On Tue, Jul 8, 2008 at 5:08 PM, Marek Wojciechowski
[EMAIL PROTECTED] wrote:
cxx.linker_so = [cxx.linker_so[0], cxx.compiler_cxx[0]] + cxx.linker_so[2:]
in line 303 of cccompiler.py in distutils.
Should be fixed in r5368. I will merge the change into 1.1.1 as well
cheers,
David
Hi all,
I wanted to point out a couple of things about the new test framework
that you should keep in mind if you're writing tests:
- Don't use NumpyTestCase any more, just use TestCase (which is
available if you do from numpy.testing import *). Using NumpyTestCase
now causes a deprecation
Tue, 08 Jul 2008 23:03:52 -0500, Robert Kern wrote:
On Tue, Jul 8, 2008 at 14:01, Keith Goodman [EMAIL PROTECTED] wrote:
I don't know what to write for a doc string for alterdot and
restoredot.
Then maybe you're the best one to figure it out. What details do you
think are missing from the
Hi all,
A `numpy.doc` sub-module has been added, which contains documentation
for topics such as indexing, broadcasting, array operations etc.
These can be edited from the documentation wiki:
http://sd-2116.dedibox.fr/pydocweb/doc/numpy.doc/
If you'd like to document a topic that is not there,
There are three separate patches in this message plus some remarks on
stealing reference counts at the bottom.
On Tue, 8 Jul 2008, Travis E. Oliphant wrote:
Michael Abbott wrote:
On Tue, 8 Jul 2008, Travis E. Oliphant wrote:
The first part of this patch is good. The second is not needed.
On Wed, Jul 9, 2008 at 03:28, Stéfan van der Walt [EMAIL PROTECTED] wrote:
Please log in and leave comments on those. Your input would be much
appreciated!
Each docstring page could use a Next link to move to the next
docstring with the same review status (actually, the same review
status that
On Wed, 9 Jul 2008, Michael Abbott wrote:
Well then, I need to redo my patch. Here's the new patch for
..._arrtype_new:
I'm sorry about this, I posted too early. Here is the final patch (and
I'll update the ticket accordingly).
commit a1ff570cbd3ca6c28f87c55cebf2675b395c6fa0
Author:
On Wed, Jul 9, 2008 at 02:53, Pauli Virtanen [EMAIL PROTECTED] wrote:
Tue, 08 Jul 2008 23:03:52 -0500, Robert Kern wrote:
On Tue, Jul 8, 2008 at 14:01, Keith Goodman [EMAIL PROTECTED] wrote:
I don't know what to write for a doc string for alterdot and
restoredot.
Then maybe you're the best
I had a chance to look at Anne's suggestion from this thread
http://www.mail-archive.com/numpy-discussion@scipy.org/msg10091.html
and I thought I should post my phase winding finder solution, which is
slightly modified from her idea. Thanks Anne. This is a vast improvement
over my original slow
I really don't think that this design of reference count handling in
PyArray_FromAny (and consequently PyArray_CheckFromAny) is a good idea.
Unfortunately these seem to be part of the published API, so presumably
it's too late to change this? (Otherwise I might see how the
corresponding
2008/7/9 Robert Kern [EMAIL PROTECTED]:
- Which operations do the functions exactly affect?
It seems that alterdot sets the dot function slot to a BLAS
version, but what operations does this affect?
dot(), vdot(), and innerproduct() on C-contiguous arrays which are
Matrix-Matrix,
On Wed, Jul 9, 2008 at 2:36 AM, Michael Abbott [EMAIL PROTECTED]
wrote:
There are three separate patches in this message plus some remarks on
stealing reference counts at the bottom.
snip
I really don't think that this design of reference count handling in
PyArray_FromAny (and consequently
Hello,
I have a question about performing element-wise logical operations
on numpy arrays.
If a, b and c are numpy arrays of the same size, does the
following
syntax work?
mask = (a 1.0) ((b 3.0) | (c 10.0))
It seems to be performing correctly, but the documentation that I've
read
On Wed, Jul 9, 2008 at 10:21 AM, Catherine Moroney
[EMAIL PROTECTED] wrote:
Hello,
I have a question about performing element-wise logical operations
on numpy arrays.
