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From: Sebastian H. <ha...@ms...> - 2005-07-05 23:04:37
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Hi, (this is regarding my post from 16 June 2005) Todd, maybe you can confirm that this patch is a good idea and that you will put it into upcoming numarray versions !? I would like to streamline my code - but only of course if you OK this. Sebastian On Thursday 16 June 2005 11:12, Sebastian Haase wrote: > Hi, > Please tell if this patch is a good idea. (Use: For large image data we > always use Float32 and I thought it would be extra overhead if I first > create everything in Float64 and then have to convert to Float32 > afterwards, myself) > > haase@gorilla:~: diff -p ~/myCVS/numarray/Lib/generic.py > ~/myCVS/numarray/Lib/generic.py.~1.74.~ > *** /home/haase/myCVS/numarray/Lib/generic.py Thu Jun 16 11:04:10 2005 > --- /home/haase/myCVS/numarray/Lib/generic.py.~1.74.~ Fri Apr 22 13:35:26 > 2005 > *************** def indices(shape, type=None): > *** 1167,1179 **** > a = a.astype(type) > return a > > ! def fromfunction(function, dimensions, type=None): # from Numeric > """fromfunction() returns an array constructed by calling function > on a tuple of number grids. The function should accept as many > arguments as there are dimensions which is a list of numbers > indicating the length of the desired output for each axis. > """ > ! return apply(function, tuple(indices(dimensions,type))) > > def _broadcast_or_resize(a, b): > try: > --- 1167,1179 ---- > a = a.astype(type) > return a > > ! def fromfunction(function, dimensions): # from Numeric > """fromfunction() returns an array constructed by calling function > on a tuple of number grids. The function should accept as many > arguments as there are dimensions which is a list of numbers > indicating the length of the desired output for each axis. > """ > ! return apply(function, tuple(indices(dimensions))) > > def _broadcast_or_resize(a, b): > try: > > Thanks, > - Sebastian Haase > > > ------------------------------------------------------- > SF.Net email is sponsored by: Discover Easy Linux Migration Strategies > from IBM. Find simple to follow Roadmaps, straightforward articles, > informative Webcasts and more! Get everything you need to get up to > speed, fast. http://ads.osdn.com/?ad_id=7477&alloc_id=16492&op=click > _______________________________________________ > Numpy-discussion mailing list > Num...@li... > https://lists.sourceforge.net/lists/listinfo/numpy-discussion |