Re: [Numpy-discussion] svn test failures: linalg with complex

Pauli Virtanen wrote: > Sat, 18 Apr 2009 13:19:39 -1000, Eric Firing wrote: > [clip] >> This is a real pain. What is the simplest work-around? > > apt-get install libatlas3gf-base > export LD_LIBRARY_PATH=/usr/lib/atlas > > Or, just uninstall libatlas3gf-sse2 in favor of the *-base version. >

Re: [Numpy-discussion] svn test failures: linalg with complex

Sat, 18 Apr 2009 13:19:39 -1000, Eric Firing wrote: [clip] > This is a real pain. What is the simplest work-around? apt-get install libatlas3gf-base export LD_LIBRARY_PATH=/usr/lib/atlas Or, just uninstall libatlas3gf-sse2 in favor of the *-base version. -- Pauli Virtanen

[Numpy-discussion] building 64bit

Hi, I'm trying to build scipy 64bit binaries. I'm on OS10.5.6, and using python2.6 built as 64bit universal from macports. When I run: python2.6 setup.py install the build doesn't fail along the way. However, when I then go into python and try something, e.g. "from scipy import linalg", I

Re: [Numpy-discussion] svn test failures: linalg with complex

Pauli Virtanen wrote: > Sat, 18 Apr 2009 09:41:28 -1000, Eric Firing wrote: > >> I updated my Thinkpad to Ubuntu 9.04 release candidate, 32-bit, got a >> fresh svn checkout of numpy trunk, built, and installed. Running >> numpy.test() yields 16 errors (output attached) in linear algebra on >> com

Re: [Numpy-discussion] svn test failures: linalg with complex

Sat, 18 Apr 2009 09:41:28 -1000, Eric Firing wrote: > I updated my Thinkpad to Ubuntu 9.04 release candidate, 32-bit, got a > fresh svn checkout of numpy trunk, built, and installed. Running > numpy.test() yields 16 errors (output attached) in linear algebra on > complex arguments. Is this expec

Re: [Numpy-discussion] svn test failures: linalg with complex

Charles R Harris wrote: On Sat, Apr 18, 2009 at 1:41 PM, Eric Firing > wrote: I updated my Thinkpad to Ubuntu 9.04 release candidate, 32-bit, got a fresh svn checkout of numpy trunk, built, and installed. Running numpy.test() yields 16 errors (output at

[Numpy-discussion] Buildbot unavailable

Hi, buildbot.scipy.org says: Service Temporarily Unavailable The server is temporarily unable to service your request due to maintenance downtime or capacity problems. Please try again later. -- Pauli Virtanen ___ Numpy-disc

Re: [Numpy-discussion] svn test failures: linalg with complex

On Sat, Apr 18, 2009 at 1:41 PM, Eric Firing wrote: > I updated my Thinkpad to Ubuntu 9.04 release candidate, 32-bit, got a fresh > svn checkout of numpy trunk, built, and installed. Running numpy.test() > yields 16 errors (output attached) in linear algebra on complex arguments. > Is this expe

[Numpy-discussion] svn test failures: linalg with complex

I updated my Thinkpad to Ubuntu 9.04 release candidate, 32-bit, got a fresh svn checkout of numpy trunk, built, and installed. Running numpy.test() yields 16 errors (output attached) in linear algebra on complex arguments. Is this expected? Eric In [2]:numpy.test() Running unit tests for nu

Re: [Numpy-discussion] Struct alignment

On Sat, Apr 18, 2009 at 10:36 PM, Dag Sverre Seljebotn wrote: > I'm looking at fixing up support for NumPy record arrays in Cython, and > realize my knowledge of NumPy is a bit too limited. Searching the docs > didn't enlighten me, so: > > Does NumPy always use packed alignment for nested dtypes?

Re: [Numpy-discussion] does numpy/scipy have solver for Ax=b, L_inf (Chebyshev norm)?

On Sat, Apr 18, 2009 at 4:29 AM, dmitrey wrote: > Hi all, > does numpy/scipy, or maybe wrapper for a lapack routine have solver > for Ax=b, L_inf (Chebyshev norm, i.e. max |Ax-b| -> min)? If there are > several ones, which ones are most suitable for large-scale, maybe ill- > conditioned problems?

[Numpy-discussion] Struct alignment

I'm looking at fixing up support for NumPy record arrays in Cython, and realize my knowledge of NumPy is a bit too limited. Searching the docs didn't enlighten me, so: Does NumPy always use packed alignment for nested dtypes? In [35]: T Out[35]: dtype([('f0', 'http://mail.scipy.org/mailman/list

Re: [Numpy-discussion] help with applying a transform

I think I've answered my own question - I remembered tensordot, and the following seems to work: def transform(tx_matrix, psi1, psi2): psi = np.tensordot(tx_matrix, np.concatenate((psi1[newaxis],psi2[newaxis])),axes=1)) return psi[0], psi[1] sorry for the noise, Gary Gary R

[Numpy-discussion] help with applying a transform

I'm trying to work out how to apply a 2x2 transform matrix to a spinor, e.g. [psi1'] [a b][psi1] [ ] = [][] [psi2'] [c d][psi2] where [[a,b],[c,d]] is a transform matrix and psi1 and psi2 are i x j x k complex arrays representing complex scalar field data. I worked that one way

[Numpy-discussion] does numpy/scipy have solver for Ax=b, L_inf (Chebyshev norm)?

Hi all, does numpy/scipy, or maybe wrapper for a lapack routine have solver for Ax=b, L_inf (Chebyshev norm, i.e. max |Ax-b| -> min)? If there are several ones, which ones are most suitable for large-scale, maybe ill- conditioned problems? Thank you in advance, D. P.S. Currently I 'm not interested

Re: [Numpy-discussion] Solving a memory leak in a numpy extension; PyArray_ContiguousFromObject

Dan S wrote: > Hi - > > I have written a numpy extension which works fine but has a memory > leak. It takes a single array argument and returns a single scalar. > After reducing the code down in order to chase the problem, I have the > following: > It does not answer your original question, but