#!/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\lamellar.h AND RE-RUN THE GENERATOR SCRIPT """ from sans.models.BaseComponent import BaseComponent from sans_extension.c_models import CLamellarModel import copy class LamellarModel(CLamellarModel, BaseComponent): """ Class that evaluates a LamellarModel model. This file was auto-generated from ..\c_extensions\lamellar.h. Refer to that file and the structure it contains for details of the model. List of default parameters: scale = 1.0 bi_thick = 50.0 [A] sld_bi = 1e-006 [1/A^(2)] sld_sol = 6.3e-006 [1/A^(2)] background = 0.0 [1/cm] """ def __init__(self): """ Initialization """ # Initialize BaseComponent first, then sphere BaseComponent.__init__(self) CLamellarModel.__init__(self) ## Name of the model self.name = "LamellarModel" ## Model description self.description ="""[Dilute Lamellar Form Factor](from a lyotropic lamellar phase) I(q)= 2*pi*P(q)/(delta *q^(2)), where P(q)=2*(contrast/q)^(2)*(1-cos(q*delta))^(2)) bi_thick = bilayer thickness sld_bi = SLD of bilayer sld_sol = SLD of solvent background = Incoherent background scale = scale factor """ ## Parameter details [units, min, max] self.details = {} self.details['scale'] = ['', None, None] self.details['bi_thick'] = ['[A]', None, None] self.details['sld_bi'] = ['[1/A^(2)]', None, None] self.details['sld_sol'] = ['[1/A^(2)]', None, None] self.details['background'] = ['[1/cm]', None, None] ## fittable parameters self.fixed=[] ## parameters with orientation self.orientation_params =[] def clone(self): """ Return a identical copy of self """ return self._clone(LamellarModel()) def __getstate__(self): """ return object state for pickling and copying """ print "__dict__",self.__dict__ #self.__dict__['params'] = self.params #self.__dict__['dispersion'] = self.dispersion #self.__dict__['log'] = self.log 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 """ 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 CLamellarModel.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 CLamellarModel.runXY(self, x) def evalDistribition(self, x = []): """ Evaluate the model in cartesian coordinates @param x: input q[], or [qx[], qy[]] @return: scattering function P(q[]) """ return CLamellarModel.evalDistribition(self, x) def calculate_ER(self): """ Calculate the effective radius for P(q)*S(q) @return: the value of the effective radius """ return CLamellarModel.calculate_ER(self) def set_dispersion(self, parameter, dispersion): """ Set the dispersion object for a model parameter @param parameter: name of the parameter [string] @dispersion: dispersion object of type DispersionModel """ return CLamellarModel.set_dispersion(self, parameter, dispersion.cdisp) # End of file