1 | """ |
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2 | Unit tests for Invertor class |
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3 | """ |
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4 | # Disable "missing docstring" complaint |
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5 | # pylint: disable-msg=C0111 |
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6 | # Disable "too many methods" complaint |
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7 | # pylint: disable-msg=R0904 |
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8 | |
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9 | |
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10 | import unittest, math, numpy |
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11 | from sans.pr.invertor import Invertor |
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12 | |
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13 | class TestFiguresOfMerit(unittest.TestCase): |
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14 | |
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15 | def setUp(self): |
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16 | self.invertor = Invertor() |
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17 | self.invertor.d_max = 100.0 |
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18 | |
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19 | # Test array |
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20 | self.ntest = 5 |
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21 | self.x_in = numpy.ones(self.ntest) |
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22 | for i in range(self.ntest): |
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23 | self.x_in[i] = 1.0*(i+1) |
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24 | |
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25 | x, y, err = load("sphere_80.txt") |
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26 | |
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27 | # Choose the right d_max... |
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28 | self.invertor.d_max = 160.0 |
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29 | # Set a small alpha |
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30 | self.invertor.alpha = .0007 |
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31 | # Set data |
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32 | self.invertor.x = x |
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33 | self.invertor.y = y |
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34 | self.invertor.err = err |
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35 | # Perform inversion |
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36 | #out, cov = self.invertor.invert(10) |
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37 | |
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38 | self.out, self.cov = self.invertor.lstsq(10) |
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39 | |
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40 | def test_positive(self): |
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41 | """ |
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42 | Test whether P(r) is positive |
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43 | """ |
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44 | self.assertEqual(self.invertor.get_positive(self.out), 1) |
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45 | |
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46 | def test_positive_err(self): |
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47 | """ |
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48 | Test whether P(r) is at least 1 sigma greater than zero |
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49 | for all r-values |
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50 | """ |
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51 | self.assertTrue(self.invertor.get_pos_err(self.out, self.cov)>0.9) |
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52 | |
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53 | class TestBasicComponent(unittest.TestCase): |
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54 | |
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55 | def setUp(self): |
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56 | self.invertor = Invertor() |
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57 | self.invertor.d_max = 100.0 |
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58 | |
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59 | # Test array |
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60 | self.ntest = 5 |
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61 | self.x_in = numpy.ones(self.ntest) |
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62 | for i in range(self.ntest): |
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63 | self.x_in[i] = 1.0*(i+1) |
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64 | |
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65 | def test_has_bck_flag(self): |
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66 | """ |
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67 | Tests the has_bck flag operations |
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68 | """ |
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69 | self.assertEqual(self.invertor.has_bck, False) |
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70 | self.invertor.has_bck=True |
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71 | self.assertEqual(self.invertor.has_bck, True) |
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72 | def doit_float(): |
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73 | self.invertor.has_bck = 2.0 |
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74 | def doit_str(): |
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75 | self.invertor.has_bck = 'a' |
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76 | |
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77 | self.assertRaises(ValueError, doit_float) |
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78 | self.assertRaises(ValueError, doit_str) |
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79 | |
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80 | |
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81 | def testset_dmax(self): |
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82 | """ |
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83 | Set and read d_max |
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84 | """ |
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85 | value = 15.0 |
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86 | self.invertor.d_max = value |
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87 | self.assertEqual(self.invertor.d_max, value) |
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88 | |
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89 | def testset_alpha(self): |
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90 | """ |
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91 | Set and read alpha |
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92 | """ |
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93 | value = 15.0 |
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94 | self.invertor.alpha = value |
