Re: [Numpy-discussion] Building numpy with ATLAS

2016-07-18 Thread Shitikanth Kashyap
As it turns out, I just had to run "python setup.py build --force" after changing my site.cfg file in order to recompile numpy/core/multiarray.so. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org

Re: [Numpy-discussion] isnan() equivalent for np.NaT?

2016-07-18 Thread Stephan Hoyer
Agreed -- this would be really nice to have. For now, the best you can do is something like the following: def is_na(x): x = np.asarray(x) if np.issubdtype(x.dtype, (np.datetime64, np.timedelta64)): # ugh int_min = np.iinfo(np.int64).min return x.view('int64') == int_min

Re: [Numpy-discussion] isnan() equivalent for np.NaT?

2016-07-18 Thread Gerrit Holl
On 18 July 2016 at 22:20, Scott Sanderson wrote: > I'm working on upgrading Zipline (github.com/quantopian/zipline) to the > latest numpy, and I'm getting a FutureWarnings about the upcoming change in > the behavior of comparisons on np.NaT. I'd like to be able to do

[Numpy-discussion] isnan() equivalent for np.NaT?

2016-07-18 Thread Scott Sanderson
Hi All, I'm working on upgrading Zipline (github.com/quantopian/zipline) to the latest numpy, and I'm getting a FutureWarnings about the upcoming change in the behavior of comparisons on np.NaT. I'd like to be able to do checks for NaT in a way that's forwards-compatible, but I couldn't find a

Re: [Numpy-discussion] deterministic, reproducible matmul / __matmult_

2016-07-18 Thread Jason Newton
On Mon, Jul 11, 2016 at 3:27 PM, Pauli Virtanen wrote: > Mon, 11 Jul 2016 13:01:49 -0400, Jason Newton kirjoitti: >> Does the ML have any ideas on how one could get a matmul that will not >> allow any funny business on the evaluation of the products? Funny >> business here is

[Numpy-discussion] Building numpy with ATLAS

2016-07-18 Thread Shitikanth Kashyap
Hey Everyone, I am trying to build numpy-1.11.1 with ATLAS libraries. The build completes successfully, and I am able to use numpy, but there seems to be some problem with my config because numpy only ever uses one core, even when multiplying 5000x5000 matrices with numpy.dot. My site.cfg