On Wed, 1 Mar 2006, Christian Kristukat wrote:

You could also try to force to use gfortran like this:

python setup.py config_fc --fcompiler=g95 build

g95 is not gfortran. One should use python setup.py config_fc --fcompiler=gnu95 build for forcing gfortran. Pearu

Christian Kristukat wrote:

Christian Kristukat wrote:

...

instructions for ATLAS on the wiki building scipy _is_ straightforward. You won't need any additional information, even building ATLAS with full is covered

Sorry, this should read: "... ATLAS with full LAPACK..."

Christian

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Hi all, After compiling ATLAS umpteen times :'( I was able to install numpy and scipy. numpy.test(1,10) passed while scipy.test(1,10) check_y_stride (scipy.linalg.tests.test_fblas.test_zswap) ... ok check_algebraic_log_weight (scipy.integrate.tests.test_quadpack.test_quad) ... ok check_cauchypv_weight (scipy.integrate.tests.test_quadpack.test_quad) ... ok check_cosine_weighted_infinite (scipy.integrate.tests.test_quadpack.test_quad)STOP 778 Any idea ? Nils

Christian Kristukat wrote:

Nils Wagner wrote:

...

Hi all,

It seems to me that installing numpy/scipy on SuSE10.0 is not straightforward in contrast to prior versions.

If I remove compat-g77 and try to rebuild numpy from scratch the ifc is used. I thought that gfortran will be used in that case. Am I missing something ?

Anyway

python setup.py build results in

ld: skipping incompatible build/temp.linux-x86_64-2.4/libfblas_src.a when searching for -lfblas_src ld: cannot find -lfblas_src ld: skipping incompatible build/temp.linux-x86_64-2.4/libfblas_src.a when searching for -lfblas_src ld: cannot find -lfblas_src error: Command "/opt2/intel/compiler70/ia32/bin/ifc -shared build/temp.linux-x86_64-2.4/numpy/core/blasdot/_dotblas.o -Lbuild/temp.linux-x86_64-2.4 -lfblas_src -o build/lib.linux-x86_64-2.4/numpy/core/_dotblas.so" failed with exit status 1

Nils

Is there someone on the list who has successfully installed numpy/scipy with or without ATLAS using SuSE 10.0 ?

Yes, me (again). Maybe this is a processor issue, but for an Intel P4, I only can repeat: if you have installed gcc4/gfortran and no other compiler, following the installation instructions for ATLAS on the wiki building scipy _is_ straightforward. You won't need any additional information, even building ATLAS with full is covered there.

You could also try to force to use gfortran like this:

python setup.py config_fc --fcompiler=g95 build

Regards, Christian

ps: I can provide numpy/scipy rpms for SuSE10 with ATLAS built on that processor:

vendor_id : GenuineIntel cpu family : 15 model : 4 model name : Intel(R) Pentium(R) 4 CPU 3.00GHz stepping : 1 cpu MHz : 3007.387 cache size : 1024 KB physical id : 0 siblings : 2 core id : 0 cpu cores : 1 fdiv_bug : no hlt_bug : no f00f_bug : no coma_bug : no fpu : yes fpu_exception : yes cpuid level : 5 wp : yes flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe pni monitor ds_cpl cid xtpr bogomips : 6019.80

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Just in the case of a processor issue ... processor : 0 vendor_id : AuthenticAMD cpu family : 15 model : 47 model name : AMD Athlon(tm) 64 Processor 3200+ stepping : 2 cpu MHz : 2000.141 cache size : 512 KB fpu : yes fpu_exception : yes cpuid level : 1 wp : yes flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 syscall nx mmxext fxsr_opt lm 3dnowext 3dnow pni lahf_lm bogomips : 4009.73 TLB size : 1024 4K pages clflush size : 64 cache_alignment : 64 address sizes : 40 bits physical, 48 bits virtual power management: ts fid vid ttp tm stc Nils