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95 | self.assertEqual(self.invertor.alpha, value) |
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96 | |
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97 | def testset_x_1(self): |
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98 | """ |
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99 | Setting and reading the x array the hard way |
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100 | """ |
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101 | # Set x |
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102 | self.invertor.x = self.x_in |
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103 | |
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104 | # Read it back |
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105 | npts = self.invertor.get_nx() |
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106 | x_out = numpy.ones(npts) |
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107 | |
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108 | self.invertor.get_x(x_out) |
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109 | |
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110 | for i in range(self.ntest): |
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111 | self.assertEqual(self.x_in[i], x_out[i]) |
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112 | |
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113 | def testset_x_2(self): |
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114 | """ |
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115 | Setting and reading the x array the easy way |
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116 | """ |
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117 | # Set x |
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118 | self.invertor.x = self.x_in |
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119 | |
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120 | # Read it back |
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121 | x_out = self.invertor.x |
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122 | |
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123 | for i in range(self.ntest): |
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124 | self.assertEqual(self.x_in[i], x_out[i]) |
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125 | |
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126 | def testset_y(self): |
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127 | """ |
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128 | Setting and reading the y array the easy way |
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129 | """ |
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130 | # Set y |
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131 | self.invertor.y = self.x_in |
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132 | |
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133 | # Read it back |
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134 | y_out = self.invertor.y |
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135 | |
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136 | for i in range(self.ntest): |
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137 | self.assertEqual(self.x_in[i], y_out[i]) |
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138 | |
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139 | def testset_err(self): |
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140 | """ |
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141 | Setting and reading the err array the easy way |
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142 | """ |
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143 | # Set err |
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144 | self.invertor.err = self.x_in |
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145 | |
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146 | # Read it back |
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147 | err_out = self.invertor.err |
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148 | |
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149 | for i in range(self.ntest): |
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150 | self.assertEqual(self.x_in[i], err_out[i]) |
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151 | |
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152 | def test_iq(self): |
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153 | """ |
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154 | Test iq calculation |
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155 | """ |
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156 | q = 0.11 |
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157 | v1 = 8.0*math.pi**2/q * self.invertor.d_max *math.sin(q*self.invertor.d_max) |
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158 | v1 /= ( math.pi**2 - (q*self.invertor.d_max)**2.0 ) |
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159 | |
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160 | pars = numpy.ones(1) |
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161 | self.assertAlmostEqual(self.invertor.iq(pars, q), v1, 2) |
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162 | |
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163 | def test_pr(self): |
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164 | """ |
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165 | Test pr calculation |
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166 | """ |
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167 | r = 10.0 |
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168 | v1 = 2.0*r*math.sin(math.pi*r/self.invertor.d_max) |
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169 | pars = numpy.ones(1) |
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170 | self.assertAlmostEqual(self.invertor.pr(pars, r), v1, 2) |
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171 | |
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172 | def test_getsetters(self): |
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173 | self.invertor.new_data = 1.0 |
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174 | self.assertEqual(self.invertor.new_data, 1.0) |
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175 | |
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176 | self.assertEqual(self.invertor.test_no_data, None) |
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177 | |
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178 | def test_slitsettings(self): |
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179 | self.invertor.slit_width = 1.0 |
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180 | self.assertEqual(self.invertor.slit_width, 1.0) |
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181 | self.invertor.slit_height = 2.0 |
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182 | self.assertEqual(self.invertor.slit_height, 2.0) |
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183 | |
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184 | |
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185 | def test_inversion(self): |
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186 | """ |
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187 | Test an inversion for which we know the answer |
