[Numpy-discussion] Good way to develop numpy as popular choice!
travis at continuum.io
Fri Jun 22 11:13:12 EDT 2012
> However, what is the timing/memory cost of converting a large numpy array that already exists into python list of lists? If all my processing before the munkres step is using NumPy, converting it into python lists has a cost. Also, your timings indicate only ~2x slowdown, while the timing tests done by eat show an order-of-magnitude difference. I suspect there is great room for improvement before even starting to worry about the array access issues.
If you are also doing scalar math with the results returned from NumPy array element access, then a.item(i,j) will be faster because it returns a Python object which will use it's scalar math instead of re-using vectorized math operations which a[i,j] will do.
I haven't looked at the code yet, just re-emphasizing known issues with trying to use NumPy as an arbitrary container of "elements" rather than a container of bytes that you do vectorized operations on.
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