1 | #!/usr/bin/env python |
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2 | |
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3 | ############################################################################## |
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4 | # This software was developed by the University of Tennessee as part of the |
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5 | # Distributed Data Analysis of Neutron Scattering Experiments (DANSE) |
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6 | # project funded by the US National Science Foundation. |
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7 | # |
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8 | # If you use DANSE applications to do scientific research that leads to |
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9 | # publication, we ask that you acknowledge the use of the software with the |
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10 | # following sentence: |
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11 | # |
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12 | # "This work benefited from DANSE software developed under NSF award DMR-0520547." |
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13 | # |
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14 | # copyright 2008, University of Tennessee |
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15 | ############################################################################## |
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16 | |
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17 | |
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18 | """ |
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19 | Provide functionality for a C extension model |
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20 | |
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21 | :WARNING: THIS FILE WAS GENERATED BY WRAPPERGENERATOR.PY |
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22 | DO NOT MODIFY THIS FILE, MODIFY ..\c_extensions\lamellar.h |
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23 | AND RE-RUN THE GENERATOR SCRIPT |
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24 | |
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25 | """ |
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26 | |
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27 | from sans.models.BaseComponent import BaseComponent |
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28 | from sans_extension.c_models import CLamellarModel |
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29 | import copy |
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30 | |
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31 | class LamellarModel(CLamellarModel, BaseComponent): |
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32 | """ |
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33 | Class that evaluates a LamellarModel model. |
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34 | This file was auto-generated from ..\c_extensions\lamellar.h. |
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35 | Refer to that file and the structure it contains |
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36 | for details of the model. |
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37 | List of default parameters: |
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38 | scale = 1.0 |
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39 | bi_thick = 50.0 [A] |
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40 | sld_bi = 1e-006 [1/A^(2)] |
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41 | sld_sol = 6.3e-006 [1/A^(2)] |
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42 | background = 0.0 [1/cm] |
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43 | |
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44 | """ |
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45 | |
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46 | def __init__(self): |
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47 | """ Initialization """ |
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48 | |
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49 | # Initialize BaseComponent first, then sphere |
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50 | BaseComponent.__init__(self) |
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51 | CLamellarModel.__init__(self) |
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52 | |
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53 | ## Name of the model |
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54 | self.name = "LamellarModel" |
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55 | ## Model description |
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56 | self.description ="""[Dilute Lamellar Form Factor](from a lyotropic lamellar phase) |
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57 | I(q)= 2*pi*P(q)/(delta *q^(2)), where |
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58 | P(q)=2*(contrast/q)^(2)*(1-cos(q*delta))^(2)) |
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59 | bi_thick = bilayer thickness |
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60 | sld_bi = SLD of bilayer |
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61 | sld_sol = SLD of solvent |
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62 | background = Incoherent background |
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63 | scale = scale factor |
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64 | """ |
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65 | |
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66 | ## Parameter details [units, min, max] |
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67 | self.details = {} |
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68 | self.details['scale'] = ['', None, None] |
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69 | self.details['bi_thick'] = ['[A]', None, None] |
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70 | self.details['sld_bi'] = ['[1/A^(2)]', None, None] |
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71 | self.details['sld_sol'] = ['[1/A^(2)]', None, None] |
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72 | self.details['background'] = ['[1/cm]', None, None] |
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73 | |
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74 | ## fittable parameters |
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75 | self.fixed=[] |
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76 | |
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77 | ## parameters with orientation |
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78 | self.orientation_params =[] |
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79 | |
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80 | def clone(self): |
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81 | """ Return a identical copy of self """ |
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82 | return self._clone(LamellarModel()) |
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83 | |
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84 | def __getstate__(self): |
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85 | """ |
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86 | return object state for pickling and copying |
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87 | """ |
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88 | model_state = {'params': self.params, 'dispersion': self.dispersion, 'log': self.log} |
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89 | |
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90 | return self.__dict__, model_state |
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91 | |
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92 | def __setstate__(self, state): |
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93 | """ |
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94 | create object from pickled state |
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95 | |
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96 | :param state: the state of the current model |
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97 | |
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98 | """ |
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99 | |
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100 | self.__dict__, model_state = state |
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101 | self.params = model_state['params'] |
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102 | self.dispersion = model_state['dispersion'] |
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103 | self.log = model_state['log'] |
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104 | |
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105 | |
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106 | def run(self, x=0.0): |
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107 | """ |
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108 | Evaluate the model |
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109 | |
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110 | :param x: input q, or [q,phi] |
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111 | |
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112 | :return: scattering function P(q) |
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113 | |
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114 | """ |
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115 | |
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116 | return CLamellarModel.run(self, x) |
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117 | |
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118 | def runXY(self, x=0.0): |
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119 | """ |
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120 | Evaluate the model in cartesian coordinates |
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121 | |
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122 | :param x: input q, or [qx, qy] |
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123 | |
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124 | :return: scattering function P(q) |
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125 | |
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126 | """ |
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127 | |
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128 | return CLamellarModel.runXY(self, x) |
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129 | |
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130 | def evalDistribution(self, x=[]): |
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131 | """ |
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132 | Evaluate the model in cartesian coordinates |
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133 | |
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134 | :param x: input q[], or [qx[], qy[]] |
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135 | |
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136 | :return: scattering function P(q[]) |
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137 | |
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138 | """ |
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139 | return CLamellarModel.evalDistribution(self, x) |
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140 | |
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141 | def calculate_ER(self): |
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142 | """ |
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143 | Calculate the effective radius for P(q)*S(q) |
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144 | |
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145 | :return: the value of the effective radius |
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146 | |
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147 | """ |
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148 | return CLamellarModel.calculate_ER(self) |
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149 | |
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150 | def set_dispersion(self, parameter, dispersion): |
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151 | """ |
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152 | Set the dispersion object for a model parameter |
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153 | |
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154 | :param parameter: name of the parameter [string] |
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155 | :param dispersion: dispersion object of type DispersionModel |
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156 | |
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157 | """ |
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158 | return CLamellarModel.set_dispersion(self, parameter, dispersion.cdisp) |
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159 | |
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160 | |
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161 | # End of file |
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