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188 | """ |
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189 | x, y, err = load("sphere_80.txt") |
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190 | |
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191 | # Choose the right d_max... |
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192 | self.invertor.d_max = 160.0 |
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193 | # Set a small alpha |
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194 | self.invertor.alpha = 1e-7 |
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195 | # Set data |
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196 | self.invertor.x = x |
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197 | self.invertor.y = y |
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198 | self.invertor.err = err |
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199 | # Perform inversion |
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200 | out, cov = self.invertor.invert_optimize(10) |
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201 | #out, cov = self.invertor.invert(10) |
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202 | # This is a very specific case |
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203 | # We should make sure it always passes |
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204 | self.assertTrue(self.invertor.chi2/len(x)<200.00) |
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205 | |
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206 | # Check the computed P(r) with the theory |
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207 | # for shpere of radius 80 |
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208 | x = numpy.arange(0.01, self.invertor.d_max, self.invertor.d_max/51.0) |
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209 | y = numpy.zeros(len(x)) |
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210 | dy = numpy.zeros(len(x)) |
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211 | y_true = numpy.zeros(len(x)) |
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212 | |
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213 | sum = 0.0 |
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214 | sum_true = 0.0 |
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215 | for i in range(len(x)): |
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216 | #y[i] = self.invertor.pr(out, x[i]) |
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217 | (y[i], dy[i]) = self.invertor.pr_err(out, cov, x[i]) |
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218 | sum += y[i] |
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219 | if x[i]<80.0: |
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220 | y_true[i] = pr_theory(x[i], 80.0) |
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221 | else: |
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222 | y_true[i] = 0 |
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223 | sum_true += y_true[i] |
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224 | |
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225 | y = y/sum*self.invertor.d_max/len(x) |
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226 | dy = dy/sum*self.invertor.d_max/len(x) |
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227 | y_true = y_true/sum_true*self.invertor.d_max/len(x) |
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228 | |
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229 | chi2 = 0.0 |
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230 | for i in range(len(x)): |
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231 | res = (y[i]-y_true[i])/dy[i] |
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232 | chi2 += res*res |
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233 | |
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234 | try: |
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235 | self.assertTrue(chi2/51.0<10.0) |
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236 | except: |
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237 | print "chi2 =", chi2/51.0 |
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238 | raise |
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239 | |
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240 | def test_lstsq(self): |
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241 | """ |
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242 | Test an inversion for which we know the answer |
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243 | """ |
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244 | x, y, err = load("sphere_80.txt") |
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245 | |
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246 | # Choose the right d_max... |
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247 | self.invertor.d_max = 160.0 |
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248 | # Set a small alpha |
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249 | self.invertor.alpha = .005 |
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250 | # Set data |
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251 | self.invertor.x = x |
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252 | self.invertor.y = y |
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253 | self.invertor.err = err |
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254 | # Perform inversion |
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255 | #out, cov = self.invertor.invert(10) |
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256 | |
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257 | out, cov = self.invertor.lstsq(10) |
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258 | |
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259 | |
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260 | # This is a very specific case |
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261 | # We should make sure it always passes |
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262 | try: |
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263 | self.assertTrue(self.invertor.chi2/len(x)<200.00) |
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264 | except: |
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265 | print "Chi2(I(q)) =", self.invertor.chi2/len(x) |
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266 | raise |
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267 | |
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268 | # Check the computed P(r) with the theory |
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269 | # for shpere of radius 80 |
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270 | x = numpy.arange(0.01, self.invertor.d_max, self.invertor.d_max/51.0) |
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271 | y = numpy.zeros(len(x)) |
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272 | dy = numpy.zeros(len(x)) |
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273 | y_true = numpy.zeros(len(x)) |
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274 | |
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275 | sum = 0.0 |
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276 | sum_true = 0.0 |
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277 | for i in range(len(x)): |
