Hello, indeed I was looking for the cartesian product.
I timed the two stackoverflow answers and the winner is not quite as clear: n_elements: 10 cartesian 0.00427 cartesian2 0.00172 n_elements: 100 cartesian 0.02758 cartesian2 0.01044 n_elements: 1000 cartesian 0.97628 cartesian2 1.12145 n_elements: 5000 cartesian 17.14133 cartesian2 31.12241 (This is for two arrays as parameters: np.linspace(0, 1, n_elements)) cartesian2 seems to be slower for bigger. I'd really appreciate if this was be part of numpy. Should I create a pull request? Regarding combinations and permutations: I could be convenient to have as well. Cheers, Stefan
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