[400155b] | 1 | ############################################################################## |
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| 2 | # This software was developed by the University of Tennessee as part of the |
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| 3 | # Distributed Data Analysis of Neutron Scattering Experiments (DANSE) |
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| 4 | # project funded by the US National Science Foundation. |
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| 5 | # |
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| 6 | # If you use DANSE applications to do scientific research that leads to |
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| 7 | # publication, we ask that you acknowledge the use of the software with the |
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| 8 | # following sentence: |
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| 9 | # |
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| 10 | # This work benefited from DANSE software developed under NSF award DMR-0520547 |
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| 11 | # |
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| 12 | # Copyright 2008-2011, University of Tennessee |
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| 13 | ############################################################################## |
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| 14 | |
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| 15 | """ |
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| 16 | Provide functionality for a C extension model |
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| 17 | |
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| 18 | .. WARNING:: |
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| 19 | |
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| 20 | THIS FILE WAS GENERATED BY WRAPPERGENERATOR.PY |
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| 21 | DO NOT MODIFY THIS FILE, MODIFY |
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| 22 | src\sans\models\include\onion.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 | from sans.models.BaseComponent import BaseComponent |
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| 27 | from sans.models.sans_extension.c_models import COnionModel |
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| 28 | |
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| 29 | def create_OnionModel(): |
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| 30 | """ |
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| 31 | Create a model instance |
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| 32 | """ |
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| 33 | obj = OnionModel() |
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| 34 | # COnionModel.__init__(obj) is called by |
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| 35 | # the OnionModel constructor |
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| 36 | return obj |
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| 37 | |
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| 38 | class OnionModel(COnionModel, BaseComponent): |
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| 39 | """ |
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| 40 | Class that evaluates a OnionModel model. |
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| 41 | This file was auto-generated from src\sans\models\include\onion.h. |
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| 42 | Refer to that file and the structure it contains |
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| 43 | for details of the model. |
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| 44 | |
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| 45 | List of default parameters: |
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| 46 | |
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| 47 | * n_shells = 1.0 |
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| 48 | * scale = 1.0 |
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| 49 | * rad_core0 = 200.0 [A] |
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| 50 | * sld_core0 = 1e-06 [1/A^(2)] |
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| 51 | * sld_solv = 6.4e-06 [1/A^(2)] |
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| 52 | * background = 0.0 [1/cm] |
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| 53 | * sld_out_shell1 = 2e-06 [1/A^(2)] |
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| 54 | * sld_out_shell2 = 2.5e-06 [1/A^(2)] |
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| 55 | * sld_out_shell3 = 3e-06 [1/A^(2)] |
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| 56 | * sld_out_shell4 = 3.5e-06 [1/A^(2)] |
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| 57 | * sld_out_shell5 = 4e-06 [1/A^(2)] |
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| 58 | * sld_out_shell6 = 4.5e-06 [1/A^(2)] |
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| 59 | * sld_out_shell7 = 5e-06 [1/A^(2)] |
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| 60 | * sld_out_shell8 = 5.5e-06 [1/A^(2)] |
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| 61 | * sld_out_shell9 = 6e-06 [1/A^(2)] |
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| 62 | * sld_out_shell10 = 6.2e-06 [1/A^(2)] |
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| 63 | * sld_in_shell1 = 1.7e-06 [1/A^(2)] |
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| 64 | * sld_in_shell2 = 2.2e-06 [1/A^(2)] |
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| 65 | * sld_in_shell3 = 2.7e-06 [1/A^(2)] |
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| 66 | * sld_in_shell4 = 3.2e-06 [1/A^(2)] |
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| 67 | * sld_in_shell5 = 3.7e-06 [1/A^(2)] |
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| 68 | * sld_in_shell6 = 4.2e-06 [1/A^(2)] |
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| 69 | * sld_in_shell7 = 4.7e-06 [1/A^(2)] |
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| 70 | * sld_in_shell8 = 5.2e-06 [1/A^(2)] |
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| 71 | * sld_in_shell9 = 5.7e-06 [1/A^(2)] |
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| 72 | * sld_in_shell10 = 6e-06 [1/A^(2)] |
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| 73 | * A_shell1 = 1.0 |
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| 74 | * A_shell2 = 1.0 |
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| 75 | * A_shell3 = 1.0 |
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| 76 | * A_shell4 = 1.0 |
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| 77 | * A_shell5 = 1.0 |
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| 78 | * A_shell6 = 1.0 |
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| 79 | * A_shell7 = 1.0 |
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| 80 | * A_shell8 = 1.0 |
