source: sasview/sansmodels/src/sans/models/Lorentzian.py @ 5650ebf

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Last change on this file since 5650ebf was 35aface, checked in by Jae Cho <jhjcho@…>, 14 years ago

addede new models and attr. non_fittable

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File size: 4.5 KB
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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\lorentzian.h
23         AND RE-RUN THE GENERATOR SCRIPT
[ae3ce4e]24
25"""
26
27from sans.models.BaseComponent import BaseComponent
28from sans_extension.c_models import CLorentzian
29import copy   
30   
31class Lorentzian(CLorentzian, BaseComponent):
[79ac6f8]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:
[ae3ce4e]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"
[9bd69098]53        ## Model description
[95986b5]54        self.description ="""f(x)=scale * 1/pi 0.5gamma / [ (x-x_0)^2 + (0.5gamma)^2 ]"""
[9bd69098]55       
[fe9c19b4]56        ## Parameter details [units, min, max]
[ae3ce4e]57        self.details = {}
58        self.details['scale'] = ['', None, None]
59        self.details['gamma'] = ['', None, None]
60        self.details['center'] = ['', None, None]
[9bd69098]61
[fe9c19b4]62        ## fittable parameters
[9bd69098]63        self.fixed=[]
64       
[35aface]65        ## non-fittable parameters
66        self.non_fittable=[]
67       
[9bd69098]68        ## parameters with orientation
69        self.orientation_params =[]
[ae3ce4e]70   
71    def clone(self):
72        """ Return a identical copy of self """
[95986b5]73        return self._clone(Lorentzian())   
[fe9c19b4]74       
75    def __getstate__(self):
[79ac6f8]76        """
77        return object state for pickling and copying
78        """
[fe9c19b4]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):
[79ac6f8]84        """
85        create object from pickled state
86       
87        :param state: the state of the current model
88       
89        """
[fe9c19b4]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       
[ae3ce4e]96   
[79ac6f8]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       
[ae3ce4e]105        """
106       
107        return CLorentzian.run(self, x)
108   
[79ac6f8]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       
[ae3ce4e]117        """
118       
119        return CLorentzian.runXY(self, x)
[95986b5]120       
[79ac6f8]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       
[9bd69098]129        """
[f9a1279]130        return CLorentzian.evalDistribution(self, x)
[9bd69098]131       
[5eb9154]132    def calculate_ER(self):
[79ac6f8]133        """
134        Calculate the effective radius for P(q)*S(q)
135       
136        :return: the value of the effective radius
137       
[5eb9154]138        """       
139        return CLorentzian.calculate_ER(self)
140       
[95986b5]141    def set_dispersion(self, parameter, dispersion):
142        """
[79ac6f8]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       
[95986b5]148        """
149        return CLorentzian.set_dispersion(self, parameter, dispersion.cdisp)
150       
[ae3ce4e]151   
152# End of file
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