On Wed, Jan 26, 2011 at 2:35 PM, <josef.pktd@gmail.com> wrote:

Regards, eat

On Wed, Jan 26, 2011 at 7:22 AM, eat <e.antero.tammi@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).

You could open a ticket for this.>

> 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.

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