Hi, I have installed numpy but the unit tests fail. When I ran them, I got Traceback (most recent call last): File "/home/jhtu/local/lib/python2.7/site-packages/numpy/testing/ decorators.py", line 215, in knownfailer return f(*args, **kwargs) File "/home/jhtu/local/lib/python2.7/site-packages/numpy/core/tests/ test_umath_complex.py", line 312, in test_special_values assert_almost_equal(np.log(np.conj(xa[i])), np.conj(np.log(xa[i]))) File "/home/jhtu/local/lib/python2.7/site-packages/numpy/testing/ utils.py", line 443, in assert_almost_equal raise AssertionError(msg) AssertionError: Arrays are not almost equal ACTUAL: array([-inf+3.14159265j]) DESIRED: array([-inf-3.14159265j]) This was with numpy built against MKL. To install I modified site.cfg to read [mkl] library_dirs = /opt/intel/mkl/10.2.4.032/lib/em64t include_dirs = /opt/intel/mkl/10.2.4.032/include lapack_libs = mkl_lapack mkl_libs = mkl_intel_lp64, mkl_intel_thread, mkl_core My cluster is using Intel Xeon processors, and I edited cc_exe as follows cc_exe = 'icc -O2 -fPIC' I installed using python setup.py config --compiler=intel build_clib --compiler=intel build_ext --compiler=intel install --prefix=/home/jhtu/local Jonathan Tu On Jan 18, 2011, at 3:39 PM, Ilan Schnell wrote:
The MKL configuration looks right, except that I had to use: mkl_libs = mkl_intel_lp64, mkl_intel_thread, mkl_core, iomp5
During the build process, it should tell you what it is linking aginast. Look at the compiler options passed to icc.
- Ilan
On Tue, Jan 18, 2011 at 2:31 PM, Jonathan Tu <jhtu@princeton.edu> wrote:
Hi,
I realized that my cluster has MKL installed. I've been trying to install against MKL, but am having trouble getting this to work. After it finishes, I do
import numpy numpy.show_config()
and nothing about the MKL libraries shows up. I have edited site.cfg to read like this:
[mkl] library_dirs = /opt/intel/mkl/10.2.4.032/lib/em64t include_dirs = /opt/intel/mkl/10.2.4.032/include lapack_libs = mkl_lapack mkl_libs = mkl, guide
My cluster is using Intel Xeon processors, and I edited cc_exe as follows
cc_exe = 'icc -O2 -fPIC'
Then I did
python setup.py config --compiler=intel build_clib --compiler=intel build_ext --compiler=intel install --prefix=/home/jhtu/local
Jonathan Tu
On Jan 18, 2011, at 3:28 PM, Ilan Schnell wrote:
Hello Jonathan,
yes, numpy work fine under Python 2.7 now. I don't see why building numpy against the system ATLAS should not work, as long as you install the developer version with the header files, and make sure that you edit the site.cfg file correct.
- Ilan
On Tue, Jan 18, 2011 at 10:39 AM, Jonathan Tu <jhtu@princeton.edu> wrote:
Hi,
I need to reinstall numpy because the cluster I am using was recently overhauled. I am wondering if numpy works with Python 2.7 now.
Also, I would like numpy to run as fast as possible. The last time I did this, I was advised to install ATLAS by hand, as the one that comes with RHEL is not suitable. The first time I tried this, I kept running into problems that I think were due to mismatched fortran compilers. Is there a good resource for how to do this? I am fairly new to Linux.
Thanks,
Jonathan Tu _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
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