dry.py 文件源码

def distance_function(values, medians):
    """This function calculates the distance metric.
    N.B. Only uses the non-NaN values.

    dist = sum( (s - m)^2 )

    s is the vector of sample values
    m is the vector of probe medians

    Args:
        values (numpy array of floats)
        medians (numpy array of floats)
    Returns:
        dist (float)
    """
    non_nan_idx = ~np.isnan(values)
    assert np.size(non_nan_idx) != 0, "All values in this sample are NaN!"

    non_nan_values = values[non_nan_idx]
    non_nan_medians = medians[non_nan_idx]
    dist = sum(np.square(non_nan_values - non_nan_medians))
    return dist

# tested #