cdt/causality/pairwise/Jarfo_model/features.py
def weighted_mean_and_std(values, weights):
    """
    Returns the weighted average and standard deviation.

    values, weights -- numpy ndarrays with the same shape.
    """
    average = np.average(values, weights=weights, axis=0)
    variance = np.dot(weights, (values - average) ** 2) / weights.sum()  # Fast and numerically precise
    return (average, np.sqrt(variance))
def weighted_mean_and_std(values, weights):
    """
    Returns the weighted average and standard deviation.

    values, weights -- numpy ndarrays with the same shape.
    """
    average = np.average(values, weights=weights, axis=0)
    variance = np.dot(weights, (values - average) ** 2) / weights.sum()  # Fast and numerically precise
    return (average, np.sqrt(variance))
def weighted_mean_and_std ( values , weights ) : average = np . average ( values , weights = weights , axis = 0 ) variance = np . dot ( weights , ( values - average ) ** 2 ) / weights . sum ( ) # Fast and numerically precise return ( average , np . sqrt ( variance ) )
Returns the weighted average and standard deviation.

    values, weights -- numpy ndarrays with the same shape.
Returns the weighted average and standard deviation .