#!/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 ..\c_extensions\sld_cal.h AND RE-RUN THE GENERATOR SCRIPT """ from sans.models.BaseComponent import BaseComponent from sans_extension.c_models import CSLDCalFunc import copy def create_SLDCalFunc(): obj = SLDCalFunc() #CSLDCalFunc.__init__(obj) is called by SLDCalFunc constructor return obj class SLDCalFunc(CSLDCalFunc, BaseComponent): """ Class that evaluates a SLDCalFunc model. This file was auto-generated from ..\c_extensions\sld_cal.h. Refer to that file and the structure it contains for details of the model. List of default parameters: fun_type = 0.0 npts_inter = 21.0 shell_num = 0.0 nu_inter = 2.5 sld_left = 0.0 [1/A^(2)] sld_right = 0.0 [1/A^(2)] """ def __init__(self): """ Initialization """ # Initialize BaseComponent first, then sphere BaseComponent.__init__(self) #apply(CSLDCalFunc.__init__, (self,)) CSLDCalFunc.__init__(self) ## Name of the model self.name = "SLDCalFunc" ## Model description self.description ="""To calculate sld values""" ## Parameter details [units, min, max] self.details = {} self.details['fun_type'] = ['', None, None] self.details['npts_inter'] = ['', None, None] self.details['shell_num'] = ['', None, None] self.details['nu_inter'] = ['', None, None] self.details['sld_left'] = ['[1/A^(2)]', None, None] self.details['sld_right'] = ['[1/A^(2)]', None, None] ## fittable parameters self.fixed=[''] ## non-fittable parameters self.non_fittable = [] ## parameters with orientation self.orientation_params = [] def __reduce_ex__(self, proto): """ Overwrite the __reduce_ex__ of PyTypeObject *type call in the init of c model. """ return (create_SLDCalFunc,tuple()) def clone(self): """ Return a identical copy of self """ return self._clone(SLDCalFunc()) def run(self, x=0.0): """ Evaluate the model :param x: input q, or [q,phi] :return: scattering function P(q) """ return CSLDCalFunc.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 CSLDCalFunc.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 CSLDCalFunc.evalDistribution(self, x) def calculate_ER(self): """ Calculate the effective radius for P(q)*S(q) :return: the value of the effective radius """ return CSLDCalFunc.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 CSLDCalFunc.set_dispersion(self, parameter, dispersion.cdisp) # End of file