在numpy数组上使用numpy.rate意外返回nan [英] Using numpy.rate, on numpy array returns nan's unexpectedly

问题描述

我正在使用np.rate函数来计算简单的增长率.我正在尝试使用向量运算.这有效:

I'm using np.rate function to calculate simple growth rates. I'm trying to use vector operations. This works:

b = np.arange(1,10)
np.rate(1,0,-b[:-1],b[1:])

这将返回:
array([1.，0.5，0.33333333，0.25，0.2，0.16666667，0.14285714，0.125])

This returns:
array([ 1. , 0.5 , 0.33333333, 0.25 , 0.2 , 0.16666667, 0.14285714, 0.125 ])

但是，这不符合我的预期:

However, this doesn't work as I'm expecting:

b = np.arange(10)
np.rate(1,0,-b[:-1],b[1:])

返回:
数组([nan，nan，nan，nan，nan，nan，nan，nan，nan])

Returns:
array([ nan, nan, nan, nan, nan, nan, nan, nan, nan])

有什么想法可以最好地解决这个问题?我假设第一个索引位置的0给np.rate函数带来了一些问题，但是我不确定纠正此问题的最佳方法是什么.感谢您的帮助.

Any thoughts to best remedy this? I'm assuming the 0 in the first index position is giving the np.rate function some problems but I'm not sure what the best way to correct this is. Your help is appreciated.

推荐答案

第二种情况在 b 中为零.

np.rate不能在那里处理0值.

np.rate can't handle a 0 value there.

正如我从np.rate的简要说明中了解到的那样，您正在要求它找到在单个支付期内将0变成1所需的利率.这是您要解决的具有挑战性的问题.

As well as I can understand from the (brief) documentation of np.rate, you're asking it to find what interest rate is needed to turn 0 into 1 in a single pay period. This is a challenging problem you're asking it to solve.

要解决此问题，您只需要在此处不设置0.

To fix it, you simply need to not have a 0 there.

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