Np dstack/hstack/vstack wasn't that bad for me but some of the things you
can do with dimensions in numpy and how you do them efficiently / sometimes
even do them at all ..wow o_o those still surprise me, .e.g. some of the
ways to do things in _geometic.py :)
On Wed, Jun 5, 2013 at 8:35 PM, Juan Nunez-Iglesias
I too was unaware of np.dstack for a long time, and was doing it via np.concatenate([R[..., np.newaxis], G[..., np.newaxis], B[..., np.newaxis]], axis=-1)... Which is a mouthful. ;) And even after I became aware of it I still couldn't remember to use it! Sometimes aliases are useful. And, as we mentioned, channel handling could be important, though I usually have three channels.
On Thu, Jun 6, 2013 at 4:26 AM, Ronnie Ghose
wrote: Its just an alias on top of for ease of use I assume On Jun 5, 2013 12:54 PM, "Johannes Schönberger"
wrote: I didn't know that one, my bad... So the only thing left is the data handling (float conversion and possibly normalization), plus the cases where you only provide 1 or 2 channels (which often the case in fluorescence images), which is probably not worth a function. Thank's for the tip anyway
If the channel handling (when one of the channels is missing) is regarded as a common use case, we could definitely add this function!
Johannes Schönberger
Am 05.06.2013 um 18:17 schrieb Guillaume Gay < guillaume@mitotic-machine.org>:
Le 05/06/2013 17:34, Johannes Schönberger a écrit :
np.dstack([R, G, B]) I didn't know that one, my bad... So the only thing left is the data
handling (float conversion and possibly normalization), plus the cases where you only provide 1 or 2 channels (which often the case in fluorescence images), which is probably not worth a function. Thank's for the tip anyway
G.
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Ronnie Ghose