From josef.pktd at gmail.com  Tue Jan  3 22:44:13 2012
From: josef.pktd at gmail.com (josef.pktd at gmail.com)
Date: Tue, 3 Jan 2012 22:44:13 -0500
Subject: [SciPy-User] splines again - a menagerie ?
Message-ID: <CAMMTP+D1cZ4O6Ax6FWNeKF6x6_zOwAW2POLewfJFdRbBT_h+Hg@mail.gmail.com>

I did a bit of a literature search on splines, mainly to get some
overview on its use in statistics.

There are quite a few different versions of splines and I don't have
too much of an idea which is which.

Does anyone now a good reference that gives an overview of different
splines? (So far I only know b-splines since they are in scipy.)

I don't really want to get into the gory details of splines, but I
would like to have a collection of basis functions for different
splines, similar to the polynomials vander functions that Chuck added
or is adding in numpy.  Just something to feed to a (penalized) least
squares estimation.

semi-aside: I just saw for the first time a reference that uses a
polynomial up to a fixed order and then adds spline terms, which looks
like an interesting combination of polynomial and (piecewise) spline
fitting.


Thanks,

Josef


From travis at continuum.io  Wed Jan  4 00:35:22 2012
From: travis at continuum.io (Travis Oliphant)
Date: Tue, 3 Jan 2012 23:35:22 -0600
Subject: [SciPy-User] splines again - a menagerie ?
In-Reply-To: <CAMMTP+D1cZ4O6Ax6FWNeKF6x6_zOwAW2POLewfJFdRbBT_h+Hg@mail.gmail.com>
References: <CAMMTP+D1cZ4O6Ax6FWNeKF6x6_zOwAW2POLewfJFdRbBT_h+Hg@mail.gmail.com>
Message-ID: <9F5F6002-B5F9-49A3-8661-1FEE85102E64@continuum.io>


On Jan 3, 2012, at 9:44 PM, josef.pktd at gmail.com wrote:

> I did a bit of a literature search on splines, mainly to get some
> overview on its use in statistics.
> 
> There are quite a few different versions of splines and I don't have
> too much of an idea which is which.

> 
> Does anyone now a good reference that gives an overview of different
> splines? (So far I only know b-splines since they are in scipy.)

This book by De Boor is a standard.    http://books.google.com/books?printsec=frontcover&id=m0QDJvBI_ecC#v=onepage&q&f=false
I remember using it 5 years ago when I added some low-level spline-calculation pieces to interpolate.   

> 
> I don't really want to get into the gory details of splines, but I
> would like to have a collection of basis functions for different
> splines, similar to the polynomials vander functions that Chuck added
> or is adding in numpy.  Just something to feed to a (penalized) least
> squares estimation.
> 
> semi-aside: I just saw for the first time a reference that uses a
> polynomial up to a fixed order and then adds spline terms, which looks
> like an interesting combination of polynomial and (piecewise) spline
> fitting.
> 

That sounds interesting.     It sounds like fitting a general trend to the data and then using splines to fit the difference between the data and the "trend".   Do you have the reference handy? 

-Travis


> 
> Thanks,
> 
> Josef
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user

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From josef.pktd at gmail.com  Wed Jan  4 09:56:25 2012
From: josef.pktd at gmail.com (josef.pktd at gmail.com)
Date: Wed, 4 Jan 2012 09:56:25 -0500
Subject: [SciPy-User] splines again - a menagerie ?
In-Reply-To: <9F5F6002-B5F9-49A3-8661-1FEE85102E64@continuum.io>
References: <CAMMTP+D1cZ4O6Ax6FWNeKF6x6_zOwAW2POLewfJFdRbBT_h+Hg@mail.gmail.com>
	<9F5F6002-B5F9-49A3-8661-1FEE85102E64@continuum.io>
Message-ID: <CAMMTP+DcSaYCWk=PvtTM6srRA2QpTLvSoAfxC7yuGnTGjODDyw@mail.gmail.com>

On Wed, Jan 4, 2012 at 12:35 AM, Travis Oliphant <travis at continuum.io> wrote:
>
> On Jan 3, 2012, at 9:44 PM, josef.pktd at gmail.com wrote:
>
> I did a bit of a literature search on splines, mainly to get some
> overview on its use in statistics.
>
> There are quite a few different versions of splines and I don't have
> too much of an idea which is which.
>
>
>
> Does anyone now a good reference that gives an overview of different
> splines? (So far I only know b-splines since they are in scipy.)
>
>
> This book by De Boor is a standard.
> ?http://books.google.com/books?printsec=frontcover&id=m0QDJvBI_ecC#v=onepage&q&f=false
> I remember using it 5 years ago when I added some low-level
> spline-calculation pieces to interpolate.

Thanks, I'm going to look at it.

>
>
> I don't really want to get into the gory details of splines, but I
> would like to have a collection of basis functions for different
> splines, similar to the polynomials vander functions that Chuck added
> or is adding in numpy. ?Just something to feed to a (penalized) least
> squares estimation.
>
>
> semi-aside: I just saw for the first time a reference that uses a
> polynomial up to a fixed order and then adds spline terms, which looks
> like an interesting combination of polynomial and (piecewise) spline
> fitting.
>
>
> That sounds interesting. ? ? It sounds like fitting a general trend to the
> data and then using splines to fit the difference between the data and the
> "trend". ? Do you have the reference handy?

David Ruppert, ?Selecting the Number of Knots for Penalized Splines,?
Journal of Computational and Graphical Statistics 11, no. 4 (December
1, 2002): 735-757.

http://scholar.google.com/scholar?cluster=3369320305950511369&hl=en&as_sdt=0,5

I just skimmed it, they also refer to Hastie and Tibishirani which I
haven't looked at in a while.

Josef

>
> -Travis
>
>
>
> Thanks,
>
> Josef
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user
>
>
>
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user
>


From chianshin at gmail.com  Wed Jan  4 23:16:18 2012
From: chianshin at gmail.com (Qian Xin)
Date: Wed, 4 Jan 2012 20:16:18 -0800 (PST)
Subject: [SciPy-User] why pythonw works python not working?
Message-ID: <1aeff9fb-2a36-444b-b257-6eadb0a4a98b@o14g2000vbo.googlegroups.com>

$ /c/Python26/python.exe draw.py
Traceback (most recent call last):
  File "draw.py", line 2, in <module>
    import matplotlib.pyplot as plt
  File "C:\Python26\lib\site-packages\matplotlib\pyplot.py", line 23,
in <module>
    from matplotlib.figure import Figure, figaspect
  File "C:\Python26\lib\site-packages\matplotlib\figure.py", line 18,
in <module>
    from axes import Axes, SubplotBase, subplot_class_factory
  File "C:\Python26\lib\site-packages\matplotlib\axes.py", line 14, in
<module>
    import matplotlib.axis as maxis
  File "C:\Python26\lib\site-packages\matplotlib\axis.py", line 12, in
<module>
    import matplotlib.patches as mpatches
  File "C:\Python26\lib\site-packages\matplotlib\patches.py", line
1574, in <module>
    class BoxStyle(_Style):
  File "C:\Python26\lib\site-packages\matplotlib\patches.py", line
2027, in BoxStyle
    {"AvailableBoxstyles": _pprint_styles(_style_list)}
  File "C:\Python26\lib\site-packages\matplotlib\patches.py", line
1502, in _pprint_styles
    import inspect
  File "C:\Python26\lib\inspect.py", line 37, in <module>
    import dis
  File "C:\Users\Qian Xin\Documents\My Dropbox\MSN\gitPlace\py\diagram
\dis.py", line 8, in <module>
    import matplotlib.pyplot as plt
AttributeError: 'module' object has no attribute 'pyplot'


Qian Xin at QianXinT41 /cygdrive/c.../py/diagram
$ /c/Python26/pythonw.exe draw.py

Qian Xin at QianXinT41 /cygdrive/c.../py/diagram
$ cat draw.opy
cat: draw.opy: No such file or directory

Qian Xin at QianXinT41 /cygdrive/c...py/diagram
$ cat draw.py
import numpy as np
import matplotlib.pyplot as plt


From harpend at gmail.com  Fri Jan  6 12:12:43 2012
From: harpend at gmail.com (Henry Harpending)
Date: Fri, 6 Jan 2012 10:12:43 -0700
Subject: [SciPy-User] scipy.stats example code with numargs
Message-ID: <72993FA4-AA4B-4D7F-B596-A95B392D416D@gmail.com>

Examples of the use of distributions in scipy documentation start with with something like this:

>>> from scipy.stats import truncnorm
>>> numargs = truncnorm.numargs
>>> [ a, b ] = [0.9,] * numargs
>>> rv = truncnorm(a, b)

What does this do?  Why 0.9?  In this particular case it seems to make no sense: the standard normal truncated between 0.9 and 0.9.  Or am I way off base?

Thanks, Henry Harpending



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From jsseabold at gmail.com  Fri Jan  6 12:16:58 2012
From: jsseabold at gmail.com (Skipper Seabold)
Date: Fri, 6 Jan 2012 12:16:58 -0500
Subject: [SciPy-User] scipy.stats example code with numargs
In-Reply-To: <72993FA4-AA4B-4D7F-B596-A95B392D416D@gmail.com>
References: <72993FA4-AA4B-4D7F-B596-A95B392D416D@gmail.com>
Message-ID: <CAKF=Djv6qm3f9b8DmkdTRTjho+e-oKcypuVhy4izPRqpZ_hY9A@mail.gmail.com>

On Fri, Jan 6, 2012 at 12:12 PM, Henry Harpending <harpend at gmail.com> wrote:
> Examples of the use of distributions in scipy documentation start with with
> something like this:
>
>>>> from scipy.stats import truncnorm
>>>> numargs = truncnorm.numargs
>>>> [ a, b ] = [0.9,] * numargs
>>>> rv = truncnorm(a, b)
>
>
> What does this do? ?Why 0.9? ?In this particular case it seems to make no
> sense: the standard normal truncated between 0.9 and 0.9. ?Or am I way off
> base?
>

I believe that all the distribution documentation is based off a
template, and there are a few cases where it doesn't make any sense.
Your understanding is correct. That doesn't make any sense, and will
actually raise an error if you try to sample from rv.

Skipper


From josef.pktd at gmail.com  Fri Jan  6 12:17:57 2012
From: josef.pktd at gmail.com (josef.pktd at gmail.com)
Date: Fri, 6 Jan 2012 12:17:57 -0500
Subject: [SciPy-User] scipy.stats example code with numargs
In-Reply-To: <72993FA4-AA4B-4D7F-B596-A95B392D416D@gmail.com>
References: <72993FA4-AA4B-4D7F-B596-A95B392D416D@gmail.com>
Message-ID: <CAMMTP+CMNZZpWx3OSk8TkkA+7u1vTM1RyB3qhB3_Ku8ZKs9okw@mail.gmail.com>

On Fri, Jan 6, 2012 at 12:12 PM, Henry Harpending <harpend at gmail.com> wrote:
> Examples of the use of distributions in scipy documentation start with with
> something like this:
>
>>>> from scipy.stats import truncnorm
>>>> numargs = truncnorm.numargs
>>>> [ a, b ] = [0.9,] * numargs
>>>> rv = truncnorm(a, b)
>
>
> What does this do? ?Why 0.9? ?In this particular case it seems to make no
> sense: the standard normal truncated between 0.9 and 0.9. ?Or am I way off
> base?

You are correct that the numbers in this example don't make any sense
(unless a one-point distribution works).

The problem is that this part of the documentation is generically
generated for all or most distributions.
It is possible to overwrite the generic template but it hasn't been
done for most distributions.

Josef


>
> Thanks, Henry Harpending
>
>
>
>
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user
>


From ryanlists at gmail.com  Sat Jan  7 13:33:46 2012
From: ryanlists at gmail.com (Ryan Krauss)
Date: Sat, 7 Jan 2012 12:33:46 -0600
Subject: [SciPy-User] problem installing numpy from source
Message-ID: <CAAroWSbYXz3Gu7J7yPmPp8kX9J+mLT-uA92LN_U+d5ymgb2h8A@mail.gmail.com>

I haven't installed numpy from source in quite a while (the packages
for ubuntu have quite good for some time).  I am having an
embarrassingly difficult time installing 1.6 from source on my Ubuntu
machine running 10.04 LTS.

The build and install seem to go ok, but when I cd into the final
installation directory, I see the following:

ryan at ryan-hpdv4|12:29 PM|~$ cd /usr/local/lib/python2.6/dist-packages/numpy/
ryan at ryan-hpdv4|12:29 PM|numpy$ ls
add_newdocs.py   __config__.pyc  distutils  f2py
__init__.py   ma          numarray    setup.py        testing
add_newdocs.pyc  core            doc        fft
__init__.pyc  matlib.py   oldnumeric  setup.pyc       tests
compat           ctypeslib.py    dual.py    _import_tools.py   lib
      matlib.pyc  polynomial  setupscons.py   version.py
__config__.py    ctypeslib.pyc   dual.pyc   _import_tools.pyc  linalg
      matrixlib   random      setupscons.pyc  version.pyc
ryan at ryan-hpdv4|12:29 PM|numpy$ ls -alh *.py
-rw-r--r-- 1 root staff 189K 2011-07-20 13:25 add_newdocs.py
-rw-r--r-- 1 root staff 1.6K 2012-01-07 12:27 __config__.py
-rw-r--r-- 1 root staff  14K 2011-07-20 13:25 ctypeslib.py
-rw-r--r-- 1 root staff 1.8K 2011-07-20 13:25 dual.py
-rw-r--r-- 1 root staff  13K 2011-07-20 13:25 _import_tools.py
-rw-r--r-- 1 root staff 4.9K 2011-07-20 13:25 __init__.py
-rw-r--r-- 1 root staff 9.3K 2010-11-21 01:34 matlib.py
-rw-r--r-- 1 root staff  946 2010-11-21 01:34 setup.py
-rw-r--r-- 1 root staff 1.5K 2010-11-21 01:34 setupscons.py
-rw-r--r-- 1 root staff  228 2012-01-07 12:27 version.py

Does it make sense that __init__.py wasn't updated?  Should it not
exist anymore?  Should I have uninstalled the numpy pacakge from the
Ubuntu package manager first?

Thanks,

Ryan

Here is my site.cfg:

[DEFAULT]
library_dirs = /usr/lib
[blas_opt]
libraries = f77blas, cblas, atlas

[lapack_opt]
libraries = lapack, f77blas, cblas, atlas


and here is the output of the build command:
sudo python setup.py build --fcompiler=gnu95

I think it builds correctly, but I can't be sure:

ryan at ryan-hpdv4|12:19 PM|numpy-1.6.1$ sudo python setup.py build
--fcompiler=gnu95
Running from numpy source directory.F2PY Version 2
blas_opt_info:
blas_mkl_info:
  libraries mkl,vml,guide not found in /usr/lib
  NOT AVAILABLE

atlas_blas_threads_info:
Setting PTATLAS=ATLAS
  libraries ptf77blas,ptcblas,atlas not found in /usr/lib/atlas
  libraries ptf77blas,ptcblas,atlas not found in /usr/lib/sse
  libraries ptf77blas,ptcblas,atlas not found in /usr/lib/sse2
  libraries ptf77blas,ptcblas,atlas not found in /usr/lib
  NOT AVAILABLE

atlas_blas_info:
  libraries f77blas,cblas,atlas not found in /usr/lib/atlas
/home/ryan/Downloads/numpy-1.6.1/numpy/distutils/command/config.py:413:
DeprecationWarning:
+++++++++++++++++++++++++++++++++++++++++++++++++
Usage of get_output is deprecated: please do not
use it anymore, and avoid configuration checks
involving running executable on the target machine.
+++++++++++++++++++++++++++++++++++++++++++++++++

  DeprecationWarning)
customize GnuFCompiler
Could not locate executable g77
Could not locate executable f77
customize IntelFCompiler
Could not locate executable ifort
Could not locate executable ifc
customize LaheyFCompiler
Could not locate executable lf95
customize PGroupFCompiler
Could not locate executable pgf90
Could not locate executable pgf77
customize AbsoftFCompiler
Could not locate executable f90
customize NAGFCompiler
Found executable /usr/bin/f95
customize VastFCompiler
customize CompaqFCompiler
Could not locate executable fort
customize IntelItaniumFCompiler
Could not locate executable efort
Could not locate executable efc
customize IntelEM64TFCompiler
customize Gnu95FCompiler
Found executable /usr/bin/gfortran
customize Gnu95FCompiler
customize Gnu95FCompiler using config
compiling '_configtest.c':

/* This file is generated from numpy/distutils/system_info.py */
void ATL_buildinfo(void);
int main(void) {
  ATL_buildinfo();
  return 0;
}
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-c'
gcc: _configtest.c
gcc -pthread _configtest.o -L/usr/lib/sse -lf77blas -lcblas -latlas -o
_configtest
ATLAS version 3.6.0 built by root on Fri Jan  9 15:57:20 UTC 2004:
   UNAME    : Linux intech67 2.4.20 #1 SMP Fri Jan 10 18:29:51 EST
2003 i686 GNU/Linux
   INSTFLG  :
   MMDEF    : /fix/g/camm/atlas3-3.6.0/CONFIG/ARCHS/P4SSE2/gcc/gemm
   ARCHDEF  : /fix/g/camm/atlas3-3.6.0/CONFIG/ARCHS/P4SSE2/gcc/misc
   F2CDEFS  : -DAdd__ -DStringSunStyle
   CACHEEDGE: 1048576
   F77      : /usr/bin/g77, version GNU Fortran (GCC) 3.3.3 20031229
(prerelease) (Debian)
   F77FLAGS : -fomit-frame-pointer -O
   CC       : /usr/bin/gcc, version gcc (GCC) 3.3.3 20031229
(prerelease) (Debian)
   CC FLAGS : -fomit-frame-pointer -O3 -funroll-all-loops
   MCC      : /usr/bin/gcc, version gcc (GCC) 3.3.3 20031229
(prerelease) (Debian)
   MCCFLAGS : -fomit-frame-pointer -O
success!
removing: _configtest.c _configtest.o _configtest
  FOUND:
    libraries = ['f77blas', 'cblas', 'atlas']
    library_dirs = ['/usr/lib/sse']
    language = c
    define_macros = [('ATLAS_INFO', '"\\"3.6.0\\""')]
    include_dirs = ['/usr/include']

  FOUND:
    libraries = ['f77blas', 'cblas', 'atlas']
    library_dirs = ['/usr/lib/sse']
    language = c
    define_macros = [('ATLAS_INFO', '"\\"3.6.0\\""')]
    include_dirs = ['/usr/include']

lapack_opt_info:
lapack_mkl_info:
mkl_info:
  libraries mkl,vml,guide not found in /usr/lib
  NOT AVAILABLE

  NOT AVAILABLE

atlas_threads_info:
Setting PTATLAS=ATLAS
  libraries ptf77blas,ptcblas,atlas not found in /usr/lib/atlas
  libraries lapack_atlas not found in /usr/lib/atlas
  libraries ptf77blas,ptcblas,atlas not found in /usr/lib/sse
  libraries ptf77blas,ptcblas,atlas not found in /usr/lib/sse2
  libraries ptf77blas,ptcblas,atlas not found in /usr/lib
numpy.distutils.system_info.atlas_threads_info
  NOT AVAILABLE

atlas_info:
  libraries f77blas,cblas,atlas not found in /usr/lib/atlas
  libraries lapack_atlas not found in /usr/lib/atlas
  libraries lapack not found in /usr/lib/sse
numpy.distutils.system_info.atlas_info
  FOUND:
    libraries = ['lapack', 'f77blas', 'cblas', 'atlas']
    library_dirs = ['/usr/lib/sse/atlas', '/usr/lib/sse']
    language = f77
    define_macros = [('ATLAS_INFO', '"\\"3.6.0\\""')]
    include_dirs = ['/usr/include']

  FOUND:
    libraries = ['lapack', 'f77blas', 'cblas', 'atlas']
    library_dirs = ['/usr/lib/sse/atlas', '/usr/lib/sse']
    language = f77
    define_macros = [('ATLAS_INFO', '"\\"3.6.0\\""')]
    include_dirs = ['/usr/include']

