##############################################################################
# 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/binaryHS.h
AND RE-RUN THE GENERATOR SCRIPT
"""
from sas.models.BaseComponent import BaseComponent
from sas.models.sas_extension.c_models import CBinaryHSModel
[docs]def create_BinaryHSModel():
"""
Create a model instance
"""
obj = BinaryHSModel()
# CBinaryHSModel.__init__(obj) is called by
# the BinaryHSModel constructor
return obj
[docs]class BinaryHSModel(CBinaryHSModel, BaseComponent):
"""
Class that evaluates a BinaryHSModel model.
This file was auto-generated from src/sas/models/include/binaryHS.h.
Refer to that file and the structure it contains
for details of the model.
List of default parameters:
* l_radius = 100.0 [A]
* s_radius = 25.0 [A]
* vol_frac_ls = 0.1
* vol_frac_ss = 0.2
* ls_sld = 3.5e-06 [1/A^(2)]
* ss_sld = 5e-07 [1/A^(2)]
* solvent_sld = 6.36e-06 [1/A^(2)]
* background = 0.001 [1/cm]
"""
def __init__(self, multfactor=1):
""" Initialization """
self.__dict__ = {}
# Initialize BaseComponent first, then sphere
BaseComponent.__init__(self)
#apply(CBinaryHSModel.__init__, (self,))
CBinaryHSModel.__init__(self)
self.is_multifunc = False
## Name of the model
self.name = "BinaryHSModel"
## Model description
self.description = """
Model parameters: l_radius : large radius of binary hard sphere
s_radius : small radius of binary hard sphere
vol_frac_ls : volume fraction of large spheres
vol_frac_ss : volume fraction of small spheres
ls_sld: large sphere scattering length density
ss_sld: small sphere scattering length density
solvent_sld: solvent scattering length density
background: incoherent background
"""
## Parameter details [units, min, max]
self.details = {}
self.details['l_radius'] = ['[A]', None, None]
self.details['s_radius'] = ['[A]', None, None]
self.details['vol_frac_ls'] = ['', None, None]
self.details['vol_frac_ss'] = ['', None, None]
self.details['ls_sld'] = ['[1/A^(2)]', None, None]
self.details['ss_sld'] = ['[1/A^(2)]', None, None]
self.details['solvent_sld'] = ['[1/A^(2)]', None, None]
self.details['background'] = ['[1/cm]', None, None]
## fittable parameters
self.fixed = ['l_radius.width',
's_radius.width']
## 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_BinaryHSModel, tuple(), state, None, None)
[docs] def clone(self):
""" Return a identical copy of self """
return self._clone(BinaryHSModel())
[docs] def run(self, x=0.0):
"""
Evaluate the model
:param x: input q, or [q,phi]
:return: scattering function P(q)
"""
return CBinaryHSModel.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 CBinaryHSModel.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 CBinaryHSModel.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 CBinaryHSModel.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 CBinaryHSModel.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 CBinaryHSModel.set_dispersion(self,
parameter, dispersion.cdisp)
# End of file