1 | """ |
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2 | Unit tests for non shape based model (Task 8.2.1) |
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3 | These tests are part of the requirements |
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4 | """ |
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5 | |
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6 | import unittest, time, math |
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7 | from scipy.special import erf,gammaln |
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8 | |
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9 | # Disable "missing docstring" complaint |
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10 | # pylint: disable-msg=C0111 |
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11 | # Disable "too many methods" complaint |
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12 | # pylint: disable-msg=R0904 |
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13 | # Disable "could be a function" complaint |
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14 | # pylint: disable-msg=R0201 |
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15 | |
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16 | import scipy |
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17 | class TestGuinier(unittest.TestCase): |
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18 | """ |
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19 | Unit tests for Guinier function |
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20 | |
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21 | F(x) = exp[ [A] + [B]*Q**2 ] |
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22 | |
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23 | The model has two parameters: A and B |
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24 | """ |
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25 | def _func(self, a, b, x): |
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26 | return a*math.exp(-(b*x)**2/3.0) |
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27 | |
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28 | def setUp(self): |
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29 | from sans.models.GuinierModel import GuinierModel |
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30 | self.model= GuinierModel() |
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31 | |
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32 | def test1D(self): |
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33 | self.model.setParam('scale', 2.0) |
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34 | self.model.setParam('rg', 1.0) |
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35 | |
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36 | self.assertEqual(self.model.run(0.0), 2.0) |
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37 | self.assertEqual(self.model.run(2.0), 2.0*math.exp(-(1.0*2.0)**2/3.0)) |
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38 | self.assertEqual(self.model.runXY(2.0), 2.0*math.exp(-(1.0*2.0)**2/3.0)) |
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39 | |
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40 | def test2D(self): |
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41 | self.model.setParam('scale', 2.0) |
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42 | self.model.setParam('rg', 1.0) |
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43 | |
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44 | #value = self._func(2.0, 1.0, 1.0)*self._func(2.0, 1.0, 2.0) |
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45 | value = self._func(2.0, 1.0, math.sqrt(5.0)) |
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46 | #self.assertEqual(self.model.runXY([0.0,0.0]), 2.0*2.0) |
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47 | self.assertEqual(self.model.runXY([0.0,0.0]), 2.0) |
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48 | self.assertEqual(self.model.runXY([1.0,2.0]), value) |
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49 | |
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50 | def test2Dphi(self): |
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51 | self.model.setParam('scale', 2.0) |
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52 | self.model.setParam('rg', 1.0) |
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53 | |
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54 | x = 1.0 |
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55 | y = 2.0 |
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56 | r = math.sqrt(x**2 + y**2) |
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57 | phi = math.atan2(y, x) |
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58 | |
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59 | #value = self._func(2.0, 1.0, x)*self._func(2.0, 1.0, y) |
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60 | value = self._func(2.0, 1.0, r) |
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61 | |
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62 | #self.assertEqual(self.model.run([r, phi]), value) |
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63 | self.assertAlmostEquals(self.model.run([r, phi]), value,1) |
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64 | |
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65 | |
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66 | class TestPorod(unittest.TestCase): |
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67 | """ |
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68 | Unit tests for Porod function |
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69 | |
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70 | F(x) = C/Q**4 |
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71 | |
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72 | The model has one parameter: C |
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73 | """ |
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74 | def _func(self, c, x): |
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75 | return c/(x**4) |
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76 | |
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77 | def setUp(self): |
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78 | from sans.models.PorodModel import PorodModel |
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79 | self.model= PorodModel() |
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80 | self.model.setParam('scale', 2.0) |
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81 | |
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82 | def test1D(self): |
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83 | value = self._func(2.0, 3.0) |
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84 | self.assertEqual(self.model.run(3.0), value) |
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85 | self.assertEqual(self.model.runXY(3.0), value) |
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86 | |
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87 | def test2D(self): |
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88 | #value = self._func(2.0, 1.0)*self._func(2.0, 2.0) |
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89 | value = self._func(2.0, math.sqrt(5.0)) |
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90 | self.assertEqual(self.model.runXY([1.0,2.0]), value) |
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91 | |