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278 | #y[i] = self.invertor.pr(out, x[i]) |
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279 | (y[i], dy[i]) = self.invertor.pr_err(out, cov, x[i]) |
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280 | sum += y[i] |
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281 | if x[i]<80.0: |
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282 | y_true[i] = pr_theory(x[i], 80.0) |
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283 | else: |
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284 | y_true[i] = 0 |
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285 | sum_true += y_true[i] |
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286 | |
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287 | y = y/sum*self.invertor.d_max/len(x) |
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288 | dy = dy/sum*self.invertor.d_max/len(x) |
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289 | y_true = y_true/sum_true*self.invertor.d_max/len(x) |
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290 | |
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291 | chi2 = 0.0 |
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292 | for i in range(len(x)): |
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293 | res = (y[i]-y_true[i])/dy[i] |
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294 | chi2 += res*res |
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295 | |
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296 | try: |
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297 | self.assertTrue(chi2/51.0<50.0) |
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298 | except: |
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299 | print "chi2(P(r)) =", chi2/51.0 |
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300 | raise |
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301 | |
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302 | # Test the number of peaks |
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303 | self.assertEqual(self.invertor.get_peaks(out), 1) |
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304 | |
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305 | def test_q_zero(self): |
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306 | """ |
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307 | Test error condition where a point has q=0 |
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308 | """ |
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309 | x, y, err = load("sphere_80.txt") |
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310 | x[0] = 0.0 |
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311 | |
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312 | # Choose the right d_max... |
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313 | self.invertor.d_max = 160.0 |
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314 | # Set a small alpha |
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315 | self.invertor.alpha = 1e-7 |
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316 | # Set data |
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317 | def doit(): |
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318 | self.invertor.x = x |
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319 | self.assertRaises(ValueError, doit) |
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320 | |
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321 | |
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322 | def test_q_neg(self): |
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323 | """ |
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324 | Test error condition where a point has q<0 |
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325 | """ |
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326 | x, y, err = load("sphere_80.txt") |
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327 | x[0] = -0.2 |
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328 | |
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329 | # Choose the right d_max... |
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330 | self.invertor.d_max = 160.0 |
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331 | # Set a small alpha |
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332 | self.invertor.alpha = 1e-7 |
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333 | # Set data |
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334 | self.invertor.x = x |
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335 | self.invertor.y = y |
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336 | self.invertor.err = err |
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337 | # Perform inversion |
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338 | out, cov = self.invertor.invert(4) |
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339 | |
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340 | try: |
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341 | self.assertTrue(self.invertor.chi2>0) |
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342 | except: |
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343 | print "Chi2 =", self.invertor.chi2 |
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344 | raise |
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345 | |
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346 | def test_Iq_zero(self): |
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347 | """ |
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348 | Test error condition where a point has q<0 |
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349 | """ |
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350 | x, y, err = load("sphere_80.txt") |
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351 | y[0] = 0.0 |
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352 | |
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353 | # Choose the right d_max... |
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354 | self.invertor.d_max = 160.0 |
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355 | # Set a small alpha |
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356 | self.invertor.alpha = 1e-7 |
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357 | # Set data |
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358 | self.invertor.x = x |
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359 | self.invertor.y = y |
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360 | self.invertor.err = err |
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361 | # Perform inversion |
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362 | out, cov = self.invertor.invert(4) |
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363 | |
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364 | try: |
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365 | self.assertTrue(self.invertor.chi2>0) |
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366 | except: |
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367 | print "Chi2 =", self.invertor.chi2 |
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368 | raise |
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369 | |
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370 | def no_test_time(self): |
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371 | x, y, err = load("sphere_80.txt") |