If a, b and c are numpy arrays of the same size, does the
following
syntax work?
mask = (a 1.0) ((b 3.0) | (c
2008/7/9 Catherine Moroney [EMAIL PROTECTED]:
I have a question about performing element-wise logical operations
on numpy arrays.
If a, b and c are numpy arrays of the same size, does the
following
syntax work?
mask = (a 1.0) ((b 3.0) | (c 10.0))
It seems to be performing correctly,
Hello,
This is a reminder that early registration for SciPy 2008 ends in two
days on Friday, July 11th. To register, please see:
http://conference.scipy.org/to_register
This year's conference has two days for tutorials, two days of
presentations, and ends with a two day coding sprint. If you
On Jul 9, 2008, at 10:00 AM, [EMAIL PROTECTED] wrote:
Send Numpy-discussion mailing list submissions to
numpy-discussion@scipy.org
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On Wed, Jul 9, 2008 at 11:11 AM, Catherine Moroney
[EMAIL PROTECTED] wrote:
On Jul 9, 2008, at 10:00 AM, [EMAIL PROTECTED] wrote:
Send Numpy-discussion mailing list submissions to
numpy-discussion@scipy.org
To subscribe or unsubscribe via the World Wide Web, visit
All:
I'm trying to take a constant vector:
v = (0.122169, 0.61516, 0.262671)
and multiply those values by every 3 components in an array of length N:
A = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, ]
So what I want is:
v[0]*A[0]
v[1]*A[1]
v[2]*A[2]
v[0]*A[3]
v[1]*A[4]
v[2]*A[5]
v[0]*A[6]
On Wed, Jul 9, 2008 at 9:26 AM, Anne Archibald
[EMAIL PROTECTED] wrote:
- Test functions and methods will only be picked up based on name if
they begin with test; check_* will no longer be seen as a test
function.
Is it possible to induce nose to pick these up and, if not actually
run them,
On Wed, Jul 9, 2008 at 1:16 PM, Marlin Rowley [EMAIL PROTECTED]
wrote:
All:
I'm trying to take a constant vector:
v = (0.122169, 0.61516, 0.262671)
and multiply those values by every 3 components in an array of length N:
A = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, ]
So what I want is:
On Wed, Jul 9, 2008 at 14:19, Alan McIntyre [EMAIL PROTECTED] wrote:
I can make a pass through all the test_* modules in the source tree
under test and post a warning if def check_ is found in them before
handing things over to nose.Anyone else have thoughts on this?
I don't think it's
On Wed, Jul 9, 2008 at 14:26, Robert Kern [EMAIL PROTECTED] wrote:
On Wed, Jul 9, 2008 at 14:19, Alan McIntyre [EMAIL PROTECTED] wrote:
I can make a pass through all the test_* modules in the source tree
under test and post a warning if def check_ is found in them before
handing things over
On Wed, Jul 9, 2008 at 3:26 PM, Robert Kern [EMAIL PROTECTED] wrote:
I don't think it's worth automating on every run. People can see for
themselves if they have any such check_methods() and make the
conversion once:
Does this fall into the how in the world should I have known to do
that
2008/7/9 Catherine Moroney [EMAIL PROTECTED]:
I have a question about performing element-wise logical operations
on numpy arrays.
If a, b and c are numpy arrays of the same size, does the
following syntax work?
mask = (a 1.0) ((b 3.0) | (c 10.0))
It seems to be
On Wed, Jul 9, 2008 at 12:43 PM, Catherine Moroney
[EMAIL PROTECTED] wrote:
2008/7/9 Catherine Moroney [EMAIL PROTECTED]:
I have a question about performing element-wise logical operations
on numpy arrays.
If a, b and c are numpy arrays of the same size, does the
following syntax
On Wed, Jul 9, 2008 at 14:35, Alan McIntyre [EMAIL PROTECTED] wrote:
On Wed, Jul 9, 2008 at 3:26 PM, Robert Kern [EMAIL PROTECTED] wrote:
I don't think it's worth automating on every run. People can see for
themselves if they have any such check_methods() and make the
conversion once:
Does
On Wed, Jul 9, 2008 at 06:36, Anne Archibald [EMAIL PROTECTED] wrote:
2008/7/9 Robert Kern [EMAIL PROTECTED]:
- Which operations do the functions exactly affect?