running build
running config_cc
unifing config_cc, config, build_clib, build_ext, build commands
--compiler options
running config_fc
unifing config_fc, config, build_clib, build_ext, build commands
--fcompiler options
running build_src
build_src
building py_modules sources
creating build
creating build/src.linux-i686-2.6
creating build/src.linux-i686-2.6/numpy
creating build/src.linux-i686-2.6/numpy/distutils
building library "npymath" sources
customize Gnu95FCompiler
customize Gnu95FCompiler using config
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
gcc -pthread _configtest.o -o _configtest
success!
removing: _configtest.c _configtest.o _configtest
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:1: warning: conflicting types for built-in function ?exp?
gcc -pthread _configtest.o -o _configtest
_configtest.o: In function `main':
/home/ryan/Downloads/numpy-1.6.1/_configtest.c:6: undefined reference to `exp'
collect2: ld returned 1 exit status
_configtest.o: In function `main':
/home/ryan/Downloads/numpy-1.6.1/_configtest.c:6: undefined reference to `exp'
collect2: ld returned 1 exit status
failure.
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:1: warning: conflicting types for built-in function ?exp?
gcc -pthread _configtest.o -lm -o _configtest
success!
removing: _configtest.c _configtest.o _configtest
creating build/src.linux-i686-2.6/numpy/core
creating build/src.linux-i686-2.6/numpy/core/src
creating build/src.linux-i686-2.6/numpy/core/src/npymath
conv_template:> build/src.linux-i686-2.6/numpy/core/src/npymath/npy_math.c
conv_template:> build/src.linux-i686-2.6/numpy/core/src/npymath/ieee754.c
conv_template:>
build/src.linux-i686-2.6/numpy/core/src/npymath/npy_math_complex.c
building extension "numpy.core._sort" sources
Generating build/src.linux-i686-2.6/numpy/core/include/numpy/config.h
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:5: warning: function declaration isn?t a prototype
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:5: warning: function declaration isn?t a prototype
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:5: warning: function declaration isn?t a prototype
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:5: warning: function declaration isn?t a prototype
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o _configtest.c _configtest.o
_configtest.c _configtest.o _configtest.c _configtest.o _configtest.c
_configtest.o _configtest.c _configtest.o _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:5: warning: function declaration isn?t a prototype
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o _configtest.c _configtest.o
_configtest.c _configtest.o _configtest.c _configtest.o _configtest.c
_configtest.o _configtest.c _configtest.o _configtest.c _configtest.o
_configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:5: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:7: error: ?SIZEOF_LONGDOUBLE? undeclared (first use in
this function)
_configtest.c:7: error: (Each undeclared identifier is reported only once
_configtest.c:7: error: for each function it appears in.)
_configtest.c:5: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:7: error: ?SIZEOF_LONGDOUBLE? undeclared (first use in
this function)
_configtest.c:7: error: (Each undeclared identifier is reported only once
_configtest.c:7: error: for each function it appears in.)
failure.
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o _configtest.c _configtest.o
_configtest.c _configtest.o _configtest.c _configtest.o _configtest.c
_configtest.o _configtest.c _configtest.o _configtest.c _configtest.o
_configtest.c _configtest.o _configtest.c _configtest.o _configtest.c
_configtest.o _configtest.c _configtest.o _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:5: error: size of array ?test_array? is negative
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:6: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:6: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:5: warning: function declaration isn?t a prototype
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:6: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:6: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:5: warning: function declaration isn?t a prototype
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:1: warning: conflicting types for built-in function ?exp?
gcc -pthread _configtest.o -o _configtest
_configtest.o: In function `main':
/home/ryan/Downloads/numpy-1.6.1/_configtest.c:6: undefined reference to `exp'
collect2: ld returned 1 exit status
_configtest.o: In function `main':
/home/ryan/Downloads/numpy-1.6.1/_configtest.c:6: undefined reference to `exp'
collect2: ld returned 1 exit status
failure.
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:1: warning: conflicting types for built-in function ?exp?
gcc -pthread _configtest.o -lm -o _configtest
success!
removing: _configtest.c _configtest.o _configtest
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:1: warning: conflicting types for built-in function ?asin?
_configtest.c:2: warning: conflicting types for built-in function ?cos?
_configtest.c:3: warning: conflicting types for built-in function ?log?
_configtest.c:4: warning: conflicting types for built-in function ?fabs?
_configtest.c:5: warning: conflicting types for built-in function ?tanh?
_configtest.c:6: warning: conflicting types for built-in function ?atan?
_configtest.c:7: warning: conflicting types for built-in function ?acos?
_configtest.c:8: warning: conflicting types for built-in function ?floor?
_configtest.c:9: warning: conflicting types for built-in function ?fmod?
_configtest.c:10: warning: conflicting types for built-in function ?sqrt?
_configtest.c:11: warning: conflicting types for built-in function ?cosh?
_configtest.c:12: warning: conflicting types for built-in function ?modf?
_configtest.c:13: warning: conflicting types for built-in function ?sinh?
_configtest.c:14: warning: conflicting types for built-in function ?frexp?
_configtest.c:15: warning: conflicting types for built-in function ?exp?
_configtest.c:16: warning: conflicting types for built-in function ?tan?
_configtest.c:17: warning: conflicting types for built-in function ?ceil?
_configtest.c:18: warning: conflicting types for built-in function ?log10?
_configtest.c:19: warning: conflicting types for built-in function ?sin?
_configtest.c:20: warning: conflicting types for built-in function ?ldexp?
gcc -pthread _configtest.o -lm -o _configtest
success!
removing: _configtest.c _configtest.o _configtest
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:6: warning: function declaration isn?t a prototype
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:6: warning: function declaration isn?t a prototype
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:6: warning: function declaration isn?t a prototype
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:6: warning: function declaration isn?t a prototype
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:6: warning: function declaration isn?t a prototype
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:6: warning: function declaration isn?t a prototype
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:6: warning: function declaration isn?t a prototype
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:1: warning: conflicting types for built-in function ?log2?
_configtest.c:2: warning: conflicting types for built-in function ?pow?
_configtest.c:3: warning: conflicting types for built-in function ?exp2?
_configtest.c:4: warning: conflicting types for built-in function ?atan2?
_configtest.c:5: warning: conflicting types for built-in function ?rint?
_configtest.c:6: warning: conflicting types for built-in function ?nextafter?
_configtest.c:7: warning: conflicting types for built-in function ?trunc?
gcc -pthread _configtest.o -lm -o _configtest
success!
removing: _configtest.c _configtest.o _configtest
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:1: warning: conflicting types for built-in function ?cosf?
_configtest.c:2: warning: conflicting types for built-in function ?coshf?
_configtest.c:3: warning: conflicting types for built-in function ?rintf?
_configtest.c:4: warning: conflicting types for built-in function ?fabsf?
_configtest.c:5: warning: conflicting types for built-in function ?floorf?
_configtest.c:6: warning: conflicting types for built-in function ?nextafterf?
_configtest.c:7: warning: conflicting types for built-in function ?tanhf?
_configtest.c:8: warning: conflicting types for built-in function ?log10f?
_configtest.c:9: warning: conflicting types for built-in function ?logf?
_configtest.c:10: warning: conflicting types for built-in function ?sinhf?
_configtest.c:11: warning: conflicting types for built-in function ?acosf?
_configtest.c:12: warning: conflicting types for built-in function ?sqrtf?
_configtest.c:13: warning: conflicting types for built-in function ?ldexpf?
_configtest.c:14: warning: conflicting types for built-in function ?hypotf?
_configtest.c:15: warning: conflicting types for built-in function ?log2f?
_configtest.c:16: warning: conflicting types for built-in function ?exp2f?
_configtest.c:17: warning: conflicting types for built-in function ?atanf?
_configtest.c:18: warning: conflicting types for built-in function ?fmodf?
_configtest.c:19: warning: conflicting types for built-in function ?atan2f?
_configtest.c:20: warning: conflicting types for built-in function ?modff?
_configtest.c:21: warning: conflicting types for built-in function ?ceilf?
_configtest.c:22: warning: conflicting types for built-in function ?log1pf?
_configtest.c:23: warning: conflicting types for built-in function ?asinf?
_configtest.c:24: warning: conflicting types for built-in function ?copysignf?
_configtest.c:25: warning: conflicting types for built-in function ?acoshf?
_configtest.c:26: warning: conflicting types for built-in function ?sinf?
_configtest.c:27: warning: conflicting types for built-in function ?tanf?
_configtest.c:28: warning: conflicting types for built-in function ?atanhf?
_configtest.c:29: warning: conflicting types for built-in function ?truncf?
_configtest.c:30: warning: conflicting types for built-in function ?asinhf?
_configtest.c:31: warning: conflicting types for built-in function ?frexpf?
_configtest.c:32: warning: conflicting types for built-in function ?powf?
_configtest.c:33: warning: conflicting types for built-in function ?expf?
_configtest.c:34: warning: conflicting types for built-in function ?expm1f?
gcc -pthread _configtest.o -lm -o _configtest
success!
removing: _configtest.c _configtest.o _configtest
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:1: warning: conflicting types for built-in function ?tanhl?
_configtest.c:2: warning: conflicting types for built-in function ?log10l?
_configtest.c:3: warning: conflicting types for built-in function ?nextafterl?
_configtest.c:4: warning: conflicting types for built-in function ?coshl?
_configtest.c:5: warning: conflicting types for built-in function ?cosl?
_configtest.c:6: warning: conflicting types for built-in function ?floorl?
_configtest.c:7: warning: conflicting types for built-in function ?rintl?
_configtest.c:8: warning: conflicting types for built-in function ?fabsl?
_configtest.c:9: warning: conflicting types for built-in function ?acosl?
_configtest.c:10: warning: conflicting types for built-in function ?ldexpl?
_configtest.c:11: warning: conflicting types for built-in function ?sqrtl?
_configtest.c:12: warning: conflicting types for built-in function ?logl?
_configtest.c:13: warning: conflicting types for built-in function ?expm1l?
_configtest.c:14: warning: conflicting types for built-in function ?hypotl?
_configtest.c:15: warning: conflicting types for built-in function ?log2l?
_configtest.c:16: warning: conflicting types for built-in function ?copysignl?
_configtest.c:17: warning: conflicting types for built-in function ?exp2l?
_configtest.c:18: warning: conflicting types for built-in function ?atanl?
_configtest.c:19: warning: conflicting types for built-in function ?frexpl?
_configtest.c:20: warning: conflicting types for built-in function ?atan2l?
_configtest.c:21: warning: conflicting types for built-in function ?sinhl?
_configtest.c:22: warning: conflicting types for built-in function ?fmodl?
_configtest.c:23: warning: conflicting types for built-in function ?log1pl?
_configtest.c:24: warning: conflicting types for built-in function ?asinl?
_configtest.c:25: warning: conflicting types for built-in function ?ceill?
_configtest.c:26: warning: conflicting types for built-in function ?sinl?
_configtest.c:27: warning: conflicting types for built-in function ?acoshl?
_configtest.c:28: warning: conflicting types for built-in function ?atanhl?
_configtest.c:29: warning: conflicting types for built-in function ?tanl?
_configtest.c:30: warning: conflicting types for built-in function ?truncl?
_configtest.c:31: warning: conflicting types for built-in function ?powl?
_configtest.c:32: warning: conflicting types for built-in function ?expl?
_configtest.c:33: warning: conflicting types for built-in function ?modfl?
_configtest.c:34: warning: conflicting types for built-in function ?asinhl?
gcc -pthread _configtest.o -lm -o _configtest
success!
removing: _configtest.c _configtest.o _configtest
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:6: warning: function declaration isn?t a prototype
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:6: warning: function declaration isn?t a prototype
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:6: warning: function declaration isn?t a prototype
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:6: warning: function declaration isn?t a prototype
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:6: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:8: error: ?HAVE_DECL_SIGNBIT? undeclared (first use in
this function)
_configtest.c:8: error: (Each undeclared identifier is reported only once
_configtest.c:8: error: for each function it appears in.)
_configtest.c:6: warning: function declaration isn?t a prototype
_configtest.c: In function ?main?:
_configtest.c:8: error: ?HAVE_DECL_SIGNBIT? undeclared (first use in
this function)
_configtest.c:8: error: (Each undeclared identifier is reported only once
_configtest.c:8: error: for each function it appears in.)
failure.
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:6: warning: function declaration isn?t a prototype
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:6: warning: function declaration isn?t a prototype
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:6: warning: function declaration isn?t a prototype
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:1: warning: conflicting types for built-in function ?cexp?
_configtest.c:2: warning: conflicting types for built-in function ?clog?
_configtest.c:3: warning: conflicting types for built-in function ?ccos?
_configtest.c:4: warning: conflicting types for built-in function ?cimag?
_configtest.c:5: warning: conflicting types for built-in function ?cabs?
_configtest.c:6: warning: conflicting types for built-in function ?cpow?
_configtest.c:7: warning: conflicting types for built-in function ?csqrt?
_configtest.c:8: warning: conflicting types for built-in function ?carg?
_configtest.c:9: warning: conflicting types for built-in function ?creal?
_configtest.c:10: warning: conflicting types for built-in function ?csin?
gcc -pthread _configtest.o -lm -o _configtest
success!
removing: _configtest.c _configtest.o _configtest
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:1: warning: conflicting types for built-in function ?ccosf?
_configtest.c:2: warning: conflicting types for built-in function ?cargf?
_configtest.c:3: warning: conflicting types for built-in function ?csqrtf?
_configtest.c:4: warning: conflicting types for built-in function ?cpowf?
_configtest.c:5: warning: conflicting types for built-in function ?cexpf?
_configtest.c:6: warning: conflicting types for built-in function ?crealf?
_configtest.c:7: warning: conflicting types for built-in function ?csinf?
_configtest.c:8: warning: conflicting types for built-in function ?cabsf?
_configtest.c:9: warning: conflicting types for built-in function ?clogf?
_configtest.c:10: warning: conflicting types for built-in function ?cimagf?
gcc -pthread _configtest.o -lm -o _configtest
success!
removing: _configtest.c _configtest.o _configtest
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:1: warning: conflicting types for built-in function ?csqrtl?
_configtest.c:2: warning: conflicting types for built-in function ?cargl?
_configtest.c:3: warning: conflicting types for built-in function ?cexpl?
_configtest.c:4: warning: conflicting types for built-in function ?ccosl?
_configtest.c:5: warning: conflicting types for built-in function ?cpowl?
_configtest.c:6: warning: conflicting types for built-in function ?cimagl?
_configtest.c:7: warning: conflicting types for built-in function ?csinl?
_configtest.c:8: warning: conflicting types for built-in function ?creall?
_configtest.c:9: warning: conflicting types for built-in function ?clogl?
_configtest.c:10: warning: conflicting types for built-in function ?cabsl?
gcc -pthread _configtest.o -lm -o _configtest
success!
removing: _configtest.c _configtest.o _configtest
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:5: warning: function declaration isn?t a prototype
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
removing: _configtest.c _configtest.o
('File:', 'build/src.linux-i686-2.6/numpy/core/include/numpy/config.h')
#define HAVE_ENDIAN_H 1
#define SIZEOF_PY_INTPTR_T 4
#define SIZEOF_PY_LONG_LONG 8
#define MATHLIB m
#define HAVE_SIN
#define HAVE_COS
#define HAVE_TAN
#define HAVE_SINH
#define HAVE_COSH
#define HAVE_TANH
#define HAVE_FABS
#define HAVE_FLOOR
#define HAVE_CEIL
#define HAVE_SQRT
#define HAVE_LOG10
#define HAVE_LOG
#define HAVE_EXP
#define HAVE_ASIN
#define HAVE_ACOS
#define HAVE_ATAN
#define HAVE_FMOD
#define HAVE_MODF
#define HAVE_FREXP
#define HAVE_LDEXP
#define HAVE_RINT
#define HAVE_TRUNC
#define HAVE_EXP2
#define HAVE_LOG2
#define HAVE_ATAN2
#define HAVE_POW
#define HAVE_NEXTAFTER
#define HAVE_SINF
#define HAVE_COSF
#define HAVE_TANF
#define HAVE_SINHF
#define HAVE_COSHF
#define HAVE_TANHF
#define HAVE_FABSF
#define HAVE_FLOORF
#define HAVE_CEILF
#define HAVE_RINTF
#define HAVE_TRUNCF
#define HAVE_SQRTF
#define HAVE_LOG10F
#define HAVE_LOGF
#define HAVE_LOG1PF
#define HAVE_EXPF
#define HAVE_EXPM1F
#define HAVE_ASINF
#define HAVE_ACOSF
#define HAVE_ATANF
#define HAVE_ASINHF
#define HAVE_ACOSHF
#define HAVE_ATANHF
#define HAVE_HYPOTF
#define HAVE_ATAN2F
#define HAVE_POWF
#define HAVE_FMODF
#define HAVE_MODFF
#define HAVE_FREXPF
#define HAVE_LDEXPF
#define HAVE_EXP2F
#define HAVE_LOG2F
#define HAVE_COPYSIGNF
#define HAVE_NEXTAFTERF
#define HAVE_SINL
#define HAVE_COSL
#define HAVE_TANL
#define HAVE_SINHL
#define HAVE_COSHL
#define HAVE_TANHL
#define HAVE_FABSL
#define HAVE_FLOORL
#define HAVE_CEILL
#define HAVE_RINTL
#define HAVE_TRUNCL
#define HAVE_SQRTL
#define HAVE_LOG10L
#define HAVE_LOGL
#define HAVE_LOG1PL
#define HAVE_EXPL
#define HAVE_EXPM1L
#define HAVE_ASINL
#define HAVE_ACOSL
#define HAVE_ATANL
#define HAVE_ASINHL
#define HAVE_ACOSHL
#define HAVE_ATANHL
#define HAVE_HYPOTL
#define HAVE_ATAN2L
#define HAVE_POWL
#define HAVE_FMODL
#define HAVE_MODFL
#define HAVE_FREXPL
#define HAVE_LDEXPL
#define HAVE_EXP2L
#define HAVE_LOG2L
#define HAVE_COPYSIGNL
#define HAVE_NEXTAFTERL
#define HAVE_DECL_SIGNBIT
#define HAVE_COMPLEX_H
#define HAVE_CREAL
#define HAVE_CIMAG
#define HAVE_CABS
#define HAVE_CARG
#define HAVE_CEXP
#define HAVE_CSQRT
#define HAVE_CLOG
#define HAVE_CCOS
#define HAVE_CSIN
#define HAVE_CPOW
#define HAVE_CREALF
#define HAVE_CIMAGF
#define HAVE_CABSF
#define HAVE_CARGF
#define HAVE_CEXPF
#define HAVE_CSQRTF
#define HAVE_CLOGF
#define HAVE_CCOSF
#define HAVE_CSINF
#define HAVE_CPOWF
#define HAVE_CREALL
#define HAVE_CIMAGL
#define HAVE_CABSL
#define HAVE_CARGL
#define HAVE_CEXPL
#define HAVE_CSQRTL
#define HAVE_CLOGL
#define HAVE_CCOSL
#define HAVE_CSINL
#define HAVE_CPOWL
#define HAVE_LDOUBLE_INTEL_EXTENDED_12_BYTES_LE 1
#ifndef __cplusplus
/* #undef inline */
#endif

#ifndef _NPY_NPY_CONFIG_H_
#error config.h should never be included directly, include npy_config.h instead
#endif

EOF
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/config.h'
to sources.
Generating build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:1: warning: conflicting types for built-in function ?exp?
gcc -pthread _configtest.o -o _configtest
_configtest.o: In function `main':
/home/ryan/Downloads/numpy-1.6.1/_configtest.c:6: undefined reference to `exp'
collect2: ld returned 1 exit status
_configtest.o: In function `main':
/home/ryan/Downloads/numpy-1.6.1/_configtest.c:6: undefined reference to `exp'
collect2: ld returned 1 exit status
failure.
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:1: warning: conflicting types for built-in function ?exp?
gcc -pthread _configtest.o -lm -o _configtest
success!
removing: _configtest.c _configtest.o _configtest
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:5: warning: function declaration isn?t a prototype
success!
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:4: warning: function declaration isn?t a prototype
_configtest.c:5:18: warning: extra tokens at end of #ifndef directive
_configtest.c: In function ?main?:
_configtest.c:8: warning: control reaches end of non-void function
success!
removing: _configtest.c _configtest.o
File: build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h
#define NPY_HAVE_ENDIAN_H 1
#define NPY_SIZEOF_SHORT SIZEOF_SHORT
#define NPY_SIZEOF_INT SIZEOF_INT
#define NPY_SIZEOF_LONG SIZEOF_LONG
#define NPY_SIZEOF_FLOAT 4
#define NPY_SIZEOF_COMPLEX_FLOAT 8
#define NPY_SIZEOF_DOUBLE 8
#define NPY_SIZEOF_COMPLEX_DOUBLE 16
#define NPY_SIZEOF_LONGDOUBLE 12
#define NPY_SIZEOF_COMPLEX_LONGDOUBLE 24
#define NPY_SIZEOF_PY_INTPTR_T 4
#define NPY_SIZEOF_PY_LONG_LONG 8
#define NPY_SIZEOF_LONGLONG 8
#define NPY_NO_SMP 0
#define NPY_HAVE_DECL_ISNAN
#define NPY_HAVE_DECL_ISINF
#define NPY_HAVE_DECL_ISFINITE
#define NPY_HAVE_DECL_SIGNBIT
#define NPY_USE_C99_COMPLEX
#define NPY_HAVE_COMPLEX_DOUBLE 1
#define NPY_HAVE_COMPLEX_FLOAT 1
#define NPY_HAVE_COMPLEX_LONG_DOUBLE 1
#define NPY_USE_C99_FORMATS 1
#define NPY_VISIBILITY_HIDDEN __attribute__((visibility("hidden")))
#define NPY_ABI_VERSION 0x01000009
#define NPY_API_VERSION 0x00000006

#ifndef __STDC_FORMAT_MACROS
#define __STDC_FORMAT_MACROS 1
#endif

EOF
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h'
to sources.
executing numpy/core/code_generators/generate_numpy_api.py
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h'
to sources.
conv_template:> build/src.linux-i686-2.6/numpy/core/src/_sortmodule.c
numpy.core - nothing done with h_files =
['build/src.linux-i686-2.6/numpy/core/include/numpy/config.h',
'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h',
'build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h']
building extension "numpy.core.multiarray" sources
non-existing path in 'numpy/core':
'build/src.linux-i686-2.6/numpy/core/src/multiarray'
creating build/src.linux-i686-2.6/numpy/core/src/multiarray
conv_template:> build/src.linux-i686-2.6/numpy/core/src/multiarray/scalartypes.c
conv_template:> build/src.linux-i686-2.6/numpy/core/src/multiarray/arraytypes.c
conv_template:> build/src.linux-i686-2.6/numpy/core/src/multiarray/nditer.c
conv_template:>
build/src.linux-i686-2.6/numpy/core/src/multiarray/lowlevel_strided_loops.c
conv_template:> build/src.linux-i686-2.6/numpy/core/src/multiarray/einsum.c
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/config.h'
to sources.
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h'
to sources.
executing numpy/core/code_generators/generate_numpy_api.py
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h'
to sources.
numpy.core - nothing done with h_files =
['build/src.linux-i686-2.6/numpy/core/include/numpy/config.h',
'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h',
'build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h']
building extension "numpy.core.umath" sources
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/config.h'
to sources.
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h'
to sources.
executing numpy/core/code_generators/generate_ufunc_api.py
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/__ufunc_api.h'
to sources.
non-existing path in 'numpy/core':
'build/src.linux-i686-2.6/numpy/core/src/umath'
creating build/src.linux-i686-2.6/numpy/core/src/umath
conv_template:> build/src.linux-i686-2.6/numpy/core/src/umath/loops.c
conv_template:> build/src.linux-i686-2.6/numpy/core/src/umath/umathmodule.c
conv_template:> build/src.linux-i686-2.6/numpy/core/src/umath/funcs.inc
  adding 'build/src.linux-i686-2.6/numpy/core/src/umath' to include_dirs.
numpy.core - nothing done with h_files =
['build/src.linux-i686-2.6/numpy/core/src/umath/funcs.inc',
'build/src.linux-i686-2.6/numpy/core/include/numpy/config.h',
'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h',
'build/src.linux-i686-2.6/numpy/core/include/numpy/__ufunc_api.h']
building extension "numpy.core.scalarmath" sources
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/config.h'
to sources.
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h'
to sources.
executing numpy/core/code_generators/generate_numpy_api.py
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h'
to sources.
executing numpy/core/code_generators/generate_ufunc_api.py
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/__ufunc_api.h'
to sources.
conv_template:> build/src.linux-i686-2.6/numpy/core/src/scalarmathmodule.c
numpy.core - nothing done with h_files =
['build/src.linux-i686-2.6/numpy/core/include/numpy/config.h',
'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h',
'build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h',
'build/src.linux-i686-2.6/numpy/core/include/numpy/__ufunc_api.h']
building extension "numpy.core._dotblas" sources
  adding 'numpy/core/blasdot/_dotblas.c' to sources.
building extension "numpy.core.umath_tests" sources
conv_template:> build/src.linux-i686-2.6/numpy/core/src/umath/umath_tests.c
building extension "numpy.core.multiarray_tests" sources
conv_template:>
build/src.linux-i686-2.6/numpy/core/src/multiarray/multiarray_tests.c
building extension "numpy.lib._compiled_base" sources
building extension "numpy.numarray._capi" sources
building extension "numpy.fft.fftpack_lite" sources
building extension "numpy.linalg.lapack_lite" sources
creating build/src.linux-i686-2.6/numpy/linalg
  adding 'numpy/linalg/lapack_litemodule.c' to sources.
  adding 'numpy/linalg/python_xerbla.c' to sources.
building extension "numpy.random.mtrand" sources
creating build/src.linux-i686-2.6/numpy/random
/home/ryan/Downloads/numpy-1.6.1/numpy/distutils/command/config.py:40:
DeprecationWarning:
+++++++++++++++++++++++++++++++++++++++++++++++++
Usage of try_run is deprecated: please do not
use it anymore, and avoid configuration checks
involving running executable on the target machine.
+++++++++++++++++++++++++++++++++++++++++++++++++