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372 | |
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373 | # Choose the right d_max... |
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374 | self.invertor.d_max = 160.0 |
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375 | # Set a small alpha |
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376 | self.invertor.alpha = 1e-7 |
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377 | # Set data |
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378 | self.invertor.x = x |
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379 | self.invertor.y = y |
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380 | self.invertor.err = err |
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381 | |
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382 | # time scales like nfunc**2 |
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383 | # on a Lenovo Intel Core 2 CPU T7400 @ 2.16GHz, |
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384 | # I get time/(nfunc)**2 = 0.022 sec |
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385 | |
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386 | out, cov = self.invertor.invert(15) |
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387 | t16 = self.invertor.elapsed |
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388 | |
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389 | out, cov = self.invertor.invert(30) |
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390 | t30 = self.invertor.elapsed |
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391 | |
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392 | t30s = t30/30.0**2 |
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393 | self.assertTrue( (t30s-t16/16.0**2)/t30s <1.2 ) |
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394 | |
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395 | def test_clone(self): |
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396 | self.invertor.x = self.x_in |
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397 | clone = self.invertor.clone() |
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398 | |
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399 | for i in range(len(self.x_in)): |
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400 | self.assertEqual(self.x_in[i], clone.x[i]) |
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401 | |
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402 | def test_save(self): |
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403 | x, y, err = load("sphere_80.txt") |
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404 | |
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405 | # Choose the right d_max... |
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406 | self.invertor.d_max = 160.0 |
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407 | # Set a small alpha |
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408 | self.invertor.alpha = .0007 |
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409 | # Set data |
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410 | self.invertor.x = x |
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411 | self.invertor.y = y |
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412 | self.invertor.err = err |
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413 | # Perform inversion |
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414 | |
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415 | out, cov = self.invertor.lstsq(10) |
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416 | |
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417 | # Save |
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418 | self.invertor.to_file("test_output.txt") |
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419 | |
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420 | def test_load(self): |
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421 | self.invertor.from_file("test_output.txt") |
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422 | self.assertEqual(self.invertor.d_max, 160.0) |
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423 | self.assertEqual(self.invertor.alpha, 0.0007) |
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424 | self.assertEqual(self.invertor.chi2, 836.797) |
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425 | self.assertAlmostEqual(self.invertor.pr(self.invertor.out, 10.0), 903.31577041, 4) |
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426 | |
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427 | def test_qmin(self): |
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428 | self.invertor.q_min = 1.0 |
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429 | self.assertEqual(self.invertor.q_min, 1.0) |
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430 | |
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431 | self.invertor.q_min = None |
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432 | self.assertEqual(self.invertor.q_min, None) |
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433 | |
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434 | |
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435 | def test_qmax(self): |
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436 | self.invertor.q_max = 1.0 |
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437 | self.assertEqual(self.invertor.q_max, 1.0) |
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438 | |
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439 | self.invertor.q_max = None |
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440 | self.assertEqual(self.invertor.q_max, None) |
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441 | |
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442 | class TestErrorConditions(unittest.TestCase): |
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443 | |
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444 | def setUp(self): |
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445 | self.invertor = Invertor() |
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446 | self.invertor.d_max = 100.0 |
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447 | |
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448 | # Test array |
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449 | self.ntest = 5 |
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450 | self.x_in = numpy.ones(self.ntest) |
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451 | for i in range(self.ntest): |
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452 | self.x_in[i] = 1.0*(i+1) |
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453 | |
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454 | def test_negative_errs(self): |
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455 | """ |
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456 | Test an inversion for which we know the answer |
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457 | """ |
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458 | x, y, err = load("data_error_1.txt") |
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459 | |
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460 | # Choose the right d_max... |
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461 | self.invertor.d_max = 160.0 |
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462 | # Set a small alpha |
