source: sasview/sansmodels/src/sans/models/LamellarPSHGModel.py @ 96d19c6

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Last change on this file since 96d19c6 was 35aface, checked in by Jae Cho <jhjcho@…>, 14 years ago

addede new models and attr. non_fittable

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1#!/usr/bin/env python
2
3##############################################################################
4#       This software was developed by the University of Tennessee as part of the
5#       Distributed Data Analysis of Neutron Scattering Experiments (DANSE)
6#       project funded by the US National Science Foundation.
7#
8#       If you use DANSE applications to do scientific research that leads to
9#       publication, we ask that you acknowledge the use of the software with the
10#       following sentence:
11#
12#       "This work benefited from DANSE software developed under NSF award DMR-0520547."
13#
14#       copyright 2008, University of Tennessee
15##############################################################################
16
17
18"""
19Provide functionality for a C extension model
20
21:WARNING: THIS FILE WAS GENERATED BY WRAPPERGENERATOR.PY
22         DO NOT MODIFY THIS FILE, MODIFY ..\c_extensions\lamellarPS_HG.h
23         AND RE-RUN THE GENERATOR SCRIPT
24
25"""
26
27from sans.models.BaseComponent import BaseComponent
28from sans_extension.c_models import CLamellarPSHGModel
29import copy   
30   
31class LamellarPSHGModel(CLamellarPSHGModel, BaseComponent):
32    """
33    Class that evaluates a LamellarPSHGModel model.
34    This file was auto-generated from ..\c_extensions\lamellarPS_HG.h.
35    Refer to that file and the structure it contains
36    for details of the model.
37    List of default parameters:
38         scale           = 1.0
39         spacing         = 40.0 [A]
40         deltaT          = 10.0 [A]
41         deltaH          = 2.0 [A]
42         sld_tail        = 4e-007 [1/A^(2)]
43         sld_head        = 2e-006 [1/A^(2)]
44         sld_solvent     = 6e-006 [1/A^(2)]
45         n_plates        = 30.0
46         caille          = 0.001
47         background      = 0.001 [1/cm]
48
49    """
50       
51    def __init__(self):
52        """ Initialization """
53       
54        # Initialize BaseComponent first, then sphere
55        BaseComponent.__init__(self)
56        CLamellarPSHGModel.__init__(self)
57       
58        ## Name of the model
59        self.name = "LamellarPSHGModel"
60        ## Model description
61        self.description ="""[Concentrated Lamellar (head+tail) Form Factor]: Calculates the
62                intensity from a lyotropic lamellar phase.
63                The intensity (form factor and structure factor)
64                calculated is for lamellae of two-layer scattering
65                length density that are randomly distributed in
66                solution (a powder average). The scattering
67                length density of the tail region, headgroup
68                region, and solvent are taken to be different.
69                The model can also be applied to large,
70                multi-lamellar vesicles.
71                No resolution smeared version is included
72                in the structure factor of this model.
73                *Parameters: spacing = repeat spacing,
74                deltaT = tail length,
75                deltaH = headgroup thickness,
76                n_plates = # of Lamellar plates
77                caille = Caille parameter (<0.8 or <1)
78                background = incoherent bgd
79                scale = scale factor ..."""
80       
81        ## Parameter details [units, min, max]
82        self.details = {}
83        self.details['scale'] = ['', None, None]
84        self.details['spacing'] = ['[A]', None, None]
85        self.details['deltaT'] = ['[A]', None, None]
86        self.details['deltaH'] = ['[A]', None, None]
87        self.details['sld_tail'] = ['[1/A^(2)]', None, None]
88        self.details['sld_head'] = ['[1/A^(2)]', None, None]
89        self.details['sld_solvent'] = ['[1/A^(2)]', None, None]
90        self.details['n_plates'] = ['', None, None]
91        self.details['caille'] = ['', None, None]
92        self.details['background'] = ['[1/cm]', None, None]
93
94        ## fittable parameters
95        self.fixed=['deltaT.width', 'deltaH.width', 'spacing.width']
96       
97        ## non-fittable parameters
98        self.non_fittable=[]
99       
100        ## parameters with orientation
101        self.orientation_params =[]
102   
103    def clone(self):
104        """ Return a identical copy of self """
105        return self._clone(LamellarPSHGModel())   
106       
107    def __getstate__(self):
108        """
109        return object state for pickling and copying
110        """
111        model_state = {'params': self.params, 'dispersion': self.dispersion, 'log': self.log}
112       
113        return self.__dict__, model_state
114       
115    def __setstate__(self, state):
116        """
117        create object from pickled state
118       
119        :param state: the state of the current model
120       
121        """
122       
123        self.__dict__, model_state = state
124        self.params = model_state['params']
125        self.dispersion = model_state['dispersion']
126        self.log = model_state['log']
127       
128   
129    def run(self, x=0.0):
130        """
131        Evaluate the model
132       
133        :param x: input q, or [q,phi]
134       
135        :return: scattering function P(q)
136       
137        """
138       
139        return CLamellarPSHGModel.run(self, x)
140   
141    def runXY(self, x=0.0):
142        """
143        Evaluate the model in cartesian coordinates
144       
145        :param x: input q, or [qx, qy]
146       
147        :return: scattering function P(q)
148       
149        """
150       
151        return CLamellarPSHGModel.runXY(self, x)
152       
153    def evalDistribution(self, x=[]):
154        """
155        Evaluate the model in cartesian coordinates
156       
157        :param x: input q[], or [qx[], qy[]]
158       
159        :return: scattering function P(q[])
160       
161        """
162        return CLamellarPSHGModel.evalDistribution(self, x)
163       
164    def calculate_ER(self):
165        """
166        Calculate the effective radius for P(q)*S(q)
167       
168        :return: the value of the effective radius
169       
170        """       
171        return CLamellarPSHGModel.calculate_ER(self)
172       
173    def set_dispersion(self, parameter, dispersion):
174        """
175        Set the dispersion object for a model parameter
176       
177        :param parameter: name of the parameter [string]
178        :param dispersion: dispersion object of type DispersionModel
179       
180        """
181        return CLamellarPSHGModel.set_dispersion(self, parameter, dispersion.cdisp)
182       
183   
184# End of file
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