  DeprecationWarning)
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
gcc -pthread _configtest.o -o _configtest
_configtest
failure.
removing: _configtest.c _configtest.o _configtest
building data_files sources
build_src: building npy-pkg config files
running build_py
creating build/lib.linux-i686-2.6
creating build/lib.linux-i686-2.6/numpy
copying numpy/version.py -> build/lib.linux-i686-2.6/numpy
copying numpy/__init__.py -> build/lib.linux-i686-2.6/numpy
copying numpy/setupscons.py -> build/lib.linux-i686-2.6/numpy
copying numpy/setup.py -> build/lib.linux-i686-2.6/numpy
copying numpy/ctypeslib.py -> build/lib.linux-i686-2.6/numpy
copying numpy/dual.py -> build/lib.linux-i686-2.6/numpy
copying numpy/matlib.py -> build/lib.linux-i686-2.6/numpy
copying numpy/_import_tools.py -> build/lib.linux-i686-2.6/numpy
copying numpy/add_newdocs.py -> build/lib.linux-i686-2.6/numpy
copying build/src.linux-i686-2.6/numpy/__config__.py ->
build/lib.linux-i686-2.6/numpy
creating build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/cpuinfo.py -> build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/__init__.py -> build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/unixccompiler.py ->
build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/__version__.py ->
build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/setupscons.py ->
build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/exec_command.py ->
build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/setup.py -> build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/line_endings.py ->
build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/info.py -> build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/numpy_distribution.py ->
build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/environment.py ->
build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/misc_util.py -> build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/extension.py -> build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/ccompiler.py -> build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/intelccompiler.py ->
build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/interactive.py ->
build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/mingw32ccompiler.py ->
build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/system_info.py ->
build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/npy_pkg_config.py ->
build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/conv_template.py ->
build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/lib2def.py -> build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/from_template.py ->
build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/pathccompiler.py ->
build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/core.py -> build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/log.py -> build/lib.linux-i686-2.6/numpy/distutils
copying numpy/distutils/compat.py -> build/lib.linux-i686-2.6/numpy/distutils
copying build/src.linux-i686-2.6/numpy/distutils/__config__.py ->
build/lib.linux-i686-2.6/numpy/distutils
creating build/lib.linux-i686-2.6/numpy/distutils/command
copying numpy/distutils/command/install.py ->
build/lib.linux-i686-2.6/numpy/distutils/command
copying numpy/distutils/command/__init__.py ->
build/lib.linux-i686-2.6/numpy/distutils/command
copying numpy/distutils/command/build_py.py ->
build/lib.linux-i686-2.6/numpy/distutils/command
copying numpy/distutils/command/build_clib.py ->
build/lib.linux-i686-2.6/numpy/distutils/command
copying numpy/distutils/command/develop.py ->
build/lib.linux-i686-2.6/numpy/distutils/command
copying numpy/distutils/command/install_headers.py ->
build/lib.linux-i686-2.6/numpy/distutils/command
copying numpy/distutils/command/sdist.py ->
build/lib.linux-i686-2.6/numpy/distutils/command
copying numpy/distutils/command/build_src.py ->
build/lib.linux-i686-2.6/numpy/distutils/command
copying numpy/distutils/command/install_clib.py ->
build/lib.linux-i686-2.6/numpy/distutils/command
copying numpy/distutils/command/bdist_rpm.py ->
build/lib.linux-i686-2.6/numpy/distutils/command
copying numpy/distutils/command/build.py ->
build/lib.linux-i686-2.6/numpy/distutils/command
copying numpy/distutils/command/scons.py ->
build/lib.linux-i686-2.6/numpy/distutils/command
copying numpy/distutils/command/egg_info.py ->
build/lib.linux-i686-2.6/numpy/distutils/command
copying numpy/distutils/command/build_ext.py ->
build/lib.linux-i686-2.6/numpy/distutils/command
copying numpy/distutils/command/autodist.py ->
build/lib.linux-i686-2.6/numpy/distutils/command
copying numpy/distutils/command/install_data.py ->
build/lib.linux-i686-2.6/numpy/distutils/command
copying numpy/distutils/command/config_compiler.py ->
build/lib.linux-i686-2.6/numpy/distutils/command
copying numpy/distutils/command/build_scripts.py ->
build/lib.linux-i686-2.6/numpy/distutils/command
copying numpy/distutils/command/config.py ->
build/lib.linux-i686-2.6/numpy/distutils/command
creating build/lib.linux-i686-2.6/numpy/distutils/fcompiler
copying numpy/distutils/fcompiler/pathf95.py ->
build/lib.linux-i686-2.6/numpy/distutils/fcompiler
copying numpy/distutils/fcompiler/gnu.py ->
build/lib.linux-i686-2.6/numpy/distutils/fcompiler
copying numpy/distutils/fcompiler/sun.py ->
build/lib.linux-i686-2.6/numpy/distutils/fcompiler
copying numpy/distutils/fcompiler/absoft.py ->
build/lib.linux-i686-2.6/numpy/distutils/fcompiler
copying numpy/distutils/fcompiler/g95.py ->
build/lib.linux-i686-2.6/numpy/distutils/fcompiler
copying numpy/distutils/fcompiler/__init__.py ->
build/lib.linux-i686-2.6/numpy/distutils/fcompiler
copying numpy/distutils/fcompiler/none.py ->
build/lib.linux-i686-2.6/numpy/distutils/fcompiler
copying numpy/distutils/fcompiler/nag.py ->
build/lib.linux-i686-2.6/numpy/distutils/fcompiler
copying numpy/distutils/fcompiler/lahey.py ->
build/lib.linux-i686-2.6/numpy/distutils/fcompiler
copying numpy/distutils/fcompiler/ibm.py ->
build/lib.linux-i686-2.6/numpy/distutils/fcompiler
copying numpy/distutils/fcompiler/compaq.py ->
build/lib.linux-i686-2.6/numpy/distutils/fcompiler
copying numpy/distutils/fcompiler/mips.py ->
build/lib.linux-i686-2.6/numpy/distutils/fcompiler
copying numpy/distutils/fcompiler/hpux.py ->
build/lib.linux-i686-2.6/numpy/distutils/fcompiler
copying numpy/distutils/fcompiler/vast.py ->
build/lib.linux-i686-2.6/numpy/distutils/fcompiler
copying numpy/distutils/fcompiler/pg.py ->
build/lib.linux-i686-2.6/numpy/distutils/fcompiler
copying numpy/distutils/fcompiler/intel.py ->
build/lib.linux-i686-2.6/numpy/distutils/fcompiler
creating build/lib.linux-i686-2.6/numpy/testing
copying numpy/testing/decorators.py -> build/lib.linux-i686-2.6/numpy/testing
copying numpy/testing/__init__.py -> build/lib.linux-i686-2.6/numpy/testing
copying numpy/testing/setupscons.py -> build/lib.linux-i686-2.6/numpy/testing
copying numpy/testing/nulltester.py -> build/lib.linux-i686-2.6/numpy/testing
copying numpy/testing/setup.py -> build/lib.linux-i686-2.6/numpy/testing
copying numpy/testing/print_coercion_tables.py ->
build/lib.linux-i686-2.6/numpy/testing
copying numpy/testing/noseclasses.py -> build/lib.linux-i686-2.6/numpy/testing
copying numpy/testing/utils.py -> build/lib.linux-i686-2.6/numpy/testing
copying numpy/testing/nosetester.py -> build/lib.linux-i686-2.6/numpy/testing
copying numpy/testing/numpytest.py -> build/lib.linux-i686-2.6/numpy/testing
creating build/lib.linux-i686-2.6/numpy/f2py
copying numpy/f2py/__init__.py -> build/lib.linux-i686-2.6/numpy/f2py
copying numpy/f2py/rules.py -> build/lib.linux-i686-2.6/numpy/f2py
copying numpy/f2py/f2py_testing.py -> build/lib.linux-i686-2.6/numpy/f2py
copying numpy/f2py/__version__.py -> build/lib.linux-i686-2.6/numpy/f2py
copying numpy/f2py/setupscons.py -> build/lib.linux-i686-2.6/numpy/f2py
copying numpy/f2py/setup.py -> build/lib.linux-i686-2.6/numpy/f2py
copying numpy/f2py/auxfuncs.py -> build/lib.linux-i686-2.6/numpy/f2py
copying numpy/f2py/info.py -> build/lib.linux-i686-2.6/numpy/f2py
copying numpy/f2py/crackfortran.py -> build/lib.linux-i686-2.6/numpy/f2py
copying numpy/f2py/use_rules.py -> build/lib.linux-i686-2.6/numpy/f2py
copying numpy/f2py/func2subr.py -> build/lib.linux-i686-2.6/numpy/f2py
copying numpy/f2py/f2py2e.py -> build/lib.linux-i686-2.6/numpy/f2py
copying numpy/f2py/cb_rules.py -> build/lib.linux-i686-2.6/numpy/f2py
copying numpy/f2py/diagnose.py -> build/lib.linux-i686-2.6/numpy/f2py
copying numpy/f2py/capi_maps.py -> build/lib.linux-i686-2.6/numpy/f2py
copying numpy/f2py/f90mod_rules.py -> build/lib.linux-i686-2.6/numpy/f2py
copying numpy/f2py/cfuncs.py -> build/lib.linux-i686-2.6/numpy/f2py
copying numpy/f2py/common_rules.py -> build/lib.linux-i686-2.6/numpy/f2py
creating build/lib.linux-i686-2.6/numpy/core
copying numpy/core/setup_common.py -> build/lib.linux-i686-2.6/numpy/core
copying numpy/core/numerictypes.py -> build/lib.linux-i686-2.6/numpy/core
copying numpy/core/shape_base.py -> build/lib.linux-i686-2.6/numpy/core
copying numpy/core/numeric.py -> build/lib.linux-i686-2.6/numpy/core
copying numpy/core/__init__.py -> build/lib.linux-i686-2.6/numpy/core
copying numpy/core/_mx_datetime_parser.py -> build/lib.linux-i686-2.6/numpy/core
copying numpy/core/setupscons.py -> build/lib.linux-i686-2.6/numpy/core
copying numpy/core/setup.py -> build/lib.linux-i686-2.6/numpy/core
copying numpy/core/info.py -> build/lib.linux-i686-2.6/numpy/core
copying numpy/core/defchararray.py -> build/lib.linux-i686-2.6/numpy/core
copying numpy/core/function_base.py -> build/lib.linux-i686-2.6/numpy/core
copying numpy/core/fromnumeric.py -> build/lib.linux-i686-2.6/numpy/core
copying numpy/core/records.py -> build/lib.linux-i686-2.6/numpy/core
copying numpy/core/getlimits.py -> build/lib.linux-i686-2.6/numpy/core
copying numpy/core/_internal.py -> build/lib.linux-i686-2.6/numpy/core
copying numpy/core/scons_support.py -> build/lib.linux-i686-2.6/numpy/core
copying numpy/core/machar.py -> build/lib.linux-i686-2.6/numpy/core
copying numpy/core/memmap.py -> build/lib.linux-i686-2.6/numpy/core
copying numpy/core/arrayprint.py -> build/lib.linux-i686-2.6/numpy/core
copying numpy/core/code_generators/generate_numpy_api.py ->
build/lib.linux-i686-2.6/numpy/core
creating build/lib.linux-i686-2.6/numpy/lib
copying numpy/lib/shape_base.py -> build/lib.linux-i686-2.6/numpy/lib
copying numpy/lib/__init__.py -> build/lib.linux-i686-2.6/numpy/lib
copying numpy/lib/_datasource.py -> build/lib.linux-i686-2.6/numpy/lib
copying numpy/lib/setupscons.py -> build/lib.linux-i686-2.6/numpy/lib
copying numpy/lib/arraysetops.py -> build/lib.linux-i686-2.6/numpy/lib
copying numpy/lib/setup.py -> build/lib.linux-i686-2.6/numpy/lib
copying numpy/lib/info.py -> build/lib.linux-i686-2.6/numpy/lib
copying numpy/lib/format.py -> build/lib.linux-i686-2.6/numpy/lib
copying numpy/lib/arrayterator.py -> build/lib.linux-i686-2.6/numpy/lib
copying numpy/lib/user_array.py -> build/lib.linux-i686-2.6/numpy/lib
copying numpy/lib/_iotools.py -> build/lib.linux-i686-2.6/numpy/lib
copying numpy/lib/recfunctions.py -> build/lib.linux-i686-2.6/numpy/lib
copying numpy/lib/financial.py -> build/lib.linux-i686-2.6/numpy/lib
copying numpy/lib/function_base.py -> build/lib.linux-i686-2.6/numpy/lib
copying numpy/lib/ufunclike.py -> build/lib.linux-i686-2.6/numpy/lib
copying numpy/lib/scimath.py -> build/lib.linux-i686-2.6/numpy/lib
copying numpy/lib/twodim_base.py -> build/lib.linux-i686-2.6/numpy/lib
copying numpy/lib/index_tricks.py -> build/lib.linux-i686-2.6/numpy/lib
copying numpy/lib/polynomial.py -> build/lib.linux-i686-2.6/numpy/lib
copying numpy/lib/utils.py -> build/lib.linux-i686-2.6/numpy/lib
copying numpy/lib/stride_tricks.py -> build/lib.linux-i686-2.6/numpy/lib
copying numpy/lib/type_check.py -> build/lib.linux-i686-2.6/numpy/lib
copying numpy/lib/npyio.py -> build/lib.linux-i686-2.6/numpy/lib
creating build/lib.linux-i686-2.6/numpy/oldnumeric
copying numpy/oldnumeric/alter_code2.py ->
build/lib.linux-i686-2.6/numpy/oldnumeric
copying numpy/oldnumeric/typeconv.py ->
build/lib.linux-i686-2.6/numpy/oldnumeric
copying numpy/oldnumeric/__init__.py ->
build/lib.linux-i686-2.6/numpy/oldnumeric
copying numpy/oldnumeric/fft.py -> build/lib.linux-i686-2.6/numpy/oldnumeric
copying numpy/oldnumeric/setupscons.py ->
build/lib.linux-i686-2.6/numpy/oldnumeric
copying numpy/oldnumeric/setup.py -> build/lib.linux-i686-2.6/numpy/oldnumeric
copying numpy/oldnumeric/alter_code1.py ->
build/lib.linux-i686-2.6/numpy/oldnumeric
copying numpy/oldnumeric/arrayfns.py ->
build/lib.linux-i686-2.6/numpy/oldnumeric
copying numpy/oldnumeric/ufuncs.py -> build/lib.linux-i686-2.6/numpy/oldnumeric
copying numpy/oldnumeric/misc.py -> build/lib.linux-i686-2.6/numpy/oldnumeric
copying numpy/oldnumeric/user_array.py ->
build/lib.linux-i686-2.6/numpy/oldnumeric
copying numpy/oldnumeric/linear_algebra.py ->
build/lib.linux-i686-2.6/numpy/oldnumeric
copying numpy/oldnumeric/matrix.py -> build/lib.linux-i686-2.6/numpy/oldnumeric
copying numpy/oldnumeric/ma.py -> build/lib.linux-i686-2.6/numpy/oldnumeric
copying numpy/oldnumeric/functions.py ->
build/lib.linux-i686-2.6/numpy/oldnumeric
copying numpy/oldnumeric/random_array.py ->
build/lib.linux-i686-2.6/numpy/oldnumeric
copying numpy/oldnumeric/precision.py ->
build/lib.linux-i686-2.6/numpy/oldnumeric
copying numpy/oldnumeric/mlab.py -> build/lib.linux-i686-2.6/numpy/oldnumeric
copying numpy/oldnumeric/rng_stats.py ->
build/lib.linux-i686-2.6/numpy/oldnumeric
copying numpy/oldnumeric/rng.py -> build/lib.linux-i686-2.6/numpy/oldnumeric
copying numpy/oldnumeric/compat.py -> build/lib.linux-i686-2.6/numpy/oldnumeric
copying numpy/oldnumeric/fix_default_axis.py ->
build/lib.linux-i686-2.6/numpy/oldnumeric
copying numpy/oldnumeric/array_printer.py ->
build/lib.linux-i686-2.6/numpy/oldnumeric
creating build/lib.linux-i686-2.6/numpy/numarray
copying numpy/numarray/numerictypes.py ->
build/lib.linux-i686-2.6/numpy/numarray
copying numpy/numarray/alter_code2.py -> build/lib.linux-i686-2.6/numpy/numarray
copying numpy/numarray/nd_image.py -> build/lib.linux-i686-2.6/numpy/numarray
copying numpy/numarray/__init__.py -> build/lib.linux-i686-2.6/numpy/numarray
copying numpy/numarray/fft.py -> build/lib.linux-i686-2.6/numpy/numarray
copying numpy/numarray/setupscons.py -> build/lib.linux-i686-2.6/numpy/numarray
copying numpy/numarray/setup.py -> build/lib.linux-i686-2.6/numpy/numarray
copying numpy/numarray/alter_code1.py -> build/lib.linux-i686-2.6/numpy/numarray
copying numpy/numarray/ufuncs.py -> build/lib.linux-i686-2.6/numpy/numarray
copying numpy/numarray/linear_algebra.py ->
build/lib.linux-i686-2.6/numpy/numarray
copying numpy/numarray/matrix.py -> build/lib.linux-i686-2.6/numpy/numarray
copying numpy/numarray/ma.py -> build/lib.linux-i686-2.6/numpy/numarray
copying numpy/numarray/functions.py -> build/lib.linux-i686-2.6/numpy/numarray
copying numpy/numarray/convolve.py -> build/lib.linux-i686-2.6/numpy/numarray
copying numpy/numarray/image.py -> build/lib.linux-i686-2.6/numpy/numarray
copying numpy/numarray/random_array.py ->
build/lib.linux-i686-2.6/numpy/numarray
copying numpy/numarray/util.py -> build/lib.linux-i686-2.6/numpy/numarray
copying numpy/numarray/mlab.py -> build/lib.linux-i686-2.6/numpy/numarray
copying numpy/numarray/session.py -> build/lib.linux-i686-2.6/numpy/numarray
copying numpy/numarray/compat.py -> build/lib.linux-i686-2.6/numpy/numarray
creating build/lib.linux-i686-2.6/numpy/fft
copying numpy/fft/fftpack.py -> build/lib.linux-i686-2.6/numpy/fft
copying numpy/fft/__init__.py -> build/lib.linux-i686-2.6/numpy/fft
copying numpy/fft/setupscons.py -> build/lib.linux-i686-2.6/numpy/fft
copying numpy/fft/setup.py -> build/lib.linux-i686-2.6/numpy/fft
copying numpy/fft/info.py -> build/lib.linux-i686-2.6/numpy/fft
copying numpy/fft/helper.py -> build/lib.linux-i686-2.6/numpy/fft
creating build/lib.linux-i686-2.6/numpy/linalg
copying numpy/linalg/__init__.py -> build/lib.linux-i686-2.6/numpy/linalg
copying numpy/linalg/setupscons.py -> build/lib.linux-i686-2.6/numpy/linalg
copying numpy/linalg/setup.py -> build/lib.linux-i686-2.6/numpy/linalg
copying numpy/linalg/info.py -> build/lib.linux-i686-2.6/numpy/linalg
copying numpy/linalg/linalg.py -> build/lib.linux-i686-2.6/numpy/linalg
creating build/lib.linux-i686-2.6/numpy/random
copying numpy/random/__init__.py -> build/lib.linux-i686-2.6/numpy/random
copying numpy/random/setupscons.py -> build/lib.linux-i686-2.6/numpy/random
copying numpy/random/setup.py -> build/lib.linux-i686-2.6/numpy/random
copying numpy/random/info.py -> build/lib.linux-i686-2.6/numpy/random
creating build/lib.linux-i686-2.6/numpy/ma
copying numpy/ma/mrecords.py -> build/lib.linux-i686-2.6/numpy/ma
copying numpy/ma/extras.py -> build/lib.linux-i686-2.6/numpy/ma
copying numpy/ma/version.py -> build/lib.linux-i686-2.6/numpy/ma
copying numpy/ma/__init__.py -> build/lib.linux-i686-2.6/numpy/ma
copying numpy/ma/setupscons.py -> build/lib.linux-i686-2.6/numpy/ma
copying numpy/ma/setup.py -> build/lib.linux-i686-2.6/numpy/ma
copying numpy/ma/testutils.py -> build/lib.linux-i686-2.6/numpy/ma
copying numpy/ma/timer_comparison.py -> build/lib.linux-i686-2.6/numpy/ma
copying numpy/ma/bench.py -> build/lib.linux-i686-2.6/numpy/ma
copying numpy/ma/core.py -> build/lib.linux-i686-2.6/numpy/ma
creating build/lib.linux-i686-2.6/numpy/matrixlib
copying numpy/matrixlib/defmatrix.py -> build/lib.linux-i686-2.6/numpy/matrixlib
copying numpy/matrixlib/__init__.py -> build/lib.linux-i686-2.6/numpy/matrixlib
copying numpy/matrixlib/setupscons.py ->
build/lib.linux-i686-2.6/numpy/matrixlib
copying numpy/matrixlib/setup.py -> build/lib.linux-i686-2.6/numpy/matrixlib
creating build/lib.linux-i686-2.6/numpy/compat
copying numpy/compat/__init__.py -> build/lib.linux-i686-2.6/numpy/compat
copying numpy/compat/py3k.py -> build/lib.linux-i686-2.6/numpy/compat
copying numpy/compat/setupscons.py -> build/lib.linux-i686-2.6/numpy/compat
copying numpy/compat/setup.py -> build/lib.linux-i686-2.6/numpy/compat
copying numpy/compat/_inspect.py -> build/lib.linux-i686-2.6/numpy/compat
creating build/lib.linux-i686-2.6/numpy/polynomial
copying numpy/polynomial/legendre.py ->
build/lib.linux-i686-2.6/numpy/polynomial
copying numpy/polynomial/__init__.py ->
build/lib.linux-i686-2.6/numpy/polynomial
copying numpy/polynomial/hermite.py -> build/lib.linux-i686-2.6/numpy/polynomial
copying numpy/polynomial/polyutils.py ->
build/lib.linux-i686-2.6/numpy/polynomial
copying numpy/polynomial/setup.py -> build/lib.linux-i686-2.6/numpy/polynomial
copying numpy/polynomial/chebyshev.py ->
build/lib.linux-i686-2.6/numpy/polynomial
copying numpy/polynomial/polynomial.py ->
build/lib.linux-i686-2.6/numpy/polynomial
copying numpy/polynomial/hermite_e.py ->
build/lib.linux-i686-2.6/numpy/polynomial
copying numpy/polynomial/laguerre.py ->
build/lib.linux-i686-2.6/numpy/polynomial
copying numpy/polynomial/polytemplate.py ->
build/lib.linux-i686-2.6/numpy/polynomial
creating build/lib.linux-i686-2.6/numpy/doc
copying numpy/doc/__init__.py -> build/lib.linux-i686-2.6/numpy/doc
copying numpy/doc/methods_vs_functions.py -> build/lib.linux-i686-2.6/numpy/doc
copying numpy/doc/basics.py -> build/lib.linux-i686-2.6/numpy/doc
copying numpy/doc/creation.py -> build/lib.linux-i686-2.6/numpy/doc
copying numpy/doc/ufuncs.py -> build/lib.linux-i686-2.6/numpy/doc
copying numpy/doc/misc.py -> build/lib.linux-i686-2.6/numpy/doc
copying numpy/doc/indexing.py -> build/lib.linux-i686-2.6/numpy/doc
copying numpy/doc/byteswapping.py -> build/lib.linux-i686-2.6/numpy/doc
copying numpy/doc/performance.py -> build/lib.linux-i686-2.6/numpy/doc
copying numpy/doc/subclassing.py -> build/lib.linux-i686-2.6/numpy/doc
copying numpy/doc/io.py -> build/lib.linux-i686-2.6/numpy/doc
copying numpy/doc/broadcasting.py -> build/lib.linux-i686-2.6/numpy/doc
copying numpy/doc/internals.py -> build/lib.linux-i686-2.6/numpy/doc
copying numpy/doc/jargon.py -> build/lib.linux-i686-2.6/numpy/doc
copying numpy/doc/structured_arrays.py -> build/lib.linux-i686-2.6/numpy/doc
copying numpy/doc/constants.py -> build/lib.linux-i686-2.6/numpy/doc
copying numpy/doc/howtofind.py -> build/lib.linux-i686-2.6/numpy/doc
copying numpy/doc/glossary.py -> build/lib.linux-i686-2.6/numpy/doc
running build_clib
customize UnixCCompiler
customize UnixCCompiler using build_clib
building 'npymath' library
compiling C sources
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

creating build/temp.linux-i686-2.6
creating build/temp.linux-i686-2.6/build
creating build/temp.linux-i686-2.6/build/src.linux-i686-2.6
creating build/temp.linux-i686-2.6/build/src.linux-i686-2.6/numpy
creating build/temp.linux-i686-2.6/build/src.linux-i686-2.6/numpy/core
creating build/temp.linux-i686-2.6/build/src.linux-i686-2.6/numpy/core/src
creating build/temp.linux-i686-2.6/build/src.linux-i686-2.6/numpy/core/src/npymath
creating build/temp.linux-i686-2.6/numpy
creating build/temp.linux-i686-2.6/numpy/core
creating build/temp.linux-i686-2.6/numpy/core/src
creating build/temp.linux-i686-2.6/numpy/core/src/npymath
compile options: '-Inumpy/core/include
-Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
-Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
-Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
-Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
gcc: build/src.linux-i686-2.6/numpy/core/src/npymath/npy_math_complex.c
gcc: numpy/core/src/npymath/halffloat.c
gcc: build/src.linux-i686-2.6/numpy/core/src/npymath/npy_math.c
gcc: build/src.linux-i686-2.6/numpy/core/src/npymath/ieee754.c
ar: adding 4 object files to build/temp.linux-i686-2.6/libnpymath.a
running build_ext
customize UnixCCompiler
customize UnixCCompiler using build_ext
customize Gnu95FCompiler
customize Gnu95FCompiler using build_ext
building 'numpy.core._sort' extension
compiling C sources
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/include
-Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
-Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
-Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
-Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
gcc: build/src.linux-i686-2.6/numpy/core/src/_sortmodule.c
gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions
build/temp.linux-i686-2.6/build/src.linux-i686-2.6/numpy/core/src/_sortmodule.o
-Lbuild/temp.linux-i686-2.6 -lnpymath -lm -o
build/lib.linux-i686-2.6/numpy/core/_sort.so
building 'numpy.core.multiarray' extension
compiling C sources
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

creating build/temp.linux-i686-2.6/numpy/core/src/multiarray
compile options: '-Inumpy/core/include
-Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
-Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
-Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
-Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
gcc: numpy/core/src/multiarray/multiarraymodule_onefile.c
numpy/core/src/multiarray/mapping.c:74: warning: ?_array_ass_item?
defined but not used
build/src.linux-i686-2.6/numpy/core/include/numpy/__ufunc_api.h:226:
warning: ?_import_umath? defined but not used
gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions
build/temp.linux-i686-2.6/numpy/core/src/multiarray/multiarraymodule_onefile.o
-Lbuild/temp.linux-i686-2.6 -lnpymath -lm -o
build/lib.linux-i686-2.6/numpy/core/multiarray.so
building 'numpy.core.umath' extension
compiling C sources
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

creating build/temp.linux-i686-2.6/numpy/core/src/umath
compile options: '-Ibuild/src.linux-i686-2.6/numpy/core/src/umath
-Inumpy/core/include
-Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
-Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
-Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
-Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
gcc: numpy/core/src/umath/umathmodule_onefile.c
numpy/core/include/numpy/npy_3kcompat.h:391: warning:
?simple_capsule_dtor? defined but not used
numpy/core/src/umath/loops.c.src:1402: warning: ?FLOAT_ldexp_long?
defined but not used
numpy/core/src/umath/loops.c.src:1402: warning: ?DOUBLE_ldexp_long?
defined but not used
numpy/core/src/umath/loops.c.src:1402: warning:
?LONGDOUBLE_ldexp_long? defined but not used
numpy/core/src/umath/loops.c.src:1709: warning: ?HALF_ldexp_long?
defined but not used
numpy/core/src/private/lowlevel_strided_loops.h:36: warning:
?PyArray_FreeStridedTransferData? declared ?static? but never defined
numpy/core/src/private/lowlevel_strided_loops.h:43: warning:
?PyArray_CopyStridedTransferData? declared ?static? but never defined
numpy/core/src/private/lowlevel_strided_loops.h:63: warning:
?PyArray_GetStridedCopyFn? declared ?static? but never defined
numpy/core/src/private/lowlevel_strided_loops.h:77: warning:
?PyArray_GetStridedCopySwapFn? declared ?static? but never defined
numpy/core/src/private/lowlevel_strided_loops.h:91: warning:
?PyArray_GetStridedCopySwapPairFn? declared ?static? but never defined
numpy/core/src/private/lowlevel_strided_loops.h:105: warning:
?PyArray_GetStridedZeroPadCopyFn? declared ?static? but never defined
numpy/core/src/private/lowlevel_strided_loops.h:118: warning:
?PyArray_GetStridedNumericCastFn? declared ?static? but never defined
numpy/core/src/private/lowlevel_strided_loops.h:168: warning:
?PyArray_GetDTypeTransferFunction? declared ?static? but never defined
numpy/core/src/private/lowlevel_strided_loops.h:220: warning:
?PyArray_TransferNDimToStrided? declared ?static? but never defined
numpy/core/src/private/lowlevel_strided_loops.h:230: warning:
?PyArray_TransferStridedToNDim? declared ?static? but never defined
gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions
build/temp.linux-i686-2.6/numpy/core/src/umath/umathmodule_onefile.o
-Lbuild/temp.linux-i686-2.6 -lnpymath -lm -o
build/lib.linux-i686-2.6/numpy/core/umath.so
building 'numpy.core.scalarmath' extension
compiling C sources
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/include
-Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
-Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
-Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
-Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
gcc: build/src.linux-i686-2.6/numpy/core/src/scalarmathmodule.c
numpy/core/src/scalarmathmodule.c.src:1054: warning: function
declaration isn?t a prototype
numpy/core/include/numpy/npy_3kcompat.h:391: warning:
?simple_capsule_dtor? defined but not used
gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions
build/temp.linux-i686-2.6/build/src.linux-i686-2.6/numpy/core/src/scalarmathmodule.o
-Lbuild/temp.linux-i686-2.6 -lnpymath -lm -o
build/lib.linux-i686-2.6/numpy/core/scalarmath.so
building 'numpy.core._dotblas' extension
compiling C sources
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

