source: sasview/sansmodels/src/sans/models/Lorentzian.py @ 1aaa579

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Last change on this file since 1aaa579 was 35aface, checked in by Jae Cho <jhjcho@…>, 14 years ago

addede new models and attr. non_fittable

  • Property mode set to 100644
File size: 4.5 KB
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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\lorentzian.h
23         AND RE-RUN THE GENERATOR SCRIPT
24
25"""
26
27from sans.models.BaseComponent import BaseComponent
28from sans_extension.c_models import CLorentzian
29import copy   
30   
31class Lorentzian(CLorentzian, BaseComponent):
32    """
33    Class that evaluates a Lorentzian model.
34    This file was auto-generated from ..\c_extensions\lorentzian.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         gamma           = 1.0
40         center          = 0.0
41
42    """
43       
44    def __init__(self):
45        """ Initialization """
46       
47        # Initialize BaseComponent first, then sphere
48        BaseComponent.__init__(self)
49        CLorentzian.__init__(self)
50       
51        ## Name of the model
52        self.name = "Lorentzian"
53        ## Model description
54        self.description ="""f(x)=scale * 1/pi 0.5gamma / [ (x-x_0)^2 + (0.5gamma)^2 ]"""
55       
56        ## Parameter details [units, min, max]
57        self.details = {}
58        self.details['scale'] = ['', None, None]
59        self.details['gamma'] = ['', None, None]
60        self.details['center'] = ['', None, None]
61
62        ## fittable parameters
63        self.fixed=[]
64       
65        ## non-fittable parameters
66        self.non_fittable=[]
67       
68        ## parameters with orientation
69        self.orientation_params =[]
70   
71    def clone(self):
72        """ Return a identical copy of self """
73        return self._clone(Lorentzian())   
74       
75    def __getstate__(self):
76        """
77        return object state for pickling and copying
78        """
79        model_state = {'params': self.params, 'dispersion': self.dispersion, 'log': self.log}
80       
81        return self.__dict__, model_state
82       
83    def __setstate__(self, state):
84        """
85        create object from pickled state
86       
87        :param state: the state of the current model
88       
89        """
90       
91        self.__dict__, model_state = state
92        self.params = model_state['params']
93        self.dispersion = model_state['dispersion']
94        self.log = model_state['log']
95       
96   
97    def run(self, x=0.0):
98        """
99        Evaluate the model
100       
101        :param x: input q, or [q,phi]
102       
103        :return: scattering function P(q)
104       
105        """
106       
107        return CLorentzian.run(self, x)
108   
109    def runXY(self, x=0.0):
110        """
111        Evaluate the model in cartesian coordinates
112       
113        :param x: input q, or [qx, qy]
114       
115        :return: scattering function P(q)
116       
117        """
118       
119        return CLorentzian.runXY(self, x)
120       
121    def evalDistribution(self, x=[]):
122        """
123        Evaluate the model in cartesian coordinates
124       
125        :param x: input q[], or [qx[], qy[]]
126       
127        :return: scattering function P(q[])
128       
129        """
130        return CLorentzian.evalDistribution(self, x)
131       
132    def calculate_ER(self):
133        """
134        Calculate the effective radius for P(q)*S(q)
135       
136        :return: the value of the effective radius
137       
138        """       
139        return CLorentzian.calculate_ER(self)
140       
141    def set_dispersion(self, parameter, dispersion):
142        """
143        Set the dispersion object for a model parameter
144       
145        :param parameter: name of the parameter [string]
146        :param dispersion: dispersion object of type DispersionModel
147       
148        """
149        return CLorentzian.set_dispersion(self, parameter, dispersion.cdisp)
150       
151   
152# End of file
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