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92 | def test2Dphi(self): |
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93 | x = 1.0 |
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94 | y = 2.0 |
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95 | r = math.sqrt(x**2 + y**2) |
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96 | phi = math.atan2(y, x) |
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97 | |
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98 | #value = self._func(2.0, 1.0)*self._func(2.0, 2.0) |
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99 | value = self._func(2.0, r) |
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100 | self.assertAlmostEquals(self.model.run([r, phi]), value,1) |
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101 | |
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102 | class TestDebye(unittest.TestCase): |
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103 | """ |
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104 | Unit tests for Debye function |
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105 | |
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106 | F(x) = 2( exp(-x)+x -1 )/x**2 |
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107 | |
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108 | The model has three parameters: |
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109 | Rg = radius of gyration |
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110 | scale = scale factor |
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111 | bkd = Constant background |
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112 | """ |
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113 | def _func(self, Rg, scale, bkg, x): |
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114 | y = (Rg * x)**2 |
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115 | return scale * (2*(math.exp(-y) + y -1)/y**2) + bkg |
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116 | |
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117 | def setUp(self): |
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118 | from sans.models.DebyeModel import DebyeModel |
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119 | self.model= DebyeModel() |
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120 | self.model.setParam('Rg', 50.0) |
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121 | self.model.setParam('scale',1.0) |
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122 | self.model.setParam('background',0.001) |
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123 | |
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124 | def test1D(self): |
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125 | value = self._func(50.0, 1.0, 0.001, 2.0) |
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126 | self.assertEqual(self.model.run(2.0), value) |
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127 | self.assertEqual(self.model.runXY(2.0), value) |
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128 | |
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129 | # User enter zero as a value of x |
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130 | # An exceptio is raised |
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131 | self.assertRaises(ZeroDivisionError, self.model.run, 0.0) |
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132 | |
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133 | def test1D_clone(self): |
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134 | value = self._func(50.0, 1.0, 10.0, 2.0) |
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135 | self.model.setParam('background', 10.0) |
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136 | clone = self.model.clone() |
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137 | self.assertEqual(clone.run(2.0), value) |
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138 | self.assertEqual(clone.runXY(2.0), value) |
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139 | |
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140 | # User enter zero as a value of x |
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141 | # An exceptio is raised |
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142 | self.assertRaises(ZeroDivisionError, clone.run, 0.0) |
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143 | |
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144 | def test2D(self): |
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145 | #value = self._func(50.0, 1.0, 0.001, 1.0)*self._func(50.0, 1.0, 0.001, 2.0) |
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146 | value = self._func(50.0, 1.0, 0.001, math.sqrt(5.0)) |
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147 | self.assertEqual(self.model.runXY([1.0,2.0]), value) |
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148 | |
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149 | def test2Dphi(self): |
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150 | x = 1.0 |
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151 | y = 2.0 |
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152 | r = math.sqrt(x**2 + y**2) |
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153 | phi = math.atan2(y, x) |
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154 | |
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155 | value = self._func(50.0, 1.0, 0.001, 1.0)*self._func(50.0, 1.0, 0.001, 2.0) |
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156 | self.assertAlmostEquals(self.model.run([r, phi]), value,1) |
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157 | |
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158 | |
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159 | class TestLorentz(unittest.TestCase): |
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160 | """ |
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161 | Unit tests for Lorentz function |
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162 | |
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163 | F(x) = scale/( 1 + (x*L)^2 ) + bkd |
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164 | |
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165 | The model has three parameters: |
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166 | L = screen Length |
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167 | scale = scale factor |
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168 | bkd = incoherent background |
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169 | """ |
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170 | def _func(self, I0 , L, bgd, qval): |
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171 | return I0/(1.0 + (qval*L)*(qval*L)) + bgd |
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172 | |
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173 | def setUp(self): |
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174 | from sans.models.LorentzModel import LorentzModel |
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175 | self.model= LorentzModel() |
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176 | |
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177 | def test1D(self): |
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178 | self.model.setParam('scale', 100.0) |
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179 | self.model.setParam('Length', 50.0) |
