[870f131] | 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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[5eb9154] | 19 | DO NOT MODIFY THIS FILE, MODIFY ..\c_extensions\lognormal.h |
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[870f131] | 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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[5eb9154] | 30 | This file was auto-generated from ..\c_extensions\lognormal.h. |
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[870f131] | 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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[5eb9154] | 91 | def calculate_ER(self): |
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| 92 | """ Calculate the effective radius for P(q)*S(q) |
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| 93 | @param x: input q, or [q,phi] |
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| 94 | @return: the value of the effective radius |
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| 95 | """ |
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| 96 | return CLogNormal.calculate_ER(self) |
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| 97 | |
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[870f131] | 98 | def set_dispersion(self, parameter, dispersion): |
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| 99 | """ |
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| 100 | Set the dispersion object for a model parameter |
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| 101 | @param parameter: name of the parameter [string] |
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| 102 | @dispersion: dispersion object of type DispersionModel |
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| 103 | """ |
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| 104 | return CLogNormal.set_dispersion(self, parameter, dispersion.cdisp) |
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| 105 | |
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| 106 | |
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| 107 | # End of file |
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