source: sasview/sansmodels/src/sans/models/LamellarPSModel.py @ 277aab4e

#!/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\lamellarPS.h
                 AND RE-RUN THE GENERATOR SCRIPT

"""

from sans.models.BaseComponent import BaseComponent
from sans_extension.c_models import CLamellarPSModel
import copy    
    
class LamellarPSModel(CLamellarPSModel, BaseComponent):
    """ Class that evaluates a LamellarPSModel model. 
        This file was auto-generated from ..\c_extensions\lamellarPS.h.
        Refer to that file and the structure it contains
        for details of the model.
        List of default parameters:
         scale           = 1.0 
         spacing         = 400.0 [A]
         delta           = 30.0 [A]
         contrast        = 5.3e-006 [1/A^(2)]
         n_plates        = 20.0 
         caille          = 0.1 
         background      = 0.0 [1/cm]

    """
        
    def __init__(self):
        """ Initialization """
        
        # Initialize BaseComponent first, then sphere
        BaseComponent.__init__(self)
        CLamellarPSModel.__init__(self)
        
        ## Name of the model
        self.name = "LamellarPSModel"
        ## Model description
        self.description ="""[Concentrated Lamellar Form Factor] Calculates the scattered
                intensity from a lyotropic lamellar phase.
                The intensity (form factor and structure
                factor)calculated is for lamellae of
                uniform scattering length density that
                are randomly distributed in solution
                (a powder average). The lamellae thickness
                is polydisperse. The model can also
                be applied to large, multi-lamellar vesicles.
                No resolution smeared version is included
                in the structure factor of this model.
                *Parameters: spacing = repeat spacing,
                delta = bilayer thickness,
                contrast = SLD_solvent - SLD_bilayer
                n_plate = # of Lamellar plates
                caille = Caille parameter (<0.8 or <1)
                background = incoherent bgd
                scale = scale factor"""
       
        ## Parameter details [units, min, max]
        self.details = {}
        self.details['scale'] = ['', None, None]
        self.details['spacing'] = ['[A]', None, None]
        self.details['delta'] = ['[A]', None, None]
        self.details['contrast'] = ['[1/A^(2)]', None, None]
        self.details['n_plates'] = ['', None, None]
        self.details['caille'] = ['', None, None]
        self.details['background'] = ['[1/cm]', None, None]

        ## fittable parameters
        self.fixed=['delta.width', 'spacing.width']
        
        ## parameters with orientation
        self.orientation_params =[]
   
    def clone(self):
        """ Return a identical copy of self """
        return self._clone(LamellarPSModel())   
        
    def __getstate__(self):
        """ return object state for pickling and copying """
        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 CLamellarPSModel.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 CLamellarPSModel.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 CLamellarPSModel.evalDistribition(self, x)
        
    def calculate_ER(self):
        """ Calculate the effective radius for P(q)*S(q)
            @return: the value of the effective radius
        """       
        return CLamellarPSModel.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 CLamellarPSModel.set_dispersion(self, parameter, dispersion.cdisp)
        
   
# End of file