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180 | self.model.setParam('background', 1.0) |
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181 | |
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182 | self.assertEqual(self.model.run(0.0), 101.0) |
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183 | self.assertEqual(self.model.run(2.0), self._func(100.0, 50.0, 1.0, 2.0)) |
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184 | self.assertEqual(self.model.runXY(2.0), self._func(100.0, 50.0, 1.0, 2.0)) |
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185 | |
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186 | def test2D(self): |
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187 | self.model.setParam('scale', 100.0) |
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188 | self.model.setParam('Length', 50.0) |
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189 | self.model.setParam('background', 1.0) |
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190 | |
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191 | #value = self._func(100.0, 50.0, 1.0, 1.0)*self._func(100.0, 50.0, 1.0, 2.0) |
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192 | value = self._func(100.0, 50.0, 1.0, math.sqrt(5.0)) |
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193 | self.assertEqual(self.model.runXY([1.0,2.0]), value) |
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194 | |
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195 | def test2Dphi(self): |
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196 | self.model.setParam('scale', 100.0) |
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197 | self.model.setParam('Length', 50.0) |
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198 | self.model.setParam('background', 1.0) |
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199 | |
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200 | x = 1.0 |
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201 | y = 2.0 |
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202 | r = math.sqrt(x**2 + y**2) |
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203 | phi = math.atan2(y, x) |
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204 | |
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205 | value = self._func(100.0, 50.0, 1.0, x)*self._func(100.0, 50.0, 1.0, y) |
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206 | self.assertAlmostEquals(self.model.run([r, phi]), value,1) |
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207 | |
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208 | class TestDAB(unittest.TestCase): |
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209 | """ |
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210 | Unit tests for DAB function |
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211 | |
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212 | F(x) = scale/( 1 + (x*L)^2 )^(2) + bkd |
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213 | |
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214 | The model has three parameters: |
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215 | L = Correlation Length |
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216 | scale = scale factor |
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217 | bkd = incoherent background |
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218 | """ |
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219 | def _func(self, Izero, range, incoh, qval): |
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220 | return Izero/pow((1.0 + (qval*range)*(qval*range)),2) + incoh |
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221 | |
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222 | def setUp(self): |
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223 | from sans.models.DABModel import DABModel |
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224 | self.model= DABModel() |
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225 | self.scale = 10.0 |
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226 | self.length = 40.0 |
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227 | self.back = 1.0 |
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228 | |
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229 | self.model.setParam('scale', self.scale) |
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230 | self.model.setParam('Length', self.length) |
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231 | self.model.setParam('background', self.back) |
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232 | |
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233 | def test1D(self): |
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234 | |
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235 | self.assertEqual(self.model.run(0.0), self.scale+self.back) |
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236 | self.assertEqual(self.model.run(2.0), self._func(self.scale, self.length, self.back, 2.0)) |
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237 | self.assertEqual(self.model.runXY(2.0), self._func(self.scale, self.length, self.back, 2.0)) |
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238 | |
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239 | def test2D(self): |
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240 | #value = self._func(self.scale, self.length, self.back, 1.0)*self._func(self.scale, self.length, self.back, 2.0) |
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241 | value = self._func(self.scale, self.length, self.back, math.sqrt(5.0)) |
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242 | self.assertEqual(self.model.runXY([1.0,2.0]), value) |
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243 | |
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244 | def test2Dphi(self): |
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245 | x = 1.0 |
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246 | y = 2.0 |
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247 | r = math.sqrt(x**2 + y**2) |
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248 | phi = math.atan2(y, x) |
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249 | |
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250 | value = self._func(self.scale, self.length, self.back, x)*self._func(self.scale, self.length, self.back, y) |
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251 | self.assertAlmostEquals(self.model.run([r, phi]), value,1) |
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252 | |
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253 | class TestPowerLaw(unittest.TestCase): |
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254 | """ |
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255 | Unit tests for PowerLaw function |
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256 | |
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257 | F(x) = scale* (x)^(m) + bkd |
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258 | |
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259 | The model has three parameters: |
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260 | m = power |
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261 | scale = scale factor |
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262 | bkd = incoherent background |
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263 | """ |
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264 | def _func(self, a, m, bgd, qval): |
