# Untitled

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Aug 19th, 2019
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1. import numpy as np
2. import matplotlib.pyplot as plt
3. from scipy.optimize import curve_fit
4.
5.
6. datapath = '/Volumes/TOSHIBA EXT/23-07-19 - Test Pulses (22deg)/'
7. data_path_output = '/Users/marialauraperez/Desktop/SummerCERN/Results/TestPulses-22deg/'
8. first_charges = np.arange(500, 1600, 100)
9. second_charges = np.arange(2000, 12000, 1000)
10. charges = np.concatenate((first_charges, second_charges))
11. ToT_data = list()
12. mean_ToT = list()
13. energies = charges*3.62/1000
14.
15. for i in range(len(charges)):
16. matrix = np.genfromtxt(datapath+str(charges[i])+'e.txt_iToT.txt')
17. ToT_data.append(matrix)
18. mean_ToT.append(np.mean(matrix)/100)
19.
20. # isotope_energies = [5.89, 22.16, 59.54]
21. # isotope_ToTs = [14.21, 48.76, 118.28]
22. theoretical_XRF = [4.512, 5.9, 6.405, 8.046, 15.775, 17.48, 25.271, 59.5]
23. ToT_XRF = [12.05, 15.82, 16.91, 20.98, 38.83, 42.64, 58.97, 118.54]
24.
25.
26. def surrogate_function(x, a, b, c, t):
27. y = a*x + b - c/(x-t)
28. y[np.where(x < t)] = 0
29. y *= y > 0
30. return y
31.
32.
33. poptmean, pcovn = curve_fit(surrogate_function, energies, mean_ToT)
34.
35. x = np.linspace(1.5, 65, 100)
36.
37. plt.figure()
38. plt.scatter(energies, mean_ToT, s=10, label='TP Data', color='navy')
39. plt.plot(x, surrogate_function(x, *poptmean), label='TP Fit: a = '+str(np.round(poptmean[0], 3))
40. + '; b = ' + str(np.round(poptmean[1], 3))
41. + '; c = '+str(np.round(poptmean[2], 3))
42. + '; t = '+str(np.round(poptmean[3], 3)), color='blue')
43. plt.scatter(theoretical_XRF, ToT_XRF, s=10, label='Source Data', color='red')
44. plt.xlabel('Energy [keV]')
45. plt.ylabel('ToT value')
46. plt.title('Source and test pulse calibrations (whole detector)', fontweight='bold')
47. plt.legend()
48. plt.savefig('/Users/marialauraperez/Desktop/total_per_source/Source+TestPulse_Calibs22deg.png')
49. plt.show()
50.
51. # plt.figure()
52. # plt.scatter(energies, mean_ToT, s=10, label='Data', color='navy')
53. # plt.plot(x, surrogate_function(x, *poptmean), label='Fit: a = '+str(np.round(poptmean[0], 3))
54. # + '; b = ' + str(np.round(poptmean[1], 3))
55. # + '; c = '+str(np.round(poptmean[2], 3))
56. # + '; t = '+str(np.round(poptmean[3], 3)), color='blue')
57. # plt.xlabel('Test pulse height [keV]')
58. # plt.ylabel('Mean ToT value')
59. # plt.title('Calibration with test pulses', fontweight='bold')
60. # plt.legend()
61. # plt.savefig(data_path_output+'22degTestPulse_AvgCalib.png')
62.
63.
64. def get_calibration_matrices(energy_vals, ToT_matrices):
65. nrows = len(ToT_matrices[0][:, 0])
66. ncols = len(ToT_matrices[0][0, :])
67. a = np.zeros(np.shape(ToT_matrices[0]))
68. b = a.copy()
69. c = a.copy()
70. t = a.copy()
71. test_vals_y = list()
72. pixel_i = list()
73. pixel_j = list()
74. test_popt = list()
75. for i in range(nrows):
76. for j in range(ncols):
77. entry = list()
78. for k in range(len(ToT_matrices)):
79. entry.append(ToT_matrices[k][i, j]/100)
80. try:
81. popt, pcov = curve_fit(surrogate_function, energy_vals, entry, p0=poptmean)
82. a[i, j] = popt[0]
83. b[i, j] = popt[1]
84. c[i, j] = popt[2]
85. t[i, j] = popt[3]
86. if (i is 20 or i is 148 or i is 50) and (j is 130 or j is 210 or j is 90):
87. test_vals_y.append(entry)
88. pixel_i.append(i)
89. pixel_j.append(j)
90. test_popt.append(popt)
91. except RuntimeError:
92. print('Error: calibration not performed in pixel (', str(i)+', '+str(j)+' )')
93. plt.figure()
94. plt.scatter(energy_vals, entry)
95. plt.show()
96.
97. return a, b, c, t, pixel_i, pixel_j, test_vals_y, test_popt
98.
99.
100. # a_matrix, b_matrix, c_matrix, t_matrix, pixels_x, pixels_y, test_vals, test_params = \
101. # get_calibration_matrices(energies, ToT_data)
102. #
103. # plt.figure()
104. # for k in range(len(pixels_x)):
105. # plt.scatter(energies, test_vals[k], s=10, label='('+str(pixels_x[k])+', '+str(pixels_y[k])+')')
106. # plt.plot(x, surrogate_function(x, *test_params[k]), label='Fit')
107. # plt.xlabel('Test pulse height [keV]')
108. # plt.ylabel('ToT value')
109. # plt.title('Calibration per pixel with test pulses', fontweight='bold')
110. # plt.legend(fontsize='small', ncol=2)
111. # plt.savefig(data_path_output+'22degTestPulse_CalibsPixels.png')
112. #
113. # np.savetxt(data_path_output+'A_TestPulse22deg.txt', a_matrix, fmt='%.5f')
114. # np.savetxt(data_path_output+'B_TestPulse22deg.txt', b_matrix, fmt='%.5f')
115. # np.savetxt(data_path_output+'C_TestPulse22deg.txt', c_matrix, fmt='%.5f')
116. # np.savetxt(data_path_output+'T_TestPulse22deg.txt', t_matrix, fmt='%.5f')
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