On Feb 10, 2008 6:48 PM, Matthew Brett <[EMAIL PROTECTED]> wrote: > > > import numpy as np > > > a = np.arange(10) > > > b = np.arange(10)+1 > > > a.data = b.data # raises error, but I hope you see what I mean > > > > > > ? > > > > Not really, no. Can you describe your use case in more detail? > > Yes - I am just writing the new median implementation. To allow > future optimization, I would like to have the same signature as > mean(): > > def median(a, axis=0, dtype=None, out=None) > > (axis=0 to change to axis=None default at some point). > > To do this, I need to copy the results of the median calculation in > the routine into the array object given by 'out' - when passed.
Ah, I see. You definitely do not want to reassign the .data buffer in this case. An out= parameter does not reassign the memory location that the array object points to. It should use the allocated memory that was already there. It shouldn't "copy" anything at all; otherwise, "median(x, out=out)" is no better than "out[:] = median(x)". Personally, I don't think that a function should expose an out= parameter unless if it can make good on that promise of memory efficency. Can you show us the current implementation that you have? -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