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265 | return a*math.pow(qval,-m) + bgd |
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266 | |
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267 | |
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268 | def setUp(self): |
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269 | from sans.models.PowerLawModel import PowerLawModel |
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270 | self.model= PowerLawModel() |
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271 | |
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272 | def test1D(self): |
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273 | self.model.setParam('scale', math.exp(-6)) |
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274 | self.model.setParam('m', 4.0) |
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275 | self.model.setParam('background', 1.0) |
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276 | |
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277 | #self.assertEqual(self.model.run(0.0), 1.0) |
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278 | self.assertEqual(self.model.run(2.0), self._func(math.exp(-6), 4.0, 1.0, 2.0)) |
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279 | self.assertEqual(self.model.runXY(2.0), self._func(math.exp(-6), 4.0, 1.0, 2.0)) |
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280 | |
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281 | def testlimit(self): |
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282 | self.model.setParam('scale', math.exp(-6)) |
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283 | self.model.setParam('m', -4.0) |
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284 | self.model.setParam('background', 1.0) |
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285 | |
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286 | self.assertEqual(self.model.run(0.0), 1.0) |
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287 | |
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288 | def test2D(self): |
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289 | self.model.setParam('scale', math.exp(-6)) |
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290 | self.model.setParam('m', 4.0) |
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291 | self.model.setParam('background', 1.0) |
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292 | |
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293 | #value = self._func(math.exp(-6), 4.0, 1.0, 1.0)\ |
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294 | #*self._func(math.exp(-6), 4.0, 1.0, 2.0) |
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295 | value = self._func(math.exp(-6), 4.0, 1.0, math.sqrt(5.0)) |
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296 | |
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297 | self.assertEqual(self.model.runXY([1.0,2.0]), value) |
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298 | |
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299 | def test2Dphi(self): |
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300 | self.model.setParam('scale', math.exp(-6)) |
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301 | self.model.setParam('m', 4.0) |
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302 | self.model.setParam('background', 1.0) |
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303 | |
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304 | x = 1.0 |
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305 | y = 2.0 |
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306 | r = math.sqrt(x**2 + y**2) |
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307 | phi = math.atan2(y, x) |
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308 | |
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309 | value = self._func(math.exp(-6), 4.0, 1.0, x)\ |
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310 | *self._func(math.exp(-6), 4.0, 1.0, y) |
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311 | self.assertAlmostEquals(self.model.run([r, phi]), value,1) |
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312 | |
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313 | class TestTeubnerStrey(unittest.TestCase): |
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314 | """ |
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315 | Unit tests for PowerLaw function |
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316 | |
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317 | F(x) = 1/( scale + c1*(x)^(2)+ c2*(x)^(4)) + bkd |
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318 | |
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319 | The model has Four parameters: |
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320 | scale = scale factor |
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321 | c1 = constant |
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322 | c2 = constant |
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323 | bkd = incoherent background |
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324 | """ |
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325 | def _func(self, scale, c1, c2, bck, q): |
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326 | |
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327 | q2 = q*q; |
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328 | q4 = q2*q2; |
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329 | |
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330 | return 1.0/(scale + c1*q2+c2*q4) + bck |
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331 | |
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332 | def setUp(self): |
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333 | from sans.models.TeubnerStreyModel import TeubnerStreyModel |
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334 | self.model= TeubnerStreyModel() |
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335 | |
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336 | def test1D(self): |
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337 | |
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338 | self.model.setParam('c1', -30.0) |
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339 | self.model.setParam('c2', 5000.0) |
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340 | self.model.setParam('scale', 0.1) |
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341 | self.model.setParam('background', 0.1) |
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342 | #self.assertEqual(1/(math.sqrt(4)), math.pow(4,-1/2)) |
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343 | #self.assertEqual(self.model.TeubnerStreyLengths(),False ) |
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344 | |
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345 | self.assertEqual(self.model.run(0.0), 10.1) |
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346 | self.assertEqual(self.model.run(2.0), self._func(0.1,-30.0,5000.0,0.1,2.0)) |
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347 | self.assertEqual(self.model.runXY(2.0), self._func(0.1,-30.0,5000.0,0.1,2.0)) |
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348 | |
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349 | def test2D(self): |
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350 | self.model.setParam('c1', -30.0) |
