获得的精确模拟numpy.array(list(itertools.product(some_list, repeat=some_length)))你可以使用numpy.array(some_list)[numpy.rollaxis(numpy.indices((len(some_list),) * some_length), 0, some_length + 1).reshape(-1, some_length)]这完全不可读——告诉我是否应该进一步解释它:)I use itertools.product to generate all possible variations of 4 elements of length 13. The 4 and 13 can be arbitrary, but as it is, I get 4^13 results, which is a lot. I need the result as a Numpy array and currently do the following: c = it.product([1,-1,np.complex(0,1), np.complex(0,-1)], repeat=length) sendbuf = np.array(list(c))With some simple profiling code shoved in between, it looks like the first line is pretty much instantaneous, whereas the conversion to a list and then Numpy array takes about 3 hours.Is there a way to make this quicker? It's probably something really obvious that I am overlooking.Thanks! 解决方案 The NumPy equivalent of itertools.product() is numpy.indices(), but it will only get you the product of ranges of the form 0,...,k-1:numpy.rollaxis(numpy.indices((2, 3, 3)), 0, 4)array([[[[0, 0, 0], [0, 0, 1], [0, 0, 2]], [[0, 1, 0], [0, 1, 1], [0, 1, 2]], [[0, 2, 0], [0, 2, 1], [0, 2, 2]]], [[[1, 0, 0], [1, 0, 1], [1, 0, 2]], [[1, 1, 0], [1, 1, 1], [1, 1, 2]], [[1, 2, 0], [1, 2, 1], [1, 2, 2]]]])For your special case, you can usea = numpy.indices((4,)*13)b = 1j ** numpy.rollaxis(a, 0, 14)(This won't run on a 32 bit system, because the array is to large. Extrapolating from the size I can test, it should run in less than a minute though.)EIDT: Just to mention it: the call to numpy.rollaxis() is more or less cosmetical, to get the same output as itertools.product(). If you don't care about the order of the indices, you can just omit it (but it is cheap anyway as long as you don't have any follow-up operations that would transform your array into a contiguous array.)EDIT2: To get the exact analogue ofnumpy.array(list(itertools.product(some_list, repeat=some_length)))you can usenumpy.array(some_list)[numpy.rollaxis( numpy.indices((len(some_list),) * some_length), 0, some_length + 1) .reshape(-1, some_length)]This got completely unreadable -- just tell me whether I should explain it any further :) 这篇关于itertools 产品加速的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！ 上岸，阿里云！
