 593, 572, 102, 116, 167] 2.301777 \n153 [400, 593, 572, 239, 102, 116, 136, 167] 2.301744 \n154 [225, 400, 593, 219, 217, 102, 116, 136, 167] 2.298320 \n155 [225, 593, 572, 217, 116, 136, 167] 2.296965 \n156 [400, 593, 217, 102, 136] 2.296866 \n157 [308, 400, 593, 572, 217, 102, 116, 167] 2.292399 \n158 [225, 400, 593, 572, 239, 102, 116, 136, 167] 2.291723 \n159 [400, 219, 102, 116, 136, 167] 2.291196 \n160 [308, 225, 400, 593, 217, 116, 136, 167] 2.291087 \n161 [225, 593, 572, 116, 136, 167] 2.290158 \n162 [225, 593, 217, 239, 102, 116, 136, 167] 2.289624 \n163 [225, 593, 217, 116, 136, 167] 2.287367 \n164 [225, 400, 217, 116, 136, 167] 2.286910 \n165 [308, 225, 400, 593, 572, 102, 116, 167] 2.285602 \n166 [225, 400, 593, 102, 136] 2.284091 \n167 [308, 400, 593, 239, 102, 116, 136, 167] 2.283750 \n168 [308, 225, 400, 593, 217, 239, 102, 116, 136, ... 2.283475 \n169 [308, 400, 593, 572, 217, 116, 136, 167] 2.281444 \n170 [308, 400, 593, 572, 102, 116, 167] 2.280681 \n171 [593, 217, 102, 116, 167] 2.280215 \n172 [308, 225, 400, 593, 239, 102, 116, 136, 167] 2.279368 \n173 [400, 572, 217, 116, 136, 167] 2.279351 \n174 [308, 400, 593, 572, 217, 239, 102, 116, 136, ... 2.277324 \n175 [225, 400, 572, 102, 116, 167] 2.277280 \n176 [308, 225, 400, 593, 572, 116, 136, 167] 2.277127 \n177 [308, 400, 593, 572, 116, 136, 167] 2.276774 \n178 [225, 400, 593, 572, 219, 217, 102, 116, 136, ... 2.276153 \n179 [400, 593, 572, 217, 102, 136] 2.275224 \n180 [593, 572, 219, 102, 116, 136, 167] 2.274362 \n181 [308, 593, 217, 239, 102, 116, 136, 167] 2.273618 \n182 [308, 225, 572, 102, 116, 136, 167] 2.273416 \n183 [593, 572, 219, 217, 102, 116, 136, 167] 2.273299 \n184 [225, 400, 572, 217, 102, 116, 167] 2.272822 \n185 [308, 225, 400, 593, 572, 217, 102, 116, 167] 2.272668 \n186 [593, 217, 102, 136, 167] 2.272380 \n187 [225, 593, 572, 217, 239, 102, 116, 136, 167] 2.272303 \n188 [400, 219, 217, 102, 116, 136, 167] 2.271875 \n189 [400, 572, 102, 116, 136] 2.271759 \n190 [225, 400, 219, 102, 116, 136, 167] 2.270309 \n191 [225, 400, 593, 102, 116] 2.268882 \n192 [400, 572, 102, 136, 167] 2.268047 \n193 [400, 593, 217, 102, 116] 2.266655 \n194 [308, 593, 572, 217, 102, 136, 167] 2.264980 \n195 [308, 593, 572, 217, 102, 116, 136] 2.264680 \n196 [400, 572, 219, 102, 116, 136, 167] 2.264048 \n197 [308, 593, 102, 116, 136, 167] 2.260859 \n198 [225, 400, 593, 217, 102, 136] 2.260355 \n199 [308, 225, 400, 593, 572, 217, 116, 136, 167] 2.259792 \n200 [593, 217, 116, 136, 167] 2.259144 \n201 [225, 572, 102, 116, 136, 167] 2.259068 \n202 [225, 400, 572, 116, 136, 167] 2.258898 \n203 [593, 219, 217, 102, 116, 136, 167] 2.258862 \n204 [308, 400, 217, 102, 116, 136] 2.258812 \n205 [308, 400, 593, 219, 102, 116, 136, 167] 2.258097 \n206 [225, 400, 593, 116, 136] 2.257570 \n207 [308, 225, 593, 217, 102, 116, 136] 2.256475 \n208 [225, 593, 572, 219, 102, 116, 136, 167] 2.256283 \n209 [308, 225, 593, 572, 217, 102, 116, 136] 2.256102 \n210 [308, 225, 400, 102, 116, 136] 2.255699 \n211 [400, 593, 102, 136] 2.254031 \n212 [308, 217, 102, 116, 136, 167] 2.253227 \n213 [593, 217, 102, 116, 136] 2.253096 \n214 [308, 225, 400, 217, 102, 116, 136] 2.252940 \n215 [308, 593, 572, 217, 239, 102, 116, 136, 167] 2.252815 \n216 [308, 225, 593, 572, 217, 102, 136, 167] 2.252589 \n217 [400, 593, 572, 102, 136] 2.252439 \n218 [308, 400, 593, 572, 239, 102, 116, 136, 167] 2.252337 \n219 [308, 225, 400, 593, 572, 217, 239, 102, 116, ... 2.251783 \n220 [225, 593, 219, 102, 116, 136, 167] 2.251335 \n221 [225, 400, 593, 572, 102, 136] 2.250618 \n222 [400, 217, 239, 102, 116, 136, 167] 2.249583 \n223 [400, 593, 217, 116, 136] 2.249361 \n224 [308, 225, 593, 217, 239, 102, 116, 136, 167] 2.249284 \n225 [400, 572, 219, 217, 102, 116, 136, 167] 2.248856 \n226 [308, 225, 400, 593, 219, 102, 116, 136, 167] 2.248730 \n227 [308, 225, 593, 217, 102, 136, 167] 2.248527 \n228 [225, 400, 572, 217, 116, 136, 167] 2.247976 \n229 [308, 400, 593, 219, 217, 102, 116, 136, 167] 2.246897 \n230 [225, 593, 102, 116, 167] 2.246520 \n231 [308, 400, 217, 102, 136, 167] 2.245420 \n232 [308, 225, 400, 593, 572, 239, 102, 116, 136, ... 2.245051 \n233 [308, 225, 593, 572, 102, 116, 136] 2.244043 \n234 [400, 593, 116, 136] 2.243982 \n235 [400, 593, 102, 116] 2.241564 \n236 [308, 225, 400, 217, 102, 136, 167] 2.239686 \n237 [308, 400, 593, 572, 219, 102, 116, 136, 167] 2.239225 \n238 [308, 593, 217, 102, 116, 136] 2.239225 \n239 [308, 400, 572, 217, 102, 116, 136] 2.239046 \n240 [225, 400, 572, 219, 102, 116, 136, 167] 2.238627 \n241 [400, 593, 217, 102, 167] 2.237901 \n242 [400, 572, 102, 116, 167] 2.237875 \n243 [225, 593, 116, 136, 167] 2.237124 \n244 [308, 225, 593, 572, 102, 136, 167] 2.236733 \n245 [225, 400, 593, 217, 102, 116] 2.236478 \n246 [593, 219, 102, 116, 136, 167] 2.235798 \n247 [308, 225, 400, 102, 136, 167] 2.235464 \n248 [225, 400, 219, 217, 102, 116, 136, 167] 2.234376 \n249 [308, 593, 217, 102, 136, 167] 2.233850 \n250 [225, 400, 593, 572, 217, 102, 136] 2.233732 \n251 [400, 102, 116, 167] 2.232358 \n252 [225, 593, 572, 219, 217, 102, 116, 136, 167] 2.231657 \n253 [308, 400, 572, 217, 102, 136, 167] 2.230854 \n254 [225, 593, 219, 217, 102, 116, 136, 167] 2.230281 \n255 [308, 400, 593, 572, 219, 217, 102, 116, 136, ... 2.230276 \n256 [225, 400, 593, 102, 167] 2.228935 \n257 [400, 593, 572, 217, 102, 116] 2.228703 \n258 [308, 225, 593, 102, 116, 136] 2.228656 \n259 [225, 400, 217, 239, 102, 116, 136, 167] 2.227941 \n260 [400, 102, 116, 136] 2.227912 \n261 [400, 572, 116, 136, 167] 2.227651 \n262 [308, 225, 400, 593, 219, 217, 102, 116, 136, ... 2.227173 \n263 [308, 225, 102, 116, 136, 167] 2.227035 \n264 [308, 225, 400, 593, 572, 219, 102, 116, 136, ... 2.226914 \n265 [308, 225, 400, 572, 102, 116, 136] 2.226689 \n266 [308, 225, 400, 572, 217, 102, 116, 136] 2.226657 \n267 [308, 225, 593, 217, 102, 116, 167] 2.226193 \n268 [400, 116, 136, 167] 2.225774 \n269 [308, 225, 593, 572, 217, 239, 102, 116, 136, ... 2.225771 \n270 [308, 593, 572, 217, 102, 116, 167] 2.221343 \n271 [400, 572, 217, 239, 102, 116, 136, 167] 2.220788 \n272 [400, 593, 217, 136, 167] 2.220235 \n273 [308, 400, 217, 102, 116, 167] 2.218515 \n274 [308, 225, 593, 239, 102, 116, 136, 167] 2.218166 \n275 [308, 225, 593, 572, 217, 102, 116, 167] 2.217863 \n276 [308, 225, 400, 572, 217, 102, 136, 167] 2.217617 \n277 [308, 225, 400, 102, 116, 167] 2.217590 \n278 [225, 400, 593, 136, 167] 2.217063 \n279 [308, 225, 400, 217, 102, 116, 167] 2.217000 \n280 [225, 400, 593, 116, 167] 2.216807 \n281 [225, 593, 572, 239, 102, 116, 136, 167] 2.216337 \n282 [225, 400, 593, 217, 116, 136] 2.215648 \n283 [225, 400, 593, 572, 102, 116] 2.215323 \n284 [308, 225, 593, 102, 136, 167] 2.213891 \n285 [308, 225, 400, 572, 102, 136, 167] 2.213166 \n286 [308, 400, 217, 239, 102, 116, 136, 167] 2.212705 \n287 [400, 593, 572, 217, 116, 136] 2.212227 \n288 [225, 400, 572, 219, 217, 102, 116, 136, 167] 2.212029 \n289 [225, 400, 593, 217, 102, 167] 2.211868 \n290 [400, 593, 572, 217, 102, 167] 2.210591 \n291 [400, 102, 136, 167] 2.210323 \n292 [308, 225, 400, 593, 572, 219, 217, 102, 116, ... 2.209953 \n293 [308, 400, 102, 116, 136] 2.209900 \n294 [225, 593, 239, 102, 116, 136, 167] 2.208720 \n295 [308, 593, 217, 102, 116, 167] 2.208539 \n296 [225, 593, 102, 116, 136] 2.208064 \n297 [308, 225, 593, 217, 116, 136, 167] 2.207953 \n298 [400, 593, 572, 102, 116] 2.207611 \n299 [308, 593, 572, 217, 116, 136, 167] 2.207359 \n300 [225, 593, 102, 136, 167] 2.206437 \n301 [400, 593, 217, 116, 167] 2.205428 \n302 [308, 225, 400, 116, 136, 167] 2.204000 \n303 [308, 225, 593, 572, 102, 116, 167] 2.203942 \n304 [400, 593, 572, 116, 136] 2.203790 \n305 [308, 400, 572, 102, 116, 136] 2.203340 \n306 [225, 400, 593, 572, 116, 136] 2.203026 \n307 [308, 225, 593, 102, 116, 167] 2.202017 \n308 [308, 400, 217, 116, 136, 167] 2.201455 \n309 [400, 593, 116, 167] 2.201297 \n310 [400, 593, 217, 239, 102, 116, 136] 2.201072 \n311 [308, 225, 593, 572, 217, 116, 136, 167] 2.201031 \n312 [225, 572, 217, 102, 136, 167] 2.200572 \n313 [308, 225, 593, 572, 239, 102, 116, 136, 167] 2.199680 \n314 [572, 219, 217, 102, 116, 136, 167] 2.199069 \n315 [225, 400, 593, 572, 217, 102, 116] 2.198722 \n316 [308, 225, 400, 217, 116, 136, 167] 2.198333 \n317 [225, 400, 572, 217, 239, 102, 116, 136, 167] 2.197712 \n318 [308, 225, 400, 217, 239, 102, 116, 136, 167] 2.197554 \n319 [308, 593, 217, 116, 136, 167] 2.194212 \n320 [308, 400, 572, 217, 102, 116, 167] 2.193956 \n321 [308, 225, 593, 572, 116, 136, 167] 2.193903 \n322 [400, 593, 572, 217, 136, 167] 2.193849 \n323 [400, 593, 219, 102, 116, 136] 2.193278 \n324 [308, 225, 593, 116, 136, 167] 2.192902 \n325 [400, 593, 136, 167] 2.192217 \n326 [400, 593, 102, 167] 2.191150 \n327 [225, 400, 593, 217, 136, 167] 2.190834 \n328 [308, 593, 239, 102, 116, 136, 167] 2.190734 \n329 [308, 593, 572, 239, 102, 116, 136, 167] 2.190152 \n330 [308, 400, 572, 102, 136, 167] 2.189594 \n331 [225, 400, 593, 572, 102, 167] 2.189358 \n332 [308, 593, 572, 102, 116, 136] 2.188851 \n333 [308, 400, 219, 102, 116, 136, 167] 2.188674 \n334 [308, 400, 593, 217, 102, 136] 2.188118 \n335 [593, 572, 102, 136, 167] 2.187933 \n336 [308, 400, 102, 136, 167] 2.187604 \n337 [308, 225, 400, 572, 217, 102, 116, 167] 2.187602 \n338 [308, 225, 400, 219, 102, 116, 136, 167] 2.186656 \n339 [308, 400, 219, 217, 102, 116, 136, 167] 2.185868 \n340 [400, 593, 217, 239, 102, 136, 167] 2.185252 \n341 [308, 225, 400, 593, 102, 136] 2.184740 \n342 [308, 593, 572, 102, 136, 167] 2.184099 \n343 [308, 400, 572, 217, 239, 102, 116, 136, 167] 2.183807 \n344 [308, 593, 572, 219, 217, 102, 116, 136, 167] 2.183533 \n345 [308, 225, 400, 572, 102, 116, 167] 2.183478 \n346 [572, 219, 102, 116, 136, 167] 2.183138 \n347 [225, 572, 217, 102, 116, 136] 2.182002 \n348 [225, 400, 593, 572, 217, 102, 167] 2.181830 \n349 [593, 572, 116, 136, 167] 2.181302 \n350 [593, 572, 239, 102, 116, 136, 167] 2.181098 \n351 [308, 593, 219, 217, 102, 116, 136, 167] 2.180767 \n352 [572, 217, 102, 136, 167] 2.180764 \n353 [219, 217, 102, 116, 136, 167] 2.180408 \n354 [225, 400, 593, 572, 217, 116, 136] 2.179980 \n355 [225, 400, 239, 102, 116, 136, 167] 2.179876 \n356 [308, 225, 593, 219, 102, 116, 136, 167] 2.179490 \n357 [593, 572, 217, 102, 136] 2.179034 \n358 [225, 400, 593, 219, 102, 116, 136] 2.178827 \n359 [308, 225, 400, 593, 217, 102, 136] 2.178707 \n360 [308, 400, 572, 217, 116, 136, 167] 2.178139 \n361 [225, 400, 593, 217, 116, 167] 2.177669 \n362 [400, 593, 219, 217, 102, 116, 136] 2.177334 \n363 [400, 593, 572, 102, 167] 2.177294 \n364 [225, 572, 217, 102, 116, 167] 2.177094 \n365 [225, 400, 593, 572, 136, 167] 2.176748 \n366 [308, 593, 572, 219, 102, 116, 136, 167] 2.176209 \n367 [308, 225, 593, 572, 219, 102, 116, 136, 167] 2.175828 \n368 [225, 572, 219, 102, 116, 136, 167] 2.175802 \n369 [225, 400, 593, 217, 239, 102, 116, 136] 2.175259 \n370 [308, 225, 400, 239, 102, 116, 136, 167] 2.174948 \n371 [593, 572, 102, 116, 167] 2.174591 \n372 [400, 593, 572, 219, 102, 116, 136] 2.172958 \n373 [400, 593, 572, 136, 167] 2.172927 \n374 [308, 400, 593, 572, 217, 102, 136] 2.172034 \n375 [400, 593, 572, 217, 239, 102, 116, 136] 2.170807 \n376 [308, 225, 400, 572, 217, 116, 136, 167] 2.170672 \n377 [308, 225, 400, 219, 217, 102, 116, 136, 167] 2.170431 \n378 [308, 225, 593, 219, 217, 102, 116, 136, 167] 2.170370 \n379 [308, 225, 400, 572, 116, 136, 167] 2.170329 \n380 [308, 400, 572, 219, 102, 116, 136, 167] 2.170261 \n381 [308, 400, 102, 116, 167] 2.169806 \n382 [308, 400, 572, 219, 217, 102, 116, 136, 167] 2.169559 \n383 [308, 225, 400, 572, 217, 239, 102, 116, 136, ... 2.169306 \n384 [225, 219, 102, 116, 136, 167] 2.168190 \n385 [400, 593, 219, 102, 136, 167] 2.168060 \n386 [308, 225, 593, 572, 219, 217, 102, 116, 136, ... 2.166577 \n387 [308, 593, 219, 102, 116, 136, 167] 2.165621 \n388 [308, 572, 102, 116, 136, 167] 2.165222 \n389 [308, 225, 400, 572, 219, 102, 116, 136, 167] 2.164623 \n390 [593, 572, 102, 116, 136] 2.164414 \n391 [225, 400, 593, 572, 217, 136, 167] 2.162902 \n392 [400, 593, 572, 219, 217, 102, 116, 136] 2.161780 \n393 [308, 400, 116, 136, 167] 2.161599 \n394 [308, 400, 593, 217, 239, 102, 116, 136] 2.161274 \n395 [308, 225, 400, 593, 102, 116] 2.161186 \n396 [308, 225, 400, 593, 572, 102, 136] 2.160970 \n397 [400, 593, 572, 217, 116, 167] 2.160817 \n398 [400, 593, 217, 239, 116, 136, 167] 2.160537 \n399 [308, 400, 593, 102, 136] 2.160490 \n400 [400, 593, 219, 217, 102, 136, 167] 2.160338 \n401 [225, 400, 593, 217, 239, 102, 136, 167] 2.160319 \n402 [400, 593, 572, 217, 239, 102, 136, 167] 2.160197 \n403 [225, 572, 219, 217, 102, 116, 136, 167] 2.159763 \n404 [308, 225, 400, 593, 572, 217, 102, 136] 2.158962 \n405 [308, 400, 593, 217, 102, 116] 2.157751 \n406 [308, 400, 239, 102, 116, 136, 167] 2.157584 \n407 [225, 400, 593, 219, 102, 136, 167] 2.156935 \n408 [225, 400, 572, 239, 102, 116, 136, 167] 2.156410 \n409 [225, 219, 217, 102, 116, 136, 167] 2.156241 \n410 [400, 593, 217, 239, 102, 116, 167] 2.156163 \n411 [225, 400, 593, 572, 219, 102, 116, 136] 2.155700 \n412 [400, 593, 572, 219, 102, 136, 167] 2.155325 \n413 [308, 400, 572, 102, 116, 167] 2.154775 \n414 [572, 217, 102, 116, 167] 2.154620 \n415 [225, 400, 593, 572, 116, 167] 2.154039 \n416 [308, 225, 400, 593, 217, 102, 116] 2.153768 \n417 [308, 225, 400, 572, 219, 217, 102, 116, 136, ... 2.153418 \n418 [225, 593, 572, 217, 102, 136] 2.152933 \n419 [225, 400, 593, 219, 217, 102, 116, 136] 2.151566 \n420 [308, 225, 400, 593, 116, 136] 2.151448 \n421 [308, 400, 593, 572, 102, 136] 2.149819 \n422 [400, 593, 572, 219, 217, 102, 136, 167] 2.149518 \n423 [225, 400, 593, 239, 102, 116, 136] 2.149212 \n424 [308, 217, 239, 102, 116, 136, 167] 2.148394 \n425 [225, 400, 593, 572, 217, 239, 102, 116, 136] 2.147143 \n426 [308, 593, 572, 102, 116, 167] 2.146784 \n427 [225, 217, 102, 116, 167] 2.146740 \n428 [308, 225, 400, 593, 217, 239, 102, 116, 136] 2.146527 \n429 [308, 225, 400, 572, 239, 102, 116, 136, 167] 2.146500 \n430 [400, 593, 572, 116, 167] 2.145754 \n431 [308, 400, 593, 217, 239, 102, 136, 167] 2.145550 \n432 [308, 400, 572, 116, 136, 167] 2.145388 \n433 [308, 400, 593, 217, 116, 136] 2.145077 \n434 [572, 217, 239, 102, 116, 136, 167] 2.144777 \n435 [308, 225, 217, 239, 102, 116, 136, 167] 2.144262 \n436 [308, 593, 572, 116, 136, 167] 2.144214 \n437 [308, 225, 572, 217, 102, 116, 136] 2.143902 \n438 [308, 225, 572, 217, 102, 136, 167] 2.142517 \n439 [225, 400, 593, 572, 219, 102, 136, 167] 2.139573 \n440 [308, 225, 400, 593, 217, 116, 136] 2.139140 \n441 [572, 217, 102, 116, 136] 2.139133 \n442 [225, 572, 217, 116, 136, 167] 2.137901 \n443 [308, 572, 217, 239, 102, 116, 136, 167] 2.137466 \n444 [225, 400, 593, 572, 217, 116, 167] 2.137397 \n445 [225, 400, 593, 217, 239, 102, 116, 167] 2.137169 \n446 [225, 400, 593, 572, 217, 239, 102, 136, 167] 2.136356 \n447 [225, 400, 593, 572, 219, 217, 102, 116, 136] 2.136047 \n448 [225, 400, 593, 219, 217, 102, 136, 167] 2.136021 \n449 [308, 400, 572, 239, 102, 116, 136, 167] 2.135960 \n450 [308, 400, 593, 572, 217, 239, 102, 116, 136] 2.135096 \n451 [308, 400, 593, 572, 217, 102, 116] 2.135031 \n452 [225, 400, 593, 217, 239, 116, 136, 167] 2.134633 \n453 [225, 217, 239, 102, 116, 136, 167] 2.134433 \n454 [400, 239, 102, 116, 136, 167] 2.134154 \n455 [225, 572, 217, 239, 102, 116, 136, 167] 2.133859 \n456 [308, 400, 593, 217, 102, 167] 2.133741 \n457 [308, 400, 593, 102, 116] 2.133486 \n458 [308, 225, 400, 593, 217, 102, 167] 2.132777 \n459 [400, 593, 239, 102, 116, 136] 2.132591 \n460 [308, 225, 217, 102, 116, 136] 2.132448 \n461 [308, 225, 400, 593, 239, 102, 116, 136] 2.132442 \n462 [400, 572, 239, 102, 116, 136, 167] 2.132256 \n463 [308, 225, 400, 593, 217, 239, 102, 136, 167] 2.132080 \n464 [308, 225, 400, 593, 102, 167] 2.131481 \n465 [219, 102, 116, 136, 167] 2.131075 \n466 [593, 572, 217, 102, 116] 2.130640 \n467 [308, 572, 217, 102, 136, 167] 2.129723 \n468 [308, 225, 400, 593, 572, 102, 116] 2.129514 \n469 [308, 400, 593, 116, 136] 2.129058 \n470 [308, 225, 400, 593, 572, 217, 102, 116] 2.128897 \n471 [400, 593, 219, 102, 116, 167] 2.128166 \n472 [225, 400, 593, 239, 102, 136, 167] 2.127439 \n473 [308, 225, 572, 217, 239, 102, 116, 136, 167] 2.126843 \n474 [308, 225, 217, 102, 136, 167] 2.126550 \n475 [593, 572, 217, 102, 167] 2.126512 \n476 [217, 102, 116, 136, 167] 2.126242 \n477 [308, 572, 217, 102, 116, 136] 2.125874 \n478 [225, 400, 593, 219, 102, 116, 167] 2.125376 \n479 [400, 593, 572, 217, 239, 116, 136, 167] 2.124762 \n480 [225, 217, 102, 136, 167] 2.124616 \n481 [308, 400, 593, 239, 102, 116, 136] 2.124541 \n482 [225, 400, 593, 572, 219, 217, 102, 136, 167] 2.124256 \n483 [400, 593, 572, 217, 239, 102, 116, 167] 2.123879 \n484 [400, 593, 219, 217, 102, 116, 167] 2.123357 \n485 [308, 400, 593, 572, 217, 239, 102, 136, 167] 2.123251 \n486 [308, 400, 593, 572, 217, 116, 136] 2.122837 \n487 [308, 225, 400, 593, 572, 217, 239, 102, 116, ... 2.121861 \n488 [308, 225, 400, 593, 136, 167] 2.121472 \n489 [225, 400, 593, 572, 239, 102, 116, 136] 2.121256 \n490 [308, 400, 593, 217, 136, 167] 2.120870 \n491 [400, 593, 219, 217, 239, 102, 116, 136, 167] 2.119997 \n492 [308, 225, 400, 593, 572, 116, 136] 2.119572 \n493 [225, 400, 217, 102, 136] 2.118817 \n494 [225, 593, 217, 102, 136] 2.118621 \n495 [225, 593, 572, 217, 102, 116] 2.118337 \n496 [308, 225, 400, 593, 217, 136, 167] 2.118034 \n497 [217, 239, 102, 116, 136, 167] 2.118021 \n498 [308, 225, 400, 593, 219, 102, 116, 136] 2.117863 \n499 [308, 400, 593, 217, 239, 116, 136, 167] 2.117782 \n500 [308, 400, 593, 217, 239, 102, 116, 167] 2.117512 \n501 [308, 400, 593, 572, 217, 102, 167] 2.117446 \n502 [308, 400, 593, 219, 102, 116, 136] 2.117090 \n503 [400, 572, 217, 102, 136] 2.117062 \n504 [400, 217, 102, 136] 2.116898 \n505 [225, 593, 572, 102, 136] 2.115813 \n506 [308, 400, 593, 219, 217, 102, 116, 136] 2.115701 \n507 [593, 217, 239, 102, 116, 136] 2.115664 \n508 [572, 217, 116, 136, 167] 2.115607 \n509 [308, 572, 219, 217, 102, 116, 136, 167] 2.115378 \n510 [308, 225, 400, 593, 572, 217, 116, 136] 2.115302 \n511 [225, 400, 593, 239, 116, 136, 167] 2.115282 \n512 [593, 572, 217, 239, 102, 116, 136] 2.115066 \n513 [593, 572, 217, 239, 102, 136, 167] 2.114737 \n514 [593, 239, 102, 116, 136, 167] 2.113986 \n515 [400, 593, 572, 239, 102, 116, 136] 2.113698 \n516 [308, 225, 400, 593, 239, 102, 136, 167] 2.113098 \n517 [225, 593, 217, 102, 116] 2.113059 \n518 [308, 225, 400, 593, 572, 217, 102, 167] 2.112926 \n519 [308, 225, 217, 102, 116, 167] 2.112707 \n520 [308, 225, 572, 217, 102, 116, 167] 2.112434 \n521 [308, 400, 593, 572, 102, 116] 2.111825 \n522 [225, 217, 102, 116, 136] 2.111635 \n523 [308, 593, 102, 116, 136] 2.110894 \n524 [308, 225, 400, 593, 572, 217, 239, 102, 136, ... 2.110584 \n525 [308, 219, 217, 102, 116, 136, 167] 2.110462 \n526 [593, 217, 239, 102, 136, 167] 2.110017 \n527 [400, 593, 572, 219, 102, 116, 167] 2.109048 \n528 [308, 225, 400, 593, 217, 239, 102, 116, 167] 2.108890 \n529 [225, 593, 572, 217, 102, 167] 2.108503 \n530 [400, 593, 572, 219, 217, 102, 116, 167] 2.108398 \n531 [225, 400, 593, 239, 102, 116, 167] 2.108396 \n532 [400, 593, 239, 102, 136, 167] 2.107869 \n533 [308, 225, 400, 593, 572, 102, 167] 2.107613 \n534 [225, 400, 593, 572, 217, 239, 102, 116, 167] 2.107595 \n535 [308, 225, 219, 102, 116, 136, 167] 2.107374 \n536 [400, 593, 219, 116, 136, 167] 2.106799 \n537 [225, 400, 593, 219, 217, 102, 116, 167] 2.106742 \n538 [308, 225, 400, 593, 116, 167] 2.106459 \n539 [593, 572, 217, 116, 136] 2.106441 \n540 [308, 225, 400, 593, 219, 217, 102, 116, 136] 2.106050 \n541 [308, 225, 219, 217, 102, 116, 136, 167] 2.105916 \n542 [225, 400, 593, 572, 239, 102, 136, 167] 2.105863 \n543 [308, 593, 217, 239, 102, 116, 136] 2.105856 \n544 [308, 225, 400, 593, 572, 239, 102, 116, 136] 2.105626 \n545 [308, 400, 593, 572, 116, 136] 2.105606 \n546 [308, 225, 400, 593, 217, 239, 116, 136, 167] 2.105452 \n547 [400, 593, 239, 116, 136, 167] 2.105292 \n548 [308, 400, 593, 572, 217, 136, 167] 2.105104 \n549 [308, 225, 572, 219, 102, 116, 136, 167] 2.104995 \n550 [225, 400, 217, 102, 116] 2.104554 \n551 [225, 400, 572, 217, 102, 136] 2.104290 \n552 [308, 400, 593, 572, 219, 217, 102, 116, 136] 2.104253 \n553 [225, 400, 593, 219, 116, 136, 167] 2.103798 \n554 [225, 400, 593, 572, 217, 239, 116, 136, 167] 2.103641 \n555 [308, 400, 593, 572, 219, 102, 116, 136] 2.103419 \n556 [308, 225, 572, 219, 217, 102, 116, 136, 167] 2.103319 \n557 [225, 400, 593, 572, 219, 102, 116, 167] 2.103056 \n558 [308, 400, 593, 239, 102, 136, 167] 2.102751 \n559 [400, 593, 572, 219, 217, 239, 102, 116, 136, ... 2.102336 \n560 [400, 593, 219, 239, 102, 116, 136, 167] 2.101766 \n561 [593, 572, 217, 136, 167] 2.101744 \n562 [400, 217, 102, 116] 2.101587 \n563 [593, 217, 239, 116, 136, 167] 2.101368 \n564 [308, 225, 400, 593, 572, 219, 102, 116, 136] 2.101362 \n565 [225, 593, 217, 239, 102, 116, 136] 2.101351 \n566 [308, 400, 593, 572, 239, 102, 116, 136] 2.100685 \n567 [308, 400, 593, 219, 217, 102, 136, 167] 2.099963 \n568 [308, 225, 400, 593, 217, 116, 167] 2.099843 \n569 [225, 400, 593, 219, 217, 239, 102, 116, 136, ... 2.099833 \n570 [400, 593, 219, 217, 116, 136, 167] 2.099832 \n571 [225, 217, 116, 136, 167] 2.099567 \n572 [308, 400, 593, 217, 116, 167] 2.099339 \n573 [308, 225, 400, 593, 572, 217, 136, 167] 2.099228 \n574 [593, 572, 219, 217, 102, 116, 136] 2.099080 \n575 [308, 225, 400, 593, 219, 102, 136, 167] 2.099072 \n576 [308, 400, 593, 102, 167] 2.098293 \n577 [308, 225, 400, 593, 572, 136, 167] 2.097492 \n578 [400, 593, 572, 239, 102, 136, 167] 2.097280 \n579 [308, 225, 572, 102, 116, 136] 2.096814 \n580 [225, 400, 102, 116] 2.096659 \n581 [400, 219, 102, 116, 136] 2.096445 \n582 [308, 593, 102, 136, 167] 2.096044 \n583 [308, 400, 593, 219, 102, 136, 167] 2.095909 \n584 [308, 225, 593, 217, 239, 102, 116, 136] 2.095742 \n585 [308, 572, 219, 102, 116, 136, 167] 2.095689 \n586 [225, 400, 593, 219, 239, 102, 116, 136, 167] 2.094579 \n587 [400, 219, 217, 102, 116, 136] 2.094057 \n588 [225, 400, 219, 102, 116, 136] 2.093727 \n589 [308, 225, 400, 593, 572, 219, 217, 102, 116, ... 2.093720 \n590 [225, 593, 217, 102, 167] 2.093450 \n591 [308, 400, 593, 136, 167] 2.093344 \n592 [225, 400, 102, 136] 2.093275 \n593 [308, 593, 217, 239, 102, 136, 167] 2.093226 \n594 [308, 225, 400, 593, 239, 116, 136, 167] 2.092823 \n595 [308, 572, 217, 102, 116, 167] 2.092497 \n596 [593, 572, 219, 217, 102, 136, 167] 2.092424 \n597 [225, 593, 572, 102, 116] 2.092021 \n598 [225, 593, 217, 239, 102, 136, 167] 2.091903 \n599 [308, 400, 593, 572, 219, 217, 102, 136, 167] 2.091887 \n600 [308, 400, 593, 572, 217, 239, 102, 116, 167] 2.091792 \n601 [308, 225, 572, 102, 136, 167] 2.091706 \n602 [308, 225, 400, 593, 219, 217, 102, 136, 167] 2.091689 \n603 [225, 593, 572, 217, 239, 102, 116, 136] 2.091559 \n604 [225, 400, 593, 572, 219, 217, 102, 116, 167] 2.091513 \n605 [308, 593, 572, 217, 239, 102, 116, 136] 2.091305 \n606 [308, 400, 593, 219, 217, 239, 102, 116, 136, ... 2.091270 \n607 [308, 225, 400, 593, 572, 239, 102, 136, 167] 2.090803 \n608 [308, 225, 400, 593, 239, 102, 116, 167] 2.090783 \n609 [225, 593, 572, 217, 116, 136] 2.090780 \n610 [308, 593, 116, 136, 167] 2.090586 \n611 [308, 400, 593, 572, 217, 239, 116, 136, 167] 2.090387 \n612 [308, 593, 102, 116, 167] 2.090099 \n613 [400, 593, 572, 219, 116, 136, 167] 2.089899 \n614 [593, 572, 219, 102, 116, 136] 2.089537 \n615 [308, 225, 593, 572, 217, 102, 136] 2.089429 \n616 [308, 225, 572, 217, 116, 136, 167] 2.089053 \n617 [308, 593, 572, 217, 102, 136] 2.087797 \n618 [400, 593, 572, 219, 217, 116, 136, 167] 2.087495 \n619 [308, 400, 593, 572, 219, 102, 136, 167] 2.087114 \n620 [308, 400, 593, 572, 102, 167] 2.086814 \n621 [225, 593, 572, 217, 239, 102, 136, 167] 2.086615 \n622 [308, 225, 400, 593, 572, 219, 102, 136, 167] 2.086497 \n623 [308, 225, 217, 116, 136, 167] 2.086180 \n624 [400, 593, 239, 102, 116, 167] 2.086178 \n625 [593, 217, 239, 102, 116, 167] 2.085636 \n626 [225, 593, 572, 219, 102, 116, 136] 2.085181 \n627 [308, 400, 593, 239, 116, 136, 167] 2.084752 \n628 [308, 400, 593, 572, 239, 102, 136, 167] 2.084548 \n629 [225, 400, 593, 219, 217, 116, 136, 167] 2.084493 \n630 [308, 225, 400, 593, 572, 217, 239, 102, 116, ... 2.084488 \n631 [225, 400, 593, 572, 219, 217, 239, 102, 116, ... 2.083848 \n632 [400, 593, 572, 219, 239, 102, 116, 136, 167] 2.083836 \n633 [225, 400, 593, 572, 219, 116, 136, 167] 2.083814 \n634 [308, 593, 572, 217, 239, 102, 136, 167] 2.083174 \n635 [308, 225, 593, 217, 239, 102, 136, 167] 2.083150 \n636 [225, 572, 102, 116, 167] 2.082763 \n637 [225, 400, 572, 102, 136] 2.082625 \n638 [593, 219, 217, 102, 116, 136] 2.082404 \n639 [308, 225, 593, 217, 102, 136] 2.082178 \n640 [308, 225, 400, 593, 572, 219, 217, 102, 136, ... 2.082138 \n641 [308, 225, 239, 102, 116, 136, 167] 2.081237 \n642 [225, 593, 217, 116, 136] 2.081126 \n643 [225, 400, 593, 572, 239, 116, 136, 167] 2.080720 \n644 [308, 219, 102, 116, 136, 167] 2.080550 \n645 [225, 593, 572, 217, 136, 167] 2.080451 \n646 [308, 225, 400, 593, 572, 217, 239, 116, 136, ... 2.080310 \n647 [308, 400, 593, 572, 136, 167] 2.080304 \n648 [400, 572, 219, 217, 102, 116, 136] 2.080140 \n649 [308, 225, 400, 593, 219, 217, 239, 102, 116, ... 2.080032 \n650 [593, 217, 102, 116] 2.079443 \n651 [593, 572, 217, 239, 116, 136, 167] 2.079313 \n652 [225, 400, 217, 102, 167] 2.079258 \n653 [308, 225, 593, 572, 217, 239, 102, 116, 136] 2.079048 \n654 [400, 572, 217, 102, 116] 2.078555 \n655 [225, 593, 219, 102, 116, 136] 2.078506 \n656 [225, 400, 593, 572, 239, 102, 116, 167] 2.077919 \n657 [593, 572, 219, 102, 136, 167] 2.077815 \n658 [400, 572, 219, 102, 116, 136] 2.077717 \n659 [308, 400, 593, 116, 167] 2.077381 \n660 [308, 400, 593, 219, 239, 102, 116, 136, 167] 2.077263 \n661 [400, 219, 217, 102, 136, 167] 2.076952 \n662 [308, 217, 102, 116, 136] 2.076824 \n663 [225, 572, 102, 136, 167] 2.076640 \n664 [308, 400, 593, 239, 102, 116, 167] 2.076549 \n665 [593, 217, 102, 136] 2.076472 \n666 [308, 400, 593, 572, 219, 217, 239, 102, 116, ... 2.076146 \n667 [225, 400, 593, 572, 219, 239, 102, 116, 136, ... 2.076115 \n668 [308, 400, 593, 572, 217, 116, 167] 2.076106 \n669 [225, 593, 572, 116, 136] 2.075975 \n670 [593, 572, 217, 116, 167] 2.075860 \n671 [308, 225, 400, 593, 572, 217, 116, 167] 2.075308 \n672 [308, 225, 400, 593, 219, 239, 102, 116, 136, ... 2.075283 \n673 [225, 400, 219, 217, 102, 116, 136] 2.075090 \n674 [308, 225, 400, 217, 102, 136] 2.075020 \n675 [225, 400, 572, 217, 102, 116] 2.074980 \n676 [308, 225, 572, 239, 102, 116, 136, 167] 2.074832 \n677 [225, 400, 217, 116, 136] 2.074761 \n678 [308, 217, 102, 136, 167] 2.074746 \n679 [225, 593, 572, 219, 217, 102, 116, 136] 2.074339 \n680 [400, 593, 572, 239, 116, 136, 167] 2.074275 \n681 [225, 400, 116, 136] 2.073706 \n682 [308, 225, 400, 593, 572, 116, 167] 2.073667 \n683 [225, 593, 217, 239, 116, 136, 167] 2.073072 \n684 [225, 593, 217, 239, 102, 116, 167] 2.072637 \n685 [225, 593, 572, 219, 102, 136, 167] 2.072372 \n686 [225, 593, 217, 116, 167] 2.072345 \n687 [225, 593, 572, 102, 167] 2.072223 \n688 [400, 217, 116, 136] 2.072198 \n689 [400, 217, 102, 167] 2.072103 \n690 [593, 572, 217, 239, 102, 116, 167] 2.071947 \n691 [308, 225, 400, 593, 219, 102, 116, 167] 2.071706 \n692 [225, 400, 593, 572, 219, 217, 116, 136, 167] 2.071618 \n693 [225, 593, 116, 167] 2.071516 \n694 [225, 400, 572, 219, 102, 116, 136] 2.071334 \n695 [593, 219, 217, 239, 102, 116, 136, 167] 2.070955 \n696 [225, 400, 219, 102, 136, 167] 2.070927 \n697 [308, 572, 217, 116, 136, 167] 2.070371 \n698 [308, 225, 593, 572, 217, 239, 102, 136, 167] 2.070132 \n699 [400, 219, 102, 136, 167] 2.070050 \n700 [593, 219, 217, 102, 136, 167] 2.070042 \n701 [308, 400, 593, 219, 217, 102, 116, 167] 2.069445 \n702 [400, 572, 219, 217, 102, 136, 167] 2.068225 \n703 [225, 593, 219, 217, 102, 116, 136] 2.068196 \n704 [308, 225, 572, 102, 116, 167] 2.067597 \n705 [308, 593, 217, 239, 116, 136, 167] 2.067594 \n706 [308, 225, 400, 593, 219, 217, 102, 116, 167] 2.066179 \n707 [225, 593, 572, 219, 217, 102, 136, 167] 2.065863 \n708 [308, 225, 400, 593, 572, 219, 217, 239, 102, ... 2.065747 \n709 [308, 400, 217, 102, 136] 2.064813 \n710 [593, 217, 116, 167] 2.064361 \n711 [308, 225, 400, 593, 572, 239, 102, 116, 167] 2.064244 \n712 [308, 225, 400, 593, 572, 239, 116, 136, 167] 2.064234 \n713 [593, 572, 219, 217, 239, 102, 116, 136, 167] 2.064042 \n714 [308, 225, 593, 572, 102, 136] 2.064000 \n715 [308, 400, 593, 219, 102, 116, 167] 2.063217 \n716 [308, 593, 217, 239, 102, 116, 167] 2.063176 \n717 [400, 593, 572, 239, 102, 116, 167] 2.063139 \n718 [308, 217, 102, 116, 167] 2.062170 \n719 [308, 400, 593, 572, 219, 239, 102, 116, 136, ... 2.061259 \n720 [593, 217, 102, 167] 2.061122 \n721 [225, 400, 572, 219, 217, 102, 116, 136] 2.061121 \n722 [308, 225, 400, 572, 217, 102, 136] 2.061082 \n723 [225, 593, 217, 136, 167] 2.060963 \n724 [400, 572, 217, 102, 167] 2.060905 \n725 [308, 225, 593, 217, 102, 116] 2.060751 \n726 [225, 593, 102, 116] 2.060642 \n727 [225, 593, 572, 217, 116, 167] 2.060450 \n728 [400, 572, 219, 102, 136, 167] 2.060028 \n729 [225, 400, 219, 217, 102, 136, 167] 2.059329 \n730 [308, 225, 593, 217, 239, 102, 116, 167] 2.059190 \n731 [308, 400, 593, 572, 219, 217, 102, 116, 167] 2.059083 \n732 [308, 225, 400, 593, 572, 219, 239, 102, 116, ... 2.058866 \n733 [225, 572, 102, 116, 136] 2.058344 \n734 [225, 593, 219, 102, 136, 167] 2.058321 \n735 [225, 400, 572, 217, 102, 167] 2.058177 \n736 [308, 593, 217, 102, 136] 2.058044 \n737 [308, 400, 572, 217, 102, 136] 2.057974 \n738 [308, 225, 102, 116, 136] 2.057559 \n739 [225, 400, 572, 102, 116] 2.057526 \n740 [308, 400, 593, 572, 239, 116, 136, 167] 2.057460 \n741 [308, 225, 400, 102, 136] 2.057137 \n742 [308, 225, 593, 572, 217, 102, 116] 2.057062 \n743 [593, 219, 102, 116, 136] 2.056873 \n744 [308, 225, 593, 217, 239, 116, 136, 167] 2.056821 \n745 [308, 225, 400, 593, 572, 219, 102, 116, 167] 2.056471 \n746 [308, 225, 400, 593, 219, 116, 136, 167] 2.056236 \n747 [308, 225, 593, 239, 102, 116, 136] 2.055956 \n748 [225, 593, 572, 136, 167] 2.055704 \n749 [225, 593, 219, 217, 102, 136, 167] 2.055269 \n750 [225, 593, 572, 217, 239, 102, 116, 167] 2.055039 \n751 [225, 400, 572, 219, 102, 136, 167] 2.055022 \n752 [308, 225, 400, 593, 572, 219, 217, 102, 116, ... 2.054621 \n753 [308, 225, 400, 217, 102, 116] 2.054249 \n754 [225, 572, 116, 136, 167] 2.054154 \n755 [225, 400, 102, 167] 2.053993 \n756 [400, 572, 217, 116, 136] 2.053195 \n757 [593, 217, 116, 136] 2.052970 \n758 [308, 400, 593, 572, 239, 102, 116, 167] 2.052968 \n759 [308, 400, 593, 219, 217, 116, 136, 167] 2.052733 \n760 [225, 593, 572, 116, 167] 2.052701 \n761 [308, 400, 217, 239, 102, 116, 136] 2.052559 \n762 [225, 593, 572, 217, 239, 116, 136, 167] 2.052466 \n763 [308, 400, 593, 572, 116, 167] 2.052169 \n764 [308, 225, 400, 217, 239, 102, 116, 136] 2.052137 \n765 [308, 400, 593, 572, 219, 102, 116, 167] 2.051223 \n766 [225, 400, 116, 167] 2.050679 \n767 [308, 225, 572, 116, 136, 167] 2.049893 \n768 [308, 225, 400, 593, 219, 217, 116, 136, 167] 2.049842 \n769 [225, 400, 572, 217, 116, 136] 2.049501 \n770 [225, 400, 572, 219, 217, 102, 136, 167] 2.049439 \n771 [225, 400, 217, 136, 167] 2.049252 \n772 [225, 400, 217, 239, 102, 116, 136] 2.048797 \n773 [225, 593, 219, 217, 239, 102, 116, 136, 167] 2.048793 \n774 [308, 225, 102, 116, 167] 2.048477 \n775 [400, 217, 239, 102, 116, 136] 2.048217 \n776 [308, 400, 593, 219, 116, 136, 167] 2.048194 \n777 [308, 593, 219, 217, 239, 102, 116, 136, 167] 2.047857 \n778 [308, 593, 572, 217, 239, 116, 136, 167] 2.047046 \n779 [308, 593, 572, 217, 102, 116] 2.046599 \n780 [225, 400, 217, 116, 167] 2.046583 \n781 [225, 593, 116, 136] 2.046219 \n782 [308, 593, 572, 217, 239, 102, 116, 167] 2.045995 \n783 [308, 225, 400, 219, 102, 116, 136] 2.045747 \n784 [308, 400, 219, 217, 102, 116, 136] 2.044640 \n785 [308, 225, 102, 136, 167] 2.044411 \n786 [400, 217, 116, 167] 2.043971 \n787 [308, 400, 593, 572, 219, 217, 116, 136, 167] 2.043785 \n788 [308, 593, 572, 219, 217, 102, 116, 136] 2.043512 \n789 [308, 225, 593, 102, 136] 2.043379 \n790 [308, 225, 593, 572, 239, 102, 116, 136] 2.043197 \n791 [308, 225, 593, 572, 217, 102, 167] 2.042878 \n792 [225, 102, 116, 136, 167] 2.042865 \n793 [308, 225, 400, 572, 102, 136] 2.042544 \n794 [400, 217, 136, 167] 2.042313 \n795 [308, 225, 400, 593, 572, 219, 116, 136, 167] 2.042252 \n796 [225, 400, 219, 102, 116, 167] 2.042048 \n797 [593, 572, 219, 217, 102, 116, 167] 2.041759 \n798 [225, 593, 572, 219, 217, 239, 102, 116, 136, ... 2.041539 \n799 [400, 219, 217, 102, 116, 167] 2.041508 \n800 [308, 225, 593, 217, 116, 136] 2.041016 \n801 [308, 225, 400, 219, 217, 102, 116, 136] 2.040987 \n802 [308, 225, 593, 572, 217, 239, 102, 116, 167] 2.040658 \n803 [308, 225, 400, 102, 116] 2.040444 \n804 [308, 225, 593, 217, 102, 167] 2.040225 \n805 [308, 400, 217, 102, 116] 2.040018 \n806 [308, 225, 400, 593, 572, 219, 217, 116, 136, ... 2.039642 \n807 [308, 593, 572, 219, 217, 239, 102, 116, 136, ... 2.039280 \n808 [308, 225, 593, 572, 217, 116, 136] 2.039137 \n809 [308, 225, 593, 572, 219, 217, 102, 116, 136] 2.037850 \n810 [308, 217, 116, 136, 167] 2.037581 \n811 [308, 225, 400, 217, 239, 102, 136, 167] 2.037520 \n812 [308, 225, 593, 239, 102, 136, 167] 2.037363 \n813 [308, 400, 593, 572, 219, 116, 136, 167] 2.037324 \n814 [308, 225, 593, 219, 217, 102, 116, 136] 2.037238 \n815 [308, 225, 593, 219, 217, 239, 102, 116, 136, ... 2.037097 \n816 [308, 225, 593, 572, 219, 102, 116, 136] 2.037025 \n817 [308, 225, 593, 572, 217, 239, 116, 136, 167] 2.036888 \n818 [308, 593, 219, 217, 102, 116, 136] 2.036875 \n819 [308, 225, 593, 219, 102, 116, 136] 2.036850 \n820 [225, 400, 572, 116, 136] 2.036708 \n821 [308, 400, 217, 239, 102, 136, 167] 2.036689 \n822 [400, 219, 217, 239, 102, 116, 136, 167] 2.036544 \n823 [308, 400, 219, 102, 116, 136] 2.035737 \n824 [400, 572, 217, 136, 167] 2.035187 \n825 [593, 219, 102, 136, 167] 2.035026 \n826 [308, 225, 400, 217, 116, 136] 2.034805 \n827 [308, 400, 572, 219, 217, 102, 116, 136] 2.034722 \n828 [308, 572, 239, 102, 116, 136, 167] 2.034419 \n829 [225, 400, 217, 239, 102, 136, 167] 2.033931 \n830 [593, 217, 136, 167] 2.033902 \n831 [308, 225, 400, 572, 217, 102, 116] 2.033770 \n832 [400, 219, 102, 116, 167] 2.033109 \n833 [308, 593, 572, 219, 217, 102, 136, 167] 2.033027 \n834 [308, 400, 572, 217, 239, 102, 116, 136] 2.032896 \n835 [308, 593, 217, 102, 116] 2.032839 \n836 [400, 217, 239, 102, 136, 167] 2.032685 \n837 [308, 225, 593, 572, 102, 116] 2.032601 \n838 [308, 225, 400, 217, 102, 167] 2.032492 \n839 [225, 400, 572, 217, 136, 167] 2.032462 \n840 [400, 572, 217, 239, 102, 116, 136] 2.032322 \n841 [308, 225, 400, 572, 217, 239, 102, 116, 136] 2.032130 \n842 [308, 593, 572, 217, 102, 167] 2.031997 \n843 [225, 400, 219, 217, 102, 116, 167] 2.031744 \n844 [225, 400, 572, 102, 167] 2.030894 \n845 [308, 593, 572, 217, 116, 136] 2.030656 \n846 [308, 225, 593, 102, 116] 2.030644 \n847 [225, 400, 136, 167] 2.030587 \n848 [308, 225, 400, 572, 219, 102, 116, 136] 2.030302 \n849 [308, 225, 593, 572, 239, 102, 136, 167] 2.030237 \n850 [225, 400, 572, 217, 239, 102, 116, 136] 2.030152 \n851 [308, 225, 400, 572, 219, 217, 102, 116, 136] 2.029870 \n852 [225, 593, 572, 219, 102, 116, 167] 2.029728 \n853 [308, 225, 116, 136, 167] 2.029676 \n854 [593, 219, 217, 102, 116, 167] 2.029313 \n855 [225, 593, 219, 239, 102, 116, 136, 167] 2.028557 \n856 [308, 400, 219, 217, 102, 136, 167] 2.028489 \n857 [308, 225, 593, 572, 219, 217, 239, 102, 116, ... 