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  1. {
  2. "cells": [
  3. {
  4. "cell_type": "code",
  5. "execution_count": 1,
  6. "metadata": {},
  7. "outputs": [],
  8. "source": [
  9. "%matplotlib inline\n",
  10. "%config InlineBackend.figure_format='retina'"
  11. ]
  12. },
  13. {
  14. "cell_type": "code",
  15. "execution_count": 2,
  16. "metadata": {},
  17. "outputs": [],
  18. "source": [
  19. "from matplotlib import rc\n",
  20. "# rc('font', **{'serif': ['Computer Modern'], 'size':22})\n",
  21. "# rc('font', **{'family': 'serif', 'serif': ['Computer Modern'], 'size':22})\n",
  22. "rc('text', usetex=True)\n",
  23. "rc('xtick', labelsize=16) \n",
  24. "rc('ytick', labelsize=16) \n",
  25. "rc('axes', labelsize=20) # fontsize of the x and y labels\n",
  26. "\n",
  27. "import xarray as xr\n",
  28. "import numpy as np\n",
  29. "import matplotlib.pyplot as plt"
  30. ]
  31. },
  32. {
  33. "cell_type": "code",
  34. "execution_count": 3,
  35. "metadata": {},
  36. "outputs": [],
  37. "source": [
  38. "from dask.distributed import Client\n",
  39. "c = Client()"
  40. ]
  41. },
  42. {
  43. "cell_type": "code",
  44. "execution_count": 4,
  45. "metadata": {},
  46. "outputs": [],
  47. "source": [
  48. "genfolder = '/g/data/v45/nc3020/SOchanBcBtEddySat/'\n",
  49. "\n",
  50. "layer1cases = [['layer1/'+'layer1_tau1e-3_manyshortridges/', 10],\n",
  51. " ['layer1/'+'layer1_tau5e-3_manyshortridges/', 7],\n",
  52. " ['layer1/'+'layer1_tau2e-2_manyshortridges/', 10],\n",
  53. " ['layer1/'+'layer1_tau5e-2_manyshortridges/', 20],\n",
  54. " ['layer1/'+'layer1_tau1e-1_manyshortridges/', 10]];"
  55. ]
  56. },
  57. {
  58. "cell_type": "code",
  59. "execution_count": 5,
  60. "metadata": {},
  61. "outputs": [],
  62. "source": [
  63. "def compute_timemean(field, meanname):\n",
  64. " meanfield = field.mean(dim='Time')\n",
  65. " meanfield = meanfield.rename(meanname)\n",
  66. " return meanfield \n",
  67. "\n",
  68. "def compute_KE(folder, yearequilibrate):\n",
  69. "\n",
  70. " FileList = folder + 'output*/prog.nc'\n",
  71. "\n",
  72. " dsx = xr.open_mfdataset(FileList, concat_dim='Time', decode_times=False, engine='netcdf4')\n",
  73. " dsx.coords['Time'] = dsx.coords['Time']/(365) # change time units from days to years\n",
  74. " dsx.Time.attrs['units'] = 'years'\n",
  75. " \n",
  76. " dsx = dsx.sel(Time=slice(yearequilibrate, None))\n",
  77. " \n",
  78. " KE = 0.5*dsx.u**2\n",
  79. " KE = KE.rename('KE')\n",
  80. "\n",
  81. " KEtot = KE.sum(dim={'xq', 'yh', 'zl'}).values[0]\n",
  82. " \n",
  83. " return KEtot"
  84. ]
  85. },
  86. {
  87. "cell_type": "code",
  88. "execution_count": 6,
  89. "metadata": {},
  90. "outputs": [
  91. {
  92. "name": "stdout",
  93. "output_type": "stream",
  94. "text": [
  95. "0\n"
  96. ]
  97. },
  98. {
  99. "name": "stderr",
  100. "output_type": "stream",
  101. "text": [
  102. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  103. "distributed.nanny - WARNING - Worker process 7806 was killed by unknown signal\n",
  104. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  105. "distributed.nanny - WARNING - Restarting worker\n",
  106. "distributed.nanny - WARNING - Worker process 7802 was killed by unknown signal\n",
  107. "distributed.nanny - WARNING - Restarting worker\n",
  108. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  109. "distributed.nanny - WARNING - Worker process 7811 was killed by unknown signal\n",
  110. "distributed.nanny - WARNING - Restarting worker\n",
  111. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  112. "distributed.nanny - WARNING - Worker process 7803 was killed by unknown signal\n",
  113. "distributed.nanny - WARNING - Restarting worker\n",
  114. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  115. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  116. "distributed.nanny - WARNING - Worker process 7807 was killed by unknown signal\n",
  117. "distributed.nanny - WARNING - Worker process 7809 was killed by unknown signal\n",
  118. "distributed.nanny - WARNING - Restarting worker\n",
  119. "distributed.nanny - WARNING - Restarting worker\n",
  120. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  121. "distributed.nanny - WARNING - Worker process 7801 was killed by unknown signal\n",
  122. "distributed.nanny - WARNING - Restarting worker\n",
  123. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  124. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  125. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  126. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  127. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  128. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  129. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  130. "distributed.nanny - WARNING - Worker process 8084 was killed by unknown signal\n",
  131. "distributed.nanny - WARNING - Restarting worker\n",
  132. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  133. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  134. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  135. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  136. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  137. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  138. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  139. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  140. "distributed.nanny - WARNING - Worker process 8112 was killed by unknown signal\n",
  141. "distributed.nanny - WARNING - Restarting worker\n",
  142. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  143. "distributed.nanny - WARNING - Worker process 7805 was killed by unknown signal\n",
  144. "distributed.nanny - WARNING - Restarting worker\n",
  145. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  146. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  147. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  148. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  149. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  150. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  151. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  152. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  153. "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
