##############################################################################
# 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/raspberry.h
AND RE-RUN THE GENERATOR SCRIPT
"""
from sas.models.BaseComponent import BaseComponent
from sas.models.sas_extension.c_models import CRaspBerryModel
from numpy import inf
[docs]def create_RaspBerryModel():
"""
Create a model instance
"""
obj = RaspBerryModel()
# CRaspBerryModel.__init__(obj) is called by
# the RaspBerryModel constructor
return obj
[docs]class RaspBerryModel(CRaspBerryModel, BaseComponent):
"""
Class that evaluates a RaspBerryModel model.
This file was auto-generated from src/sas/models/include/raspberry.h.
Refer to that file and the structure it contains
for details of the model.
List of default parameters:
* volf_Lsph = 0.05
* radius_Lsph = 5000.0 [A]
* sld_Lsph = -4e-07 [1/A^(2)]
* volf_Ssph = 0.005
* radius_Ssph = 100.0 [A]
* surfrac_Ssph = 0.4
* sld_Ssph = 3.5e-06 [1/A^(2)]
* delta_Ssph = 0.0
* sld_solv = 6.3e-06 [1/A^(2)]
* background = 0.0 [1/cm]
"""
def __init__(self, multfactor=1):
""" Initialization """
self.__dict__ = {}
# Initialize BaseComponent first, then sphere
BaseComponent.__init__(self)
#apply(CRaspBerryModel.__init__, (self,))
CRaspBerryModel.__init__(self)
self.is_multifunc = False
## Name of the model
self.name = "RaspBerryModel"
## Model description
self.description = """
RaspBerryModel:
volf_Lsph = volume fraction large spheres
radius_Lsph = radius large sphere (A)
sld_Lsph = sld large sphere (A-2)
volf_Ssph = volume fraction small spheres
radius_Ssph = radius small sphere (A)
surfrac_Ssph = fraction of small spheres at surface
sld_Ssph = sld small sphere
delta_Ssph = small sphere penetration (A)
sld_solv = sld solvent
background = background (cm-1)
Ref: J. coll. inter. sci. (2010) vol. 343 (1) pp. 36-41.
"""
## Parameter details [units, min, max]
self.details = {}
self.details['volf_Lsph'] = ['', None, None]
self.details['radius_Lsph'] = ['[A]', None, None]
self.details['sld_Lsph'] = ['[1/A^(2)]', None, None]
self.details['volf_Ssph'] = ['', None, None]
self.details['radius_Ssph'] = ['[A]', None, None]
self.details['surfrac_Ssph'] = ['', None, None]
self.details['sld_Ssph'] = ['[1/A^(2)]', None, None]
self.details['delta_Ssph'] = ['', None, None]
self.details['sld_solv'] = ['[1/A^(2)]', None, None]
self.details['background'] = ['[1/cm]', None, None]
## fittable parameters
self.fixed = ['radius_Lsph.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_RaspBerryModel, tuple(), state, None, None)
[docs] def clone(self):
""" Return a identical copy of self """
return self._clone(RaspBerryModel())
[docs] def run(self, x=0.0):
"""
Evaluate the model
:param x: input q, or [q,phi]
:return: scattering function P(q)
"""
return CRaspBerryModel.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 CRaspBerryModel.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 CRaspBerryModel.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 CRaspBerryModel.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 CRaspBerryModel.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 CRaspBerryModel.set_dispersion(self,
parameter, dispersion.cdisp)
# End of file