pyembedding.py 文件源码

def correlation_valid(x, y):
    invalid = numpy.logical_or(numpy.isnan(x), numpy.isnan(y))
    valid = numpy.logical_not(invalid)
    valid_count = valid.sum()

    if valid_count == 0:
        corr = float('nan')
        sd_x = float('nan')
        sd_y = float('nan')
    else:
        sd_x = numpy.std(x[valid])
        sd_y = numpy.std(y[valid])

        if sd_x == 0 and sd_y == 0:
            corr = 1.0
        elif sd_x == 0 or sd_y == 0:
            corr = 0.0
        else:
            corr = numpy.corrcoef(x[valid], y[valid])[0,1]

    return corr, valid_count, sd_x, sd_y