I have two numpy arrays that define the x and y axes of a grid. For example:
x = numpy.array([1,2,3]) y = numpy.array([4,5])
I’d like to generate the Cartesian product of these arrays to generate:
array([[1,4],[2,4],[3,4],[1,5],[2,5],[3,5]])
In a way that’s not terribly inefficient since I need to do this many times in a loop. I’m assuming that converting them to a Python list and using itertools.product
and back to a numpy array is not the most efficient form.
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Answer
>>> numpy.transpose([numpy.tile(x, len(y)), numpy.repeat(y, len(x))]) array([[1, 4], [2, 4], [3, 4], [1, 5], [2, 5], [3, 5]])
See Using numpy to build an array of all combinations of two arrays for a general solution for computing the Cartesian product of N arrays.