numpy:从数组中获取索引位于另一个数组中的值

问题描述：

我有一个mx1数组a，其中包含一些值.而且，我有一个nxk数组，比如b，其中包含0到m之间的索引.

I have a mx1 array, a, that contains some values. Moreover, I have a nxk array, say b, that contains indices between 0 and m.

示例:

a = np.array((0.1, 0.2, 0.3))
b = np.random.randint(0, 3, (4, 4))

对于b中的每个索引值，我想从a中获得相应的值. 我可以通过循环来做到这一点:

For every index value in b I want to get the corresponding value from a. I can do it with a loop:

c = np.zeros_like(b).astype('float')
n, k = b.shape
for i in range(n):
    for j in range(k):
        c[i, j] = a[b[i, j]]

是否有任何更优雅的内置numpy函数或技巧?这种方法对我来说有点愚蠢. PS:如果有帮助，最初，a和b是Pandas对象.

Is there any built-it numpy function or trick that is more elegant? This approach looks a little dumb to me. PS: originally, a and b are Pandas objects if that helps.

答

>>> a
array([ 0.1,  0.2,  0.3])
>>> b
array([[0, 0, 1, 1],
       [0, 0, 1, 1],
       [0, 1, 1, 0],
       [0, 1, 0, 1]])
>>> a[b]
array([[ 0.1,  0.1,  0.2,  0.2],
       [ 0.1,  0.1,  0.2,  0.2],
       [ 0.1,  0.2,  0.2,  0.1],
       [ 0.1,  0.2,  0.1,  0.2]])

多田！只是a[b]. (此外，您可能希望randint调用的上限为3.)

Tada! It's just a[b]. (Also, you probably wanted the upper bound on the randint call to be 3.)

numpy:从数组中获取索引位于另一个数组中的值

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