2.028179 \n858 [225, 593, 572, 219, 217, 102, 116, 167] 2.027938 \n859 [400, 572, 219, 217, 102, 116, 167] 2.027580 \n860 [308, 225, 593, 572, 219, 217, 102, 136, 167] 2.027505 \n861 [225, 593, 219, 102, 116, 167] 2.027312 \n862 [308, 593, 572, 219, 102, 116, 136] 2.026628 \n863 [308, 225, 400, 219, 217, 102, 136, 167] 2.026269 \n864 [593, 572, 219, 239, 102, 116, 136, 167] 2.026218 \n865 [308, 225, 400, 219, 102, 136, 167] 2.026173 \n866 [593, 219, 239, 102, 116, 136, 167] 2.025501 \n867 [400, 572, 102, 136] 2.025330 \n868 [308, 225, 400, 116, 136] 2.024964 \n869 [308, 225, 593, 572, 217, 136, 167] 2.024761 \n870 [225, 572, 239, 102, 116, 136, 167] 2.024743 \n871 [225, 593, 572, 239, 102, 116, 136] 2.024734 \n872 [225, 593, 219, 217, 102, 116, 167] 2.024560 \n873 [308, 400, 572, 217, 102, 116] 2.024435 \n874 [225, 593, 102, 136] 2.024409 \n875 [308, 225, 593, 239, 116, 136, 167] 2.024065 \n876 [308, 400, 572, 219, 102, 116, 136] 2.023967 \n877 [225, 400, 219, 217, 239, 102, 116, 136, 167] 2.023963 \n878 [308, 225, 593, 219, 217, 102, 136, 167] 2.023596 \n879 [308, 225, 593, 219, 239, 102, 116, 136, 167] 2.023265 \n880 [308, 225, 593, 572, 219, 102, 136, 167] 2.022988 \n881 [308, 400, 219, 217, 239, 102, 116, 136, 167] 2.022761 \n882 [225, 593, 572, 219, 239, 102, 116, 136, 167] 2.022439 \n883 [308, 593, 219, 217, 102, 136, 167] 2.022319 \n884 [308, 400, 572, 219, 217, 102, 136, 167] 2.022254 \n885 [400, 572, 217, 239, 102, 136, 167] 2.022201 \n886 [308, 102, 116, 136, 167] 2.021872 \n887 [400, 572, 219, 217, 239, 102, 116, 136, 167] 2.021680 \n888 [308, 400, 217, 116, 136] 2.021441 \n889 [308, 400, 572, 217, 239, 102, 136, 167] 2.021121 \n890 [308, 225, 400, 572, 217, 239, 102, 136, 167] 2.020852 \n891 [308, 593, 572, 239, 102, 116, 136] 2.020843 \n892 [225, 593, 102, 167] 2.020364 \n893 [593, 572, 219, 102, 116, 167] 2.020324 \n894 [308, 225, 593, 572, 116, 136] 2.020299 \n895 [308, 225, 593, 217, 136, 167] 2.020277 \n896 [217, 102, 116, 167] 2.019812 \n897 [225, 400, 572, 219, 102, 116, 167] 2.019804 \n898 [225, 400, 572, 217, 239, 102, 136, 167] 2.019615 \n899 [308, 225, 593, 116, 136] 2.018672 \n900 [308, 593, 219, 239, 102, 116, 136, 167] 2.018480 \n901 [308, 593, 239, 102, 116, 136] 2.018449 \n902 [308, 225, 400, 239, 102, 116, 136] 2.018394 \n903 [400, 593, 217, 102] 2.018174 \n904 [308, 225, 400, 572, 219, 217, 102, 136, 167] 2.018159 \n905 [308, 225, 593, 219, 102, 136, 167] 2.017911 \n906 [225, 400, 572, 219, 217, 102, 116, 167] 2.017589 \n907 [308, 225, 400, 572, 217, 102, 167] 2.017508 \n908 [225, 400, 593, 217, 102] 2.017311 \n909 [308, 225, 400, 217, 239, 102, 116, 167] 2.017187 \n910 [308, 225, 593, 239, 102, 116, 167] 2.017176 \n911 [308, 225, 400, 219, 217, 239, 102, 116, 136, ... 2.016959 \n912 [225, 400, 217, 239, 102, 116, 167] 2.016295 \n913 [308, 225, 400, 572, 217, 116, 136] 2.016292 \n914 [308, 593, 217, 116, 136] 2.015957 \n915 [308, 593, 572, 217, 136, 167] 2.015807 \n916 [308, 225, 400, 572, 102, 116] 2.015421 \n917 [308, 225, 400, 572, 219, 102, 136, 167] 2.015074 \n918 [308, 400, 217, 102, 167] 2.015021 \n919 [225, 593, 572, 239, 102, 136, 167] 2.014908 \n920 [400, 572, 219, 102, 116, 167] 2.014691 \n921 [225, 593, 239, 102, 116, 136] 2.014324 \n922 [308, 593, 219, 102, 116, 136] 2.014059 \n923 [308, 225, 593, 572, 219, 239, 102, 116, 136, ... 2.013773 \n924 [225, 400, 219, 116, 136, 167] 2.013659 \n925 [308, 400, 219, 102, 136, 167] 2.013543 \n926 [225, 400, 572, 217, 116, 167] 2.013278 \n927 [308, 225, 400, 217, 136, 167] 2.012944 \n928 [225, 400, 593, 102] 2.012428 \n929 [308, 239, 102, 116, 136, 167] 2.012399 \n930 [308, 593, 572, 219, 239, 102, 116, 136, 167] 2.012312 \n931 [308, 400, 217, 239, 102, 116, 167] 2.012264 \n932 [593, 572, 219, 217, 116, 136, 167] 2.011899 \n933 [308, 593, 572, 219, 102, 136, 167] 2.011672 \n934 [400, 217, 239, 102, 116, 167] 2.011286 \n935 [308, 225, 400, 217, 239, 116, 136, 167] 2.011255 \n936 [400, 572, 217, 116, 167] 2.011175 \n937 [308, 225, 593, 572, 102, 167] 2.011135 \n938 [400, 217, 239, 116, 136, 167] 2.011082 \n939 [400, 219, 217, 116, 136, 167] 2.011059 \n940 [225, 400, 572, 219, 217, 239, 102, 116, 136, ... 2.010357 \n941 [225, 400, 217, 239, 116, 136, 167] 2.009936 \n942 [308, 593, 217, 102, 167] 2.009876 \n943 [225, 593, 239, 116, 136, 167] 2.009770 \n944 [225, 400, 572, 136, 167] 2.009763 \n945 [308, 400, 217, 239, 116, 136, 167] 2.009697 \n946 [308, 400, 572, 219, 217, 239, 102, 116, 136, ... 2.009307 \n947 [308, 225, 400, 102, 167] 2.009011 \n948 [308, 225, 593, 217, 116, 167] 2.008273 \n949 [308, 593, 572, 239, 102, 136, 167] 2.007638 \n950 [308, 400, 572, 217, 116, 136] 2.007529 \n951 [308, 400, 572, 219, 102, 136, 167] 2.007243 \n952 [308, 400, 572, 217, 102, 167] 2.006546 \n953 [225, 400, 219, 239, 102, 116, 136, 167] 2.006505 \n954 [225, 593, 136, 167] 2.004972 \n955 [572, 219, 217, 102, 116, 136] 2.004627 \n956 [308, 225, 593, 572, 239, 116, 136, 167] 2.004293 \n957 [225, 400, 219, 217, 116, 136, 167] 2.004161 \n958 [308, 225, 400, 219, 239, 102, 116, 136, 167] 2.004125 \n959 [308, 225, 400, 572, 219, 217, 239, 102, 116, ... 2.004105 \n960 [308, 400, 572, 102, 136] 2.003940 \n961 [308, 593, 572, 102, 136] 2.003821 \n962 [400, 593, 572, 217, 102] 2.003481 \n963 [400, 219, 116, 136, 167] 2.002985 \n964 [225, 593, 572, 219, 116, 136, 167] 2.002500 \n965 [308, 225, 400, 219, 217, 102, 116, 167] 2.001698 \n966 [593, 102, 116, 136, 167] 2.001374 \n967 [308, 225, 593, 572, 239, 102, 116, 167] 2.001350 \n968 [400, 572, 219, 217, 116, 136, 167] 2.001286 \n969 [400, 219, 239, 102, 116, 136, 167] 2.001160 \n970 [308, 225, 593, 572, 217, 116, 167] 2.001011 \n971 [308, 225, 400, 572, 116, 136] 2.000898 \n972 [572, 219, 217, 102, 136, 167] 2.000731 \n973 [225, 593, 572, 219, 217, 116, 136, 167] 2.000707 \n974 [308, 225, 400, 219, 102, 116, 167] 2.000158 \n975 [308, 225, 400, 572, 217, 136, 167] 1.999921 \n976 [225, 400, 593, 572, 217, 102] 1.999607 \n977 [308, 225, 400, 217, 116, 167] 1.999379 \n978 [308, 225, 400, 572, 239, 102, 116, 136] 1.998875 \n979 [308, 400, 219, 217, 102, 116, 167] 1.998828 \n980 [308, 225, 400, 239, 102, 136, 167] 1.998573 \n981 [308, 225, 593, 572, 136, 167] 1.998563 \n982 [308, 225, 593, 102, 167] 1.998491 \n983 [225, 400, 572, 116, 167] 1.998075 \n984 [308, 593, 239, 102, 136, 167] 1.998039 \n985 [308, 400, 219, 239, 102, 116, 136, 167] 1.997985 \n986 [225, 593, 572, 239, 116, 136, 167] 1.997810 \n987 [400, 593, 217, 136] 1.997722 \n988 [400, 593, 219, 217, 102, 136] 1.997119 \n989 [225, 400, 593, 136] 1.997103 \n990 [308, 400, 102, 136] 1.997080 \n991 [308, 225, 400, 572, 217, 239, 102, 116, 167] 1.996861 \n992 [400, 593, 217, 239, 102, 136] 1.996777 \n993 [400, 572, 102, 116] 1.996767 \n994 [225, 593, 239, 102, 136, 167] 1.996644 \n995 [225, 400, 593, 116] 1.996529 \n996 [308, 225, 593, 572, 219, 217, 102, 116, 167] 1.996335 \n997 [308, 400, 217, 136, 167] 1.996262 \n998 [308, 225, 593, 219, 217, 102, 116, 167] 1.996117 \n999 [225, 593, 219, 116, 136, 167] 1.995726 \n1000 [308, 225, 400, 593, 217, 239, 102, 136] 1.995714 \n1001 [308, 400, 593, 217, 239, 102, 136] 1.995489 \n1002 [593, 219, 102, 116, 167] 1.995314 \n1003 [225, 400, 572, 219, 116, 136, 167] 1.995306 \n1004 [225, 400, 593, 217, 136] 1.995009 \n1005 [225, 400, 572, 217, 239, 102, 116, 167] 1.994711 \n1006 [593, 219, 217, 116, 136, 167] 1.994677 \n1007 [308, 593, 572, 219, 217, 102, 116, 167] 1.994589 \n1008 [225, 400, 593, 219, 102, 136] 1.994461 \n1009 [400, 593, 572, 219, 217, 102, 136] 1.994441 \n1010 [593, 572, 102, 136] 1.993777 \n1011 [308, 593, 239, 116, 136, 167] 1.993654 \n1012 [225, 400, 572, 219, 217, 116, 136, 167] 1.993443 \n1013 [225, 593, 219, 217, 116, 136, 167] 1.993346 \n1014 [308, 225, 400, 136, 167] 1.993304 \n1015 [225, 400, 593, 217, 239, 102, 136] 1.993083 \n1016 [308, 593, 219, 102, 136, 167] 1.992861 \n1017 [308, 225, 400, 572, 102, 167] 1.992753 \n1018 [308, 593, 217, 136, 167] 1.992669 \n1019 [400, 102, 116] 1.992542 \n1020 [593, 572, 219, 116, 136, 167] 1.992251 \n1021 [308, 400, 572, 217, 239, 102, 116, 167] 1.992233 \n1022 [225, 400, 572, 219, 239, 102, 116, 136, 167] 1.991386 \n1023 [225, 593, 239, 102, 116, 167] 1.991366 \n1024 [308, 225, 400, 572, 219, 217, 102, 116, 167] 1.991205 \n1025 [400, 572, 217, 239, 102, 116, 167] 1.991012 \n1026 [308, 225, 400, 572, 217, 239, 116, 136, 167] 1.990526 \n1027 [308, 400, 572, 219, 217, 102, 116, 167] 1.989846 \n1028 [308, 225, 400, 572, 219, 239, 102, 116, 136, ... 1.989568 \n1029 [308, 400, 572, 217, 136, 167] 1.989481 \n1030 [225, 400, 593, 219, 217, 102, 136] 1.989220 \n1031 [308, 225, 593, 219, 102, 116, 167] 1.988997 \n1032 [400, 572, 219, 116, 136, 167] 1.988917 \n1033 [308, 225, 593, 572, 219, 102, 116, 167] 1.988789 \n1034 [308, 593, 219, 217, 102, 116, 167] 1.988499 \n1035 [308, 400, 572, 217, 239, 116, 136, 167] 1.988357 \n1036 [400, 593, 219, 102, 136] 1.988278 \n1037 [225, 593, 572, 239, 102, 116, 167] 1.988233 \n1038 [400, 572, 217, 239, 116, 136, 167] 1.988045 \n1039 [400, 572, 219, 239, 102, 116, 136, 167] 1.987969 \n1040 [225, 400, 572, 217, 239, 116, 136, 167] 1.987555 \n1041 [308, 400, 239, 102, 116, 136] 1.987190 \n1042 [225, 572, 219, 217, 102, 116, 136] 1.986863 \n1043 [225, 400, 239, 102, 116, 136] 1.986426 \n1044 [308, 593, 572, 217, 116, 167] 1.986326 \n1045 [308, 572, 102, 116, 136] 1.986198 \n1046 [308, 225, 593, 136, 167] 1.986079 \n1047 [308, 225, 400, 572, 219, 102, 116, 167] 1.985826 \n1048 [308, 225, 593, 116, 167] 1.985775 \n1049 [308, 225, 400, 116, 167] 1.985772 \n1050 [225, 400, 593, 572, 219, 102, 136] 1.985486 \n1051 [225, 400, 593, 572, 102] 1.985361 \n1052 [225, 572, 219, 102, 116, 136] 1.985332 \n1053 [400, 593, 572, 217, 136] 1.984831 \n1054 [225, 400, 593, 572, 219, 217, 102, 136] 1.984765 \n1055 [308, 400, 572, 219, 239, 102, 116, 136, 167] 1.984503 \n1056 [308, 572, 102, 136, 167] 1.984280 \n1057 [400, 593, 217, 116] 1.984280 \n1058 [400, 593, 572, 217, 239, 102, 136] 1.984047 \n1059 [400, 593, 572, 219, 102, 136] 1.984045 \n1060 [308, 225, 400, 572, 239, 102, 136, 167] 1.983873 \n1061 [308, 593, 572, 239, 116, 136, 167] 1.983552 \n1062 [225, 400, 593, 217, 116] 1.983315 \n1063 [219, 217, 102, 116, 136] 1.982320 \n1064 [308, 400, 219, 102, 116, 167] 1.982274 \n1065 [308, 225, 400, 219, 217, 116, 136, 167] 1.982113 \n1066 [400, 572, 116, 136] 1.981829 \n1067 [308, 400, 593, 572, 217, 239, 102, 136] 1.981628 \n1068 [308, 225, 400, 593, 572, 217, 239, 102, 136] 1.981622 \n1069 [308, 225, 400, 593, 217, 102] 1.981478 \n1070 [225, 239, 102, 116, 136, 167] 1.981152 \n1071 [308, 400, 217, 116, 167] 1.980965 \n1072 [308, 225, 400, 219, 116, 136, 167] 1.980827 \n1073 [308, 225, 400, 239, 102, 116, 167] 1.980532 \n1074 [308, 593, 217, 116, 167] 1.980225 \n1075 [308, 400, 102, 116] 1.979984 \n1076 [308, 225, 400, 239, 116, 136, 167] 1.979850 \n1077 [225, 400, 593, 572, 217, 136] 1.979820 \n1078 [225, 400, 593, 572, 217, 239, 102, 136] 1.979700 \n1079 [400, 116, 136] 1.979643 \n1080 [225, 572, 219, 217, 102, 136, 167] 1.979633 \n1081 [308, 225, 400, 572, 217, 116, 167] 1.979123 \n1082 [308, 225, 217, 239, 102, 116, 136] 1.978737 \n1083 [308, 400, 219, 217, 116, 136, 167] 1.978201 \n1084 [308, 225, 593, 572, 116, 167] 1.978145 \n1085 [308, 225, 400, 572, 136, 167] 1.978063 \n1086 [400, 593, 219, 217, 239, 102, 116, 136] 1.977239 \n1087 [308, 225, 593, 572, 219, 217, 116, 136, 167] 1.977189 \n1088 [225, 219, 217, 102, 116, 136] 1.976652 \n1089 [593, 572, 116, 136] 1.975194 \n1090 [572, 219, 102, 116, 136] 1.975096 \n1091 [308, 593, 239, 102, 116, 167] 1.975033 \n1092 [593, 572, 239, 102, 116, 136] 1.974913 \n1093 [308, 225, 593, 219, 217, 116, 136, 167] 1.974887 \n1094 [225, 400, 572, 239, 102, 116, 136] 1.974870 \n1095 [225, 219, 102, 116, 136] 1.974845 \n1096 [308, 400, 572, 239, 102, 116, 136] 1.974752 \n1097 [308, 593, 572, 219, 217, 116, 136, 167] 1.974613 \n1098 [308, 225, 400, 593, 217, 239, 102, 116] 1.974551 \n1099 [400, 102, 136] 1.974319 \n1100 [217, 116, 136, 167] 1.974142 \n1101 [225, 572, 219, 102, 136, 167] 1.973910 \n1102 [219, 217, 239, 102, 116, 136, 167] 1.973775 \n1103 [308, 225, 400, 572, 219, 217, 116, 136, 167] 1.973517 \n1104 [593, 572, 102, 116] 1.973424 \n1105 [308, 400, 593, 219, 217, 239, 102, 116, 136] 1.972431 \n1106 [219, 217, 102, 136, 167] 1.972429 \n1107 [308, 593, 572, 239, 102, 116, 167] 1.972427 \n1108 [225, 400, 593, 217, 239, 102, 116] 1.972372 \n1109 [308, 400, 572, 219, 102, 116, 167] 1.972021 \n1110 [308, 400, 572, 102, 116] 1.971958 \n1111 [400, 593, 217, 239, 116, 136] 1.971796 \n1112 [225, 572, 217, 102, 136] 1.971706 \n1113 [308, 400, 572, 219, 217, 116, 136, 167] 1.971321 \n1114 [308, 225, 400, 593, 219, 217, 102, 136] 1.970918 \n1115 [400, 593, 217, 239, 102, 116] 1.970817 \n1116 [572, 219, 217, 239, 102, 116, 136, 167] 1.970731 \n1117 [225, 400, 593, 219, 217, 239, 102, 116, 136] 1.970482 \n1118 [308, 225, 400, 593, 219, 217, 239, 102, 116, ... 1.970431 \n1119 [225, 400, 593, 572, 136] 1.970349 \n1120 [308, 225, 593, 572, 219, 116, 136, 167] 1.970344 \n1121 [308, 219, 217, 239, 102, 116, 136, 167] 1.970172 \n1122 [308, 400, 593, 217, 239, 102, 116] 1.969980 \n1123 [308, 225, 400, 593, 217, 239, 116, 136] 1.969855 \n1124 [308, 225, 572, 217, 239, 102, 116, 136] 1.969832 \n1125 [308, 225, 400, 593, 572, 217, 102] 1.969648 \n1126 [308, 593, 572, 219, 102, 116, 167] 1.969497 \n1127 [308, 400, 116, 136] 1.968674 \n1128 [308, 400, 593, 219, 217, 102, 136] 1.968621 \n1129 [308, 225, 593, 219, 116, 136, 167] 1.968519 \n1130 [308, 225, 400, 572, 219, 116, 136, 167] 1.968440 \n1131 [308, 400, 593, 217, 239, 116, 136] 1.968343 \n1132 [217, 102, 136, 167] 1.968134 \n1133 [308, 225, 400, 593, 219, 102, 136] 1.967902 \n1134 [225, 400, 593, 217, 239, 116, 136] 1.967804 \n1135 [593, 572, 239, 102, 136, 167] 1.967737 \n1136 [308, 400, 593, 217, 102] 1.967482 \n1137 [400, 593, 572, 219, 217, 239, 102, 116, 136] 1.967437 \n1138 [400, 116, 167] 1.967380 \n1139 [308, 593, 572, 102, 116] 1.966836 \n1140 [572, 219, 102, 136, 167] 1.966804 \n1141 [593, 572, 116, 167] 1.966787 \n1142 [308, 225, 400, 593, 572, 219, 217, 102, 136] 1.966560 \n1143 [308, 225, 217, 239, 102, 136, 167] 1.966461 \n1144 [308, 593, 219, 217, 116, 136, 167] 1.966258 \n1145 [308, 400, 593, 572, 219, 217, 102, 136] 1.966227 \n1146 [308, 217, 239, 102, 116, 136] 1.966009 \n1147 [308, 225, 400, 593, 102] 1.966002 \n1148 [308, 225, 400, 593, 217, 136] 1.965897 \n1149 [308, 225, 400, 593, 239, 102, 136] 1.965851 \n1150 [308, 225, 219, 217, 239, 102, 116, 136, 167] 1.965772 \n1151 [400, 572, 102, 167] 1.965707 \n1152 [225, 400, 593, 219, 102, 116] 1.965626 \n1153 [308, 225, 572, 217, 102, 136] 1.964980 \n1154 [308, 400, 239, 102, 136, 167] 1.964835 \n1155 [225, 219, 217, 102, 136, 167] 1.964666 \n1156 [308, 225, 572, 219, 217, 102, 116, 136] 1.964571 \n1157 [308, 400, 572, 217, 116, 167] 1.964479 \n1158 [225, 400, 239, 102, 136, 167] 1.964303 \n1159 [308, 572, 219, 217, 239, 102, 116, 136, 167] 1.963697 \n1160 [400, 593, 219, 217, 102, 116] 1.963466 \n1161 [308, 572, 217, 239, 102, 116, 136] 1.963286 \n1162 [308, 572, 219, 217, 102, 116, 136] 1.963025 \n1163 [308, 400, 593, 572, 219, 217, 239, 102, 116, ... 1.962938 \n1164 [593, 219, 116, 136, 167] 1.962768 \n1165 [593, 572, 239, 116, 136, 167] 1.962750 \n1166 [308, 400, 219, 116, 136, 167] 1.962647 \n1167 [225, 400, 593, 219, 217, 102, 116] 1.962528 \n1168 [308, 225, 219, 217, 102, 116, 136] 1.961496 \n1169 [308, 225, 572, 217, 239, 102, 136, 167] 1.961379 \n1170 [225, 400, 593, 572, 219, 217, 239, 102, 116, ... 1.961232 \n1171 [308, 225, 400, 593, 572, 219, 102, 136] 1.961200 \n1172 [308, 225, 400, 593, 572, 219, 217, 239, 102, ... 1.961110 \n1173 [308, 593, 572, 116, 136] 1.960892 \n1174 [400, 593, 219, 217, 239, 102, 136, 167] 1.960586 \n1175 [225, 102, 116, 167] 1.960488 \n1176 [308, 572, 102, 116, 167] 1.960441 \n1177 [308, 225, 400, 572, 239, 102, 116, 167] 1.960398 \n1178 [225, 219, 217, 239, 102, 116, 136, 167] 1.960397 \n1179 [308, 400, 572, 116, 136] 1.960250 \n1180 [308, 400, 593, 572, 217, 102] 1.959686 \n1181 [225, 400, 572, 239, 102, 136, 167] 1.959483 \n1182 [308, 225, 400, 572, 116, 167] 1.959026 \n1183 [308, 225, 572, 219, 217, 239, 102, 116, 136, ... 1.958718 \n1184 [308, 400, 572, 239, 102, 136, 167] 1.958435 \n1185 [308, 225, 400, 572, 239, 116, 136, 167] 1.958002 \n1186 [400, 593, 116] 1.957963 \n1187 [308, 225, 400, 593, 572, 217, 239, 102, 116] 1.957780 \n1188 [308, 593, 219, 102, 116, 167] 1.957768 \n1189 [308, 400, 593, 219, 217, 239, 102, 136, 167] 1.957510 \n1190 [308, 225, 400, 593, 219, 239, 102, 116, 136] 1.957507 \n1191 [225, 400, 593, 572, 217, 116] 1.957225 \n1192 [400, 593, 572, 219, 217, 102, 116] 1.957139 \n1193 [308, 225, 400, 593, 219, 217, 239, 102, 136, ... 1.956830 \n1194 [225, 572, 219, 217, 239, 102, 116, 136, 167] 1.956611 \n1195 [225, 400, 239, 116, 136, 167] 1.956463 \n1196 [593, 572, 136, 167] 1.956184 \n1197 [308, 572, 217, 239, 102, 136, 167] 1.956015 \n1198 [400, 593, 102] 1.955895 \n1199 [308, 225, 400, 593, 217, 239, 102, 167] 1.955731 \n1200 [400, 593, 572, 217, 116] 1.955631 \n1201 [225, 400, 593, 219, 217, 239, 102, 136, 167] 1.955456 \n1202 [308, 225, 400, 593, 572, 217, 136] 1.955325 \n1203 [225, 219, 102, 136, 167] 1.955096 \n1204 [225, 400, 593, 572, 219, 217, 102, 116] 1.954931 \n1205 [593, 572, 102, 167] 1.954471 \n1206 [308, 225, 572, 219, 217, 102, 136, 167] 1.954454 \n1207 [308, 400, 572, 219, 116, 136, 167] 1.954379 \n1208 [400, 593, 572, 219, 217, 239, 102, 136, 167] 1.954308 \n1209 [308, 225, 400, 593, 136] 1.954210 \n1210 [308, 217, 239, 102, 136, 167] 1.954097 \n1211 [308, 225, 572, 219, 102, 116, 136] 1.954060 \n1212 [225, 400, 239, 102, 116, 167] 1.953999 \n1213 [225, 400, 593, 572, 217, 239, 102, 116] 1.953926 \n1214 [225, 400, 593, 219, 239, 102, 116, 136] 1.953909 \n1215 [308, 400, 593, 219, 102, 136] 1.953605 \n1216 [308, 400, 593, 217, 136] 1.953121 \n1217 [308, 572, 219, 217, 102, 136, 167] 1.953053 \n1218 [308, 400, 593, 572, 217, 239, 102, 116] 1.953020 \n1219 [308, 219, 217, 102, 116, 136] 1.952858 \n1220 [308, 225, 400, 593, 572, 217, 239, 116, 136] 1.952597 \n1221 [225, 400, 593, 572, 219, 102, 116] 1.952277 \n1222 [308, 225, 400, 593, 572, 239, 102, 136] 1.951806 \n1223 [400, 593, 572, 217, 239, 102, 116] 1.951711 \n1224 [400, 593, 219, 102, 116] 1.951678 \n1225 [308, 225, 219, 102, 116, 136] 1.951212 \n1226 [308, 593, 572, 219, 116, 136, 167] 1.951211 \n1227 [308, 400, 593, 572, 219, 102, 136] 1.950943 \n1228 [400, 593, 136] 1.950893 \n1229 [308, 225, 400, 593, 217, 239, 136, 167] 1.950885 \n1230 [308, 225, 400, 593, 572, 102] 1.950860 \n1231 [308, 400, 593, 572, 219, 217, 239, 102, 136, ... 1.950660 \n1232 [225, 400, 593, 217, 239, 102, 167] 1.950368 \n1233 [400, 572, 136, 167] 1.950226 \n1234 [225, 400, 593, 572, 116] 1.950151 \n1235 [308, 400, 593, 572, 217, 239, 116, 136] 1.950111 \n1236 [400, 593, 572, 217, 239, 116, 136] 1.950048 \n1237 [308, 225, 400, 593, 572, 219, 217, 239, 102, ... 1.949717 \n1238 [308, 400, 593, 219, 239, 102, 116, 136] 1.949644 \n1239 [308, 400, 239, 116, 136, 167] 1.949485 \n1240 [308, 225, 400, 593, 217, 116] 1.949411 \n1241 [225, 572, 217, 102, 116] 1.949399 \n1242 [572, 219, 217, 102, 116, 167] 1.949321 \n1243 [400, 593, 572, 102] 1.949123 \n1244 [225, 400, 593, 572, 219, 217, 239, 102, 136, ... 1.949062 \n1245 [308, 572, 116, 136, 167] 1.948662 \n1246 [308, 400, 593, 217, 239, 102, 167] 1.948625 \n1247 [225, 400, 593, 572, 217, 239, 116, 136] 1.948417 \n1248 [225, 400, 593, 217, 167] 1.948222 \n1249 [308, 225, 219, 217, 102, 136, 167] 1.947798 \n1250 [308, 225, 400, 593, 219, 217, 102, 116] 1.947340 \n1251 [308, 225, 217, 239, 102, 116, 167] 1.947211 \n1252 [308, 400, 593, 217, 239, 136, 167] 1.946752 \n1253 [308, 225, 400, 593, 572, 219, 239, 102, 116, ... 1.946735 \n1254 [400, 593, 219, 239, 102, 116, 136] 1.946721 \n1255 [308, 400, 593, 572, 217, 136] 1.946228 \n1256 [308, 400, 572, 102, 167] 1.945986 \n1257 [400, 593, 217, 239, 136, 167] 1.945771 \n1258 [225, 400, 593, 217, 239, 136, 167] 1.945568 \n1259 [308, 225, 400, 593, 239, 116, 136] 1.945527 \n1260 [308, 225, 400, 593, 239, 102, 116] 1.945514 \n1261 [400, 593, 217, 239, 102, 167] 1.945190 \n1262 [225, 400, 593, 239, 102, 136] 1.945121 \n1263 [308, 400, 239, 102, 116, 167] 1.944380 \n1264 [308, 225, 217, 102, 136] 1.944366 \n1265 [572, 102, 116, 136, 167] 1.944024 \n1266 [225, 400, 593, 219, 116, 136] 1.943569 \n1267 [593, 116, 136, 167] 1.943258 \n1268 [225, 400, 593, 572, 219, 239, 102, 116, 136] 1.943224 \n1269 [593, 239, 116, 136, 167] 1.943037 \n1270 [308, 593, 572, 102, 167] 1.942758 \n1271 [308, 225, 400, 593, 572, 217, 239, 102, 167] 1.942636 \n1272 [308, 225, 400, 593, 219, 102, 116] 1.942613 \n1273 [225, 572, 219, 217, 102, 116, 167] 1.942569 \n1274 [308, 400, 102, 167] 1.942483 \n1275 [225, 572, 217, 102, 167] 1.942220 \n1276 [400, 593, 572, 219, 102, 116] 1.942044 \n1277 [308, 400, 593, 239, 102, 136] 1.941816 \n1278 [225, 400, 593, 219, 217, 102, 167] 1.941631 \n1279 [308, 225, 217, 239, 116, 136, 167] 1.941220 \n1280 [308, 225, 400, 593, 572, 219, 217, 102, 116] 1.941125 \n1281 [308, 225, 219, 239, 102, 116, 136, 167] 1.940978 \n1282 [225, 400, 593, 167] 1.940937 \n1283 [308, 225, 400, 593, 219, 239, 102, 136, 167] 1.940604 \n1284 [308, 225, 400, 593, 116] 1.940526 \n1285 [308, 400, 593, 219, 217, 102, 116] 1.940475 \n1286 [400, 572, 116, 167] 1.940352 \n1287 [225, 400, 593, 219, 217, 116, 136] 1.940314 \n1288 [400, 593, 572, 136] 1.940254 \n1289 [217, 102, 116, 136] 1.940133 \n1290 [308, 225, 572, 219, 102, 136, 167] 1.940018 \n1291 [308, 400, 593, 572, 219, 239, 102, 116, 136] 1.939930 \n1292 [400, 593, 219, 217, 116, 136] 1.939715 \n1293 [400, 593, 217, 167] 1.939679 \n1294 [308, 225, 400, 593, 572, 136] 1.939398 \n1295 [400, 593, 219, 217, 102, 167] 1.939293 \n1296 [400, 593, 572, 219, 217, 102, 167] 1.938602 \n1297 [225, 572, 217, 239, 102, 116, 136] 1.938467 \n1298 [308, 219, 217, 102, 136, 167] 1.938428 \n1299 [225, 400, 593, 572, 219, 217, 102, 167] 1.938391 \n1300 [400, 102, 167] 1.938372 \n1301 [400, 593, 572, 219, 239, 102, 116, 136] 1.937614 \n1302 [308, 593, 219, 116, 136, 167] 1.937573 \n1303 [225, 400, 572, 239, 102, 116, 167] 1.937516 \n1304 [308, 225, 400, 593, 572, 217, 239, 136, 167] 1.937348 \n1305 [308, 225, 572, 217, 102, 116] 1.937288 \n1306 [225, 400, 593, 572, 217, 239, 102, 167] 1.937088 \n1307 [225, 400, 593, 219, 102, 167] 1.936953 \n1308 [225, 219, 217, 102, 116, 167] 1.936789 \n1309 [225, 400, 572, 239, 116, 136, 167] 1.936598 \n1310 [308, 593, 572, 136, 167] 1.936428 \n1311 [308, 400, 593, 572, 217, 239, 102, 167] 1.936267 \n1312 [400, 593, 572, 219, 217, 116, 136] 1.936126 \n1313 [308, 400, 593, 572, 219, 217, 102, 116] 1.936006 \n1314 [308, 225, 400, 593, 219, 217, 239, 102, 116, ... 1.935669 \n1315 [593, 572, 239, 102, 116, 167] 1.935544 \n1316 [225, 400, 593, 572, 239, 102, 136] 1.935170 \n1317 [308, 572, 217, 102, 136] 1.935142 \n1318 [225, 400, 593, 572, 219, 217, 116, 136] 1.935108 \n1319 [308, 225, 572, 217, 239, 102, 116, 167] 1.935044 \n1320 [225, 572, 217, 239, 102, 136, 167] 1.934848 \n1321 [225, 400, 593, 219, 239, 102, 136, 167] 1.934427 \n1322 [593, 102, 116, 167] 1.934333 \n1323 [572, 217, 102, 136] 1.934305 \n1324 [308, 225, 400, 593, 217, 239, 116, 167] 1.934087 \n1325 [308, 225, 572, 219, 239, 102, 116, 136, 167] 1.934080 \n1326 [219, 217, 102, 116, 167] 1.934069 \n1327 [308, 400, 572, 136, 167] 1.933999 \n1328 [308, 225, 400, 593, 572, 217, 116] 1.933642 \n1329 [308, 400, 593, 217, 116] 1.933590 \n1330 [308, 225, 400, 593, 572, 219, 102, 116] 1.933500 \n1331 [308, 400, 593, 572, 217, 239, 136, 167] 1.933208 \n1332 [400, 593, 572, 217, 239, 102, 167] 1.932892 \n1333 [308, 225, 400, 593, 572, 219, 239, 102, 136, ... 1.932773 \n1334 [225, 400, 593, 572, 219, 116, 136] 1.932727 \n1335 [225, 572, 219, 102, 116, 167] 1.932670 \n1336 [308, 400, 572, 239, 116, 136, 167] 1.932634 \n1337 [308, 400, 593, 219, 217, 239, 102, 116, 167] 1.932632 \n1338 [308, 400, 593, 572, 239, 102, 136] 1.932510 \n1339 [400, 593, 219, 217, 239, 102, 116, 167] 1.932426 \n1340 [225, 400, 593, 219, 217, 239, 102, 116, 167] 1.932362 \n1341 [225, 400, 593, 572, 217, 167] 1.931749 \n1342 [308, 225, 219, 102, 136, 167] 1.931659 \n1343 [219, 102, 116, 136] 1.931569 \n1344 [308, 572, 219, 102, 116, 136] 1.931531 \n1345 [225, 400, 593, 239, 116, 136] 1.931437 \n1346 [225, 400, 593, 572, 217, 239, 136, 167] 1.931430 \n1347 [400, 572, 239, 102, 116, 136] 1.931292 \n1348 [308, 225, 217, 102, 116] 1.931052 \n1349 [400, 593, 572, 217, 239, 136, 167] 1.931012 \n1350 [308, 225, 400, 593, 219, 217, 116, 136] 1.930899 \n1351 [308, 400, 572, 239, 102, 116, 167] 1.930891 \n1352 [225, 400, 593, 217, 239, 116, 167] 1.930870 \n1353 [308, 217, 239, 116, 136, 167] 1.930776 \n1354 [308, 400, 593, 219, 239, 102, 136, 167] 1.930748 \n1355 [308, 400, 136, 167] 1.930699 \n1356 [308, 217, 239, 102, 116, 167] 1.930414 \n1357 [225, 400, 593, 572, 219, 102, 167] 1.930281 \n1358 [225, 219, 102, 116, 167] 1.929621 \n1359 [308, 225, 400, 593, 219, 217, 102, 167] 1.929599 \n1360 [400, 593, 219, 116, 136] 1.929208 \n1361 [225, 217, 239, 102, 116, 136] 1.929088 \n1362 [225, 116, 136, 167] 1.928273 \n1363 [308, 225, 572, 217, 239, 116, 136, 167] 1.928182 \n1364 [225, 400, 593, 239, 102, 116] 1.928092 \n1365 [400, 593, 217, 239, 116, 167] 1.927817 \n1366 [225, 400, 593, 572, 219, 239, 102, 136, 167] 1.927738 \n1367 [308, 225, 400, 593, 572, 239, 102, 116] 1.927619 \n1368 [308, 225, 400, 593, 572, 219, 217, 239, 102, ... 1.927371 \n1369 [308, 225, 593, 217, 239, 102, 136] 1.927084 \n1370 [308, 225, 400, 593, 219, 217, 239, 116, 136, ... 1.926872 \n1371 [308, 400, 593, 217, 239, 116, 167] 1.926760 \n1372 [308, 225, 400, 593, 219, 116, 136] 1.926737 \n1373 [308, 225, 400, 593, 572, 219, 217, 102, 167] 1.926470 \n1374 [308, 593, 102, 136] 1.926228 \n1375 [308, 225, 400, 593, 572, 219, 217, 116, 136] 1.926083 \n1376 [308, 225, 400, 593, 572, 239, 116, 136] 1.926010 \n1377 [572, 217, 239, 102, 136, 167] 1.925971 \n1378 [308, 400, 116, 167] 1.925438 \n1379 [308, 219, 239, 102, 116, 136, 167] 1.925196 \n1380 [400, 593, 572, 217, 167] 1.925141 \n1381 [308, 400, 593, 572, 219, 239, 102, 136, 167] 1.924616 \n1382 [308, 400, 593, 572, 219, 217, 239, 102, 116, ... 1.924557 \n1383 [308, 400, 593, 219, 217, 239, 116, 136, 167] 1.924541 \n1384 [400, 593, 219, 239, 102, 136, 167] 1.924492 \n1385 [400, 136, 167] 1.924262 \n1386 [400, 593, 572, 219, 217, 239, 102, 116, 167] 1.924065 \n1387 [225, 400, 593, 572, 219, 217, 239, 102, 116, ... 1.924034 \n1388 [308, 225, 572, 219, 217, 102, 116, 167] 1.923816 \n1389 [572, 217, 239, 102, 116, 136] 1.923760 \n1390 [308, 400, 593, 219, 217, 116, 136] 1.923487 \n1391 [308, 400, 593, 219, 102, 116] 1.923396 \n1392 [308, 225, 572, 217, 102, 167] 1.923384 \n1393 [308, 400, 593, 239, 116, 136] 1.923161 \n1394 [308, 572, 217, 239, 102, 116, 167] 1.922802 \n1395 [308, 225, 400, 593, 217, 167] 1.922791 \n1396 [308, 572, 219, 239, 102, 116, 136, 167] 1.922783 \n1397 [400, 593, 219, 217, 239, 116, 136, 167] 1.922675 \n1398 [308, 225, 593, 572, 217, 239, 102, 136] 1.922290 \n1399 [400, 239, 102, 116, 136] 1.922271 \n1400 [400, 593, 572, 219, 116, 136] 1.922148 \n1401 [225, 219, 239, 102, 116, 136, 167] 1.921969 \n1402 [225, 400, 593, 219, 217, 239, 116, 136, 167] 1.921655 \n1403 [308, 225, 219, 217, 102, 116, 167] 1.921607 \n1404 [225, 572, 219, 239, 102, 116, 136, 167] 1.921337 \n1405 [308, 225, 400, 593, 239, 102, 167] 1.921027 \n1406 [225, 217, 239, 102, 136, 167] 1.920957 \n1407 [308, 225, 400, 593, 239, 136, 167] 1.920728 \n1408 [308, 400, 593, 572, 219, 217, 116, 136] 1.920513 \n1409 [308, 400, 593, 219, 217, 102, 167] 1.920513 \n1410 [400, 593, 572, 219, 239, 102, 136, 167] 1.920447 \n1411 [308, 572, 217, 239, 116, 136, 167] 1.920288 \n1412 [308, 593, 217, 239, 102, 136] 1.920120 \n1413 [308, 400, 593, 572, 217, 116] 1.920036 \n1414 [308, 400, 593, 572, 219, 217, 102, 167] 1.919832 \n1415 [308, 225, 400, 593, 219, 102, 167] 1.919812 \n1416 [225, 400, 593, 219, 217, 136, 167] 1.919431 \n1417 [308, 225, 400, 593, 572, 219, 116, 136] 1.918980 \n1418 [308, 225, 400, 593, 572, 219, 217, 239, 116, ... 1.918950 \n1419 [308, 400, 593, 102] 1.918909 \n1420 [308, 593, 572, 217, 239, 102, 136] 1.918804 \n1421 [225, 217, 102, 116] 1.918793 \n1422 [225, 400, 593, 572, 219, 217, 136, 167] 1.918540 \n1423 [308, 225, 400, 593, 219, 239, 102, 116, 167] 1.918533 \n1424 [308, 400, 593, 239, 102, 116] 1.917949 \n1425 [308, 400, 593, 572, 219, 102, 116] 1.917911 \n1426 [308, 593, 102, 116] 1.917848 \n1427 [308, 225, 400, 593, 572, 116] 1.917830 \n1428 [572, 239, 102, 116, 136, 167] 1.917790 \n1429 [400, 593, 572, 219, 217, 136, 167] 1.917537 \n1430 [308, 225, 400, 593, 572, 217, 239, 116, 167] 1.917480 \n1431 [400, 593, 219, 102, 167] 1.917185 \n1432 [308, 572, 219, 102, 136, 167] 1.916774 \n1433 [308, 400, 593, 572, 219, 217, 239, 116, 136, ... 1.916693 \n1434 [400, 593, 572, 219, 102, 167] 1.916534 \n1435 [400, 593, 572, 116] 1.915745 \n1436 [400, 593, 219, 217, 136, 167] 1.915541 \n1437 [308, 400, 593, 572, 102] 1.915412 \n1438 [308, 225, 400, 593, 572, 219, 102, 167] 1.915039 \n1439 [400, 572, 239, 102, 136, 167] 1.914934 \n1440 [225, 400, 593, 219, 136, 167] 1.914920 \n1441 [308, 593, 116, 136] 1.914726 \n1442 [400, 593, 572, 219, 217, 239, 116, 136, 167] 1.914647 \n1443 [308, 572, 219, 217, 102, 116, 167] 1.914646 \n1444 [308, 225, 593, 219, 217, 239, 102, 116, 136] 1.914326 \n1445 [593, 239, 102, 116, 136] 1.914234 \n1446 [225, 400, 593, 572, 219, 217, 239, 116, 136, ... 1.913895 \n1447 [308, 593, 572, 116, 167] 1.913873 \n1448 [308, 593, 219, 217, 239, 102, 116, 136] 1.913524 \n1449 [308, 219, 102, 116, 136] 1.913330 \n1450 [308, 225, 400, 593, 219, 217, 136, 167] 1.913159 \n1451 [308, 225, 572, 217, 116, 136] 1.913029 \n1452 [308, 225, 400, 593, 572, 217, 167] 1.912793 \n1453 [225, 400, 593, 572, 167] 1.912585 \n1454 [225, 217, 239, 102, 116, 167] 1.912571 \n1455 [593, 572, 219, 217, 102, 136] 1.912536 \n1456 [308, 400, 572, 116, 167] 1.912443 \n1457 [219, 102, 136, 167] 1.911624 \n1458 [308, 225, 400, 593, 219, 239, 116, 136, 167] 1.911415 \n1459 [308, 225, 400, 593, 572, 219, 217, 136, 167] 1.911409 \n1460 [308, 593, 572, 219, 217, 239, 102, 116, 136] 1.911286 \n1461 [308, 400, 593, 136] 1.911090 \n1462 [308, 225, 593, 572, 219, 217, 239, 102, 116, ... 1.911055 \n1463 [225, 400, 593, 572, 217, 239, 116, 167] 1.911037 \n1464 [225, 400, 593, 572, 219, 136, 167] 1.910703 \n1465 [225, 400, 593, 219, 239, 102, 116, 167] 1.910620 \n1466 [225, 400, 593, 572, 239, 116, 136] 1.910375 \n1467 [225, 400, 593, 572, 239, 102, 116] 1.910242 \n1468 [308, 225, 217, 102, 167] 1.910146 \n1469 [225, 572, 217, 239, 102, 116, 167] 1.910005 \n1470 [308, 400, 593, 572, 217, 239, 116, 167] 1.909574 \n1471 [572, 219, 239, 102, 116, 136, 167] 1.909380 \n1472 [572, 219, 217, 116, 136, 167] 1.909264 \n1473 [308, 225, 400, 593, 572, 219, 239, 102, 116, ... 1.909176 \n1474 [572, 217, 102, 167] 1.908868 \n1475 [572, 219, 102, 116, 167] 1.908788 \n1476 [225, 572, 217, 116, 136] 1.908765 \n1477 [308, 225, 400, 593, 572, 239, 102, 167] 1.908323 \n1478 [225, 572, 219, 217, 116, 136, 167] 1.908025 \n1479 [593, 572, 219, 217, 239, 102, 116, 136] 1.907877 \n1480 [308, 400, 593, 219, 116, 136] 1.907642 \n1481 [400, 593, 572, 239, 102, 136] 1.906944 \n1482 [225, 217, 239, 116, 136, 167] 1.906857 \n1483 [308, 225, 572, 239, 102, 116, 136] 1.906723 \n1484 [308, 400, 593, 572, 136] 1.906718 \n1485 [308, 225, 572, 219, 102, 116, 167] 1.906627 \n1486 [572, 217, 102, 116] 1.906524 \n1487 [308, 225, 400, 593, 572, 239, 136, 167] 1.906519 \n1488 [593, 219, 217, 239, 102, 116, 136] 1.906101 \n1489 [308, 400, 593, 572, 239, 116, 136] 1.906007 \n1490 [225, 593, 572, 219, 217, 102, 136] 1.905952 \n1491 [400, 593, 572, 217, 239, 116, 167] 1.905728 \n1492 [308, 219, 217, 102, 116, 167] 1.905660 \n1493 [308, 225, 239, 102, 116, 136] 1.905573 \n1494 [308, 225, 400, 593, 239, 116, 167] 1.905537 \n1495 [400, 593, 239, 102, 136] 1.905436 \n1496 [308, 225, 593, 217, 239, 102, 116] 1.905201 \n1497 [308, 225, 219, 102, 116, 167] 1.904839 \n1498 [308, 400, 593, 219, 239, 102, 116, 167] 1.904839 \n1499 [308, 400, 593, 572, 219, 217, 136, 167] 1.904306 \n1500 [593, 572, 217, 239, 102, 136] 1.904007 \n1501 [308, 225, 400, 593, 219, 136, 167] 1.903927 \n1502 [308, 400, 593, 572, 239, 102, 116] 1.903856 \n1503 [308, 225, 400, 593, 167] 1.903564 \n1504 [308, 400, 593, 219, 217, 136, 167] 1.903511 \n1505 [308, 400, 593, 572, 219, 116, 136] 1.903464 \n1506 [308, 225, 217, 116, 136] 1.903142 \n1507 [308, 225, 572, 102, 136] 1.902446 \n1508 [225, 572, 217, 239, 116, 136, 167] 1.902407 \n1509 [225, 593, 572, 217, 239, 102, 136] 1.902360 \n1510 [225, 400, 593, 219, 239, 116, 136, 167] 1.902262 \n1511 [308, 225, 400, 593, 572, 219, 239, 116, 136, ... 1.902141 \n1512 [308, 400, 593, 217, 167] 1.902083 \n1513 [400, 239, 116, 136, 167] 1.901725 \n1514 [225, 593, 572, 219, 217, 239, 102, 116, 136] 1.901669 \n1515 [225, 400, 593, 572, 219, 239, 102, 116, 167] 1.901299 \n1516 [225, 593, 219, 217, 239, 102, 116, 136] 1.901274 \n1517 [308, 225, 400, 219, 217, 239, 102, 116, 136] 1.901154 \n1518 [225, 217, 102, 167] 1.901083 \n1519 [308, 225, 593, 217, 239, 116, 136] 1.900887 \n1520 [225, 572, 217, 136, 167] 1.900624 \n1521 [308, 225, 572, 219, 217, 116, 136, 167] 1.900552 \n1522 [308, 225, 593, 219, 217, 239, 102, 136, 167] 1.900499 \n1523 [308, 225, 400, 593, 572, 219, 136, 167] 1.900493 \n1524 [225, 400, 593, 239, 136, 167] 1.900400 \n1525 [308, 572, 217, 102, 116] 1.900319 \n1526 [219, 239, 102, 116, 136, 167] 1.900113 \n1527 [225, 400, 219, 217, 102, 136] 1.899976 \n1528 [308, 225, 593, 572, 219, 217, 239, 102, 136, ... 1.899888 \n1529 [225, 217, 102, 136] 1.899884 \n1530 [400, 593, 239, 116, 136] 1.899423 \n1531 [308, 593, 572, 219, 217, 239, 102, 136, 167] 1.899409 \n1532 [400, 572, 219, 217, 102, 136] 1.899399 \n1533 [225, 400, 572, 219, 217, 102, 136] 1.899279 \n1534 [308, 400, 593, 219, 239, 116, 136, 167] 1.899166 \n1535 [225, 400, 593, 219, 217, 116, 167] 1.899084 \n1536 [308, 225, 572, 217, 136, 167] 1.898858 \n1537 [308, 593, 219, 217, 239, 102, 136, 167] 1.898395 \n1538 [593, 239, 102, 116, 167] 1.897991 \n1539 [308, 225, 593, 572, 219, 217, 102, 136] 1.897873 \n1540 [225, 400, 593, 239, 102, 167] 1.897619 \n1541 [400, 219, 217, 102, 136] 1.897439 \n1542 [308, 225, 400, 219, 217, 102, 136] 1.897244 \n1543 [400, 239, 102, 136, 167] 1.897172 \n1544 [308, 400, 593, 219, 102, 167] 1.897168 \n1545 [308, 400, 593, 572, 219, 102, 167] 1.897123 \n1546 [308, 400, 593, 572, 219, 239, 102, 116, 167] 1.897044 \n1547 [225, 593, 217, 239, 102, 136] 1.896702 \n1548 [400, 593, 572, 219, 136, 167] 1.896567 \n1549 [308, 400, 219, 217, 239, 102, 116, 136] 1.896456 \n1550 [308, 400, 593, 116] 1.896365 \n1551 [593, 239, 102, 136, 167] 1.896306 \n1552 [593, 572, 219, 217, 239, 102, 136, 167] 1.896251 \n1553 [308, 400, 593, 572, 217, 167] 1.896103 \n1554 [225, 219, 217, 116, 136, 167] 1.895942 \n1555 [400, 572, 239, 116, 136, 167] 1.895788 \n1556 [225, 572, 219, 116, 136, 167] 1.895638 \n1557 [400, 593, 219, 239, 102, 116, 167] 1.895555 \n1558 [308, 225, 593, 572, 217, 239, 102, 116] 1.895475 \n1559 [308, 225, 400, 572, 219, 217, 102, 136] 1.895379 \n1560 [308, 225, 219, 217, 116, 136, 167] 1.895285 \n1561 [225, 593, 572, 219, 102, 136] 1.895143 \n1562 [400, 593, 219, 136, 167] 1.894684 \n1563 [225, 400, 593, 572, 219, 217, 116, 167] 1.894519 \n1564 [225, 572, 217, 116, 167] 1.894493 \n1565 [225, 400, 593, 219, 116, 167] 1.894372 \n1566 [308, 400, 593, 239, 136, 167] 1.894235 \n1567 [572, 217, 239, 116, 136, 167] 1.894157 \n1568 [308, 225, 400, 572, 219, 217, 239, 102, 116, ... 