It seems that alterdot sets the dot function slot to a BLAS
version, but what operations does this affect?
dot(), vdot(), and
There's a _get_truendim method on matrix that isn't referenced
anywhere in NumPy, SciPy, or matplotlib. Should this get deprecated
or removed in 1.2?
___
Numpy-discussion mailing list
Numpy-discussion@scipy.org
On Wed, Jul 9, 2008 at 15:16, Alan McIntyre [EMAIL PROTECTED] wrote:
There's a _get_truendim method on matrix that isn't referenced
anywhere in NumPy, SciPy, or matplotlib. Should this get deprecated
or removed in 1.2?
We could remove it. It's a private method.
--
Robert Kern
I have come
On Wed, Jul 9, 2008 at 4:23 PM, Robert Kern [EMAIL PROTECTED] wrote:
On Wed, Jul 9, 2008 at 15:16, Alan McIntyre [EMAIL PROTECTED] wrote:
There's a _get_truendim method on matrix that isn't referenced
anywhere in NumPy, SciPy, or matplotlib. Should this get deprecated
or removed in 1.2?
We
Thanks Chuck, but I wasn't quit clear with my question.
You answered exactly according to what I asked, but I failed to mention needing
the dot product instead of just the product.
So,
v dot A = v'
v'[0] = v[0]*A[0] + v[1]*A[1] + v[2]*A[2]
v'[1] = v[0]*A[3] + v[1]*A[4] + v[2]*A[5]
v'[2]
I'd like to make the following change to the chararray constructor.
This is motivated by some of chararray's methods constructing new
chararrays with NumPy integer arguments to itemsize, and it just
seemed easier to fix this in the constructor.
Index: numpy/numpy/core/defchararray.py
On Wed, Jul 9, 2008 at 2:34 PM, Marlin Rowley [EMAIL PROTECTED]
wrote:
Thanks Chuck, but I wasn't quit clear with my question.
You answered exactly according to what I asked, but I failed to mention
needing the dot product instead of just the product.
So,
v dot A = v'
v'[0] = v[0]*A[0]
2008/7/9 Charles R Harris [EMAIL PROTECTED]:
On Wed, Jul 9, 2008 at 2:34 PM, Marlin Rowley [EMAIL PROTECTED]
wrote:
Thanks Chuck, but I wasn't quit clear with my question.
You answered exactly according to what I asked, but I failed to mention
needing the dot product instead of just the
On Wed, Jul 9, 2008 at 3:26 PM, Anne Archibald [EMAIL PROTECTED]
wrote:
2008/7/9 Charles R Harris [EMAIL PROTECTED]:
On Wed, Jul 9, 2008 at 2:34 PM, Marlin Rowley [EMAIL PROTECTED]
wrote:
Thanks Chuck, but I wasn't quit clear with my question.
You answered exactly according to
Hi,
When trying to construct an ndarray, I sometimes run into the
more-or-less mystifying error expected a single-segment buffer
object:
Out[54]: (0, 16, 8)
In [55]: A=np.zeros(2); A=A[np.newaxis,...];
np.ndarray(strides=A.strides,shape=A.shape,buffer=A,dtype=A.dtype)
On Wed, Jul 9, 2008 at 18:55, Anne Archibald [EMAIL PROTECTED] wrote:
Hi,
When trying to construct an ndarray, I sometimes run into the
more-or-less mystifying error expected a single-segment buffer
object:
Out[54]: (0, 16, 8)
In [55]: A=np.zeros(2); A=A[np.newaxis,...];
2008/7/9 Robert Kern [EMAIL PROTECTED]:
Yes, the buffer interface, at least the subset that ndarray()
consumes, requires that all of the data be contiguous in memory.
array_as_buffer() checks for that using PyArray_ISONE_SEGMENT(), which
looks like this:
#define PyArray_ISONESEGMENT(m)
On Wed, Jul 9, 2008 at 21:29, Anne Archibald [EMAIL PROTECTED] wrote:
2008/7/9 Robert Kern [EMAIL PROTECTED]:
Yes, the buffer interface, at least the subset that ndarray()
consumes, requires that all of the data be contiguous in memory.
array_as_buffer() checks for that using
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