source: sasview/pr_inversion/invertor.py @ 34ae302

from sans.pr.core.pr_inversion import Cinvertor
import numpy

class Invertor(Cinvertor):
    
    ## Chisqr of the last computation
    chisqr = 0
    
    def __init__(self):
        Cinvertor.__init__(self)
        
    def __setattr__(self, name, value):
        """
            Set the value of an attribute.
            Access the parent class methods for
            x, y, err and d_max.
        """
        if   name=='x':
            if 0.0 in value:
                raise ValueError, "Invertor: one of your q-values is zero. Delete that entry before proceeding"
            return self.set_x(value)
        elif name=='y':
            return self.set_y(value)
        elif name=='err':
            return self.set_err(value)
        elif name=='d_max':
            return self.set_dmax(value)
        elif name=='alpha':
            return self.set_alpha(value)
            
        return Cinvertor.__setattr__(self, name, value)
    
    def __getattr__(self, name):
        """
           Return the value of an attribute
           For the moment x, y, err and d_max are write-only
           TODO: change that!
        """
        import numpy
        if   name=='x':
            out = numpy.ones(self.get_nx())
            self.get_x(out)
            return out
        elif name=='y':
            out = numpy.ones(self.get_ny())
            self.get_y(out)
            return out
        elif name=='err':
            out = numpy.ones(self.get_nerr())
            self.get_err(out)
            return out
        elif name=='d_max':
            return self.get_dmax()
        elif name=='alpha':
            return self.get_alpha()
        elif name in self.__dict__:
            return self.__dict__[name]
        return None
    
    def invert(self, nfunc=5):
        """
            Perform inversion to P(r)
        """
        from scipy import optimize
        
        # First, check that the current data is valid
        if self.is_valid()<=0:
            raise RuntimeError, "Invertor.invert: Data array are of different length"
        
        p = numpy.ones(nfunc)
        out, cov_x, info, mesg, success = optimize.leastsq(self.residuals, p, full_output=1, warning=True)
        
        # Compute chi^2
        res = self.residuals(out)
        chisqr = 0
        for i in range(len(res)):
            chisqr += res[i]
        
        self.chi2 = chisqr
        
        return out, cov_x
    
    def pr_fit(self, nfunc=5):
        """
            Perform inversion to P(r)
        """
        from scipy import optimize
        
        # First, check that the current data is valid
        if self.is_valid()<=0:
            raise RuntimeError, "Invertor.invert: Data arrays are of different length"
        
        p = numpy.ones(nfunc)
        out, cov_x, info, mesg, success = optimize.leastsq(self.pr_residuals, p, full_output=1, warning=True)
        
        # Compute chi^2
        res = self.pr_residuals(out)
        chisqr = 0
        for i in range(len(res)):
            chisqr += res[i]
        
        self.chisqr = chisqr
        
        return out, cov_x
    
    def pr_err(self, c, c_cov, r):
        import math
        c_err = numpy.zeros(len(c))
        for i in range(len(c)):
            try:
                c_err[i] = math.sqrt(math.fabs(c_cov[i][i]))
            except:
                import sys
                print sys.exc_value
                print "oups", c_cov[i][i]
                c_err[i] = c[i]

        return self.get_pr_err(c, c_err, r)
        
    
if __name__ == "__main__":
    o = Invertor()