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.
Ben Root
On Thu, Aug 27, 2015 at 10:44 AM, Sebastian Berg

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

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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