def gaussian_variogram_model ( m , d ) : psill = float ( m [ 0 ] ) range_ = float ( m [ 1 ] ) nugget = float ( m [ 2 ] ) return psill * ( 1. - np . exp ( - d ** 2. / ( range_ * 4. / 7. ) ** 2. ) ) + nugget
how do you determine the probability from a gaussian model in python
Gaussian model m is [ psill range nugget ]
def gaussian_variogram_model(m, d):
    """Gaussian model, m is [psill, range, nugget]"""
    psill = float(m[0])
    range_ = float(m[1])
    nugget = float(m[2])
    return psill * (1. - np.exp(-d**2./(range_*4./7.)**2.)) + nugget