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