source: sasview/sansmodels/src/sans/models/Gaussian.py @ fe9c19b4

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Last change on this file since fe9c19b4 was fe9c19b4, checked in by Gervaise Alina <gervyh@…>, 15 years ago

implement set and get state

  • Property mode set to 100644
File size: 4.2 KB
Line 
1#!/usr/bin/env python
2"""
3        This software was developed by the University of Tennessee as part of the
4        Distributed Data Analysis of Neutron Scattering Experiments (DANSE)
5        project funded by the US National Science Foundation.
6
7        If you use DANSE applications to do scientific research that leads to
8        publication, we ask that you acknowledge the use of the software with the
9        following sentence:
10
11        "This work benefited from DANSE software developed under NSF award DMR-0520547."
12
13        copyright 2008, University of Tennessee
14"""
15
16""" Provide functionality for a C extension model
17
18        WARNING: THIS FILE WAS GENERATED BY WRAPPERGENERATOR.PY
19                 DO NOT MODIFY THIS FILE, MODIFY ..\c_extensions\gaussian.h
20                 AND RE-RUN THE GENERATOR SCRIPT
21
22"""
23
24from sans.models.BaseComponent import BaseComponent
25from sans_extension.c_models import CGaussian
26import copy   
27   
28class Gaussian(CGaussian, BaseComponent):
29    """ Class that evaluates a Gaussian model.
30        This file was auto-generated from ..\c_extensions\gaussian.h.
31        Refer to that file and the structure it contains
32        for details of the model.
33        List of default parameters:
34         scale           = 1.0
35         sigma           = 1.0
36         center          = 0.0
37
38    """
39       
40    def __init__(self):
41        """ Initialization """
42       
43        # Initialize BaseComponent first, then sphere
44        BaseComponent.__init__(self)
45        CGaussian.__init__(self)
46       
47        ## Name of the model
48        self.name = "Gaussian"
49        ## Model description
50        self.description ="""f(x)=scale * 1/(sigma^2*2pi)e^(-(x-mu)^2/2sigma^2)"""
51       
52        ## Parameter details [units, min, max]
53        self.details = {}
54        self.details['scale'] = ['', None, None]
55        self.details['sigma'] = ['', None, None]
56        self.details['center'] = ['', None, None]
57
58        ## fittable parameters
59        self.fixed=[]
60       
61        ## parameters with orientation
62        self.orientation_params =[]
63   
64    def clone(self):
65        """ Return a identical copy of self """
66        return self._clone(Gaussian())   
67       
68    def __getstate__(self):
69        """ return object state for pickling and copying """
70        print "__dict__",self.__dict__
71        #self.__dict__['params'] = self.params
72        #self.__dict__['dispersion'] = self.dispersion
73        #self.__dict__['log'] = self.log
74        model_state = {'params': self.params, 'dispersion': self.dispersion, 'log': self.log}
75       
76        return self.__dict__, model_state
77       
78    def __setstate__(self, state):
79        """ create object from pickled state """
80       
81        self.__dict__, model_state = state
82        self.params = model_state['params']
83        self.dispersion = model_state['dispersion']
84        self.log = model_state['log']
85       
86   
87    def run(self, x = 0.0):
88        """ Evaluate the model
89            @param x: input q, or [q,phi]
90            @return: scattering function P(q)
91        """
92       
93        return CGaussian.run(self, x)
94   
95    def runXY(self, x = 0.0):
96        """ Evaluate the model in cartesian coordinates
97            @param x: input q, or [qx, qy]
98            @return: scattering function P(q)
99        """
100       
101        return CGaussian.runXY(self, x)
102       
103    def evalDistribition(self, x = []):
104        """ Evaluate the model in cartesian coordinates
105            @param x: input q[], or [qx[], qy[]]
106            @return: scattering function P(q[])
107        """
108        return CGaussian.evalDistribition(self, x)
109       
110    def calculate_ER(self):
111        """ Calculate the effective radius for P(q)*S(q)
112            @return: the value of the effective radius
113        """       
114        return CGaussian.calculate_ER(self)
115       
116    def set_dispersion(self, parameter, dispersion):
117        """
118            Set the dispersion object for a model parameter
119            @param parameter: name of the parameter [string]
120            @dispersion: dispersion object of type DispersionModel
121        """
122        return CGaussian.set_dispersion(self, parameter, dispersion.cdisp)
123       
124   
125# End of file
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