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