On 15.06.2011, at 1:34AM, Mark Wiebe wrote:
These functions are now fully implemented and documented. As always, code
reviews are welcome here:
https://github.com/numpy/numpy/pull/87
and for those that don't want to dig into review C code, the commit for the
documentation is here:
Hi Ralf,
I am pleased to announce the availability of the first release candidate of
NumPy 1.6.1. This is a bugfix release, list of fixed bugs:
#1834 einsum fails for specific shapes
#1837 einsum throws nan or freezes python for specific array shapes
#1838 object - structured type
Hi Ralf,
FAIL: Test custom format function for each element in array.
--
This test is not in 1.6.x, only in master. I suspect the same is true for the
datetime tests, but perhaps not for the S5/U5 thing. Can you clean
On 13.06.2011, at 6:19PM, Ralf Gommers wrote:
I used wget using the direct link and it eventually got the complete
file after multiple tries.
Yes, SF is having a pretty bad day.
I eventually also got the tarball through the fink/debian mirror list; no
failures on OS X 10.5 i386. There
Hi Chris,
On 31 May 2011, at 13:56, cgraves wrote:
I've downloaded the latest numpy (1.6.0) and loadtxt has the ndmin
option,
however neither genfromtxt nor recfromtxt, which use loadtxt, have it.
Should they have inherited the option? Who can make it happen?
you are mistaken, genfromtxt
On 31 May 2011, at 17:33, Bruce Southey wrote:
It certainly would make sense to provide the same functionality for
genfromtxt (which should then be inherited by [nd,ma,rec]fromtxt),
so
I'd go ahead and file a feature (enhancement) request. I can't
promise
I can take care of it myself,
On 31 May 2011, at 17:45, Benjamin Root wrote:
At this point, I wonder if it might be smarter to create
a .atleast_Nd() function and use that everywhere it is needed.
Having similar logic tailored for each loading function might be a
little dangerous if bug fixes are made to one, but
On 31 May 2011, at 18:25, Pierre GM wrote:
On May 31, 2011, at 5:52 PM, Derek Homeier wrote:
I think stuff like multiple delimiters should have been dealt with
before, as the right place to insert the ndmin code (which includes
the decision to squeeze or not to squeeze as well as to add
On 26 May 2011, at 11:17, Talla wrote:
Below is the output of the coammands you mentioned.
C:\python
Python 2.6.2 (r262:71600, Jul 7 2009, 20:21:09) [MSC v.1500 32 bit
(Intel)] on win3
Type help, copyright, credits or license for more information.
import numpy
print(numpy.arange(3))
On 19.05.2011, at 12:47AM, Aradenatorix Veckhom Vacelaevus wrote:
I have a file in simple text with information obtained in Fortran 77 and I
need to use the data inside for visualize with Mayavi. I was fighting for a
while with the VTK simple legacy format. Finally I could run an small
Hi,
just a comment since I first thought the solution below might not be
what Bruce
was looking for, but having realised it's probably what he's been
asking for...
On 13 May 2011, at 17:20, josef.p...@gmail.com wrote:
On Fri, May 13, 2011 at 10:58 AM, Bruce Southey bsout...@gmail.com
On 13 May 2011, at 22:04, josef.p...@gmail.com wrote:
Thus I am wondering why broadcasting should not be possible in this
case,
Even a 1 column table is still a table (or a list of records), and a 1
item row is still a row.
True, but even multiplying the shape (6, ) array e.g. with a shape
On 6 May 2011, at 07:53, Ralf Gommers wrote:
Looks okay, and I agree that it's better to fix it now. The timing
is a bit unfortunate though, just after RC2. I'll have closer look
tomorrow and if it can go in, probably tag RC3.
If in the meantime a few more people could test this, that
On 5 May 2011, at 22:53, Derek Homeier wrote:
However, the problem that ndmin is supposed to address is not fixed
by the current implementation for the rc. Essentially, a single-
row, multi-column file with ndmin=2 comes out as a Nx1 array which
is the same result for a multi-row, single
On 04.05.2011, at 8:42PM, Ralf Gommers wrote:
==
FAIL: test_return_character.TestF90ReturnCharacter.test_all
--
Traceback (most recent call last):
File
Hi Paul,
I've got back to your suggestion re. the ndmin flag for loadtxt from a few
weeks ago...
On 27.03.2011, at 12:09PM, Paul Anton Letnes wrote:
1562:
I attach a possible patch. This could also be the default
behavior to my mind, since the function caller can simply call
On 05.05.2011, at 2:40AM, Paul Anton Letnes wrote:
But: Isn't the numpy.atleast_2d and numpy.atleast_1d functions written for
this? Shouldn't we reuse them? Perhaps it's overkill, and perhaps it will
reintroduce the 'transposed' problem?
