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 | |
---|
24 | from sans.models.BaseComponent import BaseComponent |
---|
25 | from sans_extension.c_models import CGaussian |
---|
26 | import copy |
---|
27 | |
---|
28 | class 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 |
---|