On Thu, 2013-04-04 at 16:56 +0300, Jaakko Luttinen wrote:
I don't quite understand how einsum handles broadcasting. I get the
following error, but I don't understand why:
In [8]: import numpy as np
In [9]: A = np.arange(12).reshape((4,3))
In [10]: B = np.arange(6).reshape((3,2))
In [11]:
I don't quite understand how einsum handles broadcasting. I get the
following error, but I don't understand why:
In [8]: import numpy as np
In [9]: A = np.arange(12).reshape((4,3))
In [10]: B = np.arange(6).reshape((3,2))
In [11]: np.einsum('ik,k...-i...', A, B)
On 25 October 2012 22:54, David Warde-Farley warde...@iro.umontreal.cawrote:
On Wed, Oct 24, 2012 at 7:18 AM, George Nurser gnur...@gmail.com wrote:
Hi,
I was just looking at the einsum function.
To me, it's a really elegant and clear way of doing array operations,
which
is the core
On Wed, Oct 24, 2012 at 7:18 AM, George Nurser gnur...@gmail.com wrote:
Hi,
I was just looking at the einsum function.
To me, it's a really elegant and clear way of doing array operations, which
is the core of what numpy is about.
It removes the need to remember a range of functions, some of
Hi,
I was just looking at the einsum function.
To me, it's a really elegant and clear way of doing array operations, which
is the core of what numpy is about.
It removes the need to remember a range of functions, some of which I find
tricky (e.g. tile).
Unfortunately the present implementation
Dear all,
I was just looking into numpy.einsum and encountered an issue which might
be worth pointing out in the documentation.
Let us say you wish to evaluate something like this (repeated indices a
summed)
D[alpha, alphaprime] = A[alpha, beta, sigma] * B[alphaprime, betaprime,
sigma] *
On Tue, Jan 24, 2012 at 6:32 AM, Søren Gammelmark gammelm...@gmail.comwrote:
Dear all,
I was just looking into numpy.einsum and encountered an issue which might
be worth pointing out in the documentation.
Let us say you wish to evaluate something like this (repeated indices a
summed)
Hi,
I was playing around with einsum (which is really cool, by the way!),
and I noticed something strange (or unexpected at least)
performance-wise. Here is an example:
Let x and y be two NxM arrays, and W be a NxN array. I want to compute
f = x^{ik} W_i^j y_{jk}
(I hope the notation is
I wrote a new function, einsum, which implements Einstein summation
notation, and I'd like comments/thoughts from people who might be interested
in this kind of thing.
In testing it, it is also faster than many of NumPy's built-in functions,
except for dot and inner. At the bottom of this email
On Wed, Jan 26, 2011 at 11:27 AM, Mark Wiebe mwwi...@gmail.com wrote:
I wrote a new function, einsum, which implements Einstein summation
notation, and I'd like comments/thoughts from people who might be interested
in this kind of thing.
This sounds really cool! I've definitely considered
On Wed, Jan 26, 2011 at 1:36 PM, Joshua Holbrook josh.holbr...@gmail.comwrote:
On Wed, Jan 26, 2011 at 11:27 AM, Mark Wiebe mwwi...@gmail.com wrote:
I wrote a new function, einsum, which implements Einstein summation
notation, and I'd like comments/thoughts from people who might be
On Wed, Jan 26, 2011 at 12:48 PM, Mark Wiebe mwwi...@gmail.com wrote:
On Wed, Jan 26, 2011 at 1:36 PM, Joshua Holbrook josh.holbr...@gmail.com
wrote:
On Wed, Jan 26, 2011 at 11:27 AM, Mark Wiebe mwwi...@gmail.com wrote:
I wrote a new function, einsum, which implements Einstein summation
On Wed, Jan 26, 2011 at 2:01 PM, Joshua Holbrook josh.holbr...@gmail.comwrote:
snip
How closely coupled is this new code with numpy's internals? That is,
could you factor it out into its own package? If so, then people could
have immediate use out of it without having to integrate it into
On Wed, Jan 26, 2011 at 16:43, Mark Wiebe mwwi...@gmail.com wrote:
On Wed, Jan 26, 2011 at 2:01 PM, Joshua Holbrook josh.holbr...@gmail.com
wrote:
snip
How closely coupled is this new code with numpy's internals? That is,
could you factor it out into its own package? If so, then people could
It think his real question is whether einsum() and the iterator stuff
can live in a separate module that *uses* a released version of numpy
rather than a development branch.
