[Numpy-discussion] 1.10.0rc1

[Sebastian Berg]

On Do, 2015-08-27 at 11:15 -0400, Benjamin Root wrote:
> Ok, I just wanted to make sure I understood the issue before going bug
> hunting. Chances are, it has been a bug on our end for a while now.
> Just to make sure, is the following valid?
> 
> 
> arr = np.zeros((5, 3))
> 
> ind = np.array([True, True, True, False, True])
> 
> arr[ind]   # gives a 4x3 result
> 
> 
> Running that at the REPL doesn't produce a warning, so i am guessing
> that it is valid.
> 

Sure, that is perfect (you can add the slice and write `arr[ind, :]` to
make it a bit more clear if you like I guess).

- Sebastian


> 
> Ben Root
> 
> 
> On Thu, Aug 27, 2015 at 10:44 AM, Sebastian Berg
> <sebastian at sipsolutions.net> wrote:
>         On Do, 2015-08-27 at 08:04 -0600, Charles R Harris wrote:
>         >
>         >
>         > On Thu, Aug 27, 2015 at 7:52 AM, Benjamin Root
>         <ben.v.root at gmail.com>
>         > wrote:
>         >
>         >
>         >         Ok, I tested matplotlib master against numpy master,
>         and there
>         >         were no errors. I did get a bunch of new deprecation
>         warnings
>         >         though such as:
>         >
>         >
>          "/nas/home/broot/centos6/lib/python2.7/site-packages/matplotlib-1.5.dev1-py2.7-linux-x86_64.egg/matplotlib/colorbar.py:539: VisibleDeprecationWarning: boolean index did not match indexed array along dimension 0; dimension is 5 but corresponding boolean dimension is 3
>         >           colors = np.asarray(colors)[igood]"
>         >
>         >
>         >         The message isn't exactly clear. I suspect the
>         problem is a
>         >         shape mismatch, like colors is 5x3, and igood is
>         just 3 for
>         >         some reason. Could somebody shine some light on
>         this, please?
>         >
>         >
>         >
>         > IIRC, Boolean indexing would fill out the dimension, i.e.,
>         len 3 would
>         > be expanded to len 5 in this case. That behavior is
>         deprecated.
>         >
>         
>         Yes, this is exactly the case, you have something like:
>         
>         arr = np.zeros((5, 3))
>         ind = np.array([True, False, False])
>         arr[ind, :]
>         
>         and numpy nowadays thinks that such code is likely a bug (when
>         the ind
>         is shorter than arr it is somewhat OK, the other way around
>         gets more
>         creepy). If you have an idea of how to make the error message
>         clearer,
>         or objections to the change, I am happy to hear it!
>         
>         - Sebastian
>         
>         
>         >
>         > Chuck
>         >
>         >
>         >
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