  154. "distributed.nanny - WARNING - Worker process 8070 was killed by unknown signal\n",
  155. "distributed.nanny - WARNING - Restarting worker\n"
  156. ]
  157. },
  158. {
  159. "ename": "KilledWorker",
  160. "evalue": "(\"('open_dataset-getitem-a3605cb894c4c68a696d2bdf8f247c66', 0, 0, 0, 0)\", 'tcp://127.0.0.1:35365')",
  161. "output_type": "error",
  162. "traceback": [
  163. "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
  164. "\u001b[0;31mKilledWorker\u001b[0m Traceback (most recent call last)",
  165. "\u001b[0;32m<ipython-input-6-3f4ff5f487b1>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mdsx_geom\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mxr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mopen_mfdataset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfolder\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m'output000/ocean_geometry.nc'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconcat_dim\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Time'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdecode_times\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mengine\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'netcdf4'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 13\u001b[0;31m \u001b[0mke\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcompute_KE\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfolder\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0myearequilibrate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 14\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 15\u001b[0m \u001b[0mKE\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mj\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mke\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
  166. "\u001b[0;32m<ipython-input-5-fa998eb9c9c7>\u001b[0m in \u001b[0;36mcompute_KE\u001b[0;34m(folder, yearequilibrate)\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mFileList\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfolder\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m'output*/prog.nc'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 10\u001b[0;31m \u001b[0mdsx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mxr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mopen_mfdataset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mFileList\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconcat_dim\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Time'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdecode_times\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mengine\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'netcdf4'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 11\u001b[0m \u001b[0mdsx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcoords\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Time'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdsx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcoords\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Time'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m365\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# change time units from days to years\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[0mdsx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mattrs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'units'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'years'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
  167. "\u001b[0;32m/g/data3/hh5/public/apps/miniconda3/envs/analysis3-18.10/lib/python3.6/site-packages/xarray/backends/api.py\u001b[0m in \u001b[0;36mopen_mfdataset\u001b[0;34m(paths, chunks, concat_dim, compat, preprocess, engine, lock, data_vars, coords, autoclose, parallel, **kwargs)\u001b[0m\n\u001b[1;32m 658\u001b[0m \u001b[0mdata_vars\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdata_vars\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcoords\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcoords\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 659\u001b[0m \u001b[0minfer_order_from_coords\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0minfer_order_from_coords\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 660\u001b[0;31m ids=ids)\n\u001b[0m\u001b[1;32m 661\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 662\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mds\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mdatasets\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
  168. "\u001b[0;32m/g/data3/hh5/public/apps/miniconda3/envs/analysis3-18.10/lib/python3.6/site-packages/xarray/core/combine.py\u001b[0m in \u001b[0;36m_auto_combine\u001b[0;34m(datasets, concat_dims, compat, data_vars, coords, infer_order_from_coords, ids)\u001b[0m\n\u001b[1;32m 545\u001b[0m \u001b[0;31m# Repeatedly concatenate then merge along each dimension\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 546\u001b[0m combined = _combine_nd(combined_ids, concat_dims, compat=compat,\n\u001b[0;32m--> 547\u001b[0;31m data_vars=data_vars, coords=coords)\n\u001b[0m\u001b[1;32m 548\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mcombined\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 549\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
  169. "\u001b[0;32m/g/data3/hh5/public/apps/miniconda3/envs/analysis3-18.10/lib/python3.6/site-packages/xarray/core/combine.py\u001b[0m in \u001b[0;36m_combine_nd\u001b[0;34m(combined_ids, concat_dims, data_vars, coords, compat)\u001b[0m\n\u001b[1;32m 472\u001b[0m \u001b[0mdata_vars\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdata_vars\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 473\u001b[0m \u001b[0mcoords\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcoords\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 474\u001b[0;31m compat=compat)\n\u001b[0m\u001b[1;32m 475\u001b[0m \u001b[0mcombined_ds\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcombined_ids\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 476\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mcombined_ds\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