--
Robert Kern
Indeed, I would like to be able to install and use einsum() without
having to install another
Mark,
interesting idea. Given the fact that in 2-d euclidean metric, the
Einstein summation conventions are only a way to write out
conventional matrix multiplications, do you consider at some point to
include a non-euclidean metric in this thing? (As you have in special
relativity, for
On Thu, Jan 27, 2011 at 12:18:30AM +0100, Hanno Klemm wrote:
interesting idea. Given the fact that in 2-d euclidean metric, the
Einstein summation conventions are only a way to write out
conventional matrix multiplications, do you consider at some point to
include a non-euclidean metric
On Wed, Jan 26, 2011 at 3:05 PM, Joshua Holbrook josh.holbr...@gmail.comwrote:
It think his real question is whether einsum() and the iterator stuff
can live in a separate module that *uses* a released version of numpy
rather than a development branch.
--
Robert Kern
Indeed, I
On Wed, Jan 26, 2011 at 3:18 PM, Hanno Klemm kl...@phys.ethz.ch wrote:
Mark,
interesting idea. Given the fact that in 2-d euclidean metric, the
Einstein summation conventions are only a way to write out
conventional matrix multiplications, do you consider at some point to
include a
Am 27.01.2011 um 00:29 schrieb Mark Wiebe:
On Wed, Jan 26, 2011 at 3:18 PM, Hanno Klemm kl...@phys.ethz.ch
wrote:
Mark,
interesting idea. Given the fact that in 2-d euclidean metric, the
Einstein summation conventions are only a way to write out
conventional matrix multiplications, do you
On Wednesday, January 26, 2011, Gael Varoquaux
gael.varoqu...@normalesup.org wrote:
On Thu, Jan 27, 2011 at 12:18:30AM +0100, Hanno Klemm wrote:
interesting idea. Given the fact that in 2-d euclidean metric, the
Einstein summation conventions are only a way to write out
conventional matrix
Ah, sorry for misunderstanding. That would actually be very difficult,
as the iterator required a fair bit of fixes and adjustments to the core.
The new_iterator branch should be 1.5 ABI compatible, if that helps.
I see. Perhaps the fixes and adjustments can/should be included with
numpy
On Wed, Jan 26, 2011 at 5:02 PM, Joshua Holbrook
josh.holbr...@gmail.com wrote:
Ah, sorry for misunderstanding. That would actually be very difficult,
as the iterator required a fair bit of fixes and adjustments to the core.
The new_iterator branch should be 1.5 ABI compatible, if that helps.
On Wed, Jan 26, 2011 at 7:35 PM, Benjamin Root ben.r...@ou.edu wrote:
On Wednesday, January 26, 2011, Gael Varoquaux
gael.varoqu...@normalesup.org wrote:
On Thu, Jan 27, 2011 at 12:18:30AM +0100, Hanno Klemm wrote:
interesting idea. Given the fact that in 2-d euclidean metric, the
Einstein
Nice function, and wonderful that it speeds some tasks up.
some feedback: the following notation is a little counter intuitive to me:
np.einsum('i...-', a)
array([50, 55, 60, 65, 70])
np.sum(a, axis=0)
array([50, 55, 60, 65, 70])
Since there is nothing after the -, I expected a
On Wed, Jan 26, 2011 at 6:41 PM, Jonathan Rocher jroc...@enthought.comwrote:
Nice function, and wonderful that it speeds some tasks up.
some feedback: the following notation is a little counter intuitive to me:
np.einsum('i...-', a)
array([50, 55, 60, 65, 70])
np.sum(a,
On Wed, Jan 26, 2011 at 5:23 PM, josef.p...@gmail.com wrote:
snip
So, if I read the examples correctly we finally get dot along an axis
np.einsum('ijk,ji-', a, b)
np.einsum('ijk,jik-k', a, b)
or something like this.
the notation might require getting used to but it doesn't look worse
The only disadvantage I see, is that choosing the axes to operate on
in a program or function requires string manipulation.
One possibility would be for the Python exposure to accept lists or tuples
of integers. The subscript 'ii' could be [(0,0)], and 'ij,jk-ik' could be
[(0,1), (1,2),
On Wed, Jan 26, 2011 at 8:29 PM, Joshua Holbrook josh.holbr...@gmail.comwrote:
The only disadvantage I see, is that choosing the axes to operate on
in a program or function requires string manipulation.
One possibility would be for the Python exposure to accept lists or
tuples
of
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