creating build/temp.linux-i686-2.6/numpy/core/blasdot
compile options: '-DATLAS_INFO="\"3.6.0\"" -Inumpy/core/blasdot
-I/usr/include -Inumpy/core/include
-Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
-Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
-Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
-Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
gcc: numpy/core/blasdot/_dotblas.c
numpy/core/blasdot/_dotblas.c: In function ?dotblas_matrixproduct?:
numpy/core/blasdot/_dotblas.c:239: warning: comparison of distinct
pointer types lacks a cast
numpy/core/blasdot/_dotblas.c:257: warning: passing argument 3 of
?(struct PyObject * (*)(struct PyObject *, struct PyObject *, struct
PyArrayObject *))*(PyArray_API + 1120u)? from incompatible pointer
type
numpy/core/blasdot/_dotblas.c:257: note: expected ?struct
PyArrayObject *? but argument is of type ?struct PyObject *?
numpy/core/blasdot/_dotblas.c:292: warning: passing argument 3 of
?(struct PyObject * (*)(struct PyObject *, struct PyObject *, struct
PyArrayObject *))*(PyArray_API + 1120u)? from incompatible pointer
type
numpy/core/blasdot/_dotblas.c:292: note: expected ?struct
PyArrayObject *? but argument is of type ?struct PyObject *?
gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions
build/temp.linux-i686-2.6/numpy/core/blasdot/_dotblas.o -L/usr/lib/sse
-Lbuild/temp.linux-i686-2.6 -lf77blas -lcblas -latlas -o
build/lib.linux-i686-2.6/numpy/core/_dotblas.so
building 'numpy.core.umath_tests' extension
compiling C sources
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

creating build/temp.linux-i686-2.6/build/src.linux-i686-2.6/numpy/core/src/umath
compile options: '-Inumpy/core/include
-Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
-Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
-Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
-Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
gcc: build/src.linux-i686-2.6/numpy/core/src/umath/umath_tests.c
numpy/core/include/numpy/npy_3kcompat.h:391: warning:
?simple_capsule_dtor? defined but not used
gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions
build/temp.linux-i686-2.6/build/src.linux-i686-2.6/numpy/core/src/umath/umath_tests.o
-Lbuild/temp.linux-i686-2.6 -o
build/lib.linux-i686-2.6/numpy/core/umath_tests.so
building 'numpy.core.multiarray_tests' extension
compiling C sources
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

creating build/temp.linux-i686-2.6/build/src.linux-i686-2.6/numpy/core/src/multiarray
compile options: '-Inumpy/core/include
-Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
-Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
-Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
-Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
gcc: build/src.linux-i686-2.6/numpy/core/src/multiarray/multiarray_tests.c
numpy/core/include/numpy/npy_3kcompat.h:391: warning:
?simple_capsule_dtor? defined but not used
gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions
build/temp.linux-i686-2.6/build/src.linux-i686-2.6/numpy/core/src/multiarray/multiarray_tests.o
-Lbuild/temp.linux-i686-2.6 -o
build/lib.linux-i686-2.6/numpy/core/multiarray_tests.so
building 'numpy.lib._compiled_base' extension
compiling C sources
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

creating build/temp.linux-i686-2.6/numpy/lib
creating build/temp.linux-i686-2.6/numpy/lib/src
compile options: '-Inumpy/core/include
-Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
-Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
-Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
-Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
gcc: numpy/lib/src/_compiled_base.c
gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions
build/temp.linux-i686-2.6/numpy/lib/src/_compiled_base.o
-Lbuild/temp.linux-i686-2.6 -o
build/lib.linux-i686-2.6/numpy/lib/_compiled_base.so
building 'numpy.numarray._capi' extension
compiling C sources
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

creating build/temp.linux-i686-2.6/numpy/numarray
compile options: '-Inumpy/core/include
-Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
-Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
-Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
-Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
gcc: numpy/numarray/_capi.c
numpy/core/include/numpy/npy_3kcompat.h:391: warning:
?simple_capsule_dtor? defined but not used
gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions
build/temp.linux-i686-2.6/numpy/numarray/_capi.o
-Lbuild/temp.linux-i686-2.6 -o
build/lib.linux-i686-2.6/numpy/numarray/_capi.so
building 'numpy.fft.fftpack_lite' extension
compiling C sources
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

creating build/temp.linux-i686-2.6/numpy/fft
compile options: '-Inumpy/core/include
-Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
-Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
-Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
-Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
gcc: numpy/fft/fftpack_litemodule.c
gcc: numpy/fft/fftpack.c
gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions
build/temp.linux-i686-2.6/numpy/fft/fftpack_litemodule.o
build/temp.linux-i686-2.6/numpy/fft/fftpack.o
-Lbuild/temp.linux-i686-2.6 -o
build/lib.linux-i686-2.6/numpy/fft/fftpack_lite.so
building 'numpy.linalg.lapack_lite' extension
compiling C sources
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

creating build/temp.linux-i686-2.6/numpy/linalg
compile options: '-DATLAS_INFO="\"3.6.0\"" -I/usr/include
-Inumpy/core/include
-Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
-Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
-Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
-Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
gcc: numpy/linalg/lapack_litemodule.c
gcc: numpy/linalg/python_xerbla.c
/usr/bin/gfortran -Wall -Wall -shared
build/temp.linux-i686-2.6/numpy/linalg/lapack_litemodule.o
build/temp.linux-i686-2.6/numpy/linalg/python_xerbla.o
-L/usr/lib/sse/atlas -L/usr/lib/sse -Lbuild/temp.linux-i686-2.6
-llapack -lf77blas -lcblas -latlas -lgfortran -o
build/lib.linux-i686-2.6/numpy/linalg/lapack_lite.so
building 'numpy.random.mtrand' extension
compiling C sources
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

creating build/temp.linux-i686-2.6/numpy/random
creating build/temp.linux-i686-2.6/numpy/random/mtrand
compile options: '-Inumpy/core/include
-Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
-Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
-Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
-Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
gcc: numpy/random/mtrand/distributions.c
gcc: numpy/random/mtrand/initarray.c
gcc: numpy/random/mtrand/randomkit.c
gcc: numpy/random/mtrand/mtrand.c
gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions
build/temp.linux-i686-2.6/numpy/random/mtrand/mtrand.o
build/temp.linux-i686-2.6/numpy/random/mtrand/randomkit.o
build/temp.linux-i686-2.6/numpy/random/mtrand/initarray.o
build/temp.linux-i686-2.6/numpy/random/mtrand/distributions.o
-Lbuild/temp.linux-i686-2.6 -o
build/lib.linux-i686-2.6/numpy/random/mtrand.so
running scons
running build_scripts
creating build/scripts.linux-i686-2.6
Creating build/scripts.linux-i686-2.6/f2py
  adding 'build/scripts.linux-i686-2.6/f2py' to scripts
changing mode of build/scripts.linux-i686-2.6/f2py from 644 to 755
ryan at ryan-hpdv4|12:20 PM|numpy-1.6.1$


Here is the output of the install command:

ryan at ryan-hpdv4|12:27 PM|numpy-1.6.1$ sudo python setup.py install
Running from numpy source directory.F2PY Version 2
blas_opt_info:
blas_mkl_info:
  libraries mkl,vml,guide not found in /usr/lib
  NOT AVAILABLE

atlas_blas_threads_info:
Setting PTATLAS=ATLAS
  libraries ptf77blas,ptcblas,atlas not found in /usr/lib/atlas
  libraries ptf77blas,ptcblas,atlas not found in /usr/lib/sse
  libraries ptf77blas,ptcblas,atlas not found in /usr/lib/sse2
  libraries ptf77blas,ptcblas,atlas not found in /usr/lib
  NOT AVAILABLE

atlas_blas_info:
  libraries f77blas,cblas,atlas not found in /usr/lib/atlas
/home/ryan/Downloads/numpy-1.6.1/numpy/distutils/command/config.py:413:
DeprecationWarning:
+++++++++++++++++++++++++++++++++++++++++++++++++
Usage of get_output is deprecated: please do not
use it anymore, and avoid configuration checks
involving running executable on the target machine.
+++++++++++++++++++++++++++++++++++++++++++++++++

  DeprecationWarning)
customize GnuFCompiler
Could not locate executable g77
Could not locate executable f77
customize IntelFCompiler
Could not locate executable ifort
Could not locate executable ifc
customize LaheyFCompiler
Could not locate executable lf95
customize PGroupFCompiler
Could not locate executable pgf90
Could not locate executable pgf77
customize AbsoftFCompiler
Could not locate executable f90
customize NAGFCompiler
Found executable /usr/bin/f95
customize VastFCompiler
customize CompaqFCompiler
Could not locate executable fort
customize IntelItaniumFCompiler
Could not locate executable efort
Could not locate executable efc
customize IntelEM64TFCompiler
customize Gnu95FCompiler
Found executable /usr/bin/gfortran
customize Gnu95FCompiler
customize Gnu95FCompiler using config
compiling '_configtest.c':

/* This file is generated from numpy/distutils/system_info.py */
void ATL_buildinfo(void);
int main(void) {
  ATL_buildinfo();
  return 0;
}
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-c'
gcc: _configtest.c
gcc -pthread _configtest.o -L/usr/lib/sse -lf77blas -lcblas -latlas -o
_configtest
ATLAS version 3.6.0 built by root on Fri Jan  9 15:57:20 UTC 2004:
   UNAME    : Linux intech67 2.4.20 #1 SMP Fri Jan 10 18:29:51 EST
2003 i686 GNU/Linux
   INSTFLG  :
   MMDEF    : /fix/g/camm/atlas3-3.6.0/CONFIG/ARCHS/P4SSE2/gcc/gemm
   ARCHDEF  : /fix/g/camm/atlas3-3.6.0/CONFIG/ARCHS/P4SSE2/gcc/misc
   F2CDEFS  : -DAdd__ -DStringSunStyle
   CACHEEDGE: 1048576
   F77      : /usr/bin/g77, version GNU Fortran (GCC) 3.3.3 20031229
(prerelease) (Debian)
   F77FLAGS : -fomit-frame-pointer -O
   CC       : /usr/bin/gcc, version gcc (GCC) 3.3.3 20031229
(prerelease) (Debian)
   CC FLAGS : -fomit-frame-pointer -O3 -funroll-all-loops
   MCC      : /usr/bin/gcc, version gcc (GCC) 3.3.3 20031229
(prerelease) (Debian)
   MCCFLAGS : -fomit-frame-pointer -O
success!
removing: _configtest.c _configtest.o _configtest
  FOUND:
    libraries = ['f77blas', 'cblas', 'atlas']
    library_dirs = ['/usr/lib/sse']
    language = c
    define_macros = [('ATLAS_INFO', '"\\"3.6.0\\""')]
    include_dirs = ['/usr/include']

  FOUND:
    libraries = ['f77blas', 'cblas', 'atlas']
    library_dirs = ['/usr/lib/sse']
    language = c
    define_macros = [('ATLAS_INFO', '"\\"3.6.0\\""')]
    include_dirs = ['/usr/include']

lapack_opt_info:
lapack_mkl_info:
mkl_info:
  libraries mkl,vml,guide not found in /usr/lib
  NOT AVAILABLE

  NOT AVAILABLE

atlas_threads_info:
Setting PTATLAS=ATLAS
  libraries ptf77blas,ptcblas,atlas not found in /usr/lib/atlas
  libraries lapack_atlas not found in /usr/lib/atlas
  libraries ptf77blas,ptcblas,atlas not found in /usr/lib/sse
  libraries ptf77blas,ptcblas,atlas not found in /usr/lib/sse2
  libraries ptf77blas,ptcblas,atlas not found in /usr/lib
numpy.distutils.system_info.atlas_threads_info
  NOT AVAILABLE

atlas_info:
  libraries f77blas,cblas,atlas not found in /usr/lib/atlas
  libraries lapack_atlas not found in /usr/lib/atlas
  libraries lapack not found in /usr/lib/sse
numpy.distutils.system_info.atlas_info
  FOUND:
    libraries = ['lapack', 'f77blas', 'cblas', 'atlas']
    library_dirs = ['/usr/lib/sse/atlas', '/usr/lib/sse']
    language = f77
    define_macros = [('ATLAS_INFO', '"\\"3.6.0\\""')]
    include_dirs = ['/usr/include']

  FOUND:
    libraries = ['lapack', 'f77blas', 'cblas', 'atlas']
    library_dirs = ['/usr/lib/sse/atlas', '/usr/lib/sse']
    language = f77
    define_macros = [('ATLAS_INFO', '"\\"3.6.0\\""')]
    include_dirs = ['/usr/include']

running install
running build
running config_cc
unifing config_cc, config, build_clib, build_ext, build commands
--compiler options
running config_fc
unifing config_fc, config, build_clib, build_ext, build commands
--fcompiler options
running build_src
build_src
building py_modules sources
building library "npymath" sources
customize GnuFCompiler
customize IntelFCompiler
customize LaheyFCompiler
customize PGroupFCompiler
customize AbsoftFCompiler
customize NAGFCompiler
customize VastFCompiler
customize CompaqFCompiler
customize IntelItaniumFCompiler
customize IntelEM64TFCompiler
customize Gnu95FCompiler
customize Gnu95FCompiler
customize Gnu95FCompiler using config
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
gcc -pthread _configtest.o -o _configtest
success!
removing: _configtest.c _configtest.o _configtest
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:1: warning: conflicting types for built-in function ?exp?
gcc -pthread _configtest.o -o _configtest
_configtest.o: In function `main':
/home/ryan/Downloads/numpy-1.6.1/_configtest.c:6: undefined reference to `exp'
collect2: ld returned 1 exit status
_configtest.o: In function `main':
/home/ryan/Downloads/numpy-1.6.1/_configtest.c:6: undefined reference to `exp'
collect2: ld returned 1 exit status
failure.
removing: _configtest.c _configtest.o
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
_configtest.c:1: warning: conflicting types for built-in function ?exp?
gcc -pthread _configtest.o -lm -o _configtest
success!
removing: _configtest.c _configtest.o _configtest
building extension "numpy.core._sort" sources
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/config.h'
to sources.
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h'
to sources.
executing numpy/core/code_generators/generate_numpy_api.py
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h'
to sources.
numpy.core - nothing done with h_files =
['build/src.linux-i686-2.6/numpy/core/include/numpy/config.h',
'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h',
'build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h']
building extension "numpy.core.multiarray" sources
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/config.h'
to sources.
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h'
to sources.
executing numpy/core/code_generators/generate_numpy_api.py
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h'
to sources.
numpy.core - nothing done with h_files =
['build/src.linux-i686-2.6/numpy/core/include/numpy/config.h',
'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h',
'build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h']
building extension "numpy.core.umath" sources
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/config.h'
to sources.
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h'
to sources.
executing numpy/core/code_generators/generate_ufunc_api.py
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/__ufunc_api.h'
to sources.
  adding 'build/src.linux-i686-2.6/numpy/core/src/umath' to include_dirs.
numpy.core - nothing done with h_files =
['build/src.linux-i686-2.6/numpy/core/src/umath/funcs.inc',
'build/src.linux-i686-2.6/numpy/core/include/numpy/config.h',
'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h',
'build/src.linux-i686-2.6/numpy/core/include/numpy/__ufunc_api.h']
building extension "numpy.core.scalarmath" sources
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/config.h'
to sources.
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h'
to sources.
executing numpy/core/code_generators/generate_numpy_api.py
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h'
to sources.
executing numpy/core/code_generators/generate_ufunc_api.py
  adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/__ufunc_api.h'
to sources.
numpy.core - nothing done with h_files =
['build/src.linux-i686-2.6/numpy/core/include/numpy/config.h',
'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h',
'build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h',
'build/src.linux-i686-2.6/numpy/core/include/numpy/__ufunc_api.h']
building extension "numpy.core._dotblas" sources
  adding 'numpy/core/blasdot/_dotblas.c' to sources.
building extension "numpy.core.umath_tests" sources
building extension "numpy.core.multiarray_tests" sources
building extension "numpy.lib._compiled_base" sources
building extension "numpy.numarray._capi" sources
building extension "numpy.fft.fftpack_lite" sources
building extension "numpy.linalg.lapack_lite" sources
  adding 'numpy/linalg/lapack_litemodule.c' to sources.
  adding 'numpy/linalg/python_xerbla.c' to sources.
building extension "numpy.random.mtrand" sources
/home/ryan/Downloads/numpy-1.6.1/numpy/distutils/command/config.py:40:
DeprecationWarning:
+++++++++++++++++++++++++++++++++++++++++++++++++
Usage of try_run is deprecated: please do not
use it anymore, and avoid configuration checks
involving running executable on the target machine.
+++++++++++++++++++++++++++++++++++++++++++++++++

  DeprecationWarning)
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
-Wall -Wstrict-prototypes -fPIC

compile options: '-Inumpy/core/src/private -Inumpy/core/src
-Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
-Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
-c'
gcc: _configtest.c
gcc -pthread _configtest.o -o _configtest
_configtest
failure.
removing: _configtest.c _configtest.o _configtest
building data_files sources
build_src: building npy-pkg config files
running build_py
copying numpy/version.py -> build/lib.linux-i686-2.6/numpy
copying build/src.linux-i686-2.6/numpy/__config__.py ->
build/lib.linux-i686-2.6/numpy
copying build/src.linux-i686-2.6/numpy/distutils/__config__.py ->
build/lib.linux-i686-2.6/numpy/distutils
running build_clib
customize UnixCCompiler
customize UnixCCompiler using build_clib
running build_ext
customize UnixCCompiler
customize UnixCCompiler using build_ext
customize GnuFCompiler
customize IntelFCompiler
customize LaheyFCompiler
customize PGroupFCompiler
customize AbsoftFCompiler
customize NAGFCompiler
customize VastFCompiler
customize CompaqFCompiler
customize IntelItaniumFCompiler
customize IntelEM64TFCompiler
customize Gnu95FCompiler
customize Gnu95FCompiler
customize Gnu95FCompiler using build_ext
running scons
running build_scripts
  adding 'build/scripts.linux-i686-2.6/f2py' to scripts
running install_lib
copying build/lib.linux-i686-2.6/numpy/numarray/_capi.so ->
/usr/local/lib/python2.6/dist-packages/numpy/numarray
copying build/lib.linux-i686-2.6/numpy/version.py ->
/usr/local/lib/python2.6/dist-packages/numpy
copying build/lib.linux-i686-2.6/numpy/distutils/__config__.py ->
/usr/local/lib/python2.6/dist-packages/numpy/distutils
copying build/lib.linux-i686-2.6/numpy/__config__.py ->
/usr/local/lib/python2.6/dist-packages/numpy
copying build/lib.linux-i686-2.6/numpy/random/mtrand.so ->
/usr/local/lib/python2.6/dist-packages/numpy/random
copying build/lib.linux-i686-2.6/numpy/linalg/lapack_lite.so ->
/usr/local/lib/python2.6/dist-packages/numpy/linalg
copying build/lib.linux-i686-2.6/numpy/core/_dotblas.so ->
/usr/local/lib/python2.6/dist-packages/numpy/core
copying build/lib.linux-i686-2.6/numpy/core/umath.so ->
/usr/local/lib/python2.6/dist-packages/numpy/core
copying build/lib.linux-i686-2.6/numpy/core/_sort.so ->
/usr/local/lib/python2.6/dist-packages/numpy/core
copying build/lib.linux-i686-2.6/numpy/core/umath_tests.so ->
/usr/local/lib/python2.6/dist-packages/numpy/core
copying build/lib.linux-i686-2.6/numpy/core/multiarray.so ->
/usr/local/lib/python2.6/dist-packages/numpy/core
copying build/lib.linux-i686-2.6/numpy/core/multiarray_tests.so ->
/usr/local/lib/python2.6/dist-packages/numpy/core
copying build/lib.linux-i686-2.6/numpy/core/scalarmath.so ->
/usr/local/lib/python2.6/dist-packages/numpy/core
copying build/lib.linux-i686-2.6/numpy/lib/_compiled_base.so ->
/usr/local/lib/python2.6/dist-packages/numpy/lib
copying build/lib.linux-i686-2.6/numpy/fft/fftpack_lite.so ->
/usr/local/lib/python2.6/dist-packages/numpy/fft
byte-compiling /usr/local/lib/python2.6/dist-packages/numpy/version.py
to version.pyc
byte-compiling /usr/local/lib/python2.6/dist-packages/numpy/distutils/__config__.py
to __config__.pyc
byte-compiling /usr/local/lib/python2.6/dist-packages/numpy/__config__.py
to __config__.pyc
running install_scripts
copying build/scripts.linux-i686-2.6/f2py -> /usr/local/bin
changing mode of /usr/local/bin/f2py to 755
running install_data
copying build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h
-> /usr/local/lib/python2.6/dist-packages/numpy/core/include/numpy
copying build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h
-> /usr/local/lib/python2.6/dist-packages/numpy/core/include/numpy
copying build/src.linux-i686-2.6/numpy/core/include/numpy/multiarray_api.txt
-> /usr/local/lib/python2.6/dist-packages/numpy/core/include/numpy
copying build/src.linux-i686-2.6/numpy/core/include/numpy/__ufunc_api.h
-> /usr/local/lib/python2.6/dist-packages/numpy/core/include/numpy
copying build/src.linux-i686-2.6/numpy/core/include/numpy/ufunc_api.txt
-> /usr/local/lib/python2.6/dist-packages/numpy/core/include/numpy
copying build/src.linux-i686-2.6/numpy/core/lib/npy-pkg-config/npymath.ini
-> /usr/local/lib/python2.6/dist-packages/numpy/core/lib/npy-pkg-config
copying build/src.linux-i686-2.6/numpy/core/lib/npy-pkg-config/mlib.ini
-> /usr/local/lib/python2.6/dist-packages/numpy/core/lib/npy-pkg-config
running install_egg_info
Removing /usr/local/lib/python2.6/dist-packages/numpy-1.6.1.egg-info
Writing /usr/local/lib/python2.6/dist-packages/numpy-1.6.1.egg-info
running install_clib
copying build/temp.linux-i686-2.6/libnpymath.a ->
/usr/local/lib/python2.6/dist-packages/numpy/core/lib


Thanks,

Ryan


From ryanlists at gmail.com  Sat Jan  7 14:53:01 2012
From: ryanlists at gmail.com (Ryan Krauss)
Date: Sat, 7 Jan 2012 13:53:01 -0600
Subject: [SciPy-User] problem installing numpy from source
In-Reply-To: <CAAroWSbYXz3Gu7J7yPmPp8kX9J+mLT-uA92LN_U+d5ymgb2h8A@mail.gmail.com>
References: <CAAroWSbYXz3Gu7J7yPmPp8kX9J+mLT-uA92LN_U+d5ymgb2h8A@mail.gmail.com>
Message-ID: <CAAroWSY91vaUA2qApzf-BupjvepHLUM8-WYKnJ0roVs4W+6zWQ@mail.gmail.com>

I think removing the numpy 1.3 package from the ubuntu package
installer solved the problem.  I am not completely done testing, but
it seems to have worked.