  170. "\u001b[0;32m/g/data3/hh5/public/apps/miniconda3/envs/analysis3-18.10/lib/python3.6/site-packages/xarray/core/combine.py\u001b[0m in \u001b[0;36m_auto_combine_all_along_first_dim\u001b[0;34m(combined_ids, dim, data_vars, coords, compat)\u001b[0m\n\u001b[1;32m 490\u001b[0m \u001b[0mdatasets\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcombined_ids\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 491\u001b[0m new_combined_ids[new_id] = _auto_combine_1d(datasets, dim, compat,\n\u001b[0;32m--> 492\u001b[0;31m data_vars, coords)\n\u001b[0m\u001b[1;32m 493\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mnew_combined_ids\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 494\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
  171. "\u001b[0;32m/g/data3/hh5/public/apps/miniconda3/envs/analysis3-18.10/lib/python3.6/site-packages/xarray/core/combine.py\u001b[0m in \u001b[0;36m_auto_combine_1d\u001b[0;34m(datasets, concat_dim, compat, data_vars, coords)\u001b[0m\n\u001b[1;32m 506\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 507\u001b[0m \u001b[0mconcatenated\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdatasets\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 508\u001b[0;31m \u001b[0mmerged\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmerge\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconcatenated\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcompat\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcompat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 509\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mmerged\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 510\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
  172. "\u001b[0;32m/g/data3/hh5/public/apps/miniconda3/envs/analysis3-18.10/lib/python3.6/site-packages/xarray/core/merge.py\u001b[0m in \u001b[0;36mmerge\u001b[0;34m(objects, compat, join)\u001b[0m\n\u001b[1;32m 520\u001b[0m for obj in objects]\n\u001b[1;32m 521\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 522\u001b[0;31m \u001b[0mvariables\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcoord_names\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdims\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmerge_core\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdict_like_objects\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcompat\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mjoin\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 523\u001b[0m \u001b[0mmerged\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mDataset\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_construct_direct\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvariables\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcoord_names\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdims\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 524\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
  173. "\u001b[0;32m/g/data3/hh5/public/apps/miniconda3/envs/analysis3-18.10/lib/python3.6/site-packages/xarray/core/merge.py\u001b[0m in \u001b[0;36mmerge_core\u001b[0;34m(objs, compat, join, priority_arg, explicit_coords, indexes)\u001b[0m\n\u001b[1;32m 439\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 440\u001b[0m \u001b[0mpriority_vars\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_get_priority_vars\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maligned\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpriority_arg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcompat\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcompat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 441\u001b[0;31m \u001b[0mvariables\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmerge_variables\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mexpanded\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpriority_vars\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcompat\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcompat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 442\u001b[0m \u001b[0massert_unique_multiindex_level_names\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvariables\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 443\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
  174. "\u001b[0;32m/g/data3/hh5/public/apps/miniconda3/envs/analysis3-18.10/lib/python3.6/site-packages/xarray/core/merge.py\u001b[0m in \u001b[0;36mmerge_variables\u001b[0;34m(list_of_variables_dicts, priority_vars, compat)\u001b[0m\n\u001b[1;32m 160\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 161\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 162\u001b[0;31m \u001b[0mmerged\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0munique_variable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvariables\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcompat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 163\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mMergeError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 164\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mcompat\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;34m'minimal'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
  175. "\u001b[0;32m/g/data3/hh5/public/apps/miniconda3/envs/analysis3-18.10/lib/python3.6/site-packages/xarray/core/merge.py\u001b[0m in \u001b[0;36munique_variable\u001b[0;34m(name, variables, compat)\u001b[0m\n\u001b[1;32m 76\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 77\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mvar\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mvariables\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 78\u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mout\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcompat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvar\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 79\u001b[0m raise MergeError('conflicting values for variable %r on '\n\u001b[1;32m 80\u001b[0m \u001b[0;34m'objects to be combined:\\n'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
