numpy.where()详细的分步说明/示例 [英] numpy.where() detailed, step-by-step explanation / examples

问题描述

尽管阅读这篇文章和有人可以提供有关1D和2D阵列的分步注释示例吗?

Can someone provide step-by-step commented examples with 1D and 2D arrays?

推荐答案

摆弄了一会儿之后，我发现了问题，并将它们发布在这里，希望对其他人有帮助.

After fiddling around for a while, I figured things out, and am posting them here hoping it will help others.

直观地，np.where就像问"告诉我该数组中的位置满足给定条件".

>>> a = np.arange(5,10)
>>> np.where(a < 8)       # tell me where in a, entries are < 8
(array([0, 1, 2]),)       # answer: entries indexed by 0, 1, 2

它也可以用于获取满足以下条件的数组中的条目:

It can also be used to get entries in array that satisfy the condition:

>>> a[np.where(a < 8)] 
array([5, 6, 7])          # selects from a entries 0, 1, 2

---

当a是2d数组时，np.where()返回行idx的数组和col idx的数组:

---

When a is a 2d array, np.where() returns an array of row idx's, and an array of col idx's:

>>> a = np.arange(4,10).reshape(2,3)
array([[4, 5, 6],
       [7, 8, 9]])
>>> np.where(a > 8)
(array(1), array(2))

与一维情况一样，我们可以使用np.where()在2d数组中获取满足以下条件的条目:

As in the 1d case, we can use np.where() to get entries in the 2d array that satisfy the condition:

>>> a[np.where(a > 8)] # selects from a entries 0, 1, 2

array([9])

array([9])

请注意，当a为1d时，np.where()仍返回行idx的数组和col idx的数组，但列的长度为1，因此后者为空数组.

Note, when a is 1d, np.where() still returns an array of row idx's and an array of col idx's, but columns are of length 1, so latter is empty array.

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