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| 81 | * A_shell9 = 1.0 |
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| 82 | * A_shell10 = 1.0 |
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| 83 | * thick_shell1 = 50.0 [A] |
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| 84 | * thick_shell2 = 50.0 [A] |
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| 85 | * thick_shell3 = 50.0 [A] |
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| 86 | * thick_shell4 = 50.0 [A] |
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| 87 | * thick_shell5 = 50.0 [A] |
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| 88 | * thick_shell6 = 50.0 [A] |
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| 89 | * thick_shell7 = 50.0 [A] |
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| 90 | * thick_shell8 = 50.0 [A] |
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| 91 | * thick_shell9 = 50.0 [A] |
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| 92 | * thick_shell10 = 50.0 [A] |
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| 93 | * func_shell1 = 2.0 |
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| 94 | * func_shell2 = 2.0 |
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| 95 | * func_shell3 = 2.0 |
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| 96 | * func_shell4 = 2.0 |
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| 97 | * func_shell5 = 2.0 |
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| 98 | * func_shell6 = 2.0 |
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| 99 | * func_shell7 = 2.0 |
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| 100 | * func_shell8 = 2.0 |
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| 101 | * func_shell9 = 2.0 |
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| 102 | * func_shell10 = 2.0 |
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| 103 | |
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| 104 | """ |
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| 105 | |
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| 106 | def __init__(self, multfactor=1): |
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| 107 | """ Initialization """ |
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| 108 | self.__dict__ = {} |
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| 109 | |
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| 110 | # Initialize BaseComponent first, then sphere |
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| 111 | BaseComponent.__init__(self) |
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| 112 | #apply(COnionModel.__init__, (self,)) |
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| 113 | |
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| 114 | COnionModel.__init__(self) |
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| 115 | self.is_multifunc = False |
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| 116 | |
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| 117 | ## Name of the model |
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| 118 | self.name = "OnionModel" |
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| 119 | ## Model description |
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| 120 | self.description = """ |
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| 121 | Form factor of mutishells normalized by the volume. Here each shell is described |
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| 122 | by an exponential function; |
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| 123 | I) |
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| 124 | For A_shell != 0, |
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| 125 | f(r) = B*exp(A_shell*(r-r_in)/thick_shell)+C |
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| 126 | where |
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| 127 | B=(sld_out-sld_in)/(exp(A_shell)-1) |
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| 128 | C=sld_in-B. |
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| 129 | Note that in the above case, |
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| 130 | the function becomes a linear function |
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| 131 | as A_shell --> 0+ or 0-. |
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| 132 | II) |
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| 133 | For the exact point of A_shell == 0, |
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| 134 | f(r) = sld_in ,i.e., it crosses over flat function |
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| 135 | Note that the 'sld_out' becaomes NULL in this case. |
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| 136 | |
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| 137 | background:background, |
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| 138 | rad_core0: radius of sphere(core) |
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| 139 | thick_shell#:the thickness of the shell# |
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| 140 | sld_core0: the SLD of the sphere |
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| 141 | sld_solv: the SLD of the solvent |
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| 142 | sld_shell: the SLD of the shell# |
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| 143 | A_shell#: the coefficient in the exponential function |
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| 144 | """ |
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| 145 | |
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| 146 | ## Parameter details [units, min, max] |
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| 147 | self.details = {} |
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| 148 | self.details['n_shells'] = ['', None, None] |
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| 149 | self.details['scale'] = ['', None, None] |
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| 150 | self.details['rad_core0'] = ['[A]', None, None] |
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| 151 | self.details['sld_core0'] = ['[1/A^(2)]', None, None] |
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| 152 | self.details['sld_solv'] = ['[1/A^(2)]', None, None] |
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| 153 | self.details['background'] = ['[1/cm]', None, None] |
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| 154 | self.details['sld_out_shell1'] = ['[1/A^(2)]', None, None] |
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| 155 | self.details['sld_out_shell2'] = ['[1/A^(2)]', None, None] |
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| 156 | self.details['sld_out_shell3'] = ['[1/A^(2)]', None, None] |
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| 157 | self.details['sld_out_shell4'] = ['[1/A^(2)]', None, None] |
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| 158 | self.details['sld_out_shell5'] = ['[1/A^(2)]', None, None] |