  176. "\u001b[0;32m/g/data3/hh5/public/apps/miniconda3/envs/analysis3-18.10/lib/python3.6/site-packages/xarray/core/variable.py\u001b[0m in \u001b[0;36mno_conflicts\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 1483\u001b[0m \"\"\"\n\u001b[1;32m 1484\u001b[0m return self.broadcast_equals(\n\u001b[0;32m-> 1485\u001b[0;31m other, equiv=duck_array_ops.array_notnull_equiv)\n\u001b[0m\u001b[1;32m 1486\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1487\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mquantile\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mq\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdim\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minterpolation\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'linear'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
  177. "\u001b[0;32m/g/data3/hh5/public/apps/miniconda3/envs/analysis3-18.10/lib/python3.6/site-packages/xarray/core/variable.py\u001b[0m in \u001b[0;36mbroadcast_equals\u001b[0;34m(self, other, equiv)\u001b[0m\n\u001b[1;32m 1464\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mValueError\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mAttributeError\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1465\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1466\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mequals\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mother\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mequiv\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mequiv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1467\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1468\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0midentical\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
  178. "\u001b[0;32m/g/data3/hh5/public/apps/miniconda3/envs/analysis3-18.10/lib/python3.6/site-packages/xarray/core/variable.py\u001b[0m in \u001b[0;36mequals\u001b[0;34m(self, other, equiv)\u001b[0m\n\u001b[1;32m 1449\u001b[0m return (self.dims == other.dims and\n\u001b[1;32m 1450\u001b[0m (self._data is other._data or\n\u001b[0;32m-> 1451\u001b[0;31m equiv(self.data, other.data)))\n\u001b[0m\u001b[1;32m 1452\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mTypeError\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mAttributeError\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1453\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
  179. "\u001b[0;32m/g/data3/hh5/public/apps/miniconda3/envs/analysis3-18.10/lib/python3.6/site-packages/xarray/core/duck_array_ops.py\u001b[0m in \u001b[0;36marray_notnull_equiv\u001b[0;34m(arr1, arr2)\u001b[0m\n\u001b[1;32m 170\u001b[0m \u001b[0mflag_array\u001b[0m \u001b[0;34m|=\u001b[0m \u001b[0misnull\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marr2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 171\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 172\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mbool\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mflag_array\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mall\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 173\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 174\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
  180. "\u001b[0;32m/g/data3/hh5/public/apps/miniconda3/envs/analysis3-18.10/lib/python3.6/site-packages/dask/array/core.py\u001b[0m in \u001b[0;36m__bool__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1184\u001b[0m .format(self.__class__.__name__))\n\u001b[1;32m 1185\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1186\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mbool\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcompute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1187\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1188\u001b[0m \u001b[0m__nonzero__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m__bool__\u001b[0m \u001b[0;31m# python 2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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  185. "\u001b[0;32m/g/data3/hh5/public/apps/miniconda3/envs/analysis3-18.10/lib/python3.6/site-packages/distributed/client.py\u001b[0m in \u001b[0;36msync\u001b[0;34m(self, func, *args, **kwargs)\u001b[0m\n\u001b[1;32m 674\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mfuture\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 675\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 676\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0msync\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloop\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 677\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 678\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__repr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
  186. "\u001b[0;32m/g/data3/hh5/public/apps/miniconda3/envs/analysis3-18.10/lib/python3.6/site-packages/distributed/utils.py\u001b[0m in \u001b[0;36msync\u001b[0;34m(loop, func, *args, **kwargs)\u001b[0m\n\u001b[1;32m 275\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwait\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 276\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0merror\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 277\u001b[0;31m \u001b[0msix\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreraise\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0merror\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 278\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 279\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
