Numpy比较数组一次到多个标量 [英] Numpy compare array to multiple scalars at once

问题描述

假设我有一个数组

a = np.array([1,2,3])

，我想将其与某个标量进行比较；像

and I want to compare it to some scalar; this works fine like

a == 2 # [False, True, False]

有没有一种方法可以同时进行多个标量的比较?比较两个数组时的默认行为是进行逐元素比较，但我希望将一个数组的每个元素与整个另一个数组进行逐元素比较，如下所示:

Is there a way I can do such a comparison but with multiple scalars at once? The default behavior when comparing two arrays is to do an elementwise comparison, but instead I want each element of one array to be compared elementwise with the entire other array, like this:

scalars = np.array([1, 2])
some_function(a, scalars)
[[True, False, False],
 [False, True, False]]

很明显，我可以做到这一点，例如，使用for循环然后堆叠，但是有没有矢量化的方法来实现相同的结果?

Obviously I can do this, e.g., with a for loop and then stacking, but is there any vectorized way to achieve the same result?

推荐答案

外部产品，除了它等于产品而不是产品:

numpy.equal.outer(scalars, a)

或调整尺寸并进行广播比较:

or adjust the dimensions and perform a broadcasted comparison:

scalars[:, None] == a

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