[python] 실행 표준 편차를 효율적으로 계산하는 방법은 무엇입니까?

다음은 http://www.johndcook.com/standard_deviation.html 에서 Welford 알고리즘 구현의 문자 그대로 순수한 Python 번역입니다 . .

https://github.com/liyanage/python-modules/blob/master/running_stats.py

import math

class RunningStats:

    def __init__(self):
        self.n = 0
        self.old_m = 0
        self.new_m = 0
        self.old_s = 0
        self.new_s = 0

    def clear(self):
        self.n = 0

    def push(self, x):
        self.n += 1

        if self.n == 1:
            self.old_m = self.new_m = x
            self.old_s = 0
        else:
            self.new_m = self.old_m + (x - self.old_m) / self.n
            self.new_s = self.old_s + (x - self.old_m) * (x - self.new_m)

            self.old_m = self.new_m
            self.old_s = self.new_s

    def mean(self):
        return self.new_m if self.n else 0.0

    def variance(self):
        return self.new_s / (self.n - 1) if self.n > 1 else 0.0

    def standard_deviation(self):
        return math.sqrt(self.variance())

용법:

rs = RunningStats()
rs.push(17.0)
rs.push(19.0)
rs.push(24.0)

mean = rs.mean()
variance = rs.variance()
stdev = rs.standard_deviation()

print(f'Mean: {mean}, Variance: {variance}, Std. Dev.: {stdev}')