#!/usr/bin/env python ############################################################################## # This software was developed by the University of Tennessee as part of the # Distributed Data Analysis of Neutron Scattering Experiments (DANSE) # project funded by the US National Science Foundation. # # If you use DANSE applications to do scientific research that leads to # publication, we ask that you acknowledge the use of the software with the # following sentence: # # "This work benefited from DANSE software developed under NSF award DMR-0520547." # # copyright 2008, University of Tennessee ############################################################################## """ Provide functionality for a C extension model :WARNING: THIS FILE WAS GENERATED BY WRAPPERGENERATOR.PY DO NOT MODIFY THIS FILE, MODIFY [INCLUDE_FILE] AND RE-RUN THE GENERATOR SCRIPT """ from sans.models.BaseComponent import BaseComponent from sans_extension.c_models import [CPYTHONCLASS] import copy class [PYTHONCLASS]([CPYTHONCLASS], BaseComponent): """ Class that evaluates a [PYTHONCLASS] model. This file was auto-generated from [INCLUDE_FILE]. Refer to that file and the structure it contains for details of the model. [DEFAULT_LIST] """ def __init__(self): """ Initialization """ # Initialize BaseComponent first, then sphere BaseComponent.__init__(self) [CPYTHONCLASS].__init__(self) ## Name of the model self.name = "[PYTHONCLASS]" ## Model description self.description ="""[DESCRIPTION]""" [PAR_DETAILS] ## fittable parameters self.fixed=[FIXED] ## parameters with orientation self.orientation_params =[ORIENTATION_PARAMS] def clone(self): """ Return a identical copy of self """ return self._clone([PYTHONCLASS]()) def __getstate__(self): """ return object state for pickling and copying """ model_state = {'params': self.params, 'dispersion': self.dispersion, 'log': self.log} return self.__dict__, model_state def __setstate__(self, state): """ create object from pickled state :param state: the state of the current model """ self.__dict__, model_state = state self.params = model_state['params'] self.dispersion = model_state['dispersion'] self.log = model_state['log'] def run(self, x=0.0): """ Evaluate the model :param x: input q, or [q,phi] :return: scattering function P(q) """ return [CPYTHONCLASS].run(self, x) def runXY(self, x=0.0): """ Evaluate the model in cartesian coordinates :param x: input q, or [qx, qy] :return: scattering function P(q) """ return [CPYTHONCLASS].runXY(self, x) def evalDistribution(self, x=[]): """ Evaluate the model in cartesian coordinates :param x: input q[], or [qx[], qy[]] :return: scattering function P(q[]) """ return [CPYTHONCLASS].evalDistribution(self, x) def calculate_ER(self): """ Calculate the effective radius for P(q)*S(q) :return: the value of the effective radius """ return [CPYTHONCLASS].calculate_ER(self) def set_dispersion(self, parameter, dispersion): """ Set the dispersion object for a model parameter :param parameter: name of the parameter [string] :param dispersion: dispersion object of type DispersionModel """ return [CPYTHONCLASS].set_dispersion(self, parameter, dispersion.cdisp) # End of file