I'm stumped. I can't figure out how to extract from e.g.
view = A[:, 3]
that the view starts at element 3 of A. I was planning to make a
may_share_memory implementation based on the idea of swapping in a buffer
of 0s, and using the shapes, strides, itemsize etc. to increment just the
parts of the
Thanks, this is exactly what I was looking for. I'll look into what this
Diophantine equation is. Also, relatedly, a few months ago Julian Taylor at
least wrote what was there in C, which made it faster, if not better.
- James
On Fri, Sep 6, 2013 at 1:27 PM, Robert Kern wrote:
> On Fri, Sep 6,
For the astropy Table class (which wraps numpy structured arrays), I
wrote functions that perform table joins and concatenate tables along
rows or columns. These are reasonably full-featured and handle most
of the common needs for these operations. The join function here
addresses some limitation
FWIW -- updated runs of the benchmarks are available at
http://yarikoptic.github.io/numpy-vbench which now include also
maintenance/1.8.x branch (no divergences were detected yet). There are
only recent improvements as I see and no new (but some old ones are
still there, some might be specific to
On Fri, Sep 6, 2013 at 1:21 PM, Yaroslav Halchenko wrote:
> FWIW -- updated runs of the benchmarks are available at
> http://yarikoptic.github.io/numpy-vbench which now include also
> maintenance/1.8.x branch (no divergences were detected yet). There are
> only recent improvements as I see and no
On Fri, Sep 6, 2013 at 3:21 PM, Yaroslav Halchenko wrote:
> FWIW -- updated runs of the benchmarks are available at
> http://yarikoptic.github.io/numpy-vbench which now include also
> maintenance/1.8.x branch (no divergences were detected yet). There are
> only recent improvements as I see and no
On 6 September 2013 21:21, Yaroslav Halchenko wrote:
> some old ones are
> still there, some might be specific to my CPU here
>
How long does one run take? Maybe I can run it in my machine (Intel i5) for
comparison.
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Hi, could someone help me understand why this assertion fails?
def test_is(self):
a = np.empty(1)
b = np.empty(1)
if a.data is not b.data:
assert id(a.data) != id(b.data) # <-- fail
I'm trying to write an alternate may_share_memory function.
Thanks,
- James
_
Thanks for the tips! FWIW my guess is that since '.data' is dynamically
generated property rather than an attribute, it is being freed and
re-allocated in the loop, and once for each of my id() expressions.
On Fri, Sep 6, 2013 at 12:32 PM, Charles R Harris wrote:
>
>
>
> On Fri, Sep 6, 2013 at
On Fri, Sep 6, 2013 at 5:58 PM, James Bergstra
wrote:
>
> I'm stumped. I can't figure out how to extract from e.g.
>
> view = A[:, 3]
>
> that the view starts at element 3 of A. I was planning to make a
may_share_memory implementation based on the idea of swapping in a buffer
of 0s, and using the
On Fri, Sep 6, 2013 at 10:19 AM, James Bergstra
wrote:
> Hi, could someone help me understand why this assertion fails?
>
> def test_is(self):
> a = np.empty(1)
> b = np.empty(1)
> if a.data is not b.data:
> assert id(a.data) != id(b.data) # <-- fail
>
> I'm trying to write an
On Fri, Sep 6, 2013 at 9:19 AM, James Bergstra wrote:
> def test_is(self):
> a = np.empty(1)
> b = np.empty(1)
> if a.data is not b.data:
> assert id(a.data) != id(b.data) # <-- fail
>
>
I'm not familiar with the internals, but:
In [27]: a = np.empty(1)
In [28]: a.data
Out[28
The .data attribute is generated on the fly when accessed. So it returns an
anonymous temporary that's deallocated as soon as it's no longer needed.
a.data is b.data needs both objects, so both get allocated and then
compared. In the second one though, each object gets allocated one at a
time and
Hi experts!
I wanna use networkx.has_path(). This is applies, necesary, to a networkx
graph. I have a adjacency matrix of a undirected graph (M, wich is a numpy
matrix (array of N x N elements)).
How can I do for use M in networkx.has_path()?
If I must transform M into a networkx graph: ho
On Fri, Sep 6, 2013 at 12:09 AM, Jaime Fernández del Río
wrote:
> Hi all,
>
> I am seeing some very weird behavior on a gufunc I coded.
>
> It has a pretty complicated signature:
> '(r,c,p),(i,j,k,n),(u,v),(d),(n,q)->(q,r,c)'
>
> And a single registered loop function, for types:
> uint8, uint16,
Charles R Harris wrote:
> On Thu, Sep 5, 2013 at 5:34 AM, Neal Becker wrote:
>
>> Just want to make sure this post had been noted:
>>
>> Neal Becker wrote:
>>
>> > Built on fedora linux 19 x86_64 using mkl:
>> >
>> > build OK using:
>> > env ATLAS=/usr/lib64 FFTW=/usr/lib64 BLAS=/usr/lib64
>> LA
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