添加时NumPy中的cumsum函数会衰减吗? [英] Can the cumsum function in NumPy decay while adding?

问题描述

我有一个值数组 a =(2,3,0,0,4,3)

y=0
for x in a:
  y = (y+x)*.95

有什么方法可以在 numpy 中使用 cumsum 并在添加下一个值之前对每行应用.95衰减?

Is there any way to use cumsum in numpy and apply the .95 decay to each row before adding the next value?

推荐答案

您要的是简单的 IIR过滤器.为此，Scipy的 lfilter()的用途是:

You're asking for a simple IIR Filter. Scipy's lfilter() is made for that:

import numpy as np
from scipy.signal import lfilter

data = np.array([2, 3, 0, 0, 4, 3], dtype=float)  # lfilter wants floats

# Conventional approach:
result_conv = []
last_value = 0
for elmt in data:
    last_value = (last_value + elmt)*.95
    result_conv.append(last_value)

# IIR Filter:
result_IIR = lfilter([.95], [1, -.95], data)

if np.allclose(result_IIR, result_conv, 1e-12):
    print("Values are equal.")

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