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351 | self.model.setParam('c2', 5000.0) |
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352 | self.model.setParam('scale', 0.1) |
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353 | self.model.setParam('background', 0.1) |
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354 | #value = self._func(0.1,-30.0,5000.0,0.1, 1.0)\ |
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355 | #*self._func(0.1,-30.0,5000.0,0.1, 2.0) |
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356 | value = self._func(0.1,-30.0,5000.0,0.1, math.sqrt(5.0)) |
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357 | |
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358 | self.assertEqual(self.model.runXY([1.0,2.0]), value) |
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359 | |
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360 | def test2Dphi(self): |
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361 | self.model.setParam('c1', -30.0) |
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362 | self.model.setParam('c2', 5000.0) |
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363 | self.model.setParam('scale', 0.1) |
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364 | self.model.setParam('background', 0.1) |
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365 | |
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366 | x = 1.0 |
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367 | y = 2.0 |
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368 | r = math.sqrt(x**2 + y**2) |
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369 | phi = math.atan2(y, x) |
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370 | |
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371 | #value = self._func(0.1,-30.0,5000.0,0.1, x)\ |
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372 | #*self._func(0.1,-30.0,5000.0,0.1, y) |
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373 | value = self._func(0.1,-30.0,5000.0,0.1, r) |
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374 | self.assertAlmostEquals(self.model.run([r, phi]), value,1) |
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375 | |
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376 | class TestBEPolyelectrolyte(unittest.TestCase): |
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377 | """ |
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378 | Unit tests for BEPolyelectrolyte function |
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379 | |
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380 | F(x) = K*1/(4*pi()*Lb*(alpha)^(2)*(q^(2)+k2)/(1+(r02)^(2))*(q^(2)+k2)\ |
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381 | *(q^(2)-(12*h*C/b^(2))) |
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382 | |
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383 | The model has Eight parameters: |
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384 | K = Constrast factor of the polymer |
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385 | Lb = Bjerrum length |
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386 | H = virial parameter |
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387 | B = monomer length |
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388 | Cs = Concentration of monovalent salt |
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389 | alpha = ionazation degree |
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390 | C = polymer molar concentration |
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391 | bkd = background |
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392 | """ |
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393 | def _func(self, K, Lb, H, B, Cs, alpha, C, bkd, r02, k2, x): |
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394 | return (K /( (4*math.pi *Lb*(alpha**2)*(x**2 +k2)) *( (1 +(r02**2)) \ |
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395 | *((x**2) + k2)*((x**2) -(12 * H * C/(B**2))) )))+ bkd |
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396 | |
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397 | def setUp(self): |
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398 | from sans.models.BEPolyelectrolyte import BEPolyelectrolyte |
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399 | self.model= BEPolyelectrolyte() |
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400 | |
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401 | self.K = 10.0 |
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402 | self.Lb = 6.5 |
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403 | self.h = 11 |
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404 | self.b = 13 |
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405 | self.Cs = 0.1 |
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406 | self.alpha = 0.05 |
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407 | self.C = .7 |
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408 | self.Bkd =0.01 |
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409 | |
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410 | self.model.setParam('K', self.K) |
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411 | self.model.setParam('Lb', self.Lb) |
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412 | self.model.setParam('H', self.h) |
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413 | self.model.setParam('B', self.b) |
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414 | self.model.setParam('Cs',self.Cs) |
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415 | self.model.setParam('alpha', self.alpha) |
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416 | self.model.setParam('C', self.C) |
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417 | self.model.setParam('background', self.Bkd) |
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418 | |
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419 | def _func(self, q): |
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420 | |
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421 | Ca = self.C *6.022136e-4 |
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422 | Csa = self.Cs * 6.022136e-4 |
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423 | k2= 4*math.pi*self.Lb*(2*self.Cs+self.alpha*Ca) |
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424 | |
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425 | r02 = 1./self.alpha / Ca**0.5*( self.b / (48*math.pi*self.Lb)**0.5 ) |
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426 | q2 = q**2 |
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427 | Sq = self.K*1./(4*math.pi*self.Lb*self.alpha**2) * (q2 + k2) / (1+(r02**2) * (q2+k2) * (q2- (12*self.h*Ca/self.b**2)) ) + self.Bkd |
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428 | return Sq |
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429 | |
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430 | def test1D(self): |
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431 | |
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432 | |
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433 | q = 0.001 |
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434 | |
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435 | self.assertEqual(self.model.run(q), self._func(q)) |
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436 | self.assertEqual(self.model.runXY(q), self._func(q)) |
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437 | |
