我正在尝试构建一个指数移动平均算法,其输出与Pandas的
下图是一个示例:
下面的代码在移动平均窗口开始移动超出初始数据集时能够正确工作,但此时我与Pandas计算结果不同。
我已经看了几个小时了,但还没有头绪。有人可以指出我如何错误地实现了上述公式吗?
ewm()
函数相同。特别地,我正尝试实现以下方法:下图是一个示例:
![enter image description here](https://istack.dev59.com/ipfkX.webp)
我已经看了几个小时了,但还没有头绪。有人可以指出我如何错误地实现了上述公式吗?
import numpy as np
import pandas as pd
class MovingAverages(object):
def __init__(self, **kwargs):
self.measures = []
self.lookback_period = 5
ema_multiplier = 2 / (self.lookback_period + 1)
self.lookback_alphas = []
for i in range(1,self.lookback_period+1):
self.lookback_alphas.append((1 - ema_multiplier ) ** i)
def insert_bar(self):
self.measures.insert(0, 0)
def on_calculate(self, c):
index = min(len(c), self.lookback_period+1)
y = c[0]
for i in range(1,index):
y += self.lookback_alphas[i-1] * c[i]
y /= 1 + sum(self.lookback_alphas[0:index-1])
self.measures[0] = y
if __name__ == "__main__":
data = [5.00,7.00,4.00,3.00,4.00,
5.00,6.00,7.00,9.00,13.00,
15.00,14.00,14.00,12.00,
11.00,10.00,9.00,8.00,
8.00,8.00,10.00,11.00,
13.00,16.00,18.00,20.00]
# Manually calculate exponential MA and write into list
ma_online = MovingAverages()
series = []
for d in data:
series.insert(0, d)
ma_online.insert_bar()
ma_online.on_calculate(series)
# Calculate a reference exponential MA using Pandas
df = pd.DataFrame({'close': data})
ma_pd = list(df.close.ewm(span=ma_online.lookback_period, adjust=True, ignore_na=True).mean())
# Compare the two lists
ma_online.measures.reverse()
for i in range(len(data)):
assert round(ma_pd[i], 2) == round(ma_online.measures[i], 2)