def calculate_rms_means(means, corrected_means):
    """Calculates RMS of means from zero before and after correction

    Parameters
    ----------
    means: numpy array of means of gaussians of all PMT combinations
    corrected_means: numpy array of corrected gaussian means for all PMT combs

    Returns
    -------
    rms_means: RMS of means from zero
    rms_corrected_means: RMS of corrected_means from zero
    """
    rms_means = np.sqrt(np.mean((means - 0)**2))
    rms_corrected_means = np.sqrt(np.mean((corrected_means - 0)**2))
    return rms_means, rms_corrected_means
def calculate_rms_means ( means , corrected_means ) : rms_means = np . sqrt ( np . mean ( ( means - 0 ) ** 2 ) ) rms_corrected_means = np . sqrt ( np . mean ( ( corrected_means - 0 ) ** 2 ) ) return rms_means , rms_corrected_means
Calculates RMS of means from zero before and after correction

    Parameters
    ----------
    means: numpy array of means of gaussians of all PMT combinations
    corrected_means: numpy array of corrected gaussian means for all PMT combs

    Returns
    -------
    rms_means: RMS of means from zero
    rms_corrected_means: RMS of corrected_means from zero