def clscale (cl):
    """Say we take a Gaussian bivariate and convert the parameters of the
    distribution to an ellipse (major, minor, PA). By what factor should we
    scale those axes to make the area of the ellipse correspond to the
    confidence interval CL? (I.e. 0 < CL < 1)

    """
    rv = np.sqrt (-2 * np.log (1 - cl))
    rv[np.where (cl <= 0)] = np.nan
    return rv
def clscale ( cl ) : rv = np . sqrt ( - 2 * np . log ( 1 - cl ) ) rv [ np . where ( cl <= 0 ) ] = np . nan return rv
Say we take a Gaussian bivariate and convert the parameters of the
    distribution to an ellipse (major, minor, PA). By what factor should we
    scale those axes to make the area of the ellipse correspond to the
    confidence interval CL? (I.e. 0 < CL < 1)