#!/usr/bin/env python
""" 
    
    Provide F(x)= P(x)*S(x) + bkd
    Fractal as a BaseComponent model
"""

from sans.models.BaseComponent import BaseComponent
import math
from scipy.special import gamma

class FractalModel(BaseComponent):
   
    """
        Class that evaluates a Fractal function.
        
        F(x)= P(x)*S(x) + bkd
        The model has Seven parameters: 
            scale        =  Volume fraction
            radius       =  Block radius
            fractal_dim  =  Fractal dimension
            corr_length  =  correlation Length
            block_sld    =  SDL block
            solvent_sld  =  SDL solvent
            background   =  background
           
    """
        
    def __init__(self):
        """ Initialization """
        
        # Initialize BaseComponent first, then sphere
        BaseComponent.__init__(self)
        
        ## Name of the model
        self.name = "Number Density Fractal"

        ## Define parameters
        self.params = {}
        self.params['scale']       = 0.05
        self.params['radius']      = 5.0
        self.params['fractal_dim'] = 2.0
        self.params['corr_length'] = 100.0
        self.params['block_sld']   = 2.0e-6
        self.params['solvent_sld'] = 6.0e-6
        self.params['background']  = 0.0
        

        ## Parameter details [units, min, max]
        self.details = {}
        self.details['scale']       = ['', None, None]
        self.details['radius']      = ['A', None, None]
        self.details['fractal_dim'] = ['', None, None]
        self.details['corr_length'] = ['A', None, None]
        self.details['block_sld']   = ['A-2', None, None]
        self.details['solvent_sld'] = ['A-2', None, None]
        self.details['background']  = ['cm-1', None, None]
       
               
    def _Fractal(self, x):
        """
            Evaluate  
            F(x) = p(x) * s(x) + bkd  
        """
        return self.params['background']+ self._scatterRanDom(x)* self._Block(x)
    
    def _Block(self,x):
        
        
        
        return 1.0 + (math.sin((self.params['fractal_dim']-1.0) * math.atan(x * self.params['corr_length']))\
             * self.params['fractal_dim'] * gamma(self.params['fractal_dim']-1.0))\
           /( math.pow( (x*self.params['radius']), self.params['fractal_dim'])*\
           math.pow( 1.0 + 1.0/((x**2)*(self.params['corr_length']**2)),(self.params['fractal_dim']-1.0)/2.0))   
           
    def _Spherical(self,x):
        """
            F(x) = 3*[sin(x)-xcos(x)]/x**3
        """
        return 3.0*(math.sin(x)-x*math.cos(x))/(math.pow(x,3.0))
        
    def _scatterRanDom(self,x):
        """
             calculate p(x)= scale* V^(2)*delta^(2)* F(x*Radius)^(2)
        """
        V =(4.0/3.0)*math.pi* math.pow(self.params['radius'],3.0) 
        delta = self.params['block_sld']-self.params['solvent_sld']
        
        return 1.0e8*self.params['scale']* V *(delta**2)*\
                (self._Spherical(x*self.params['radius'])**2)
        
    def run(self, x = 0.0):
        """ Evaluate the model
            @param x: input q-value (float or [float, float] as [r, theta])
            @return: (Fractal value)
        """
        if x.__class__.__name__ == 'list':
            return self._Fractal(x[0]*math.cos(x[1]))*self._Fractal(x[0]*math.sin(x[1]))
        elif x.__class__.__name__ == 'tuple':
            raise ValueError, "Tuples are not allowed as input to BaseComponent models"
        else:
            return self._Fractal(x)
   
    def runXY(self, x = 0.0):
        """ Evaluate the model
            @param x: input q-value (float or [float, float] as [qx, qy])
            @return: Fractal value
        """
        if x.__class__.__name__ == 'list':
            return self._Fractal(x[0])*self._Fractal(x[1])
        elif x.__class__.__name__ == 'tuple':
            raise ValueError, "Tuples are not allowed as input to BaseComponent models"
        else:
            return self._Fractal(x)