Source code for sas.models.DABModel

##############################################################################
# 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 2008-2011, University of Tennessee
##############################################################################

"""
Provide functionality for a C extension model

.. WARNING::
   THIS FILE WAS GENERATED BY WRAPPERGENERATOR.PY
   DO NOT MODIFY THIS FILE, MODIFY
   src/sas/models/include/dabmodel.h
   AND RE-RUN THE GENERATOR SCRIPT
"""

from sas.models.BaseComponent import BaseComponent
from sas.models.sas_extension.c_models import CDABModel
from numpy import inf

[docs]def create_DABModel(): """ Create a model instance """ obj = DABModel() # CDABModel.__init__(obj) is called by # the DABModel constructor return obj
[docs]class DABModel(CDABModel, BaseComponent): """ Class that evaluates a DABModel model. This file was auto-generated from src/sas/models/include/dabmodel.h. Refer to that file and the structure it contains for details of the model. List of default parameters: * length = 50.0 [A] * scale = 1.0 * background = 0.0 [1/cm] """ def __init__(self, multfactor=1): """ Initialization """ self.__dict__ = {} # Initialize BaseComponent first, then sphere BaseComponent.__init__(self) #apply(CDABModel.__init__, (self,)) CDABModel.__init__(self) self.is_multifunc = False ## Name of the model self.name = "DABModel" ## Model description self.description = """ DAB (Debye Anderson Brumberger) Model F(x) = scale * L^3/( 1 + (q*L)^2 )^2 + background L: the correlation length """ ## Parameter details [units, min, max] self.details = {} self.details['length'] = ['[A]', None, None] self.details['scale'] = ['', None, None] self.details['background'] = ['[1/cm]', None, None] ## fittable parameters self.fixed = [] ## non-fittable parameters self.non_fittable = [] ## parameters with orientation self.orientation_params = [] ## parameters with magnetism self.magnetic_params = [] self.category = None self.multiplicity_info = None def __setstate__(self, state): """ restore the state of a model from pickle """ self.__dict__, self.params, self.dispersion = state def __reduce_ex__(self, proto): """ Overwrite the __reduce_ex__ of PyTypeObject *type call in the init of c model. """ state = (self.__dict__, self.params, self.dispersion) return (create_DABModel, tuple(), state, None, None)
[docs] def clone(self): """ Return a identical copy of self """ return self._clone(DABModel())
[docs] def run(self, x=0.0): """ Evaluate the model :param x: input q, or [q,phi] :return: scattering function P(q) """ return CDABModel.run(self, x)
[docs] 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 CDABModel.runXY(self, x)
[docs] def evalDistribution(self, x): """ Evaluate the model in cartesian coordinates :param x: input q[], or [qx[], qy[]] :return: scattering function P(q[]) """ return CDABModel.evalDistribution(self, x)
[docs] def calculate_ER(self): """ Calculate the effective radius for P(q)*S(q) :return: the value of the effective radius """ return CDABModel.calculate_ER(self)
[docs] def calculate_VR(self): """ Calculate the volf ratio for P(q)*S(q) :return: the value of the volf ratio """ return CDABModel.calculate_VR(self)
[docs] 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 CDABModel.set_dispersion(self, parameter, dispersion.cdisp) # End of file