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| 159 | self.details['sld_out_shell6'] = ['[1/A^(2)]', None, None] |
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| 160 | self.details['sld_out_shell7'] = ['[1/A^(2)]', None, None] |
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| 161 | self.details['sld_out_shell8'] = ['[1/A^(2)]', None, None] |
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| 162 | self.details['sld_out_shell9'] = ['[1/A^(2)]', None, None] |
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| 163 | self.details['sld_out_shell10'] = ['[1/A^(2)]', None, None] |
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| 164 | self.details['sld_in_shell1'] = ['[1/A^(2)]', None, None] |
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| 165 | self.details['sld_in_shell2'] = ['[1/A^(2)]', None, None] |
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| 166 | self.details['sld_in_shell3'] = ['[1/A^(2)]', None, None] |
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| 167 | self.details['sld_in_shell4'] = ['[1/A^(2)]', None, None] |
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| 168 | self.details['sld_in_shell5'] = ['[1/A^(2)]', None, None] |
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| 169 | self.details['sld_in_shell6'] = ['[1/A^(2)]', None, None] |
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| 170 | self.details['sld_in_shell7'] = ['[1/A^(2)]', None, None] |
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| 171 | self.details['sld_in_shell8'] = ['[1/A^(2)]', None, None] |
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| 172 | self.details['sld_in_shell9'] = ['[1/A^(2)]', None, None] |
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| 173 | self.details['sld_in_shell10'] = ['[1/A^(2)]', None, None] |
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| 174 | self.details['A_shell1'] = ['', None, None] |
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| 175 | self.details['A_shell2'] = ['', None, None] |
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| 176 | self.details['A_shell3'] = ['', None, None] |
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| 177 | self.details['A_shell4'] = ['', None, None] |
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| 178 | self.details['A_shell5'] = ['', None, None] |
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| 179 | self.details['A_shell6'] = ['', None, None] |
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| 180 | self.details['A_shell7'] = ['', None, None] |
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| 181 | self.details['A_shell8'] = ['', None, None] |
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| 182 | self.details['A_shell9'] = ['', None, None] |
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| 183 | self.details['A_shell10'] = ['', None, None] |
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| 184 | self.details['thick_shell1'] = ['[A]', None, None] |
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| 185 | self.details['thick_shell2'] = ['[A]', None, None] |
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| 186 | self.details['thick_shell3'] = ['[A]', None, None] |
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| 187 | self.details['thick_shell4'] = ['[A]', None, None] |
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| 188 | self.details['thick_shell5'] = ['[A]', None, None] |
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| 189 | self.details['thick_shell6'] = ['[A]', None, None] |
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| 190 | self.details['thick_shell7'] = ['[A]', None, None] |
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| 191 | self.details['thick_shell8'] = ['[A]', None, None] |
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| 192 | self.details['thick_shell9'] = ['[A]', None, None] |
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| 193 | self.details['thick_shell10'] = ['[A]', None, None] |
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| 194 | self.details['func_shell1'] = ['', None, None] |
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| 195 | self.details['func_shell2'] = ['', None, None] |
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| 196 | self.details['func_shell3'] = ['', None, None] |
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| 197 | self.details['func_shell4'] = ['', None, None] |
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| 198 | self.details['func_shell5'] = ['', None, None] |
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| 199 | self.details['func_shell6'] = ['', None, None] |
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| 200 | self.details['func_shell7'] = ['', None, None] |
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| 201 | self.details['func_shell8'] = ['', None, None] |
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| 202 | self.details['func_shell9'] = ['', None, None] |
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| 203 | self.details['func_shell10'] = ['', None, None] |
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| 204 | |
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| 205 | ## fittable parameters |
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| 206 | self.fixed = ['rad_core0.width', |
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| 207 | 'thick_shell1.width', |
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| 208 | 'thick_shell2.width', |
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| 209 | 'thick_shell3.width', |
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| 210 | 'thick_shell4.width', |
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| 211 | 'thick_shell5.width', |
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| 212 | 'thick_shell6.width', |
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| 213 | 'thick_shell7.width', |
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| 214 | 'thick_shell8.width', |
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| 215 | 'thick_shell9.width', |
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| 216 | 'thick_shell10.width'] |
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| 217 | |
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| 218 | ## non-fittable parameters |
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| 219 | self.non_fittable = [] |
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| 220 | |
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| 221 | ## parameters with orientation |
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| 222 | self.orientation_params = [] |
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| 223 | |
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| 224 | ## parameters with magnetism |
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| 225 | self.magnetic_params = [] |
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| 226 | |
