Hi, On Wed, Jan 26, 2011 at 2:35 PM, <josef.p...@gmail.com> wrote:
> On Wed, Jan 26, 2011 at 7:22 AM, eat <e.antero.ta...@gmail.com> wrote: > > Hi, > > > > I just noticed a document/ implementation conflict with tril and triu. > > According tril documentation it should return of same shape and data-type > as > > called. But this is not the case at least with dtype bool. > > > > The input shape is referred as (M, N) in tril and triu, but as (N, M) in > > tri. > > Inconsistent? > Any comments about the names for rows and cols. I prefer (M, N). > > > > Also I'm not very happy with the performance, at least dtype bool can be > > accelerated as follows. > > > > In []: M= ones((2000, 3000), dtype= bool) > > In []: timeit triu(M) > > 10 loops, best of 3: 173 ms per loop > > In []: timeit triu_(M) > > 10 loops, best of 3: 107 ms per loop > > > > In []: M= asarray(M, dtype= int) > > In []: timeit triu(M) > > 10 loops, best of 3: 160 ms per loop > > In []: timeit triu_(M) > > 10 loops, best of 3: 163 ms per loop > > > > In []: M= asarray(M, dtype= float) > > In []: timeit triu(M) > > 10 loops, best of 3: 195 ms per loop > > In []: timeit triu_(M) > > 10 loops, best of 3: 157 ms per loop > > > > I have attached a crude 'fix' incase someone is interested. > > You could open a ticket for this. > > just one comment: > I don't think this is readable, especially if we only look at the > source of the function with np.source > > out= mul(ge(so(ar(m.shape[0]), ar(m.shape[1])), -k), m) > > from np.source(np.tri) with numpy 1.5.1 > m = greater_equal(subtract.outer(arange(N), arange(M)),-k) I agree, thats why I called it crude. Before opening a ticket I'll try to figure out if there exists somewhere in numpy .astype functionality, but not copying if allready proper dtype. Also I'm afraid that I can't produce sufficient testing. Regards, eat > > Josef > > > > > Regards, > > eat > > _______________________________________________ > > NumPy-Discussion mailing list > > NumPy-Discussion@scipy.org > > http://mail.scipy.org/mailman/listinfo/numpy-discussion > > > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion >
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