1.894063 \n1569 [308, 225, 400, 593, 219, 217, 116, 167] 1.894009 \n1570 [308, 225, 572, 239, 102, 136, 167] 1.893969 \n1571 [308, 593, 217, 239, 116, 136] 1.893866 \n1572 [225, 593, 572, 217, 102] 1.893750 \n1573 [225, 400, 593, 572, 219, 239, 116, 136, 167] 1.893035 \n1574 [572, 217, 239, 102, 116, 167] 1.892985 \n1575 [308, 225, 400, 217, 239, 102, 136] 1.892764 \n1576 [308, 593, 217, 239, 102, 116] 1.892545 \n1577 [225, 400, 219, 102, 136] 1.892200 \n1578 [308, 219, 102, 136, 167] 1.891421 \n1579 [308, 400, 593, 572, 219, 239, 116, 136, 167] 1.891132 \n1580 [217, 239, 102, 116, 136] 1.891017 \n1581 [308, 593, 572, 219, 217, 102, 136] 1.890932 \n1582 [308, 225, 593, 219, 239, 102, 116, 136] 1.890858 \n1583 [225, 400, 593, 239, 116, 167] 1.890666 \n1584 [400, 593, 219, 217, 116, 167] 1.890495 \n1585 [225, 593, 572, 219, 217, 239, 102, 136, 167] 1.890383 \n1586 [308, 225, 593, 572, 217, 239, 116, 136] 1.890184 \n1587 [308, 225, 400, 593, 572, 219, 217, 116, 167] 1.890074 \n1588 [593, 219, 217, 239, 102, 136, 167] 1.890072 \n1589 [308, 225, 400, 593, 572, 167] 1.889924 \n1590 [308, 400, 572, 219, 217, 239, 102, 116, 136] 1.889654 \n1591 [308, 400, 593, 239, 102, 167] 1.889546 \n1592 [308, 572, 219, 217, 116, 136, 167] 1.889529 \n1593 [400, 593, 219, 239, 116, 136, 167] 1.889467 \n1594 [217, 239, 116, 136, 167] 1.889416 \n1595 [400, 572, 239, 102, 116, 167] 1.889327 \n1596 [593, 217, 239, 102, 136] 1.889248 \n1597 [225, 217, 116, 167] 1.888861 \n1598 [308, 225, 593, 219, 217, 102, 136] 1.888634 \n1599 [400, 593, 572, 219, 239, 102, 116, 167] 1.888479 \n1600 [225, 593, 219, 217, 102, 136] 1.888460 \n1601 [400, 239, 102, 116, 167] 1.888268 \n1602 [217, 239, 102, 136, 167] 1.888044 \n1603 [400, 593, 572, 219, 217, 116, 167] 1.888032 \n1604 [308, 400, 572, 219, 217, 102, 136] 1.887847 \n1605 [308, 225, 593, 572, 219, 239, 102, 116, 136] 1.887634 \n1606 [225, 400, 593, 572, 239, 102, 167] 1.887590 \n1607 [225, 400, 593, 572, 239, 136, 167] 1.887417 \n1608 [225, 400, 572, 219, 102, 136] 1.887349 \n1609 [308, 225, 400, 219, 217, 239, 102, 136, 167] 1.887176 \n1610 [308, 400, 219, 217, 102, 136] 1.887077 \n1611 [308, 225, 400, 593, 572, 239, 116, 167] 1.886958 \n1612 [308, 225, 239, 102, 136, 167] 1.886808 \n1613 [225, 593, 219, 217, 239, 102, 136, 167] 1.886502 \n1614 [308, 572, 217, 102, 167] 1.886411 \n1615 [225, 400, 219, 217, 239, 102, 116, 136] 1.886034 \n1616 [400, 593, 239, 102, 116] 1.885936 \n1617 [219, 217, 116, 136, 167] 1.885506 \n1618 [308, 225, 593, 217, 239, 102, 167] 1.885200 \n1619 [308, 593, 572, 217, 239, 102, 116] 1.885037 \n1620 [225, 400, 593, 572, 219, 116, 167] 1.884950 \n1621 [308, 225, 400, 219, 102, 136] 1.884886 \n1622 [308, 225, 400, 572, 217, 239, 102, 136] 1.884770 \n1623 [225, 219, 116, 136, 167] 1.884390 \n1624 [593, 219, 217, 102, 136] 1.884162 \n1625 [308, 225, 400, 593, 219, 116, 167] 1.884110 \n1626 [308, 400, 593, 572, 239, 136, 167] 1.883903 \n1627 [593, 572, 217, 102] 1.883775 \n1628 [308, 593, 572, 217, 239, 116, 136] 1.883679 \n1629 [400, 593, 572, 239, 116, 136] 1.883522 \n1630 [308, 593, 116, 167] 1.883508 \n1631 [308, 225, 572, 219, 116, 136, 167] 1.883171 \n1632 [400, 219, 217, 239, 102, 116, 136] 1.883013 \n1633 [308, 400, 593, 572, 219, 136, 167] 1.882623 \n1634 [308, 225, 400, 572, 219, 217, 239, 102, 136, ... 1.882446 \n1635 [308, 400, 593, 572, 239, 102, 167] 1.882052 \n1636 [400, 593, 167] 1.882047 \n1637 [308, 225, 217, 136, 167] 1.881969 \n1638 [400, 593, 572, 219, 239, 116, 136, 167] 1.881894 \n1639 [308, 225, 593, 572, 219, 102, 136] 1.881880 \n1640 [308, 400, 593, 219, 136, 167] 1.881368 \n1641 [308, 400, 593, 572, 116] 1.881251 \n1642 [308, 400, 219, 217, 239, 102, 136, 167] 1.881076 \n1643 [308, 225, 400, 572, 219, 102, 136] 1.881052 \n1644 [217, 239, 102, 116, 167] 1.881004 \n1645 [308, 400, 593, 219, 217, 116, 167] 1.880989 \n1646 [593, 572, 219, 102, 136] 1.880847 \n1647 [308, 217, 102, 136] 1.880675 \n1648 [308, 225, 593, 217, 239, 136, 167] 1.880671 \n1649 [308, 225, 572, 217, 116, 167] 1.880495 \n1650 [225, 400, 572, 219, 217, 239, 102, 116, 136] 1.880431 \n1651 [308, 225, 593, 572, 217, 239, 102, 167] 1.880235 \n1652 [308, 593, 102, 167] 1.879581 \n1653 [308, 225, 572, 102, 116] 1.879449 \n1654 [225, 593, 217, 239, 102, 116] 1.879291 \n1655 [308, 400, 593, 572, 219, 217, 116, 167] 1.879256 \n1656 [219, 102, 116, 167] 1.879071 \n1657 [308, 225, 400, 219, 239, 102, 116, 136] 1.879051 \n1658 [308, 225, 217, 116, 167] 1.879013 \n1659 [308, 225, 593, 572, 217, 102] 1.878659 \n1660 [308, 225, 219, 116, 136, 167] 1.878007 \n1661 [308, 225, 400, 593, 572, 219, 116, 167] 1.877799 \n1662 [400, 572, 219, 217, 239, 102, 116, 136] 1.877722 \n1663 [308, 225, 239, 116, 136, 167] 1.877433 \n1664 [308, 400, 572, 219, 217, 239, 102, 136, 167] 1.877120 \n1665 [308, 225, 593, 219, 217, 239, 102, 116, 167] 1.877004 \n1666 [308, 219, 217, 116, 136, 167] 1.876960 \n1667 [308, 400, 593, 239, 116, 167] 1.876811 \n1668 [400, 593, 572, 239, 102, 116] 1.876610 \n1669 [308, 400, 217, 239, 102, 136] 1.876380 \n1670 [308, 572, 217, 116, 136] 1.876313 \n1671 [225, 593, 217, 239, 116, 136] 1.876261 \n1672 [593, 217, 239, 116, 136] 1.876180 \n1673 [308, 593, 136, 167] 1.875618 \n1674 [225, 593, 219, 102, 136] 1.875263 \n1675 [225, 400, 219, 217, 102, 116] 1.875225 \n1676 [308, 572, 219, 102, 116, 167] 1.874971 \n1677 [308, 593, 219, 217, 102, 136] 1.874852 \n1678 [308, 225, 593, 572, 217, 239, 136, 167] 1.874806 \n1679 [308, 225, 400, 219, 217, 102, 116] 1.874774 \n1680 [308, 593, 572, 219, 239, 102, 116, 136] 1.874665 \n1681 [308, 225, 400, 217, 239, 102, 116] 1.874496 \n1682 [308, 225, 593, 572, 219, 217, 239, 102, 116, ... 1.874473 \n1683 [308, 225, 239, 102, 116, 167] 1.874402 \n1684 [225, 593, 572, 217, 239, 102, 116] 1.874177 \n1685 [308, 593, 219, 239, 102, 116, 136] 1.874124 \n1686 [308, 225, 593, 572, 219, 239, 102, 136, 167] 1.873393 \n1687 [308, 225, 593, 219, 239, 102, 136, 167] 1.872903 \n1688 [225, 593, 217, 102] 1.871851 \n1689 [225, 593, 572, 219, 217, 102, 116] 1.871453 \n1690 [308, 225, 593, 219, 102, 136] 1.871332 \n1691 [225, 102, 136, 167] 1.871321 \n1692 [400, 572, 219, 102, 136] 1.871212 \n1693 [308, 225, 400, 572, 219, 239, 102, 116, 136] 1.871155 \n1694 [308, 400, 572, 217, 239, 102, 136] 1.870887 \n1695 [308, 225, 593, 572, 239, 102, 136] 1.870723 \n1696 [308, 225, 400, 572, 219, 217, 102, 116] 1.870699 \n1697 [225, 400, 572, 219, 217, 102, 116] 1.870656 \n1698 [308, 593, 217, 239, 136, 167] 1.870601 \n1699 [225, 400, 219, 217, 239, 102, 136, 167] 1.870592 \n1700 [308, 225, 572, 239, 102, 116, 167] 1.870155 \n1701 [225, 593, 572, 219, 239, 102, 116, 136] 1.869971 \n1702 [308, 593, 219, 217, 239, 102, 116, 167] 1.869768 \n1703 [308, 225, 572, 239, 116, 136, 167] 1.869686 \n1704 [308, 593, 217, 239, 102, 167] 1.869626 \n1705 [308, 225, 593, 239, 102, 136] 1.869612 \n1706 [400, 593, 219, 116, 167] 1.869550 \n1707 [308, 225, 400, 217, 102] 1.869347 \n1708 [400, 219, 102, 136] 1.869340 \n1709 [308, 225, 593, 572, 219, 217, 102, 116] 1.869141 \n1710 [225, 102, 116, 136] 1.869046 \n1711 [225, 593, 572, 217, 239, 116, 136] 1.869010 \n1712 [225, 400, 593, 572, 239, 116, 167] 1.868855 \n1713 [308, 593, 572, 219, 217, 239, 102, 116, 167] 1.868702 \n1714 [308, 225, 593, 217, 102] 1.868636 \n1715 [593, 572, 217, 239, 116, 136] 1.868457 \n1716 [225, 217, 116, 136] 1.868383 \n1717 [308, 593, 572, 217, 239, 102, 167] 1.868317 \n1718 [400, 593, 572, 167] 1.868206 \n1719 [225, 400, 572, 219, 217, 239, 102, 136, 167] 1.868054 \n1720 [225, 593, 219, 239, 102, 116, 136] 1.867706 \n1721 [308, 217, 102, 116] 1.867603 \n1722 [308, 225, 400, 217, 239, 116, 136] 1.867322 \n1723 [572, 219, 116, 136, 167] 1.867110 \n1724 [308, 225, 400, 219, 217, 239, 102, 116, 167] 1.867005 \n1725 [308, 593, 572, 217, 239, 136, 167] 1.866774 \n1726 [593, 217, 239, 102, 116] 1.866564 \n1727 [308, 225, 593, 219, 217, 239, 116, 136, 167] 1.866449 \n1728 [593, 572, 219, 217, 102, 116] 1.866383 \n1729 [225, 400, 219, 102, 116] 1.866281 \n1730 [400, 219, 217, 239, 102, 136, 167] 1.865853 \n1731 [400, 219, 217, 102, 116] 1.865742 \n1732 [593, 572, 217, 239, 102, 116] 1.865713 \n1733 [225, 400, 217, 102] 1.864899 \n1734 [308, 225, 593, 217, 239, 116, 167] 1.864840 \n1735 [400, 593, 572, 219, 116, 167] 1.864760 \n1736 [308, 225, 593, 572, 219, 217, 239, 116, 136, ... 1.864461 \n1737 [400, 572, 219, 217, 239, 102, 136, 167] 1.864376 \n1738 [308, 225, 400, 572, 217, 102] 1.864242 \n1739 [225, 593, 572, 217, 136] 1.864108 \n1740 [572, 217, 136, 167] 1.863795 \n1741 [308, 225, 593, 219, 217, 102, 116] 1.863228 \n1742 [308, 225, 400, 572, 217, 239, 102, 116] 1.863130 \n1743 [400, 572, 219, 217, 102, 116] 1.863109 \n1744 [572, 217, 116, 136] 1.863066 \n1745 [593, 102, 116, 136] 1.863009 \n1746 [593, 116, 167] 1.862428 \n1747 [308, 572, 217, 136, 167] 1.862032 \n1748 [572, 217, 116, 167] 1.861815 \n1749 [400, 593, 239, 136, 167] 1.861608 \n1750 [308, 400, 219, 239, 102, 116, 136] 1.861607 \n1751 [308, 225, 400, 219, 239, 102, 136, 167] 1.861523 \n1752 [225, 593, 572, 219, 217, 239, 102, 116, 167] 1.861477 \n1753 [308, 102, 116, 167] 1.861146 \n1754 [308, 225, 400, 219, 102, 116] 1.861133 \n1755 [225, 593, 219, 217, 239, 102, 116, 167] 1.861007 \n1756 [308, 400, 593, 572, 239, 116, 167] 1.860994 \n1757 [593, 102, 136, 167] 1.860974 \n1758 [308, 225, 400, 572, 219, 217, 239, 102, 116, ... 1.860862 \n1759 [308, 400, 572, 219, 102, 136] 1.860482 \n1760 [225, 593, 219, 217, 102, 116] 1.860301 \n1761 [308, 593, 219, 217, 239, 116, 136, 167] 1.860185 \n1762 [308, 400, 219, 217, 102, 116] 1.860040 \n1763 [225, 400, 572, 217, 102] 1.859971 \n1764 [308, 225, 593, 572, 217, 136] 1.859583 \n1765 [308, 225, 572, 116, 136] 1.859435 \n1766 [308, 593, 572, 219, 217, 239, 116, 136, 167] 1.859429 \n1767 [593, 572, 219, 217, 239, 102, 116, 167] 1.859415 \n1768 [308, 593, 572, 219, 239, 102, 136, 167] 1.859068 \n1769 [308, 225, 102, 116] 1.859022 \n1770 [308, 400, 219, 102, 136] 1.858956 \n1771 [308, 219, 102, 116, 167] 1.858624 \n1772 [308, 400, 572, 219, 217, 102, 116] 1.858307 \n1773 [225, 593, 572, 217, 239, 102, 167] 1.858287 \n1774 [308, 400, 593, 219, 116, 167] 1.858169 \n1775 [308, 593, 572, 219, 102, 136] 1.857674 \n1776 [308, 225, 572, 102, 167] 1.857577 \n1777 [308, 400, 219, 217, 239, 102, 116, 167] 1.857242 \n1778 [308, 102, 116, 136] 1.857171 \n1779 [593, 219, 217, 239, 102, 116, 167] 1.857156 \n1780 [308, 225, 400, 572, 219, 239, 102, 136, 167] 1.856812 \n1781 [400, 593, 572, 239, 136, 167] 1.856799 \n1782 [593, 572, 219, 239, 102, 116, 136] 1.856534 \n1783 [308, 225, 102, 136] 1.856499 \n1784 [225, 593, 217, 239, 102, 167] 1.856489 \n1785 [308, 225, 400, 219, 217, 239, 116, 136, 167] 1.856379 \n1786 [308, 225, 400, 219, 217, 102, 167] 1.856237 \n1787 [225, 593, 572, 219, 102, 116] 1.856042 \n1788 [308, 400, 593, 572, 219, 116, 167] 1.855960 \n1789 [225, 400, 572, 219, 102, 116] 1.855838 \n1790 [308, 225, 400, 572, 217, 239, 116, 136] 1.855824 \n1791 [308, 400, 572, 219, 239, 102, 116, 136] 1.855696 \n1792 [308, 225, 400, 572, 219, 217, 102, 167] 1.855555 \n1793 [308, 593, 572, 219, 217, 102, 116] 1.855545 \n1794 [225, 400, 219, 239, 102, 116, 136] 1.855482 \n1795 [308, 225, 400, 219, 217, 116, 136] 1.855245 \n1796 [308, 225, 400, 217, 239, 102, 167] 1.855034 \n1797 [593, 572, 217, 136] 1.854979 \n1798 [225, 593, 572, 219, 217, 102, 167] 1.854956 \n1799 [225, 400, 217, 239, 102, 136] 1.854857 \n1800 [225, 593, 572, 219, 239, 102, 136, 167] 1.854708 \n1801 [308, 225, 593, 239, 116, 136] 1.854678 \n1802 [308, 400, 217, 239, 102, 116] 1.854549 \n1803 [308, 225, 400, 572, 219, 102, 116] 1.854362 \n1804 [308, 225, 593, 572, 219, 217, 102, 167] 1.854076 \n1805 [308, 593, 219, 239, 102, 136, 167] 1.853867 \n1806 [225, 400, 572, 219, 217, 102, 167] 1.853528 \n1807 [308, 225, 593, 572, 217, 239, 116, 167] 1.853431 \n1808 [225, 400, 219, 217, 102, 167] 1.853222 \n1809 [225, 400, 572, 217, 239, 102, 136] 1.853179 \n1810 [225, 593, 217, 239, 136, 167] 1.853127 \n1811 [308, 225, 400, 572, 219, 217, 116, 136] 1.853088 \n1812 [225, 593, 572, 217, 239, 136, 167] 1.852939 \n1813 [308, 400, 572, 219, 217, 239, 102, 116, 167] 1.851793 \n1814 [400, 593, 239, 116, 167] 1.851675 \n1815 [593, 572, 217, 239, 136, 167] 1.851470 \n1816 [308, 572, 239, 102, 116, 136] 1.851368 \n1817 [308, 400, 593, 167] 1.851263 \n1818 [308, 593, 217, 239, 116, 167] 1.851074 \n1819 [308, 225, 593, 239, 102, 116] 1.850985 \n1820 [308, 225, 400, 572, 219, 217, 239, 116, 136, ... 1.850853 \n1821 [308, 572, 219, 116, 136, 167] 1.850510 \n1822 [400, 593, 572, 239, 102, 167] 1.850397 \n1823 [308, 225, 593, 572, 219, 102, 116] 1.850300 \n1824 [308, 593, 572, 217, 102] 1.850234 \n1825 [308, 400, 217, 239, 116, 136] 1.850021 \n1826 [308, 116, 136, 167] 1.849993 \n1827 [308, 225, 593, 572, 219, 217, 116, 136] 1.849941 \n1828 [225, 400, 572, 219, 239, 102, 116, 136] 1.849814 \n1829 [225, 217, 136, 167] 1.849579 \n1830 [593, 217, 239, 136, 167] 1.849249 \n1831 [400, 593, 239, 102, 167] 1.849200 \n1832 [225, 400, 219, 217, 239, 102, 116, 167] 1.849155 \n1833 [308, 225, 400, 217, 136] 1.849147 \n1834 [225, 593, 572, 219, 217, 239, 116, 136, 167] 1.848956 \n1835 [593, 572, 217, 239, 102, 167] 1.848899 \n1836 [308, 225, 593, 219, 239, 102, 116, 167] 1.848561 \n1837 [308, 400, 593, 572, 167] 1.848344 \n1838 [308, 225, 400, 593, 219, 217, 239, 102, 136] 1.848237 \n1839 [593, 572, 219, 217, 102, 167] 1.848183 \n1840 [225, 400, 219, 217, 116, 136] 1.848030 \n1841 [593, 572, 219, 217, 239, 116, 136, 167] 1.847885 \n1842 [308, 225, 400, 217, 239, 136, 167] 1.847715 \n1843 [308, 225, 400, 572, 217, 239, 102, 167] 1.847613 \n1844 [225, 593, 219, 217, 239, 116, 136, 167] 1.847596 \n1845 [308, 225, 593, 217, 136] 1.847327 \n1846 [593, 219, 239, 102, 116, 136] 1.847245 \n1847 [225, 593, 219, 239, 102, 136, 167] 1.847237 \n1848 [225, 572, 102, 116] 1.847216 \n1849 [308, 400, 219, 217, 239, 116, 136, 167] 1.847053 \n1850 [225, 400, 572, 219, 217, 116, 136] 1.846876 \n1851 [308, 225, 593, 572, 219, 239, 102, 116, 167] 1.846448 \n1852 [225, 593, 217, 116] 1.846395 \n1853 [593, 219, 217, 102, 116] 1.846373 \n1854 [308, 225, 400, 572, 217, 136] 1.846210 \n1855 [308, 225, 400, 593, 572, 219, 217, 239, 102, ... 1.846168 \n1856 [225, 593, 572, 217, 116] 1.846087 \n1857 [225, 593, 219, 102, 116] 1.846086 \n1858 [593, 219, 217, 239, 116, 136, 167] 1.845138 \n1859 [308, 400, 572, 217, 239, 102, 116] 1.845000 \n1860 [308, 225, 593, 572, 239, 116, 136] 1.844849 \n1861 [225, 593, 217, 239, 116, 167] 1.844703 \n1862 [308, 225, 593, 572, 239, 102, 116] 1.844412 \n1863 [308, 225, 593, 219, 102, 116] 1.844402 \n1864 [225, 593, 572, 219, 217, 116, 136] 1.844391 \n1865 [308, 217, 102, 167] 1.844321 \n1866 [225, 572, 102, 136] 1.844299 \n1867 [308, 225, 593, 219, 217, 102, 167] 1.844288 \n1868 [225, 400, 572, 219, 217, 239, 102, 116, 167] 1.844253 \n1869 [400, 572, 219, 217, 102, 167] 1.843820 \n1870 [308, 102, 136, 167] 1.843650 \n1871 [308, 593, 219, 217, 102, 116] 1.843513 \n1872 [308, 400, 572, 219, 217, 239, 116, 136, 167] 1.842116 \n1873 [308, 400, 219, 239, 102, 136, 167] 1.841918 \n1874 [308, 225, 593, 219, 217, 116, 136] 1.841868 \n1875 [308, 225, 400, 239, 102, 136] 1.841582 \n1876 [308, 225, 400, 219, 116, 136] 1.841541 \n1877 [308, 400, 572, 219, 217, 102, 167] 1.841522 \n1878 [308, 225, 400, 219, 239, 102, 116, 167] 1.840814 \n1879 [308, 225, 593, 219, 239, 116, 136, 167] 1.840353 \n1880 [308, 217, 116, 136] 1.840231 \n1881 [308, 225, 400, 572, 217, 239, 136, 167] 1.840204 \n1882 [593, 217, 239, 102, 167] 1.840150 \n1883 [308, 593, 572, 217, 239, 116, 167] 1.840145 \n1884 [308, 572, 217, 116, 167] 1.840031 \n1885 [400, 219, 217, 102, 167] 1.840012 \n1886 [593, 572, 219, 239, 102, 136, 167] 1.839928 \n1887 [308, 400, 572, 219, 239, 102, 136, 167] 1.839920 \n1888 [308, 400, 572, 219, 217, 116, 136] 1.839745 \n1889 [593, 217, 239, 116, 167] 1.839693 \n1890 [308, 400, 572, 217, 239, 116, 136] 1.839617 \n1891 [308, 400, 593, 219, 217, 239, 102, 136] 1.839587 \n1892 [225, 400, 217, 239, 102, 116] 1.839538 \n1893 [400, 219, 217, 239, 102, 116, 167] 1.839530 \n1894 [308, 400, 219, 217, 116, 136] 1.839309 \n1895 [225, 593, 116] 1.839211 \n1896 [308, 400, 219, 217, 102, 167] 1.839033 \n1897 [225, 593, 572, 102] 1.838909 \n1898 [308, 593, 572, 219, 217, 102, 167] 1.838904 \n1899 [308, 400, 593, 572, 219, 217, 239, 102, 136] 1.838527 \n1900 [308, 572, 239, 102, 136, 167] 1.838521 \n1901 [308, 225, 593, 572, 219, 239, 116, 136, 167] 1.838318 \n1902 [225, 593, 219, 217, 102, 167] 1.838093 \n1903 [308, 225, 593, 572, 217, 116] 1.838059 \n1904 [308, 225, 400, 572, 219, 217, 136, 167] 1.837932 \n1905 [225, 400, 219, 116, 136] 1.837767 \n1906 [593, 219, 102, 136] 1.837302 \n1907 [308, 225, 572, 136, 167] 1.837249 \n1908 [308, 225, 400, 217, 116] 1.837191 \n1909 [400, 572, 219, 217, 116, 136] 1.837071 \n1910 [308, 225, 116, 136] 1.836971 \n1911 [308, 225, 400, 219, 102, 167] 1.836960 \n1912 [308, 225, 400, 572, 219, 116, 136] 1.836813 \n1913 [308, 225, 400, 219, 217, 136, 167] 1.836728 \n1914 [308, 225, 400, 572, 239, 102, 136] 1.836710 \n1915 [225, 593, 217, 136] 1.836660 \n1916 [308, 400, 572, 217, 102] 1.836488 \n1917 [593, 572, 219, 217, 116, 136] 1.836363 \n1918 [308, 225, 593, 217, 116] 1.836292 \n1919 [400, 219, 102, 116] 1.836047 \n1920 [225, 400, 219, 217, 239, 116, 136, 167] 1.835858 \n1921 [400, 219, 217, 116, 136] 1.835494 \n1922 [400, 572, 219, 217, 239, 102, 116, 167] 1.835433 \n1923 [225, 400, 219, 102, 167] 1.835353 \n1924 [308, 593, 572, 219, 217, 116, 136] 1.835309 \n1925 [225, 400, 219, 239, 102, 136, 167] 1.835212 \n1926 [308, 225, 400, 572, 219, 102, 167] 1.835071 \n1927 [308, 225, 593, 572, 219, 217, 136, 167] 1.834828 \n1928 [400, 593, 572, 239, 116, 167] 1.834670 \n1929 [308, 225, 219, 217, 239, 102, 116, 136] 1.834273 \n1930 [308, 593, 219, 102, 136] 1.834268 \n1931 [308, 225, 400, 572, 219, 239, 102, 116, 167] 1.834249 \n1932 [308, 400, 217, 102] 1.834159 \n1933 [225, 400, 217, 136] 1.834127 \n1934 [308, 225, 572, 219, 217, 239, 102, 116, 136] 1.834085 \n1935 [308, 225, 400, 217, 239, 116, 167] 1.833982 \n1936 [225, 400, 572, 219, 239, 102, 136, 167] 1.833902 \n1937 [225, 400, 572, 217, 136] 1.833858 \n1938 [400, 572, 217, 239, 102, 136] 1.833767 \n1939 [400, 219, 239, 102, 116, 136] 1.833175 \n1940 [225, 400, 572, 219, 102, 167] 1.832662 \n1941 [400, 572, 217, 102] 1.832616 \n1942 [225, 593, 572, 217, 239, 116, 167] 1.832541 \n1943 [225, 593, 572, 219, 102, 167] 1.832409 \n1944 [308, 400, 217, 239, 102, 167] 1.832371 \n1945 [225, 400, 217, 116] 1.832241 \n1946 [308, 593, 572, 239, 102, 136] 1.832236 \n1947 [308, 593, 572, 217, 136] 1.832199 \n1948 [308, 225, 593, 572, 102] 1.832177 \n1949 [225, 400, 572, 219, 217, 239, 116, 136, 167] 1.831922 \n1950 [308, 225, 400, 219, 239, 116, 136, 167] 1.831670 \n1951 [308, 225, 593, 572, 219, 116, 136] 1.831428 \n1952 [225, 400, 572, 219, 116, 136] 1.831346 \n1953 [225, 400, 572, 217, 239, 102, 116] 1.831319 \n1954 [225, 400, 217, 239, 116, 136] 1.831181 \n1955 [400, 572, 219, 239, 102, 116, 136] 1.831021 \n1956 [400, 572, 219, 102, 116] 1.830807 \n1957 [308, 219, 116, 136, 167] 1.830520 \n1958 [308, 400, 219, 102, 116] 1.830431 \n1959 [308, 225, 593, 572, 219, 102, 167] 1.830428 \n1960 [593, 572, 217, 116] 1.830390 \n1961 [225, 400, 572, 219, 217, 136, 167] 1.829726 \n1962 [225, 572, 102, 167] 1.829468 \n1963 [225, 593, 219, 217, 116, 136] 1.829134 \n1964 [400, 217, 239, 102, 136] 1.829133 \n1965 [308, 225, 400, 102] 1.828904 \n1966 [308, 225, 400, 593, 219, 217, 239, 102, 116] 1.828764 \n1967 [308, 400, 572, 219, 102, 116] 1.828459 \n1968 [225, 593, 572, 219, 116, 136] 1.828297 \n1969 [225, 400, 593, 572, 219, 217, 239, 102, 136] 1.827859 \n1970 [308, 400, 572, 217, 239, 102, 167] 1.827796 \n1971 [225, 593, 572, 219, 217, 136, 167] 1.827785 \n1972 [308, 225, 400, 572, 217, 116] 1.827709 \n1973 [308, 400, 217, 239, 136, 167] 1.827610 \n1974 [593, 572, 219, 102, 116] 1.827397 \n1975 [225, 400, 593, 219, 217, 239, 102, 136] 1.827354 \n1976 [219, 116, 136, 167] 1.827027 \n1977 [400, 219, 217, 239, 116, 136, 167] 1.826700 \n1978 [308, 593, 572, 219, 239, 102, 116, 167] 1.826502 \n1979 [308, 572, 219, 217, 239, 102, 116, 136] 1.826412 \n1980 [308, 225, 593, 239, 136, 167] 1.826293 \n1981 [308, 225, 572, 116, 167] 1.826175 \n1982 [400, 217, 102] 1.826118 \n1983 [225, 400, 219, 217, 136, 167] 1.826076 \n1984 [593, 217, 102] 1.825738 \n1985 [308, 225, 400, 593, 572, 219, 217, 239, 102, ... 1.825555 \n1986 [308, 225, 400, 239, 102, 116] 1.825478 \n1987 [308, 225, 400, 572, 219, 239, 116, 136, 167] 1.825458 \n1988 [308, 219, 217, 239, 102, 116, 136] 1.824933 \n1989 [308, 225, 102, 167] 1.824821 \n1990 [308, 239, 102, 116, 136] 1.824431 \n1991 [308, 593, 219, 239, 102, 116, 167] 1.824317 \n1992 [225, 593, 572, 219, 239, 102, 116, 167] 1.824159 \n1993 [593, 572, 217, 239, 116, 167] 1.824138 \n1994 [308, 225, 593, 572, 239, 136, 167] 1.823928 \n1995 [308, 225, 400, 572, 102] 1.823817 \n1996 [308, 225, 593, 572, 239, 102, 167] 1.823765 \n1997 [593, 219, 239, 102, 136, 167] 1.823756 \n1998 [308, 225, 400, 593, 219, 239, 102, 136] 1.823645 \n1999 [400, 572, 219, 217, 239, 116, 136, 167] 1.823431 \n2000 [308, 225, 593, 219, 116, 136] 1.823298 \n2001 [308, 225, 593, 239, 102, 167] 1.823117 \n2002 [308, 400, 572, 219, 217, 136, 167] 1.822937 \n2003 [308, 225, 593, 219, 217, 136, 167] 1.822912 \n2004 [308, 225, 572, 219, 217, 239, 102, 136, 167] 1.822771 \n2005 [308, 225, 400, 239, 116, 136] 1.822688 \n2006 [225, 400, 572, 217, 239, 116, 136] 1.822680 \n2007 [308, 225, 400, 593, 217, 239, 102] 1.822680 \n2008 [308, 225, 400, 572, 217, 239, 116, 167] 1.822672 \n2009 [308, 593, 217, 102] 1.822541 \n2010 [308, 400, 572, 217, 239, 136, 167] 1.822264 \n2011 [225, 572, 116, 167] 1.821992 \n2012 [308, 593, 219, 217, 102, 167] 1.821970 \n2013 [225, 593, 219, 239, 102, 116, 167] 1.821680 \n2014 [308, 225, 400, 593, 572, 219, 239, 102, 136] 1.821634 \n2015 [308, 593, 219, 217, 116, 136] 1.820856 \n2016 [400, 593, 572, 219, 217, 239, 102, 136] 1.820780 \n2017 [593, 219, 217, 102, 167] 1.820409 \n2018 [308, 225, 219, 217, 239, 102, 136, 167] 1.820090 \n2019 [308, 593, 572, 219, 239, 116, 136, 167] 1.820060 \n2020 [308, 225, 400, 593, 219, 217, 239, 116, 136] 1.819579 \n2021 [308, 225, 400, 219, 217, 116, 167] 1.819033 \n2022 [308, 225, 116, 167] 1.818955 \n2023 [400, 593, 219, 217, 239, 102, 136] 1.818861 \n2024 [308, 225, 593, 219, 102, 167] 1.818753 \n2025 [225, 593, 572, 217, 167] 1.818744 \n2026 [593, 217, 116] 1.818694 \n2027 [308, 593, 572, 219, 102, 116] 1.818634 \n2028 [308, 593, 572, 219, 217, 136, 167] 1.818592 \n2029 [308, 400, 572, 217, 136] 1.818478 \n2030 [308, 593, 219, 239, 116, 136, 167] 1.818372 \n2031 [308, 400, 219, 217, 136, 167] 1.818316 \n2032 [593, 572, 219, 217, 136, 167] 1.817976 \n2033 [400, 572, 219, 217, 136, 167] 1.817737 \n2034 [308, 217, 116, 167] 1.817710 \n2035 [225, 593, 572, 136] 1.817697 \n2036 [308, 225, 400, 572, 219, 217, 116, 167] 1.817648 \n2037 [308, 572, 239, 116, 136, 167] 1.817591 \n2038 [308, 400, 219, 239, 102, 116, 167] 1.817557 \n2039 [308, 225, 400, 572, 219, 136, 167] 1.817513 \n2040 [225, 400, 572, 217, 116] 1.817471 \n2041 [308, 225, 593, 572, 136] 1.817413 \n2042 [308, 225, 400, 593, 572, 217, 239, 102] 1.817399 \n2043 [308, 225, 400, 219, 136, 167] 1.817399 \n2044 [225, 572, 239, 102, 116, 136] 1.817040 \n2045 [308, 225, 400, 593, 572, 219, 217, 239, 116, ... 1.816816 \n2046 [308, 400, 593, 219, 217, 239, 102, 116] 1.816794 \n2047 [225, 400, 217, 239, 102, 167] 1.816757 \n2048 [308, 225, 400, 593, 217, 239, 136] 1.816682 \n2049 [308, 217, 136, 167] 1.816527 \n2050 [308, 225, 400, 572, 239, 102, 116] 1.815672 \n2051 [308, 593, 239, 102, 136] 1.815464 \n2052 [308, 225, 593, 572, 217, 167] 1.815454 \n2053 [225, 593, 572, 239, 102, 136] 1.815177 \n2054 [308, 225, 593, 239, 116, 167] 1.815002 \n2055 [308, 225, 572, 219, 217, 102, 136] 1.814572 \n2056 [308, 400, 593, 572, 219, 217, 239, 102, 116] 1.814559 \n2057 [308, 572, 219, 217, 239, 102, 136, 167] 1.814412 \n2058 [308, 225, 593, 102] 1.814383 \n2059 [225, 593, 572, 219, 239, 116, 136, 167] 1.814332 \n2060 [225, 400, 572, 217, 239, 102, 167] 1.814090 \n2061 [308, 400, 217, 136] 1.814036 \n2062 [308, 225, 400, 593, 572, 219, 217, 102] 1.814008 \n2063 [225, 400, 219, 239, 102, 116, 167] 1.813817 \n2064 [225, 593, 572, 116] 1.813648 \n2065 [225, 593, 219, 116, 136] 1.813515 \n2066 [308, 400, 572, 219, 239, 102, 116, 167] 1.813488 \n2067 [225, 572, 116, 136] 1.813442 \n2068 [400, 572, 219, 239, 102, 136, 167] 1.813333 \n2069 [308, 225, 400, 593, 219, 217, 239, 102, 167] 1.812943 \n2070 [225, 593, 219, 102, 167] 1.812795 \n2071 [308, 225, 400, 593, 572, 219, 217, 239, 102, ... 1.812107 \n2072 [225, 593, 219, 239, 116, 136, 167] 1.811779 \n2073 [225, 400, 102] 1.811683 \n2074 [308, 225, 400, 572, 239, 116, 136] 1.811655 \n2075 [308, 225, 593, 572, 219, 217, 116, 167] 1.811640 \n2076 [308, 225, 400, 593, 219, 217, 102] 1.811618 \n2077 [308, 400, 217, 239, 116, 167] 1.811527 \n2078 [308, 225, 593, 572, 219, 136, 167] 1.811505 \n2079 [308, 225, 400, 136] 1.811458 \n2080 [593, 219, 217, 116, 136] 1.811220 \n2081 [308, 225, 400, 593, 572, 217, 239, 136] 1.811195 \n2082 [400, 217, 239, 102, 116] 1.810680 \n2083 [572, 102, 116, 167] 1.810616 \n2084 [308, 572, 239, 102, 116, 167] 1.810459 \n2085 [308, 400, 572, 219, 116, 136] 1.810404 \n2086 [308, 400, 219, 116, 136] 1.810195 \n2087 [217, 116, 167] 1.810169 \n2088 [400, 219, 239, 102, 136, 167] 1.809902 \n2089 [400, 219, 217, 136, 167] 1.809816 \n2090 [308, 400, 219, 239, 116, 136, 167] 1.809588 \n2091 [308, 219, 217, 239, 102, 136, 167] 1.809395 \n2092 [225, 400, 572, 219, 239, 102, 116, 167] 1.809212 \n2093 [308, 225, 400, 217, 167] 1.809041 \n2094 [225, 400, 219, 217, 116, 167] 1.808269 \n2095 [225, 400, 217, 239, 136, 167] 1.808178 \n2096 [225, 400, 572, 219, 136, 167] 1.808176 \n2097 [308, 400, 593, 219, 217, 239, 116, 136] 1.808111 \n2098 [225, 572, 239, 102, 136, 167] 1.807950 \n2099 [308, 225, 400, 572, 136] 1.807903 \n2100 [308, 593, 239, 116, 136] 1.807760 \n2101 [225, 400, 572, 219, 217, 116, 167] 1.807415 \n2102 [308, 593, 572, 239, 116, 136] 1.807394 \n2103 [225, 400, 219, 136, 167] 1.806960 \n2104 [400, 217, 239, 116, 136] 1.806949 \n2105 [225, 593, 219, 217, 136, 167] 1.806895 \n2106 [400, 572, 217, 239, 102, 116] 1.806667 \n2107 [308, 400, 572, 219, 102, 167] 1.806590 \n2108 [225, 400, 593, 219, 217, 239, 102, 116] 1.806453 \n2109 [308, 239, 116, 136, 167] 1.806445 \n2110 [225, 400, 572, 102] 1.806380 \n2111 [308, 400, 593, 572, 219, 217, 239, 116, 136] 1.806215 \n2112 [308, 225, 400, 572, 217, 167] 1.805988 \n2113 [225, 572, 219, 217, 239, 102, 116, 136] 1.805985 \n2114 [308, 225, 593, 217, 167] 1.805606 \n2115 [308, 400, 572, 219, 239, 116, 136, 167] 1.805588 \n2116 [400, 572, 217, 136] 1.805472 \n2117 [308, 593, 572, 217, 116] 1.805326 \n2118 [225, 400, 572, 217, 239, 136, 167] 1.805303 \n2119 [400, 219, 116, 136] 1.805130 \n2120 [225, 400, 593, 572, 219, 217, 239, 102, 116] 1.805122 \n2121 [308, 225, 400, 116] 1.804942 \n2122 [225, 116, 167] 1.804745 \n2123 [400, 572, 219, 116, 136] 1.804626 \n2124 [225, 593, 572, 219, 136, 167] 1.804571 \n2125 [308, 400, 593, 572, 219, 239, 102, 136] 1.804142 \n2126 [308, 225, 593, 572, 239, 116, 167] 1.804057 \n2127 [308, 239, 102, 136, 167] 1.803849 \n2128 [225, 593, 217, 167] 1.803799 \n2129 [308, 225, 400, 593, 219, 217, 239, 136, 167] 1.803714 \n2130 [308, 400, 593, 219, 239, 102, 136] 1.803658 \n2131 [400, 572, 219, 102, 167] 1.803645 \n2132 [308, 225, 593, 219, 217, 116, 167] 1.803479 \n2133 [308, 225, 400, 593, 219, 239, 102, 116] 1.803418 \n2134 [308, 225, 400, 593, 572, 219, 217, 239, 136, ... 1.803329 \n2135 [225, 572, 219, 217, 102, 136] 1.803309 \n2136 [225, 400, 593, 572, 219, 217, 102] 1.803133 \n2137 [308, 225, 572, 217, 239, 102, 136] 1.802975 \n2138 [225, 400, 116] 1.802895 \n2139 [308, 593, 217, 136] 1.802794 \n2140 [225, 400, 219, 239, 116, 136, 167] 1.802517 \n2141 [308, 225, 136, 167] 1.802344 \n2142 [308, 400, 219, 102, 167] 1.802336 \n2143 [308, 400, 593, 217, 239, 102] 1.802047 \n2144 [225, 593, 572, 219, 217, 116, 167] 1.801700 \n2145 [308, 225, 400, 593, 217, 239, 116] 1.801637 \n2146 [308, 400, 572, 217, 239, 116, 167] 1.801530 \n2147 [308, 593, 219, 102, 116] 1.801267 \n2148 [400, 572, 217, 239, 116, 136] 1.801148 \n2149 [308, 225, 219, 217, 102, 136] 1.801041 \n2150 [593, 572, 219, 239, 102, 116, 167] 1.800941 \n2151 [308, 400, 217, 116] 1.800597 \n2152 [572, 219, 217, 239, 102, 116, 136] 1.800469 \n2153 [225, 219, 217, 239, 102, 116, 136] 1.800071 \n2154 [308, 593, 572, 239, 102, 116] 1.800064 \n2155 [308, 225, 400, 593, 572, 219, 239, 102, 116] 1.799960 \n2156 [308, 225, 400, 239, 102, 167] 1.799941 \n2157 [308, 400, 593, 572, 219, 217, 239, 102, 167] 1.799816 \n2158 [308, 225, 400, 219, 116, 167] 1.799609 \n2159 [593, 572, 219, 102, 167] 1.799603 \n2160 [308, 593, 572, 219, 116, 136] 1.799506 \n2161 [308, 593, 219, 217, 136, 167] 1.799273 \n2162 [308, 400, 593, 219, 217, 239, 102, 167] 1.799192 \n2163 [225, 400, 217, 239, 116, 167] 1.799070 \n2164 [308, 225, 593, 136] 1.799031 \n2165 [308, 400, 572, 219, 217, 116, 167] 1.799005 \n2166 [308, 225, 572, 219, 239, 102, 116, 136] 1.799003 \n2167 [308, 225, 400, 593, 572, 219, 217, 136] 1.798916 \n2168 [308, 400, 593, 572, 217, 239, 102] 1.798847 \n2169 [308, 225, 593, 572, 116] 1.798623 \n2170 [225, 400, 572, 219, 239, 116, 136, 167] 1.798471 \n2171 [308, 400, 593, 217, 239, 136] 1.798410 \n2172 [572, 219, 217, 102, 136] 1.798378 \n2173 [225, 400, 593, 219, 217, 102] 1.798344 \n2174 [593, 219, 102, 116] 1.798335 \n2175 [225, 593, 102] 1.798258 \n2176 [308, 225, 593, 116] 1.798247 \n2177 [308, 225, 572, 219, 217, 239, 102, 116, 167] 1.798215 \n2178 [400, 219, 102, 167] 1.798117 \n2179 [308, 225, 219, 239, 102, 116, 136] 1.798051 \n2180 [308, 572, 219, 217, 102, 136] 1.798028 \n2181 [593, 572, 219, 116, 136] 1.797892 \n2182 [308, 225, 219, 217, 239, 102, 116, 167] 1.797832 \n2183 [308, 225, 217, 239, 102, 136] 1.797749 \n2184 [308, 400, 593, 572, 219, 217, 102] 1.797658 \n2185 [308, 225, 593, 219, 136, 167] 1.797635 \n2186 [308, 400, 219, 217, 116, 167] 1.797428 \n2187 [593, 572, 217, 167] 1.797302 \n2188 [308, 225, 400, 239, 136, 167] 1.796844 \n2189 [308, 400, 572, 239, 102, 136] 1.796699 \n2190 [225, 572, 239, 116, 136, 167] 1.796411 \n2191 [308, 400, 572, 217, 116] 1.796379 \n2192 [308, 225, 400, 572, 219, 116, 167] 1.796233 \n2193 [225, 593, 572, 239, 116, 136] 1.796186 \n2194 [225, 400, 593, 572, 219, 239, 102, 136] 1.796069 \n2195 [308, 593, 572, 219, 102, 167] 1.795980 \n2196 [308, 225, 400, 572, 239, 102, 167] 1.795761 \n2197 [400, 217, 116] 1.795695 \n2198 [308, 225, 400, 593, 219, 239, 116, 136] 1.795631 \n2199 [225, 400, 593, 219, 217, 239, 116, 136] 1.795251 \n2200 [225, 593, 239, 116, 136] 1.795239 \n2201 [308, 225, 400, 593, 219, 217, 136] 1.795111 \n2202 [225, 572, 136, 167] 1.794788 \n2203 [225, 572, 219, 217, 239, 102, 136, 167] 1.794714 \n2204 [225, 400, 593, 219, 239, 102, 136] 1.794605 \n2205 [225, 400, 593, 572, 219, 217, 239, 116, 136] 1.794591 \n2206 [225, 400, 217, 167] 1.794567 \n2207 [308, 400, 593, 572, 217, 239, 136] 1.794407 \n2208 [572, 116, 136, 167] 1.794143 \n2209 [593, 572, 219, 239, 116, 136, 167] 1.793916 \n2210 [400, 217, 136] 1.793885 \n2211 [308, 593, 239, 102, 116] 1.793856 \n2212 [400, 593, 219, 217, 239, 102, 116] 1.793535 \n2213 [217, 102, 116] 1.793522 \n2214 [400, 593, 572, 219, 217, 239, 102, 116] 1.793488 \n2215 [308, 225, 400, 593, 572, 217, 239, 116] 1.793285 \n2216 [225, 572, 239, 102, 116, 167] 1.792899 \n2217 [308, 225, 400, 593, 572, 219, 102] 1.792885 \n2218 [308, 225, 400, 593, 572, 219, 239, 116, 136] 1.792381 \n2219 [593, 217, 136] 1.792332 \n2220 [308, 400, 239, 102, 136] 1.792247 \n2221 [308, 239, 102, 116, 167] 1.792216 \n2222 [308, 400, 593, 219, 217, 102] 1.792125 \n2223 [219, 217, 239, 102, 116, 136] 1.791915 \n2224 [308, 225, 400, 572, 239, 136, 167] 1.791554 \n2225 [308, 400, 593, 572, 219, 217, 239, 136, 167] 1.791415 \n2226 [225, 593, 572, 239, 102, 116] 1.791199 \n2227 [308, 225, 400, 593, 219, 102] 1.791177 \n2228 [308, 225, 400, 572, 116] 1.791097 \n2229 [593, 219, 239, 102, 116, 167] 1.791067 \n2230 [308, 593, 217, 116] 1.790944 \n2231 [225, 400, 572, 217, 167] 1.790775 \n2232 [308, 593, 572, 219, 217, 116, 167] 1.790526 \n2233 [308, 400, 593, 219, 217, 239, 136, 167] 1.790440 \n2234 [225, 400, 219, 116, 167] 1.790270 \n2235 [400, 572, 219, 217, 116, 167] 1.790081 \n2236 [225, 400, 593, 572, 219, 217, 239, 102, 167] 1.790063 \n2237 [572, 219, 217, 239, 102, 136, 167] 1.789063 \n2238 [225, 400, 572, 217, 239, 116, 167] 1.788957 \n2239 [308, 400, 572, 219, 136, 167] 1.788507 \n2240 [400, 593, 572, 219, 217, 102] 1.788362 \n2241 [225, 400, 593, 219, 217, 239, 102, 167] 1.788256 \n2242 [225, 593, 239, 102, 136] 1.787978 \n2243 [225, 593, 219, 217, 116, 167] 1.787848 \n2244 [400, 219, 217, 116, 167] 1.787766 \n2245 [400, 572, 217, 239, 102, 167] 1.787377 \n2246 [308, 225, 400, 593, 219, 217, 239, 116, 167] 1.787311 \n2247 [225, 400, 593, 217, 239, 102] 1.787087 \n2248 [308, 225, 593, 572, 219, 116, 167] 1.786939 \n2249 [308, 225, 572, 219, 217, 102, 116] 1.786671 \n2250 [308, 225, 572, 219, 102, 136] 1.786117 \n2251 [308, 225, 400, 239, 116, 167] 1.786064 \n2252 [308, 225, 572, 219, 217, 239, 116, 136, 167] 1.785989 \n2253 [308, 225, 400, 593, 572, 219, 217, 239, 116, ... 