

def get_mean_masked_features_distance(mean_features_0, mean_features_1, mean_masks_0, mean_masks_1, n_features_per_channel=None):
    'Compute the distance between the mean masked features.'
    assert (n_features_per_channel > 0)
    mu_0 = mean_features_0.ravel()
    mu_1 = mean_features_1.ravel()
    omeg_0 = mean_masks_0
    omeg_1 = n_features_per_channel
    omeg_0 = np.repeat(omeg_0, n_features_per_channel)
    omeg_1 = np.repeat(omeg_1, n_features_per_channel)
    d_0 = (mu_0 * omeg_0)
    d_1 = (mu_1 * omeg_1)
    return np.linalg.norm((d_0 - d_1))

dataset/ETHPy150Open kwikteam/phy/phy/stats/clusters.py get_mean_masked_features_distance/VarMisuse@51/126 `mean_masks_1`->`n_features_per_channel`