source: sasview/sansmodels/src/sans/models/LogNormal.py @ a3149c5

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Last change on this file since a3149c5 was 96656e3, checked in by Jae Cho <jhjcho@…>, 14 years ago

update models due to changes of template

  • Property mode set to 100644
File size: 4.2 KB
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[870f131]1#!/usr/bin/env python
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##############################################################################
[870f131]16
17
[79ac6f8]18"""
19Provide functionality for a C extension model
[870f131]20
[79ac6f8]21:WARNING: THIS FILE WAS GENERATED BY WRAPPERGENERATOR.PY
22         DO NOT MODIFY THIS FILE, MODIFY ..\c_extensions\logNormal.h
23         AND RE-RUN THE GENERATOR SCRIPT
[870f131]24
25"""
26
27from sans.models.BaseComponent import BaseComponent
28from sans_extension.c_models import CLogNormal
29import copy   
[96656e3]30
31def create_LogNormal():
32    obj = LogNormal()
33    #CLogNormal.__init__(obj) is called by LogNormal constructor
34    return obj
35
[870f131]36class LogNormal(CLogNormal, BaseComponent):
[79ac6f8]37    """
38    Class that evaluates a LogNormal model.
39    This file was auto-generated from ..\c_extensions\logNormal.h.
40    Refer to that file and the structure it contains
41    for details of the model.
42    List of default parameters:
[870f131]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(CLogNormal.__init__, (self,))
[870f131]55        CLogNormal.__init__(self)
56       
57        ## Name of the model
58        self.name = "LogNormal"
59        ## Model description
60        self.description ="""f(x)=scale * 1/(sigma*math.sqrt(2pi))e^(-1/2*((math.log(x)-mu)/sigma)^2)"""
61       
[fe9c19b4]62        ## Parameter details [units, min, max]
[870f131]63        self.details = {}
64        self.details['scale'] = ['', None, None]
65        self.details['sigma'] = ['', None, None]
66        self.details['center'] = ['', None, None]
67
[fe9c19b4]68        ## fittable parameters
[870f131]69        self.fixed=[]
70       
[35aface]71        ## non-fittable parameters
[96656e3]72        self.non_fittable = []
[35aface]73       
[870f131]74        ## parameters with orientation
[96656e3]75        self.orientation_params = []
[870f131]76   
[96656e3]77    def __reduce_ex__(self, proto):
[79ac6f8]78        """
[96656e3]79        Overwrite the __reduce_ex__ of PyTypeObject *type call in the init of
80        c model.
[79ac6f8]81        """
[96656e3]82        return (create_LogNormal,tuple())
[fe9c19b4]83       
[96656e3]84    def clone(self):
85        """ Return a identical copy of self """
86        return self._clone(LogNormal())   
[fe9c19b4]87       
[870f131]88   
[79ac6f8]89    def run(self, x=0.0):
90        """
91        Evaluate the model
92       
93        :param x: input q, or [q,phi]
94       
95        :return: scattering function P(q)
96       
[870f131]97        """
98       
99        return CLogNormal.run(self, x)
100   
[79ac6f8]101    def runXY(self, x=0.0):
102        """
103        Evaluate the model in cartesian coordinates
104       
105        :param x: input q, or [qx, qy]
106       
107        :return: scattering function P(q)
108       
[870f131]109        """
110       
111        return CLogNormal.runXY(self, x)
112       
[79ac6f8]113    def evalDistribution(self, x=[]):
114        """
115        Evaluate the model in cartesian coordinates
116       
117        :param x: input q[], or [qx[], qy[]]
118       
119        :return: scattering function P(q[])
120       
[870f131]121        """
[f9a1279]122        return CLogNormal.evalDistribution(self, x)
[870f131]123       
[5eb9154]124    def calculate_ER(self):
[79ac6f8]125        """
126        Calculate the effective radius for P(q)*S(q)
127       
128        :return: the value of the effective radius
129       
[5eb9154]130        """       
131        return CLogNormal.calculate_ER(self)
132       
[870f131]133    def set_dispersion(self, parameter, dispersion):
134        """
[79ac6f8]135        Set the dispersion object for a model parameter
136       
137        :param parameter: name of the parameter [string]
138        :param dispersion: dispersion object of type DispersionModel
139       
[870f131]140        """
141        return CLogNormal.set_dispersion(self, parameter, dispersion.cdisp)
142       
143   
144# End of file
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