如何优化这个numpy 2D排序数组创建？(How can this numpy 2D sorted array creation be optimized?)

如何优化这个numpy 2D排序数组创建？(How can this numpy 2D sorted array creation be optimized?)

我有一个名为coefficients的NxM矩阵我要排序：

import numpy N = 10 M = 42 coefficients = numpy.random.uniform(size=(N, M))

我有一个名为order的数组order其中有N元素，表示coefficients行应该在的顺序：

order = numpy.random.choice(range(N), N, False)

我按排序order对coefficients进行排序：

coefficients = numpy.array([mag for (orig, mag) in sorted(zip(order, coefficients), key=lambda pair: pair[0])])

这可行，但它可能比它应该慢。 如果这是1D，我会使用fromiter ，但我不知道如何处理这个，因为它是2D。 我可以在这里进行优化吗？

I have a NxM matrix called coefficients that I want to sort:

import numpy N = 10 M = 42 coefficients = numpy.random.uniform(size=(N, M))

I have an array called order with N elements that says the order that the rows of coefficients should be in:

order = numpy.random.choice(range(N), N, False)

I'm sorting coefficients by sorting order:

coefficients = numpy.array([mag for (orig, mag) in sorted(zip(order, coefficients), key=lambda pair: pair[0])])

This works, but it's probably slower than it should be. If this was in 1D, I'd use fromiter, but I don't know how to tackle this since it's 2D. Is there an optimization I can make here?

最满意答案

要回答你的问题，只需coefficients[order.argsort()] :)

另见Numpy：按键排序功能 。

To answer your question, just coefficients[order.argsort()] is enough :)

See also Numpy: sort by key function.