1.785563 \n2254 [225, 400, 593, 572, 217, 239, 102] 1.785381 \n2255 [593, 219, 239, 116, 136, 167] 1.785194 \n2256 [593, 219, 217, 136, 167] 1.785172 \n2257 [400, 572, 217, 116] 1.785126 \n2258 [225, 219, 217, 239, 102, 136, 167] 1.785034 \n2259 [308, 572, 102, 136] 1.784944 \n2260 [225, 400, 136] 1.784880 \n2261 [225, 400, 572, 219, 116, 167] 1.784865 \n2262 [308, 225, 219, 217, 239, 116, 136, 167] 1.784667 \n2263 [308, 572, 219, 217, 239, 102, 116, 167] 1.784454 \n2264 [308, 225, 572, 219, 239, 102, 136, 167] 1.784388 \n2265 [593, 572, 219, 217, 116, 167] 1.784063 \n2266 [308, 225, 400, 593, 219, 239, 102, 167] 1.784046 \n2267 [400, 217, 239, 102, 167] 1.784024 \n2268 [400, 219, 239, 102, 116, 167] 1.783897 \n2269 [308, 225, 400, 593, 572, 219, 239, 102, 167] 1.783724 \n2270 [400, 593, 572, 219, 217, 239, 116, 136] 1.783420 \n2271 [225, 400, 593, 572, 219, 217, 136] 1.783408 \n2272 [400, 572, 219, 239, 102, 116, 167] 1.783403 \n2273 [308, 593, 572, 239, 136, 167] 1.783368 \n2274 [308, 225, 593, 572, 219, 217, 239, 102, 136] 1.783167 \n2275 [225, 400, 572, 136] 1.783156 \n2276 [400, 593, 219, 217, 239, 116, 136] 1.782954 \n2277 [225, 593, 239, 102, 116] 1.782759 \n2278 [593, 116, 136] 1.782259 \n2279 [239, 102, 116, 136, 167] 1.782246 \n2280 [308, 400, 219, 136, 167] 1.782110 \n2281 [308, 400, 593, 572, 219, 217, 136] 1.781981 \n2282 [308, 219, 217, 239, 102, 116, 167] 1.781960 \n2283 [400, 572, 217, 239, 136, 167] 1.781640 \n2284 [308, 400, 593, 217, 239, 116] 1.780623 \n2285 [308, 225, 217, 239, 102, 116] 1.780561 \n2286 [225, 400, 593, 217, 239, 136] 1.780454 \n2287 [225, 400, 593, 572, 219, 102] 1.780346 \n2288 [225, 593, 219, 136, 167] 1.780262 \n2289 [308, 400, 593, 219, 239, 102, 116] 1.780014 \n2290 [217, 102, 167] 1.779951 \n2291 [400, 217, 239, 136, 167] 1.779904 \n2292 [308, 593, 219, 116, 136] 1.779878 \n2293 [400, 593, 219, 217, 102] 1.779633 \n2294 [225, 400, 593, 572, 219, 217, 239, 136, 167] 1.779481 \n2295 [572, 102, 136, 167] 1.779446 \n2296 [308, 225, 572, 217, 239, 102, 116] 1.779442 \n2297 [308, 225, 400, 593, 217, 239, 167] 1.779427 \n2298 [308, 225, 400, 593, 572, 219, 217, 116] 1.779386 \n2299 [308, 225, 219, 239, 102, 136, 167] 1.779349 \n2300 [308, 593, 572, 217, 167] 1.778949 \n2301 [308, 400, 593, 572, 219, 239, 102, 116] 1.778936 \n2302 [225, 219, 217, 102, 136] 1.778620 \n2303 [308, 225, 593, 219, 116, 167] 1.778354 \n2304 [225, 400, 593, 572, 217, 239, 136] 1.778330 \n2305 [308, 572, 217, 239, 102, 136] 1.778220 \n2306 [308, 225, 400, 593, 572, 219, 136] 1.778087 \n2307 [308, 225, 593, 219, 217, 239, 102, 136] 1.777739 \n2308 [308, 225, 400, 593, 219, 217, 116] 1.777635 \n2309 [225, 400, 572, 239, 102, 136] 1.777595 \n2310 [400, 572, 219, 136, 167] 1.777440 \n2311 [225, 400, 593, 219, 102] 1.777158 \n2312 [308, 225, 219, 217, 102, 116] 1.777144 \n2313 [225, 400, 593, 219, 217, 239, 136, 167] 1.776998 \n2314 [225, 593, 572, 219, 116, 167] 1.776940 \n2315 [308, 593, 572, 219, 136, 167] 1.776756 \n2316 [400, 593, 572, 219, 217, 239, 102, 167] 1.776746 \n2317 [225, 593, 136] 1.776543 \n2318 [308, 225, 400, 593, 239, 102] 1.776478 \n2319 [308, 593, 572, 239, 102, 167] 1.776472 \n2320 [225, 400, 593, 219, 217, 136] 1.776246 \n2321 [308, 225, 400, 593, 219, 239, 136, 167] 1.776175 \n2322 [308, 219, 217, 102, 136] 1.776093 \n2323 [308, 225, 400, 593, 572, 219, 239, 136, 167] 1.776079 \n2324 [308, 400, 239, 116, 136] 1.775959 \n2325 [308, 593, 219, 217, 116, 167] 1.775862 \n2326 [219, 217, 239, 102, 136, 167] 1.775722 \n2327 [308, 225, 400, 572, 239, 116, 167] 1.775267 \n2328 [400, 593, 572, 219, 239, 102, 136] 1.775139 \n2329 [308, 225, 400, 593, 572, 217, 239, 167] 1.775127 \n2330 [308, 225, 400, 593, 219, 136] 1.774941 \n2331 [225, 239, 116, 136, 167] 1.774932 \n2332 [225, 572, 219, 102, 136] 1.774918 \n2333 [308, 400, 593, 219, 217, 136] 1.774896 \n2334 [400, 219, 239, 116, 136, 167] 1.774365 \n2335 [308, 225, 400, 593, 239, 136] 1.774295 \n2336 [308, 572, 219, 239, 102, 116, 136] 1.774105 \n2337 [308, 400, 239, 102, 116] 1.774062 \n2338 [593, 102, 116] 1.774045 \n2339 [400, 572, 219, 239, 116, 136, 167] 1.773923 \n2340 [308, 225, 400, 572, 219, 217, 239, 102, 136] 1.773639 \n2341 [308, 593, 239, 136, 167] 1.773587 \n2342 [225, 400, 572, 116] 1.773429 \n2343 [308, 400, 593, 219, 239, 116, 136] 1.773354 \n2344 [308, 225, 400, 593, 217] 1.773350 \n2345 [308, 400, 593, 572, 217, 239, 116] 1.773254 \n2346 [225, 400, 593, 219, 239, 102, 116] 1.773194 \n2347 [400, 593, 219, 217, 239, 102, 167] 1.772876 \n2348 [308, 225, 400, 593, 572, 239, 102] 1.772872 \n2349 [308, 572, 219, 217, 239, 116, 136, 167] 1.772588 \n2350 [308, 225, 217, 239, 116, 136] 1.772567 \n2351 [308, 225, 400, 593, 572, 217] 1.772543 \n2352 [308, 225, 400, 219, 217, 239, 102, 136] 1.772526 \n2353 [308, 400, 593, 572, 219, 239, 116, 136] 1.772230 \n2354 [225, 400, 593, 572, 219, 239, 102, 116] 1.772202 \n2355 [308, 400, 572, 239, 102, 116] 1.772171 \n2356 [225, 593, 572, 239, 136, 167] 1.772009 \n2357 [308, 400, 572, 239, 116, 136] 1.771473 \n2358 [308, 593, 572, 219, 217, 239, 102, 136] 1.771428 \n2359 [308, 400, 593, 219, 217, 239, 116, 167] 1.771425 \n2360 [308, 400, 572, 217, 167] 1.771292 \n2361 [308, 225, 572, 219, 217, 102, 167] 1.771099 \n2362 [308, 593, 219, 102, 167] 1.771098 \n2363 [308, 225, 572, 217, 239, 116, 136] 1.771067 \n2364 [308, 400, 593, 572, 219, 217, 239, 116, 167] 1.770922 \n2365 [308, 225, 219, 102, 136] 1.770273 \n2366 [225, 572, 219, 217, 102, 116] 1.770199 \n2367 [593, 572, 219, 136, 167] 1.769904 \n2368 [400, 217, 239, 116, 167] 1.769733 \n2369 [400, 593, 219, 239, 102, 136] 1.769625 \n2370 [308, 225, 400, 593, 572, 239, 136] 1.769594 \n2371 [308, 219, 217, 239, 116, 136, 167] 1.769302 \n2372 [225, 400, 239, 102, 136] 1.768225 \n2373 [225, 239, 102, 116, 136] 1.767987 \n2374 [225, 400, 593, 217, 239, 116] 1.767784 \n2375 [308, 219, 239, 102, 116, 136] 1.767771 \n2376 [225, 593, 572, 239, 102, 167] 1.767439 \n2377 [225, 572, 219, 217, 239, 102, 116, 167] 1.767330 \n2378 [400, 219, 136, 167] 1.767323 \n2379 [400, 593, 572, 219, 217, 136] 1.767270 \n2380 [308, 400, 217, 167] 1.766937 \n2381 [400, 593, 572, 219, 217, 239, 136, 167] 1.766600 \n2382 [225, 593, 572, 167] 1.766183 \n2383 [308, 225, 593, 572, 167] 1.765894 \n2384 [225, 593, 239, 116, 167] 1.765349 \n2385 [308, 225, 400, 167] 1.765152 \n2386 [308, 217, 239, 102, 136] 1.764776 \n2387 [308, 400, 593, 572, 219, 102] 1.764253 \n2388 [225, 239, 102, 116, 167] 1.763977 \n2389 [225, 400, 593, 219, 239, 116, 136] 1.763878 \n2390 [308, 225, 572, 217, 239, 102, 167] 1.763864 \n2391 [225, 593, 219, 116, 167] 1.763755 \n2392 [308, 225, 572, 219, 217, 116, 136] 1.763579 \n2393 [308, 400, 572, 219, 116, 167] 1.763451 \n2394 [308, 593, 219, 217, 239, 102, 136] 1.763406 \n2395 [593, 219, 116, 136] 1.763330 \n2396 [225, 400, 593, 572, 219, 239, 116, 136] 1.763188 \n2397 [308, 572, 219, 217, 102, 116] 1.763139 \n2398 [308, 225, 400, 593, 572, 219, 217, 167] 1.762410 \n2399 [400, 593, 572, 217, 239, 102] 1.762372 \n2400 [400, 593, 219, 217, 239, 136, 167] 1.762198 \n2401 [225, 219, 217, 239, 102, 116, 167] 1.761874 \n2402 [225, 400, 593, 572, 219, 217, 116] 1.761840 \n2403 [400, 572, 217, 239, 116, 167] 1.761760 \n2404 [308, 225, 400, 572, 167] 1.761668 \n2405 [308, 593, 239, 116, 167] 1.761546 \n2406 [308, 400, 219, 116, 167] 1.761335 \n2407 [308, 572, 102, 116] 1.761018 \n2408 [308, 400, 593, 572, 219, 239, 102, 167] 1.760895 \n2409 [308, 225, 400, 593, 239, 116] 1.760831 \n2410 [593, 219, 217, 116, 167] 1.760755 \n2411 [308, 593, 239, 102, 167] 1.760634 \n2412 [219, 217, 102, 136] 1.760613 \n2413 [225, 400, 593, 572, 219, 136] 1.760554 \n2414 [225, 400, 593, 572, 217, 239, 116] 1.760460 \n2415 [400, 593, 217, 239, 102] 1.760442 \n2416 [225, 400, 593, 572, 219, 217, 239, 116, 167] 1.760438 \n2417 [225, 400, 593, 219, 217, 239, 116, 167] 1.760112 \n2418 [308, 225, 593, 572, 219, 217, 239, 102, 116] 1.759895 \n2419 [308, 400, 572, 102] 1.759841 \n2420 [308, 225, 217, 239, 102, 167] 1.759799 \n2421 [593, 217, 167] 1.759619 \n2422 [308, 225, 400, 593, 219, 239, 116, 167] 1.759542 \n2423 [225, 400, 239, 102, 116] 1.759535 \n2424 [308, 593, 572, 239, 116, 167] 1.759489 \n2425 [308, 400, 593, 572, 219, 217, 116] 1.759164 \n2426 [225, 593, 239, 136, 167] 1.758781 \n2427 [308, 225, 572, 219, 239, 102, 116, 167] 1.758699 \n2428 [308, 400, 572, 219, 217, 239, 102, 136] 1.758698 \n2429 [225, 400, 572, 239, 102, 116] 1.758566 \n2430 [225, 400, 239, 116, 136] 1.758286 \n2431 [400, 593, 572, 217, 239, 136] 1.758183 \n2432 [308, 400, 593, 219, 239, 102, 167] 1.758142 \n2433 [225, 400, 593, 219, 217, 116] 1.758078 \n2434 [308, 572, 219, 239, 102, 136, 167] 1.758068 \n2435 [400, 593, 217, 239, 136] 1.757909 \n2436 [308, 225, 400, 593, 572, 219, 239, 116, 167] 1.757709 \n2437 [225, 593, 572, 239, 116, 167] 1.757466 \n2438 [308, 225, 400, 593, 572, 219, 116] 1.757415 \n2439 [308, 225, 400, 593, 219, 217, 167] 1.757400 \n2440 [308, 225, 219, 217, 102, 167] 1.757219 \n2441 [308, 400, 593, 219, 102] 1.757147 \n2442 [308, 225, 400, 593, 219, 116] 1.756939 \n2443 [308, 225, 219, 239, 102, 116, 167] 1.756845 \n2444 [593, 219, 102, 167] 1.756536 \n2445 [308, 225, 593, 219, 217, 239, 102, 116] 1.756267 \n2446 [308, 400, 219, 217, 239, 102, 136] 1.755830 \n2447 [400, 593, 219, 217, 136] 1.755759 \n2448 [308, 225, 572, 219, 102, 116] 1.755694 \n2449 [225, 572, 219, 239, 102, 116, 136] 1.755687 \n2450 [308, 225, 572, 217, 239, 136, 167] 1.755344 \n2451 [308, 400, 593, 217, 239, 167] 1.754969 \n2452 [225, 400, 572, 239, 116, 136] 1.754942 \n2453 [225, 400, 593, 219, 136] 1.754765 \n2454 [308, 400, 593, 219, 217, 116] 1.754434 \n2455 [225, 400, 593, 217] 1.754426 \n2456 [308, 225, 400, 219, 217, 239, 102, 116] 1.754160 \n2457 [308, 400, 593, 572, 219, 239, 136, 167] 1.754089 \n2458 [308, 225, 400, 572, 219, 217, 239, 102, 116] 1.753910 \n2459 [225, 593, 167] 1.753595 \n2460 [572, 219, 217, 239, 102, 116, 167] 1.753577 \n2461 [225, 219, 217, 102, 116] 1.753547 \n2462 [225, 400, 593, 572, 219, 239, 102, 167] 1.753440 \n2463 [225, 400, 593, 572, 217] 1.753395 \n2464 [572, 102, 116, 136] 1.753367 \n2465 [308, 593, 217, 167] 1.753324 \n2466 [225, 572, 219, 217, 102, 167] 1.753264 \n2467 [400, 572, 217, 167] 1.752880 \n2468 [308, 400, 593, 572, 217, 239, 167] 1.752749 \n2469 [572, 219, 217, 102, 116] 1.752430 \n2470 [308, 225, 400, 593, 572, 239, 116] 1.752107 \n2471 [308, 225, 217, 239, 136, 167] 1.751587 \n2472 [225, 572, 219, 217, 239, 116, 136, 167] 1.751535 \n2473 [308, 400, 593, 219, 239, 136, 167] 1.751344 \n2474 [308, 225, 593, 167] 1.751304 \n2475 [225, 102, 116] 1.751196 \n2476 [308, 225, 219, 217, 116, 136] 1.750941 \n2477 [225, 593, 572, 219, 217, 239, 102, 136] 1.750702 \n2478 [225, 239, 102, 136, 167] 1.750532 \n2479 [225, 400, 593, 219, 239, 102, 167] 1.750091 \n2480 [308, 593, 219, 136, 167] 1.749637 \n2481 [308, 400, 572, 239, 102, 167] 1.749606 \n2482 [308, 225, 593, 572, 219, 217, 239, 116, 136] 1.749459 \n2483 [400, 593, 572, 219, 102] 1.749437 \n2484 [308, 400, 593, 572, 219, 136] 1.749271 \n2485 [308, 593, 572, 102] 1.748872 \n2486 [308, 572, 217, 239, 102, 116] 1.748663 \n2487 [308, 400, 572, 239, 136, 167] 1.748612 \n2488 [400, 572, 219, 116, 167] 1.748502 \n2489 [308, 225, 572, 219, 239, 116, 136, 167] 1.748093 \n2490 [308, 225, 572, 219, 217, 136, 167] 1.747954 \n2491 [225, 593, 239, 102, 167] 1.747338 \n2492 [400, 219, 116, 167] 1.747160 \n2493 [308, 225, 593, 572, 219, 239, 102, 136] 1.747138 \n2494 [308, 593, 572, 219, 116, 167] 1.747086 \n2495 [400, 217, 167] 1.746866 \n2496 [225, 219, 102, 136] 1.746834 \n2497 [308, 572, 219, 102, 136] 1.746722 \n2498 [308, 219, 239, 102, 136, 167] 1.746532 \n2499 [400, 593, 572, 219, 239, 102, 116] 1.746480 \n2500 [308, 219, 217, 102, 116] 1.746138 \n2501 [308, 572, 219, 217, 102, 167] 1.745873 \n2502 [308, 225, 219, 239, 116, 136, 167] 1.745716 \n2503 [308, 400, 572, 136] 1.745687 \n2504 [308, 225, 593, 572, 219, 217, 239, 102, 167] 1.745682 \n2505 [308, 400, 239, 136, 167] 1.745681 \n2506 [217, 102, 136] 1.745624 \n2507 [308, 225, 219, 102, 116] 1.745622 \n2508 [308, 400, 102] 1.745526 \n2509 [308, 572, 116, 136] 1.745474 \n2510 [593, 572, 239, 102, 136] 1.745267 \n2511 [219, 217, 239, 102, 116, 167] 1.745214 \n2512 [225, 219, 239, 102, 116, 136] 1.745191 \n2513 [308, 225, 593, 219, 217, 239, 116, 136] 1.745180 \n2514 [225, 219, 217, 239, 116, 136, 167] 1.744460 \n2515 [225, 400, 593, 572, 219, 239, 136, 167] 1.744335 \n2516 [308, 400, 239, 102, 167] 1.744313 \n2517 [400, 593, 572, 219, 217, 239, 116, 167] 1.743992 \n2518 [308, 225, 572, 217, 102] 1.743777 \n2519 [400, 593, 219, 239, 102, 116] 1.743757 \n2520 [308, 225, 400, 572, 219, 217, 239, 116, 136] 1.743637 \n2521 [308, 572, 217, 239, 116, 136] 1.743624 \n2522 [308, 217, 239, 102, 116] 1.743555 \n2523 [308, 593, 572, 219, 217, 239, 102, 116] 1.743448 \n2524 [308, 225, 400, 219, 217, 239, 116, 136] 1.743202 \n2525 [400, 593, 217, 239, 116] 1.742603 \n2526 [400, 593, 219, 217, 239, 116, 167] 1.742018 \n2527 [225, 400, 593, 572, 219, 217, 167] 1.741871 \n2528 [225, 400, 167] 1.741131 \n2529 [308, 400, 593, 572, 217] 1.741020 \n2530 [400, 593, 572, 219, 217, 116] 1.740973 \n2531 [308, 225, 217, 239, 116, 167] 1.740806 \n2532 [572, 219, 102, 136] 1.740737 \n2533 [308, 400, 593, 219, 136] 1.740689 \n2534 [225, 400, 593, 219, 239, 136, 167] 1.740654 \n2535 [308, 217, 239, 116, 136] 1.740531 \n2536 [225, 400, 593, 217, 239, 167] 1.740498 \n2537 [308, 400, 593, 572, 219, 217, 167] 1.740179 \n2538 [225, 572, 219, 239, 102, 136, 167] 1.740124 \n2539 [308, 225, 400, 572, 219, 217, 239, 102, 167] 1.740061 \n2540 [225, 400, 572, 219, 217, 239, 102, 136] 1.739764 \n2541 [308, 225, 593, 219, 239, 102, 136] 1.739673 \n2542 [217, 116, 136] 1.739624 \n2543 [308, 225, 400, 572, 219, 239, 102, 136] 1.739530 \n2544 [593, 572, 219, 217, 239, 102, 136] 1.739383 \n2545 [225, 400, 593, 572, 217, 239, 167] 1.739080 \n2546 [308, 225, 593, 219, 217, 239, 102, 167] 1.739073 \n2547 [308, 593, 572, 136] 1.738954 \n2548 [400, 593, 219, 102] 1.738832 \n2549 [400, 593, 572, 219, 239, 116, 136] 1.738711 \n2550 [225, 593, 219, 217, 239, 102, 136] 1.738352 \n2551 [572, 219, 217, 239, 116, 136, 167] 1.738019 \n2552 [308, 572, 219, 217, 116, 136] 1.738018 \n2553 [225, 572, 219, 102, 116] 1.737794 \n2554 [308, 225, 400, 219, 217, 239, 102, 167] 1.737753 \n2555 [225, 400, 593, 572, 219, 116] 1.737604 \n2556 [308, 225, 572, 217, 239, 116, 167] 1.737505 \n2557 [308, 225, 400, 219, 239, 102, 136] 1.737385 \n2558 [308, 225, 400, 593] 1.737362 \n2559 [308, 593, 219, 217, 239, 102, 116] 1.737345 \n2560 [225, 400, 593, 219, 116] 1.736545 \n2561 [308, 400, 593, 217] 1.736441 \n2562 [308, 572, 102, 167] 1.736394 \n2563 [225, 572, 219, 217, 116, 136] 1.736363 \n2564 [308, 225, 400, 593, 572, 219, 167] 1.736338 \n2565 [400, 593, 572, 217, 239, 116] 1.736281 \n2566 [308, 225, 400, 572, 219, 217, 102] 1.736244 \n2567 [400, 593, 219, 239, 116, 136] 1.736134 \n2568 [308, 400, 572, 219, 217, 239, 102, 116] 1.735684 \n2569 [593, 572, 239, 116, 136] 1.735577 \n2570 [308, 225, 593, 572, 219, 217, 239, 136, 167] 1.735189 \n2571 [225, 400, 572, 239, 102, 167] 1.735185 \n2572 [308, 225, 593, 572, 217, 239, 102] 1.735018 \n2573 [225, 572, 217, 239, 102, 136] 1.734996 \n2574 [308, 225, 400, 593, 572] 1.734856 \n2575 [308, 225, 572, 219, 102, 167] 1.734764 \n2576 [308, 400, 219, 217, 239, 102, 116] 1.734255 \n2577 [308, 400, 239, 116, 167] 1.734141 \n2578 [225, 400, 219, 217, 239, 102, 136] 1.734124 \n2579 [572, 219, 217, 102, 167] 1.733858 \n2580 [593, 572, 219, 116, 167] 1.733717 \n2581 [308, 400, 593, 572, 239, 102] 1.733644 \n2582 [400, 593, 219, 217, 116] 1.733534 \n2583 [308, 593, 572, 219, 217, 239, 116, 136] 1.733495 \n2584 [225, 400, 593, 219, 217, 167] 1.733435 \n2585 [308, 400, 593, 572, 239, 136] 1.733314 \n2586 [225, 400, 572, 167] 1.733282 \n2587 [308, 400, 593, 572, 219, 239, 116, 167] 1.732932 \n2588 [308, 400, 593, 239, 136] 1.732609 \n2589 [308, 225, 400, 593, 239, 167] 1.732368 \n2590 [308, 400, 593, 219, 239, 116, 167] 1.732139 \n2591 [308, 225, 572, 219, 116, 136] 1.732019 \n2592 [308, 572, 217, 239, 102, 167] 1.731559 \n2593 [308, 400, 593, 219, 217, 167] 1.731427 \n2594 [308, 225, 400, 593, 219, 167] 1.731300 \n2595 [225, 400, 572, 239, 136, 167] 1.731264 \n2596 [308, 225, 219, 217, 136, 167] 1.731018 \n2597 [593, 136, 167] 1.730742 \n2598 [308, 400, 593, 239, 102] 1.730741 \n2599 [308, 400, 136] 1.730694 \n2600 [308, 225, 400, 219, 217, 102] 1.730317 \n2601 [308, 225, 593, 217, 239, 102] 1.730115 \n2602 [225, 219, 217, 102, 167] 1.730025 \n2603 [308, 400, 572, 239, 116, 167] 1.729962 \n2604 [308, 225, 400, 572, 219, 217, 239, 136, 167] 1.729753 \n2605 [308, 225, 400, 593, 572, 239, 167] 1.729364 \n2606 [400, 593, 572, 219, 136] 1.728865 \n2607 [219, 217, 239, 116, 136, 167] 1.728204 \n2608 [308, 225, 593, 572, 217, 239, 136] 1.728181 \n2609 [308, 225, 593, 219, 217, 239, 136, 167] 1.727923 \n2610 [308, 593, 572, 219, 217, 239, 102, 167] 1.727741 \n2611 [225, 400, 239, 102, 167] 1.727692 \n2612 [308, 593, 219, 217, 239, 116, 136] 1.726901 \n2613 [308, 593, 219, 116, 167] 1.726876 \n2614 [308, 572, 219, 239, 102, 116, 167] 1.726792 \n2615 [308, 225, 400, 219, 217, 239, 136, 167] 1.726761 \n2616 [308, 400, 572, 116] 1.726751 \n2617 [308, 225, 593, 572, 219, 217, 102] 1.726707 \n2618 [308, 572, 217, 239, 136, 167] 1.726325 \n2619 [308, 400, 116] 1.726209 \n2620 [308, 225, 572, 219, 217, 116, 167] 1.726147 \n2621 [225, 400, 239, 136, 167] 1.725891 \n2622 [308, 400, 572, 219, 217, 239, 116, 136] 1.725579 \n2623 [219, 217, 102, 116] 1.725533 \n2624 [400, 593, 572, 219, 239, 102, 167] 1.725214 \n2625 [308, 400, 593, 572, 219, 116] 1.725103 \n2626 [225, 400, 593, 572, 219, 239, 116, 167] 1.724842 \n2627 [225, 593, 572, 219, 217, 239, 102, 116] 1.724724 \n2628 [225, 400, 239, 116, 167] 1.724698 \n2629 [593, 102, 167] 1.724361 \n2630 [225, 400, 593, 219, 239, 116, 167] 1.724048 \n2631 [217, 136, 167] 1.724034 \n2632 [225, 219, 239, 102, 136, 167] 1.723835 \n2633 [308, 225, 593, 217, 239, 136] 1.723762 \n2634 [308, 400, 219, 217, 239, 116, 136] 1.723523 \n2635 [308, 219, 217, 102, 167] 1.723248 \n2636 [225, 219, 102, 116] 1.723069 \n2637 [593, 219, 217, 239, 102, 136] 1.722977 \n2638 [308, 225, 593, 572, 219, 239, 102, 116] 1.722569 \n2639 [572, 219, 239, 102, 116, 136] 1.722510 \n2640 [308, 225, 572, 239, 102, 136] 1.722070 \n2641 [400, 572, 219, 217, 239, 102, 136] 1.722027 \n2642 [593, 219, 136, 167] 1.721478 \n2643 [225, 400, 593, 572, 239, 102] 1.721199 \n2644 [308, 572, 219, 217, 136, 167] 1.720665 \n2645 [308, 593, 572, 219, 239, 102, 136] 1.720521 \n2646 [400, 593, 572, 217] 1.720501 \n2647 [308, 400, 572, 219, 217, 239, 102, 167] 1.720448 \n2648 [308, 572, 136, 167] 1.720406 \n2649 [308, 225, 217, 102] 1.720208 \n2650 [308, 400, 593, 219, 116] 1.719689 \n2651 [308, 217, 239, 102, 167] 1.719623 \n2652 [225, 572, 219, 217, 136, 167] 1.719271 \n2653 [308, 225, 400, 572, 219, 239, 102, 116] 1.719031 \n2654 [308, 219, 239, 102, 116, 167] 1.719026 \n2655 [308, 225, 400, 572, 219, 217, 136] 1.718727 \n2656 [225, 400, 572, 239, 116, 167] 1.718677 \n2657 [308, 225, 400, 219, 239, 102, 116] 1.718650 \n2658 [225, 400, 593, 572, 239, 136] 1.718590 \n2659 [308, 225, 572, 217, 136] 1.718563 \n2660 [225, 400, 572, 219, 217, 239, 102, 116] 1.718427 \n2661 [308, 225, 219, 116, 136] 1.718349 \n2662 [400, 593, 572, 219, 217, 167] 1.718058 \n2663 [308, 225, 219, 102, 167] 1.717946 \n2664 [308, 593, 219, 217, 239, 102, 167] 1.717934 \n2665 [308, 593, 572, 219, 217, 239, 136, 167] 1.717705 \n2666 [308, 593, 572, 116] 1.717652 \n2667 [308, 572, 219, 239, 116, 136, 167] 1.717500 \n2668 [308, 225, 593, 219, 239, 102, 116] 1.717496 \n2669 [225, 400, 593, 239, 102] 1.717436 \n2670 [400, 593, 572, 219, 239, 136, 167] 1.717296 \n2671 [308, 400, 593, 239, 116] 1.717277 \n2672 [308, 219, 217, 116, 136] 1.717273 \n2673 [400, 593, 219, 239, 102, 167] 1.716952 \n2674 [225, 400, 593, 239, 136] 1.716941 \n2675 [225, 400, 593] 1.716887 \n2676 [308, 217, 239, 136, 167] 1.716245 \n2677 [400, 593, 217] 1.715979 \n2678 [308, 400, 219, 217, 239, 102, 167] 1.715912 \n2679 [593, 572, 239, 102, 116] 1.715782 \n2680 [308, 225, 593, 572, 219, 217, 239, 116, 167] 1.715663 \n2681 [308, 225, 400, 572, 217, 239, 102] 1.715545 \n2682 [225, 593, 219, 217, 239, 102, 116] 1.715512 \n2683 [400, 593, 219, 136] 1.715395 \n2684 [225, 400, 219, 217, 239, 102, 116] 1.715035 \n2685 [308, 219, 102, 136] 1.714484 \n2686 [308, 225, 400, 217, 239, 102] 1.713807 \n2687 [308, 225, 219, 217, 116, 167] 1.713742 \n2688 [308, 225, 593, 572, 219, 239, 116, 136] 1.713666 \n2689 [225, 572, 217, 239, 102, 116] 1.713549 \n2690 [400, 219, 217, 239, 102, 136] 1.713541 \n2691 [225, 219, 217, 116, 136] 1.713358 \n2692 [593, 572, 116] 1.713018 \n2693 [308, 225, 400, 572, 219, 217, 239, 116, 167] 1.713005 \n2694 [308, 400, 593, 572, 239, 116] 1.712993 \n2695 [572, 219, 217, 116, 136] 1.712891 \n2696 [225, 572, 219, 102, 167] 1.712708 \n2697 [593, 572, 102] 1.712437 \n2698 [308, 400, 572, 219, 239, 102, 136] 1.712087 \n2699 [308, 572, 116, 167] 1.712038 \n2700 [225, 572, 219, 239, 102, 116, 167] 1.711970 \n2701 [225, 593, 572, 219, 217, 239, 116, 136] 1.711657 \n2702 [308, 225, 400, 219, 217, 239, 116, 167] 1.711621 \n2703 [225, 400, 593, 572, 219, 167] 1.711599 \n2704 [308, 225, 400, 593, 572, 219, 217, 239, 102] 1.711557 \n2705 [400, 593, 572, 217, 239, 167] 1.711463 \n2706 [400, 572, 102] 1.711239 \n2707 [400, 572, 239, 102, 136] 1.711053 \n2708 [308, 225, 572, 219, 136, 167] 1.711053 \n2709 [308, 400, 572, 219, 217, 102] 1.711031 \n2710 [308, 225, 400, 219, 217, 136] 1.710894 \n2711 [225, 116, 136] 1.710847 \n2712 [308, 225, 593, 219, 217, 239, 116, 167] 1.710515 \n2713 [308, 225, 593, 219, 217, 102] 1.710488 \n2714 [308, 400, 572, 219, 217, 239, 136, 167] 1.710292 \n2715 [308, 225, 593, 217, 239, 116] 1.709798 \n2716 [400, 593, 217, 239, 167] 1.709776 \n2717 [308, 225, 400, 572, 219, 239, 116, 136] 1.709737 \n2718 [308, 219, 239, 116, 136, 167] 1.709731 \n2719 [308, 225, 593, 572, 217, 239, 116] 1.709171 \n2720 [225, 102, 167] 1.709144 \n2721 [400, 593, 219, 239, 136, 167] 1.709108 \n2722 [225, 400, 593, 239, 116] 1.708873 \n2723 [308, 225, 400, 219, 239, 116, 136] 1.708870 \n2724 [225, 593, 572, 219, 217, 239, 102, 167] 1.708835 \n2725 [225, 400, 593, 572] 1.708666 \n2726 [308, 572, 219, 102, 116] 1.708564 \n2727 [308, 225, 593, 219, 239, 116, 136] 1.708314 \n2728 [225, 400, 572, 219, 217, 102] 1.708178 \n2729 [593, 239, 116, 136] 1.707673 \n2730 [308, 225, 593, 572, 219, 217, 136] 1.707463 \n2731 [308, 593, 219, 239, 102, 136] 1.707396 \n2732 [308, 593, 219, 217, 239, 136, 167] 1.707386 \n2733 [593, 572, 239, 136, 167] 1.707289 \n2734 [308, 225, 400, 593, 219, 217, 239, 102] 1.707285 \n2735 [308, 225, 400, 572, 217, 239, 136] 1.707262 \n2736 [593, 572, 136] 1.707125 \n2737 [225, 217, 239, 102, 136] 1.706561 \n2738 [593, 572, 219, 217, 239, 102, 116] 1.706506 \n2739 [308, 593, 572, 217, 239, 102] 1.706142 \n2740 [308, 400, 219, 239, 102, 136] 1.706131 \n2741 [225, 400, 572, 219, 217, 239, 116, 136] 1.705803 \n2742 [572, 219, 239, 102, 136, 167] 1.705643 \n2743 [308, 225, 400, 217, 239, 136] 1.705364 \n2744 [308, 400, 219, 217, 239, 136, 167] 1.705121 \n2745 [308, 225, 593, 572, 219, 239, 102, 167] 1.704822 \n2746 [308, 225, 400, 572, 219, 102] 1.704551 \n2747 [400, 593, 219, 217, 167] 1.704519 \n2748 [308, 572, 217, 239, 116, 167] 1.704284 \n2749 [308, 225, 239, 102, 136] 1.704034 \n2750 [308, 217, 239, 116, 167] 1.703632 \n2751 [225, 400, 593, 219, 167] 1.703423 \n2752 [225, 572, 217, 239, 116, 136] 1.703370 \n2753 [225, 400, 572, 219, 217, 239, 102, 167] 1.702876 \n2754 [225, 400, 593, 572, 239, 116] 1.702600 \n2755 [308, 225, 400, 593, 572, 219, 217, 239, 136] 1.702495 \n2756 [308, 225, 572, 217, 116] 1.702416 \n2757 [308, 593, 572, 217, 239, 136] 1.702322 \n2758 [308, 225, 400, 572, 219, 239, 102, 167] 1.702210 \n2759 [225, 219, 239, 102, 116, 167] 1.702075 \n2760 [593, 219, 116, 167] 1.701628 \n2761 [225, 593, 219, 217, 239, 116, 136] 1.701383 \n2762 [225, 400, 219, 217, 239, 116, 136] 1.701352 \n2763 [225, 593, 572, 219, 239, 102, 136] 1.701322 \n2764 [308, 400, 593, 572, 219, 167] 1.701137 \n2765 [219, 239, 102, 116, 136] 1.700994 \n2766 [308, 400, 219, 217, 102] 1.700922 \n2767 [308, 225, 572, 239, 102, 116] 1.700884 \n2768 [225, 572, 219, 116, 136] 1.700766 \n2769 [400, 593, 572, 219, 116] 1.700720 \n2770 [308, 225, 400, 572, 219, 217, 116] 1.700384 \n2771 [225, 572, 217, 102] 1.699809 \n2772 [225, 217, 239, 102, 116] 1.699510 \n2773 [308, 593, 572, 219, 217, 102] 1.698844 \n2774 [308, 225, 572, 219, 217, 239, 102, 136] 1.698598 \n2775 [308, 225, 400, 219, 102] 1.698457 \n2776 [308, 225, 400, 219, 239, 102, 167] 1.698409 \n2777 [225, 572, 219, 239, 116, 136, 167] 1.698369 \n2778 [593, 102, 136] 1.697831 \n2779 [225, 400, 219, 217, 102] 1.697821 \n2780 [308, 225, 572, 239, 116, 136] 1.697766 \n2781 [308, 225, 400, 593, 219, 217, 239, 136] 1.697707 \n2782 [219, 217, 102, 167] 1.697680 \n2783 [225, 572, 217, 239, 102, 167] 1.697442 \n2784 [225, 593, 572, 219, 217, 102] 1.697375 \n2785 [400, 572, 219, 217, 239, 102, 116] 1.696311 \n2786 [225, 400, 219, 217, 239, 102, 167] 1.696077 \n2787 [308, 225, 593, 572, 219, 239, 136, 167] 1.695824 \n2788 [308, 593, 217, 239, 102] 1.695759 \n2789 [225, 593, 572, 219, 217, 239, 136, 167] 1.695686 \n2790 [225, 572, 219, 217, 116, 167] 1.695664 \n2791 [308, 225, 593, 219, 239, 102, 167] 1.695622 \n2792 [225, 593, 219, 217, 239, 102, 167] 1.695532 \n2793 [308, 225, 400, 219, 217, 116] 1.694988 \n2794 [308, 593, 572, 219, 217, 239, 116, 167] 1.694486 \n2795 [308, 219, 217, 136, 167] 1.694367 \n2796 [400, 593, 572, 219, 239, 116, 167] 1.694210 \n2797 [572, 217, 239, 102, 136] 1.694055 \n2798 [572, 219, 217, 136, 167] 1.694020 \n2799 [308, 572, 219, 217, 116, 167] 1.694002 \n2800 [593, 572, 219, 217, 239, 116, 136] 1.693984 \n2801 [225, 400, 572, 219, 239, 102, 136] 1.693752 \n2802 [308, 593, 217, 239, 136] 1.693736 \n2803 [593, 219, 217, 239, 102, 116] 1.693627 \n2804 [308, 225, 400, 217, 239, 116] 1.693379 \n2805 [400, 593, 219, 116] 1.693195 \n2806 [308, 225, 239, 102, 116] 1.692970 \n2807 [308, 225, 400, 572, 219, 239, 136, 167] 1.692857 \n2808 [308, 225, 239, 116, 136] 1.692482 \n2809 [308, 400, 572, 219, 217, 136] 1.692450 \n2810 [572, 239, 102, 116, 136] 1.692078 \n2811 [308, 400, 572, 167] 1.691806 \n2812 [308, 225, 400, 572, 217, 239, 116] 1.691741 \n2813 [400, 572, 136] 1.691242 \n2814 [400, 572, 239, 116, 136] 1.691153 \n2815 [308, 400, 593, 572, 219, 217, 239, 102] 1.691138 \n2816 [308, 593, 572, 219, 239, 102, 116] 1.690956 \n2817 [308, 400, 572, 219, 217, 239, 116, 167] 1.690940 \n2818 [308, 225, 217, 136] 1.690864 \n2819 [308, 225, 219, 136, 167] 1.690723 \n2820 [308, 225, 593, 572, 219, 102] 1.690712 \n2821 [593, 572, 239, 116, 167] 1.690570 \n2822 [400, 219, 217, 239, 102, 116] 1.690312 \n2823 [225, 400, 572, 219, 217, 239, 136, 167] 1.690207 \n2824 [225, 217, 239, 116, 136] 1.690162 \n2825 [572, 239, 116, 136, 167] 1.690113 \n2826 [308, 400, 593, 219, 167] 1.689978 \n2827 [225, 219, 217, 136, 167] 1.689810 \n2828 [400, 593, 219, 239, 116, 167] 1.689430 \n2829 [400, 572, 239, 102, 116] 1.689121 \n2830 [308, 225, 593, 219, 217, 136] 1.689054 \n2831 [308, 225, 593, 572, 217, 239, 167] 1.689034 \n2832 [593, 572, 219, 217, 239, 102, 167] 1.688699 \n2833 [308, 225, 219, 217, 239, 102, 136] 1.688577 \n2834 [308, 225, 400, 219, 239, 136, 167] 1.688559 \n2835 [308, 225, 572, 219, 116, 167] 1.688461 \n2836 [308, 225, 217, 116] 1.688458 \n2837 [308, 400, 572, 219, 239, 102, 116] 1.688227 \n2838 [400, 116] 1.688150 \n2839 [593, 572, 239, 102, 167] 1.688139 \n2840 [308, 400, 219, 217, 239, 116, 167] 1.687548 \n2841 [225, 219, 239, 116, 136, 167] 1.687538 \n2842 [572, 219, 102, 116] 1.687509 \n2843 [225, 572, 217, 239, 136, 167] 1.687052 \n2844 [308, 400, 593, 572, 239, 167] 1.686887 \n2845 [308, 225, 400, 572, 219, 136] 1.686880 \n2846 [308, 593, 219, 217, 239, 116, 167] 1.686547 \n2847 [308, 225, 593, 572, 219, 217, 116] 1.686425 \n2848 [308, 225, 593, 219, 239, 136, 167] 1.686312 \n2849 [308, 225, 400, 593, 572, 219, 217, 239, 116] 1.686246 \n2850 [225, 219, 102, 167] 1.685975 \n2851 [308, 593, 102] 1.685838 \n2852 [572, 239, 102, 136, 167] 1.685377 \n2853 [225, 400, 219, 239, 102, 136] 1.685173 \n2854 [225, 400, 572, 219, 217, 136] 1.684791 \n2855 [308, 572, 217, 102] 1.684746 \n2856 [308, 400, 593, 219, 217, 239, 102] 1.684606 \n2857 [308, 572, 219, 102, 167] 1.684460 \n2858 [308, 400, 219, 239, 102, 116] 1.684226 \n2859 [308, 225, 593, 217, 239, 167] 1.684031 \n2860 [308, 219, 102, 116] 1.683972 \n2861 [225, 593, 219, 239, 102, 136] 1.683872 \n2862 [308, 593, 116] 1.683870 \n2863 [308, 400, 593, 239, 167] 1.683779 \n2864 [400, 572, 219, 217, 239, 116, 136] 1.683760 \n2865 [308, 572, 219, 116, 136] 1.683431 \n2866 [308, 593, 572, 219, 239, 116, 136] 1.683326 \n2867 [400, 572, 116] 1.683107 \n2868 [219, 102, 136] 1.683057 \n2869 [308, 225, 400, 593, 219, 217, 239, 116] 1.682776 \n2870 [308, 225, 400, 572, 219, 217, 167] 1.682696 \n2871 [225, 400, 219, 217, 239, 136, 167] 1.682351 \n2872 [308, 400, 593, 572, 219, 217, 239, 136] 1.682304 \n2873 [308, 400, 572, 217, 239, 102] 1.682086 \n2874 [225, 593, 219, 217, 239, 136, 167] 1.681313 \n2875 [400, 572, 219, 217, 102] 1.680574 \n2876 [308, 593, 219, 239, 102, 116] 1.680540 \n2877 [593, 219, 217, 239, 116, 136] 1.680285 \n2878 [308, 400, 219, 217, 136] 1.680144 \n2879 [308, 400, 572, 219, 239, 116, 136] 1.679557 \n2880 [308, 225, 572, 239, 102, 167] 1.679461 \n2881 [400, 572, 219, 217, 239, 102, 167] 1.678947 \n2882 [308, 593, 572, 217, 239, 116] 1.678805 \n2883 [308, 225, 400, 219, 136] 1.678690 \n2884 [593, 239, 116, 167] 1.678671 \n2885 [308, 225, 572, 217, 167] 1.678668 \n2886 [308, 593, 572, 219, 217, 136] 1.678356 \n2887 [400, 239, 116, 136] 1.677898 \n2888 [400, 239, 102, 136] 1.677894 \n2889 [308, 593, 572, 167] 1.677664 \n2890 [308, 593, 136] 1.677555 \n2891 [225, 219, 116, 136] 1.677208 \n2892 [308, 572, 219, 217, 239, 102, 136] 1.677116 \n2893 [308, 400, 167] 1.677099 \n2894 [219, 217, 116, 136] 1.677073 \n2895 [308, 400, 593, 572] 1.676956 \n2896 [400, 219, 217, 239, 116, 136] 1.676752 \n2897 [308, 593, 217, 239, 116] 1.676566 \n2898 [308, 225, 572, 219, 217, 239, 102, 116] 1.676391 \n2899 [219, 239, 102, 136, 167] 1.676317 \n2900 [225, 593, 572, 217, 239, 102] 1.676191 \n2901 [308, 225, 572, 239, 136, 167] 1.676064 \n2902 [593, 572, 219, 217, 239, 136, 167] 1.676050 \n2903 [225, 217, 239, 102, 167] 1.675867 \n2904 [308, 225, 400, 572, 219, 239, 116, 167] 1.675821 \n2905 [308, 225, 400, 593, 572, 219, 239, 102] 1.675754 \n2906 [308, 400, 217, 239, 102] 1.675704 \n2907 [308, 225, 593, 572, 219, 239, 116, 167] 1.675704 \n2908 [225, 572, 219, 136, 167] 1.675583 \n2909 [308, 400, 593, 219, 217, 239, 136] 1.675317 \n2910 [308, 400, 219, 239, 116, 136] 1.675274 \n2911 [308, 400, 572, 217, 239, 136] 1.675185 \n2912 [225, 219, 217, 116, 167] 1.675154 \n2913 [225, 593, 572, 219, 217, 239, 116, 167] 1.674787 \n2914 [308, 225, 219, 116, 167] 1.674724 \n2915 [308, 593, 219, 217, 102] 1.674712 \n2916 [225, 400, 593, 572, 239, 167] 1.674576 \n2917 [225, 593, 572, 219, 239, 102, 116] 1.674038 \n2918 [593, 116] 1.673801 \n2919 [308, 225, 400, 219, 217, 167] 1.673698 \n2920 [225, 572, 217, 239, 116, 167] 1.673698 \n2921 [308, 225, 400, 219, 239, 116, 167] 1.673609 \n2922 [308, 219, 217, 116, 167] 1.673428 \n2923 [308, 593, 219, 239, 116, 136] 1.673079 \n2924 [308, 225, 400, 572, 217, 239, 167] 1.672974 \n2925 [225, 400, 593, 572, 219, 217, 239, 102] 1.672862 \n2926 [225, 400, 572, 219, 217, 239, 116, 167] 1.672742 \n2927 [225, 400, 593, 239, 167] 1.671875 \n2928 [225, 400, 572, 219, 239, 102, 116] 1.671833 \n2929 [572, 239, 102, 116, 167] 1.671628 \n2930 [308, 225, 593, 219, 102] 1.671543 \n2931 [308, 225, 593, 219, 217, 116] 1.671476 \n2932 [308, 225, 593, 572, 219, 136] 1.671449 \n2933 [308, 225, 400, 593, 572, 219, 217, 239, 167] 1.671203 \n2934 [225, 400, 219, 217, 136] 1.671123 \n2935 [225, 593, 219, 217, 102] 1.670974 \n2936 [308, 400, 572, 219, 217, 116] 1.670956 \n2937 [308, 593, 572, 219, 239, 102, 167] 1.670936 \n2938 [593, 239, 102, 116] 1.670866 \n2939 [400, 239, 102, 116] 1.670565 \n2940 [593, 239, 102, 136] 1.670565 \n2941 [225, 593, 572, 219, 217, 136] 1.670499 \n2942 [593, 219, 217, 239, 102, 167] 1.670463 \n2943 [400, 102] 1.670436 \n2944 [308, 225, 400, 217, 239, 167] 1.670232 \n2945 [308, 225, 400, 593, 219, 239, 102] 1.670092 \n2946 [400, 593, 572, 219, 167] 1.670048 \n2947 [225, 400, 572, 219, 102] 1.669700 \n2948 [593, 572, 219, 217, 102] 1.669494 \n2949 [308, 400, 572, 219, 239, 102, 167] 1.669455 \n2950 [572, 219, 239, 102, 116, 167] 1.669302 \n2951 [308, 400, 217, 239, 136] 1.669147 \n2952 [308, 225, 593, 219, 239, 116, 167] 1.669015 \n2953 [225, 217, 239, 116, 167] 1.668750 \n2954 [400, 219, 217, 239, 102, 167] 1.668642 \n2955 [308, 225, 219, 217, 239, 102, 116] 1.668533 \n2956 [225, 593, 572, 217, 239, 136] 1.668450 \n2957 [308, 102, 116] 1.667828 \n2958 [308, 225, 593, 572, 219, 217, 167] 1.667814 \n2959 [308, 225, 400, 572, 219, 116] 1.667785 \n2960 [308, 400, 593] 1.667691 \n2961 [308, 225, 400, 593, 572, 219, 239, 136] 1.667614 \n2962 [225, 136, 167] 1.667583 \n2963 [225, 400, 219, 217, 239, 116, 167] 1.667488 \n2964 [593, 572, 219, 239, 102, 136] 1.667417 \n2965 [400, 593, 572, 239, 136] 1.666419 \n2966 [225, 400, 219, 239, 102, 116] 1.666336 \n2967 [400, 572, 219, 217, 239, 136, 167] 1.666324 \n2968 [225, 217, 239, 136, 167] 1.666170 \n2969 [572, 217, 239, 102, 116] 1.665637 \n2970 [308, 225, 593, 572, 239, 102] 1.665345 \n2971 [308, 225, 400, 593, 219, 217, 239, 167] 1.665261 \n2972 [225, 400, 572, 219, 217, 116] 1.665140 \n2973 [400, 219, 217, 102] 1.664471 \n2974 [225, 593, 219, 217, 239, 116, 167] 1.664032 \n2975 [225, 400, 593, 219, 217, 239, 102] 1.664010 \n2976 [400, 593, 572, 239, 102] 1.663944 \n2977 [308, 225, 572, 219, 217, 239, 116, 136] 1.663820 \n2978 [308, 400, 593, 572, 219, 217, 239, 116] 1.663670 \n2979 [308, 225, 239, 102, 167] 1.663531 \n2980 [400, 572, 239, 136, 167] 1.663523 \n2981 [308, 400, 572, 219, 102] 1.663505 \n2982 [308, 219, 217, 239, 102, 136] 1.663299 \n2983 [308, 593, 572, 219, 239, 136, 167] 1.663156 \n2984 [308, 225, 593, 572, 239, 136] 1.663123 \n2985 [225, 593, 572, 219, 239, 116, 136] 1.663061 \n2986 [308, 225, 400, 219, 116] 1.662834 \n2987 [572, 219, 217, 116, 167] 1.662549 \n2988 [308, 225, 239, 136, 167] 1.662513 \n2989 [400, 572, 239, 102, 167] 1.661993 \n2990 [225, 400, 593, 572, 219, 217, 239, 136] 1.661943 \n2991 [572, 217, 239, 116, 136] 1.661831 \n2992 [225, 102, 136] 1.661728 \n2993 [308, 225, 572, 219, 217, 239, 102, 167] 1.661689 \n2994 [308, 225, 400, 593, 219, 239, 136] 1.661610 \n2995 [308, 225, 572, 239, 116, 167] 1.661569 \n2996 [308, 400, 219, 217, 116] 1.661489 \n2997 [308, 400, 219, 239, 102, 167] 1.661235 \n2998 [225, 593, 219, 239, 102, 116] 1.661080 \n2999 [593, 239, 136, 167] 1.660881 \n3000 [308, 400, 572, 219, 239, 136, 167] 1.660693 \n3001 [225, 400, 572, 219, 239, 116, 136] 1.660418 \n3002 [225, 400, 219, 102] 1.659448 \n3003 [308, 572, 219, 136, 167] 1.659249 \n3004 [308, 225, 239, 116, 167] 1.659230 \n3005 [308, 225, 572, 102] 1.659163 \n3006 [225, 593, 217, 239, 102] 1.659145 \n3007 [308, 572, 217, 136] 1.658682 \n3008 [308, 400, 593, 219, 217, 239, 116] 1.658114 \n3009 [572, 219, 239, 116, 136, 167] 1.657736 \n3010 [572, 219, 102, 167] 1.657586 \n3011 [400, 572, 219, 239, 102, 136] 1.657442 \n3012 [225, 572, 217, 136] 1.657367 \n3013 [308, 400, 572, 217, 239, 116] 1.657018 \n3014 [593, 219, 217, 239, 136, 167] 1.656959 \n3015 [308, 225, 400, 572, 217] 1.656182 \n3016 [225, 400, 219, 217, 116] 1.655636 \n3017 [308, 593, 572, 217, 239, 167] 1.655562 \n3018 [308, 225, 217, 167] 1.655379 \n3019 [308, 400, 217, 239, 116] 1.655276 \n3020 [308, 593, 219, 239, 102, 167] 1.655275 \n3021 [400, 219, 217, 239, 136, 167] 1.655002 \n3022 [225, 593, 572, 219, 102] 1.654929 \n3023 [308, 225, 219, 217, 239, 116, 136] 1.654916 \n3024 [400, 572, 219, 217, 136] 1.654829 \n3025 [308, 219, 116, 136] 1.654720 \n3026 [225, 400, 219, 239, 116, 136] 1.654146 \n3027 [400, 593, 239, 136] 1.653522 \n3028 [308, 225, 593, 239, 136] 1.653384 \n3029 [308, 225, 593, 239, 102] 1.653332 \n3030 [225, 593, 572, 219, 239, 102, 167] 1.653264 \n3031 [308, 225, 400, 593, 572, 219, 217] 1.653034 \n3032 [308, 593, 572, 219, 217, 116] 1.653013 \n3033 [225, 400, 572, 217, 239, 102] 1.652948 \n3034 [400, 593, 219, 167] 1.652862 \n3035 [308, 225, 400, 593, 572, 217, 239] 1.652837 \n3036 [308, 102, 136] 1.652757 \n3037 [225, 593, 217, 239, 136] 1.652495 \n3038 [225, 572, 217, 116] 1.652454 \n3039 [308, 225, 400, 572, 239, 102] 1.652333 \n3040 [225, 400, 593, 219, 217, 239, 136] 1.652323 \n3041 [225, 400, 572, 219, 239, 102, 167] 1.652309 \n3042 [308, 400, 219, 239, 136, 167] 1.652159 \n3043 [308, 116, 136] 1.652116 \n3044 [225, 572, 219, 116, 167] 1.651839 \n3045 [308, 593, 219, 217, 136] 1.651696 \n3046 [308, 400, 572, 219, 217, 167] 1.651058 \n3047 [225, 593, 572, 217, 239, 116] 1.651036 \n3048 [308, 225, 400, 593, 572, 219, 239, 116] 1.650925 \n3049 [308, 225, 593, 572, 217] 1.650901 \n3050 [308, 219, 102, 167] 1.650816 \n3051 [308, 225, 219, 217, 239, 102, 167] 1.650562 \n3052 [219, 102, 116] 1.650226 \n3053 [308, 572, 219, 217, 239, 102, 116] 1.650208 \n3054 [308, 400, 219, 102] 1.650168 \n3055 [593, 572, 219, 217, 239, 116, 167] 1.650017 \n3056 [308, 225, 593, 219, 136] 1.649900 \n3057 [400, 572, 239, 116, 167] 1.649790 \n3058 [225, 593, 219, 239, 116, 136] 1.649656 \n3059 [400, 136] 1.649393 \n3060 [308, 225, 593, 572, 219, 116] 1.649252 \n3061 [308, 225, 572, 219, 239, 102, 136] 1.649141 \n3062 [219, 217, 136, 167] 1.649113 \n3063 [308, 225, 572, 219, 217, 239, 136, 167] 1.649062 \n3064 [308, 225, 400, 593, 217, 239] 1.648869 \n3065 [572, 217, 239, 102, 167] 1.648707 \n3066 [308, 225, 593, 219, 217, 167] 1.648633 \n3067 [219, 239, 102, 116, 167] 1.648342 \n3068 [400, 593, 572, 219, 217, 239, 102] 1.647977 \n3069 [308, 225, 400, 217] 1.647962 \n3070 [308, 572, 239, 102, 136] 1.647705 \n3071 [400, 593, 572, 239, 116] 1.647624 \n3072 [308, 593, 219, 239, 136, 167] 1.647591 \n3073 [225, 593, 572, 219, 217, 116] 1.647393 \n3074 [308, 400, 593, 572, 219, 217, 239, 167] 1.647051 \n3075 [593, 572, 167] 1.646795 \n3076 [308, 225, 400, 572, 239, 136] 1.646646 \n3077 [308, 225, 400, 593, 219, 239, 116] 1.646585 \n3078 [400, 593, 239, 102] 1.646484 \n3079 [225, 217, 102] 1.646078 \n3080 [308, 593, 217, 239, 167] 1.645698 \n3081 [225, 593, 217, 239, 116] 1.645680 \n3082 [308, 225, 400, 239, 102] 1.645636 \n3083 [308, 225, 593, 572, 239, 116] 1.645626 \n3084 [308, 225, 400, 572, 219, 167] 1.645618 \n3085 [400, 572, 219, 217, 239, 116, 167] 1.645557 \n3086 [400, 593, 239, 116] 1.645501 \n3087 [225, 400, 572, 219, 136] 1.645321 \n3088 [308, 400, 572, 219, 136] 1.645077 \n3089 [225, 400, 593, 572, 219, 217, 239, 116] 1.644860 \n3090 [572, 219, 116, 136] 1.644733 \n3091 [572, 217, 239, 136, 167] 1.644706 \n3092 [225, 572, 219, 217, 239, 102, 136] 1.644299 \n3093 [225, 400, 572, 219, 217, 167] 1.644179 \n3094 [308, 400, 593, 572, 219, 239, 102] 1.643993 \n3095 [308, 116, 167] 1.643963 \n3096 [308, 225, 593, 239, 116] 1.643588 \n3097 [225, 400, 572, 217, 239, 136] 1.642860 \n3098 [308, 225, 400, 593, 219, 217] 1.642259 \n3099 [308, 593, 572, 219, 102] 1.642222 \n3100 [225, 593, 572, 219, 239, 136, 167] 1.642145 \n3101 [400, 219, 239, 102, 136] 1.642054 \n3102 [225, 400, 219, 239, 102, 167] 1.642027 \n3103 [225, 400, 217, 239, 102] 1.641727 \n3104 [308, 400, 572, 219, 239, 116, 167] 1.641098 \n3105 [217, 239, 102, 136] 1.640917 \n3106 [225, 400, 572, 219, 239, 136, 167] 1.640816 \n3107 [400, 239, 116, 167] 1.640782 \n3108 [308, 225, 400, 239, 136] 1.640599 \n3109 [225, 219, 136, 167] 1.640330 \n3110 [225, 593, 219, 217, 136] 1.639999 \n3111 [593, 219, 239, 102, 136] 1.639643 \n3112 [593, 572, 219, 217, 136] 1.639337 \n3113 [308, 572, 217, 116] 1.639285 \n3114 [308, 593, 572, 219, 239, 116, 167] 1.639278 \n3115 [308, 219, 217, 239, 102, 116] 1.638740 \n3116 [308, 400, 593, 219, 217, 239, 167] 1.638509 \n3117 [400, 239, 136, 167] 1.638331 \n3118 [593, 572, 217, 239, 102] 1.638045 \n3119 [308, 572, 219, 217, 239, 116, 136] 1.637731 \n3120 [225, 400, 593, 219, 217, 239, 116] 1.637303 \n3121 [400, 593, 572, 219, 217, 239, 136] 1.637261 \n3122 [400, 219, 217, 239, 116, 167] 1.637245 \n3123 [308, 400, 219, 217, 167] 1.637080 \n3124 [219, 239, 116, 136, 167] 1.636932 \n3125 [308, 225, 219, 217, 239, 136, 167] 1.636891 \n3126 [308, 225, 572, 136] 1.636661 \n3127 [308, 400, 593, 572, 219, 239, 136] 1.636460 \n3128 [593, 572, 217, 239, 136] 1.636158 \n3129 [217, 239, 116, 136] 1.636119 \n3130 [308, 400, 572, 217, 239, 167] 1.635742 \n3131 [400, 593, 219, 217, 239, 102] 1.635639 \n3132 [308, 225, 400, 219, 167] 1.635517 \n3133 [308, 225, 219, 239, 102, 136] 1.635354 \n3134 [593, 219, 217, 239, 116, 167] 1.635221 \n3135 [308, 400, 219, 239, 116, 167] 1.634960 \n3136 [217, 239, 102, 116] 1.634729 \n3137 [400, 219, 217, 136] 1.634578 \n3138 [308, 225, 400, 572, 219, 217, 239, 102] 1.634523 \n3139 [308, 400, 593, 219, 239, 102] 1.634331 \n3140 [225, 593, 219, 239, 102, 167] 1.634248 \n3141 [400, 593, 572] 1.633889 \n3142 [308, 572, 219, 217, 239, 102, 167] 1.633881 \n3143 [308, 225, 572, 219, 217, 102] 1.633694 \n3144 [308, 217, 102] 1.633403 \n3145 [308, 225, 400, 593, 572, 219, 239, 167] 1.632966 \n3146 [593, 572, 219, 239, 102, 116] 1.632798 \n3147 [308, 225, 593, 219, 116] 1.632497 \n3148 [308, 225, 400, 572, 239, 116] 1.632452 \n3149 [400, 239, 102, 167] 1.632083 \n3150 [308, 225, 593, 572, 219, 217, 239, 102] 1.631887 \n3151 [308, 593, 572, 219, 217, 167] 1.631859 \n3152 [308, 572, 219, 116, 167] 1.631817 \n3153 [400, 572, 167] 1.631735 \n3154 [225, 219, 116, 167] 1.631697 \n3155 [308, 225, 400, 239, 116] 1.631462 \n3156 [225, 400, 217, 239, 136] 1.631379 \n3157 [400, 572, 219, 239, 102, 116] 1.631139 \n3158 [225, 400, 219, 136] 1.631059 \n3159 [308, 225, 572, 219, 217, 239, 116, 167] 1.630839 \n3160 [593, 219, 217, 102] 1.630741 \n3161 [400, 572, 219, 217, 116] 1.630738 \n3162 [308, 593, 219, 217, 116] 1.630580 \n3163 [219, 217, 116, 167] 1.630196 \n3164 [225, 400, 219, 239, 136, 167] 1.629740 \n3165 [308, 225, 593, 217] 1.629685 \n3166 [225, 400, 219, 217, 167] 1.629406 \n3167 [308, 400, 219, 136] 1.629400 \n3168 [225, 400, 572, 217, 239, 116] 1.629023 \n3169 [308, 400, 217, 239, 167] 1.628383 \n3170 [572, 217, 239, 116, 167] 1.627734 \n3171 [225, 400, 593, 572, 219, 217, 239, 167] 1.627646 \n3172 [225, 217, 116] 1.627412 \n3173 [308, 593, 219, 239, 116, 167] 1.627038 \n3174 [308, 225, 572, 116] 1.626938 \n3175 [225, 593, 572, 217, 239, 167] 1.626886 \n3176 [572, 217, 102] 1.626875 \n3177 [225, 593, 572, 219, 136] 1.626785 \n3178 [308, 102, 167] 1.626656 \n3179 [308, 400, 593, 219, 239, 136] 1.626624 \n3180 [593, 239, 102, 167] 1.626371 \n3181 [308, 225, 400, 219, 217, 239, 102] 1.626309 \n3182 [308, 225, 572, 219, 239, 102, 116] 1.626072 \n3183 [225, 400, 593, 572, 219, 239, 102] 1.626014 \n3184 [308, 572, 239, 116, 136] 1.625719 \n3185 [308, 225, 400, 593, 219, 239, 167] 1.625379 \n3186 [308, 219, 217, 239, 116, 136] 1.625276 \n3187 [308, 225, 593, 572, 219, 167] 1.625171 \n3188 [225, 593, 572, 219, 217, 167] 1.625104 \n3189 [400, 593] 1.625097 \n3190 [225, 400, 572, 219, 116] 1.625066 \n3191 [400, 593, 219, 217, 239, 136] 1.624227 \n3192 [225, 400, 217, 239, 116] 1.624108 \n3193 [308, 225, 400, 572, 219, 217, 239, 136] 1.623985 \n3194 [225, 593, 219, 102] 1.623939 \n3195 [225, 219, 217, 239, 102, 136] 1.623875 \n3196 [593, 572, 219, 239, 116, 136] 1.623811 \n3197 [225, 572, 217, 167] 1.623579 \n3198 [308, 593, 167] 1.623575 \n3199 [225, 400, 572, 219, 239, 116, 167] 1.623477 \n3200 [225, 593, 219, 217, 116] 1.623244 \n3201 [308, 572, 239, 102, 116] 1.622771 \n3202 [308, 400, 572, 219, 116] 1.622759 \n3203 [225, 593, 219, 239, 136, 167] 1.622622 \n3204 [308, 593, 572, 219, 136] 1.622265 \n3205 [308, 219, 136, 167] 1.621587 \n3206 [308, 400, 593, 572, 219, 217] 1.621378 \n3207 [308, 572, 219, 217, 239, 136, 167] 1.621322 \n3208 [308, 225, 219, 217, 239, 116, 167] 1.621196 \n3209 [225, 593, 572, 219, 239, 116, 167] 1.621063 \n3210 [308, 225, 593, 572, 219, 217, 239, 136] 1.621021 \n3211 [400, 572, 219, 239, 116, 136] 1.620523 \n3212 [225, 572, 219, 217, 239, 102, 116] 1.620165 \n3213 [400, 572, 219, 102] 1.619520 \n3214 [400, 219, 239, 102, 116] 1.619386 \n3215 [308, 225, 593, 572, 239, 167] 1.619061 \n3216 [308, 225, 593, 219, 217, 239, 102] 1.618847 \n3217 [308, 400, 593, 572, 217, 239] 1.618408 \n3218 [308, 219, 217, 239, 102, 167] 1.618291 \n3219 [572, 219, 217, 239, 102, 136] 1.617873 \n3220 [308, 225, 102] 1.617447 \n3221 [308, 400, 593, 572, 219, 239, 116] 1.617366 \n3222 [308, 225, 400, 593, 572, 219] 1.617187 \n3223 [400, 593, 572, 219, 217, 239, 116] 1.617159 \n3224 [225, 400, 219, 116] 1.616813 \n3225 [225, 400, 593, 219, 217, 239, 167] 1.616798 \n3226 [217, 239, 116, 167] 1.616456 \n3227 [225, 400, 593, 572, 219, 239, 136] 1.616243 \n3228 [225, 400, 219, 239, 116, 167] 1.615961 \n3229 [400, 219, 217, 116] 1.615607 \n3230 [308, 225, 219, 239, 102, 116] 1.615229 \n3231 [308, 225, 400, 219, 217, 239, 136] 1.615025 \n3232 [308, 225, 572, 219, 239, 116, 136] 1.614739 \n3233 [572, 219, 136, 167] 1.614576 \n3234 [400, 593, 572, 239, 167] 1.614287 \n3235 [225, 400, 593, 219, 239, 102] 1.614146 \n3236 [593, 217, 239, 136] 1.613179 \n3237 [593, 572, 217, 239, 116] 1.613048 \n3238 [225, 593, 217, 239, 167] 1.612555 \n3239 [308, 225, 219, 217, 102] 1.611533 \n3240 [308, 572, 217, 167] 1.611280 \n3241 [225, 400, 593, 572, 219, 217] 1.611023 \n3242 [308, 400, 219, 116] 1.611006 \n3243 [308, 225, 572, 219, 217, 136] 1.610786 \n3244 [308, 400, 593, 217, 239] 1.610672 \n3245 [593, 219, 239, 102, 116] 1.610510 \n3246 [593, 217, 239, 102] 1.610354 \n3247 [308, 136, 167] 1.610103 \n3248 [593, 572, 219, 217, 116] 1.609479 \n3249 [308, 400, 593, 219, 239, 116] 1.609395 \n3250 [308, 593, 219, 102] 1.609298 \n3251 [400, 572, 219, 239, 102, 167] 1.608881 \n3252 [308, 225, 400, 572, 219, 217, 239, 116] 1.608842 \n3253 [308, 225, 400, 572, 239, 167] 1.608838 \n3254 [593, 572, 219, 239, 102, 167] 1.608720 \n3255 [308, 225, 593, 239, 167] 1.608387 \n3256 [400, 219, 239, 116, 136] 1.608324 \n3257 [308, 572, 219, 239, 102, 136] 1.608219 \n3258 [308, 225, 572, 217, 239, 102] 1.608153 \n3259 [217, 239, 136, 167] 1.608067 \n3260 [308, 225, 572, 219, 239, 102, 167] 1.607530 \n3261 [308, 225, 593, 219, 217, 239, 136] 1.607223 \n3262 [217, 239, 102, 167] 1.607204 \n3263 [308, 225, 116] 1.606914 \n3264 [225, 400, 572, 217, 239, 167] 1.606866 \n3265 [225, 593, 219, 239, 116, 167] 1.606716 \n3266 [400, 572, 219, 217, 167] 1.606467 \n3267 [400, 593, 219, 217, 239, 116] 1.606449 \n3268 [308, 400, 593, 219, 217] 1.605983 \n3269 [308, 400, 572, 219, 217, 239, 102] 1.605819 \n3270 [593, 217, 239, 116] 1.605413 \n3271 [308, 225, 400, 593, 219] 1.605157 \n3272 [400, 572, 217, 239, 102] 1.604891 \n3273 [308, 219, 217, 239, 136, 167] 1.604732 \n3274 [308, 400, 572, 217] 1.604231 \n3275 [308, 217, 116] 1.604065 \n3276 [308, 593, 219, 217, 167] 1.604007 \n3277 [225, 572, 219, 217, 239, 116, 136] 1.603982 \n3278 [225, 400, 593, 219, 239, 136] 1.603854 \n3279 [225, 572, 219, 217, 239, 102, 167] 1.603668 \n3280 [225, 219, 217, 239, 102, 116] 1.603640 \n3281 [308, 593, 572, 239, 136] 1.603383 \n3282 [308, 225, 593, 572, 219, 217, 239, 116] 1.603376 \n3283 [308, 225, 219, 239, 116, 136] 1.603147 \n3284 [308, 593, 572, 219, 217, 239, 102] 1.603050 \n3285 [308, 219, 116, 167] 1.602995 \n3286 [308, 217, 136] 1.602910 \n3287 [225, 593, 572, 219, 116] 1.602432 \n3288 [308, 239, 102, 136] 1.602357 \n3289 [308, 225, 593, 219, 167] 1.602107 \n3290 [593, 219, 239, 116, 136] 1.601998 \n3291 [239, 116, 136, 167] 1.601875 \n3292 [400, 167] 1.601789 \n3293 [308, 225, 400, 239, 167] 1.601610 \n3294 [219, 102, 167] 1.601502 \n3295 [308, 225, 400, 219, 217, 239, 116] 1.601438 \n3296 [308, 572, 239, 136, 167] 1.600643 \n3297 [308, 239, 116, 136] 1.600619 \n3298 [308, 593, 572, 239, 102] 1.600224 \n3299 [400, 593, 239, 167] 1.599682 \n3300 [308, 572, 219, 217, 239, 116, 167] 1.599540 \n3301 [593, 572, 219, 239, 136, 167] 1.599487 \n3302 [225, 400, 593, 572, 219, 239, 116] 1.598946 \n3303 [400, 219, 102] 1.598313 \n3304 [572, 116, 167] 1.598259 \n3305 [308, 225, 572, 217, 239, 136] 1.598256 \n3306 [225, 593, 572, 217] 1.598193 \n3307 [308, 572, 239, 102, 167] 1.598138 \n3308 [400, 572, 219, 239, 136, 167] 1.598129 \n3309 [593, 572, 219, 102] 1.597868 \n3310 [400, 593, 572, 219, 217, 239, 167] 1.597801 \n3311 [225, 400, 572, 219, 167] 1.597384 \n3312 [308, 400, 572, 219, 167] 1.597363 \n3313 [308, 400, 593, 572, 219, 239, 167] 1.597304 \n3314 [225, 400, 572, 217] 1.597070 \n3315 [400, 572, 217, 239, 136] 1.596880 \n3316 [308, 225, 400, 593, 572, 239] 1.596327 \n3317 [308, 225, 572, 219, 239, 136, 167] 1.596109 \n3318 [308, 593, 572, 219, 116] 1.595548 \n3319 [225, 400, 217, 239, 167] 1.595540 \n3320 [308, 400, 572, 219, 217, 239, 136] 1.595282 \n3321 [593, 219, 217, 136] 1.595276 \n3322 [219, 116, 136] 1.595036 \n3323 [308, 225, 400, 572] 1.594500 \n3324 [225, 593, 219, 217, 167] 1.594478 \n3325 [308, 400, 219, 217, 239, 102] 1.594330 \n3326 [225, 400, 593, 219, 217] 1.594067 \n3327 [308, 593, 572, 217] 1.593501 \n3328 [308, 225, 400, 572, 219, 217, 239, 167] 1.593291 \n3329 [400, 572, 219, 136] 1.593069 \n3330 [308, 572, 219, 217, 102] 1.592995 \n3331 [308, 593, 572, 219, 217, 239, 136] 1.592403 \n3332 [308, 225, 219, 239, 102, 167] 1.592072 \n3333 [225, 217, 136] 1.592023 \n3334 [308, 239, 102, 116] 1.591831 \n3335 [308, 225, 572, 167] 1.591702 \n3336 [308, 225, 217, 239, 102] 1.591675 \n3337 [308, 225, 136] 1.591656 \n3338 [308, 225, 593, 219, 217, 239, 116] 1.591594 \n3339 [308, 400, 572, 239, 102] 1.591578 \n3340 [308, 225, 572, 219, 217, 116] 1.591351 \n3341 [225, 400, 593, 572, 217, 239] 1.591290 \n3342 [400, 219, 239, 102, 167] 1.590940 \n3343 [219, 217, 239, 102, 136] 1.590841 \n3344 [225, 593, 219, 136] 1.590705 \n3345 [225, 572, 239, 102, 136] 1.589859 \n3346 [225, 400, 593, 219, 239, 116] 1.589287 \n3347 [308, 225, 400, 593, 239] 1.589281 \n3348 [308, 225, 400, 572, 219, 239, 102] 1.588380 \n3349 [308, 400, 572, 239, 136] 1.588329 \n3350 [225, 572, 219, 217, 239, 136, 167] 1.587400 \n3351 [572, 219, 217, 239, 102, 116] 1.586934 \n3352 [308, 225, 593, 572, 219, 217, 239, 167] 1.586838 \n3353 [308, 593, 219, 136] 1.586751 \n3354 [308, 400, 217] 1.586480 \n3355 [308, 219, 239, 102, 136] 1.586311 \n3356 [308, 219, 217, 239, 116, 167] 1.585848 \n3357 [225, 219, 217, 239, 116, 136] 1.585678 \n3358 [308, 593, 219, 217, 239, 102] 1.585584 \n3359 [308, 225, 219, 217, 136] 1.585534 \n3360 [308, 400, 593, 219, 239, 167] 1.585357 \n3361 [400, 593, 572, 219, 239, 102] 1.584796 \n3362 [400, 219, 217, 167] 1.584291 \n3363 [308, 572, 239, 116, 167] 1.584277 \n3364 [593, 572, 217, 239, 167] 1.584013 \n3365 [400, 217, 239, 102] 1.583940 \n3366 [308, 225, 400] 1.583738 \n3367 [308, 225, 400, 219, 217, 239, 167] 1.583219 \n3368 [593, 572, 219, 217, 167] 1.583214 \n3369 [308, 400, 219, 217, 239, 136] 1.583053 \n3370 [400, 593, 219, 217, 239, 167] 1.582965 \n3371 [308, 225, 572, 217, 239, 116] 1.582863 \n3372 [572, 219, 116, 167] 1.582799 \n3373 [225, 219, 217, 239, 102, 167] 1.582592 \n3374 [308, 593, 572, 239, 116] 1.582493 \n3375 [308, 225, 572, 219, 102] 1.582187 \n3376 [308, 225, 217, 239, 136] 1.581609 \n3377 [308, 225, 593, 572, 219, 239, 102] 1.581378 \n3378 [308, 225, 593, 572] 1.581242 \n3379 [225, 400, 219, 167] 1.580825 \n3380 [225, 400, 217] 1.580671 \n3381 [400, 572, 217, 239, 116] 1.580383 \n3382 [308, 572, 219, 239, 102, 116] 1.580333 \n3383 [225, 400, 593, 217, 239] 1.580135 \n3384 [225, 217, 167] 1.579880 \n3385 [308, 225, 219, 239, 136, 167] 1.579878 \n3386 [400, 219, 239, 136, 167] 1.579682 \n3387 [308, 593, 239, 136] 1.579672 \n3388 [225, 572, 219, 217, 102] 1.579398 \n3389 [308, 400, 219, 167] 1.578997 \n3390 [225, 400, 572, 219, 217, 239, 102] 1.578995 \n3391 [308, 225, 400, 572, 219, 239, 136] 1.578576 \n3392 [593, 219, 239, 102, 167] 1.578194 \n3393 [308, 400, 572, 219, 217, 239, 116] 1.577917 \n3394 [225, 400, 593, 572, 219, 239, 167] 1.577829 \n3395 [308, 225, 572, 219, 239, 116, 167] 1.577786 \n3396 [572, 217, 136] 1.577744 \n3397 [400, 572, 219, 239, 116, 167] 1.577698 \n3398 [308, 225, 400, 219, 239, 102] 1.577535 \n3399 [225, 572, 239, 102, 116] 1.577166 \n3400 [400, 217, 239, 136] 1.576633 \n3401 [225, 593, 219, 116] 1.576183 \n3402 [400, 593, 572, 219, 239, 136] 1.575817 \n3403 [225, 572, 239, 116, 136] 1.575729 \n3404 [572, 217, 116] 1.575679 \n3405 [572, 102, 116] 1.575160 \n3406 [308, 593, 219, 217, 239, 136] 1.574255 \n3407 [593, 219, 217, 116] 1.573797 \n3408 [308, 400, 239, 102] 1.573513 \n3409 [593, 572, 219, 239, 116, 167] 1.573300 \n3410 [225, 572, 219, 239, 102, 136] 1.573278 \n3411 [308, 225, 400, 593, 572, 219, 217, 239] 1.573273 \n3412 [225, 593, 572, 219, 217, 239, 102] 1.572985 \n3413 [400, 593, 572, 219, 217] 1.572788 \n3414 [308, 225, 217, 239, 116] 1.572627 \n3415 [308, 400, 572, 239, 116] 1.572300 \n3416 [308, 400, 239, 136] 1.571877 \n3417 [308, 225, 593, 219, 217, 239, 167] 1.571876 \n3418 [308, 225, 572, 219, 217, 167] 1.571766 \n3419 [308, 225, 593, 572, 219, 239, 136] 1.571679 \n3420 [308, 593, 239, 102] 1.571611 \n3421 [308, 593, 572, 219, 217, 239, 116] 1.571575 \n3422 [225, 593, 572, 219, 167] 1.571398 \n3423 [308, 400, 593, 572, 219] 1.571301 \n3424 [572, 219, 217, 239, 116, 136] 1.570528 \n3425 [308, 225, 219, 217, 116] 1.570274 \n3426 [308, 572, 219, 239, 116, 136] 1.569849 \n3427 [593, 219, 239, 136, 167] 1.569268 \n3428 [308, 593, 239, 116] 1.569236 \n3429 [239, 102, 116, 167] 1.569142 \n3430 [400, 217, 239, 116] 1.568826 \n3431 [225, 572, 219, 217, 239, 116, 167] 1.568694 \n3432 [572, 219, 217, 239, 102, 167] 1.568325 \n3433 [400, 572, 219, 116] 1.568237 \n3434 [308, 572, 219, 217, 136] 1.567882 \n3435 [308, 593, 572, 219, 167] 1.567486 \n3436 [308, 400, 219, 217, 239, 116] 1.567411 \n3437 [308, 225, 400, 219, 239, 136] 1.567111 \n3438 [593, 572, 219, 136] 1.567030 \n3439 [400, 219, 136] 1.566916 \n3440 [308, 225, 400, 572, 219, 217] 1.566893 \n3441 [400, 593, 219, 239, 102] 1.566289 \n3442 [308, 593, 219, 116] 1.566187 \n3443 [225, 400, 572, 219, 217, 239, 136] 1.566087 \n3444 [225, 400, 593, 572, 219] 1.565927 \n3445 [225, 593, 572, 239, 136] 1.565566 \n3446 [225, 593, 572, 239, 102] 1.565474 \n3447 [308, 225, 219, 239, 116, 167] 1.565003 \n3448 [225, 219, 217, 239, 136, 167] 1.564552 \n3449 [308, 225, 593, 219, 239, 102] 1.564463 \n3450 [219, 217, 239, 102, 116] 1.564421 \n3451 [308, 239, 136, 167] 1.564179 \n3452 [225, 400, 219, 217, 239, 102] 1.563858 \n3453 [308, 239, 116, 167] 1.563849 \n3454 [225, 400, 593, 219, 239, 167] 1.563651 \n3455 [400, 219, 239, 116, 167] 1.563582 \n3456 [225, 593, 217] 1.563419 \n3457 [308, 225, 400, 572, 219, 239, 116] 1.563320 \n3458 [308, 217, 167] 1.562668 \n3459 [593, 217, 239, 167] 1.562623 \n3460 [308, 400, 239, 116] 1.562313 \n3461 [308, 225, 400, 593, 219, 217, 239] 1.562135 \n3462 [308, 225, 572, 217, 239, 167] 1.561856 \n3463 [308, 219, 239, 102, 116] 1.561842 \n3464 [308, 400, 572, 219, 217, 239, 167] 1.560670 \n3465 [308, 219, 217, 102] 1.560600 \n3466 [225, 593, 572, 219, 217, 239, 136] 1.559375 \n3467 [308, 572, 219, 239, 102, 167] 1.559262 \n3468 [225, 572, 102] 1.559188 \n3469 [308, 225, 572, 219, 136] 1.558363 \n3470 [239, 102, 116, 136] 1.557658 \n3471 [225, 400, 572, 239, 102] 1.557626 \n3472 [572, 102, 167] 1.557563 \n3473 [400, 593, 219, 239, 136] 1.557059 \n3474 [308, 239, 102, 167] 1.556410 \n3475 [308, 572, 217, 239, 102] 1.555784 \n3476 [308, 593, 219, 217, 239, 116] 1.555684 \n3477 [400, 593, 572, 219, 239, 116] 1.555549 \n3478 [308, 225, 219, 102] 1.555133 \n3479 [308, 593, 217] 1.554979 \n3480 [400, 572, 217, 239, 167] 1.554539 \n3481 [308, 225, 167] 1.554346 \n3482 [308, 225, 593, 219, 239, 136] 1.554259 \n3483 [308, 225, 400, 219, 239, 116] 1.553855 \n3484 [308, 225, 593, 572, 219, 239, 116] 1.553657 \n3485 [225, 593, 572, 239, 116] 1.553572 \n3486 [308, 225, 593] 1.553305 \n3487 [308, 593, 572, 219, 217, 239, 167] 1.553018 \n3488 [225, 572, 239, 102, 167] 1.552402 \n3489 [308, 400, 593, 219] 1.552093 \n3490 [572, 219, 217, 239, 136, 167] 1.551786 \n3491 [225, 400, 572, 239, 136] 1.551270 \n3492 [572, 116, 136] 1.551097 \n3493 [308, 225, 400, 219, 217] 1.551014 \n3494 [308, 219, 239, 116, 136] 1.550962 \n3495 [308, 593, 572, 239, 167] 1.550959 \n3496 [225, 400, 572, 219, 217, 239, 116] 1.550697 \n3497 [225, 572, 239, 136, 167] 1.550537 \n3498 [225, 593, 219, 217, 239, 102] 1.550374 \n3499 [225, 219, 217, 239, 116, 167] 1.550302 \n3500 [400, 219, 116] 1.549909 \n3501 [225, 400, 219, 217, 239, 136] 1.549813 \n3502 [593, 219, 239, 116, 167] 1.549647 \n3503 [400, 593, 219, 217] 1.548882 \n3504 [225, 572, 219, 239, 102, 116] 1.548774 \n3505 [308, 572, 219, 239, 136, 167] 1.548633 \n3506 [572, 102, 136] 1.548336 \n3507 [308, 572, 217, 239, 136] 1.548191 \n3508 [225, 572, 239, 116, 167] 1.547540 \n3509 [308, 400, 219, 217, 239, 167] 1.546911 \n3510 [225, 400, 593, 219] 1.546745 \n3511 [219, 136, 167] 1.546606 \n3512 [225, 572, 219, 217, 136] 1.546278 \n3513 [219, 217, 239, 116, 136] 1.546203 \n3514 [308, 225, 219, 217, 167] 1.545880 \n3515 [308, 225, 593, 572, 217, 239] 1.545696 \n3516 [308, 400, 572, 219, 239, 102] 1.545521 \n3517 [308, 225, 217, 239, 167] 1.545375 \n3518 [308, 400, 572, 239, 167] 1.545104 \n3519 [400, 593, 572, 217, 239] 1.544963 \n3520 [308, 225, 400, 572, 219, 239, 167] 1.544667 \n3521 [308, 572, 219, 217, 116] 1.544306 \n3522 [308, 225, 400, 572, 217, 239] 1.544141 \n3523 [225, 219, 239, 102, 136] 1.543694 \n3524 [225, 572, 116] 1.543480 \n3525 [593, 219, 102] 1.543129 \n3526 [308, 225, 593, 572, 219, 217] 1.543004 \n3527 [225, 219, 217, 102] 1.542747 \n3528 [400, 572, 219, 217, 239, 102] 1.541892 \n3529 [308, 400, 593, 572, 219, 217, 239] 1.541278 \n3530 [225, 400, 572, 239, 116] 1.541106 \n3531 [225, 593, 572, 219, 217, 239, 116] 1.540992 \n3532 [308, 225, 572, 219, 217, 239, 102] 1.540744 \n3533 [308, 400, 593, 572, 239] 1.540498 \n3534 [572, 217, 167] 1.540291 \n3535 [400, 593, 219, 239, 116] 1.540000 \n3536 [219, 217, 239, 102, 167] 1.539717 \n3537 [225, 593, 239, 116] 1.539542 \n3538 [308, 225, 593, 219, 239, 116] 1.538892 \n3539 [239, 102, 136, 167] 1.538786 \n3540 [219, 116, 167] 1.538507 \n3541 [593, 219, 217, 167] 1.538473 \n3542 [308, 225, 572, 219, 116] 1.538415 \n3543 [225, 400, 219, 217, 239, 116] 1.536908 \n3544 [593, 572, 219, 217, 239, 102] 1.536213 \n3545 [308, 400, 572, 219, 239, 136] 1.536063 \n3546 [225, 593, 219, 217, 239, 136] 1.535540 \n3547 [308, 593, 572, 219, 239, 102] 1.535290 \n3548 [400, 572, 219, 167] 1.535169 \n3549 [225, 239, 116, 136] 1.535145 \n3550 [593, 572, 219, 116] 1.535140 \n3551 [308, 219, 239, 102, 167] 1.534797 \n3552 [593, 572, 217] 1.534248 \n3553 [400, 217, 239, 167] 1.534200 \n3554 [225, 572, 219, 239, 116, 136] 1.534116 \n3555 [225, 593, 219, 167] 1.534103 \n3556 [308, 225, 593, 572, 219, 239, 167] 1.533313 \n3557 [308, 593, 219, 217, 239, 167] 1.533144 \n3558 [225, 400, 239, 102] 1.533121 \n3559 [225, 593, 239, 136] 1.533034 \n3560 [225, 400, 572, 219, 217, 239, 167] 1.532834 \n3561 [572, 136, 167] 1.532803 \n3562 [572, 219, 217, 102] 1.532239 \n3563 [308, 225, 400, 217, 239] 1.531704 \n3564 [308, 219, 217, 136] 1.531676 \n3565 [308, 225, 400, 219, 239, 167] 1.531659 \n3566 [400, 593, 572, 219, 239, 167] 1.531432 \n3567 [225, 239, 102, 116] 1.530975 \n3568 [593, 167] 1.530806 \n3569 [225, 116] 1.530784 \n3570 [308, 593, 219, 167] 1.529803 \n3571 [308, 572, 217, 239, 116] 1.529429 \n3572 [308, 225, 593, 217, 239] 1.529192 \n3573 [308, 400, 219, 239, 102] 1.528987 \n3574 [400, 572, 219, 217, 239, 136] 1.528804 \n3575 [308, 217, 239, 102] 1.528367 \n3576 [572, 219, 217, 239, 116, 167] 1.528298 \n3577 [225, 400, 239, 136] 1.527928 \n3578 [225, 400, 239, 116] 1.527918 \n3579 [308, 225, 572, 219, 217, 239, 136] 1.527825 \n3580 [225, 593, 239, 102] 1.527772 \n3581 [308, 225, 219, 136] 1.527601 \n3582 [308, 225, 400, 593, 572, 219, 239] 1.527598 \n3583 [400, 572, 217] 1.527145 \n3584 [400, 593, 217, 239] 1.527106 \n3585 [308, 400, 239, 167] 1.527005 \n3586 [225, 572, 219, 239, 102, 167] 1.526889 \n3587 [308, 572, 219, 239, 116, 167] 1.526883 \n3588 [308, 400, 593, 219, 217, 239] 1.526659 \n3589 [308, 593, 572, 219, 239, 136] 1.526415 \n3590 [225, 572, 219, 217, 116] 1.526021 \n3591 [308, 593, 239, 167] 1.525647 \n3592 [308, 400, 593, 239] 1.525313 \n3593 [225, 219, 239, 102, 116] 1.524965 \n3594 [308, 400, 572, 219, 217] 1.524417 \n3595 [593, 136] 1.523855 \n3596 [308, 219, 239, 136, 167] 1.523705 \n3597 [593, 572, 219, 217, 239, 136] 1.522698 \n3598 [225, 239, 116, 167] 1.521952 \n3599 [308, 572, 219, 217, 167] 1.521828 \n3600 [308, 225, 219, 217, 239, 102] 1.521808 \n3601 [225, 593, 572, 219, 217, 239, 167] 1.521741 \n3602 [308, 217, 239, 136] 1.521731 \n3603 [219, 217, 239, 136, 167] 1.521348 \n3604 [400, 219, 217, 239, 102] 1.521308 \n3605 [225, 593, 219, 217, 239, 116] 1.520548 \n3606 [593, 102] 1.519465 \n3607 [225, 572, 136] 1.519230 \n3608 [225, 593, 572, 239, 167] 1.519207 \n3609 [308, 400, 219, 239, 136] 1.519011 \n3610 [308, 400, 572, 219, 239, 116] 1.518675 \n3611 [225, 239, 102, 136] 1.518538 \n3612 [308, 225, 400, 572, 219] 1.518510 \n3613 [308, 572, 102] 1.517505 \n3614 [225, 400, 572, 219, 239, 102] 1.516821 \n3615 [217, 116] 1.516507 \n3616 [308, 225, 593, 219, 217] 1.516456 \n3617 [225, 400, 219, 217, 239, 167] 1.515465 \n3618 [572, 219, 239, 102, 136] 1.514983 \n3619 [308, 225, 593, 219, 239, 167] 1.514166 \n3620 [308, 572, 219, 102] 1.514050 \n3621 [225, 400, 593, 572, 219, 217, 239] 1.513973 \n3622 [308, 225, 400, 593, 219, 239] 1.513806 \n3623 [308, 225, 219, 116] 1.513632 \n3624 [308, 219, 217, 116] 1.513303 \n3625 [308, 225, 572, 219, 167] 1.512669 \n3626 [225, 572, 219, 102] 1.512423 \n3627 [225, 572, 219, 239, 136, 167] 1.512098 \n3628 [225, 400, 572, 239, 167] 1.511956 \n3629 [308, 225, 572, 219, 217, 239, 116] 1.511636 \n3630 [308, 217, 239, 116] 1.511407 \n3631 [225, 400, 593, 572, 239] 1.510904 \n3632 [400, 572, 219, 217, 239, 116] 1.510728 \n3633 [308, 593, 219, 239, 102] 1.510436 \n3634 [400, 593, 219, 239, 167] 1.510102 \n3635 [225, 219, 239, 116, 136] 1.508943 \n3636 [308, 225, 572, 239, 102] 1.508227 \n3637 [225, 400, 572] 1.508175 \n3638 [308, 225, 219, 217, 239, 136] 1.507748 \n3639 [225, 593, 572] 1.507266 \n3640 [400, 593, 572, 219] 1.507189 \n3641 [400, 219, 217, 239, 136] 1.507039 \n3642 [593, 219, 217, 239, 102] 1.506237 \n3643 [308, 219, 239, 116, 167] 1.506118 \n3644 [593, 219, 136] 1.505917 \n3645 [308, 593, 572, 219, 239, 116] 1.505208 \n3646 [400, 219, 167] 1.505170 \n3647 [308, 400, 572] 1.505096 \n3648 [308, 572, 217, 239, 167] 1.504992 \n3649 [225, 400, 572, 219, 239, 136] 1.504746 \n3650 [225, 400, 572, 219, 217] 1.503983 \n3651 [308, 400, 219, 239, 116] 1.503918 \n3652 [225, 219, 217, 136] 1.503448 \n3653 [102, 116, 136, 167] 1.503368 \n3654 [219, 217, 239, 116, 167] 1.503327 \n3655 [225, 593, 572, 219, 239, 102] 1.503326 \n3656 [308, 225, 572, 239, 136] 1.502331 \n3657 [308, 400, 219, 217] 1.502295 \n3658 [225, 572, 219, 217, 167] 1.502259 \n3659 [308, 593, 219, 239, 136] 1.501335 \n3660 [217, 102] 1.500246 \n3661 [308, 572, 219, 217, 239, 102] 1.500241 \n3662 [593, 572, 219, 217, 239, 116] 1.500071 \n3663 [308, 225, 400, 219] 1.499800 \n3664 [225, 572, 217, 239, 102] 1.499327 \n3665 [308, 225, 572, 217] 1.498324 \n3666 [308, 400, 572, 219, 239, 167] 1.497747 \n3667 [308, 572, 136] 1.497511 \n3668 [225, 593, 219, 217, 239, 167] 1.496853 \n3669 [593, 572, 219, 167] 1.496719 \n3670 [225, 239, 136, 167] 1.496340 \n3671 [225, 400, 219, 239, 102] 1.496203 \n3672 [225, 219, 239, 102, 167] 1.496148 \n3673 [225, 400, 593, 219, 217, 239] 1.495916 \n3674 [308, 593, 572, 217, 239] 1.494450 \n3675 [308, 225, 572, 219, 217, 239, 167] 1.494402 \n3676 [400, 217] 1.494315 \n3677 [225, 572, 219, 239, 116, 167] 1.494234 \n3678 [308, 593, 572, 219, 217] 1.494160 \n3679 [308, 225, 219, 217, 239, 116] 1.493968 \n3680 [308, 400, 572, 217, 239] 1.493373 \n3681 [225, 239, 102, 167] 1.493249 \n3682 [572, 219, 217, 136] 1.493239 \n3683 [225, 400, 593, 239] 1.492119 \n3684 [400, 219, 217, 239, 116] 1.491843 \n3685 [593, 219, 217, 239, 136] 1.491560 \n3686 [225, 219, 217, 116] 1.491243 \n3687 [225, 593, 572, 219, 239, 136] 1.491185 \n3688 [308, 225, 400, 572, 219, 217, 239] 1.490629 \n3689 [400, 572, 219, 217, 239, 167] 1.490535 \n3690 [225, 572, 167] 1.490350 \n3691 [308, 225, 572, 239, 116] 1.490213 \n3692 [308, 572, 116] 1.490053 \n3693 [225, 400, 572, 219, 239, 116] 1.489730 \n3694 [225, 593, 239, 167] 1.489500 \n3695 [225, 400, 239, 167] 1.488982 \n3696 [308, 572, 219, 136] 1.488314 \n3697 [593, 219, 116] 1.488078 \n3698 [225, 400] 1.487270 \n3699 [308, 572, 219, 217, 239, 136] 1.487147 \n3700 [308, 225, 593, 572, 219] 1.487129 \n3701 [225, 572, 217, 239, 136] 1.486612 \n3702 [308, 219, 217, 167] 1.484509 \n3703 [572, 219, 239, 102, 116] 1.483722 \n3704 [308, 593, 219, 239, 116] 1.483232 \n3705 [308, 400, 593, 572, 219, 239] 1.483163 \n3706 [225, 400, 219, 239, 136] 1.483137 \n3707 [308, 593, 572, 219, 239, 167] 1.482001 \n3708 [308, 225, 219, 167] 1.480440 \n3709 [225, 219, 239, 136, 167] 1.479955 \n3710 [219, 217, 102] 1.478911 \n3711 [308, 400, 219, 239, 167] 1.478606 \n3712 [225, 400, 219, 217] 1.478583 \n3713 [308, 217, 239, 167] 1.478345 \n3714 [593, 572, 219, 217, 239, 167] 1.477911 \n3715 [308, 225, 239, 102] 1.477257 \n3716 [400, 593, 219] 1.476457 \n3717 [225, 593] 1.476378 \n3718 [225, 572, 217, 239, 116] 1.476141 \n3719 [593, 217] 1.475654 \n3720 [225, 572, 219, 136] 1.475632 \n3721 [308, 225, 593, 572, 219, 217, 239] 1.475614 \n3722 [308, 225, 572, 219, 239, 102] 1.475347 \n3723 [308, 219, 217, 239, 102] 1.475040 \n3724 [308, 225, 400, 219, 217, 239] 1.474545 \n3725 [308, 400, 217, 239] 1.474051 \n3726 [308, 400] 1.473833 \n3727 [308, 225, 219, 217, 239, 167] 1.473233 \n3728 [400, 593, 572, 219, 217, 239] 1.473046 \n3729 [225, 593, 572, 219, 239, 116] 1.472944 \n3730 [593, 219, 217, 239, 116] 1.472938 \n3731 [308, 225, 239, 136] 1.472813 \n3732 [225, 593, 219, 239, 102] 1.472629 \n3733 [225, 400, 219, 239, 116] 1.471483 \n3734 [225, 593, 572, 219, 217] 1.470929 \n3735 [308, 225, 239, 116] 1.470743 \n3736 [572, 219, 239, 116, 136] 1.470161 \n3737 [308, 593, 572] 1.470025 \n3738 [308, 593, 217, 239] 1.469893 \n3739 [219, 239, 102, 136] 1.468945 \n3740 [225, 219, 239, 116, 167] 1.468678 \n3741 [308, 219, 102] 1.468474 \n3742 [308, 572, 219, 217, 239, 116] 1.467999 \n3743 [308, 225, 400, 572, 239] 1.467952 \n3744 [225, 219, 102] 1.467748 \n3745 [225, 400, 572, 219, 239, 167] 1.467694 \n3746 [593, 572, 239, 136] 1.467519 \n3747 [400, 219, 217, 239, 167] 1.467105 \n3748 [572, 219, 217, 116] 1.466572 \n3749 [308, 572, 219, 116] 1.464283 \n3750 [308, 400, 593, 219, 239] 1.463906 \n3751 [308, 225, 572, 219, 239, 136] 1.463280 \n3752 [308, 225, 572, 239, 167] 1.462248 \n3753 [400, 572, 239, 102] 1.461571 \n3754 [308, 219, 217, 239, 136] 1.460764 \n3755 [308, 225, 593, 572, 239] 1.460547 \n3756 [225, 219, 217, 167] 1.459829 \n3757 [225, 593, 219, 239, 136] 1.459630 \n3758 [308, 225, 217] 1.459132 \n3759 [400, 572, 239, 136] 1.459032 \n3760 [400, 572, 219, 239, 102] 1.458373 \n3761 [572, 219, 239, 102, 167] 1.458056 \n3762 [308, 400, 572, 219] 1.457659 \n3763 [225, 572, 219, 217, 239, 102] 1.457541 \n3764 [308, 593, 219, 217] 1.457478 \n3765 [225, 217, 239, 102] 1.457344 \n3766 [593, 572, 239, 102] 1.456249 \n3767 [225, 572, 219, 116] 1.455633 \n3768 [308, 225, 593, 219] 1.454724 \n3769 [308, 593, 219, 239, 167] 1.454419 \n3770 [593, 572, 239, 116] 1.453944 \n3771 [225, 400, 593, 572, 219, 239] 1.453893 \n3772 [308, 225, 593, 219, 217, 239] 1.453823 \n3773 [225, 572, 217, 239, 167] 1.450741 \n3774 [308, 225, 219, 239, 102] 1.450206 \n3775 [225, 400, 572, 217, 239] 1.450031 \n3776 [400, 593, 219, 217, 239] 1.449413 \n3777 [308, 400, 572, 219, 217, 239] 1.449227 \n3778 [400, 572, 219, 217] 1.449093 \n3779 [308, 225, 400, 239] 1.448632 \n3780 [308, 572, 219, 217, 239, 167] 1.448536 \n3781 [400, 572, 239, 116] 1.448408 \n3782 [225, 593, 572, 219, 239, 167] 1.448314 \n3783 [225, 217, 239, 116] 1.447771 \n3784 [308, 225, 572, 219, 239, 116] 1.447237 \n3785 [400, 572, 219, 239, 136] 1.446623 \n3786 [308, 572, 167] 1.446335 \n3787 [225, 593, 572, 217, 239] 1.446242 \n3788 [225, 593, 219, 239, 116] 1.446167 \n3789 [217, 167] 1.446102 \n3790 [219, 239, 102, 116] 1.445051 \n3791 [593, 219, 217, 239, 167] 1.444875 \n3792 [225, 400, 219, 239, 167] 1.444470 \n3793 [308, 219, 217, 239, 116] 1.444376 \n3794 [225, 102] 1.444307 \n3795 [225, 217, 239, 136] 1.444261 \n3796 [572, 219, 239, 136, 167] 1.444250 \n3797 [225, 572, 219, 217, 239, 136] 1.440981 \n3798 [593, 572, 219, 239, 102] 1.439500 \n3799 [225, 400, 572, 219] 1.439417 \n3800 [572, 239, 102, 136] 1.438465 \n3801 [308, 219, 136] 1.438248 \n3802 [572, 219, 217, 167] 1.438072 \n3803 [308, 225, 572, 219, 217] 1.437320 \n3804 [308, 225, 219, 239, 136] 1.437154 \n3805 [572, 239, 116, 136] 1.437055 \n3806 [308, 225, 593, 239] 1.435216 \n3807 [217, 136] 1.434696 \n3808 [308, 572, 219, 167] 1.433858 \n3809 [308, 225, 400, 572, 219, 239] 1.433666 \n3810 [308, 225, 239, 167] 1.433025 \n3811 [593, 219, 167] 1.433022 \n3812 [308, 593, 572, 219, 217, 239] 1.431059 \n3813 [219, 217, 136] 1.430961 \n3814 [219, 239, 116, 136] 1.430763 \n3815 [225, 400, 593, 219, 239] 1.430760 \n3816 [400, 593, 572, 239] 1.429313 \n3817 [400, 572, 219, 239, 116] 1.429217 \n3818 [308, 400, 219] 1.428976 \n3819 [225, 593, 219, 217] 1.428621 \n3820 [593, 572, 219, 239, 136] 1.428477 \n3821 [308, 400, 219, 217, 239] 1.428291 \n3822 [400, 219, 239, 102] 1.427569 \n3823 [572, 239, 102, 116] 1.427056 \n3824 [308, 225, 572, 219, 239, 167] 1.425872 \n3825 [225, 572, 219, 217, 239, 116] 1.425010 \n3826 [225, 219, 217, 239, 102] 1.424668 \n3827 [308, 225, 219, 239, 116] 1.424360 \n3828 [225, 400, 217, 239] 1.423555 \n3829 [572, 219, 102] 1.422657 \n3830 [572, 219, 239, 116, 167] 1.422171 \n3831 [308, 219, 116] 1.422102 \n3832 [225, 219, 136] 1.422003 \n3833 [225, 572, 219, 167] 1.421586 \n3834 [225, 167] 1.421551 \n3835 [308, 219, 217, 239, 167] 1.420457 \n3836 [102, 116, 167] 1.419267 \n3837 [219, 217, 116] 1.415349 \n3838 [225, 219, 116] 1.415312 \n3839 [593, 239, 116] 1.415080 \n3840 [572, 217, 239, 102] 1.415065 \n3841 [225, 593, 219, 239, 167] 1.414995 \n3842 [400, 219, 239, 136] 1.414950 \n3843 [400, 239, 116] 1.414700 \n3844 [308, 593, 572, 219] 1.414263 \n3845 [400, 572, 239, 167] 1.413660 \n3846 [400, 219, 217] 1.413364 \n3847 [308, 225, 400, 219, 239] 1.413322 \n3848 [225, 400, 572, 219, 217, 239] 1.412867 \n3849 [308, 572, 219, 239, 102] 1.412534 \n3850 [225, 593, 217, 239] 1.412475 \n3851 [225, 217, 239, 167] 1.412256 \n3852 [308, 225, 593, 572, 219, 239] 1.412101 \n3853 [308, 116] 1.411406 \n3854 [400, 239, 136] 1.411099 \n3855 [400, 239, 102] 1.410651 \n3856 [593, 572, 239, 167] 1.410415 \n3857 [219, 239, 102, 167] 1.409657 \n3858 [572, 239, 116, 167] 1.408650 \n3859 [225, 400, 219] 1.408384 \n3860 [308, 225, 572, 217, 239] 1.408163 \n3861 [593, 572, 219, 217] 1.407299 \n3862 [572, 239, 136, 167] 1.407068 \n3863 [572, 217, 239, 136] 1.406320 \n3864 [225, 219, 217, 239, 136] 1.406200 \n3865 [593, 572, 219, 239, 116] 1.406163 \n3866 [308, 572, 239, 102] 1.405249 \n3867 [225, 572, 219, 217, 239, 167] 1.404802 \n3868 [308, 572, 217] 1.404083 \n3869 [400, 572, 219, 239, 167] 1.403907 \n3870 [308, 572, 239, 136] 1.403643 \n3871 [308, 593, 219, 217, 239] 1.402845 \n3872 [572, 219, 217, 239, 102] 1.402108 \n3873 [308, 225, 219, 217] 1.401936 \n3874 [308, 593] 1.401907 \n3875 [308, 102] 1.401624 \n3876 [400, 219, 239, 116] 1.401624 \n3877 [308, 572, 219, 239, 136] 1.400824 \n3878 [593, 239, 136] 1.398582 \n3879 [308, 225, 219, 239, 167] 1.398085 \n3880 [572, 239, 102, 167] 1.397739 \n3881 [116, 136, 167] 1.396639 \n3882 [225, 593, 572, 219] 1.395155 \n3883 [219, 239, 136, 167] 1.394967 \n3884 [400, 593, 572, 219, 239] 1.394747 \n3885 [225, 219, 217, 239, 116] 1.394408 \n3886 [593, 219, 239, 102] 1.394112 \n3887 [400, 593, 239] 1.393917 \n3888 [572, 217, 239, 116] 1.393516 \n3889 [225, 136] 1.392220 \n3890 [308, 572, 239, 116] 1.390316 \n3891 [225, 593, 572, 219, 217, 239] 1.389369 \n3892 [308, 400, 572, 239] 1.388975 \n3893 [225, 400, 219, 217, 239] 1.386948 \n3894 [308, 225, 572] 1.385070 \n3895 [572, 219, 217, 239, 136] 1.384873 \n3896 [308, 225, 593, 219, 239] 1.384452 \n3897 [593, 219, 239, 136] 1.382719 \n3898 [308, 572, 219, 239, 116] 1.382041 \n3899 [219, 239, 116, 167] 1.381607 \n3900 [308, 219, 167] 1.381500 \n3901 [308, 136] 1.379457 \n3902 [572, 219, 136] 1.379126 \n3903 [308, 225, 217, 239] 1.377155 \n3904 [593, 572, 219, 239, 167] 1.377074 \n3905 [308, 400, 572, 219, 239] 1.376758 \n3906 [400, 572, 217, 239] 1.376349 \n3907 [308, 225, 572, 219, 217, 239] 1.376327 \n3908 [308, 219, 239, 102] 1.375993 \n3909 [219, 217, 167] 1.375580 \n3910 [593, 239, 102] 1.374495 \n3911 [225, 572, 217] 1.372381 \n3912 [308, 593, 572, 239] 1.372066 \n3913 [593, 572, 217, 239] 1.371845 \n3914 [308, 572, 219, 217] 1.371617 \n3915 [400, 219, 239, 167] 1.369862 \n3916 [225, 219, 217, 239, 167] 1.369226 \n3917 [400, 572] 1.367319 \n3918 [225, 219, 167] 1.367174 \n3919 [593, 219, 239, 116] 1.366407 \n3920 [400, 239, 167] 1.366362 \n3921 [572, 219, 217, 239, 116] 1.365207 \n3922 [308, 593, 219] 1.365164 \n3923 [225, 572, 219, 239, 102] 1.363804 \n3924 [308, 219, 239, 136] 1.363434 \n3925 [572, 217, 239, 167] 1.362554 \n3926 [400, 593, 219, 239] 1.362312 \n3927 [308, 225, 572, 219] 1.361895 \n3928 [400, 572, 219, 217, 239] 1.357931 \n3929 [219, 217, 239, 102] 1.357794 \n3930 [308, 572, 219, 239, 167] 1.357478 \n3931 [308, 572, 239, 167] 1.356857 \n3932 [400, 572, 219] 1.355849 \n3933 [308, 400, 239] 1.355763 \n3934 [225, 593, 219, 217, 239] 1.354396 \n3935 [572, 219, 116] 1.352621 \n3936 [308, 400, 219, 239] 1.348708 \n3937 [308, 219, 239, 116] 1.348562 \n3938 [308, 593, 572, 219, 239] 1.348372 \n3939 [225, 572, 219, 239, 136] 1.348111 \n3940 [217, 239, 116] 1.348020 \n3941 [308, 239, 116] 1.347995 \n3942 [593, 219, 217] 1.347250 \n3943 [308, 239, 136] 1.347097 \n3944 [308, 225, 219, 217, 239] 1.346846 \n3945 [593, 239, 167] 1.345906 \n3946 [217, 239, 102] 1.345428 \n3947 [308, 239, 102] 1.345027 \n3948 [219, 102] 1.344321 \n3949 [308, 167] 1.342292 \n3950 [593, 572] 1.341895 \n3951 [572, 219, 217, 239, 167] 1.341711 \n3952 [225, 593, 219] 1.341477 \n3953 [217, 239, 136] 1.339042 \n3954 [219, 217, 239, 136] 1.338408 \n3955 [225, 400, 572, 239] 1.337085 \n3956 [225, 400, 572, 219, 239] 1.336019 \n3957 [400, 217, 239] 1.335754 \n3958 [308, 217] 1.334933 \n3959 [225, 572, 219, 239, 116] 1.333353 \n3960 [225, 572, 219, 217] 1.332536 \n3961 [308, 572, 217, 239] 1.330104 \n3962 [225, 572, 239, 102] 1.330085 \n3963 [239, 116, 136] 1.329372 \n3964 [593, 572, 219, 217, 239] 1.329183 \n3965 [593, 219, 239, 167] 1.328305 \n3966 [239, 116, 167] 1.328076 \n3967 [308, 593, 239] 1.327795 \n3968 [308, 225] 1.326018 \n3969 [219, 217, 239, 116] 1.323865 \n3970 [400, 219, 217, 239] 1.323737 \n3971 [225, 572, 239, 136] 1.323430 \n3972 [116, 167] 1.323295 \n3973 [225, 572, 239, 116] 1.322502 \n3974 [593, 217, 239] 1.322279 \n3975 [308, 219, 217] 1.322177 \n3976 [308, 572, 219, 217, 239] 1.317927 \n3977 [308, 219, 239, 167] 1.317594 \n3978 [225, 219, 239, 102] 1.317471 \n3979 [308, 225, 219] 1.316771 \n3980 [225, 593, 572, 239] 1.313573 \n3981 [102, 116, 136] 1.312975 \n3982 [308, 593, 219, 239] 1.310192 \n3983 [572, 219, 167] 1.309107 \n3984 [225, 572, 219, 239, 167] 1.307230 \n3985 [239, 102, 116] 1.307101 \n3986 [400, 219] 1.306500 \n3987 [102, 136, 167] 1.303011 \n3988 [225, 400, 219, 239] 1.301825 \n3989 [225, 593, 572, 219, 239] 1.301182 \n3990 [217, 239, 167] 1.300997 \n3991 [308, 239, 167] 1.300712 \n3992 [225, 219, 239, 136] 1.299985 \n3993 [308, 225, 572, 219, 239] 1.296107 \n3994 [225, 217] 1.294878 \n3995 [225, 400, 239] 1.293949 \n3996 [219, 217, 239, 167] 1.293595 \n3997 [593, 572, 219] 1.292522 \n3998 [225, 219, 239, 116] 1.291312 \n3999 [308, 225, 572, 239] 1.290446 \n4000 [219, 136] 1.287069 \n4001 [225, 572, 239, 167] 1.285988 \n4002 [572, 116] 1.284576 \n4003 [308, 217, 239] 1.283784 \n4004 [593, 219, 217, 239] 1.282947 \n4005 [219, 116] 1.280944 \n4006 [308, 219, 217, 239] 1.279298 \n4007 [239, 102, 136] 1.278831 \n4008 [239, 136, 167] 1.278779 \n4009 [225, 219, 217] 1.273669 \n4010 [572, 219, 239, 102] 1.270827 \n4011 [225, 239, 116] 1.264636 \n4012 [308, 572, 219] 1.263453 \n4013 [225, 572, 219, 217, 239] 1.262644 \n4014 [239, 102, 167] 1.259024 \n4015 [572, 102] 1.257862 \n4016 [225, 219, 239, 167] 1.257693 \n4017 [308, 225, 219, 239] 1.257549 \n4018 [400, 572, 219, 239] 1.257338 \n4019 [225, 593, 239] 1.256648 \n4020 [572, 219, 239, 136] 1.255254 \n4021 [225, 593, 219, 239] 1.254484 \n4022 [225, 572, 217, 239] 1.253987 \n4023 [225, 239, 102] 1.244785 \n4024 [308, 225, 239] 1.241564 \n4025 [225, 239, 136] 1.240733 \n4026 [572, 219, 217] 1.239719 \n4027 [572, 219, 239, 116] 1.237578 \n4028 [572, 217] 1.225138 \n4029 [225, 