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463 | self.invertor.alpha = .0007 |
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464 | # Set data |
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465 | self.invertor.x = x |
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466 | self.invertor.y = y |
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467 | self.invertor.err = err |
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468 | # Perform inversion |
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469 | |
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470 | out, cov = self.invertor.lstsq(10) |
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471 | |
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472 | def test_zero_errs(self): |
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473 | """ |
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474 | Have zero as an error should raise an exception |
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475 | """ |
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476 | x, y, err = load("data_error_2.txt") |
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477 | |
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478 | # Set data |
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479 | self.invertor.x = x |
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480 | self.invertor.y = y |
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481 | self.invertor.err = err |
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482 | # Perform inversion |
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483 | self.assertRaises(RuntimeError, self.invertor.invert, 10) |
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484 | |
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485 | def test_invalid(self): |
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486 | """ |
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487 | Test an inversion for which we know the answer |
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488 | """ |
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489 | x, y, err = load("data_error_1.txt") |
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490 | |
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491 | # Set data |
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492 | self.invertor.x = x |
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493 | self.invertor.y = y |
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494 | err = numpy.zeros(len(x)-1) |
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495 | self.invertor.err = err |
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496 | # Perform inversion |
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497 | self.assertRaises(RuntimeError, self.invertor.invert, 10) |
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498 | |
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499 | |
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500 | def test_zero_q(self): |
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501 | """ |
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502 | One of the q-values is zero. |
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503 | An exception should be raised. |
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504 | """ |
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505 | x, y, err = load("data_error_3.txt") |
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506 | |
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507 | # Set data |
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508 | self.assertRaises(ValueError, self.invertor.__setattr__, 'x', x) |
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509 | |
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510 | def test_zero_Iq(self): |
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511 | """ |
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512 | One of the I(q) points has a value of zero |
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513 | Should not complain or crash. |
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514 | """ |
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515 | x, y, err = load("data_error_4.txt") |
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516 | |
---|
517 | # Set data |
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518 | self.invertor.x = x |
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519 | self.invertor.y = y |
---|
520 | self.invertor.err = err |
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521 | # Perform inversion |
---|
522 | out, cov = self.invertor.lstsq(10) |
---|
523 | |
---|
524 | def test_negative_q(self): |
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525 | """ |
---|
526 | One q value is negative. |
---|
527 | Makes not sense, but should not complain or crash. |
---|
528 | """ |
---|
529 | x, y, err = load("data_error_5.txt") |
---|
530 | |
---|
531 | # Set data |
---|
532 | self.invertor.x = x |
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533 | self.invertor.y = y |
---|
534 | self.invertor.err = err |
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535 | # Perform inversion |
---|
536 | out, cov = self.invertor.lstsq(10) |
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537 | |
---|
538 | def test_negative_Iq(self): |
---|
539 | """ |
---|
540 | One I(q) value is negative. |
---|
541 | Makes not sense, but should not complain or crash. |
---|
542 | """ |
---|
543 | x, y, err = load("data_error_6.txt") |
---|
544 | |
---|
545 | # Set data |
---|
546 | self.invertor.x = x |
---|
547 | self.invertor.y = y |
---|
548 | self.invertor.err = err |
---|
549 | # Perform inversion |
---|
550 | out, cov = self.invertor.lstsq(10) |
---|
551 | |
---|
552 | def test_nodata(self): |
---|
553 | """ |
---|
554 | No data was loaded. Should not complain. |
---|
555 | """ |
---|
556 | out, cov = self.invertor.lstsq(10) |
---|
557 | |
---|
558 | |
---|
559 | |
---|
560 | def pr_theory(r, R): |
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561 | """ |
---|
562 | P(r) for a sphere |
---|
563 | """ |
---|
564 | if r<=2*R: |
---|
565 | return 12.0* ((0.5*r/R)**2) * ((1.0-0.5*r/R)**2) * ( 2.0 + 0.5*r/R ) |
---|
566 | else: |
---|
567 | return 0.0 |
---|
568 | |
---|
569 | def load(path = "sphere_60_q0_2.txt"): |
---|
570 | import numpy, math, sys |
---|
571 | # Read the data from the data file |
---|
572 | data_x = numpy.zeros(0) |
---|
573 | data_y = numpy.zeros(0) |
---|
574 | data_err = numpy.zeros(0) |
---|
575 | scale = None |
---|
576 | if not path == None: |
---|
577 | input_f = open(path,'r') |
---|
578 | buff = input_f.read() |
---|
579 | lines = buff.split('\n') |
---|
580 | for line in lines: |
---|
581 | try: |
---|
582 | toks = line.split() |
---|
583 | x = float(toks[0]) |
---|
584 | y = float(toks[1]) |
---|
585 | if len(toks)>2: |
---|
586 | err = float(toks[2]) |
---|
587 | else: |
---|
588 | if scale==None: |
---|
589 | scale = 0.15*math.sqrt(y) |
---|
590 | err = scale*math.sqrt(y) |
---|
591 | data_x = numpy.append(data_x, x) |
---|
592 | data_y = numpy.append(data_y, y) |
---|
593 | data_err = numpy.append(data_err, err) |
---|
594 | except: |
---|
595 | pass |
---|
596 | |
---|
597 | return data_x, data_y, data_err |
---|
598 | |
---|
599 | if __name__ == '__main__': |
---|
600 | unittest.main(testRunner=unittest.TextTestRunner(verbosity=2)) |
---|