On Sat, Jan 7, 2012 at 12:33 PM, Ryan Krauss <ryanlists at gmail.com> wrote:
> I haven't installed numpy from source in quite a while (the packages
> for ubuntu have quite good for some time). ?I am having an
> embarrassingly difficult time installing 1.6 from source on my Ubuntu
> machine running 10.04 LTS.
>
> The build and install seem to go ok, but when I cd into the final
> installation directory, I see the following:
>
> ryan at ryan-hpdv4|12:29 PM|~$ cd /usr/local/lib/python2.6/dist-packages/numpy/
> ryan at ryan-hpdv4|12:29 PM|numpy$ ls
> add_newdocs.py ? __config__.pyc ?distutils ?f2py
> __init__.py ? ma ? ? ? ? ?numarray ? ?setup.py ? ? ? ?testing
> add_newdocs.pyc ?core ? ? ? ? ? ?doc ? ? ? ?fft
> __init__.pyc ?matlib.py ? oldnumeric ?setup.pyc ? ? ? tests
> compat ? ? ? ? ? ctypeslib.py ? ?dual.py ? ?_import_tools.py ? lib
> ? ? ?matlib.pyc ?polynomial ?setupscons.py ? version.py
> __config__.py ? ?ctypeslib.pyc ? dual.pyc ? _import_tools.pyc ?linalg
> ? ? ?matrixlib ? random ? ? ?setupscons.pyc ?version.pyc
> ryan at ryan-hpdv4|12:29 PM|numpy$ ls -alh *.py
> -rw-r--r-- 1 root staff 189K 2011-07-20 13:25 add_newdocs.py
> -rw-r--r-- 1 root staff 1.6K 2012-01-07 12:27 __config__.py
> -rw-r--r-- 1 root staff ?14K 2011-07-20 13:25 ctypeslib.py
> -rw-r--r-- 1 root staff 1.8K 2011-07-20 13:25 dual.py
> -rw-r--r-- 1 root staff ?13K 2011-07-20 13:25 _import_tools.py
> -rw-r--r-- 1 root staff 4.9K 2011-07-20 13:25 __init__.py
> -rw-r--r-- 1 root staff 9.3K 2010-11-21 01:34 matlib.py
> -rw-r--r-- 1 root staff ?946 2010-11-21 01:34 setup.py
> -rw-r--r-- 1 root staff 1.5K 2010-11-21 01:34 setupscons.py
> -rw-r--r-- 1 root staff ?228 2012-01-07 12:27 version.py
>
> Does it make sense that __init__.py wasn't updated? ?Should it not
> exist anymore? ?Should I have uninstalled the numpy pacakge from the
> Ubuntu package manager first?
>
> Thanks,
>
> Ryan
>
> Here is my site.cfg:
>
> [DEFAULT]
> library_dirs = /usr/lib
> [blas_opt]
> libraries = f77blas, cblas, atlas
>
> [lapack_opt]
> libraries = lapack, f77blas, cblas, atlas
>
>
> and here is the output of the build command:
> sudo python setup.py build --fcompiler=gnu95
>
> I think it builds correctly, but I can't be sure:
>
> ryan at ryan-hpdv4|12:19 PM|numpy-1.6.1$ sudo python setup.py build
> --fcompiler=gnu95
> Running from numpy source directory.F2PY Version 2
> blas_opt_info:
> blas_mkl_info:
> ?libraries mkl,vml,guide not found in /usr/lib
> ?NOT AVAILABLE
>
> atlas_blas_threads_info:
> Setting PTATLAS=ATLAS
> ?libraries ptf77blas,ptcblas,atlas not found in /usr/lib/atlas
> ?libraries ptf77blas,ptcblas,atlas not found in /usr/lib/sse
> ?libraries ptf77blas,ptcblas,atlas not found in /usr/lib/sse2
> ?libraries ptf77blas,ptcblas,atlas not found in /usr/lib
> ?NOT AVAILABLE
>
> atlas_blas_info:
> ?libraries f77blas,cblas,atlas not found in /usr/lib/atlas
> /home/ryan/Downloads/numpy-1.6.1/numpy/distutils/command/config.py:413:
> DeprecationWarning:
> +++++++++++++++++++++++++++++++++++++++++++++++++
> Usage of get_output is deprecated: please do not
> use it anymore, and avoid configuration checks
> involving running executable on the target machine.
> +++++++++++++++++++++++++++++++++++++++++++++++++
>
> ?DeprecationWarning)
> customize GnuFCompiler
> Could not locate executable g77
> Could not locate executable f77
> customize IntelFCompiler
> Could not locate executable ifort
> Could not locate executable ifc
> customize LaheyFCompiler
> Could not locate executable lf95
> customize PGroupFCompiler
> Could not locate executable pgf90
> Could not locate executable pgf77
> customize AbsoftFCompiler
> Could not locate executable f90
> customize NAGFCompiler
> Found executable /usr/bin/f95
> customize VastFCompiler
> customize CompaqFCompiler
> Could not locate executable fort
> customize IntelItaniumFCompiler
> Could not locate executable efort
> Could not locate executable efc
> customize IntelEM64TFCompiler
> customize Gnu95FCompiler
> Found executable /usr/bin/gfortran
> customize Gnu95FCompiler
> customize Gnu95FCompiler using config
> compiling '_configtest.c':
>
> /* This file is generated from numpy/distutils/system_info.py */
> void ATL_buildinfo(void);
> int main(void) {
> ?ATL_buildinfo();
> ?return 0;
> }
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-c'
> gcc: _configtest.c
> gcc -pthread _configtest.o -L/usr/lib/sse -lf77blas -lcblas -latlas -o
> _configtest
> ATLAS version 3.6.0 built by root on Fri Jan ?9 15:57:20 UTC 2004:
> ? UNAME ? ?: Linux intech67 2.4.20 #1 SMP Fri Jan 10 18:29:51 EST
> 2003 i686 GNU/Linux
> ? INSTFLG ?:
> ? MMDEF ? ?: /fix/g/camm/atlas3-3.6.0/CONFIG/ARCHS/P4SSE2/gcc/gemm
> ? ARCHDEF ?: /fix/g/camm/atlas3-3.6.0/CONFIG/ARCHS/P4SSE2/gcc/misc
> ? F2CDEFS ?: -DAdd__ -DStringSunStyle
> ? CACHEEDGE: 1048576
> ? F77 ? ? ?: /usr/bin/g77, version GNU Fortran (GCC) 3.3.3 20031229
> (prerelease) (Debian)
> ? F77FLAGS : -fomit-frame-pointer -O
> ? CC ? ? ? : /usr/bin/gcc, version gcc (GCC) 3.3.3 20031229
> (prerelease) (Debian)
> ? CC FLAGS : -fomit-frame-pointer -O3 -funroll-all-loops
> ? MCC ? ? ?: /usr/bin/gcc, version gcc (GCC) 3.3.3 20031229
> (prerelease) (Debian)
> ? MCCFLAGS : -fomit-frame-pointer -O
> success!
> removing: _configtest.c _configtest.o _configtest
> ?FOUND:
> ? ?libraries = ['f77blas', 'cblas', 'atlas']
> ? ?library_dirs = ['/usr/lib/sse']
> ? ?language = c
> ? ?define_macros = [('ATLAS_INFO', '"\\"3.6.0\\""')]
> ? ?include_dirs = ['/usr/include']
>
> ?FOUND:
> ? ?libraries = ['f77blas', 'cblas', 'atlas']
> ? ?library_dirs = ['/usr/lib/sse']
> ? ?language = c
> ? ?define_macros = [('ATLAS_INFO', '"\\"3.6.0\\""')]
> ? ?include_dirs = ['/usr/include']
>
> lapack_opt_info:
> lapack_mkl_info:
> mkl_info:
> ?libraries mkl,vml,guide not found in /usr/lib
> ?NOT AVAILABLE
>
> ?NOT AVAILABLE
>
> atlas_threads_info:
> Setting PTATLAS=ATLAS
> ?libraries ptf77blas,ptcblas,atlas not found in /usr/lib/atlas
> ?libraries lapack_atlas not found in /usr/lib/atlas
> ?libraries ptf77blas,ptcblas,atlas not found in /usr/lib/sse
> ?libraries ptf77blas,ptcblas,atlas not found in /usr/lib/sse2
> ?libraries ptf77blas,ptcblas,atlas not found in /usr/lib
> numpy.distutils.system_info.atlas_threads_info
> ?NOT AVAILABLE
>
> atlas_info:
> ?libraries f77blas,cblas,atlas not found in /usr/lib/atlas
> ?libraries lapack_atlas not found in /usr/lib/atlas
> ?libraries lapack not found in /usr/lib/sse
> numpy.distutils.system_info.atlas_info
> ?FOUND:
> ? ?libraries = ['lapack', 'f77blas', 'cblas', 'atlas']
> ? ?library_dirs = ['/usr/lib/sse/atlas', '/usr/lib/sse']
> ? ?language = f77
> ? ?define_macros = [('ATLAS_INFO', '"\\"3.6.0\\""')]
> ? ?include_dirs = ['/usr/include']
>
> ?FOUND:
> ? ?libraries = ['lapack', 'f77blas', 'cblas', 'atlas']
> ? ?library_dirs = ['/usr/lib/sse/atlas', '/usr/lib/sse']
> ? ?language = f77
> ? ?define_macros = [('ATLAS_INFO', '"\\"3.6.0\\""')]
> ? ?include_dirs = ['/usr/include']
>
> running build
> running config_cc
> unifing config_cc, config, build_clib, build_ext, build commands
> --compiler options
> running config_fc
> unifing config_fc, config, build_clib, build_ext, build commands
> --fcompiler options
> running build_src
> build_src
> building py_modules sources
> creating build
> creating build/src.linux-i686-2.6
> creating build/src.linux-i686-2.6/numpy
> creating build/src.linux-i686-2.6/numpy/distutils
> building library "npymath" sources
> customize Gnu95FCompiler
> customize Gnu95FCompiler using config
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> gcc -pthread _configtest.o -o _configtest
> success!
> removing: _configtest.c _configtest.o _configtest
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:1: warning: conflicting types for built-in function ?exp?
> gcc -pthread _configtest.o -o _configtest
> _configtest.o: In function `main':
> /home/ryan/Downloads/numpy-1.6.1/_configtest.c:6: undefined reference to `exp'
> collect2: ld returned 1 exit status
> _configtest.o: In function `main':
> /home/ryan/Downloads/numpy-1.6.1/_configtest.c:6: undefined reference to `exp'
> collect2: ld returned 1 exit status
> failure.
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:1: warning: conflicting types for built-in function ?exp?
> gcc -pthread _configtest.o -lm -o _configtest
> success!
> removing: _configtest.c _configtest.o _configtest
> creating build/src.linux-i686-2.6/numpy/core
> creating build/src.linux-i686-2.6/numpy/core/src
> creating build/src.linux-i686-2.6/numpy/core/src/npymath
> conv_template:> build/src.linux-i686-2.6/numpy/core/src/npymath/npy_math.c
> conv_template:> build/src.linux-i686-2.6/numpy/core/src/npymath/ieee754.c
> conv_template:>
> build/src.linux-i686-2.6/numpy/core/src/npymath/npy_math_complex.c
> building extension "numpy.core._sort" sources
> Generating build/src.linux-i686-2.6/numpy/core/include/numpy/config.h
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:5: warning: function declaration isn?t a prototype
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:5: warning: function declaration isn?t a prototype
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:5: warning: function declaration isn?t a prototype
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:5: warning: function declaration isn?t a prototype
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o _configtest.c _configtest.o
> _configtest.c _configtest.o _configtest.c _configtest.o _configtest.c
> _configtest.o _configtest.c _configtest.o _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:5: warning: function declaration isn?t a prototype
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o _configtest.c _configtest.o
> _configtest.c _configtest.o _configtest.c _configtest.o _configtest.c
> _configtest.o _configtest.c _configtest.o _configtest.c _configtest.o
> _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:5: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:7: error: ?SIZEOF_LONGDOUBLE? undeclared (first use in
> this function)
> _configtest.c:7: error: (Each undeclared identifier is reported only once
> _configtest.c:7: error: for each function it appears in.)
> _configtest.c:5: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:7: error: ?SIZEOF_LONGDOUBLE? undeclared (first use in
> this function)
> _configtest.c:7: error: (Each undeclared identifier is reported only once
> _configtest.c:7: error: for each function it appears in.)
> failure.
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o _configtest.c _configtest.o
> _configtest.c _configtest.o _configtest.c _configtest.o _configtest.c
> _configtest.o _configtest.c _configtest.o _configtest.c _configtest.o
> _configtest.c _configtest.o _configtest.c _configtest.o _configtest.c
> _configtest.o _configtest.c _configtest.o _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:5: error: size of array ?test_array? is negative
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:6: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:6: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:5: warning: function declaration isn?t a prototype
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:6: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:6: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:5: warning: function declaration isn?t a prototype
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:1: warning: conflicting types for built-in function ?exp?
> gcc -pthread _configtest.o -o _configtest
> _configtest.o: In function `main':
> /home/ryan/Downloads/numpy-1.6.1/_configtest.c:6: undefined reference to `exp'
> collect2: ld returned 1 exit status
> _configtest.o: In function `main':
> /home/ryan/Downloads/numpy-1.6.1/_configtest.c:6: undefined reference to `exp'
> collect2: ld returned 1 exit status
> failure.
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:1: warning: conflicting types for built-in function ?exp?
> gcc -pthread _configtest.o -lm -o _configtest
> success!
> removing: _configtest.c _configtest.o _configtest
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:1: warning: conflicting types for built-in function ?asin?
> _configtest.c:2: warning: conflicting types for built-in function ?cos?
> _configtest.c:3: warning: conflicting types for built-in function ?log?
> _configtest.c:4: warning: conflicting types for built-in function ?fabs?
> _configtest.c:5: warning: conflicting types for built-in function ?tanh?
> _configtest.c:6: warning: conflicting types for built-in function ?atan?
> _configtest.c:7: warning: conflicting types for built-in function ?acos?
> _configtest.c:8: warning: conflicting types for built-in function ?floor?
> _configtest.c:9: warning: conflicting types for built-in function ?fmod?
> _configtest.c:10: warning: conflicting types for built-in function ?sqrt?
> _configtest.c:11: warning: conflicting types for built-in function ?cosh?
> _configtest.c:12: warning: conflicting types for built-in function ?modf?
> _configtest.c:13: warning: conflicting types for built-in function ?sinh?
> _configtest.c:14: warning: conflicting types for built-in function ?frexp?
> _configtest.c:15: warning: conflicting types for built-in function ?exp?
> _configtest.c:16: warning: conflicting types for built-in function ?tan?
> _configtest.c:17: warning: conflicting types for built-in function ?ceil?
> _configtest.c:18: warning: conflicting types for built-in function ?log10?
> _configtest.c:19: warning: conflicting types for built-in function ?sin?
> _configtest.c:20: warning: conflicting types for built-in function ?ldexp?
> gcc -pthread _configtest.o -lm -o _configtest
> success!
> removing: _configtest.c _configtest.o _configtest
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:6: warning: function declaration isn?t a prototype
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:6: warning: function declaration isn?t a prototype
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:6: warning: function declaration isn?t a prototype
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:6: warning: function declaration isn?t a prototype
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:6: warning: function declaration isn?t a prototype
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:6: warning: function declaration isn?t a prototype
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:6: warning: function declaration isn?t a prototype
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:1: warning: conflicting types for built-in function ?log2?
> _configtest.c:2: warning: conflicting types for built-in function ?pow?
> _configtest.c:3: warning: conflicting types for built-in function ?exp2?
> _configtest.c:4: warning: conflicting types for built-in function ?atan2?
> _configtest.c:5: warning: conflicting types for built-in function ?rint?
> _configtest.c:6: warning: conflicting types for built-in function ?nextafter?
> _configtest.c:7: warning: conflicting types for built-in function ?trunc?
> gcc -pthread _configtest.o -lm -o _configtest
> success!
> removing: _configtest.c _configtest.o _configtest
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:1: warning: conflicting types for built-in function ?cosf?
> _configtest.c:2: warning: conflicting types for built-in function ?coshf?
> _configtest.c:3: warning: conflicting types for built-in function ?rintf?
> _configtest.c:4: warning: conflicting types for built-in function ?fabsf?
> _configtest.c:5: warning: conflicting types for built-in function ?floorf?
> _configtest.c:6: warning: conflicting types for built-in function ?nextafterf?
> _configtest.c:7: warning: conflicting types for built-in function ?tanhf?
> _configtest.c:8: warning: conflicting types for built-in function ?log10f?
> _configtest.c:9: warning: conflicting types for built-in function ?logf?
> _configtest.c:10: warning: conflicting types for built-in function ?sinhf?
> _configtest.c:11: warning: conflicting types for built-in function ?acosf?
> _configtest.c:12: warning: conflicting types for built-in function ?sqrtf?
> _configtest.c:13: warning: conflicting types for built-in function ?ldexpf?
> _configtest.c:14: warning: conflicting types for built-in function ?hypotf?
> _configtest.c:15: warning: conflicting types for built-in function ?log2f?
> _configtest.c:16: warning: conflicting types for built-in function ?exp2f?
> _configtest.c:17: warning: conflicting types for built-in function ?atanf?
> _configtest.c:18: warning: conflicting types for built-in function ?fmodf?
> _configtest.c:19: warning: conflicting types for built-in function ?atan2f?
> _configtest.c:20: warning: conflicting types for built-in function ?modff?
> _configtest.c:21: warning: conflicting types for built-in function ?ceilf?
> _configtest.c:22: warning: conflicting types for built-in function ?log1pf?
> _configtest.c:23: warning: conflicting types for built-in function ?asinf?
> _configtest.c:24: warning: conflicting types for built-in function ?copysignf?
> _configtest.c:25: warning: conflicting types for built-in function ?acoshf?
> _configtest.c:26: warning: conflicting types for built-in function ?sinf?
> _configtest.c:27: warning: conflicting types for built-in function ?tanf?
> _configtest.c:28: warning: conflicting types for built-in function ?atanhf?
> _configtest.c:29: warning: conflicting types for built-in function ?truncf?
> _configtest.c:30: warning: conflicting types for built-in function ?asinhf?
> _configtest.c:31: warning: conflicting types for built-in function ?frexpf?
> _configtest.c:32: warning: conflicting types for built-in function ?powf?
> _configtest.c:33: warning: conflicting types for built-in function ?expf?
> _configtest.c:34: warning: conflicting types for built-in function ?expm1f?
> gcc -pthread _configtest.o -lm -o _configtest
> success!
> removing: _configtest.c _configtest.o _configtest
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:1: warning: conflicting types for built-in function ?tanhl?
> _configtest.c:2: warning: conflicting types for built-in function ?log10l?
> _configtest.c:3: warning: conflicting types for built-in function ?nextafterl?
> _configtest.c:4: warning: conflicting types for built-in function ?coshl?
> _configtest.c:5: warning: conflicting types for built-in function ?cosl?
> _configtest.c:6: warning: conflicting types for built-in function ?floorl?
> _configtest.c:7: warning: conflicting types for built-in function ?rintl?
> _configtest.c:8: warning: conflicting types for built-in function ?fabsl?
> _configtest.c:9: warning: conflicting types for built-in function ?acosl?
> _configtest.c:10: warning: conflicting types for built-in function ?ldexpl?
> _configtest.c:11: warning: conflicting types for built-in function ?sqrtl?
> _configtest.c:12: warning: conflicting types for built-in function ?logl?
> _configtest.c:13: warning: conflicting types for built-in function ?expm1l?
> _configtest.c:14: warning: conflicting types for built-in function ?hypotl?
> _configtest.c:15: warning: conflicting types for built-in function ?log2l?
> _configtest.c:16: warning: conflicting types for built-in function ?copysignl?
> _configtest.c:17: warning: conflicting types for built-in function ?exp2l?
> _configtest.c:18: warning: conflicting types for built-in function ?atanl?
> _configtest.c:19: warning: conflicting types for built-in function ?frexpl?
> _configtest.c:20: warning: conflicting types for built-in function ?atan2l?
> _configtest.c:21: warning: conflicting types for built-in function ?sinhl?
> _configtest.c:22: warning: conflicting types for built-in function ?fmodl?
> _configtest.c:23: warning: conflicting types for built-in function ?log1pl?
> _configtest.c:24: warning: conflicting types for built-in function ?asinl?
> _configtest.c:25: warning: conflicting types for built-in function ?ceill?
> _configtest.c:26: warning: conflicting types for built-in function ?sinl?
> _configtest.c:27: warning: conflicting types for built-in function ?acoshl?
> _configtest.c:28: warning: conflicting types for built-in function ?atanhl?
> _configtest.c:29: warning: conflicting types for built-in function ?tanl?
> _configtest.c:30: warning: conflicting types for built-in function ?truncl?
> _configtest.c:31: warning: conflicting types for built-in function ?powl?
> _configtest.c:32: warning: conflicting types for built-in function ?expl?
> _configtest.c:33: warning: conflicting types for built-in function ?modfl?
> _configtest.c:34: warning: conflicting types for built-in function ?asinhl?
> gcc -pthread _configtest.o -lm -o _configtest
> success!
> removing: _configtest.c _configtest.o _configtest
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:6: warning: function declaration isn?t a prototype
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:6: warning: function declaration isn?t a prototype
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:6: warning: function declaration isn?t a prototype
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:6: warning: function declaration isn?t a prototype
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:6: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:8: error: ?HAVE_DECL_SIGNBIT? undeclared (first use in
> this function)
> _configtest.c:8: error: (Each undeclared identifier is reported only once
> _configtest.c:8: error: for each function it appears in.)
> _configtest.c:6: warning: function declaration isn?t a prototype
> _configtest.c: In function ?main?:
> _configtest.c:8: error: ?HAVE_DECL_SIGNBIT? undeclared (first use in
> this function)
> _configtest.c:8: error: (Each undeclared identifier is reported only once
> _configtest.c:8: error: for each function it appears in.)
> failure.
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:6: warning: function declaration isn?t a prototype
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:6: warning: function declaration isn?t a prototype
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:6: warning: function declaration isn?t a prototype
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:1: warning: conflicting types for built-in function ?cexp?
> _configtest.c:2: warning: conflicting types for built-in function ?clog?
> _configtest.c:3: warning: conflicting types for built-in function ?ccos?
> _configtest.c:4: warning: conflicting types for built-in function ?cimag?
> _configtest.c:5: warning: conflicting types for built-in function ?cabs?
> _configtest.c:6: warning: conflicting types for built-in function ?cpow?
> _configtest.c:7: warning: conflicting types for built-in function ?csqrt?
> _configtest.c:8: warning: conflicting types for built-in function ?carg?
> _configtest.c:9: warning: conflicting types for built-in function ?creal?
> _configtest.c:10: warning: conflicting types for built-in function ?csin?
> gcc -pthread _configtest.o -lm -o _configtest
> success!
> removing: _configtest.c _configtest.o _configtest
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:1: warning: conflicting types for built-in function ?ccosf?
> _configtest.c:2: warning: conflicting types for built-in function ?cargf?
> _configtest.c:3: warning: conflicting types for built-in function ?csqrtf?
> _configtest.c:4: warning: conflicting types for built-in function ?cpowf?
> _configtest.c:5: warning: conflicting types for built-in function ?cexpf?
> _configtest.c:6: warning: conflicting types for built-in function ?crealf?
> _configtest.c:7: warning: conflicting types for built-in function ?csinf?
> _configtest.c:8: warning: conflicting types for built-in function ?cabsf?
> _configtest.c:9: warning: conflicting types for built-in function ?clogf?
> _configtest.c:10: warning: conflicting types for built-in function ?cimagf?
> gcc -pthread _configtest.o -lm -o _configtest
> success!
> removing: _configtest.c _configtest.o _configtest
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:1: warning: conflicting types for built-in function ?csqrtl?
> _configtest.c:2: warning: conflicting types for built-in function ?cargl?
> _configtest.c:3: warning: conflicting types for built-in function ?cexpl?
> _configtest.c:4: warning: conflicting types for built-in function ?ccosl?
> _configtest.c:5: warning: conflicting types for built-in function ?cpowl?
> _configtest.c:6: warning: conflicting types for built-in function ?cimagl?
> _configtest.c:7: warning: conflicting types for built-in function ?csinl?
> _configtest.c:8: warning: conflicting types for built-in function ?creall?
> _configtest.c:9: warning: conflicting types for built-in function ?clogl?
> _configtest.c:10: warning: conflicting types for built-in function ?cabsl?
> gcc -pthread _configtest.o -lm -o _configtest
> success!
> removing: _configtest.c _configtest.o _configtest
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:5: warning: function declaration isn?t a prototype
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> removing: _configtest.c _configtest.o
> ('File:', 'build/src.linux-i686-2.6/numpy/core/include/numpy/config.h')
> #define HAVE_ENDIAN_H 1
> #define SIZEOF_PY_INTPTR_T 4
> #define SIZEOF_PY_LONG_LONG 8
> #define MATHLIB m
> #define HAVE_SIN
> #define HAVE_COS
> #define HAVE_TAN
> #define HAVE_SINH
> #define HAVE_COSH
> #define HAVE_TANH
> #define HAVE_FABS
> #define HAVE_FLOOR
> #define HAVE_CEIL
> #define HAVE_SQRT
> #define HAVE_LOG10
> #define HAVE_LOG
> #define HAVE_EXP
> #define HAVE_ASIN
> #define HAVE_ACOS
> #define HAVE_ATAN
> #define HAVE_FMOD
> #define HAVE_MODF
> #define HAVE_FREXP
> #define HAVE_LDEXP
> #define HAVE_RINT
> #define HAVE_TRUNC
> #define HAVE_EXP2
> #define HAVE_LOG2
> #define HAVE_ATAN2
> #define HAVE_POW
> #define HAVE_NEXTAFTER
> #define HAVE_SINF
> #define HAVE_COSF
> #define HAVE_TANF
> #define HAVE_SINHF
> #define HAVE_COSHF
> #define HAVE_TANHF
> #define HAVE_FABSF
> #define HAVE_FLOORF
> #define HAVE_CEILF
> #define HAVE_RINTF
> #define HAVE_TRUNCF
> #define HAVE_SQRTF
> #define HAVE_LOG10F
> #define HAVE_LOGF
> #define HAVE_LOG1PF
> #define HAVE_EXPF
> #define HAVE_EXPM1F
> #define HAVE_ASINF
> #define HAVE_ACOSF
> #define HAVE_ATANF
> #define HAVE_ASINHF
> #define HAVE_ACOSHF
> #define HAVE_ATANHF
> #define HAVE_HYPOTF
> #define HAVE_ATAN2F
> #define HAVE_POWF
> #define HAVE_FMODF
> #define HAVE_MODFF
> #define HAVE_FREXPF
> #define HAVE_LDEXPF
> #define HAVE_EXP2F
> #define HAVE_LOG2F
> #define HAVE_COPYSIGNF
> #define HAVE_NEXTAFTERF
> #define HAVE_SINL
> #define HAVE_COSL
> #define HAVE_TANL
> #define HAVE_SINHL
> #define HAVE_COSHL
> #define HAVE_TANHL
> #define HAVE_FABSL
> #define HAVE_FLOORL
> #define HAVE_CEILL
> #define HAVE_RINTL
> #define HAVE_TRUNCL
> #define HAVE_SQRTL
> #define HAVE_LOG10L
> #define HAVE_LOGL
> #define HAVE_LOG1PL
> #define HAVE_EXPL
> #define HAVE_EXPM1L
> #define HAVE_ASINL
> #define HAVE_ACOSL
> #define HAVE_ATANL
> #define HAVE_ASINHL
> #define HAVE_ACOSHL
> #define HAVE_ATANHL
> #define HAVE_HYPOTL
> #define HAVE_ATAN2L
> #define HAVE_POWL
> #define HAVE_FMODL
> #define HAVE_MODFL
> #define HAVE_FREXPL
> #define HAVE_LDEXPL
> #define HAVE_EXP2L
> #define HAVE_LOG2L
> #define HAVE_COPYSIGNL
> #define HAVE_NEXTAFTERL
> #define HAVE_DECL_SIGNBIT
> #define HAVE_COMPLEX_H
> #define HAVE_CREAL
> #define HAVE_CIMAG
> #define HAVE_CABS
> #define HAVE_CARG
> #define HAVE_CEXP
> #define HAVE_CSQRT
> #define HAVE_CLOG
> #define HAVE_CCOS
> #define HAVE_CSIN
> #define HAVE_CPOW
> #define HAVE_CREALF
> #define HAVE_CIMAGF
> #define HAVE_CABSF
> #define HAVE_CARGF
> #define HAVE_CEXPF
> #define HAVE_CSQRTF
> #define HAVE_CLOGF
> #define HAVE_CCOSF
> #define HAVE_CSINF
> #define HAVE_CPOWF
> #define HAVE_CREALL
> #define HAVE_CIMAGL
> #define HAVE_CABSL
> #define HAVE_CARGL
> #define HAVE_CEXPL
> #define HAVE_CSQRTL
> #define HAVE_CLOGL
> #define HAVE_CCOSL
> #define HAVE_CSINL
> #define HAVE_CPOWL
> #define HAVE_LDOUBLE_INTEL_EXTENDED_12_BYTES_LE 1
> #ifndef __cplusplus
> /* #undef inline */
> #endif
>
> #ifndef _NPY_NPY_CONFIG_H_
> #error config.h should never be included directly, include npy_config.h instead
> #endif
>
> EOF
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/config.h'
> to sources.
> Generating build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:1: warning: conflicting types for built-in function ?exp?
> gcc -pthread _configtest.o -o _configtest
> _configtest.o: In function `main':
> /home/ryan/Downloads/numpy-1.6.1/_configtest.c:6: undefined reference to `exp'
> collect2: ld returned 1 exit status
> _configtest.o: In function `main':