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| 227 | self.category = None |
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| 228 | self.multiplicity_info = None |
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| 229 | |
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| 230 | def __setstate__(self, state): |
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| 231 | """ |
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| 232 | restore the state of a model from pickle |
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| 233 | """ |
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| 234 | self.__dict__, self.params, self.dispersion = state |
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| 235 | |
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| 236 | def __reduce_ex__(self, proto): |
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| 237 | """ |
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| 238 | Overwrite the __reduce_ex__ of PyTypeObject *type call in the init of |
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| 239 | c model. |
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| 240 | """ |
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| 241 | state = (self.__dict__, self.params, self.dispersion) |
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| 242 | return (create_OnionModel, tuple(), state, None, None) |
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| 243 | |
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| 244 | def clone(self): |
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| 245 | """ Return a identical copy of self """ |
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| 246 | return self._clone(OnionModel()) |
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| 247 | |
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| 248 | def run(self, x=0.0): |
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| 249 | """ |
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| 250 | Evaluate the model |
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| 251 | |
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| 252 | :param x: input q, or [q,phi] |
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| 253 | |
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| 254 | :return: scattering function P(q) |
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| 255 | |
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| 256 | """ |
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| 257 | return COnionModel.run(self, x) |
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| 258 | |
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| 259 | def runXY(self, x=0.0): |
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| 260 | """ |
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| 261 | Evaluate the model in cartesian coordinates |
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| 262 | |
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| 263 | :param x: input q, or [qx, qy] |
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| 264 | |
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| 265 | :return: scattering function P(q) |
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| 266 | |
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| 267 | """ |
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| 268 | return COnionModel.runXY(self, x) |
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| 269 | |
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| 270 | def evalDistribution(self, x): |
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| 271 | """ |
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| 272 | Evaluate the model in cartesian coordinates |
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| 273 | |
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| 274 | :param x: input q[], or [qx[], qy[]] |
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| 275 | |
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| 276 | :return: scattering function P(q[]) |
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| 277 | |
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| 278 | """ |
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| 279 | return COnionModel.evalDistribution(self, x) |
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| 280 | |
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| 281 | def calculate_ER(self): |
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| 282 | """ |
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| 283 | Calculate the effective radius for P(q)*S(q) |
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| 284 | |
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| 285 | :return: the value of the effective radius |
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| 286 | |
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| 287 | """ |
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| 288 | return COnionModel.calculate_ER(self) |
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| 289 | |
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| 290 | def calculate_VR(self): |
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| 291 | """ |
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| 292 | Calculate the volf ratio for P(q)*S(q) |
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| 293 | |
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| 294 | :return: the value of the volf ratio |
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| 295 | |
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| 296 | """ |
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| 297 | return COnionModel.calculate_VR(self) |
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| 298 | |
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| 299 | def set_dispersion(self, parameter, dispersion): |
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| 300 | """ |
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| 301 | Set the dispersion object for a model parameter |
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| 302 | |
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| 303 | :param parameter: name of the parameter [string] |
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| 304 | :param dispersion: dispersion object of type DispersionModel |
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| 305 | |
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| 306 | """ |
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| 307 | return COnionModel.set_dispersion(self, |
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| 308 | parameter, dispersion.cdisp) |
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| 309 | |
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| 310 | |
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| 311 | # End of file |
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| 312 | |
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