572, 219] 1.222448 \n4030 [572, 136] 1.221922 \n4031 [225, 219, 217, 239] 1.214239 \n4032 [219, 167] 1.214021 \n4033 [400, 572, 239] 1.213903 \n4034 [308, 572, 219, 239] 1.212752 \n4035 [225, 239, 167] 1.210190 \n4036 [593, 572, 219, 239] 1.210073 \n4037 [400, 219, 239] 1.208980 \n4038 [308, 572] 1.206602 \n4039 [572, 219, 239, 167] 1.206341 \n4040 [572, 167] 1.206226 \n4041 [593, 219] 1.205971 \n4042 [219, 239, 102] 1.200929 \n4043 [308, 219] 1.193416 \n4044 [102, 116] 1.190801 \n4045 [225, 217, 239] 1.189271 \n4046 [219, 239, 136] 1.183604 \n4047 [572, 219, 217, 239] 1.179769 \n4048 [225, 572] 1.179115 \n4049 [219, 239, 116] 1.173958 \n4050 [593, 572, 239] 1.166241 \n4051 [308, 572, 239] 1.159678 \n4052 [116, 136] 1.159043 \n4053 [308, 219, 239] 1.158597 \n4054 [219, 217] 1.152890 \n4055 [225, 572, 219, 239] 1.147189 \n4056 [593, 219, 239] 1.143013 \n4057 [225, 219] 1.141725 \n4058 [572, 239, 116] 1.140662 \n4059 [400, 239] 1.138507 \n4060 [572, 239, 136] 1.136570 \n4061 [572, 239, 102] 1.136379 \n4062 [102, 167] 1.134207 \n4063 [219, 239, 167] 1.132073 \n4064 [572, 217, 239] 1.126306 \n4065 [219, 217, 239] 1.113772 \n4066 [136, 167] 1.100145 \n4067 [572, 239, 167] 1.093898 \n4068 [225, 219, 239] 1.079517 \n4069 [308, 239] 1.075236 \n4070 [572, 219] 1.068853 \n4071 [102, 136] 1.060123 \n4072 [593, 239] 1.059879 \n4073 [225, 572, 239] 1.058020 \n4074 [217, 239] 1.022142 \n4075 [572, 219, 239] 1.021043 \n4076 [239, 116] 1.010654 \n4077 [239, 136] 0.965136 \n4078 [239, 102] 0.959413 \n4079 [225, 239] 0.941099 \n4080 [239, 167] 0.934426 \n4081 [219, 239] 0.919083 \n4082 [572, 239] 0.813601 \n\n LongRules ShortRules \nCombi Index \n0 4 3 \n1 4 3 \n2 4 4 \n3 4 3 \n4 4 2 \n5 4 4 \n6 4 4 \n7 4 5 \n8 4 2 \n9 4 3 \n10 4 3 \n11 4 2 \n12 4 3 \n13 4 4 \n14 4 4 \n15 4 4 \n16 4 3 \n17 4 3 \n18 3 3 \n19 3 3 \n20 3 3 \n21 4 4 \n22 4 4 \n23 4 5 \n24 4 5 \n25 4 3 \n26 4 3 \n27 4 2 \n28 3 3 \n29 4 5 \n30 3 2 \n31 3 4 \n32 3 4 \n33 3 3 \n34 3 3 \n35 3 3 \n36 3 3 \n37 3 3 \n38 3 2 \n39 3 2 \n40 3 4 \n41 3 3 \n42 3 4 \n43 4 6 \n44 3 2 \n45 3 4 \n46 3 4 \n47 4 3 \n48 4 1 \n49 3 4 \n50 4 4 \n51 3 4 \n52 4 3 \n53 3 3 \n54 3 3 \n55 3 5 \n56 4 2 \n57 3 5 \n58 3 4 \n59 3 4 \n60 4 4 \n61 4 4 \n62 4 5 \n63 4 4 \n64 3 4 \n65 4 4 \n66 3 4 \n67 4 3 \n68 3 3 \n69 4 4 \n70 4 3 \n71 4 2 \n72 4 4 \n73 4 3 \n74 4 3 \n75 4 5 \n76 3 5 \n77 3 3 \n78 3 4 \n79 3 4 \n80 4 3 \n81 3 5 \n82 4 2 \n83 3 4 \n84 3 3 \n85 3 2 \n86 3 4 \n87 4 3 \n88 3 2 \n89 4 2 \n90 3 3 \n91 3 4 \n92 3 4 \n93 4 5 \n94 3 3 \n95 3 5 \n96 3 3 \n97 4 5 \n98 4 4 \n99 3 5 \n100 3 3 \n101 4 4 \n102 3 2 \n103 4 4 \n104 3 2 \n105 3 4 \n106 3 3 \n107 3 5 \n108 3 5 \n109 3 5 \n110 3 3 \n111 3 3 \n112 4 4 \n113 4 3 \n114 4 2 \n115 3 2 \n116 3 4 \n117 3 3 \n118 3 4 \n119 3 4 \n120 3 2 \n121 4 3 \n122 3 4 \n123 3 3 \n124 3 5 \n125 4 4 \n126 4 5 \n127 3 4 \n128 3 3 \n129 3 3 \n130 3 6 \n131 4 4 \n132 3 3 \n133 3 3 \n134 3 3 \n135 4 5 \n136 3 4 \n137 3 2 \n138 4 2 \n139 4 5 \n140 3 4 \n141 4 3 \n142 3 2 \n143 3 3 \n144 3 3 \n145 3 4 \n146 3 6 \n147 4 6 \n148 3 5 \n149 3 3 \n150 4 3 \n151 3 3 \n152 3 3 \n153 4 4 \n154 4 5 \n155 3 4 \n156 2 3 \n157 3 5 \n158 4 5 \n159 4 2 \n160 3 5 \n161 3 3 \n162 4 4 \n163 3 3 \n164 3 3 \n165 3 5 \n166 2 3 \n167 4 4 \n168 4 6 \n169 3 5 \n170 3 4 \n171 3 2 \n172 4 5 \n173 3 3 \n174 4 6 \n175 3 3 \n176 3 5 \n177 3 4 \n178 4 6 \n179 2 4 \n180 4 3 \n181 4 4 \n182 4 3 \n183 4 4 \n184 3 4 \n185 3 6 \n186 3 2 \n187 4 5 \n188 4 3 \n189 3 2 \n190 4 3 \n191 2 3 \n192 3 2 \n193 2 3 \n194 3 4 \n195 3 4 \n196 4 3 \n197 4 2 \n198 2 4 \n199 3 6 \n200 3 2 \n201 4 2 \n202 3 3 \n203 4 3 \n204 3 3 \n205 4 4 \n206 2 3 \n207 3 4 \n208 4 4 \n209 3 5 \n210 3 3 \n211 2 2 \n212 4 2 \n213 3 2 \n214 3 4 \n215 4 5 \n216 3 5 \n217 2 3 \n218 4 5 \n219 4 7 \n220 4 3 \n221 2 4 \n222 4 3 \n223 2 3 \n224 4 5 \n225 4 4 \n226 4 5 \n227 3 4 \n228 3 4 \n229 4 5 \n230 3 2 \n231 3 3 \n232 4 6 \n233 3 4 \n234 2 2 \n235 2 2 \n236 3 4 \n237 4 5 \n238 3 3 \n239 3 4 \n240 4 4 \n241 2 3 \n242 3 2 \n243 3 2 \n244 3 4 \n245 2 4 \n246 4 2 \n247 3 3 \n248 4 4 \n249 3 3 \n250 2 5 \n251 3 1 \n252 4 5 \n253 3 4 \n254 4 4 \n255 4 6 \n256 2 3 \n257 2 4 \n258 3 3 \n259 4 4 \n260 3 1 \n261 3 2 \n262 4 6 \n263 4 2 \n264 4 6 \n265 3 4 \n266 3 5 \n267 3 4 \n268 3 1 \n269 4 6 \n270 3 4 \n271 4 4 \n272 2 3 \n273 3 3 \n274 4 4 \n275 3 5 \n276 3 5 \n277 3 3 \n278 2 3 \n279 3 4 \n280 2 3 \n281 4 4 \n282 2 4 \n283 2 4 \n284 3 3 \n285 3 4 \n286 4 4 \n287 2 4 \n288 4 5 \n289 2 4 \n290 2 4 \n291 3 1 \n292 4 7 \n293 3 2 \n294 4 3 \n295 3 3 \n296 3 2 \n297 3 4 \n298 2 3 \n299 3 4 \n300 3 2 \n301 2 3 \n302 3 3 \n303 3 4 \n304 2 3 \n305 3 3 \n306 2 4 \n307 3 3 \n308 3 3 \n309 2 2 \n310 3 4 \n311 3 5 \n312 3 3 \n313 4 5 \n314 4 3 \n315 2 5 \n316 3 4 \n317 4 5 \n318 4 5 \n319 3 3 \n320 3 4 \n321 3 4 \n322 2 4 \n323 3 3 \n324 3 3 \n325 2 2 \n326 2 2 \n327 2 4 \n328 4 3 \n329 4 4 \n330 3 3 \n331 2 4 \n332 3 3 \n333 4 3 \n334 2 4 \n335 3 2 \n336 3 2 \n337 3 5 \n338 4 4 \n339 4 4 \n340 3 4 \n341 2 4 \n342 3 3 \n343 4 5 \n344 4 5 \n345 3 4 \n346 4 2 \n347 3 3 \n348 2 5 \n349 3 2 \n350 4 3 \n351 4 4 \n352 3 2 \n353 4 2 \n354 2 5 \n355 4 3 \n356 4 4 \n357 2 3 \n358 3 4 \n359 2 5 \n360 3 4 \n361 2 4 \n362 3 4 \n363 2 3 \n364 3 3 \n365 2 4 \n366 4 4 \n367 4 5 \n368 4 3 \n369 3 5 \n370 4 4 \n371 3 2 \n372 3 4 \n373 2 3 \n374 2 5 \n375 3 5 \n376 3 5 \n377 4 5 \n378 4 5 \n379 3 4 \n380 4 4 \n381 3 2 \n382 4 5 \n383 4 6 \n384 4 2 \n385 3 3 \n386 4 6 \n387 4 3 \n388 4 2 \n389 4 5 \n390 3 2 \n391 2 5 \n392 3 5 \n393 3 2 \n394 3 5 \n395 2 4 \n396 2 5 \n397 2 4 \n398 3 4 \n399 2 3 \n400 3 4 \n401 3 5 \n402 3 5 \n403 4 4 \n404 2 6 \n405 2 4 \n406 4 3 \n407 3 4 \n408 4 4 \n409 4 3 \n410 3 4 \n411 3 5 \n412 3 4 \n413 3 3 \n414 3 2 \n415 2 4 \n416 2 5 \n417 4 6 \n418 2 4 \n419 3 5 \n420 2 4 \n421 2 4 \n422 3 5 \n423 3 4 \n424 4 3 \n425 3 6 \n426 3 3 \n427 3 2 \n428 3 6 \n429 4 5 \n430 2 3 \n431 3 5 \n432 3 3 \n433 2 4 \n434 4 3 \n435 4 4 \n436 3 3 \n437 3 4 \n438 3 4 \n439 3 5 \n440 2 5 \n441 3 2 \n442 3 3 \n443 4 4 \n444 2 5 \n445 3 5 \n446 3 6 \n447 3 6 \n448 3 5 \n449 4 4 \n450 3 6 \n451 2 5 \n452 3 5 \n453 4 3 \n454 4 2 \n455 4 4 \n456 2 4 \n457 2 3 \n458 2 5 \n459 3 3 \n460 3 3 \n461 3 5 \n462 4 3 \n463 3 6 \n464 2 4 \n465 4 1 \n466 2 3 \n467 3 3 \n468 2 5 \n469 2 3 \n470 2 6 \n471 3 3 \n472 3 4 \n473 4 5 \n474 3 3 \n475 2 3 \n476 4 1 \n477 3 3 \n478 3 4 \n479 3 5 \n480 3 2 \n481 3 4 \n482 3 6 \n483 3 5 \n484 3 4 \n485 3 6 \n486 2 5 \n487 3 7 \n488 2 4 \n489 3 5 \n490 2 4 \n491 4 5 \n492 2 5 \n493 2 3 \n494 2 3 \n495 2 4 \n496 2 5 \n497 4 2 \n498 3 5 \n499 3 5 \n500 3 5 \n501 2 5 \n502 3 4 \n503 2 3 \n504 2 2 \n505 2 3 \n506 3 5 \n507 3 3 \n508 3 2 \n509 4 4 \n510 2 6 \n511 3 4 \n512 3 4 \n513 3 4 \n514 4 2 \n515 3 4 \n516 3 5 \n517 2 3 \n518 2 6 \n519 3 3 \n520 3 4 \n521 2 4 \n522 3 2 \n523 3 2 \n524 3 7 \n525 4 3 \n526 3 3 \n527 3 4 \n528 3 6 \n529 2 4 \n530 3 5 \n531 3 4 \n532 3 3 \n533 2 5 \n534 3 6 \n535 4 3 \n536 3 3 \n537 3 5 \n538 2 4 \n539 2 3 \n540 3 6 \n541 4 4 \n542 3 5 \n543 3 4 \n544 3 6 \n545 2 4 \n546 3 6 \n547 3 3 \n548 2 5 \n549 4 4 \n550 2 3 \n551 2 4 \n552 3 6 \n553 3 4 \n554 3 6 \n555 3 5 \n556 4 5 \n557 3 5 \n558 3 4 \n559 4 6 \n560 4 4 \n561 2 3 \n562 2 2 \n563 3 3 \n564 3 6 \n565 3 4 \n566 3 5 \n567 3 5 \n568 2 5 \n569 4 6 \n570 3 4 \n571 3 2 \n572 2 4 \n573 2 6 \n574 3 4 \n575 3 5 \n576 2 3 \n577 2 5 \n578 3 4 \n579 3 3 \n580 2 2 \n581 3 2 \n582 3 2 \n583 3 4 \n584 3 5 \n585 4 3 \n586 4 5 \n587 3 3 \n588 3 3 \n589 3 7 \n590 2 3 \n591 2 3 \n592 2 2 \n593 3 4 \n594 3 5 \n595 3 3 \n596 3 4 \n597 2 3 \n598 3 4 \n599 3 6 \n600 3 6 \n601 3 3 \n602 3 6 \n603 3 5 \n604 3 6 \n605 3 5 \n606 4 6 \n607 3 6 \n608 3 5 \n609 2 4 \n610 3 2 \n611 3 6 \n612 3 2 \n613 3 4 \n614 3 3 \n615 2 5 \n616 3 4 \n617 2 4 \n618 3 5 \n619 3 5 \n620 2 4 \n621 3 5 \n622 3 6 \n623 3 3 \n624 3 3 \n625 3 3 \n626 3 4 \n627 3 4 \n628 3 5 \n629 3 5 \n630 3 7 \n631 4 7 \n632 4 5 \n633 3 5 \n634 3 5 \n635 3 5 \n636 3 2 \n637 2 3 \n638 3 3 \n639 2 4 \n640 3 7 \n641 4 3 \n642 2 3 \n643 3 5 \n644 4 2 \n645 2 4 \n646 3 7 \n647 2 4 \n648 3 4 \n649 4 7 \n650 2 2 \n651 3 4 \n652 2 3 \n653 3 6 \n654 2 3 \n655 3 3 \n656 3 5 \n657 3 3 \n658 3 3 \n659 2 3 \n660 4 5 \n661 3 3 \n662 3 2 \n663 3 2 \n664 3 4 \n665 2 2 \n666 4 7 \n667 4 6 \n668 2 5 \n669 2 3 \n670 2 3 \n671 2 6 \n672 4 6 \n673 3 4 \n674 2 4 \n675 2 4 \n676 4 4 \n677 2 3 \n678 3 2 \n679 3 5 \n680 3 4 \n681 2 2 \n682 2 5 \n683 3 4 \n684 3 4 \n685 3 4 \n686 2 3 \n687 2 3 \n688 2 2 \n689 2 2 \n690 3 4 \n691 3 5 \n692 3 6 \n693 2 2 \n694 3 4 \n695 4 4 \n696 3 3 \n697 3 3 \n698 3 6 \n699 3 2 \n700 3 3 \n701 3 5 \n702 3 4 \n703 3 4 \n704 3 3 \n705 3 4 \n706 3 6 \n707 3 5 \n708 4 8 \n709 2 3 \n710 2 2 \n711 3 6 \n712 3 6 \n713 4 5 \n714 2 4 \n715 3 4 \n716 3 4 \n717 3 4 \n718 3 2 \n719 4 6 \n720 2 2 \n721 3 5 \n722 2 5 \n723 2 3 \n724 2 3 \n725 2 4 \n726 2 2 \n727 2 4 \n728 3 3 \n729 3 4 \n730 3 5 \n731 3 6 \n732 4 7 \n733 3 2 \n734 3 3 \n735 2 4 \n736 2 3 \n737 2 4 \n738 3 2 \n739 2 3 \n740 3 5 \n741 2 3 \n742 2 5 \n743 3 2 \n744 3 5 \n745 3 6 \n746 3 5 \n747 3 4 \n748 2 3 \n749 3 4 \n750 3 5 \n751 3 4 \n752 3 7 \n753 2 4 \n754 3 2 \n755 2 2 \n756 2 3 \n757 2 2 \n758 3 5 \n759 3 5 \n760 2 3 \n761 3 4 \n762 3 5 \n763 2 4 \n764 3 5 \n765 3 5 \n766 2 2 \n767 3 3 \n768 3 6 \n769 2 4 \n770 3 5 \n771 2 3 \n772 3 4 \n773 4 5 \n774 3 2 \n775 3 3 \n776 3 4 \n777 4 5 \n778 3 5 \n779 2 4 \n780 2 3 \n781 2 2 \n782 3 5 \n783 3 4 \n784 3 4 \n785 3 2 \n786 2 2 \n787 3 6 \n788 3 5 \n789 2 3 \n790 3 5 \n791 2 5 \n792 4 1 \n793 2 4 \n794 2 2 \n795 3 6 \n796 3 3 \n797 3 4 \n798 4 6 \n799 3 3 \n800 2 4 \n801 3 5 \n802 3 6 \n803 2 3 \n804 2 4 \n805 2 3 \n806 3 7 \n807 4 6 \n808 2 5 \n809 3 6 \n810 3 2 \n811 3 5 \n812 3 4 \n813 3 5 \n814 3 5 \n815 4 6 \n816 3 5 \n817 3 6 \n818 3 4 \n819 3 4 \n820 2 3 \n821 3 4 \n822 4 4 \n823 3 3 \n824 2 3 \n825 3 2 \n826 2 4 \n827 3 5 \n828 4 3 \n829 3 4 \n830 2 2 \n831 2 5 \n832 3 2 \n833 3 5 \n834 3 5 \n835 2 3 \n836 3 3 \n837 2 4 \n838 2 4 \n839 2 4 \n840 3 4 \n841 3 6 \n842 2 4 \n843 3 4 \n844 2 3 \n845 2 4 \n846 2 3 \n847 2 2 \n848 3 5 \n849 3 5 \n850 3 5 \n851 3 6 \n852 3 4 \n853 3 2 \n854 3 3 \n855 4 4 \n856 3 4 \n857 4 7 \n858 3 5 \n859 3 4 \n860 3 6 \n861 3 3 \n862 3 4 \n863 3 5 \n864 4 4 \n865 3 4 \n866 4 3 \n867 2 2 \n868 2 3 \n869 2 5 \n870 4 3 \n871 3 4 \n872 3 4 \n873 2 4 \n874 2 2 \n875 3 4 \n876 3 4 \n877 4 5 \n878 3 5 \n879 4 5 \n880 3 5 \n881 4 5 \n882 4 5 \n883 3 4 \n884 3 5 \n885 3 4 \n886 4 1 \n887 4 5 \n888 2 3 \n889 3 5 \n890 3 6 \n891 3 4 \n892 2 2 \n893 3 3 \n894 2 4 \n895 2 4 \n896 3 1 \n897 3 4 \n898 3 5 \n899 2 3 \n900 4 4 \n901 3 3 \n902 3 4 \n903 1 3 \n904 3 6 \n905 3 4 \n906 3 5 \n907 2 5 \n908 1 4 \n909 3 5 \n910 3 4 \n911 4 6 \n912 3 4 \n913 2 5 \n914 2 3 \n915 2 4 \n916 2 4 \n917 3 5 \n918 2 3 \n919 3 4 \n920 3 3 \n921 3 3 \n922 3 3 \n923 4 6 \n924 3 3 \n925 3 3 \n926 2 4 \n927 2 4 \n928 1 3 \n929 4 2 \n930 4 5 \n931 3 4 \n932 3 4 \n933 3 4 \n934 3 3 \n935 3 5 \n936 2 3 \n937 2 4 \n938 3 3 \n939 3 3 \n940 4 6 \n941 3 4 \n942 2 3 \n943 3 3 \n944 2 3 \n945 3 4 \n946 4 6 \n947 2 3 \n948 2 4 \n949 3 4 \n950 2 4 \n951 3 4 \n952 2 4 \n953 4 4 \n954 2 2 \n955 3 3 \n956 3 5 \n957 3 4 \n958 4 5 \n959 4 7 \n960 2 3 \n961 2 3 \n962 1 4 \n963 3 2 \n964 3 4 \n965 3 5 \n966 4 1 \n967 3 5 \n968 3 4 \n969 4 3 \n970 2 5 \n971 2 4 \n972 3 3 \n973 3 5 \n974 3 4 \n975 2 5 \n976 1 5 \n977 2 4 \n978 3 5 \n979 3 4 \n980 3 4 \n981 2 4 \n982 2 3 \n983 2 3 \n984 3 3 \n985 4 4 \n986 3 4 \n987 1 3 \n988 2 4 \n989 1 3 \n990 2 2 \n991 3 6 \n992 2 4 \n993 2 2 \n994 3 3 \n995 1 3 \n996 3 6 \n997 2 3 \n998 3 5 \n999 3 3 \n1000 2 6 \n1001 2 5 \n1002 3 2 \n1003 3 4 \n1004 1 4 \n1005 3 5 \n1006 3 3 \n1007 3 5 \n1008 2 4 \n1009 2 5 \n1010 2 2 \n1011 3 3 \n1012 3 5 \n1013 3 4 \n1014 2 3 \n1015 2 5 \n1016 3 3 \n1017 2 4 \n1018 2 3 \n1019 2 1 \n1020 3 3 \n1021 3 5 \n1022 4 5 \n1023 3 3 \n1024 3 6 \n1025 3 4 \n1026 3 6 \n1027 3 5 \n1028 4 6 \n1029 2 4 \n1030 2 5 \n1031 3 4 \n1032 3 3 \n1033 3 5 \n1034 3 4 \n1035 3 5 \n1036 2 3 \n1037 3 4 \n1038 3 4 \n1039 4 4 \n1040 3 5 \n1041 3 3 \n1042 3 4 \n1043 3 3 \n1044 2 4 \n1045 3 2 \n1046 2 3 \n1047 3 5 \n1048 2 3 \n1049 2 3 \n1050 2 5 \n1051 1 4 \n1052 3 3 \n1053 1 4 \n1054 2 6 \n1055 4 5 \n1056 3 2 \n1057 1 3 \n1058 2 5 \n1059 2 4 \n1060 3 5 \n1061 3 4 \n1062 1 4 \n1063 3 2 \n1064 3 3 \n1065 3 5 \n1066 2 2 \n1067 2 6 \n1068 2 7 \n1069 1 5 \n1070 4 2 \n1071 2 3 \n1072 3 4 \n1073 3 4 \n1074 2 3 \n1075 2 2 \n1076 3 4 \n1077 1 5 \n1078 2 6 \n1079 2 1 \n1080 3 4 \n1081 2 5 \n1082 3 4 \n1083 3 4 \n1084 2 4 \n1085 2 4 \n1086 3 5 \n1087 3 6 \n1088 3 3 \n1089 2 2 \n1090 3 2 \n1091 3 3 \n1092 3 3 \n1093 3 5 \n1094 3 4 \n1095 3 2 \n1096 3 4 \n1097 3 5 \n1098 2 6 \n1099 2 1 \n1100 3 1 \n1101 3 3 \n1102 4 3 \n1103 3 6 \n1104 2 2 \n1105 3 6 \n1106 3 2 \n1107 3 4 \n1108 2 5 \n1109 3 4 \n1110 2 3 \n1111 2 4 \n1112 2 3 \n1113 3 5 \n1114 2 6 \n1115 2 4 \n1116 4 4 \n1117 3 6 \n1118 3 7 \n1119 1 4 \n1120 3 5 \n1121 4 4 \n1122 2 5 \n1123 2 6 \n1124 3 5 \n1125 1 6 \n1126 3 4 \n1127 2 2 \n1128 2 5 \n1129 3 4 \n1130 3 5 \n1131 2 5 \n1132 3 1 \n1133 2 5 \n1134 2 5 \n1135 3 3 \n1136 1 4 \n1137 3 6 \n1138 2 1 \n1139 2 3 \n1140 3 2 \n1141 2 2 \n1142 2 7 \n1143 3 4 \n1144 3 4 \n1145 2 6 \n1146 3 3 \n1147 1 4 \n1148 1 5 \n1149 2 5 \n1150 4 5 \n1151 2 2 \n1152 2 4 \n1153 2 4 \n1154 3 3 \n1155 3 3 \n1156 3 5 \n1157 2 4 \n1158 3 3 \n1159 4 5 \n1160 2 4 \n1161 3 4 \n1162 3 4 \n1163 3 7 \n1164 3 2 \n1165 3 3 \n1166 3 3 \n1167 2 5 \n1168 3 4 \n1169 3 5 \n1170 3 7 \n1171 2 6 \n1172 3 8 \n1173 2 3 \n1174 3 5 \n1175 3 1 \n1176 3 2 \n1177 3 5 \n1178 4 4 \n1179 2 3 \n1180 1 5 \n1181 3 4 \n1182 2 4 \n1183 4 6 \n1184 3 4 \n1185 3 5 \n1186 1 2 \n1187 2 7 \n1188 3 3 \n1189 3 6 \n1190 3 6 \n1191 1 5 \n1192 2 5 \n1193 3 7 \n1194 4 5 \n1195 3 3 \n1196 2 2 \n1197 3 4 \n1198 1 2 \n1199 2 6 \n1200 1 4 \n1201 3 6 \n1202 1 6 \n1203 3 2 \n1204 2 6 \n1205 2 2 \n1206 3 5 \n1207 3 4 \n1208 3 6 \n1209 1 4 \n1210 3 3 \n1211 3 4 \n1212 3 3 \n1213 2 6 \n1214 3 5 \n1215 2 4 \n1216 1 4 \n1217 3 4 \n1218 2 6 \n1219 3 3 \n1220 2 7 \n1221 2 5 \n1222 2 6 \n1223 2 5 \n1224 2 3 \n1225 3 3 \n1226 3 4 \n1227 2 5 \n1228 1 2 \n1229 2 6 \n1230 1 5 \n1231 3 7 \n1232 2 5 \n1233 2 2 \n1234 1 4 \n1235 2 6 \n1236 2 5 \n1237 3 8 \n1238 3 5 \n1239 3 3 \n1240 1 5 \n1241 2 3 \n1242 3 3 \n1243 1 3 \n1244 3 7 \n1245 3 2 \n1246 2 5 \n1247 2 6 \n1248 1 4 \n1249 3 4 \n1250 2 6 \n1251 3 4 \n1252 2 5 \n1253 3 7 \n1254 3 4 \n1255 1 5 \n1256 2 3 \n1257 2 4 \n1258 2 5 \n1259 2 5 \n1260 2 5 \n1261 2 4 \n1262 2 4 \n1263 3 3 \n1264 2 3 \n1265 4 1 \n1266 2 4 \n1267 3 1 \n1268 3 6 \n1269 3 2 \n1270 2 3 \n1271 2 7 \n1272 2 5 \n1273 3 4 \n1274 2 2 \n1275 2 3 \n1276 2 4 \n1277 2 4 \n1278 2 5 \n1279 3 4 \n1280 2 7 \n1281 4 4 \n1282 1 3 \n1283 3 6 \n1284 1 4 \n1285 2 5 \n1286 2 2 \n1287 2 5 \n1288 1 3 \n1289 3 1 \n1290 3 4 \n1291 3 6 \n1292 2 4 \n1293 1 3 \n1294 1 5 \n1295 2 4 \n1296 2 5 \n1297 3 4 \n1298 3 3 \n1299 2 6 \n1300 2 1 \n1301 3 5 \n1302 3 3 \n1303 3 4 \n1304 2 7 \n1305 2 4 \n1306 2 6 \n1307 2 4 \n1308 3 3 \n1309 3 4 \n1310 2 3 \n1311 2 6 \n1312 2 5 \n1313 2 6 \n1314 3 7 \n1315 3 3 \n1316 2 5 \n1317 2 3 \n1318 2 6 \n1319 3 5 \n1320 3 4 \n1321 3 5 \n1322 3 1 \n1323 2 2 \n1324 2 6 \n1325 4 5 \n1326 3 2 \n1327 2 3 \n1328 1 6 \n1329 1 4 \n1330 2 6 \n1331 2 6 \n1332 2 5 \n1333 3 7 \n1334 2 5 \n1335 3 3 \n1336 3 4 \n1337 3 6 \n1338 2 5 \n1339 3 5 \n1340 3 6 \n1341 1 5 \n1342 3 3 \n1343 3 1 \n1344 3 3 \n1345 2 4 \n1346 2 6 \n1347 3 3 \n1348 2 3 \n1349 2 5 \n1350 2 6 \n1351 3 4 \n1352 2 5 \n1353 3 3 \n1354 3 5 \n1355 2 2 \n1356 3 3 \n1357 2 5 \n1358 3 2 \n1359 2 6 \n1360 2 3 \n1361 3 3 \n1362 3 1 \n1363 3 5 \n1364 2 4 \n1365 2 4 \n1366 3 6 \n1367 2 6 \n1368 3 8 \n1369 2 5 \n1370 3 7 \n1371 2 5 \n1372 2 5 \n1373 2 7 \n1374 2 2 \n1375 2 7 \n1376 2 6 \n1377 3 3 \n1378 2 2 \n1379 4 3 \n1380 1 4 \n1381 3 6 \n1382 3 7 \n1383 3 6 \n1384 3 4 \n1385 2 1 \n1386 3 6 \n1387 3 7 \n1388 3 5 \n1389 3 3 \n1390 2 5 \n1391 2 4 \n1392 2 4 \n1393 2 4 \n1394 3 4 \n1395 1 5 \n1396 4 4 \n1397 3 5 \n1398 2 6 \n1399 3 2 \n1400 2 4 \n1401 4 3 \n1402 3 6 \n1403 3 4 \n1404 4 4 \n1405 2 5 \n1406 3 3 \n1407 2 5 \n1408 2 6 \n1409 2 5 \n1410 3 5 \n1411 3 4 \n1412 2 4 \n1413 1 5 \n1414 2 6 \n1415 2 5 \n1416 2 5 \n1417 2 6 \n1418 3 8 \n1419 1 3 \n1420 2 5 \n1421 2 2 \n1422 2 6 \n1423 3 6 \n1424 2 4 \n1425 2 5 \n1426 2 2 \n1427 1 5 \n1428 4 2 \n1429 2 5 \n1430 2 7 \n1431 2 3 \n1432 3 3 \n1433 3 7 \n1434 2 4 \n1435 1 3 \n1436 2 4 \n1437 1 4 \n1438 2 6 \n1439 3 3 \n1440 2 4 \n1441 2 2 \n1442 3 6 \n1443 3 4 \n1444 3 6 \n1445 3 2 \n1446 3 7 \n1447 2 3 \n1448 3 5 \n1449 3 2 \n1450 2 6 \n1451 2 4 \n1452 1 6 \n1453 1 4 \n1454 3 3 \n1455 2 4 \n1456 2 3 \n1457 3 1 \n1458 3 6 \n1459 2 7 \n1460 3 6 \n1461 1 3 \n1462 3 7 \n1463 2 6 \n1464 2 5 \n1465 3 5 \n1466 2 5 \n1467 2 5 \n1468 2 3 \n1469 3 4 \n1470 2 6 \n1471 4 3 \n1472 3 3 \n1473 3 7 \n1474 2 2 \n1475 3 2 \n1476 2 3 \n1477 2 6 \n1478 3 4 \n1479 3 5 \n1480 2 4 \n1481 2 4 \n1482 3 3 \n1483 3 4 \n1484 1 4 \n1485 3 4 \n1486 2 2 \n1487 2 6 \n1488 3 4 \n1489 2 5 \n1490 2 5 \n1491 2 5 \n1492 3 3 \n1493 3 3 \n1494 2 5 \n1495 2 3 \n1496 2 5 \n1497 3 3 \n1498 3 5 \n1499 2 6 \n1500 2 4 \n1501 2 5 \n1502 2 5 \n1503 1 4 \n1504 2 5 \n1505 2 5 \n1506 2 3 \n1507 2 3 \n1508 3 4 \n1509 2 5 \n1510 3 5 \n1511 3 7 \n1512 1 4 \n1513 3 2 \n1514 3 6 \n1515 3 6 \n1516 3 5 \n1517 3 6 \n1518 2 2 \n1519 2 5 \n1520 2 3 \n1521 3 5 \n1522 3 6 \n1523 2 6 \n1524 2 4 \n1525 2 3 \n1526 4 2 \n1527 2 4 \n1528 3 7 \n1529 2 2 \n1530 2 3 \n1531 3 6 \n1532 2 4 \n1533 2 5 \n1534 3 5 \n1535 2 5 \n1536 2 4 \n1537 3 5 \n1538 3 2 \n1539 2 6 \n1540 2 4 \n1541 2 3 \n1542 2 5 \n1543 3 2 \n1544 2 4 \n1545 2 5 \n1546 3 6 \n1547 2 4 \n1548 2 4 \n1549 3 5 \n1550 1 3 \n1551 3 2 \n1552 3 5 \n1553 1 5 \n1554 3 3 \n1555 3 3 \n1556 3 3 \n1557 3 4 \n1558 2 6 \n1559 2 6 \n1560 3 4 \n1561 2 4 \n1562 2 3 \n1563 2 6 \n1564 2 3 \n1565 2 4 \n1566 2 4 \n1567 3 3 \n1568 3 7 \n1569 2 6 \n1570 3 4 \n1571 2 4 \n1572 1 4 \n1573 3 6 \n1574 3 3 \n1575 2 5 \n1576 2 4 \n1577 2 3 \n1578 3 2 \n1579 3 6 \n1580 3 2 \n1581 2 5 \n1582 3 5 \n1583 2 4 \n1584 2 4 \n1585 3 6 \n1586 2 6 \n1587 2 7 \n1588 3 4 \n1589 1 5 \n1590 3 6 \n1591 2 4 \n1592 3 4 \n1593 3 4 \n1594 3 2 \n1595 3 3 \n1596 2 3 \n1597 2 2 \n1598 2 5 \n1599 3 5 \n1600 2 4 \n1601 3 2 \n1602 3 2 \n1603 2 5 \n1604 2 5 \n1605 3 6 \n1606 2 5 \n1607 2 5 \n1608 2 4 \n1609 3 6 \n1610 2 4 \n1611 2 6 \n1612 3 3 \n1613 3 5 \n1614 2 3 \n1615 3 5 \n1616 2 3 \n1617 3 2 \n1618 2 5 \n1619 2 5 \n1620 2 5 \n1621 2 4 \n1622 2 6 \n1623 3 2 \n1624 2 3 \n1625 2 5 \n1626 2 5 \n1627 1 3 \n1628 2 5 \n1629 2 4 \n1630 2 2 \n1631 3 4 \n1632 3 4 \n1633 2 5 \n1634 3 7 \n1635 2 5 \n1636 1 2 \n1637 2 3 \n1638 3 5 \n1639 2 5 \n1640 2 4 \n1641 1 4 \n1642 3 5 \n1643 2 5 \n1644 3 2 \n1645 2 5 \n1646 2 3 \n1647 2 2 \n1648 2 5 \n1649 2 4 \n1650 3 6 \n1651 2 6 \n1652 2 2 \n1653 2 3 \n1654 2 4 \n1655 2 6 \n1656 3 1 \n1657 3 5 \n1658 2 3 \n1659 1 5 \n1660 3 3 \n1661 2 6 \n1662 3 5 \n1663 3 3 \n1664 3 6 \n1665 3 6 \n1666 3 3 \n1667 2 4 \n1668 2 4 \n1669 2 4 \n1670 2 3 \n1671 2 4 \n1672 2 3 \n1673 2 2 \n1674 2 3 \n1675 2 4 \n1676 3 3 \n1677 2 4 \n1678 2 6 \n1679 2 5 \n1680 3 5 \n1681 2 5 \n1682 3 7 \n1683 3 3 \n1684 2 5 \n1685 3 4 \n1686 3 6 \n1687 3 5 \n1688 1 3 \n1689 2 5 \n1690 2 4 \n1691 3 1 \n1692 2 3 \n1693 3 6 \n1694 2 5 \n1695 2 5 \n1696 2 6 \n1697 2 5 \n1698 2 4 \n1699 3 5 \n1700 3 4 \n1701 3 5 \n1702 3 5 \n1703 3 4 \n1704 2 4 \n1705 2 4 \n1706 2 3 \n1707 1 4 \n1708 2 2 \n1709 2 6 \n1710 3 1 \n1711 2 5 \n1712 2 5 \n1713 3 6 \n1714 1 4 \n1715 2 4 \n1716 2 2 \n1717 2 5 \n1718 1 3 \n1719 3 6 \n1720 3 4 \n1721 2 2 \n1722 2 5 \n1723 3 2 \n1724 3 6 \n1725 2 5 \n1726 2 3 \n1727 3 6 \n1728 2 4 \n1729 2 3 \n1730 3 4 \n1731 2 3 \n1732 2 4 \n1733 1 3 \n1734 2 5 \n1735 2 4 \n1736 3 7 \n1737 3 5 \n1738 1 5 \n1739 1 4 \n1740 2 2 \n1741 2 5 \n1742 2 6 \n1743 2 4 \n1744 2 2 \n1745 3 1 \n1746 2 1 \n1747 2 3 \n1748 2 2 \n1749 2 3 \n1750 3 4 \n1751 3 5 \n1752 3 6 \n1753 3 1 \n1754 2 4 \n1755 3 5 \n1756 2 5 \n1757 3 1 \n1758 3 7 \n1759 2 4 \n1760 2 4 \n1761 3 5 \n1762 2 4 \n1763 1 4 \n1764 1 5 \n1765 2 3 \n1766 3 6 \n1767 3 5 \n1768 3 5 \n1769 2 2 \n1770 2 3 \n1771 3 2 \n1772 2 5 \n1773 2 5 \n1774 2 4 \n1775 2 4 \n1776 2 3 \n1777 3 5 \n1778 3 1 \n1779 3 4 \n1780 3 6 \n1781 2 4 \n1782 3 4 \n1783 2 2 \n1784 2 4 \n1785 3 6 \n1786 2 5 \n1787 2 4 \n1788 2 5 \n1789 2 4 \n1790 2 6 \n1791 3 5 \n1792 2 6 \n1793 2 5 \n1794 3 4 \n1795 2 5 \n1796 2 5 \n1797 1 3 \n1798 2 5 \n1799 2 4 \n1800 3 5 \n1801 2 4 \n1802 2 4 \n1803 2 5 \n1804 2 6 \n1805 3 4 \n1806 2 5 \n1807 2 6 \n1808 2 4 \n1809 2 5 \n1810 2 4 \n1811 2 6 \n1812 2 5 \n1813 3 6 \n1814 2 3 \n1815 2 4 \n1816 3 3 \n1817 1 3 \n1818 2 4 \n1819 2 4 \n1820 3 7 \n1821 3 3 \n1822 2 4 \n1823 2 5 \n1824 1 4 \n1825 2 4 \n1826 3 1 \n1827 2 6 \n1828 3 5 \n1829 2 2 \n1830 2 3 \n1831 2 3 \n1832 3 5 \n1833 1 4 \n1834 3 6 \n1835 2 4 \n1836 3 5 \n1837 1 4 \n1838 2 7 \n1839 2 4 \n1840 2 4 \n1841 3 5 \n1842 2 5 \n1843 2 6 \n1844 3 5 \n1845 1 4 \n1846 3 3 \n1847 3 4 \n1848 2 2 \n1849 3 5 \n1850 2 5 \n1851 3 6 \n1852 1 3 \n1853 2 3 \n1854 1 5 \n1855 2 8 \n1856 1 4 \n1857 2 3 \n1858 3 4 \n1859 2 5 \n1860 2 5 \n1861 2 4 \n1862 2 5 \n1863 2 4 \n1864 2 5 \n1865 2 2 \n1866 2 2 \n1867 2 5 \n1868 3 6 \n1869 2 4 \n1870 3 1 \n1871 2 4 \n1872 3 6 \n1873 3 4 \n1874 2 5 \n1875 2 4 \n1876 2 4 \n1877 2 5 \n1878 3 5 \n1879 3 5 \n1880 2 2 \n1881 2 6 \n1882 2 3 \n1883 2 5 \n1884 2 3 \n1885 2 3 \n1886 3 4 \n1887 3 5 \n1888 2 5 \n1889 2 3 \n1890 2 5 \n1891 2 6 \n1892 2 4 \n1893 3 4 \n1894 2 4 \n1895 1 2 \n1896 2 4 \n1897 1 3 \n1898 2 5 \n1899 2 7 \n1900 3 3 \n1901 3 6 \n1902 2 4 \n1903 1 5 \n1904 2 6 \n1905 2 3 \n1906 2 2 \n1907 2 3 \n1908 1 4 \n1909 2 4 \n1910 2 2 \n1911 2 4 \n1912 2 5 \n1913 2 5 \n1914 2 5 \n1915 1 3 \n1916 1 4 \n1917 2 4 \n1918 1 4 \n1919 2 2 \n1920 3 5 \n1921 2 3 \n1922 3 5 \n1923 2 3 \n1924 2 5 \n1925 3 4 \n1926 2 5 \n1927 2 6 \n1928 2 4 \n1929 3 5 \n1930 2 3 \n1931 3 6 \n1932 1 3 \n1933 1 3 \n1934 3 6 \n1935 2 5 \n1936 3 5 \n1937 1 4 \n1938 2 4 \n1939 3 3 \n1940 2 4 \n1941 1 3 \n1942 2 5 \n1943 2 4 \n1944 2 4 \n1945 1 3 \n1946 2 4 \n1947 1 4 \n1948 1 4 \n1949 3 6 \n1950 3 5 \n1951 2 5 \n1952 2 4 \n1953 2 5 \n1954 2 4 \n1955 3 4 \n1956 2 3 \n1957 3 2 \n1958 2 3 \n1959 2 5 \n1960 1 3 \n1961 2 5 \n1962 2 2 \n1963 2 4 \n1964 2 3 \n1965 1 3 \n1966 2 7 \n1967 2 4 \n1968 2 4 \n1969 2 7 \n1970 2 5 \n1971 2 5 \n1972 1 5 \n1973 2 4 \n1974 2 3 \n1975 2 6 \n1976 3 1 \n1977 3 4 \n1978 3 5 \n1979 3 5 \n1980 2 4 \n1981 2 3 \n1982 1 2 \n1983 2 4 \n1984 1 2 \n1985 2 8 \n1986 2 4 \n1987 3 6 \n1988 3 4 \n1989 2 2 \n1990 3 2 \n1991 3 4 \n1992 3 5 \n1993 2 4 \n1994 2 5 \n1995 1 4 \n1996 2 5 \n1997 3 3 \n1998 2 6 \n1999 3 5 \n2000 2 4 \n2001 2 4 \n2002 2 5 \n2003 2 5 \n2004 3 6 \n2005 2 4 \n2006 2 5 \n2007 1 6 \n2008 2 6 \n2009 1 3 \n2010 2 5 \n2011 2 2 \n2012 2 4 \n2013 3 4 \n2014 2 7 \n2015 2 4 \n2016 2 6 \n2017 2 3 \n2018 3 5 \n2019 3 5 \n2020 2 7 \n2021 2 5 \n2022 2 2 \n2023 2 5 \n2024 2 4 \n2025 1 4 \n2026 1 2 \n2027 2 4 \n2028 2 5 \n2029 1 4 \n2030 3 4 \n2031 2 4 \n2032 2 4 \n2033 2 4 \n2034 2 2 \n2035 1 3 \n2036 2 6 \n2037 3 3 \n2038 3 4 \n2039 2 5 \n2040 1 4 \n2041 1 4 \n2042 1 7 \n2043 2 4 \n2044 3 3 \n2045 2 8 \n2046 2 6 \n2047 2 4 \n2048 1 6 \n2049 2 2 \n2050 2 5 \n2051 2 3 \n2052 1 5 \n2053 2 4 \n2054 2 4 \n2055 2 5 \n2056 2 7 \n2057 3 5 \n2058 1 3 \n2059 3 5 \n2060 2 5 \n2061 1 3 \n2062 1 7 \n2063 3 4 \n2064 1 3 \n2065 2 3 \n2066 3 5 \n2067 2 2 \n2068 3 4 \n2069 2 7 \n2070 2 3 \n2071 2 8 \n2072 3 4 \n2073 1 2 \n2074 2 5 \n2075 2 6 \n2076 1 6 \n2077 2 4 \n2078 2 5 \n2079 1 3 \n2080 2 3 \n2081 1 7 \n2082 2 3 \n2083 3 1 \n2084 3 3 \n2085 2 4 \n2086 2 3 \n2087 2 1 \n2088 3 3 \n2089 2 3 \n2090 3 4 \n2091 3 4 \n2092 3 5 \n2093 1 4 \n2094 2 4 \n2095 2 4 \n2096 2 4 \n2097 2 6 \n2098 3 3 \n2099 1 4 \n2100 2 3 \n2101 2 5 \n2102 2 4 \n2103 2 3 \n2104 2 3 \n2105 2 4 \n2106 2 4 \n2107 2 4 \n2108 2 6 \n2109 3 2 \n2110 1 3 \n2111 2 7 \n2112 1 5 \n2113 3 5 \n2114 1 4 \n2115 3 5 \n2116 1 3 \n2117 1 4 \n2118 2 5 \n2119 2 2 \n2120 2 7 \n2121 1 3 \n2122 2 1 \n2123 2 3 \n2124 2 4 \n2125 2 6 \n2126 2 5 \n2127 3 2 \n2128 1 3 \n2129 2 7 \n2130 2 5 \n2131 2 3 \n2132 2 5 \n2133 2 6 \n2134 2 8 \n2135 2 4 \n2136 1 6 \n2137 2 5 \n2138 1 2 \n2139 1 3 \n2140 3 4 \n2141 2 2 \n2142 2 3 \n2143 1 5 \n2144 2 5 \n2145 1 6 \n2146 2 5 \n2147 2 3 \n2148 2 4 \n2149 2 4 \n2150 3 4 \n2151 1 3 \n2152 3 4 \n2153 3 4 \n2154 2 4 \n2155 2 7 \n2156 2 4 \n2157 2 7 \n2158 2 4 \n2159 2 3 \n2160 2 4 \n2161 2 4 \n2162 2 6 \n2163 2 4 \n2164 1 3 \n2165 2 5 \n2166 3 5 \n2167 1 7 \n2168 1 6 \n2169 1 4 \n2170 3 5 \n2171 1 5 \n2172 2 3 \n2173 1 5 \n2174 2 2 \n2175 1 2 \n2176 1 3 \n2177 3 6 \n2178 2 2 \n2179 3 4 \n2180 2 4 \n2181 2 3 \n2182 3 5 \n2183 2 4 \n2184 1 6 \n2185 2 4 \n2186 2 4 \n2187 1 3 \n2188 2 4 \n2189 2 4 \n2190 3 3 \n2191 1 4 \n2192 2 5 \n2193 2 4 \n2194 2 6 \n2195 2 4 \n2196 2 5 \n2197 1 2 \n2198 2 6 \n2199 2 6 \n2200 2 3 \n2201 1 6 \n2202 2 2 \n2203 3 5 \n2204 2 5 \n2205 2 7 \n2206 1 3 \n2207 1 6 \n2208 3 1 \n2209 3 4 \n2210 1 2 \n2211 2 3 \n2212 2 5 \n2213 2 1 \n2214 2 6 \n2215 1 7 \n2216 3 3 \n2217 1 6 \n2218 2 7 \n2219 1 2 \n2220 2 3 \n2221 3 2 \n2222 1 5 \n2223 3 3 \n2224 2 5 \n2225 2 7 \n2226 2 4 \n2227 1 5 \n2228 1 4 \n2229 3 3 \n2230 1 3 \n2231 1 4 \n2232 2 5 \n2233 2 6 \n2234 2 3 \n2235 2 4 \n2236 2 7 \n2237 3 4 \n2238 2 5 \n2239 2 4 \n2240 1 5 \n2241 2 6 \n2242 2 3 \n2243 2 4 \n2244 2 3 \n2245 2 4 \n2246 2 7 \n2247 1 5 \n2248 2 5 \n2249 2 5 \n2250 2 4 \n2251 2 4 \n2252 3 6 \n2253 2 8 \n2254 1 6 \n2255 3 3 \n2256 2 3 \n2257 1 3 \n2258 3 4 \n2259 2 2 \n2260 1 2 \n2261 2 4 \n2262 3 5 \n2263 3 5 \n2264 3 5 \n2265 2 4 \n2266 2 6 \n2267 2 3 \n2268 3 3 \n2269 2 7 \n2270 2 6 \n2271 1 6 \n2272 3 4 \n2273 2 4 \n2274 2 7 \n2275 1 3 \n2276 2 5 \n2277 2 3 \n2278 2 1 \n2279 4 1 \n2280 2 3 \n2281 1 6 \n2282 3 4 \n2283 2 4 \n2284 1 5 \n2285 2 4 \n2286 1 5 \n2287 1 5 \n2288 2 3 \n2289 2 5 \n2290 2 1 \n2291 2 3 \n2292 2 3 \n2293 1 4 \n2294 2 7 \n2295 3 1 \n2296 2 5 \n2297 1 6 \n2298 1 7 \n2299 3 4 \n2300 1 4 \n2301 2 6 \n2302 2 3 \n2303 2 4 \n2304 1 6 \n2305 2 4 \n2306 1 6 \n2307 2 6 \n2308 1 6 \n2309 2 4 \n2310 2 3 \n2311 1 4 \n2312 2 4 \n2313 2 6 \n2314 2 4 \n2315 2 4 \n2316 2 6 \n2317 1 2 \n2318 1 5 \n2319 2 4 \n2320 1 5 \n2321 2 6 \n2322 2 3 \n2323 2 7 \n2324 2 3 \n2325 2 4 \n2326 3 3 \n2327 2 5 \n2328 2 5 \n2329 1 7 \n2330 1 5 \n2331 3 2 \n2332 2 3 \n2333 1 5 \n2334 3 3 \n2335 1 5 \n2336 3 4 \n2337 2 3 \n2338 2 1 \n2339 3 4 \n2340 2 7 \n2341 2 3 \n2342 1 3 \n2343 2 5 \n2344 0 5 \n2345 1 6 \n2346 2 5 \n2347 2 5 \n2348 1 6 \n2349 3 5 \n2350 2 4 \n2351 0 6 \n2352 2 6 \n2353 2 6 \n2354 2 6 \n2355 2 4 \n2356 2 4 \n2357 2 4 \n2358 2 6 \n2359 2 6 \n2360 1 4 \n2361 2 5 \n2362 2 3 \n2363 2 5 \n2364 2 7 \n2365 2 3 \n2366 2 4 \n2367 2 3 \n2368 2 3 \n2369 2 4 \n2370 1 6 \n2371 3 4 \n2372 2 3 \n2373 3 2 \n2374 1 5 \n2375 3 3 \n2376 2 4 \n2377 3 5 \n2378 2 2 \n2379 1 5 \n2380 1 3 \n2381 2 6 \n2382 1 3 \n2383 1 4 \n2384 2 3 \n2385 1 3 \n2386 2 3 \n2387 1 5 \n2388 3 2 \n2389 2 5 \n2390 2 5 \n2391 2 3 \n2392 2 5 \n2393 2 4 \n2394 2 5 \n2395 2 2 \n2396 2 6 \n2397 2 4 \n2398 1 7 \n2399 1 5 \n2400 2 5 \n2401 3 4 \n2402 1 6 \n2403 2 4 \n2404 1 4 \n2405 2 3 \n2406 2 3 \n2407 2 2 \n2408 2 6 \n2409 1 5 \n2410 2 3 \n2411 2 3 \n2412 2 2 \n2413 1 5 \n2414 1 6 \n2415 1 4 \n2416 2 7 \n2417 2 6 \n2418 2 7 \n2419 1 3 \n2420 2 4 \n2421 1 2 \n2422 2 6 \n2423 2 3 \n2424 2 4 \n2425 1 6 \n2426 2 3 \n2427 3 5 \n2428 2 6 \n2429 2 4 \n2430 2 3 \n2431 1 5 \n2432 2 5 \n2433 1 5 \n2434 3 4 \n2435 1 4 \n2436 2 7 \n2437 2 4 \n2438 1 6 \n2439 1 6 \n2440 2 4 \n2441 1 4 \n2442 1 5 \n2443 3 4 \n2444 2 2 \n2445 2 6 \n2446 2 5 \n2447 1 4 \n2448 2 4 \n2449 3 4 \n2450 2 5 \n2451 1 5 \n2452 2 4 \n2453 1 4 \n2454 1 5 \n2455 0 4 \n2456 2 6 \n2457 2 6 \n2458 2 7 \n2459 1 2 \n2460 3 4 \n2461 2 3 \n2462 2 6 \n2463 0 5 \n2464 3 1 \n2465 1 3 \n2466 2 4 \n2467 1 3 \n2468 1 6 \n2469 2 3 \n2470 1 6 \n2471 2 4 \n2472 3 5 \n2473 2 5 \n2474 1 3 \n2475 2 1 \n2476 2 4 \n2477 2 6 \n2478 3 2 \n2479 2 5 \n2480 2 3 \n2481 2 4 \n2482 2 7 \n2483 1 4 \n2484 1 5 \n2485 1 3 \n2486 2 4 \n2487 2 4 \n2488 2 3 \n2489 3 5 \n2490 2 5 \n2491 2 3 \n2492 2 2 \n2493 2 6 \n2494 2 4 \n2495 1 2 \n2496 2 2 \n2497 2 3 \n2498 3 3 \n2499 2 5 \n2500 2 3 \n2501 2 4 \n2502 3 4 \n2503 1 3 \n2504 2 7 \n2505 2 3 \n2506 2 1 \n2507 2 3 \n2508 1 2 \n2509 2 2 \n2510 2 3 \n2511 3 3 \n2512 3 3 \n2513 2 6 \n2514 3 4 \n2515 2 6 \n2516 2 3 \n2517 2 6 \n2518 1 4 \n2519 2 4 \n2520 2 7 \n2521 2 4 \n2522 2 3 \n2523 2 6 \n2524 2 6 \n2525 1 4 \n2526 2 5 \n2527 1 6 \n2528 1 2 \n2529 0 5 \n2530 1 5 \n2531 2 4 \n2532 2 2 \n2533 1 4 \n2534 2 5 \n2535 2 3 \n2536 1 5 \n2537 1 6 \n2538 3 4 \n2539 2 7 \n2540 2 6 \n2541 2 5 \n2542 2 1 \n2543 2 6 \n2544 2 5 \n2545 1 6 \n2546 2 6 \n2547 1 3 \n2548 1 3 \n2549 2 5 \n2550 2 5 \n2551 3 4 \n2552 2 4 \n2553 2 3 \n2554 2 6 \n2555 1 5 \n2556 2 5 \n2557 2 5 \n2558 0 4 \n2559 2 5 \n2560 1 4 \n2561 0 4 \n2562 2 2 \n2563 2 4 \n2564 1 6 \n2565 1 5 \n2566 1 6 \n2567 2 4 \n2568 2 6 \n2569 2 3 \n2570 2 7 \n2571 2 4 \n2572 1 6 \n2573 2 4 \n2574 0 5 \n2575 2 4 \n2576 2 5 \n2577 2 3 \n2578 2 5 \n2579 2 3 \n2580 2 3 \n2581 1 5 \n2582 1 4 \n2583 2 6 \n2584 1 5 \n2585 1 5 \n2586 1 3 \n2587 2 6 \n2588 1 4 \n2589 1 5 \n2590 2 5 \n2591 2 4 \n2592 2 4 \n2593 1 5 \n2594 1 5 \n2595 2 4 \n2596 2 4 \n2597 2 1 \n2598 1 4 \n2599 1 2 \n2600 1 5 \n2601 1 5 \n2602 2 3 \n2603 2 4 \n2604 2 7 \n2605 1 6 \n2606 1 4 \n2607 3 3 \n2608 1 6 \n2609 2 6 \n2610 2 6 \n2611 2 3 \n2612 2 5 \n2613 2 3 \n2614 3 4 \n2615 2 6 \n2616 1 3 \n2617 1 6 \n2618 2 4 \n2619 1 2 \n2620 2 5 \n2621 2 3 \n2622 2 6 \n2623 2 2 \n2624 2 5 \n2625 1 5 \n2626 2 6 \n2627 2 6 \n2628 2 3 \n2629 2 1 \n2630 2 5 \n2631 2 1 \n2632 3 3 \n2633 1 5 \n2634 2 5 \n2635 2 3 \n2636 2 2 \n2637 2 4 \n2638 2 6 \n2639 3 3 \n2640 2 4 \n2641 2 5 \n2642 2 2 \n2643 1 5 \n2644 2 4 \n2645 2 5 \n2646 0 4 \n2647 2 6 \n2648 2 2 \n2649 1 3 \n2650 1 4 \n2651 2 3 \n2652 2 4 \n2653 2 6 \n2654 3 3 \n2655 1 6 \n2656 2 4 \n2657 2 5 \n2658 1 5 \n2659 1 4 \n2660 2 6 \n2661 2 3 \n2662 1 5 \n2663 2 3 \n2664 2 5 \n2665 2 6 \n2666 1 3 \n2667 3 4 \n2668 2 5 \n2669 1 4 \n2670 2 5 \n2671 1 4 \n2672 2 3 \n2673 2 4 \n2674 1 4 \n2675 0 3 \n2676 2 3 \n2677 0 3 \n2678 2 5 \n2679 2 3 \n2680 2 7 \n2681 1 6 \n2682 2 5 \n2683 1 3 \n2684 2 5 \n2685 2 2 \n2686 1 5 \n2687 2 4 \n2688 2 6 \n2689 2 4 \n2690 2 4 \n2691 2 3 \n2692 1 2 \n2693 2 7 \n2694 1 5 \n2695 2 3 \n2696 2 3 \n2697 1 2 \n2698 2 5 \n2699 2 2 \n2700 3 4 \n2701 2 6 \n2702 2 6 \n2703 1 5 \n2704 1 8 \n2705 1 5 \n2706 1 2 \n2707 2 3 \n2708 2 4 \n2709 1 5 \n2710 1 5 \n2711 2 1 \n2712 2 6 \n2713 1 5 \n2714 2 6 \n2715 1 5 \n2716 1 4 \n2717 2 6 \n2718 3 3 \n2719 1 6 \n2720 2 1 \n2721 2 4 \n2722 1 4 \n2723 2 5 \n2724 2 6 \n2725 0 4 \n2726 2 3 \n2727 2 5 \n2728 1 5 \n2729 2 2 \n2730 1 6 \n2731 2 4 \n2732 2 5 \n2733 2 3 \n2734 1 7 \n2735 1 6 \n2736 1 2 \n2737 2 3 \n2738 2 5 \n2739 1 5 \n2740 2 4 \n2741 2 6 \n2742 3 3 \n2743 1 5 \n2744 2 5 \n2745 2 6 \n2746 1 5 \n2747 1 4 \n2748 2 4 \n2749 2 3 \n2750 2 3 \n2751 1 4 \n2752 2 4 \n2753 2 6 \n2754 1 5 \n2755 1 8 \n2756 1 4 \n2757 1 5 \n2758 2 6 \n2759 3 3 \n2760 2 2 \n2761 2 5 \n2762 2 5 \n2763 2 5 \n2764 1 5 \n2765 3 2 \n2766 1 4 \n2767 2 4 \n2768 2 3 \n2769 1 4 \n2770 1 6 \n2771 1 3 \n2772 2 3 \n2773 1 5 \n2774 2 6 \n2775 1 4 \n2776 2 5 \n2777 3 4 \n2778 2 1 \n2779 1 4 \n2780 2 4 \n2781 1 7 \n2782 2 2 \n2783 2 4 \n2784 1 5 \n2785 2 5 \n2786 2 5 \n2787 2 6 \n2788 1 4 \n2789 2 6 \n2790 2 4 \n2791 2 5 \n2792 2 5 \n2793 1 5 \n2794 2 6 \n2795 2 3 \n2796 2 5 \n2797 2 3 \n2798 2 3 \n2799 2 4 \n2800 2 5 \n2801 2 5 \n2802 1 4 \n2803 2 4 \n2804 1 5 \n2805 1 3 \n2806 2 3 \n2807 2 6 \n2808 2 3 \n2809 1 5 \n2810 3 2 \n2811 1 3 \n2812 1 6 \n2813 1 2 \n2814 2 3 \n2815 1 7 \n2816 2 5 \n2817 2 6 \n2818 1 3 \n2819 2 3 \n2820 1 5 \n2821 2 3 \n2822 2 4 \n2823 2 6 \n2824 2 3 \n2825 3 2 \n2826 1 4 \n2827 2 3 \n2828 2 4 \n2829 2 3 \n2830 1 5 \n2831 1 6 \n2832 2 5 \n2833 2 5 \n2834 2 5 \n2835 2 4 \n2836 1 3 \n2837 2 5 \n2838 1 1 \n2839 2 3 \n2840 2 5 \n2841 3 3 \n2842 2 2 \n2843 2 4 \n2844 1 5 \n2845 1 5 \n2846 2 5 \n2847 1 6 \n2848 2 5 \n2849 1 8 \n2850 2 2 \n2851 1 2 \n2852 3 2 \n2853 2 4 \n2854 1 5 \n2855 1 3 \n2856 1 6 \n2857 2 3 \n2858 2 4 \n2859 1 5 \n2860 2 2 \n2861 2 4 \n2862 1 2 \n2863 1 4 \n2864 2 5 \n2865 2 3 \n2866 2 5 \n2867 1 2 \n2868 2 1 \n2869 1 7 \n2870 1 6 \n2871 2 5 \n2872 1 7 \n2873 1 5 \n2874 2 5 \n2875 1 4 \n2876 2 4 \n2877 2 4 \n2878 1 4 \n2879 2 5 \n2880 2 4 \n2881 2 5 \n2882 1 5 \n2883 1 4 \n2884 2 2 \n2885 1 4 \n2886 1 5 \n2887 2 2 \n2888 2 2 \n2889 1 3 \n2890 1 2 \n2891 2 2 \n2892 2 5 \n2893 1 2 \n2894 2 2 \n2895 0 4 \n2896 2 4 \n2897 1 4 \n2898 2 6 \n2899 3 2 \n2900 1 5 \n2901 2 4 \n2902 2 5 \n2903 2 3 \n2904 2 6 \n2905 1 7 \n2906 1 4 \n2907 2 6 \n2908 2 3 \n2909 1 6 \n2910 2 4 \n2911 1 5 \n2912 2 3 \n2913 2 6 \n2914 2 3 \n2915 1 4 \n2916 1 5 \n2917 2 5 \n2918 1 1 \n2919 1 5 \n2920 2 4 \n2921 2 5 \n2922 2 3 \n2923 2 4 \n2924 1 6 \n2925 1 7 \n2926 2 6 \n2927 1 4 \n2928 2 5 \n2929 3 2 \n2930 1 4 \n2931 1 5 \n2932 1 5 \n2933 1 8 \n2934 1 4 \n2935 1 4 \n2936 1 5 \n2937 2 5 \n2938 2 2 \n2939 2 2 \n2940 2 2 \n2941 1 5 \n2942 2 4 \n2943 1 1 \n2944 1 5 \n2945 1 6 \n2946 1 4 \n2947 1 4 \n2948 1 4 \n2949 2 5 \n2950 3 3 \n2951 1 4 \n2952 2 5 \n2953 2 3 \n2954 2 4 \n2955 2 5 \n2956 1 5 \n2957 2 1 \n2958 1 6 \n2959 1 5 \n2960 0 3 \n2961 1 7 \n2962 2 1 \n2963 2 5 \n2964 2 4 \n2965 1 4 \n2966 2 4 \n2967 2 5 \n2968 2 3 \n2969 2 3 \n2970 1 5 \n2971 1 7 \n2972 1 5 \n2973 1 3 \n2974 2 5 \n2975 1 6 \n2976 1 4 \n2977 2 6 \n2978 1 7 \n2979 2 3 \n2980 2 3 \n2981 1 4 \n2982 2 4 \n2983 2 5 \n2984 1 5 \n2985 2 5 \n2986 1 4 \n2987 2 3 \n2988 2 3 \n2989 2 3 \n2990 1 7 \n2991 2 3 \n2992 2 1 \n2993 2 6 \n2994 1 6 \n2995 2 4 \n2996 1 4 \n2997 2 4 \n2998 2 4 \n2999 2 2 \n3000 2 5 \n3001 2 5 \n3002 1 3 \n3003 2 3 \n3004 2 3 \n3005 1 3 \n3006 1 4 \n3007 1 3 \n3008 1 6 \n3009 3 3 \n3010 2 2 \n3011 2 4 \n3012 1 3 \n3013 1 5 \n3014 2 4 \n3015 0 5 \n3016 1 4 \n3017 1 5 \n3018 1 3 \n3019 1 4 \n3020 2 4 \n3021 2 4 \n3022 1 4 \n3023 2 5 \n3024 1 4 \n3025 2 2 \n3026 2 4 \n3027 1 3 \n3028 1 4 \n3029 1 4 \n3030 2 5 \n3031 0 7 \n3032 1 5 \n3033 1 5 \n3034 1 3 \n3035 0 7 \n3036 2 1 \n3037 1 4 \n3038 1 3 \n3039 1 5 \n3040 1 6 \n3041 2 5 \n3042 2 4 \n3043 2 1 \n3044 2 3 \n3045 1 4 \n3046 1 5 \n3047 1 5 \n3048 1 7 \n3049 0 5 \n3050 2 2 \n3051 2 5 \n3052 2 1 \n3053 2 5 \n3054 1 3 \n3055 2 5 \n3056 1 4 \n3057 2 3 \n3058 2 4 \n3059 1 1 \n3060 1 5 \n3061 2 5 \n3062 2 2 \n3063 2 6 \n3064 0 6 \n3065 2 3 \n3066 1 5 \n3067 3 2 \n3068 1 6 \n3069 0 4 \n3070 2 3 \n3071 1 4 \n3072 2 4 \n3073 1 5 \n3074 1 7 \n3075 1 2 \n3076 1 5 \n3077 1 6 \n3078 1 3 \n3079 1 2 \n3080 1 4 \n3081 1 4 \n3082 1 4 \n3083 1 5 \n3084 1 5 \n3085 2 5 \n3086 1 3 \n3087 1 4 \n3088 1 4 \n3089 1 7 \n3090 2 2 \n3091 2 3 \n3092 2 5 \n3093 1 5 \n3094 1 6 \n3095 2 1 \n3096 1 4 \n3097 1 5 \n3098 0 6 \n3099 1 4 \n3100 2 5 \n3101 2 3 \n3102 2 4 \n3103 1 4 \n3104 2 5 \n3105 2 2 \n3106 2 5 \n3107 2 2 \n3108 1 4 \n3109 2 2 \n3110 1 4 \n3111 2 3 \n3112 1 4 \n3113 1 3 \n3114 2 5 \n3115 2 4 \n3116 1 6 \n3117 2 2 \n3118 1 4 \n3119 2 5 \n3120 1 6 \n3121 1 6 \n3122 2 4 \n3123 1 4 \n3124 3 2 \n3125 2 5 \n3126 1 3 \n3127 1 6 \n3128 1 4 \n3129 2 2 \n3130 1 5 \n3131 1 5 \n3132 1 4 \n3133 2 4 \n3134 2 4 \n3135 2 4 \n3136 2 2 \n3137 1 3 \n3138 1 7 \n3139 1 5 \n3140 2 4 \n3141 0 3 \n3142 2 5 \n3143 1 5 \n3144 1 2 \n3145 1 7 \n3146 2 4 \n3147 1 4 \n3148 1 5 \n3149 2 2 \n3150 1 7 \n3151 1 5 \n3152 2 3 \n3153 1 2 \n3154 2 2 \n3155 1 4 \n3156 1 4 \n3157 2 4 \n3158 1 3 \n3159 2 6 \n3160 1 3 \n3161 1 4 \n3162 1 4 \n3163 2 2 \n3164 2 4 \n3165 0 4 \n3166 1 4 \n3167 1 3 \n3168 1 5 \n3169 1 4 \n3170 2 3 \n3171 1 7 \n3172 1 2 \n3173 2 4 \n3174 1 3 \n3175 1 5 \n3176 1 2 \n3177 1 4 \n3178 2 1 \n3179 1 5 \n3180 2 2 \n3181 1 6 \n3182 2 5 \n3183 1 6 \n3184 2 3 \n3185 1 6 \n3186 2 4 \n3187 1 5 \n3188 1 5 \n3189 0 2 \n3190 1 4 \n3191 1 5 \n3192 1 4 \n3193 1 7 \n3194 1 3 \n3195 2 4 \n3196 2 4 \n3197 1 3 \n3198 1 2 \n3199 2 5 \n3200 1 4 \n3201 2 3 \n3202 1 4 \n3203 2 4 \n3204 1 4 \n3205 2 2 \n3206 0 6 \n3207 2 5 \n3208 2 5 \n3209 2 5 \n3210 1 7 \n3211 2 4 \n3212 2 5 \n3213 1 3 \n3214 2 3 \n3215 1 5 \n3216 1 6 \n3217 0 6 \n3218 2 4 \n3219 2 4 \n3220 1 2 \n3221 1 6 \n3222 0 6 \n3223 1 6 \n3224 1 3 \n3225 1 6 \n3226 2 2 \n3227 1 6 \n3228 2 4 \n3229 1 3 \n3230 2 4 \n3231 1 6 \n3232 2 5 \n3233 2 2 \n3234 1 4 \n3235 1 5 \n3236 1 3 \n3237 1 4 \n3238 1 4 \n3239 1 4 \n3240 1 3 \n3241 0 6 \n3242 1 3 \n3243 1 5 \n3244 0 5 \n3245 2 3 \n3246 1 3 \n3247 2 1 \n3248 1 4 \n3249 1 5 \n3250 1 3 \n3251 2 4 \n3252 1 7 \n3253 1 5 \n3254 