source: sasview/sansmodels/src/sans/models/Gaussian.py @ 876192b2

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Last change on this file since 876192b2 was c7a7e1b, checked in by Gervaise Alina <gervyh@…>, 13 years ago

working on model pickle

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[ae3ce4e]1#!/usr/bin/env python
[95986b5]2
[79ac6f8]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##############################################################################
[95986b5]16
17
[79ac6f8]18"""
19Provide functionality for a C extension model
[ae3ce4e]20
[79ac6f8]21:WARNING: THIS FILE WAS GENERATED BY WRAPPERGENERATOR.PY
22         DO NOT MODIFY THIS FILE, MODIFY ..\c_extensions\gaussian.h
23         AND RE-RUN THE GENERATOR SCRIPT
[ae3ce4e]24
25"""
26
27from sans.models.BaseComponent import BaseComponent
28from sans_extension.c_models import CGaussian
29import copy   
[96656e3]30
31def create_Gaussian():
32    obj = Gaussian()
33    #CGaussian.__init__(obj) is called by Gaussian constructor
34    return obj
35
[ae3ce4e]36class Gaussian(CGaussian, BaseComponent):
[79ac6f8]37    """
38    Class that evaluates a Gaussian model.
39    This file was auto-generated from ..\c_extensions\gaussian.h.
40    Refer to that file and the structure it contains
41    for details of the model.
42    List of default parameters:
[ae3ce4e]43         scale           = 1.0
44         sigma           = 1.0
45         center          = 0.0
46
47    """
48       
49    def __init__(self):
50        """ Initialization """
51       
52        # Initialize BaseComponent first, then sphere
53        BaseComponent.__init__(self)
[96656e3]54        #apply(CGaussian.__init__, (self,))
[ae3ce4e]55        CGaussian.__init__(self)
56       
57        ## Name of the model
58        self.name = "Gaussian"
[9bd69098]59        ## Model description
[95986b5]60        self.description ="""f(x)=scale * 1/(sigma^2*2pi)e^(-(x-mu)^2/2sigma^2)"""
[9bd69098]61       
[fe9c19b4]62        ## Parameter details [units, min, max]
[ae3ce4e]63        self.details = {}
64        self.details['scale'] = ['', None, None]
65        self.details['sigma'] = ['', None, None]
66        self.details['center'] = ['', None, None]
[9bd69098]67
[fe9c19b4]68        ## fittable parameters
[9bd69098]69        self.fixed=[]
70       
[35aface]71        ## non-fittable parameters
[96656e3]72        self.non_fittable = []
[35aface]73       
[9bd69098]74        ## parameters with orientation
[96656e3]75        self.orientation_params = []
[c7a7e1b]76
77    def __setstate__(self, state):
78        """
79        restore the state of a model from pickle
80        """
81        self.__dict__, self.params, self.dispersion = state
82       
[96656e3]83    def __reduce_ex__(self, proto):
[79ac6f8]84        """
[96656e3]85        Overwrite the __reduce_ex__ of PyTypeObject *type call in the init of
86        c model.
[79ac6f8]87        """
[c7a7e1b]88        state = (self.__dict__, self.params, self.dispersion)
89        return (create_Gaussian,tuple(), state, None, None)
[fe9c19b4]90       
[96656e3]91    def clone(self):
92        """ Return a identical copy of self """
93        return self._clone(Gaussian())   
[fe9c19b4]94       
[ae3ce4e]95   
[79ac6f8]96    def run(self, x=0.0):
97        """
98        Evaluate the model
99       
100        :param x: input q, or [q,phi]
101       
102        :return: scattering function P(q)
103       
[ae3ce4e]104        """
105       
106        return CGaussian.run(self, x)
107   
[79ac6f8]108    def runXY(self, x=0.0):
109        """
110        Evaluate the model in cartesian coordinates
111       
112        :param x: input q, or [qx, qy]
113       
114        :return: scattering function P(q)
115       
[ae3ce4e]116        """
117       
118        return CGaussian.runXY(self, x)
[95986b5]119       
[79ac6f8]120    def evalDistribution(self, x=[]):
121        """
122        Evaluate the model in cartesian coordinates
123       
124        :param x: input q[], or [qx[], qy[]]
125       
126        :return: scattering function P(q[])
127       
[9bd69098]128        """
[f9a1279]129        return CGaussian.evalDistribution(self, x)
[9bd69098]130       
[5eb9154]131    def calculate_ER(self):
[79ac6f8]132        """
133        Calculate the effective radius for P(q)*S(q)
134       
135        :return: the value of the effective radius
136       
[5eb9154]137        """       
138        return CGaussian.calculate_ER(self)
139       
[95986b5]140    def set_dispersion(self, parameter, dispersion):
141        """
[79ac6f8]142        Set the dispersion object for a model parameter
143       
144        :param parameter: name of the parameter [string]
145        :param dispersion: dispersion object of type DispersionModel
146       
[95986b5]147        """
148        return CGaussian.set_dispersion(self, parameter, dispersion.cdisp)
149       
[ae3ce4e]150   
151# End of file
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