def l2_norm( self, degree ):
if numpy.isscalar( degree ):
degree = numpy.array( [degree] )
else:
degree = numpy.array( degree )
norm = numpy.empty( degree.shape[0] )
for i in xrange( degree.shape[0] ):
d = degree[i]
if ( d == 0 ): norm[i] = 1.;
else:
beta_func = \
gamma( self.alpha_poly+1 ) * gamma( self.beta_poly+1 ) \
/ gamma( self.alpha_poly + self.beta_poly + 2 );
norm[i] = gamma( d + self.alpha_poly + 1.0 ) * gamma( d + self.beta_poly + 1.0 ) / ( ( 2.0 * d + self.alpha_poly + self.beta_poly + 1.0 ) * gamma( d + self.alpha_poly + self.beta_poly + 1.0 ) * factorial( d ) * beta_func )
return norm
def l2_norm( self, degree ):
return factorial( degree )