> /home/ryan/Downloads/numpy-1.6.1/_configtest.c:6: undefined reference to `exp'
> collect2: ld returned 1 exit status
> failure.
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:1: warning: conflicting types for built-in function ?exp?
> gcc -pthread _configtest.o -lm -o _configtest
> success!
> removing: _configtest.c _configtest.o _configtest
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:5: warning: function declaration isn?t a prototype
> success!
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:4: warning: function declaration isn?t a prototype
> _configtest.c:5:18: warning: extra tokens at end of #ifndef directive
> _configtest.c: In function ?main?:
> _configtest.c:8: warning: control reaches end of non-void function
> success!
> removing: _configtest.c _configtest.o
> File: build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h
> #define NPY_HAVE_ENDIAN_H 1
> #define NPY_SIZEOF_SHORT SIZEOF_SHORT
> #define NPY_SIZEOF_INT SIZEOF_INT
> #define NPY_SIZEOF_LONG SIZEOF_LONG
> #define NPY_SIZEOF_FLOAT 4
> #define NPY_SIZEOF_COMPLEX_FLOAT 8
> #define NPY_SIZEOF_DOUBLE 8
> #define NPY_SIZEOF_COMPLEX_DOUBLE 16
> #define NPY_SIZEOF_LONGDOUBLE 12
> #define NPY_SIZEOF_COMPLEX_LONGDOUBLE 24
> #define NPY_SIZEOF_PY_INTPTR_T 4
> #define NPY_SIZEOF_PY_LONG_LONG 8
> #define NPY_SIZEOF_LONGLONG 8
> #define NPY_NO_SMP 0
> #define NPY_HAVE_DECL_ISNAN
> #define NPY_HAVE_DECL_ISINF
> #define NPY_HAVE_DECL_ISFINITE
> #define NPY_HAVE_DECL_SIGNBIT
> #define NPY_USE_C99_COMPLEX
> #define NPY_HAVE_COMPLEX_DOUBLE 1
> #define NPY_HAVE_COMPLEX_FLOAT 1
> #define NPY_HAVE_COMPLEX_LONG_DOUBLE 1
> #define NPY_USE_C99_FORMATS 1
> #define NPY_VISIBILITY_HIDDEN __attribute__((visibility("hidden")))
> #define NPY_ABI_VERSION 0x01000009
> #define NPY_API_VERSION 0x00000006
>
> #ifndef __STDC_FORMAT_MACROS
> #define __STDC_FORMAT_MACROS 1
> #endif
>
> EOF
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h'
> to sources.
> executing numpy/core/code_generators/generate_numpy_api.py
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h'
> to sources.
> conv_template:> build/src.linux-i686-2.6/numpy/core/src/_sortmodule.c
> numpy.core - nothing done with h_files =
> ['build/src.linux-i686-2.6/numpy/core/include/numpy/config.h',
> 'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h',
> 'build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h']
> building extension "numpy.core.multiarray" sources
> non-existing path in 'numpy/core':
> 'build/src.linux-i686-2.6/numpy/core/src/multiarray'
> creating build/src.linux-i686-2.6/numpy/core/src/multiarray
> conv_template:> build/src.linux-i686-2.6/numpy/core/src/multiarray/scalartypes.c
> conv_template:> build/src.linux-i686-2.6/numpy/core/src/multiarray/arraytypes.c
> conv_template:> build/src.linux-i686-2.6/numpy/core/src/multiarray/nditer.c
> conv_template:>
> build/src.linux-i686-2.6/numpy/core/src/multiarray/lowlevel_strided_loops.c
> conv_template:> build/src.linux-i686-2.6/numpy/core/src/multiarray/einsum.c
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/config.h'
> to sources.
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h'
> to sources.
> executing numpy/core/code_generators/generate_numpy_api.py
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h'
> to sources.
> numpy.core - nothing done with h_files =
> ['build/src.linux-i686-2.6/numpy/core/include/numpy/config.h',
> 'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h',
> 'build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h']
> building extension "numpy.core.umath" sources
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/config.h'
> to sources.
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h'
> to sources.
> executing numpy/core/code_generators/generate_ufunc_api.py
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/__ufunc_api.h'
> to sources.
> non-existing path in 'numpy/core':
> 'build/src.linux-i686-2.6/numpy/core/src/umath'
> creating build/src.linux-i686-2.6/numpy/core/src/umath
> conv_template:> build/src.linux-i686-2.6/numpy/core/src/umath/loops.c
> conv_template:> build/src.linux-i686-2.6/numpy/core/src/umath/umathmodule.c
> conv_template:> build/src.linux-i686-2.6/numpy/core/src/umath/funcs.inc
> ?adding 'build/src.linux-i686-2.6/numpy/core/src/umath' to include_dirs.
> numpy.core - nothing done with h_files =
> ['build/src.linux-i686-2.6/numpy/core/src/umath/funcs.inc',
> 'build/src.linux-i686-2.6/numpy/core/include/numpy/config.h',
> 'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h',
> 'build/src.linux-i686-2.6/numpy/core/include/numpy/__ufunc_api.h']
> building extension "numpy.core.scalarmath" sources
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/config.h'
> to sources.
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h'
> to sources.
> executing numpy/core/code_generators/generate_numpy_api.py
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h'
> to sources.
> executing numpy/core/code_generators/generate_ufunc_api.py
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/__ufunc_api.h'
> to sources.
> conv_template:> build/src.linux-i686-2.6/numpy/core/src/scalarmathmodule.c
> numpy.core - nothing done with h_files =
> ['build/src.linux-i686-2.6/numpy/core/include/numpy/config.h',
> 'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h',
> 'build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h',
> 'build/src.linux-i686-2.6/numpy/core/include/numpy/__ufunc_api.h']
> building extension "numpy.core._dotblas" sources
> ?adding 'numpy/core/blasdot/_dotblas.c' to sources.
> building extension "numpy.core.umath_tests" sources
> conv_template:> build/src.linux-i686-2.6/numpy/core/src/umath/umath_tests.c
> building extension "numpy.core.multiarray_tests" sources
> conv_template:>
> build/src.linux-i686-2.6/numpy/core/src/multiarray/multiarray_tests.c
> building extension "numpy.lib._compiled_base" sources
> building extension "numpy.numarray._capi" sources
> building extension "numpy.fft.fftpack_lite" sources
> building extension "numpy.linalg.lapack_lite" sources
> creating build/src.linux-i686-2.6/numpy/linalg
> ?adding 'numpy/linalg/lapack_litemodule.c' to sources.
> ?adding 'numpy/linalg/python_xerbla.c' to sources.
> building extension "numpy.random.mtrand" sources
> creating build/src.linux-i686-2.6/numpy/random
> /home/ryan/Downloads/numpy-1.6.1/numpy/distutils/command/config.py:40:
> DeprecationWarning:
> +++++++++++++++++++++++++++++++++++++++++++++++++
> Usage of try_run is deprecated: please do not
> use it anymore, and avoid configuration checks
> involving running executable on the target machine.
> +++++++++++++++++++++++++++++++++++++++++++++++++
>
> ?DeprecationWarning)
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> gcc -pthread _configtest.o -o _configtest
> _configtest
> failure.
> removing: _configtest.c _configtest.o _configtest
> building data_files sources
> build_src: building npy-pkg config files
> running build_py
> creating build/lib.linux-i686-2.6
> creating build/lib.linux-i686-2.6/numpy
> copying numpy/version.py -> build/lib.linux-i686-2.6/numpy
> copying numpy/__init__.py -> build/lib.linux-i686-2.6/numpy
> copying numpy/setupscons.py -> build/lib.linux-i686-2.6/numpy
> copying numpy/setup.py -> build/lib.linux-i686-2.6/numpy
> copying numpy/ctypeslib.py -> build/lib.linux-i686-2.6/numpy
> copying numpy/dual.py -> build/lib.linux-i686-2.6/numpy
> copying numpy/matlib.py -> build/lib.linux-i686-2.6/numpy
> copying numpy/_import_tools.py -> build/lib.linux-i686-2.6/numpy
> copying numpy/add_newdocs.py -> build/lib.linux-i686-2.6/numpy
> copying build/src.linux-i686-2.6/numpy/__config__.py ->
> build/lib.linux-i686-2.6/numpy
> creating build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/cpuinfo.py -> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/__init__.py -> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/unixccompiler.py ->
> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/__version__.py ->
> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/setupscons.py ->
> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/exec_command.py ->
> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/setup.py -> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/line_endings.py ->
> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/info.py -> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/numpy_distribution.py ->
> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/environment.py ->
> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/misc_util.py -> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/extension.py -> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/ccompiler.py -> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/intelccompiler.py ->
> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/interactive.py ->
> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/mingw32ccompiler.py ->
> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/system_info.py ->
> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/npy_pkg_config.py ->
> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/conv_template.py ->
> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/lib2def.py -> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/from_template.py ->
> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/pathccompiler.py ->
> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/core.py -> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/log.py -> build/lib.linux-i686-2.6/numpy/distutils
> copying numpy/distutils/compat.py -> build/lib.linux-i686-2.6/numpy/distutils
> copying build/src.linux-i686-2.6/numpy/distutils/__config__.py ->
> build/lib.linux-i686-2.6/numpy/distutils
> creating build/lib.linux-i686-2.6/numpy/distutils/command
> copying numpy/distutils/command/install.py ->
> build/lib.linux-i686-2.6/numpy/distutils/command
> copying numpy/distutils/command/__init__.py ->
> build/lib.linux-i686-2.6/numpy/distutils/command
> copying numpy/distutils/command/build_py.py ->
> build/lib.linux-i686-2.6/numpy/distutils/command
> copying numpy/distutils/command/build_clib.py ->
> build/lib.linux-i686-2.6/numpy/distutils/command
> copying numpy/distutils/command/develop.py ->
> build/lib.linux-i686-2.6/numpy/distutils/command
> copying numpy/distutils/command/install_headers.py ->
> build/lib.linux-i686-2.6/numpy/distutils/command
> copying numpy/distutils/command/sdist.py ->
> build/lib.linux-i686-2.6/numpy/distutils/command
> copying numpy/distutils/command/build_src.py ->
> build/lib.linux-i686-2.6/numpy/distutils/command
> copying numpy/distutils/command/install_clib.py ->
> build/lib.linux-i686-2.6/numpy/distutils/command
> copying numpy/distutils/command/bdist_rpm.py ->
> build/lib.linux-i686-2.6/numpy/distutils/command
> copying numpy/distutils/command/build.py ->
> build/lib.linux-i686-2.6/numpy/distutils/command
> copying numpy/distutils/command/scons.py ->
> build/lib.linux-i686-2.6/numpy/distutils/command
> copying numpy/distutils/command/egg_info.py ->
> build/lib.linux-i686-2.6/numpy/distutils/command
> copying numpy/distutils/command/build_ext.py ->
> build/lib.linux-i686-2.6/numpy/distutils/command
> copying numpy/distutils/command/autodist.py ->
> build/lib.linux-i686-2.6/numpy/distutils/command
> copying numpy/distutils/command/install_data.py ->
> build/lib.linux-i686-2.6/numpy/distutils/command
> copying numpy/distutils/command/config_compiler.py ->
> build/lib.linux-i686-2.6/numpy/distutils/command
> copying numpy/distutils/command/build_scripts.py ->
> build/lib.linux-i686-2.6/numpy/distutils/command
> copying numpy/distutils/command/config.py ->
> build/lib.linux-i686-2.6/numpy/distutils/command
> creating build/lib.linux-i686-2.6/numpy/distutils/fcompiler
> copying numpy/distutils/fcompiler/pathf95.py ->
> build/lib.linux-i686-2.6/numpy/distutils/fcompiler
> copying numpy/distutils/fcompiler/gnu.py ->
> build/lib.linux-i686-2.6/numpy/distutils/fcompiler
> copying numpy/distutils/fcompiler/sun.py ->
> build/lib.linux-i686-2.6/numpy/distutils/fcompiler
> copying numpy/distutils/fcompiler/absoft.py ->
> build/lib.linux-i686-2.6/numpy/distutils/fcompiler
> copying numpy/distutils/fcompiler/g95.py ->
> build/lib.linux-i686-2.6/numpy/distutils/fcompiler
> copying numpy/distutils/fcompiler/__init__.py ->
> build/lib.linux-i686-2.6/numpy/distutils/fcompiler
> copying numpy/distutils/fcompiler/none.py ->
> build/lib.linux-i686-2.6/numpy/distutils/fcompiler
> copying numpy/distutils/fcompiler/nag.py ->
> build/lib.linux-i686-2.6/numpy/distutils/fcompiler
> copying numpy/distutils/fcompiler/lahey.py ->
> build/lib.linux-i686-2.6/numpy/distutils/fcompiler
> copying numpy/distutils/fcompiler/ibm.py ->
> build/lib.linux-i686-2.6/numpy/distutils/fcompiler
> copying numpy/distutils/fcompiler/compaq.py ->
> build/lib.linux-i686-2.6/numpy/distutils/fcompiler
> copying numpy/distutils/fcompiler/mips.py ->
> build/lib.linux-i686-2.6/numpy/distutils/fcompiler
> copying numpy/distutils/fcompiler/hpux.py ->
> build/lib.linux-i686-2.6/numpy/distutils/fcompiler
> copying numpy/distutils/fcompiler/vast.py ->
> build/lib.linux-i686-2.6/numpy/distutils/fcompiler
> copying numpy/distutils/fcompiler/pg.py ->
> build/lib.linux-i686-2.6/numpy/distutils/fcompiler
> copying numpy/distutils/fcompiler/intel.py ->
> build/lib.linux-i686-2.6/numpy/distutils/fcompiler
> creating build/lib.linux-i686-2.6/numpy/testing
> copying numpy/testing/decorators.py -> build/lib.linux-i686-2.6/numpy/testing
> copying numpy/testing/__init__.py -> build/lib.linux-i686-2.6/numpy/testing
> copying numpy/testing/setupscons.py -> build/lib.linux-i686-2.6/numpy/testing
> copying numpy/testing/nulltester.py -> build/lib.linux-i686-2.6/numpy/testing
> copying numpy/testing/setup.py -> build/lib.linux-i686-2.6/numpy/testing
> copying numpy/testing/print_coercion_tables.py ->
> build/lib.linux-i686-2.6/numpy/testing
> copying numpy/testing/noseclasses.py -> build/lib.linux-i686-2.6/numpy/testing
> copying numpy/testing/utils.py -> build/lib.linux-i686-2.6/numpy/testing
> copying numpy/testing/nosetester.py -> build/lib.linux-i686-2.6/numpy/testing
> copying numpy/testing/numpytest.py -> build/lib.linux-i686-2.6/numpy/testing
> creating build/lib.linux-i686-2.6/numpy/f2py
> copying numpy/f2py/__init__.py -> build/lib.linux-i686-2.6/numpy/f2py
> copying numpy/f2py/rules.py -> build/lib.linux-i686-2.6/numpy/f2py
> copying numpy/f2py/f2py_testing.py -> build/lib.linux-i686-2.6/numpy/f2py
> copying numpy/f2py/__version__.py -> build/lib.linux-i686-2.6/numpy/f2py
> copying numpy/f2py/setupscons.py -> build/lib.linux-i686-2.6/numpy/f2py
> copying numpy/f2py/setup.py -> build/lib.linux-i686-2.6/numpy/f2py
> copying numpy/f2py/auxfuncs.py -> build/lib.linux-i686-2.6/numpy/f2py
> copying numpy/f2py/info.py -> build/lib.linux-i686-2.6/numpy/f2py
> copying numpy/f2py/crackfortran.py -> build/lib.linux-i686-2.6/numpy/f2py
> copying numpy/f2py/use_rules.py -> build/lib.linux-i686-2.6/numpy/f2py
> copying numpy/f2py/func2subr.py -> build/lib.linux-i686-2.6/numpy/f2py
> copying numpy/f2py/f2py2e.py -> build/lib.linux-i686-2.6/numpy/f2py
> copying numpy/f2py/cb_rules.py -> build/lib.linux-i686-2.6/numpy/f2py
> copying numpy/f2py/diagnose.py -> build/lib.linux-i686-2.6/numpy/f2py
> copying numpy/f2py/capi_maps.py -> build/lib.linux-i686-2.6/numpy/f2py
> copying numpy/f2py/f90mod_rules.py -> build/lib.linux-i686-2.6/numpy/f2py
> copying numpy/f2py/cfuncs.py -> build/lib.linux-i686-2.6/numpy/f2py
> copying numpy/f2py/common_rules.py -> build/lib.linux-i686-2.6/numpy/f2py
> creating build/lib.linux-i686-2.6/numpy/core
> copying numpy/core/setup_common.py -> build/lib.linux-i686-2.6/numpy/core
> copying numpy/core/numerictypes.py -> build/lib.linux-i686-2.6/numpy/core
> copying numpy/core/shape_base.py -> build/lib.linux-i686-2.6/numpy/core
> copying numpy/core/numeric.py -> build/lib.linux-i686-2.6/numpy/core
> copying numpy/core/__init__.py -> build/lib.linux-i686-2.6/numpy/core
> copying numpy/core/_mx_datetime_parser.py -> build/lib.linux-i686-2.6/numpy/core
> copying numpy/core/setupscons.py -> build/lib.linux-i686-2.6/numpy/core
> copying numpy/core/setup.py -> build/lib.linux-i686-2.6/numpy/core
> copying numpy/core/info.py -> build/lib.linux-i686-2.6/numpy/core
> copying numpy/core/defchararray.py -> build/lib.linux-i686-2.6/numpy/core
> copying numpy/core/function_base.py -> build/lib.linux-i686-2.6/numpy/core
> copying numpy/core/fromnumeric.py -> build/lib.linux-i686-2.6/numpy/core
> copying numpy/core/records.py -> build/lib.linux-i686-2.6/numpy/core
> copying numpy/core/getlimits.py -> build/lib.linux-i686-2.6/numpy/core
> copying numpy/core/_internal.py -> build/lib.linux-i686-2.6/numpy/core
> copying numpy/core/scons_support.py -> build/lib.linux-i686-2.6/numpy/core
> copying numpy/core/machar.py -> build/lib.linux-i686-2.6/numpy/core
> copying numpy/core/memmap.py -> build/lib.linux-i686-2.6/numpy/core
> copying numpy/core/arrayprint.py -> build/lib.linux-i686-2.6/numpy/core
> copying numpy/core/code_generators/generate_numpy_api.py ->
> build/lib.linux-i686-2.6/numpy/core
> creating build/lib.linux-i686-2.6/numpy/lib
> copying numpy/lib/shape_base.py -> build/lib.linux-i686-2.6/numpy/lib
> copying numpy/lib/__init__.py -> build/lib.linux-i686-2.6/numpy/lib
> copying numpy/lib/_datasource.py -> build/lib.linux-i686-2.6/numpy/lib
> copying numpy/lib/setupscons.py -> build/lib.linux-i686-2.6/numpy/lib
> copying numpy/lib/arraysetops.py -> build/lib.linux-i686-2.6/numpy/lib
> copying numpy/lib/setup.py -> build/lib.linux-i686-2.6/numpy/lib
> copying numpy/lib/info.py -> build/lib.linux-i686-2.6/numpy/lib
> copying numpy/lib/format.py -> build/lib.linux-i686-2.6/numpy/lib
> copying numpy/lib/arrayterator.py -> build/lib.linux-i686-2.6/numpy/lib
> copying numpy/lib/user_array.py -> build/lib.linux-i686-2.6/numpy/lib
> copying numpy/lib/_iotools.py -> build/lib.linux-i686-2.6/numpy/lib
> copying numpy/lib/recfunctions.py -> build/lib.linux-i686-2.6/numpy/lib
> copying numpy/lib/financial.py -> build/lib.linux-i686-2.6/numpy/lib
> copying numpy/lib/function_base.py -> build/lib.linux-i686-2.6/numpy/lib
> copying numpy/lib/ufunclike.py -> build/lib.linux-i686-2.6/numpy/lib
> copying numpy/lib/scimath.py -> build/lib.linux-i686-2.6/numpy/lib
> copying numpy/lib/twodim_base.py -> build/lib.linux-i686-2.6/numpy/lib
> copying numpy/lib/index_tricks.py -> build/lib.linux-i686-2.6/numpy/lib
> copying numpy/lib/polynomial.py -> build/lib.linux-i686-2.6/numpy/lib
> copying numpy/lib/utils.py -> build/lib.linux-i686-2.6/numpy/lib
> copying numpy/lib/stride_tricks.py -> build/lib.linux-i686-2.6/numpy/lib
> copying numpy/lib/type_check.py -> build/lib.linux-i686-2.6/numpy/lib
> copying numpy/lib/npyio.py -> build/lib.linux-i686-2.6/numpy/lib
> creating build/lib.linux-i686-2.6/numpy/oldnumeric
> copying numpy/oldnumeric/alter_code2.py ->
> build/lib.linux-i686-2.6/numpy/oldnumeric
> copying numpy/oldnumeric/typeconv.py ->
> build/lib.linux-i686-2.6/numpy/oldnumeric
> copying numpy/oldnumeric/__init__.py ->
> build/lib.linux-i686-2.6/numpy/oldnumeric
> copying numpy/oldnumeric/fft.py -> build/lib.linux-i686-2.6/numpy/oldnumeric
> copying numpy/oldnumeric/setupscons.py ->
> build/lib.linux-i686-2.6/numpy/oldnumeric
> copying numpy/oldnumeric/setup.py -> build/lib.linux-i686-2.6/numpy/oldnumeric
> copying numpy/oldnumeric/alter_code1.py ->
> build/lib.linux-i686-2.6/numpy/oldnumeric
> copying numpy/oldnumeric/arrayfns.py ->
> build/lib.linux-i686-2.6/numpy/oldnumeric
> copying numpy/oldnumeric/ufuncs.py -> build/lib.linux-i686-2.6/numpy/oldnumeric
> copying numpy/oldnumeric/misc.py -> build/lib.linux-i686-2.6/numpy/oldnumeric
> copying numpy/oldnumeric/user_array.py ->
> build/lib.linux-i686-2.6/numpy/oldnumeric
> copying numpy/oldnumeric/linear_algebra.py ->
> build/lib.linux-i686-2.6/numpy/oldnumeric
> copying numpy/oldnumeric/matrix.py -> build/lib.linux-i686-2.6/numpy/oldnumeric
> copying numpy/oldnumeric/ma.py -> build/lib.linux-i686-2.6/numpy/oldnumeric
> copying numpy/oldnumeric/functions.py ->
> build/lib.linux-i686-2.6/numpy/oldnumeric
> copying numpy/oldnumeric/random_array.py ->
> build/lib.linux-i686-2.6/numpy/oldnumeric
> copying numpy/oldnumeric/precision.py ->
> build/lib.linux-i686-2.6/numpy/oldnumeric
> copying numpy/oldnumeric/mlab.py -> build/lib.linux-i686-2.6/numpy/oldnumeric
> copying numpy/oldnumeric/rng_stats.py ->
> build/lib.linux-i686-2.6/numpy/oldnumeric
> copying numpy/oldnumeric/rng.py -> build/lib.linux-i686-2.6/numpy/oldnumeric
> copying numpy/oldnumeric/compat.py -> build/lib.linux-i686-2.6/numpy/oldnumeric
> copying numpy/oldnumeric/fix_default_axis.py ->
> build/lib.linux-i686-2.6/numpy/oldnumeric
> copying numpy/oldnumeric/array_printer.py ->
> build/lib.linux-i686-2.6/numpy/oldnumeric
> creating build/lib.linux-i686-2.6/numpy/numarray
> copying numpy/numarray/numerictypes.py ->
> build/lib.linux-i686-2.6/numpy/numarray
> copying numpy/numarray/alter_code2.py -> build/lib.linux-i686-2.6/numpy/numarray
> copying numpy/numarray/nd_image.py -> build/lib.linux-i686-2.6/numpy/numarray
> copying numpy/numarray/__init__.py -> build/lib.linux-i686-2.6/numpy/numarray
> copying numpy/numarray/fft.py -> build/lib.linux-i686-2.6/numpy/numarray
> copying numpy/numarray/setupscons.py -> build/lib.linux-i686-2.6/numpy/numarray
> copying numpy/numarray/setup.py -> build/lib.linux-i686-2.6/numpy/numarray
> copying numpy/numarray/alter_code1.py -> build/lib.linux-i686-2.6/numpy/numarray
> copying numpy/numarray/ufuncs.py -> build/lib.linux-i686-2.6/numpy/numarray
> copying numpy/numarray/linear_algebra.py ->
> build/lib.linux-i686-2.6/numpy/numarray
> copying numpy/numarray/matrix.py -> build/lib.linux-i686-2.6/numpy/numarray
> copying numpy/numarray/ma.py -> build/lib.linux-i686-2.6/numpy/numarray
> copying numpy/numarray/functions.py -> build/lib.linux-i686-2.6/numpy/numarray
> copying numpy/numarray/convolve.py -> build/lib.linux-i686-2.6/numpy/numarray
> copying numpy/numarray/image.py -> build/lib.linux-i686-2.6/numpy/numarray
> copying numpy/numarray/random_array.py ->
> build/lib.linux-i686-2.6/numpy/numarray
> copying numpy/numarray/util.py -> build/lib.linux-i686-2.6/numpy/numarray
> copying numpy/numarray/mlab.py -> build/lib.linux-i686-2.6/numpy/numarray
> copying numpy/numarray/session.py -> build/lib.linux-i686-2.6/numpy/numarray
> copying numpy/numarray/compat.py -> build/lib.linux-i686-2.6/numpy/numarray
> creating build/lib.linux-i686-2.6/numpy/fft
> copying numpy/fft/fftpack.py -> build/lib.linux-i686-2.6/numpy/fft
> copying numpy/fft/__init__.py -> build/lib.linux-i686-2.6/numpy/fft
> copying numpy/fft/setupscons.py -> build/lib.linux-i686-2.6/numpy/fft
> copying numpy/fft/setup.py -> build/lib.linux-i686-2.6/numpy/fft
> copying numpy/fft/info.py -> build/lib.linux-i686-2.6/numpy/fft
> copying numpy/fft/helper.py -> build/lib.linux-i686-2.6/numpy/fft
> creating build/lib.linux-i686-2.6/numpy/linalg
> copying numpy/linalg/__init__.py -> build/lib.linux-i686-2.6/numpy/linalg
> copying numpy/linalg/setupscons.py -> build/lib.linux-i686-2.6/numpy/linalg
> copying numpy/linalg/setup.py -> build/lib.linux-i686-2.6/numpy/linalg
> copying numpy/linalg/info.py -> build/lib.linux-i686-2.6/numpy/linalg
> copying numpy/linalg/linalg.py -> build/lib.linux-i686-2.6/numpy/linalg
> creating build/lib.linux-i686-2.6/numpy/random
> copying numpy/random/__init__.py -> build/lib.linux-i686-2.6/numpy/random
> copying numpy/random/setupscons.py -> build/lib.linux-i686-2.6/numpy/random
> copying numpy/random/setup.py -> build/lib.linux-i686-2.6/numpy/random
> copying numpy/random/info.py -> build/lib.linux-i686-2.6/numpy/random
> creating build/lib.linux-i686-2.6/numpy/ma
> copying numpy/ma/mrecords.py -> build/lib.linux-i686-2.6/numpy/ma
> copying numpy/ma/extras.py -> build/lib.linux-i686-2.6/numpy/ma
> copying numpy/ma/version.py -> build/lib.linux-i686-2.6/numpy/ma
> copying numpy/ma/__init__.py -> build/lib.linux-i686-2.6/numpy/ma
> copying numpy/ma/setupscons.py -> build/lib.linux-i686-2.6/numpy/ma
> copying numpy/ma/setup.py -> build/lib.linux-i686-2.6/numpy/ma
> copying numpy/ma/testutils.py -> build/lib.linux-i686-2.6/numpy/ma
> copying numpy/ma/timer_comparison.py -> build/lib.linux-i686-2.6/numpy/ma
> copying numpy/ma/bench.py -> build/lib.linux-i686-2.6/numpy/ma
> copying numpy/ma/core.py -> build/lib.linux-i686-2.6/numpy/ma
> creating build/lib.linux-i686-2.6/numpy/matrixlib
> copying numpy/matrixlib/defmatrix.py -> build/lib.linux-i686-2.6/numpy/matrixlib
> copying numpy/matrixlib/__init__.py -> build/lib.linux-i686-2.6/numpy/matrixlib
> copying numpy/matrixlib/setupscons.py ->
> build/lib.linux-i686-2.6/numpy/matrixlib
> copying numpy/matrixlib/setup.py -> build/lib.linux-i686-2.6/numpy/matrixlib
> creating build/lib.linux-i686-2.6/numpy/compat
> copying numpy/compat/__init__.py -> build/lib.linux-i686-2.6/numpy/compat
> copying numpy/compat/py3k.py -> build/lib.linux-i686-2.6/numpy/compat
> copying numpy/compat/setupscons.py -> build/lib.linux-i686-2.6/numpy/compat
> copying numpy/compat/setup.py -> build/lib.linux-i686-2.6/numpy/compat
> copying numpy/compat/_inspect.py -> build/lib.linux-i686-2.6/numpy/compat
> creating build/lib.linux-i686-2.6/numpy/polynomial
> copying numpy/polynomial/legendre.py ->
> build/lib.linux-i686-2.6/numpy/polynomial
> copying numpy/polynomial/__init__.py ->
> build/lib.linux-i686-2.6/numpy/polynomial
> copying numpy/polynomial/hermite.py -> build/lib.linux-i686-2.6/numpy/polynomial
> copying numpy/polynomial/polyutils.py ->
> build/lib.linux-i686-2.6/numpy/polynomial
> copying numpy/polynomial/setup.py -> build/lib.linux-i686-2.6/numpy/polynomial
> copying numpy/polynomial/chebyshev.py ->
> build/lib.linux-i686-2.6/numpy/polynomial
> copying numpy/polynomial/polynomial.py ->
> build/lib.linux-i686-2.6/numpy/polynomial
> copying numpy/polynomial/hermite_e.py ->
> build/lib.linux-i686-2.6/numpy/polynomial
> copying numpy/polynomial/laguerre.py ->
> build/lib.linux-i686-2.6/numpy/polynomial
> copying numpy/polynomial/polytemplate.py ->
> build/lib.linux-i686-2.6/numpy/polynomial
> creating build/lib.linux-i686-2.6/numpy/doc
> copying numpy/doc/__init__.py -> build/lib.linux-i686-2.6/numpy/doc
> copying numpy/doc/methods_vs_functions.py -> build/lib.linux-i686-2.6/numpy/doc
> copying numpy/doc/basics.py -> build/lib.linux-i686-2.6/numpy/doc
> copying numpy/doc/creation.py -> build/lib.linux-i686-2.6/numpy/doc
> copying numpy/doc/ufuncs.py -> build/lib.linux-i686-2.6/numpy/doc
> copying numpy/doc/misc.py -> build/lib.linux-i686-2.6/numpy/doc
> copying numpy/doc/indexing.py -> build/lib.linux-i686-2.6/numpy/doc
> copying numpy/doc/byteswapping.py -> build/lib.linux-i686-2.6/numpy/doc
> copying numpy/doc/performance.py -> build/lib.linux-i686-2.6/numpy/doc
> copying numpy/doc/subclassing.py -> build/lib.linux-i686-2.6/numpy/doc
> copying numpy/doc/io.py -> build/lib.linux-i686-2.6/numpy/doc
> copying numpy/doc/broadcasting.py -> build/lib.linux-i686-2.6/numpy/doc
> copying numpy/doc/internals.py -> build/lib.linux-i686-2.6/numpy/doc
> copying numpy/doc/jargon.py -> build/lib.linux-i686-2.6/numpy/doc
> copying numpy/doc/structured_arrays.py -> build/lib.linux-i686-2.6/numpy/doc
> copying numpy/doc/constants.py -> build/lib.linux-i686-2.6/numpy/doc
> copying numpy/doc/howtofind.py -> build/lib.linux-i686-2.6/numpy/doc
> copying numpy/doc/glossary.py -> build/lib.linux-i686-2.6/numpy/doc
> running build_clib
> customize UnixCCompiler
> customize UnixCCompiler using build_clib
> building 'npymath' library
> compiling C sources
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> creating build/temp.linux-i686-2.6
> creating build/temp.linux-i686-2.6/build
> creating build/temp.linux-i686-2.6/build/src.linux-i686-2.6
> creating build/temp.linux-i686-2.6/build/src.linux-i686-2.6/numpy
> creating build/temp.linux-i686-2.6/build/src.linux-i686-2.6/numpy/core
> creating build/temp.linux-i686-2.6/build/src.linux-i686-2.6/numpy/core/src
> creating build/temp.linux-i686-2.6/build/src.linux-i686-2.6/numpy/core/src/npymath
> creating build/temp.linux-i686-2.6/numpy
> creating build/temp.linux-i686-2.6/numpy/core
> creating build/temp.linux-i686-2.6/numpy/core/src
> creating build/temp.linux-i686-2.6/numpy/core/src/npymath
> compile options: '-Inumpy/core/include
> -Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
> -Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
> -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
