gt; np.where(x, 0, x)
>
> where x is a masked array, will return a masked array in 1.8.2 and
> earlier, but will return a regular numpy array in 1.9 and above (drops the
> mask).
> That bug took a long time for me to track down!
>
> Ben Root
>
> On Wed, Jul 29, 2015 at 5:16 P
Hi,
The numpy.where() function was rewritten in numpy 1.9 to speed it up. I
traced it to this changeset.
https://github.com/numpy/numpy/commit/593e3c30c24f0c61a271dc883c614724d7a57e1e
The weird thing is the 1.9 behavior changed the resulting dtype in some
situations when using scalar values as t
Hi,
I was wondering if there was any way to speed up the global import of
numpy modules. For a simple import numpy, it takes ~250 ms. In
comparison, importing Numeric is only taking 40 ms. It appears that
even if you only import a numpy submodule, it loads all the libraries,
resulting in the pa