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438 | def test2D(self): |
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439 | #self.assertAlmostEquals(self.model.runXY([1.0,2.0]), self._func(1.0)*self._func(2.0), 8) |
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440 | self.assertAlmostEquals(self.model.runXY([1.0,2.0]), self._func(math.sqrt(1.0+2.0**2)), 8) |
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441 | |
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442 | def test2Dphi(self): |
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443 | |
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444 | x = 1.0 |
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445 | y = 2.0 |
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446 | r = math.sqrt(x**2 + y**2) |
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447 | phi = math.atan2(y, x) |
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448 | |
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449 | self.assertAlmostEquals(self.model.run([r, phi]), self._func(r), 8) |
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450 | |
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451 | class TestFractalModel(unittest.TestCase): |
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452 | """ |
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453 | Unit tests for Number Density Fractal function |
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454 | F(x)= P(x)*S(x) + bkd |
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455 | The model has Seven parameters: |
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456 | scale = Volume fraction |
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457 | Radius = Block radius |
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458 | Fdim = Fractal dimension |
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459 | L = correlation Length |
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460 | SDLB = SDL block |
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461 | SDLS = SDL solvent |
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462 | bkd = background |
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463 | """ |
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464 | def setUp(self): |
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465 | from sans.models.FractalModel import FractalModel |
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466 | self.model= FractalModel() |
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467 | self.r0 = 5.0 |
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468 | self.sldp = 2.0e-6 |
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469 | self.sldm = 6.35e-6 |
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470 | self.phi = 0.05 |
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471 | self.Df = 2 |
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472 | self.corr = 100.0 |
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473 | self.bck = 1.0 |
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474 | |
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475 | self.model.setParam('scale', self.phi) |
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476 | self.model.setParam('Radius', self.r0) |
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477 | self.model.setParam('fractal_dim',self.Df) |
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478 | self.model.setParam('corr_length', self.corr) |
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479 | self.model.setParam('block_sld', self.sldp) |
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480 | self.model.setParam('solvent_sld', self.sldm) |
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481 | self.model.setParam('background', self.bck) |
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482 | |
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483 | def _func(self, x): |
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484 | r0 = self.r0 |
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485 | sldp = self.sldp |
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486 | sldm = self.sldm |
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487 | phi = self.phi |
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488 | Df = self.Df |
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489 | corr = self.corr |
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490 | bck = self.bck |
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491 | |
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492 | pq = 1.0e8*phi*4.0/3.0*math.pi*r0*r0*r0*(sldp-sldm)*(sldp-sldm)*math.pow((3*(math.sin(x*r0) - x*r0*math.cos(x*r0))/math.pow((x*r0),3)),2); |
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493 | |
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494 | sq = Df*math.exp(gammaln(Df-1.0))*math.sin((Df-1.0)*math.atan(x*corr)); |
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495 | sq /= math.pow((x*r0),Df) * math.pow((1.0 + 1.0/(x*corr)/(x*corr)),((Df-1.0)/2.0)); |
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496 | sq += 1.0; |
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497 | |
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498 | self.assertAlmostEqual(self.model._scatterRanDom(x), pq, 8 ) |
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499 | self.assertEqual(self.model._Block(x),sq ) |
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500 | |
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501 | return sq*pq+bck |
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502 | |
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503 | def test1D(self): |
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504 | x = 0.001 |
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505 | |
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506 | iq = self._func(x) |
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507 | self.assertEqual(self.model.run(x), iq) |
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508 | self.assertEqual(self.model.runXY(x), iq) |
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509 | |
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510 | def test2D(self): |
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511 | x = 1.0 |
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512 | y = 2.0 |
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513 | r = math.sqrt(x**2 + y**2) |
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514 | phi = math.atan2(y, x) |
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515 | iq_x = self._func(x) |
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516 | iq_y = self._func(y) |
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517 | |
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518 | #self.assertEqual(self.model.run([r, phi]), iq_x*iq_y) |
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519 | self.assertEqual(self.model.run([r, phi]), self.model.run(r)) |
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520 | #self.assertEqual(self.model.runXY([x,y]), iq_x*iq_y) |
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521 | self.assertEqual(self.model.runXY([x,y]), self.model.run(r)) |
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522 | |
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523 | if __name__ == '__main__': |
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524 | unittest.main() |
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