> -Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
> gcc: build/src.linux-i686-2.6/numpy/core/src/npymath/npy_math_complex.c
> gcc: numpy/core/src/npymath/halffloat.c
> gcc: build/src.linux-i686-2.6/numpy/core/src/npymath/npy_math.c
> gcc: build/src.linux-i686-2.6/numpy/core/src/npymath/ieee754.c
> ar: adding 4 object files to build/temp.linux-i686-2.6/libnpymath.a
> running build_ext
> customize UnixCCompiler
> customize UnixCCompiler using build_ext
> customize Gnu95FCompiler
> customize Gnu95FCompiler using build_ext
> building 'numpy.core._sort' extension
> compiling C sources
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/include
> -Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
> -Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
> -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
> -Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
> gcc: build/src.linux-i686-2.6/numpy/core/src/_sortmodule.c
> gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions
> build/temp.linux-i686-2.6/build/src.linux-i686-2.6/numpy/core/src/_sortmodule.o
> -Lbuild/temp.linux-i686-2.6 -lnpymath -lm -o
> build/lib.linux-i686-2.6/numpy/core/_sort.so
> building 'numpy.core.multiarray' extension
> compiling C sources
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> creating build/temp.linux-i686-2.6/numpy/core/src/multiarray
> compile options: '-Inumpy/core/include
> -Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
> -Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
> -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
> -Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
> gcc: numpy/core/src/multiarray/multiarraymodule_onefile.c
> numpy/core/src/multiarray/mapping.c:74: warning: ?_array_ass_item?
> defined but not used
> build/src.linux-i686-2.6/numpy/core/include/numpy/__ufunc_api.h:226:
> warning: ?_import_umath? defined but not used
> gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions
> build/temp.linux-i686-2.6/numpy/core/src/multiarray/multiarraymodule_onefile.o
> -Lbuild/temp.linux-i686-2.6 -lnpymath -lm -o
> build/lib.linux-i686-2.6/numpy/core/multiarray.so
> building 'numpy.core.umath' extension
> compiling C sources
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> creating build/temp.linux-i686-2.6/numpy/core/src/umath
> compile options: '-Ibuild/src.linux-i686-2.6/numpy/core/src/umath
> -Inumpy/core/include
> -Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
> -Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
> -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
> -Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
> gcc: numpy/core/src/umath/umathmodule_onefile.c
> numpy/core/include/numpy/npy_3kcompat.h:391: warning:
> ?simple_capsule_dtor? defined but not used
> numpy/core/src/umath/loops.c.src:1402: warning: ?FLOAT_ldexp_long?
> defined but not used
> numpy/core/src/umath/loops.c.src:1402: warning: ?DOUBLE_ldexp_long?
> defined but not used
> numpy/core/src/umath/loops.c.src:1402: warning:
> ?LONGDOUBLE_ldexp_long? defined but not used
> numpy/core/src/umath/loops.c.src:1709: warning: ?HALF_ldexp_long?
> defined but not used
> numpy/core/src/private/lowlevel_strided_loops.h:36: warning:
> ?PyArray_FreeStridedTransferData? declared ?static? but never defined
> numpy/core/src/private/lowlevel_strided_loops.h:43: warning:
> ?PyArray_CopyStridedTransferData? declared ?static? but never defined
> numpy/core/src/private/lowlevel_strided_loops.h:63: warning:
> ?PyArray_GetStridedCopyFn? declared ?static? but never defined
> numpy/core/src/private/lowlevel_strided_loops.h:77: warning:
> ?PyArray_GetStridedCopySwapFn? declared ?static? but never defined
> numpy/core/src/private/lowlevel_strided_loops.h:91: warning:
> ?PyArray_GetStridedCopySwapPairFn? declared ?static? but never defined
> numpy/core/src/private/lowlevel_strided_loops.h:105: warning:
> ?PyArray_GetStridedZeroPadCopyFn? declared ?static? but never defined
> numpy/core/src/private/lowlevel_strided_loops.h:118: warning:
> ?PyArray_GetStridedNumericCastFn? declared ?static? but never defined
> numpy/core/src/private/lowlevel_strided_loops.h:168: warning:
> ?PyArray_GetDTypeTransferFunction? declared ?static? but never defined
> numpy/core/src/private/lowlevel_strided_loops.h:220: warning:
> ?PyArray_TransferNDimToStrided? declared ?static? but never defined
> numpy/core/src/private/lowlevel_strided_loops.h:230: warning:
> ?PyArray_TransferStridedToNDim? declared ?static? but never defined
> gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions
> build/temp.linux-i686-2.6/numpy/core/src/umath/umathmodule_onefile.o
> -Lbuild/temp.linux-i686-2.6 -lnpymath -lm -o
> build/lib.linux-i686-2.6/numpy/core/umath.so
> building 'numpy.core.scalarmath' extension
> compiling C sources
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/include
> -Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
> -Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
> -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
> -Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
> gcc: build/src.linux-i686-2.6/numpy/core/src/scalarmathmodule.c
> numpy/core/src/scalarmathmodule.c.src:1054: warning: function
> declaration isn?t a prototype
> numpy/core/include/numpy/npy_3kcompat.h:391: warning:
> ?simple_capsule_dtor? defined but not used
> gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions
> build/temp.linux-i686-2.6/build/src.linux-i686-2.6/numpy/core/src/scalarmathmodule.o
> -Lbuild/temp.linux-i686-2.6 -lnpymath -lm -o
> build/lib.linux-i686-2.6/numpy/core/scalarmath.so
> building 'numpy.core._dotblas' extension
> compiling C sources
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> creating build/temp.linux-i686-2.6/numpy/core/blasdot
> compile options: '-DATLAS_INFO="\"3.6.0\"" -Inumpy/core/blasdot
> -I/usr/include -Inumpy/core/include
> -Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
> -Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
> -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
> -Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
> gcc: numpy/core/blasdot/_dotblas.c
> numpy/core/blasdot/_dotblas.c: In function ?dotblas_matrixproduct?:
> numpy/core/blasdot/_dotblas.c:239: warning: comparison of distinct
> pointer types lacks a cast
> numpy/core/blasdot/_dotblas.c:257: warning: passing argument 3 of
> ?(struct PyObject * (*)(struct PyObject *, struct PyObject *, struct
> PyArrayObject *))*(PyArray_API + 1120u)? from incompatible pointer
> type
> numpy/core/blasdot/_dotblas.c:257: note: expected ?struct
> PyArrayObject *? but argument is of type ?struct PyObject *?
> numpy/core/blasdot/_dotblas.c:292: warning: passing argument 3 of
> ?(struct PyObject * (*)(struct PyObject *, struct PyObject *, struct
> PyArrayObject *))*(PyArray_API + 1120u)? from incompatible pointer
> type
> numpy/core/blasdot/_dotblas.c:292: note: expected ?struct
> PyArrayObject *? but argument is of type ?struct PyObject *?
> gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions
> build/temp.linux-i686-2.6/numpy/core/blasdot/_dotblas.o -L/usr/lib/sse
> -Lbuild/temp.linux-i686-2.6 -lf77blas -lcblas -latlas -o
> build/lib.linux-i686-2.6/numpy/core/_dotblas.so
> building 'numpy.core.umath_tests' extension
> compiling C sources
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> creating build/temp.linux-i686-2.6/build/src.linux-i686-2.6/numpy/core/src/umath
> compile options: '-Inumpy/core/include
> -Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
> -Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
> -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
> -Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
> gcc: build/src.linux-i686-2.6/numpy/core/src/umath/umath_tests.c
> numpy/core/include/numpy/npy_3kcompat.h:391: warning:
> ?simple_capsule_dtor? defined but not used
> gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions
> build/temp.linux-i686-2.6/build/src.linux-i686-2.6/numpy/core/src/umath/umath_tests.o
> -Lbuild/temp.linux-i686-2.6 -o
> build/lib.linux-i686-2.6/numpy/core/umath_tests.so
> building 'numpy.core.multiarray_tests' extension
> compiling C sources
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> creating build/temp.linux-i686-2.6/build/src.linux-i686-2.6/numpy/core/src/multiarray
> compile options: '-Inumpy/core/include
> -Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
> -Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
> -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
> -Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
> gcc: build/src.linux-i686-2.6/numpy/core/src/multiarray/multiarray_tests.c
> numpy/core/include/numpy/npy_3kcompat.h:391: warning:
> ?simple_capsule_dtor? defined but not used
> gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions
> build/temp.linux-i686-2.6/build/src.linux-i686-2.6/numpy/core/src/multiarray/multiarray_tests.o
> -Lbuild/temp.linux-i686-2.6 -o
> build/lib.linux-i686-2.6/numpy/core/multiarray_tests.so
> building 'numpy.lib._compiled_base' extension
> compiling C sources
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> creating build/temp.linux-i686-2.6/numpy/lib
> creating build/temp.linux-i686-2.6/numpy/lib/src
> compile options: '-Inumpy/core/include
> -Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
> -Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
> -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
> -Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
> gcc: numpy/lib/src/_compiled_base.c
> gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions
> build/temp.linux-i686-2.6/numpy/lib/src/_compiled_base.o
> -Lbuild/temp.linux-i686-2.6 -o
> build/lib.linux-i686-2.6/numpy/lib/_compiled_base.so
> building 'numpy.numarray._capi' extension
> compiling C sources
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> creating build/temp.linux-i686-2.6/numpy/numarray
> compile options: '-Inumpy/core/include
> -Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
> -Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
> -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
> -Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
> gcc: numpy/numarray/_capi.c
> numpy/core/include/numpy/npy_3kcompat.h:391: warning:
> ?simple_capsule_dtor? defined but not used
> gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions
> build/temp.linux-i686-2.6/numpy/numarray/_capi.o
> -Lbuild/temp.linux-i686-2.6 -o
> build/lib.linux-i686-2.6/numpy/numarray/_capi.so
> building 'numpy.fft.fftpack_lite' extension
> compiling C sources
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> creating build/temp.linux-i686-2.6/numpy/fft
> compile options: '-Inumpy/core/include
> -Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
> -Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
> -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
> -Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
> gcc: numpy/fft/fftpack_litemodule.c
> gcc: numpy/fft/fftpack.c
> gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions
> build/temp.linux-i686-2.6/numpy/fft/fftpack_litemodule.o
> build/temp.linux-i686-2.6/numpy/fft/fftpack.o
> -Lbuild/temp.linux-i686-2.6 -o
> build/lib.linux-i686-2.6/numpy/fft/fftpack_lite.so
> building 'numpy.linalg.lapack_lite' extension
> compiling C sources
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> creating build/temp.linux-i686-2.6/numpy/linalg
> compile options: '-DATLAS_INFO="\"3.6.0\"" -I/usr/include
> -Inumpy/core/include
> -Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
> -Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
> -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
> -Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
> gcc: numpy/linalg/lapack_litemodule.c
> gcc: numpy/linalg/python_xerbla.c
> /usr/bin/gfortran -Wall -Wall -shared
> build/temp.linux-i686-2.6/numpy/linalg/lapack_litemodule.o
> build/temp.linux-i686-2.6/numpy/linalg/python_xerbla.o
> -L/usr/lib/sse/atlas -L/usr/lib/sse -Lbuild/temp.linux-i686-2.6
> -llapack -lf77blas -lcblas -latlas -lgfortran -o
> build/lib.linux-i686-2.6/numpy/linalg/lapack_lite.so
> building 'numpy.random.mtrand' extension
> compiling C sources
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> creating build/temp.linux-i686-2.6/numpy/random
> creating build/temp.linux-i686-2.6/numpy/random/mtrand
> compile options: '-Inumpy/core/include
> -Ibuild/src.linux-i686-2.6/numpy/core/include/numpy
> -Inumpy/core/src/private -Inumpy/core/src -Inumpy/core
> -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -Ibuild/src.linux-i686-2.6/numpy/core/src/multiarray
> -Ibuild/src.linux-i686-2.6/numpy/core/src/umath -c'
> gcc: numpy/random/mtrand/distributions.c
> gcc: numpy/random/mtrand/initarray.c
> gcc: numpy/random/mtrand/randomkit.c
> gcc: numpy/random/mtrand/mtrand.c
> gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions
> build/temp.linux-i686-2.6/numpy/random/mtrand/mtrand.o
> build/temp.linux-i686-2.6/numpy/random/mtrand/randomkit.o
> build/temp.linux-i686-2.6/numpy/random/mtrand/initarray.o
> build/temp.linux-i686-2.6/numpy/random/mtrand/distributions.o
> -Lbuild/temp.linux-i686-2.6 -o
> build/lib.linux-i686-2.6/numpy/random/mtrand.so
> running scons
> running build_scripts
> creating build/scripts.linux-i686-2.6
> Creating build/scripts.linux-i686-2.6/f2py
> ?adding 'build/scripts.linux-i686-2.6/f2py' to scripts
> changing mode of build/scripts.linux-i686-2.6/f2py from 644 to 755
> ryan at ryan-hpdv4|12:20 PM|numpy-1.6.1$
>
>
> Here is the output of the install command:
>
> ryan at ryan-hpdv4|12:27 PM|numpy-1.6.1$ sudo python setup.py install
> Running from numpy source directory.F2PY Version 2
> blas_opt_info:
> blas_mkl_info:
> ?libraries mkl,vml,guide not found in /usr/lib
> ?NOT AVAILABLE
>
> atlas_blas_threads_info:
> Setting PTATLAS=ATLAS
> ?libraries ptf77blas,ptcblas,atlas not found in /usr/lib/atlas
> ?libraries ptf77blas,ptcblas,atlas not found in /usr/lib/sse
> ?libraries ptf77blas,ptcblas,atlas not found in /usr/lib/sse2
> ?libraries ptf77blas,ptcblas,atlas not found in /usr/lib
> ?NOT AVAILABLE
>
> atlas_blas_info:
> ?libraries f77blas,cblas,atlas not found in /usr/lib/atlas
> /home/ryan/Downloads/numpy-1.6.1/numpy/distutils/command/config.py:413:
> DeprecationWarning:
> +++++++++++++++++++++++++++++++++++++++++++++++++
> Usage of get_output is deprecated: please do not
> use it anymore, and avoid configuration checks
> involving running executable on the target machine.
> +++++++++++++++++++++++++++++++++++++++++++++++++
>
> ?DeprecationWarning)
> customize GnuFCompiler
> Could not locate executable g77
> Could not locate executable f77
> customize IntelFCompiler
> Could not locate executable ifort
> Could not locate executable ifc
> customize LaheyFCompiler
> Could not locate executable lf95
> customize PGroupFCompiler
> Could not locate executable pgf90
> Could not locate executable pgf77
> customize AbsoftFCompiler
> Could not locate executable f90
> customize NAGFCompiler
> Found executable /usr/bin/f95
> customize VastFCompiler
> customize CompaqFCompiler
> Could not locate executable fort
> customize IntelItaniumFCompiler
> Could not locate executable efort
> Could not locate executable efc
> customize IntelEM64TFCompiler
> customize Gnu95FCompiler
> Found executable /usr/bin/gfortran
> customize Gnu95FCompiler
> customize Gnu95FCompiler using config
> compiling '_configtest.c':
>
> /* This file is generated from numpy/distutils/system_info.py */
> void ATL_buildinfo(void);
> int main(void) {
> ?ATL_buildinfo();
> ?return 0;
> }
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-c'
> gcc: _configtest.c
> gcc -pthread _configtest.o -L/usr/lib/sse -lf77blas -lcblas -latlas -o
> _configtest
> ATLAS version 3.6.0 built by root on Fri Jan ?9 15:57:20 UTC 2004:
> ? UNAME ? ?: Linux intech67 2.4.20 #1 SMP Fri Jan 10 18:29:51 EST
> 2003 i686 GNU/Linux
> ? INSTFLG ?:
> ? MMDEF ? ?: /fix/g/camm/atlas3-3.6.0/CONFIG/ARCHS/P4SSE2/gcc/gemm
> ? ARCHDEF ?: /fix/g/camm/atlas3-3.6.0/CONFIG/ARCHS/P4SSE2/gcc/misc
> ? F2CDEFS ?: -DAdd__ -DStringSunStyle
> ? CACHEEDGE: 1048576
> ? F77 ? ? ?: /usr/bin/g77, version GNU Fortran (GCC) 3.3.3 20031229
> (prerelease) (Debian)
> ? F77FLAGS : -fomit-frame-pointer -O
> ? CC ? ? ? : /usr/bin/gcc, version gcc (GCC) 3.3.3 20031229
> (prerelease) (Debian)
> ? CC FLAGS : -fomit-frame-pointer -O3 -funroll-all-loops
> ? MCC ? ? ?: /usr/bin/gcc, version gcc (GCC) 3.3.3 20031229
> (prerelease) (Debian)
> ? MCCFLAGS : -fomit-frame-pointer -O
> success!
> removing: _configtest.c _configtest.o _configtest
> ?FOUND:
> ? ?libraries = ['f77blas', 'cblas', 'atlas']
> ? ?library_dirs = ['/usr/lib/sse']
> ? ?language = c
> ? ?define_macros = [('ATLAS_INFO', '"\\"3.6.0\\""')]
> ? ?include_dirs = ['/usr/include']
>
> ?FOUND:
> ? ?libraries = ['f77blas', 'cblas', 'atlas']
> ? ?library_dirs = ['/usr/lib/sse']
> ? ?language = c
> ? ?define_macros = [('ATLAS_INFO', '"\\"3.6.0\\""')]
> ? ?include_dirs = ['/usr/include']
>
> lapack_opt_info:
> lapack_mkl_info:
> mkl_info:
> ?libraries mkl,vml,guide not found in /usr/lib
> ?NOT AVAILABLE
>
> ?NOT AVAILABLE
>
> atlas_threads_info:
> Setting PTATLAS=ATLAS
> ?libraries ptf77blas,ptcblas,atlas not found in /usr/lib/atlas
> ?libraries lapack_atlas not found in /usr/lib/atlas
> ?libraries ptf77blas,ptcblas,atlas not found in /usr/lib/sse
> ?libraries ptf77blas,ptcblas,atlas not found in /usr/lib/sse2
> ?libraries ptf77blas,ptcblas,atlas not found in /usr/lib
> numpy.distutils.system_info.atlas_threads_info
> ?NOT AVAILABLE
>
> atlas_info:
> ?libraries f77blas,cblas,atlas not found in /usr/lib/atlas
> ?libraries lapack_atlas not found in /usr/lib/atlas
> ?libraries lapack not found in /usr/lib/sse
> numpy.distutils.system_info.atlas_info
> ?FOUND:
> ? ?libraries = ['lapack', 'f77blas', 'cblas', 'atlas']
> ? ?library_dirs = ['/usr/lib/sse/atlas', '/usr/lib/sse']
> ? ?language = f77
> ? ?define_macros = [('ATLAS_INFO', '"\\"3.6.0\\""')]
> ? ?include_dirs = ['/usr/include']
>
> ?FOUND:
> ? ?libraries = ['lapack', 'f77blas', 'cblas', 'atlas']
> ? ?library_dirs = ['/usr/lib/sse/atlas', '/usr/lib/sse']
> ? ?language = f77
> ? ?define_macros = [('ATLAS_INFO', '"\\"3.6.0\\""')]
> ? ?include_dirs = ['/usr/include']
>
> running install
> running build
> running config_cc
> unifing config_cc, config, build_clib, build_ext, build commands
> --compiler options
> running config_fc
> unifing config_fc, config, build_clib, build_ext, build commands
> --fcompiler options
> running build_src
> build_src
> building py_modules sources
> building library "npymath" sources
> customize GnuFCompiler
> customize IntelFCompiler
> customize LaheyFCompiler
> customize PGroupFCompiler
> customize AbsoftFCompiler
> customize NAGFCompiler
> customize VastFCompiler
> customize CompaqFCompiler
> customize IntelItaniumFCompiler
> customize IntelEM64TFCompiler
> customize Gnu95FCompiler
> customize Gnu95FCompiler
> customize Gnu95FCompiler using config
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> gcc -pthread _configtest.o -o _configtest
> success!
> removing: _configtest.c _configtest.o _configtest
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:1: warning: conflicting types for built-in function ?exp?
> gcc -pthread _configtest.o -o _configtest
> _configtest.o: In function `main':
> /home/ryan/Downloads/numpy-1.6.1/_configtest.c:6: undefined reference to `exp'
> collect2: ld returned 1 exit status
> _configtest.o: In function `main':
> /home/ryan/Downloads/numpy-1.6.1/_configtest.c:6: undefined reference to `exp'
> collect2: ld returned 1 exit status
> failure.
> removing: _configtest.c _configtest.o
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> _configtest.c:1: warning: conflicting types for built-in function ?exp?
> gcc -pthread _configtest.o -lm -o _configtest
> success!
> removing: _configtest.c _configtest.o _configtest
> building extension "numpy.core._sort" sources
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/config.h'
> to sources.
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h'
> to sources.
> executing numpy/core/code_generators/generate_numpy_api.py
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h'
> to sources.
> numpy.core - nothing done with h_files =
> ['build/src.linux-i686-2.6/numpy/core/include/numpy/config.h',
> 'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h',
> 'build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h']
> building extension "numpy.core.multiarray" sources
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/config.h'
> to sources.
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h'
> to sources.
> executing numpy/core/code_generators/generate_numpy_api.py
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h'
> to sources.
> numpy.core - nothing done with h_files =
> ['build/src.linux-i686-2.6/numpy/core/include/numpy/config.h',
> 'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h',
> 'build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h']
> building extension "numpy.core.umath" sources
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/config.h'
> to sources.
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h'
> to sources.
> executing numpy/core/code_generators/generate_ufunc_api.py
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/__ufunc_api.h'
> to sources.
> ?adding 'build/src.linux-i686-2.6/numpy/core/src/umath' to include_dirs.
> numpy.core - nothing done with h_files =
> ['build/src.linux-i686-2.6/numpy/core/src/umath/funcs.inc',
> 'build/src.linux-i686-2.6/numpy/core/include/numpy/config.h',
> 'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h',
> 'build/src.linux-i686-2.6/numpy/core/include/numpy/__ufunc_api.h']
> building extension "numpy.core.scalarmath" sources
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/config.h'
> to sources.
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h'
> to sources.
> executing numpy/core/code_generators/generate_numpy_api.py
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h'
> to sources.
> executing numpy/core/code_generators/generate_ufunc_api.py
> ?adding 'build/src.linux-i686-2.6/numpy/core/include/numpy/__ufunc_api.h'
> to sources.
> numpy.core - nothing done with h_files =
> ['build/src.linux-i686-2.6/numpy/core/include/numpy/config.h',
> 'build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h',
> 'build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h',
> 'build/src.linux-i686-2.6/numpy/core/include/numpy/__ufunc_api.h']
> building extension "numpy.core._dotblas" sources
> ?adding 'numpy/core/blasdot/_dotblas.c' to sources.
> building extension "numpy.core.umath_tests" sources
> building extension "numpy.core.multiarray_tests" sources
> building extension "numpy.lib._compiled_base" sources
> building extension "numpy.numarray._capi" sources
> building extension "numpy.fft.fftpack_lite" sources
> building extension "numpy.linalg.lapack_lite" sources
> ?adding 'numpy/linalg/lapack_litemodule.c' to sources.
> ?adding 'numpy/linalg/python_xerbla.c' to sources.
> building extension "numpy.random.mtrand" sources
> /home/ryan/Downloads/numpy-1.6.1/numpy/distutils/command/config.py:40:
> DeprecationWarning:
> +++++++++++++++++++++++++++++++++++++++++++++++++
> Usage of try_run is deprecated: please do not
> use it anymore, and avoid configuration checks
> involving running executable on the target machine.
> +++++++++++++++++++++++++++++++++++++++++++++++++
>
> ?DeprecationWarning)
> C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2
> -Wall -Wstrict-prototypes -fPIC
>
> compile options: '-Inumpy/core/src/private -Inumpy/core/src
> -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray
> -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6
> -c'
> gcc: _configtest.c
> gcc -pthread _configtest.o -o _configtest
> _configtest
> failure.
> removing: _configtest.c _configtest.o _configtest
> building data_files sources
> build_src: building npy-pkg config files
> running build_py
> copying numpy/version.py -> build/lib.linux-i686-2.6/numpy
> copying build/src.linux-i686-2.6/numpy/__config__.py ->
> build/lib.linux-i686-2.6/numpy
> copying build/src.linux-i686-2.6/numpy/distutils/__config__.py ->
> build/lib.linux-i686-2.6/numpy/distutils
> running build_clib
> customize UnixCCompiler
> customize UnixCCompiler using build_clib
> running build_ext
> customize UnixCCompiler
> customize UnixCCompiler using build_ext
> customize GnuFCompiler
> customize IntelFCompiler
> customize LaheyFCompiler
> customize PGroupFCompiler
> customize AbsoftFCompiler
> customize NAGFCompiler
> customize VastFCompiler
> customize CompaqFCompiler
> customize IntelItaniumFCompiler
> customize IntelEM64TFCompiler
> customize Gnu95FCompiler
> customize Gnu95FCompiler
> customize Gnu95FCompiler using build_ext
> running scons
> running build_scripts
> ?adding 'build/scripts.linux-i686-2.6/f2py' to scripts
> running install_lib
> copying build/lib.linux-i686-2.6/numpy/numarray/_capi.so ->
> /usr/local/lib/python2.6/dist-packages/numpy/numarray
> copying build/lib.linux-i686-2.6/numpy/version.py ->
> /usr/local/lib/python2.6/dist-packages/numpy
> copying build/lib.linux-i686-2.6/numpy/distutils/__config__.py ->
> /usr/local/lib/python2.6/dist-packages/numpy/distutils
> copying build/lib.linux-i686-2.6/numpy/__config__.py ->
> /usr/local/lib/python2.6/dist-packages/numpy
> copying build/lib.linux-i686-2.6/numpy/random/mtrand.so ->
> /usr/local/lib/python2.6/dist-packages/numpy/random
> copying build/lib.linux-i686-2.6/numpy/linalg/lapack_lite.so ->
> /usr/local/lib/python2.6/dist-packages/numpy/linalg
> copying build/lib.linux-i686-2.6/numpy/core/_dotblas.so ->
> /usr/local/lib/python2.6/dist-packages/numpy/core
> copying build/lib.linux-i686-2.6/numpy/core/umath.so ->
> /usr/local/lib/python2.6/dist-packages/numpy/core
> copying build/lib.linux-i686-2.6/numpy/core/_sort.so ->
> /usr/local/lib/python2.6/dist-packages/numpy/core
> copying build/lib.linux-i686-2.6/numpy/core/umath_tests.so ->
> /usr/local/lib/python2.6/dist-packages/numpy/core
> copying build/lib.linux-i686-2.6/numpy/core/multiarray.so ->
> /usr/local/lib/python2.6/dist-packages/numpy/core
> copying build/lib.linux-i686-2.6/numpy/core/multiarray_tests.so ->
> /usr/local/lib/python2.6/dist-packages/numpy/core
> copying build/lib.linux-i686-2.6/numpy/core/scalarmath.so ->
> /usr/local/lib/python2.6/dist-packages/numpy/core
> copying build/lib.linux-i686-2.6/numpy/lib/_compiled_base.so ->
> /usr/local/lib/python2.6/dist-packages/numpy/lib
> copying build/lib.linux-i686-2.6/numpy/fft/fftpack_lite.so ->
> /usr/local/lib/python2.6/dist-packages/numpy/fft
> byte-compiling /usr/local/lib/python2.6/dist-packages/numpy/version.py
> to version.pyc
> byte-compiling /usr/local/lib/python2.6/dist-packages/numpy/distutils/__config__.py
> to __config__.pyc
> byte-compiling /usr/local/lib/python2.6/dist-packages/numpy/__config__.py
> to __config__.pyc
> running install_scripts
> copying build/scripts.linux-i686-2.6/f2py -> /usr/local/bin
> changing mode of /usr/local/bin/f2py to 755
> running install_data
> copying build/src.linux-i686-2.6/numpy/core/include/numpy/_numpyconfig.h
> -> /usr/local/lib/python2.6/dist-packages/numpy/core/include/numpy
> copying build/src.linux-i686-2.6/numpy/core/include/numpy/__multiarray_api.h
> -> /usr/local/lib/python2.6/dist-packages/numpy/core/include/numpy
> copying build/src.linux-i686-2.6/numpy/core/include/numpy/multiarray_api.txt
> -> /usr/local/lib/python2.6/dist-packages/numpy/core/include/numpy
> copying build/src.linux-i686-2.6/numpy/core/include/numpy/__ufunc_api.h
> -> /usr/local/lib/python2.6/dist-packages/numpy/core/include/numpy
> copying build/src.linux-i686-2.6/numpy/core/include/numpy/ufunc_api.txt
> -> /usr/local/lib/python2.6/dist-packages/numpy/core/include/numpy
> copying build/src.linux-i686-2.6/numpy/core/lib/npy-pkg-config/npymath.ini
> -> /usr/local/lib/python2.6/dist-packages/numpy/core/lib/npy-pkg-config
> copying build/src.linux-i686-2.6/numpy/core/lib/npy-pkg-config/mlib.ini
> -> /usr/local/lib/python2.6/dist-packages/numpy/core/lib/npy-pkg-config
> running install_egg_info
> Removing /usr/local/lib/python2.6/dist-packages/numpy-1.6.1.egg-info
> Writing /usr/local/lib/python2.6/dist-packages/numpy-1.6.1.egg-info
> running install_clib
> copying build/temp.linux-i686-2.6/libnpymath.a ->
> /usr/local/lib/python2.6/dist-packages/numpy/core/lib
>
>
> Thanks,
>
> Ryan