  187. "\u001b[0;32m/g/data3/hh5/public/apps/miniconda3/envs/analysis3-18.10/lib/python3.6/site-packages/six.py\u001b[0m in \u001b[0;36mreraise\u001b[0;34m(tp, value, tb)\u001b[0m\n\u001b[1;32m 691\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__traceback__\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mtb\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 692\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwith_traceback\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 693\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 694\u001b[0m \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 695\u001b[0m \u001b[0mvalue\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
  188. "\u001b[0;32m/g/data3/hh5/public/apps/miniconda3/envs/analysis3-18.10/lib/python3.6/site-packages/distributed/utils.py\u001b[0m in \u001b[0;36mf\u001b[0;34m()\u001b[0m\n\u001b[1;32m 260\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mtimeout\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 261\u001b[0m \u001b[0mfuture\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgen\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwith_timeout\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimedelta\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mseconds\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfuture\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 262\u001b[0;31m \u001b[0mresult\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32myield\u001b[0m \u001b[0mfuture\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 263\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mexc\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 264\u001b[0m \u001b[0merror\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexc_info\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
  189. "\u001b[0;32m/g/data3/hh5/public/apps/miniconda3/envs/analysis3-18.10/lib/python3.6/site-packages/tornado/gen.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1131\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1132\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1133\u001b[0;31m \u001b[0mvalue\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfuture\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1134\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1135\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhad_exception\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
  190. "\u001b[0;32m/g/data3/hh5/public/apps/miniconda3/envs/analysis3-18.10/lib/python3.6/site-packages/tornado/gen.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1139\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mexc_info\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1140\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1141\u001b[0;31m \u001b[0myielded\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgen\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mthrow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mexc_info\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1142\u001b[0m \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1143\u001b[0m \u001b[0;31m# Break up a reference to itself\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
  191. "\u001b[0;32m/g/data3/hh5/public/apps/miniconda3/envs/analysis3-18.10/lib/python3.6/site-packages/distributed/client.py\u001b[0m in \u001b[0;36m_gather\u001b[0;34m(self, futures, errors, direct, local_worker)\u001b[0m\n\u001b[1;32m 1501\u001b[0m six.reraise(type(exception),\n\u001b[1;32m 1502\u001b[0m \u001b[0mexception\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1503\u001b[0;31m traceback)\n\u001b[0m\u001b[1;32m 1504\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0merrors\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'skip'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1505\u001b[0m \u001b[0mbad_keys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
  192. "\u001b[0;32m/g/data3/hh5/public/apps/miniconda3/envs/analysis3-18.10/lib/python3.6/site-packages/six.py\u001b[0m in \u001b[0;36mreraise\u001b[0;34m(tp, value, tb)\u001b[0m\n\u001b[1;32m 691\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__traceback__\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mtb\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 692\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwith_traceback\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 693\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 694\u001b[0m \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 695\u001b[0m \u001b[0mvalue\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
  193. "\u001b[0;31mKilledWorker\u001b[0m: (\"('open_dataset-getitem-a3605cb894c4c68a696d2bdf8f247c66', 0, 0, 0, 0)\", 'tcp://127.0.0.1:35365')"
  194. ]
  195. }
  196. ],
  197. "source": [
  198. "WS = np.array([1.e-3, 5.e-3, 2.e-2, 5.e-2, 1.e-1])\n",
  199. "KE = np.zeros(len(layer1cases))\n",
  200. "MKE = np.zeros(len(layer1cases))\n",
  201. "EKE = np.zeros(len(layer1cases))\n",
  202. " \n",
  203. "for j in np.arange(0, len(layer1cases)):\n",
  204. " print(j)\n",
  205. " folder = genfolder + layer1cases[j][0]\n",
  206. " yearequilibrate = layer1cases[j][1]\n",
  207. "\n",
  208. " dsx_geom = xr.open_mfdataset(folder + 'output000/ocean_geometry.nc', concat_dim='Time', decode_times=False, engine='netcdf4')\n",
  209. "\n",
  210. " ke = compute_KE(folder, yearequilibrate)\n",
  211. "\n",
  212. " KE[j] = ke"
  213. ]
  214. },
  215. {
  216. "cell_type": "code",
  217. "execution_count": null,
  218. "metadata": {},
  219. "outputs": [],
  220. "source": [
  221. "plt.figure()\n",
  222. "semilogx(WS, KE)"
  223. ]
  224. }
  225. ],
  226. "metadata": {
  227. "kernelspec": {
  228. "display_name": "Python [default]",
  229. "language": "python",
  230. "name": "python3"
  231. },
  232. "language_info": {
  233. "codemirror_mode": {
  234. "name": "ipython",
  235. "version": 3
  236. },
  237. "file_extension": ".py",
  238. "mimetype": "text/x-python",
  239. "name": "python",
  240. "nbconvert_exporter": "python",
  241. "pygments_lexer": "ipython3",
  242. "version": "3.6.7"
  243. }
  244. },
  245. "nbformat": 4,
  246. "nbformat_minor": 2
  247. }
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