Yes, they all are present in that directory. Also, I tried with root as login.
-r-xr-xr-x 1 root root 26342559 Aug 9 22:19 libmkl_avx.so
-r--r--r-- 1 root root 1190224 Aug 9 22:26 libmkl_blacs_ilp64.a
-r--r--r-- 1 root root 1191496 Aug 9 22:25 libmkl_blacs_intelmpi_ilp64.a
-r-xr-xr-x 1
It seems you are missing libiomp5.so, which is sound if you re using the
whole Composer package: the needed libs are split in two different
locations, and unfortunately, Numpy cannot cope with this last time I
checked (I think it was one of the reasons David Cournapeau created numscons
and bento).
My bad, iomp5md is in compiler/lib dir, I copied it to the mkl dir and it
worked.
From: Igor Ying igor.y...@yahoo.com
To: numpy-discussion@scipy.org numpy-discussion@scipy.org
Sent: Wednesday, September 14, 2011 1:07 PM
Subject: Re: Numpy - MKL - build error
Dear list,
I'm encountering a problem with np.loadtxt.
Suppose i have a file containing three columns of data (and 10 rows), like:
0.001 0.003 0.005
0.001 0.003 0.006
0.002 0.004 0.002
0.004 0.002 0.007
0.001 0.003 0.006
0.002 0.004 0.002
0.004 0.002 0.007
0.001 0.003 0.006
0.002 0.004 0.002
ERROR: test_polyfit (test_polynomial.TestDocs)
--
Traceback (most recent call last):
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/lib/tests/test_polynomial.py,
line 106, in test_polyfit
weights =
On Wed, Sep 14, 2011 at 10:45 PM, Samuel John sc...@samueljohn.de wrote:
Hi Nils,
which version of numpy, which os?
Latest master. Due to https://github.com/numpy/numpy/commit/af22fc43
Travis, did you run the test suite? arange is used but not imported.
Ralf
I can infer that you use
On Wed, Sep 14, 2011 at 2:45 PM, Samuel John sc...@samueljohn.de wrote:
Hi Nils,
which version of numpy, which os?
I can infer that you use python 2.6 in 64bit, right?
Right after the beginning of the numpy.test() are some crucial information.
bests
Samuel
On 14.09.2011, at 22:09,
On 9/14/11 1:01 PM, Christopher Barker wrote:
numpy.ndarray.resize is a different method, and I'm pretty sure it
should be as fast or faster that np.empty + np.append.
My profile:
In [25]: %timeit f1 # numpy.resize()
1000 loops, best of 3: 163 ns per loop
In [26]: %timeit f2
On Wed, Sep 14, 2011 at 4:25 PM, Christopher Barker
chris.bar...@noaa.govwrote:
On 9/14/11 1:01 PM, Christopher Barker wrote:
numpy.ndarray.resize is a different method, and I'm pretty sure it
should be as fast or faster that np.empty + np.append.
My profile:
In [25]: %timeit f1 #
On 9/14/11 2:41 PM, Benjamin Root wrote:
Are you sure the f2 code works? a.resize() takes only a shape tuple. As
coded, you should get an exception.
wow, what an idiot!
I think I just timed how long it takes to raise that exception...
And when I fix that, I get a memory error.
When I fix
On Wed, Sep 14, 2011 at 5:30 PM, Christopher Barker
chris.bar...@noaa.gov wrote:
On 9/14/11 2:41 PM, Benjamin Root wrote:
Are you sure the f2 code works? a.resize() takes only a shape tuple. As
coded, you should get an exception.
wow, what an idiot!
I think I just timed how long it takes
Hi all,
There were some failures in the polynomial tests earlier today, and
while investigating I saw that numpy.ma implements its own root
finder. It uses inversion of a Van der Monde matrix, which I believe
may suffer from some numerical instability problems. Given that
Charles has gone to
Hi all,
Has there been a discussion of a 1.7.x release of NumPy? There are a few
new features that should go into the 1.x release of NumPy, that don't require
the ABI changes of 2.0.I thought I had heard Mark talk in support of such a
thing.
What are the plans for the release of
On Thu, Sep 15, 2011 at 5:32 AM, Travis Oliphant teoliph...@gmail.comwrote:
Hi all,
Has there been a discussion of a 1.7.x release of NumPy? There are a
few new features that should go into the 1.x release of NumPy, that don't
require the ABI changes of 2.0.I thought I had heard Mark
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