Yes, good point, one could replace the
X.shape =
Hi Ralf,
I am pleased to announce the availability of the second release
candidate of NumPy 1.6.0.
Compared to the first release candidate, one segfault on (32-bit
Windows + MSVC) and several memory leaks were fixed. If no new
problems are reported, the final release will be in one week.
Hi Emmanuelle,
a, b, c = np.array([10]), np.array([2]), np.array([7])
min_val = np.minimum(a, b, c)
min_val
array([2])
max_val = np.maximum(a, b, c)
max_val
array([10])
min_val
array([10])
(I'm using numpy 1.4, and I observed the same behavior with numpy
2.0.0.dev8600 on another
Hi Bruce,
I think that I have resolved my issue down to creating a structured
string array.
I am using numpy version '2.0.0.dev-3c338cb'.
Without a structured array, it should be a 2 by 2 array:
np.array([('a','b'),('c','d')])
array([['a', 'b'],
['c', 'd']],
dtype='|S1')
On 4 Apr 2011, at 21:41, Darren Dale wrote:
Just tried again with python3.2 and 1.6.0b2, installs fine. The line
it fails on is only reached when a numpy/version.py exists, which is
the case for source releases or if you did not clean your local git
repo before building.
... but I think
Hi all,
On 4 Apr 2011, at 22:04, Ralf Gommers wrote:
I am pleased to announce the availability of the second beta of NumPy
1.6.0. Due to the extensive changes in the Numpy core for this
release, the beta testing phase will last at least one month. Please
test this beta and report any
On 31 Mar 2011, at 17:03, Bruce Southey wrote:
This is an invalid ticket because the docstring clearly states that in
3 different, yet critical places, that missing values are not handled
here:
Each row in the text file must have the same number of values.
genfromtxt : Load data with
On 30 Mar 2011, at 23:26, Benjamin Root wrote:
Ticket 301: 'Make power and divide return floats from int inputs (like
true_divide)'
http://projects.scipy.org/numpy/ticket/301
Invalid because the output dtype is the same as the input dtype unless
you override using the dtype argument:
Hi,
On 30 Mar 2011, at 21:37, Bruce Southey wrote:
Ticket 1071: 'loadtxt fails if the last column contains empty value'
http://projects.scipy.org/numpy/ticket/1071
Invalid mainly because loadtxt states that 'Each row in the text file
must have the same number of values.' So of cause loadtxt
Hi,
On 26 Mar 2011, at 14:36, Pauli Virtanen wrote:
On Sat, 26 Mar 2011 13:11:46 +0100, Paul Anton Letnes wrote:
[clip]
I hope you find this useful! Is there some way of submitting the
patches
for review in a more convenient fashion than e-mail?
You can attach them on the trac to each
Hi again,
On 26 Mar 2011, at 15:20, Derek Homeier wrote:
1562:
I attach a possible patch. This could also be the default
behavior to my mind, since the function caller can simply call
numpy.squeeze if needed. Changing default behavior would probably
break old code,
Seems the fastest
Hi Paul,
having had a look at the other tickets you dug up,
My opinions are my own, and in detail, they are:
1752:
I attach a possible patch. FWIW, I agree with the request. The
patch is written to be compatible with the fix in ticket #1562, but
I did not test that yet.
Tested, see
In a numpy array of m x n size, I would like to delete few rows when
a given element in that row is ‘nan’ or say any other value.
For e.g. as in example given below, if I wish to delete a row when
the 3rd element of row is zero, or if 3rd, 4th, 5th element are zero
or either of 3rd,
On 24.03.2011, at 9:11AM, Pearu Peterson wrote:
Intel-64bit:
ERROR: test_assumed_shape.TestAssumedShapeSumExample.test_all
--
Traceback (most recent call last):
File /sw/lib/python3.2/site-packages/nose/case.py, line 372,
Hi Bruce,
Sorry as I should I have paid more attention to you first email as I
raised this on the numpy list. (At least with gmail, the reply is to
the
scipy-dev list rather than the numpy list.)
Based on Pauli's answer I got around it by commenting out a line in
the
setup.py file
Hi again,
On 23 Mar 2011, at 17:07, Ralf Gommers wrote:
I am pleased to announce the availability of the first beta of NumPy
1.6.0. Due to the extensive changes in the Numpy core for this
release, the beta testing phase will last at least one month. Please
test this beta and report any
On 24 Mar 2011, at 00:34, Derek Homeier wrote:
tests with the fink-installed pythons on MacOS X mostly succeeded,
with one failure in python2.4 and a couple of issues seemingly
related to PPC floating point accuracy, as below:
Probably last update for tonight: with the 'full' test suite
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