Python sum() 正在为两个不同的列表计算相同的值

Question

我正在尝试使用 RSI 进行技术分析，其中包含 2 个收益和损失列表，然后获取 2 个列表的平均值。出于某种原因，当使用 sum() 时，我收到了 2 个列表的相同值。当手动添加列表的总和时，我看到了不同的结果。这就是我所拥有的：

def calculate_avg_gain(in_list : list) -> tuple:
gain_list = []
loss_list = []
for i, close in enumerate(in_list):
    try:
        change = close - in_list[i-1]
    except IndexError:
        change = 0.0
    if change >= 0.0:
        gain_list.append(change)
        loss_list.append(0.0)
    else:
        gain_list.append(0.0)
        loss_list.append(abs(change))
avg_gain = sum(gain_list) / 14
avg_loss = sum(loss_list) / 14
return avg_gain, avg_loss

当每个条目有 14 个条目时，我就进入了代码：

gain_list = [1.1800000000000068, 0.0, 0.0, 0.10000000000002274, 0.0, 0.44999999999998863, 0.030000000000001137, 0.0, 0.160000000000025, 0.0, 0.0, 0.15000000000000568, 0.0, 0.05000000000001137]
loss_list = [0.0, 0.19999999999998863, 0.10999999999998522, 0.0, 0.0, 0.0, 0.5, 0.3299999999999841, 0.0, 0.47999999999998977, 0.0, 0.10000000000002274, 0.25, 0.0]

avg_gain = 0.15142857142857583
avg_loss = 0.1407142857142836

两者的总和为 2.12，这是我得到 loss_list 总和的结果，而我得到 2.1799 的 gain_list。我错过了什么吗？

Answer 1

如果您发现这里的问题是，无论何时执行in_list[-1]，它都不会抛出IndexError，但它会使用最后一个元素in_list[len(list)-1]

In [4]: def calculate_avg_gain(in_list : list) -> tuple:
   ...:     gain_list = []
   ...:     loss_list = []
   ...:     for i, close in enumerate(in_list):
   ...:         try:
   ...:             change = close - in_list[i-1]
   ...:         except IndexError:
   ...:             change = 0.0
   ...:         if change >= 0.0:
   ...:             gain_list.append(change)
   ...:             loss_list.append(0.0)
   ...:         else:
   ...:             gain_list.append(0.0)
   ...:             loss_list.append(abs(change))
   ...:         print(gain_list, loss_list, change)
   ...:     avg_gain = sum(gain_list) / 14
   ...:     avg_loss = sum(loss_list) / 14
   ...:     return avg_gain, avg_loss
   ...:

In [5]: calculate_avg_gain(a)
[0.0] [4] -4
[0.0, 1] [4, 0.0] 1
[0.0, 1, 1] [4, 0.0, 0.0] 1
[0.0, 1, 1, 1] [4, 0.0, 0.0, 0.0] 1
[0.0, 1, 1, 1, 1] [4, 0.0, 0.0, 0.0, 0.0] 1
Out[5]: (0.2857142857142857, 0.2857142857142857)

您可以将代码更新为以下内容：

In [6]: def calculate_avg_gain(in_list : list) -> tuple:
   ...:     gain_list = []
   ...:     loss_list = []
   ...:     for i, close in enumerate(in_list):
   ...:         if i == 0:
   ...:             continue
   ...:         change = close - in_list[i-1]
   ...:         if change >= 0.0:
   ...:             gain_list.append(change)
   ...:             loss_list.append(0.0)
   ...:         else:
   ...:             gain_list.append(0.0)
   ...:             loss_list.append(abs(change))
   ...:         print(gain_list, loss_list, change)
   ...:     avg_gain = sum(gain_list) / 14
   ...:     avg_loss = sum(loss_list) / 14
   ...:     return avg_gain, avg_loss
   ...:

In [7]: calculate_avg_gain(a)
[1] [0.0] 1
[1, 1] [0.0, 0.0] 1
[1, 1, 1] [0.0, 0.0, 0.0] 1
[1, 1, 1, 1] [0.0, 0.0, 0.0, 0.0] 1
Out[7]: (0.2857142857142857, 0.0)

如果您想要单线进行更改，您可以执行以下操作

>>> [j-i for i, j in zip(t[:-1], t[1:])]
[2, 3]

如果变化> 0，则可以增加收益，如果不增加损失。

其他方式：

for i in range(1, len(in_list)):
    change = in_list[i] - in_list[i-1]

如果你已经在你的项目中使用NumPy，你可以这样做

import numpy as np
in_list = np.array([5, 4, 89, 12, 32, 45])
  
  
# Calculating difference list
diff_list = np.diff(in_list)