2 4 \n3255 1 4 \n3256 2 3 \n3257 2 4 \n3258 1 5 \n3259 2 2 \n3260 2 5 \n3261 1 6 \n3262 2 2 \n3263 1 2 \n3264 1 5 \n3265 2 4 \n3266 1 4 \n3267 1 5 \n3268 0 5 \n3269 1 6 \n3270 1 3 \n3271 0 5 \n3272 1 4 \n3273 2 4 \n3274 0 4 \n3275 1 2 \n3276 1 4 \n3277 2 5 \n3278 1 5 \n3279 2 5 \n3280 2 4 \n3281 1 4 \n3282 1 7 \n3283 2 4 \n3284 1 6 \n3285 2 2 \n3286 1 2 \n3287 1 4 \n3288 2 2 \n3289 1 4 \n3290 2 3 \n3291 3 1 \n3292 1 1 \n3293 1 4 \n3294 2 1 \n3295 1 6 \n3296 2 3 \n3297 2 2 \n3298 1 4 \n3299 1 3 \n3300 2 5 \n3301 2 4 \n3302 1 6 \n3303 1 2 \n3304 2 1 \n3305 1 5 \n3306 0 4 \n3307 2 3 \n3308 2 4 \n3309 1 3 \n3310 1 6 \n3311 1 4 \n3312 1 4 \n3313 1 6 \n3314 0 4 \n3315 1 4 \n3316 0 6 \n3317 2 5 \n3318 1 4 \n3319 1 4 \n3320 1 6 \n3321 1 3 \n3322 2 1 \n3323 0 4 \n3324 1 4 \n3325 1 5 \n3326 0 5 \n3327 0 4 \n3328 1 7 \n3329 1 3 \n3330 1 4 \n3331 1 6 \n3332 2 4 \n3333 1 2 \n3334 2 2 \n3335 1 3 \n3336 1 4 \n3337 1 2 \n3338 1 6 \n3339 1 4 \n3340 1 5 \n3341 0 6 \n3342 2 3 \n3343 2 3 \n3344 1 3 \n3345 2 3 \n3346 1 5 \n3347 0 5 \n3348 1 6 \n3349 1 4 \n3350 2 5 \n3351 2 4 \n3352 1 7 \n3353 1 3 \n3354 0 3 \n3355 2 3 \n3356 2 4 \n3357 2 4 \n3358 1 5 \n3359 1 4 \n3360 1 5 \n3361 1 5 \n3362 1 3 \n3363 2 3 \n3364 1 4 \n3365 1 3 \n3366 0 3 \n3367 1 6 \n3368 1 4 \n3369 1 5 \n3370 1 5 \n3371 1 5 \n3372 2 2 \n3373 2 4 \n3374 1 4 \n3375 1 4 \n3376 1 4 \n3377 1 6 \n3378 0 4 \n3379 1 3 \n3380 0 3 \n3381 1 4 \n3382 2 4 \n3383 0 5 \n3384 1 2 \n3385 2 4 \n3386 2 3 \n3387 1 3 \n3388 1 4 \n3389 1 3 \n3390 1 6 \n3391 1 6 \n3392 2 3 \n3393 1 6 \n3394 1 6 \n3395 2 5 \n3396 1 2 \n3397 2 4 \n3398 1 5 \n3399 2 3 \n3400 1 3 \n3401 1 3 \n3402 1 5 \n3403 2 3 \n3404 1 2 \n3405 2 1 \n3406 1 5 \n3407 1 3 \n3408 1 3 \n3409 2 4 \n3410 2 4 \n3411 0 8 \n3412 1 6 \n3413 0 5 \n3414 1 4 \n3415 1 4 \n3416 1 3 \n3417 1 6 \n3418 1 5 \n3419 1 6 \n3420 1 3 \n3421 1 6 \n3422 1 4 \n3423 0 5 \n3424 2 4 \n3425 1 4 \n3426 2 4 \n3427 2 3 \n3428 1 3 \n3429 3 1 \n3430 1 3 \n3431 2 5 \n3432 2 4 \n3433 1 3 \n3434 1 4 \n3435 1 4 \n3436 1 5 \n3437 1 5 \n3438 1 3 \n3439 1 2 \n3440 0 6 \n3441 1 4 \n3442 1 3 \n3443 1 6 \n3444 0 5 \n3445 1 4 \n3446 1 4 \n3447 2 4 \n3448 2 4 \n3449 1 5 \n3450 2 3 \n3451 2 2 \n3452 1 5 \n3453 2 2 \n3454 1 5 \n3455 2 3 \n3456 0 3 \n3457 1 6 \n3458 1 2 \n3459 1 3 \n3460 1 3 \n3461 0 7 \n3462 1 5 \n3463 2 3 \n3464 1 6 \n3465 1 3 \n3466 1 6 \n3467 2 4 \n3468 1 2 \n3469 1 4 \n3470 3 1 \n3471 1 4 \n3472 2 1 \n3473 1 4 \n3474 2 2 \n3475 1 4 \n3476 1 5 \n3477 1 5 \n3478 1 3 \n3479 0 3 \n3480 1 4 \n3481 1 2 \n3482 1 5 \n3483 1 5 \n3484 1 6 \n3485 1 4 \n3486 0 3 \n3487 1 6 \n3488 2 3 \n3489 0 4 \n3490 2 4 \n3491 1 4 \n3492 2 1 \n3493 0 5 \n3494 2 3 \n3495 1 4 \n3496 1 6 \n3497 2 3 \n3498 1 5 \n3499 2 4 \n3500 1 2 \n3501 1 5 \n3502 2 3 \n3503 0 4 \n3504 2 4 \n3505 2 4 \n3506 2 1 \n3507 1 4 \n3508 2 3 \n3509 1 5 \n3510 0 4 \n3511 2 1 \n3512 1 4 \n3513 2 3 \n3514 1 4 \n3515 0 6 \n3516 1 5 \n3517 1 4 \n3518 1 4 \n3519 0 5 \n3520 1 6 \n3521 1 4 \n3522 0 6 \n3523 2 3 \n3524 1 2 \n3525 1 2 \n3526 0 6 \n3527 1 3 \n3528 1 5 \n3529 0 7 \n3530 1 4 \n3531 1 6 \n3532 1 6 \n3533 0 5 \n3534 1 2 \n3535 1 4 \n3536 2 3 \n3537 1 3 \n3538 1 5 \n3539 3 1 \n3540 2 1 \n3541 1 3 \n3542 1 4 \n3543 1 5 \n3544 1 5 \n3545 1 5 \n3546 1 5 \n3547 1 5 \n3548 1 3 \n3549 2 2 \n3550 1 3 \n3551 2 3 \n3552 0 3 \n3553 1 3 \n3554 2 4 \n3555 1 3 \n3556 1 6 \n3557 1 5 \n3558 1 3 \n3559 1 3 \n3560 1 6 \n3561 2 1 \n3562 1 3 \n3563 0 5 \n3564 1 3 \n3565 1 5 \n3566 1 5 \n3567 2 2 \n3568 1 1 \n3569 1 1 \n3570 1 3 \n3571 1 4 \n3572 0 5 \n3573 1 4 \n3574 1 5 \n3575 1 3 \n3576 2 4 \n3577 1 3 \n3578 1 3 \n3579 1 6 \n3580 1 3 \n3581 1 3 \n3582 0 7 \n3583 0 3 \n3584 0 4 \n3585 1 3 \n3586 2 4 \n3587 2 4 \n3588 0 6 \n3589 1 5 \n3590 1 4 \n3591 1 3 \n3592 0 4 \n3593 2 3 \n3594 0 5 \n3595 1 1 \n3596 2 3 \n3597 1 5 \n3598 2 2 \n3599 1 4 \n3600 1 5 \n3601 1 6 \n3602 1 3 \n3603 2 3 \n3604 1 4 \n3605 1 5 \n3606 1 1 \n3607 1 2 \n3608 1 4 \n3609 1 4 \n3610 1 5 \n3611 2 2 \n3612 0 5 \n3613 1 2 \n3614 1 5 \n3615 1 1 \n3616 0 5 \n3617 1 5 \n3618 2 3 \n3619 1 5 \n3620 1 3 \n3621 0 7 \n3622 0 6 \n3623 1 3 \n3624 1 3 \n3625 1 4 \n3626 1 3 \n3627 2 4 \n3628 1 4 \n3629 1 6 \n3630 1 3 \n3631 0 5 \n3632 1 5 \n3633 1 4 \n3634 1 4 \n3635 2 3 \n3636 1 4 \n3637 0 3 \n3638 1 5 \n3639 0 3 \n3640 0 4 \n3641 1 4 \n3642 1 4 \n3643 2 3 \n3644 1 2 \n3645 1 5 \n3646 1 2 \n3647 0 3 \n3648 1 4 \n3649 1 5 \n3650 0 5 \n3651 1 4 \n3652 1 3 \n3653 4 0 \n3654 2 3 \n3655 1 5 \n3656 1 4 \n3657 0 4 \n3658 1 4 \n3659 1 4 \n3660 1 1 \n3661 1 5 \n3662 1 5 \n3663 0 4 \n3664 1 4 \n3665 0 4 \n3666 1 5 \n3667 1 2 \n3668 1 5 \n3669 1 3 \n3670 2 2 \n3671 1 4 \n3672 2 3 \n3673 0 6 \n3674 0 5 \n3675 1 6 \n3676 0 2 \n3677 2 4 \n3678 0 5 \n3679 1 5 \n3680 0 5 \n3681 2 2 \n3682 1 3 \n3683 0 4 \n3684 1 4 \n3685 1 4 \n3686 1 3 \n3687 1 5 \n3688 0 7 \n3689 1 5 \n3690 1 2 \n3691 1 4 \n3692 1 2 \n3693 1 5 \n3694 1 3 \n3695 1 3 \n3696 1 3 \n3697 1 2 \n3698 0 2 \n3699 1 5 \n3700 0 5 \n3701 1 4 \n3702 1 3 \n3703 2 3 \n3704 1 4 \n3705 0 6 \n3706 1 4 \n3707 1 5 \n3708 1 3 \n3709 2 3 \n3710 1 2 \n3711 1 4 \n3712 0 4 \n3713 1 3 \n3714 1 5 \n3715 1 3 \n3716 0 3 \n3717 0 2 \n3718 1 4 \n3719 0 2 \n3720 1 3 \n3721 0 7 \n3722 1 5 \n3723 1 4 \n3724 0 6 \n3725 0 4 \n3726 0 2 \n3727 1 5 \n3728 0 6 \n3729 1 5 \n3730 1 4 \n3731 1 3 \n3732 1 4 \n3733 1 4 \n3734 0 5 \n3735 1 3 \n3736 2 3 \n3737 0 3 \n3738 0 4 \n3739 2 2 \n3740 2 3 \n3741 1 2 \n3742 1 5 \n3743 0 5 \n3744 1 2 \n3745 1 5 \n3746 1 3 \n3747 1 4 \n3748 1 3 \n3749 1 3 \n3750 0 5 \n3751 1 5 \n3752 1 4 \n3753 1 3 \n3754 1 4 \n3755 0 5 \n3756 1 3 \n3757 1 4 \n3758 0 3 \n3759 1 3 \n3760 1 4 \n3761 2 3 \n3762 0 4 \n3763 1 5 \n3764 0 4 \n3765 1 3 \n3766 1 3 \n3767 1 3 \n3768 0 4 \n3769 1 4 \n3770 1 3 \n3771 0 6 \n3772 0 6 \n3773 1 4 \n3774 1 4 \n3775 0 5 \n3776 0 5 \n3777 0 6 \n3778 0 4 \n3779 0 4 \n3780 1 5 \n3781 1 3 \n3782 1 5 \n3783 1 3 \n3784 1 5 \n3785 1 4 \n3786 1 2 \n3787 0 5 \n3788 1 4 \n3789 1 1 \n3790 2 2 \n3791 1 4 \n3792 1 4 \n3793 1 4 \n3794 1 1 \n3795 1 3 \n3796 2 3 \n3797 1 5 \n3798 1 4 \n3799 0 4 \n3800 2 2 \n3801 1 2 \n3802 1 3 \n3803 0 5 \n3804 1 4 \n3805 2 2 \n3806 0 4 \n3807 1 1 \n3808 1 3 \n3809 0 6 \n3810 1 3 \n3811 1 2 \n3812 0 6 \n3813 1 2 \n3814 2 2 \n3815 0 5 \n3816 0 4 \n3817 1 4 \n3818 0 3 \n3819 0 4 \n3820 1 4 \n3821 0 5 \n3822 1 3 \n3823 2 2 \n3824 1 5 \n3825 1 5 \n3826 1 4 \n3827 1 4 \n3828 0 4 \n3829 1 2 \n3830 2 3 \n3831 1 2 \n3832 1 2 \n3833 1 3 \n3834 1 1 \n3835 1 4 \n3836 3 0 \n3837 1 2 \n3838 1 2 \n3839 1 2 \n3840 1 3 \n3841 1 4 \n3842 1 3 \n3843 1 2 \n3844 0 4 \n3845 1 3 \n3846 0 3 \n3847 0 5 \n3848 0 6 \n3849 1 4 \n3850 0 4 \n3851 1 3 \n3852 0 6 \n3853 1 1 \n3854 1 2 \n3855 1 2 \n3856 1 3 \n3857 2 2 \n3858 2 2 \n3859 0 3 \n3860 0 5 \n3861 0 4 \n3862 2 2 \n3863 1 3 \n3864 1 4 \n3865 1 4 \n3866 1 3 \n3867 1 5 \n3868 0 3 \n3869 1 4 \n3870 1 3 \n3871 0 5 \n3872 1 4 \n3873 0 4 \n3874 0 2 \n3875 1 1 \n3876 1 3 \n3877 1 4 \n3878 1 2 \n3879 1 4 \n3880 2 2 \n3881 3 0 \n3882 0 4 \n3883 2 2 \n3884 0 5 \n3885 1 4 \n3886 1 3 \n3887 0 3 \n3888 1 3 \n3889 1 1 \n3890 1 3 \n3891 0 6 \n3892 0 4 \n3893 0 5 \n3894 0 3 \n3895 1 4 \n3896 0 5 \n3897 1 3 \n3898 1 4 \n3899 2 2 \n3900 1 2 \n3901 1 1 \n3902 1 2 \n3903 0 4 \n3904 1 4 \n3905 0 5 \n3906 0 4 \n3907 0 6 \n3908 1 3 \n3909 1 2 \n3910 1 2 \n3911 0 3 \n3912 0 4 \n3913 0 4 \n3914 0 4 \n3915 1 3 \n3916 1 4 \n3917 0 2 \n3918 1 2 \n3919 1 3 \n3920 1 2 \n3921 1 4 \n3922 0 3 \n3923 1 4 \n3924 1 3 \n3925 1 3 \n3926 0 4 \n3927 0 4 \n3928 0 5 \n3929 1 3 \n3930 1 4 \n3931 1 3 \n3932 0 3 \n3933 0 3 \n3934 0 5 \n3935 1 2 \n3936 0 4 \n3937 1 3 \n3938 0 5 \n3939 1 4 \n3940 1 2 \n3941 1 2 \n3942 0 3 \n3943 1 2 \n3944 0 5 \n3945 1 2 \n3946 1 2 \n3947 1 2 \n3948 1 1 \n3949 1 1 \n3950 0 2 \n3951 1 4 \n3952 0 3 \n3953 1 2 \n3954 1 3 \n3955 0 4 \n3956 0 5 \n3957 0 3 \n3958 0 2 \n3959 1 4 \n3960 0 4 \n3961 0 4 \n3962 1 3 \n3963 2 1 \n3964 0 5 \n3965 1 3 \n3966 2 1 \n3967 0 3 \n3968 0 2 \n3969 1 3 \n3970 0 4 \n3971 1 3 \n3972 2 0 \n3973 1 3 \n3974 0 3 \n3975 0 3 \n3976 0 5 \n3977 1 3 \n3978 1 3 \n3979 0 3 \n3980 0 4 \n3981 3 0 \n3982 0 4 \n3983 1 2 \n3984 1 4 \n3985 2 1 \n3986 0 2 \n3987 3 0 \n3988 0 4 \n3989 0 5 \n3990 1 2 \n3991 1 2 \n3992 1 3 \n3993 0 5 \n3994 0 2 \n3995 0 3 \n3996 1 3 \n3997 0 3 \n3998 1 3 \n3999 0 4 \n4000 1 1 \n4001 1 3 \n4002 1 1 \n4003 0 3 \n4004 0 4 \n4005 1 1 \n4006 0 4 \n4007 2 1 \n4008 2 1 \n4009 0 3 \n4010 1 3 \n4011 1 2 \n4012 0 3 \n4013 0 5 \n4014 2 1 \n4015 1 1 \n4016 1 3 \n4017 0 4 \n4018 0 4 \n4019 0 3 \n4020 1 3 \n4021 0 4 \n4022 0 4 \n4023 1 2 \n4024 0 3 \n4025 1 2 \n4026 0 3 \n4027 1 3 \n4028 0 2 \n4029 0 3 \n4030 1 1 \n4031 0 4 \n4032 1 1 \n4033 0 3 \n4034 0 4 \n4035 1 2 \n4036 0 4 \n4037 0 3 \n4038 0 2 \n4039 1 3 \n4040 1 1 \n4041 0 2 \n4042 1 2 \n4043 0 2 \n4044 2 0 \n4045 0 3 \n4046 1 2 \n4047 0 4 \n4048 0 2 \n4049 1 2 \n4050 0 3 \n4051 0 3 \n4052 2 0 \n4053 0 3 \n4054 0 2 \n4055 0 4 \n4056 0 3 \n4057 0 2 \n4058 1 2 \n4059 0 2 \n4060 1 2 \n4061 1 2 \n4062 2 0 \n4063 1 2 \n4064 0 3 \n4065 0 3 \n4066 2 0 \n4067 1 2 \n4068 0 3 \n4069 0 2 \n4070 0 2 \n4071 2 0 \n4072 0 2 \n4073 0 3 \n4074 0 2 \n4075 0 3 \n4076 1 1 \n4077 1 1 \n4078 1 1 \n4079 0 2 \n4080 1 1 \n4081 0 2 \n4082 0 2 "
  479. },
  480. "metadata": {},
  481. "output_type": "display_data"
  482. }
  483. ]
  484. },
  485. {
  486. "metadata": {
  487. "trusted": true
  488. },
  489. "cell_type": "code",
  490. "source": "# input: top_combi, df_allcombi, final_df\n\ntop_combi = 10\n\nt0 = time.time()\nprint(\"Combi | Sharpe\")\nnum_long_array=[]\nnum_short_array=[]\ncombi_index_array=[]\ncombi_array=[]\nsharpe_array=[]\nulcer_array=[]\ncorr_array=[]\nmaxdd_array=[]\ndf_combined_array=[]\nmetric_dict_array=[]\nfor combi in df_allcombi[:10]['Combinations']:\n \n num_long = 0\n num_short = 0\n for i in combi:\n if final.loc[i]['Direction'][0]=='L':\n num_long=num_long+1\n elif final.loc[i]['Direction'][0]=='S':\n num_short=num_short+1\n num_long_array.append(num_long)\n num_short_array.append(num_short)\n \n df_combined = pd.DataFrame()\n df_combined, metric_dict = DoCombine([df_list[i] for i in combi], df_bench, \n np.ones(len(combi)) , 1, OOS_Date = OOS_date,Opti=False,Metrics=False)\n df_combined.name = len(combi_array)\n df_combined_array.append(df_combined.copy())\n metric_dict_array.append(metric_dict.copy())\n \n combi_index_array.append(len(combi_array))\n combi_array.append(combi)\n sharpe_array.append(metric_dict['Combined']['Strategy']['Sharpe'])\n ulcer_array.append(metric_dict['Combined']['Strategy']['Ulcer'])\n corr_array.append(DoCorrMatrix(df_combined).loc['Combined Return','Benchmark Returns'])\n maxdd_array.append(metric_dict['Combined']['Strategy']['MaxDrawdown'])\n print(combi, \" | \",metric_dict['Combined']['Strategy']['Sharpe'])\n \nt1 = time.time()\n\n \ndf_topcombi = pd.DataFrame({'Combi Index':combi_index_array,'Combinations':combi_array, 'Sharpe':sharpe_array,\n 'Ulcer':ulcer_array,'Correlation':corr_array,'Max DD':maxdd_array,\n 'LongRules':num_long_array,'ShortRules':num_short_array})\ndf_topcombi =df_topcombi.set_index('Combi Index')\n\nprint(\"Run Time:\",t1-t0, \"Seconds\")\n\n\n# return combi_array,df_combined_dict,metric_dict_array,df_topcombi",
  491. "execution_count": 127,
  492. "outputs": [
  493. {
  494. "name": "stdout",
  495. "output_type": "stream",
  496. "text": "Combi | Sharpe\n[400, 593, 217, 102, 116, 136, 167] | 2.675198323681977\n[225, 400, 593, 102, 116, 136, 167] | 2.6612025030766353\n[400, 593, 572, 217, 102, 116, 136, 167] | 2.6426119545610405\n[400, 593, 572, 102, 116, 136, 167] | 2.642498962603359\n[400, 593, 102, 116, 136, 167] | 2.6336344279418795\n[225, 400, 593, 572, 102, 116, 136, 167] | 2.6163476635666743\n[225, 400, 593, 217, 102, 116, 136, 167] | 2.609441137637003\n[225, 400, 593, 572, 217, 102, 116, 136, 167] | 2.5644016897321515\n[400, 217, 102, 116, 136, 167] | 2.5346222854734197\n[593, 572, 217, 102, 116, 136, 167] | 2.5233523881240196\nRun Time: 346.33125948905945 Seconds\n"
  497. }
  498. ]
  499. },
  500. {
  501. "metadata": {
  502. "trusted": true
  503. },
  504. "cell_type": "code",
  505. "source": "df_topcombi = df_topcombi.sort_values(by=\"Sharpe\", ascending = False)\nwith pd.option_context('display.max_rows', None, 'display.max_columns', None):\n display(df_topcombi[['Combinations','Sharpe','Ulcer','Correlation','Max DD','LongRules','ShortRules']]\n .style.apply(highlight_max, subset=['Sharpe','Ulcer'])\n .apply(highlight_min, subset=['Max DD']))",
  506. "execution_count": 128,
  507. "outputs": [
  508. {
  509. "data": {
  510. "text/html": "<style type=\"text/css\" >\n #T_dc6aaf08_269c_11e8_8f5a_002683143c82row0_col1 {\n background-color: lightgreen;\n } #T_dc6aaf08_269c_11e8_8f5a_002683143c82row4_col2 {\n background-color: lightgreen;\n } #T_dc6aaf08_269c_11e8_8f5a_002683143c82row8_col4 {\n background-color: red;\n }</style> \n<table id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82\" > \n<thead> <tr> \n <th class=\"blank level0\" ></th> \n <th class=\"col_heading level0 col0\" >Combinations</th> \n <th class=\"col_heading level0 col1\" >Sharpe</th> \n <th class=\"col_heading level0 col2\" >Ulcer</th> \n <th class=\"col_heading level0 col3\" >Correlation</th> \n <th class=\"col_heading level0 col4\" >Max DD</th> \n <th class=\"col_heading level0 col5\" >LongRules</th> \n <th class=\"col_heading level0 col6\" >ShortRules</th> \n </tr> <tr> \n <th class=\"index_name level0\" >Combi Index</th> \n <th class=\"blank\" ></th> \n <th class=\"blank\" ></th> \n <th class=\"blank\" ></th> \n <th class=\"blank\" ></th> \n <th class=\"blank\" ></th> \n <th class=\"blank\" ></th> \n <th class=\"blank\" ></th> \n </tr></thead> \n<tbody> <tr> \n <th id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82level0_row0\" class=\"row_heading level0 row0\" >0</th> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row0_col0\" class=\"data row0 col0\" >[400, 593, 217, 102, 116, 136, 167]</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row0_col1\" class=\"data row0 col1\" >2.6752</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row0_col2\" class=\"data row0 col2\" >12.1843</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row0_col3\" class=\"data row0 col3\" >-0.17474</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row0_col4\" class=\"data row0 col4\" >-0.0209416</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row0_col5\" class=\"data row0 col5\" >4</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row0_col6\" class=\"data row0 col6\" >3</td> \n </tr> <tr> \n <th id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82level0_row1\" class=\"row_heading level0 row1\" >1</th> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row1_col0\" class=\"data row1 col0\" >[225, 400, 593, 102, 116, 136, 167]</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row1_col1\" class=\"data row1 col1\" >2.6612</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row1_col2\" class=\"data row1 col2\" >11.9805</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row1_col3\" class=\"data row1 col3\" >-0.16063</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row1_col4\" class=\"data row1 col4\" >-0.0181913</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row1_col5\" class=\"data row1 col5\" >4</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row1_col6\" class=\"data row1 col6\" >3</td> \n </tr> <tr> \n <th id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82level0_row2\" class=\"row_heading level0 row2\" >2</th> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row2_col0\" class=\"data row2 col0\" >[400, 593, 572, 217, 102, 116, 136, 167]</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row2_col1\" class=\"data row2 col1\" >2.64261</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row2_col2\" class=\"data row2 col2\" >10.6038</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row2_col3\" class=\"data row2 col3\" >-0.229101</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row2_col4\" class=\"data row2 col4\" >-0.0210566</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row2_col5\" class=\"data row2 col5\" >4</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row2_col6\" class=\"data row2 col6\" >4</td> \n </tr> <tr> \n <th id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82level0_row3\" class=\"row_heading level0 row3\" >3</th> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row3_col0\" class=\"data row3 col0\" >[400, 593, 572, 102, 116, 136, 167]</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row3_col1\" class=\"data row3 col1\" >2.6425</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row3_col2\" class=\"data row3 col2\" >11.5995</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row3_col3\" class=\"data row3 col3\" >-0.186307</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row3_col4\" class=\"data row3 col4\" >-0.0195925</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row3_col5\" class=\"data row3 col5\" >4</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row3_col6\" class=\"data row3 col6\" >3</td> \n </tr> <tr> \n <th id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82level0_row4\" class=\"row_heading level0 row4\" >4</th> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row4_col0\" class=\"data row4 col0\" >[400, 593, 102, 116, 136, 167]</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row4_col1\" class=\"data row4 col1\" >2.63363</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row4_col2\" class=\"data row4 col2\" >13.2164</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row4_col3\" class=\"data row4 col3\" >-0.110976</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row4_col4\" class=\"data row4 col4\" >-0.019212</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row4_col5\" class=\"data row4 col5\" >4</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row4_col6\" class=\"data row4 col6\" >2</td> \n </tr> <tr> \n <th id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82level0_row5\" class=\"row_heading level0 row5\" >5</th> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row5_col0\" class=\"data row5 col0\" >[225, 400, 593, 572, 102, 116, 136, 167]</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row5_col1\" class=\"data row5 col1\" >2.61635</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row5_col2\" class=\"data row5 col2\" >10.2093</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row5_col3\" class=\"data row5 col3\" >-0.216264</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row5_col4\" class=\"data row5 col4\" >-0.0186549</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row5_col5\" class=\"data row5 col5\" >4</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row5_col6\" class=\"data row5 col6\" >4</td> \n </tr> <tr> \n <th id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82level0_row6\" class=\"row_heading level0 row6\" >6</th> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row6_col0\" class=\"data row6 col0\" >[225, 400, 593, 217, 102, 116, 136, 167]</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row6_col1\" class=\"data row6 col1\" >2.60944</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row6_col2\" class=\"data row6 col2\" >10.9841</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row6_col3\" class=\"data row6 col3\" >-0.202235</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row6_col4\" class=\"data row6 col4\" >-0.0198318</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row6_col5\" class=\"data row6 col5\" >4</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row6_col6\" class=\"data row6 col6\" >4</td> \n </tr> <tr> \n <th id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82level0_row7\" class=\"row_heading level0 row7\" >7</th> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row7_col0\" class=\"data row7 col0\" >[225, 400, 593, 572, 217, 102, 116, 136, 167]</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row7_col1\" class=\"data row7 col1\" >2.5644</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row7_col2\" class=\"data row7 col2\" >9.39801</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row7_col3\" class=\"data row7 col3\" >-0.243874</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row7_col4\" class=\"data row7 col4\" >-0.02006</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row7_col5\" class=\"data row7 col5\" >4</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row7_col6\" class=\"data row7 col6\" >5</td> \n </tr> <tr> \n <th id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82level0_row8\" class=\"row_heading level0 row8\" >8</th> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row8_col0\" class=\"data row8 col0\" >[400, 217, 102, 116, 136, 167]</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row8_col1\" class=\"data row8 col1\" >2.53462</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row8_col2\" class=\"data row8 col2\" >9.73122</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row8_col3\" class=\"data row8 col3\" >-0.156128</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row8_col4\" class=\"data row8 col4\" >-0.0222987</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row8_col5\" class=\"data row8 col5\" >4</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row8_col6\" class=\"data row8 col6\" >2</td> \n </tr> <tr> \n <th id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82level0_row9\" class=\"row_heading level0 row9\" >9</th> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row9_col0\" class=\"data row9 col0\" >[593, 572, 217, 102, 116, 136, 167]</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row9_col1\" class=\"data row9 col1\" >2.52335</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row9_col2\" class=\"data row9 col2\" >10.9585</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row9_col3\" class=\"data row9 col3\" >-0.0752816</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row9_col4\" class=\"data row9 col4\" >-0.0143376</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row9_col5\" class=\"data row9 col5\" >4</td> \n <td id=\"T_dc6aaf08_269c_11e8_8f5a_002683143c82row9_col6\" class=\"data row9 col6\" >3</td> \n </tr></tbody> \n</table> ",
  511. "text/plain": "<pandas.io.formats.style.Styler at 0x288ca6403c8>"
  512. },
  513. "metadata": {},
  514. "output_type": "display_data"
  515. }
  516. ]
  517. },
  518. {
  519. "metadata": {
  520. "trusted": true
  521. },
  522. "cell_type": "code",
  523. "source": "print(\"Index |\",\" Combination\\n--------------------------------------------------\")\nfor x,y in zip(range(len(combi_array)),combi_array):\n print(x,\" | \",y)",
  524. "execution_count": 129,
  525. "outputs": [
  526. {
  527. "name": "stdout",
  528. "output_type": "stream",
  529. "text": "Index | Combination\n--------------------------------------------------\n0 | [400, 593, 217, 102, 116, 136, 167]\n1 | [225, 400, 593, 102, 116, 136, 167]\n2 | [400, 593, 572, 217, 102, 116, 136, 167]\n3 | [400, 593, 572, 102, 116, 136, 167]\n4 | [400, 593, 102, 116, 136, 167]\n5 | [225, 400, 593, 572, 102, 116, 136, 167]\n6 | [225, 400, 593, 217, 102, 116, 136, 167]\n7 | [225, 400, 593, 572, 217, 102, 116, 136, 167]\n8 | [400, 217, 102, 116, 136, 167]\n9 | [593, 572, 217, 102, 116, 136, 167]\n"
  530. }
  531. ]
  532. },
  533. {
  534. "metadata": {
  535. "trusted": true
  536. },
  537. "cell_type": "code",
  538. "source": "# edit\n# Choose the combination that you want to plot by its combi_index\ncombination_index = 1\n\n#=================================================================================================================\nresults_com = metric_dict_array[combination_index]['Combined']\ndf_com_results = pd.DataFrame(results_com)\ndisplay(df_com_results)\ndf_com_results\nDoPlots(df_combined, df_bench, 'Combined Return', 'SPY', ninja_start_date, ninja_end_date, OOS_date)\n#=================================================================================================================",
  539. "execution_count": 130,
  540. "outputs": [
  541. {
  542. "data": {
  543. "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Strategy</th>\n <th>IS</th>\n <th>OOS</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>CAGR</th>\n <td>0.056581</td>\n <td>0.045485</td>\n <td>0.080252</td>\n </tr>\n <tr>\n <th>Calmar</th>\n <td>3.110352</td>\n <td>3.806802</td>\n <td>4.411590</td>\n </tr>\n <tr>\n <th>LongestRecovery</th>\n <td>240.000000</td>\n <td>240.000000</td>\n <td>97.000000</td>\n </tr>\n <tr>\n <th>MaxDrawdown</th>\n <td>-0.018191</td>\n <td>-0.011948</td>\n <td>-0.018191</td>\n </tr>\n <tr>\n <th>Sharpe</th>\n <td>2.661203</td>\n <td>2.577809</td>\n <td>2.941327</td>\n </tr>\n <tr>\n <th>Ulcer</th>\n <td>11.980503</td>\n <td>9.895288</td>\n <td>16.124119</td>\n </tr>\n <tr>\n <th>Volatility</th>\n <td>0.021262</td>\n <td>0.017645</td>\n <td>0.027284</td>\n </tr>\n </tbody>\n</table>\n</div>",
  544. "text/plain": " Strategy IS OOS\nCAGR 0.056581 0.045485 0.080252\nCalmar 3.110352 3.806802 4.411590\nLongestRecovery 240.000000 240.000000 97.000000\nMaxDrawdown -0.018191 -0.011948 -0.018191\nSharpe 2.661203 2.577809 2.941327\nUlcer 11.980503 9.895288 16.124119\nVolatility 0.021262 0.017645 0.027284"
  545. },
  546. "metadata": {},
  547. "output_type": "display_data"
  548. },
  549. {
  550. "data": {
  551. "image/png": "iVBORw0KGgoAAAANSUhEUgAABM8AAAOSCAYAAABjoPdpAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
  552. "text/plain": "<matplotlib.figure.Figure at 0x288d38a4128>"
  553. },
  554. "metadata": {},
  555. "output_type": "display_data"
  556. }
  557. ]
  558. },
  559. {
  560. "metadata": {},
  561. "cell_type": "markdown",
  562. "source": "# SharpeSlices() slices the OOS (without IS) with each sample length = sample_length_days\n- The indices will increase if you shorten sample_length_days, and you might see a lot of 0, as it is flat\n- For now, it is for you reference to see how your chosen rules perform during different period\n- This function might be improved in the future"
  563. },
  564. {
  565. "metadata": {
  566. "trusted": true
  567. },
  568. "cell_type": "code",
  569. "source": "# edit\nsample_length_days = 180\n\n#================================================================================================================\nprint(\"Each Sample Length in Days: \",sample_length_days)\n\n# flat_period_threshold = 0.8 means in order to be eligible sample for mean, std dev calculation,flat period\n# must be < 80%\nfor i in range(len(df_combined_array)):\n df_combined_array[i].name = i\n df_combined_array[i]['Daily Return']=df_combined_array[i]['Combined Return'].copy()\n\ndf_stats,df_stats_same_period,combined_dict = SharpeSlices(df_combined_array,sample_length_days\n ,ninja_start_date, start_date,OOS_date, \n ninja_end_date,flat_period_threshold=1)\ndf_stats['Combinations']=combi_array\ndf_stats=df_stats.set_index('Name')",
  570. "execution_count": 131,
  571. "outputs": [
  572. {
  573. "name": "stdout",
  574. "output_type": "stream",
  575. "text": "Each Sample Length in Days: 180\nTotal Number of Periods (Samples): 5\nIS Period Index: 351 -- 1320\n"
  576. }
  577. ]
  578. },
  579. {
  580. "metadata": {
  581. "trusted": true
  582. },
  583. "cell_type": "code",
  584. "source": "# Run\n\nprint(\"=======================================================================================================\")\nprint(\"Individual Combinations' Sharpe Profiles on Different Periods\")\nwith pd.option_context('display.max_rows', None, 'display.max_columns', None):\n display(df_stats[df_stats['NumSamples']>1].style\n .apply(highlight_max, subset=['Overall Sharpe','Sharpe Mean','Sharpe Median','Sharpe Max'])\n .apply(highlight_min, subset=['NumSamples','Sharpe Min'])\n .apply(highlight_good_min, subset = ['Sharpe Std Dev']))\nprint(\"=======================================================================================================\\n\")\nprint(\"Sharpe of Different Combinations in Different Periods\")\nwith pd.option_context('display.max_rows', None, 'display.max_columns', None):\n display(combined_dict.transpose().style.apply(highlight_max).apply(highlight_min))\nprint(\"=======================================================================================================\\n\")\nprint(\"Sharpe Profiles on Each Periods Across All Combinations\")\nwith pd.option_context('display.max_rows', None, 'display.max_columns', None):\n display(df_stats_same_period.style\n .apply(highlight_max, subset=['Sharpe Mean','Sharpe Max','Sharpe Median'])\n .apply(highlight_min, subset=['Sharpe Min'])\n .apply(highlight_good_min,subset=['Sharpe Std Dev']))",
  585. "execution_count": 132,
  586. "outputs": [
  587. {
  588. "name": "stdout",
  589. "output_type": "stream",
  590. "text": "=======================================================================================================\nIndividual Combinations' Sharpe Profiles on Different Periods\n"
  591. },
  592. {
  593. "data": {
  594. "text/html": "<style type=\"text/css\" >\n #T_ea258b28_269c_11e8_b542_002683143c82row0_col0 {\n background-color: lightgreen;\n } #T_ea258b28_269c_11e8_b542_002683143c82row0_col1 {\n background-color: red;\n } #T_ea258b28_269c_11e8_b542_002683143c82row0_col2 {\n background-color: lightgreen;\n } #T_ea258b28_269c_11e8_b542_002683143c82row1_col1 {\n background-color: red;\n } #T_ea258b28_269c_11e8_b542_002683143c82row1_col4 {\n background-color: lightgreen;\n } #T_ea258b28_269c_11e8_b542_002683143c82row1_col5 {\n background-color: lightgreen;\n } #T_ea258b28_269c_11e8_b542_002683143c82row2_col1 {\n background-color: red;\n } #T_ea258b28_269c_11e8_b542_002683143c82row3_col1 {\n background-color: red;\n } #T_ea258b28_269c_11e8_b542_002683143c82row4_col1 {\n background-color: red;\n } #T_ea258b28_269c_11e8_b542_002683143c82row5_col1 {\n background-color: red;\n } #T_ea258b28_269c_11e8_b542_002683143c82row5_col6 {\n background-color: red;\n } #T_ea258b28_269c_11e8_b542_002683143c82row6_col1 {\n background-color: red;\n } #T_ea258b28_269c_11e8_b542_002683143c82row7_col1 {\n background-color: red;\n } #T_ea258b28_269c_11e8_b542_002683143c82row8_col1 {\n background-color: red;\n } #T_ea258b28_269c_11e8_b542_002683143c82row9_col1 {\n background-color: red;\n } #T_ea258b28_269c_11e8_b542_002683143c82row9_col3 {\n background-color: lightgreen;\n }</style> \n<table id=\"T_ea258b28_269c_11e8_b542_002683143c82\" > \n<thead> <tr> \n <th class=\"blank level0\" ></th> \n <th class=\"col_heading level0 col0\" >Overall Sharpe</th> \n <th class=\"col_heading level0 col1\" >NumSamples</th> \n <th class=\"col_heading level0 col2\" >Sharpe Mean</th> \n <th class=\"col_heading level0 col3\" >Sharpe Std Dev</th> \n <th class=\"col_heading level0 col4\" >Sharpe Median</th> \n <th class=\"col_heading level0 col5\" >Sharpe Max</th> \n <th class=\"col_heading level0 col6\" >Sharpe Min</th> \n <th class=\"col_heading level0 col7\" >Combinations</th> \n </tr> <tr> \n <th class=\"index_name level0\" >Name</th> \n <th class=\"blank\" ></th> \n <th class=\"blank\" ></th> \n <th class=\"blank\" ></th> \n <th class=\"blank\" ></th> \n <th class=\"blank\" ></th> \n <th class=\"blank\" ></th> \n <th class=\"blank\" ></th> \n <th class=\"blank\" ></th> \n </tr></thead> \n<tbody> <tr> \n <th id=\"T_ea258b28_269c_11e8_b542_002683143c82level0_row0\" class=\"row_heading level0 row0\" >0</th> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row0_col0\" class=\"data row0 col0\" >2.6752</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row0_col1\" class=\"data row0 col1\" >5</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row0_col2\" class=\"data row0 col2\" >2.24322</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row0_col3\" class=\"data row0 col3\" >1.34814</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row0_col4\" class=\"data row0 col4\" >2.18252</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row0_col5\" class=\"data row0 col5\" >4.21985</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row0_col6\" class=\"data row0 col6\" >0.619554</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row0_col7\" class=\"data row0 col7\" >[400, 593, 217, 102, 116, 136, 167]</td> \n </tr> <tr> \n <th id=\"T_ea258b28_269c_11e8_b542_002683143c82level0_row1\" class=\"row_heading level0 row1\" >1</th> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row1_col0\" class=\"data row1 col0\" >2.6612</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row1_col1\" class=\"data row1 col1\" >5</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row1_col2\" class=\"data row1 col2\" >1.92306</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row1_col3\" class=\"data row1 col3\" >2.40292</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row1_col4\" class=\"data row1 col4\" >2.26403</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row1_col5\" class=\"data row1 col5\" >4.81801</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row1_col6\" class=\"data row1 col6\" >-1.81555</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row1_col7\" class=\"data row1 col7\" >[225, 400, 593, 102, 116, 136, 167]</td> \n </tr> <tr> \n <th id=\"T_ea258b28_269c_11e8_b542_002683143c82level0_row2\" class=\"row_heading level0 row2\" >2</th> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row2_col0\" class=\"data row2 col0\" >2.64261</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row2_col1\" class=\"data row2 col1\" >5</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row2_col2\" class=\"data row2 col2\" >2.07426</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row2_col3\" class=\"data row2 col3\" >1.58031</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row2_col4\" class=\"data row2 col4\" >2.07696</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row2_col5\" class=\"data row2 col5\" >4.38074</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row2_col6\" class=\"data row2 col6\" >-0.00476544</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row2_col7\" class=\"data row2 col7\" >[400, 593, 572, 217, 102, 116, 136, 167]</td> \n </tr> <tr> \n <th id=\"T_ea258b28_269c_11e8_b542_002683143c82level0_row3\" class=\"row_heading level0 row3\" >3</th> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row3_col0\" class=\"data row3 col0\" >2.6425</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row3_col1\" class=\"data row3 col1\" >5</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row3_col2\" class=\"data row3 col2\" >2.05008</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row3_col3\" class=\"data row3 col3\" >1.97895</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row3_col4\" class=\"data row3 col4\" >2.10497</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row3_col5\" class=\"data row3 col5\" >4.25813</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row3_col6\" class=\"data row3 col6\" >-1.07661</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row3_col7\" class=\"data row3 col7\" >[400, 593, 572, 102, 116, 136, 167]</td> \n </tr> <tr> \n <th id=\"T_ea258b28_269c_11e8_b542_002683143c82level0_row4\" class=\"row_heading level0 row4\" >4</th> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row4_col0\" class=\"data row4 col0\" >2.63363</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row4_col1\" class=\"data row4 col1\" >5</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row4_col2\" class=\"data row4 col2\" >2.16286</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row4_col3\" class=\"data row4 col3\" >1.83026</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row4_col4\" class=\"data row4 col4\" >2.24702</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row4_col5\" class=\"data row4 col5\" >4.05765</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row4_col6\" class=\"data row4 col6\" >-0.715596</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row4_col7\" class=\"data row4 col7\" >[400, 593, 102, 116, 136, 167]</td> \n </tr> <tr> \n <th id=\"T_ea258b28_269c_11e8_b542_002683143c82level0_row5\" class=\"row_heading level0 row5\" >5</th> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row5_col0\" class=\"data row5 col0\" >2.61635</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row5_col1\" class=\"data row5 col1\" >5</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row5_col2\" class=\"data row5 col2\" >1.80384</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row5_col3\" class=\"data row5 col3\" >2.41747</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row5_col4\" class=\"data row5 col4\" >2.16749</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row5_col5\" class=\"data row5 col5\" >4.78122</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row5_col6\" class=\"data row5 col6\" >-1.95712</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row5_col7\" class=\"data row5 col7\" >[225, 400, 593, 572, 102, 116, 136, 167]</td> \n </tr> <tr> \n <th id=\"T_ea258b28_269c_11e8_b542_002683143c82level0_row6\" class=\"row_heading level0 row6\" >6</th> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row6_col0\" class=\"data row6 col0\" >2.60944</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row6_col1\" class=\"data row6 col1\" >5</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row6_col2\" class=\"data row6 col2\" >1.94728</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row6_col3\" class=\"data row6 col3\" >1.90108</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row6_col4\" class=\"data row6 col4\" >2.07078</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row6_col5\" class=\"data row6 col5\" >4.65342</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row6_col6\" class=\"data row6 col6\" >-0.660415</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row6_col7\" class=\"data row6 col7\" >[225, 400, 593, 217, 102, 116, 136, 167]</td> \n </tr> <tr> \n <th id=\"T_ea258b28_269c_11e8_b542_002683143c82level0_row7\" class=\"row_heading level0 row7\" >7</th> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row7_col0\" class=\"data row7 col0\" >2.5644</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row7_col1\" class=\"data row7 col1\" >5</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row7_col2\" class=\"data row7 col2\" >1.8143</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row7_col3\" class=\"data row7 col3\" >2.00889</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row7_col4\" class=\"data row7 col4\" >1.75334</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row7_col5\" class=\"data row7 col5\" >4.65981</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row7_col6\" class=\"data row7 col6\" >-0.985466</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row7_col7\" class=\"data row7 col7\" >[225, 400, 593, 572, 217, 102, 116, 136, 167]</td> \n </tr> <tr> \n <th id=\"T_ea258b28_269c_11e8_b542_002683143c82level0_row8\" class=\"row_heading level0 row8\" >8</th> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row8_col0\" class=\"data row8 col0\" >2.53462</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row8_col1\" class=\"data row8 col1\" >5</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row8_col2\" class=\"data row8 col2\" >2.03948</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row8_col3\" class=\"data row8 col3\" >1.25856</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row8_col4\" class=\"data row8 col4\" >1.98338</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row8_col5\" class=\"data row8 col5\" >3.86412</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row8_col6\" class=\"data row8 col6\" >0.619203</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row8_col7\" class=\"data row8 col7\" >[400, 217, 102, 116, 136, 167]</td> \n </tr> <tr> \n <th id=\"T_ea258b28_269c_11e8_b542_002683143c82level0_row9\" class=\"row_heading level0 row9\" >9</th> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row9_col0\" class=\"data row9 col0\" >2.52335</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row9_col1\" class=\"data row9 col1\" >5</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row9_col2\" class=\"data row9 col2\" >2.20957</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row9_col3\" class=\"data row9 col3\" >1.02244</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row9_col4\" class=\"data row9 col4\" >2.11605</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row9_col5\" class=\"data row9 col5\" >3.698</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row9_col6\" class=\"data row9 col6\" >1.18924</td> \n <td id=\"T_ea258b28_269c_11e8_b542_002683143c82row9_col7\" class=\"data row9 col7\" >[593, 572, 217, 102, 116, 136, 167]</td> \n </tr></tbody> \n</table> ",
