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thouis opened this issue Oct 19, 2012 · 4 comments
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Building Numpy / Scipy on AIX system (Trac #1419) #2017

thouis opened this issue Oct 19, 2012 · 4 comments
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00 - Bug component: numpy.distutils

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@thouis
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thouis commented Oct 19, 2012

Original ticket http://projects.scipy.org/numpy/ticket/1419 on 2010-03-02 by trac user A_LARAS, assigned to unknown.

Hi,[[BR]]
I wounder if somebody have success to build Numpy/Scipy on AIX system with any of the IBM compilers (XLC, XLF) or Gnu gcc, g++[[BR]]
I have lot of issues make it installed on AIX 5.3, 64 bits machine[[BR]]

vac 8.0[[BR]]
xlf 10.1[[BR]]
gcc-4.2.4-2[[BR]]
AIX 5.3[[BR]]
@numpy-gitbot numpy-gitbot mentioned this issue Oct 23, 2012
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trac user gdrapala wrote on 2010-05-28

I was able to build numpy on AIX 5.3 with gcc using a gcc-compiled version of Python 2.6. Initially, I needed to learn to mind the CC and CXX environment variables as they take precedence over the values in /path/to/python/lib/python2.X/config/Makefile. Then gcc had a problem linking the math library by default (ERROR: Undefined symbol: .exp), so I set CC="gcc -pthread -lm", for lack of a more general solution. Next, I edited the same Makefile to change Modules/python.exp to a full path, and the ld_so_aix file to modify the second CCOPT line to be:

CCOPT="$CCOPT -Wl,-bM:SRE -Wl,-T512 -Wl,-H512 -Wl,-brtl -Wl,-bnortllib -lm -lbsd -o $objfile"

Finally, see numpy issue #2093. Hope that helps.

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@rgommers wrote on 2011-03-25

@A_LARAS: Did those instructions help you out?

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Milestone changed to Unscheduled by @rgommers on 2011-03-30

certik pushed a commit to certik/numpy that referenced this issue Nov 14, 2012
@cournape @charris
BUG: ticket numpy#2017, fix type hash.
89d6d41 
This is a squashed backport of 4 commits.
STY: cleanup hashdesc.c to follow our C conventions.

BUG: fix inconsistencies in dtype flag type at the C level.

Conflicts:

	numpy/core/src/multiarray/descriptor.c
	numpy/core/src/multiarray/hashdescr.c

BUG: fix numpy#2017 by ignoring type_num in the hash input.

Since type_num is not considered in PyArray_EquivTypes (for dtype
equality comparison), seems reasonable to ignore it for hashing as
well.

Conflicts:

	numpy/core/tests/test_dtype.py

BUG: fix flags type when exposed to python.
@cournape cournape mentioned this issue May 3, 2013
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charris commented Feb 19, 2014

Closing this. If an AIX wants to update things, open another ticket.

@charris charris closed this as completed Feb 19, 2014
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Fix dtype int vs char inconsistencies + dtype hashing cournape/numpy
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