def makeGauss(x, mean=0.0, sd=1.0, gain=1.0, base=0.0):
 simpleGauss = numpy.exp(((- numpy.power((mean - x), 2)) / (2 * (sd ** 2))))
 return (base + (gain * simpleGauss))

def makeGauss ( x , mean = 0.0 , sd = 1.0 , gain = 1.0 , base = 0.0 ) : simpleGauss = numpy . exp ( ( ( - numpy . power ( ( mean - x ) , 2 ) ) / ( 2 * ( sd ** 2 ) ) ) ) return ( base + ( gain * simpleGauss ) )
return the gaussian distribution for a given set of x-vals .