Source code for sas.models.TeubnerStreyModel

##############################################################################
# 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/teubner_strey.h
   AND RE-RUN THE GENERATOR SCRIPT
"""

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

def create_TeubnerStreyModel():
    """
    Create a model instance
    """
    obj = TeubnerStreyModel()
    # CTeubnerStreyModel.__init__(obj) is called by
    # the TeubnerStreyModel constructor
    return obj

class TeubnerStreyModel(CTeubnerStreyModel, BaseComponent):
    """
    Class that evaluates a TeubnerStreyModel model.
    This file was auto-generated from src/sas/models/include/teubner_strey.h.
    Refer to that file and the structure it contains
    for details of the model.
    
    List of default parameters:

    * scale           = 0.1 
    * c1              = -30.0 
    * c2              = 5000.0 
    * background      = 0.0 

    """

    def __init__(self, multfactor=1):
        """ Initialization """
        self.__dict__ = {}

        # Initialize BaseComponent first, then sphere
        BaseComponent.__init__(self)
        #apply(CTeubnerStreyModel.__init__, (self,)) 

        CTeubnerStreyModel.__init__(self)
        self.is_multifunc = False

        ## Name of the model
        self.name = "TeubnerStreyModel"
        ## Model description
        self.description = """
        F(x) = 1/( scale + c1*(x)^(2)+  c2*(x)^(4)) + bkd 
        """

        ## Parameter details [units, min, max]
        self.details = {}
        self.details['scale'] = ['', None, None]
        self.details['c1'] = ['', None, None]
        self.details['c2'] = ['', None, None]
        self.details['background'] = ['', 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_TeubnerStreyModel, tuple(), state, None, None)

    def clone(self):
        """ Return a identical copy of self """
        return self._clone(TeubnerStreyModel())

    def run(self, x=0.0):
        """
        Evaluate the model

        :param x: input q, or [q,phi]
        :return: scattering function P(q)
        """
        return CTeubnerStreyModel.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 CTeubnerStreyModel.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 CTeubnerStreyModel.evalDistribution(self, x)

    def calculate_ER(self):
        """
        Calculate the effective radius for P(q)*S(q)

        :return: the value of the effective radius
        """
        return CTeubnerStreyModel.calculate_ER(self)

    def calculate_VR(self):
        """
        Calculate the volf ratio for P(q)*S(q)

        :return: the value of the volf ratio
        """
        return CTeubnerStreyModel.calculate_VR(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 CTeubnerStreyModel.set_dispersion(self,
               parameter, dispersion.cdisp)

# End of file