  595. "text/plain": "<pandas.io.formats.style.Styler at 0x288cc0d22b0>"
  596. },
  597. "metadata": {},
  598. "output_type": "display_data"
  599. },
  600. {
  601. "name": "stdout",
  602. "output_type": "stream",
  603. "text": "=======================================================================================================\n\nSharpe of Different Combinations in Different Periods\n"
  604. },
  605. {
  606. "data": {
  607. "text/html": "<style type=\"text/css\" >\n #T_ea2c438c_269c_11e8_bb74_002683143c82row1_col2 {\n background-color: lightgreen;\n : ;\n } #T_ea2c438c_269c_11e8_bb74_002683143c82row1_col4 {\n background-color: lightgreen;\n : ;\n } #T_ea2c438c_269c_11e8_bb74_002683143c82row3_col3 {\n background-color: lightgreen;\n : ;\n } #T_ea2c438c_269c_11e8_bb74_002683143c82row4_col1 {\n background-color: lightgreen;\n : ;\n } #T_ea2c438c_269c_11e8_bb74_002683143c82row5_col0 {\n : ;\n background-color: red;\n } #T_ea2c438c_269c_11e8_bb74_002683143c82row7_col1 {\n : ;\n background-color: red;\n } #T_ea2c438c_269c_11e8_bb74_002683143c82row8_col3 {\n : ;\n background-color: red;\n } #T_ea2c438c_269c_11e8_bb74_002683143c82row9_col0 {\n background-color: lightgreen;\n : ;\n } #T_ea2c438c_269c_11e8_bb74_002683143c82row9_col2 {\n : ;\n background-color: red;\n } #T_ea2c438c_269c_11e8_bb74_002683143c82row9_col4 {\n : ;\n background-color: red;\n }</style> \n<table id=\"T_ea2c438c_269c_11e8_bb74_002683143c82\" > \n<thead> <tr> \n <th class=\"index_name level0\" >Start Index</th> \n <th class=\"col_heading level0 col0\" >0</th> \n <th class=\"col_heading level0 col1\" >180</th> \n <th class=\"col_heading level0 col2\" >1320</th> \n <th class=\"col_heading level0 col3\" >1500</th> \n <th class=\"col_heading level0 col4\" >1680</th> \n </tr></thead> \n<tbody> <tr> \n <th id=\"T_ea2c438c_269c_11e8_bb74_002683143c82level0_row0\" class=\"row_heading level0 row0\" >0</th> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row0_col0\" class=\"data row0 col0\" >0.619554</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row0_col1\" class=\"data row0 col1\" >2.68026</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row0_col2\" class=\"data row0 col2\" >4.21985</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row0_col3\" class=\"data row0 col3\" >1.51394</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row0_col4\" class=\"data row0 col4\" >2.18252</td> \n </tr> <tr> \n <th id=\"T_ea2c438c_269c_11e8_bb74_002683143c82level0_row1\" class=\"row_heading level0 row1\" >1</th> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row1_col0\" class=\"data row1 col0\" >-1.81555</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row1_col1\" class=\"data row1 col1\" >2.67215</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row1_col2\" class=\"data row1 col2\" >4.81801</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row1_col3\" class=\"data row1 col3\" >1.67667</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row1_col4\" class=\"data row1 col4\" >2.26403</td> \n </tr> <tr> \n <th id=\"T_ea2c438c_269c_11e8_bb74_002683143c82level0_row2\" class=\"row_heading level0 row2\" >2</th> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row2_col0\" class=\"data row2 col0\" >-0.00476544</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row2_col1\" class=\"data row2 col1\" >2.35965</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row2_col2\" class=\"data row2 col2\" >4.38074</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row2_col3\" class=\"data row2 col3\" >1.55871</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row2_col4\" class=\"data row2 col4\" >2.07696</td> \n </tr> <tr> \n <th id=\"T_ea2c438c_269c_11e8_bb74_002683143c82level0_row3\" class=\"row_heading level0 row3\" >3</th> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row3_col0\" class=\"data row3 col0\" >-1.07661</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row3_col1\" class=\"data row3 col1\" >3.04642</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row3_col2\" class=\"data row3 col2\" >4.25813</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row3_col3\" class=\"data row3 col3\" >1.9175</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row3_col4\" class=\"data row3 col4\" >2.10497</td> \n </tr> <tr> \n <th id=\"T_ea2c438c_269c_11e8_bb74_002683143c82level0_row4\" class=\"row_heading level0 row4\" >4</th> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row4_col0\" class=\"data row4 col0\" >-0.715596</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row4_col1\" class=\"data row4 col1\" >3.35827</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row4_col2\" class=\"data row4 col2\" >4.05765</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row4_col3\" class=\"data row4 col3\" >1.86696</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row4_col4\" class=\"data row4 col4\" >2.24702</td> \n </tr> <tr> \n <th id=\"T_ea2c438c_269c_11e8_bb74_002683143c82level0_row5\" class=\"row_heading level0 row5\" >5</th> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row5_col0\" class=\"data row5 col0\" >-1.95712</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row5_col1\" class=\"data row5 col1\" >2.28457</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row5_col2\" class=\"data row5 col2\" >4.78122</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row5_col3\" class=\"data row5 col3\" >1.74303</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row5_col4\" class=\"data row5 col4\" >2.16749</td> \n </tr> <tr> \n <th id=\"T_ea2c438c_269c_11e8_bb74_002683143c82level0_row6\" class=\"row_heading level0 row6\" >6</th> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row6_col0\" class=\"data row6 col0\" >-0.660415</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row6_col1\" class=\"data row6 col1\" >2.07078</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row6_col2\" class=\"data row6 col2\" >4.65342</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row6_col3\" class=\"data row6 col3\" >1.45332</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row6_col4\" class=\"data row6 col4\" >2.21929</td> \n </tr> <tr> \n <th id=\"T_ea2c438c_269c_11e8_bb74_002683143c82level0_row7\" class=\"row_heading level0 row7\" >7</th> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row7_col0\" class=\"data row7 col0\" >-0.985466</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row7_col1\" class=\"data row7 col1\" >1.75334</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row7_col2\" class=\"data row7 col2\" >4.65981</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row7_col3\" class=\"data row7 col3\" >1.50318</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row7_col4\" class=\"data row7 col4\" >2.14061</td> \n </tr> <tr> \n <th id=\"T_ea2c438c_269c_11e8_bb74_002683143c82level0_row8\" class=\"row_heading level0 row8\" >8</th> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row8_col0\" class=\"data row8 col0\" >0.619203</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row8_col1\" class=\"data row8 col1\" >2.54564</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row8_col2\" class=\"data row8 col2\" >3.86412</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row8_col3\" class=\"data row8 col3\" >1.18507</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row8_col4\" class=\"data row8 col4\" >1.98338</td> \n </tr> <tr> \n <th id=\"T_ea2c438c_269c_11e8_bb74_002683143c82level0_row9\" class=\"row_heading level0 row9\" >9</th> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row9_col0\" class=\"data row9 col0\" >2.6727</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row9_col1\" class=\"data row9 col1\" >2.11605</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row9_col2\" class=\"data row9 col2\" >3.698</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row9_col3\" class=\"data row9 col3\" >1.37186</td> \n <td id=\"T_ea2c438c_269c_11e8_bb74_002683143c82row9_col4\" class=\"data row9 col4\" >1.18924</td> \n </tr></tbody> \n</table> ",
  608. "text/plain": "<pandas.io.formats.style.Styler at 0x288c7e080b8>"
  609. },
  610. "metadata": {},
  611. "output_type": "display_data"
  612. },
  613. {
  614. "name": "stdout",
  615. "output_type": "stream",
  616. "text": "=======================================================================================================\n\nSharpe Profiles on Each Periods Across All Combinations\n"
  617. },
  618. {
  619. "data": {
  620. "text/html": "<style type=\"text/css\" >\n #T_ea2f9fc6_269c_11e8_b582_002683143c82row0_col4 {\n background-color: red;\n } #T_ea2f9fc6_269c_11e8_b582_002683143c82row2_col0 {\n background-color: lightgreen;\n } #T_ea2f9fc6_269c_11e8_b582_002683143c82row2_col2 {\n background-color: lightgreen;\n } #T_ea2f9fc6_269c_11e8_b582_002683143c82row2_col3 {\n background-color: lightgreen;\n } #T_ea2f9fc6_269c_11e8_b582_002683143c82row3_col1 {\n background-color: lightgreen;\n }</style> \n<table id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82\" > \n<thead> <tr> \n <th class=\"blank level0\" ></th> \n <th class=\"col_heading level0 col0\" >Sharpe Mean</th> \n <th class=\"col_heading level0 col1\" >Sharpe Std Dev</th> \n <th class=\"col_heading level0 col2\" >Sharpe Median</th> \n <th class=\"col_heading level0 col3\" >Sharpe Max</th> \n <th class=\"col_heading level0 col4\" >Sharpe Min</th> \n </tr> <tr> \n <th class=\"index_name level0\" >Period</th> \n <th class=\"blank\" ></th> \n <th class=\"blank\" ></th> \n <th class=\"blank\" ></th> \n <th class=\"blank\" ></th> \n <th class=\"blank\" ></th> \n </tr></thead> \n<tbody> <tr> \n <th id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82level0_row0\" class=\"row_heading level0 row0\" >0</th> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row0_col0\" class=\"data row0 col0\" >-0.330406</td> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row0_col1\" class=\"data row0 col1\" >1.37534</td> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row0_col2\" class=\"data row0 col2\" >-0.688006</td> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row0_col3\" class=\"data row0 col3\" >2.6727</td> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row0_col4\" class=\"data row0 col4\" >-1.95712</td> \n </tr> <tr> \n <th id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82level0_row1\" class=\"row_heading level0 row1\" >1</th> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row1_col0\" class=\"data row1 col0\" >2.48871</td> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row1_col1\" class=\"data row1 col1\" >0.477656</td> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row1_col2\" class=\"data row1 col2\" >2.45265</td> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row1_col3\" class=\"data row1 col3\" >3.35827</td> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row1_col4\" class=\"data row1 col4\" >1.75334</td> \n </tr> <tr> \n <th id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82level0_row2\" class=\"row_heading level0 row2\" >2</th> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row2_col0\" class=\"data row2 col0\" >4.3391</td> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row2_col1\" class=\"data row2 col1\" >0.389417</td> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row2_col2\" class=\"data row2 col2\" >4.31944</td> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row2_col3\" class=\"data row2 col3\" >4.81801</td> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row2_col4\" class=\"data row2 col4\" >3.698</td> \n </tr> <tr> \n <th id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82level0_row3\" class=\"row_heading level0 row3\" >3</th> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row3_col0\" class=\"data row3 col0\" >1.57902</td> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row3_col1\" class=\"data row3 col1\" >0.225641</td> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row3_col2\" class=\"data row3 col2\" >1.53633</td> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row3_col3\" class=\"data row3 col3\" >1.9175</td> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row3_col4\" class=\"data row3 col4\" >1.18507</td> \n </tr> <tr> \n <th id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82level0_row4\" class=\"row_heading level0 row4\" >4</th> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row4_col0\" class=\"data row4 col0\" >2.05755</td> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row4_col1\" class=\"data row4 col1\" >0.316471</td> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row4_col2\" class=\"data row4 col2\" >2.15405</td> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row4_col3\" class=\"data row4 col3\" >2.26403</td> \n <td id=\"T_ea2f9fc6_269c_11e8_b582_002683143c82row4_col4\" class=\"data row4 col4\" >1.18924</td> \n </tr></tbody> \n</table> ",
  621. "text/plain": "<pandas.io.formats.style.Styler at 0x288ca55d048>"
  622. },
  623. "metadata": {},
  624. "output_type": "display_data"
  625. }
  626. ]
  627. },
  628. {
  629. "metadata": {},
  630. "cell_type": "markdown",
  631. "source": "# Consistency Check, the deviation of sharpe in the chosen number of samples\n- It depends on yourself whether you want to take this into account\n- Sample_length_days at least about 4-6 months, default 180 days\n- if a sample is chosen, and one of the rules is trading < 30% of the days, the sample will be discarded for all the rules\n- if you want to change the threshold of 30%, change the input for ConsistencyCheck()"
  632. },
  633. {
  634. "metadata": {
  635. "trusted": true
  636. },
  637. "cell_type": "code",
  638. "source": "# Edit\n\nnum_random_sample_cc = 50\nsample_length_days_cc = 180\n\n#=================================================================================================================\nprint(\"Number of Random Sample: \",num_random_sample_cc)\nprint(\"Each Sample Length in Days: \",sample_length_days_cc)\n\n\n# Taking very long time\ndf_random_sample = ConsistencyCheck(df_combined_array, num_random_sample_cc, sample_length_days_cc, \n ninja_start_date, start_date, OOS_date,ninja_end_date,\n flat_period_threshold =1)\ndf_random_sample['Combinations']=combi_array\ndf_random_sample=df_random_sample.set_index('Name')\nwith pd.option_context('display.max_rows', None, 'display.max_columns', None):\n display(df_random_sample.style\n .apply(highlight_max, subset=['Overall Sharpe','Sharpe Mean','Sharpe Median','Sample Max'])\n .apply(highlight_good_min, subset = ['Sharpe Std Deviation'])\n .apply(highlight_min, subset = ['Sample Min']))",
  639. "execution_count": 133,
  640. "outputs": [
  641. {
  642. "name": "stdout",
  643. "output_type": "stream",
  644. "text": "Number of Random Sample: 50\nEach Sample Length in Days: 180\n"
  645. },
  646. {
  647. "data": {
  648. "text/html": "<style type=\"text/css\" >\n #T_ee189b5e_269c_11e8_af6d_002683143c82row0_col0 {\n background-color: lightgreen;\n } #T_ee189b5e_269c_11e8_af6d_002683143c82row0_col3 {\n background-color: lightgreen;\n } #T_ee189b5e_269c_11e8_af6d_002683143c82row1_col4 {\n background-color: lightgreen;\n } #T_ee189b5e_269c_11e8_af6d_002683143c82row4_col1 {\n background-color: lightgreen;\n } #T_ee189b5e_269c_11e8_af6d_002683143c82row5_col5 {\n background-color: red;\n } #T_ee189b5e_269c_11e8_af6d_002683143c82row9_col2 {\n background-color: lightgreen;\n }</style> \n<table id=\"T_ee189b5e_269c_11e8_af6d_002683143c82\" > \n<thead> <tr> \n <th class=\"blank level0\" ></th> \n <th class=\"col_heading level0 col0\" >Overall Sharpe</th> \n <th class=\"col_heading level0 col1\" >Sharpe Mean</th> \n <th class=\"col_heading level0 col2\" >Sharpe Std Deviation</th> \n <th class=\"col_heading level0 col3\" >Sharpe Median</th> \n <th class=\"col_heading level0 col4\" >Sample Max</th> \n <th class=\"col_heading level0 col5\" >Sample Min</th> \n <th class=\"col_heading level0 col6\" >Combinations</th> \n </tr> <tr> \n <th class=\"index_name level0\" >Name</th> \n <th class=\"blank\" ></th> \n <th class=\"blank\" ></th> \n <th class=\"blank\" ></th> \n <th class=\"blank\" ></th> \n <th class=\"blank\" ></th> \n <th class=\"blank\" ></th> \n <th class=\"blank\" ></th> \n </tr></thead> \n<tbody> <tr> \n <th id=\"T_ee189b5e_269c_11e8_af6d_002683143c82level0_row0\" class=\"row_heading level0 row0\" >0</th> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row0_col0\" class=\"data row0 col0\" >2.6752</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row0_col1\" class=\"data row0 col1\" >1.9732</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row0_col2\" class=\"data row0 col2\" >1.09357</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row0_col3\" class=\"data row0 col3\" >1.86744</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row0_col4\" class=\"data row0 col4\" >4.1923</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row0_col5\" class=\"data row0 col5\" >0.432346</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row0_col6\" class=\"data row0 col6\" >[400, 593, 217, 102, 116, 136, 167]</td> \n </tr> <tr> \n <th id=\"T_ee189b5e_269c_11e8_af6d_002683143c82level0_row1\" class=\"row_heading level0 row1\" >1</th> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row1_col0\" class=\"data row1 col0\" >2.6612</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row1_col1\" class=\"data row1 col1\" >1.97895</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row1_col2\" class=\"data row1 col2\" >1.56119</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row1_col3\" class=\"data row1 col3\" >1.86142</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row1_col4\" class=\"data row1 col4\" >4.77063</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row1_col5\" class=\"data row1 col5\" >-1.72707</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row1_col6\" class=\"data row1 col6\" >[225, 400, 593, 102, 116, 136, 167]</td> \n </tr> <tr> \n <th id=\"T_ee189b5e_269c_11e8_af6d_002683143c82level0_row2\" class=\"row_heading level0 row2\" >2</th> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row2_col0\" class=\"data row2 col0\" >2.64261</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row2_col1\" class=\"data row2 col1\" >1.88564</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row2_col2\" class=\"data row2 col2\" >1.14772</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row2_col3\" class=\"data row2 col3\" >1.72556</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row2_col4\" class=\"data row2 col4\" >4.16253</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row2_col5\" class=\"data row2 col5\" >-0.00476544</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row2_col6\" class=\"data row2 col6\" >[400, 593, 572, 217, 102, 116, 136, 167]</td> \n </tr> <tr> \n <th id=\"T_ee189b5e_269c_11e8_af6d_002683143c82level0_row3\" class=\"row_heading level0 row3\" >3</th> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row3_col0\" class=\"data row3 col0\" >2.6425</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row3_col1\" class=\"data row3 col1\" >1.99477</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row3_col2\" class=\"data row3 col2\" >1.45268</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row3_col3\" class=\"data row3 col3\" >1.65609</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row3_col4\" class=\"data row3 col4\" >4.38827</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row3_col5\" class=\"data row3 col5\" >-1.19776</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row3_col6\" class=\"data row3 col6\" >[400, 593, 572, 102, 116, 136, 167]</td> \n </tr> <tr> \n <th id=\"T_ee189b5e_269c_11e8_af6d_002683143c82level0_row4\" class=\"row_heading level0 row4\" >4</th> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row4_col0\" class=\"data row4 col0\" >2.63363</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row4_col1\" class=\"data row4 col1\" >2.05675</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row4_col2\" class=\"data row4 col2\" >1.37509</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row4_col3\" class=\"data row4 col3\" >1.79654</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row4_col4\" class=\"data row4 col4\" >4.32641</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row4_col5\" class=\"data row4 col5\" >-0.88149</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row4_col6\" class=\"data row4 col6\" >[400, 593, 102, 116, 136, 167]</td> \n </tr> <tr> \n <th id=\"T_ee189b5e_269c_11e8_af6d_002683143c82level0_row5\" class=\"row_heading level0 row5\" >5</th> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row5_col0\" class=\"data row5 col0\" >2.61635</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row5_col1\" class=\"data row5 col1\" >1.93643</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row5_col2\" class=\"data row5 col2\" >1.55519</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row5_col3\" class=\"data row5 col3\" >1.69259</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row5_col4\" class=\"data row5 col4\" >4.74767</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row5_col5\" class=\"data row5 col5\" >-1.88449</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row5_col6\" class=\"data row5 col6\" >[225, 400, 593, 572, 102, 116, 136, 167]</td> \n </tr> <tr> \n <th id=\"T_ee189b5e_269c_11e8_af6d_002683143c82level0_row6\" class=\"row_heading level0 row6\" >6</th> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row6_col0\" class=\"data row6 col0\" >2.60944</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row6_col1\" class=\"data row6 col1\" >1.89038</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row6_col2\" class=\"data row6 col2\" >1.22243</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row6_col3\" class=\"data row6 col3\" >1.71724</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row6_col4\" class=\"data row6 col4\" >4.39943</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row6_col5\" class=\"data row6 col5\" >-0.586024</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row6_col6\" class=\"data row6 col6\" >[225, 400, 593, 217, 102, 116, 136, 167]</td> \n </tr> <tr> \n <th id=\"T_ee189b5e_269c_11e8_af6d_002683143c82level0_row7\" class=\"row_heading level0 row7\" >7</th> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row7_col0\" class=\"data row7 col0\" >2.5644</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row7_col1\" class=\"data row7 col1\" >1.82726</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row7_col2\" class=\"data row7 col2\" >1.22897</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row7_col3\" class=\"data row7 col3\" >1.63717</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row7_col4\" class=\"data row7 col4\" >4.36942</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row7_col5\" class=\"data row7 col5\" >-0.921424</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row7_col6\" class=\"data row7 col6\" >[225, 400, 593, 572, 217, 102, 116, 136, 167]</td> \n </tr> <tr> \n <th id=\"T_ee189b5e_269c_11e8_af6d_002683143c82level0_row8\" class=\"row_heading level0 row8\" >8</th> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row8_col0\" class=\"data row8 col0\" >2.53462</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row8_col1\" class=\"data row8 col1\" >1.77376</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row8_col2\" class=\"data row8 col2\" >1.0538</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row8_col3\" class=\"data row8 col3\" >1.58625</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row8_col4\" class=\"data row8 col4\" >3.72637</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row8_col5\" class=\"data row8 col5\" >0.118429</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row8_col6\" class=\"data row8 col6\" >[400, 217, 102, 116, 136, 167]</td> \n </tr> <tr> \n <th id=\"T_ee189b5e_269c_11e8_af6d_002683143c82level0_row9\" class=\"row_heading level0 row9\" >9</th> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row9_col0\" class=\"data row9 col0\" >2.52335</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row9_col1\" class=\"data row9 col1\" >1.79477</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row9_col2\" class=\"data row9 col2\" >0.925762</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row9_col3\" class=\"data row9 col3\" >1.73901</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row9_col4\" class=\"data row9 col4\" >3.40506</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row9_col5\" class=\"data row9 col5\" >-0.0930076</td> \n <td id=\"T_ee189b5e_269c_11e8_af6d_002683143c82row9_col6\" class=\"data row9 col6\" >[593, 572, 217, 102, 116, 136, 167]</td> \n </tr></tbody> \n</table> ",
  649. "text/plain": "<pandas.io.formats.style.Styler at 0x288ca5592e8>"
  650. },
  651. "metadata": {},
  652. "output_type": "display_data"
  653. }
  654. ]
  655. },
  656. {
  657. "metadata": {
  658. "trusted": true
  659. },
  660. "cell_type": "markdown",
  661. "source": "# Generate multisignal .cs file and move to Ninja Folder\n- Choose the combination by giving the index"
  662. },
  663. {
  664. "metadata": {
  665. "trusted": true
  666. },
  667. "cell_type": "code",
  668. "source": "chosen_combi_index = 1\n\nchosen_combi_rule_numbers = combi_array[chosen_combi_index]\ncombi_rules,ms_output_filename=WriteMultiSignalCS(ins_and_timeframe,chosen_combi_rule_numbers,\n all_rules_list, long_short_list, TP, SL)\n\nms_output_file = ms_output_filename+'.cs'\n\n# print(\"ms output_file: \",ms_output_file)\n# print(\"ninja_local_rel_path:\",os.path.join(ninja_local_rel_path,output_file))\n\nif Path(ms_output_file).is_file():\n print(\"Path is file\",Path(ms_output_file).is_file())\n shutil.move(ms_output_file,os.path.join(ninja_local_rel_path,ms_output_file))\n print(\"\\nCS File Moved to C:\\\\Users\\\\Workstation\\\\Documents\\\\NinjaTrader 8\\\\bin\\\\Custom\\\\Strategies\")\n print(\"\\nFile Name: \",ms_output_file)",
  669. "execution_count": 65,
  670. "outputs": [
  671. {
  672. "name": "stdout",
  673. "output_type": "stream",
  674. "text": "..\\..\\..\\..\\Documents\\NinjaTrader 8\\bin\\Custom\\Strategies\\cxt-strategies\\Miscellaneous\\System_DLPALOptimizer.cs\nFile exists\n----------------------------\nSuccessfully Created :MS_AMLP_M60_3L1S_TP2_SL2.cs\n----------------------------\n\nNinja Script Created.\nPath is file True\n\nCS File Moved to C:\\Users\\Workstation\\Documents\\NinjaTrader 8\\bin\\Custom\\Strategies\n\nFile Name: MS_AMLP_M60_3L1S_TP2_SL2.cs\n"
  675. }
  676. ]
  677. },
  678. {
  679. "metadata": {},
  680. "cell_type": "markdown",
  681. "source": "# Import the return output generated by Ninja"
  682. },
  683. {
  684. "metadata": {
  685. "trusted": true
  686. },
  687. "cell_type": "code",
  688. "source": "\n# Run\n\nms_opti_backtest_path=\"C:\\\\Algos\\\\Backtest\\\\\"+ms_output_filename\nprint(\"Output Files are in: \",opti_backtest_path)\n\nColumns = ['Date', 'Model', 'Daily Return', 'Equity', 'Allocations', 'Attributions']\nTargetColName = 'Daily Return'\nSkipfooter = 1\n\nresult = glob.glob(opti_backtest_path + '\\\\*.csv')\n\ntry:\n os.remove(opti_backtest_path +'\\\\_Combine.cmd')\nexcept OSError:\n pass\n\nFileSwitch = np.repeat(True, len(result))\nWeights = 1\nLeverage = 1\n\ndf_multisignal = DoFolderImport(opti_backtest_path, FileSwitch ,Columns,Skipfooter)\ndf_multisignal = df_multisignal[0].copy()\n\nprint(\"Sharpe of the Multisignal is: \",get_sharpe(df_multisignal))",
  689. "execution_count": 81,
  690. "outputs": [
  691. {
  692. "name": "stdout",
  693. "output_type": "stream",
  694. "text": "Output Files are in: C:\\Algos\\Backtest\\MS_AMLP_M60_3L1S_TP2_SL2\nImporting C:\\Algos\\Backtest\\MS_AMLP_M60_3L1S_TP2_SL2\\AMLP-00000.csv with first row as headers\nAMLP-00000 has been imported!\nSharpe of the Multisignal is: 1.9514215149013145\n"
  695. }
  696. ]
  697. },
  698. {
  699. "metadata": {},
  700. "cell_type": "markdown",
  701. "source": "# Metric of the Multisignal Strat \n- Might need to adjust the Leveraging Factor in Ninja if too many rules\n- The metrics should not deviate too far away from doing DoCombine as shown above"
  702. },
  703. {
  704. "metadata": {
  705. "trusted": true
  706. },
  707. "cell_type": "code",
  708. "source": "multisignal_metric = GetMetricsSplit(df_multisignal,'Daily Return',ninja_start_date, ninja_end_date, OOS_date)\nmultisignal_metric_df = pd.DataFrame(multisignal_metric)\ndisplay(multisignal_metric_df)\nDoPlots(df_multisignal, df_bench, 'Daily Return', 'SPY', ninja_start_date, ninja_end_date, OOS_date)",
  709. "execution_count": 90,
  710. "outputs": [
  711. {
  712. "data": {
  713. "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Strategy</th>\n <th>IS</th>\n <th>OOS</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>CAGR</th>\n <td>0.042160</td>\n <td>0.041395</td>\n <td>0.043774</td>\n </tr>\n <tr>\n <th>Calmar</th>\n <td>2.650371</td>\n <td>3.262131</td>\n <td>2.751834</td>\n </tr>\n <tr>\n <th>LongestRecovery</th>\n <td>111.000000</td>\n <td>111.000000</td>\n <td>81.000000</td>\n </tr>\n <tr>\n <th>MaxDrawdown</th>\n <td>-0.015907</td>\n <td>-0.012690</td>\n <td>-0.015907</td>\n </tr>\n <tr>\n <th>Sharpe</th>\n <td>1.951422</td>\n <td>2.230301</td>\n <td>1.626205</td>\n </tr>\n <tr>\n <th>Ulcer</th>\n <td>10.616628</td>\n <td>11.388760</td>\n <td>9.967649</td>\n </tr>\n <tr>\n <th>Volatility</th>\n <td>0.021605</td>\n <td>0.018560</td>\n <td>0.026918</td>\n </tr>\n </tbody>\n</table>\n</div>",
  714. "text/plain": " Strategy IS OOS\nCAGR 0.042160 0.041395 0.043774\nCalmar 2.650371 3.262131 2.751834\nLongestRecovery 111.000000 111.000000 81.000000\nMaxDrawdown -0.015907 -0.012690 -0.015907\nSharpe 1.951422 2.230301 1.626205\nUlcer 10.616628 11.388760 9.967649\nVolatility 0.021605 0.018560 0.026918"
  715. },
  716. "metadata": {},
  717. "output_type": "display_data"
  718. },
  719. {
  720. "data": {
  721. "image/png": "iVBORw0KGgoAAAANSUhEUgAABM8AAAOSCAYAAABjoPdpAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYII=\n",
  722. "text/plain": "<matplotlib.figure.Figure at 0x288cbfee400>"
  723. },
  724. "metadata": {},
  725. "output_type": "display_data"
  726. }
  727. ]
  728. },
  729. {
  730. "metadata": {},
  731. "cell_type": "markdown",
  732. "source": "# Future Improvements:\n- Improve the speed of df_allcombi, because it uses the dict and calculated everything.\n- Improve the speed of DoFolderImport\n- DoImport instead of DoFolderImport in Multisignal strat stage"
  733. },
  734. {
  735. "metadata": {
  736. "trusted": true,
  737. "collapsed": true
  738. },
  739. "cell_type": "code",
  740. "source": "",
  741. "execution_count": null,
  742. "outputs": []
  743. }
  744. ],
  745. "metadata": {
  746. "kernelspec": {
  747. "name": "python3",
  748. "display_name": "Python 3",
  749. "language": "python"
  750. },
  751. "language_info": {
  752. "name": "python",
  753. "version": "3.6.3",
  754. "mimetype": "text/x-python",
  755. "codemirror_mode": {
  756. "name": "ipython",
  757. "version": 3
  758. },
  759. "pygments_lexer": "ipython3",
  760. "nbconvert_exporter": "python",
  761. "file_extension": ".py"
  762. },
  763. "widgets": {
  764. "application/vnd.jupyter.widget-state+json": {
  765. "version_major": 2,
  766. "version_minor": 0,
  767. "state": {}
  768. }
  769. }
  770. },
  771. "nbformat": 4,
  772. "nbformat_minor": 2
  773. }
Add Comment
Please, Sign In to add comment
Public Pastes
We use cookies for various purposes including analytics. By continuing to use Pastebin, you agree to our use of cookies as described in the Cookies Policy.  OK, I Understand
Not a member of Pastebin yet?
Sign Up, it unlocks many cool features!