Improve performance of converting matlab arrays to numpy arrays

Asked Aug 28 '18 at 07:36

Active Aug 28 '18 at 07:36

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I'm using python from matlab (reference). creating numpy arrays is as easy as py.numpy.array(rand(1, 10)). By passing the dimensions I can also create a small method that will allow me to pass multidimensional arrays.

The performance, though, is awful. I guess it's because the conversion is first to python's list and then to matlab array (boxing and unboxing).

Is there a way (like the one suggested in the referenced question) to improve that conversion?

asked Aug 28 '18 at 07:36

galah92

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Something like this?: https://stackoverflow.com/a/45290997/4045774 – max9111 Aug 28 '18 at 09:05
that's when calling matlab from inside python. I'm doing the opposite - inside matlab calling python. – galah92 Aug 28 '18 at 10:02

Improve performance of converting matlab arrays to numpy arrays

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