python - scipypercentileofscore 的加权版本

Question

我想将权重传递给scipy.stats.percentileofscore 。例如:

from scipy import stats
a = [1, 2, 3, 4]
val = 3
stats.percentileofscore(a, val)

返回 75，因为 a 中 75% 的值等于或低于 val 3。

我想添加权重，例如:

weights = [2, 2, 3, 3]
weightedpercentileofscore(a, val, weights)

应返回 70，因为 (2 + 2 + 3)/(2 + 2 + 3 + 3) = 7/10 的权重落在或低于 3。

这也适用于小数权重和大权重，因此仅扩展数组并不理想。

Weighted percentile using numpy相关，但计算百分位数(例如，要求第 10 个百分位数值)而不是值的特定百分位数。

Answer 1

这应该可以完成工作。

import numpy as np

def weighted_percentile_of_score(a, weights, score, kind='weak'):
    npa = np.array(a)
    npw = np.array(weights)

    if kind == 'rank':  # Equivalent to 'weak' since we have weights.
        kind = 'weak'

    if kind in ['strict', 'mean']:
        indx = npa < score
        strict = 100 * sum(npw[indx]) / sum(weights)
    if kind == 'strict':
        return strict

    if kind in ['weak', 'mean']:    
        indx = npa <= score
        weak = 100 * sum(npw[indx]) / sum(weights)
    if kind == 'weak':
        return weak

    if kind == 'mean':
        return (strict + weak) / 2


a = [1, 2, 3, 4]
weights = [2, 2, 3, 3]
print(weighted_percentile_of_score(a, weights, 3))  # 70.0 as desired.

实际上，您想要做的是查看分数的总体权重小于或等于您的阈值分数 - 除以权重总和和百分比。

以数组形式获取每个值对应的加权百分位数:

[weighted_percentile_of_score(a, weights, val) for val in a]
# [20.0, 40.0, 70.0, 100.0]