From klonuo at gmail.com  Sun Jan  8 06:07:58 2012
From: klonuo at gmail.com (klo uo)
Date: Sun, 8 Jan 2012 12:07:58 +0100
Subject: [SciPy-User] List Scipy submodules programatically
Message-ID: <CAA-8Ld8QGO-ffS6rYdxAmUbKs1wUKcn_C4KrHP+QrH1eTe_q=g@mail.gmail.com>

I first tried with dir(scipy), then by using help from python modules
pyclbr and inspect, but I just can't find how to get this sub-packages
listed programatically from within script

I mean about this:
http://docs.scipy.org/doc/scipy/reference/tutorial/general.html#scipy-organization

What I'm missing?
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From robert.kern at gmail.com  Sun Jan  8 06:15:12 2012
From: robert.kern at gmail.com (Robert Kern)
Date: Sun, 8 Jan 2012 11:15:12 +0000
Subject: [SciPy-User] List Scipy submodules programatically
In-Reply-To: <CAA-8Ld8QGO-ffS6rYdxAmUbKs1wUKcn_C4KrHP+QrH1eTe_q=g@mail.gmail.com>
References: <CAA-8Ld8QGO-ffS6rYdxAmUbKs1wUKcn_C4KrHP+QrH1eTe_q=g@mail.gmail.com>
Message-ID: <CAF6FJit5N45xqOtnX3ouhZMRsWDZaTjA5SH-6s7VLcRwtJw2Fw@mail.gmail.com>

On Sun, Jan 8, 2012 at 11:07, klo uo <klonuo at gmail.com> wrote:
> I first tried with dir(scipy), then by using help from python modules pyclbr
> and inspect, but I just can't find how to get this sub-packages listed
> programatically from within script
>
> I mean about this:
> http://docs.scipy.org/doc/scipy/reference/tutorial/general.html#scipy-organization
>
> What I'm missing?

scipy/__init__.py does not import the subpackages itself; it's too
expensive to import all of them every time. So dir(scipy) won't work
nor will anything else that is depending on the modules to already be
imported. You need to find the directory containing scipy/__init__.py
[os.path.dirname(scipy.__file__)] and then look in that directory for
subdirectories with __init__.py files in them.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad attempt to interpret it as
though it had an underlying truth."
? -- Umberto Eco


From klonuo at gmail.com  Sun Jan  8 06:42:56 2012
From: klonuo at gmail.com (klo uo)
Date: Sun, 8 Jan 2012 12:42:56 +0100
Subject: [SciPy-User] List Scipy submodules programatically
In-Reply-To: <CAF6FJit5N45xqOtnX3ouhZMRsWDZaTjA5SH-6s7VLcRwtJw2Fw@mail.gmail.com>
References: <CAA-8Ld8QGO-ffS6rYdxAmUbKs1wUKcn_C4KrHP+QrH1eTe_q=g@mail.gmail.com>
	<CAF6FJit5N45xqOtnX3ouhZMRsWDZaTjA5SH-6s7VLcRwtJw2Fw@mail.gmail.com>
Message-ID: <CAA-8Ld85U4+Ve7_EvZGR1vZ1RBrxPY3N=iFtgvGtcwMqYxdLGw@mail.gmail.com>

Thanks, it shows fine that way

==================================================
import os, scipy

scipy_dir = os.path.dirname(scipy.__file__)
print [d for d in os.listdir(scipy_dir) if
os.path.isfile(os.path.join(scipy_dir, d + '/__init__.py'))]
==================================================


On Sun, Jan 8, 2012 at 12:15 PM, Robert Kern <robert.kern at gmail.com> wrote:

> os.path.dirname(scipy.__file__)
>
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From victor.larie at gmail.com  Sun Jan  8 07:59:14 2012
From: victor.larie at gmail.com (Victor Larie)
Date: Sun, 8 Jan 2012 14:59:14 +0200
Subject: [SciPy-User] Equivalent for matlab interpft
Message-ID: <CAHsGqM8NVhN2WAkE_CwvLWgm+-jG1MSidCvHARfCX-6t6+zKqA@mail.gmail.com>

Hi there!

It's my first question on this list, pretty new with scipy and the dsp
world also.

I've been trying to find a scypy/numpy implementation (or way to do it) for
the matlab 1-D interpolation using FFT (interpft).
It's eithter too simple or I just couldn't find it.

No luck so far, I guess any suggestion is more than welcomed.

Regards,
Victor
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From josef.pktd at gmail.com  Sun Jan  8 08:20:07 2012
From: josef.pktd at gmail.com (josef.pktd at gmail.com)
Date: Sun, 8 Jan 2012 08:20:07 -0500
Subject: [SciPy-User] Equivalent for matlab interpft
In-Reply-To: <CAHsGqM8NVhN2WAkE_CwvLWgm+-jG1MSidCvHARfCX-6t6+zKqA@mail.gmail.com>
References: <CAHsGqM8NVhN2WAkE_CwvLWgm+-jG1MSidCvHARfCX-6t6+zKqA@mail.gmail.com>
Message-ID: <CAMMTP+CtS0t3w+3SdOBzxKSoQ4R-3n6MphgA0kF=OV2YSQNKOQ@mail.gmail.com>

On Sun, Jan 8, 2012 at 7:59 AM, Victor Larie <victor.larie at gmail.com> wrote:
> Hi there!
>
> It's my first question on this list, pretty new with scipy and the dsp world
> also.
>
> I've been trying to find a scypy/numpy implementation (or way to do it) for
> the matlab 1-D interpolation using FFT (interpft).
> It's eithter too simple or I just couldn't find it.
>
> No luck so far, I guess any suggestion is more than welcomed.

scipy.signal.resample might do what you want

there might be something in ndimage, but I don't know whether it uses fft.

Josef

>
> Regards,
> Victor
>
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user
>


From zachary.pincus at yale.edu  Sun Jan  8 10:30:40 2012
From: zachary.pincus at yale.edu (Zachary Pincus)
Date: Sun, 8 Jan 2012 10:30:40 -0500
Subject: [SciPy-User] Equivalent for matlab interpft
In-Reply-To: <CAMMTP+CtS0t3w+3SdOBzxKSoQ4R-3n6MphgA0kF=OV2YSQNKOQ@mail.gmail.com>
References: <CAHsGqM8NVhN2WAkE_CwvLWgm+-jG1MSidCvHARfCX-6t6+zKqA@mail.gmail.com>
	<CAMMTP+CtS0t3w+3SdOBzxKSoQ4R-3n6MphgA0kF=OV2YSQNKOQ@mail.gmail.com>
Message-ID: <E87F3D36-7AAA-4E4C-9834-7133980468D3@yale.edu>

>> I've been trying to find a scypy/numpy implementation (or way to do it) for
>> the matlab 1-D interpolation using FFT (interpft).
>> It's eithter too simple or I just couldn't find it.
>> 
>> No luck so far, I guess any suggestion is more than welcomed.
> 
> scipy.signal.resample might do what you want
> 
> there might be something in ndimage, but I don't know whether it uses fft.

The stuff in scipy.ndimage (zoom(), map_coordinates(), etc.) uses interpolating splines (order 0 to 5, user-specified) -- which, FYI, can be a bit prone to ringing in some cases.

scipy.signal.resample() uses FFTs, though I don't know if the implementation is identical to that in Matlab. Lots of options for windowing functions to avoid ringing, though.

Zach

From Phillip.M.Feldman at gmail.com  Sun Jan  8 01:54:23 2012
From: Phillip.M.Feldman at gmail.com (Dr. Phillip M. Feldman)
Date: Sat, 7 Jan 2012 22:54:23 -0800 (PST)
Subject: [SciPy-User] [SciPy-user] optimization with nonlinear constraints
Message-ID: <33101263.post@talk.nabble.com>


>From the SciPy documentation, it looks as though there's no way to do
optimization with nonlinear constraints.  Have I overlooked something?  If
not, then this seems like a fairly important omission.
-- 
View this message in context: http://old.nabble.com/optimization-with-nonlinear-constraints-tp33101263p33101263.html
Sent from the Scipy-User mailing list archive at Nabble.com.



From robert.kern at gmail.com  Mon Jan  9 09:52:19 2012
From: robert.kern at gmail.com (Robert Kern)
Date: Mon, 9 Jan 2012 14:52:19 +0000
Subject: [SciPy-User] [SciPy-user] optimization with nonlinear
	constraints
In-Reply-To: <33101263.post@talk.nabble.com>
References: <33101263.post@talk.nabble.com>
Message-ID: <CAF6FJit_fQRO1h62-w7GJeYTH-FYAt3iXT9Fdn+dfMaLepsQBQ@mail.gmail.com>

On Sun, Jan 8, 2012 at 06:54, Dr. Phillip M. Feldman
<Phillip.M.Feldman at gmail.com> wrote:
>
> >From the SciPy documentation, it looks as though there's no way to do
> optimization with nonlinear constraints. ?Have I overlooked something? ?If
> not, then this seems like a fairly important omission.

http://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.fmin_cobyla.html

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad attempt to interpret it as
though it had an underlying truth."
? -- Umberto Eco


From josef.pktd at gmail.com  Mon Jan  9 10:39:39 2012
From: josef.pktd at gmail.com (josef.pktd at gmail.com)
Date: Mon, 9 Jan 2012 10:39:39 -0500
Subject: [SciPy-User] [SciPy-user] optimization with nonlinear
	constraints
In-Reply-To: <CAF6FJit_fQRO1h62-w7GJeYTH-FYAt3iXT9Fdn+dfMaLepsQBQ@mail.gmail.com>
References: <33101263.post@talk.nabble.com>
	<CAF6FJit_fQRO1h62-w7GJeYTH-FYAt3iXT9Fdn+dfMaLepsQBQ@mail.gmail.com>
Message-ID: <CAMMTP+AF-TUEGiDq8FB8ojsTB-Z+yo100kric1DOo_JT5VEmaw@mail.gmail.com>

On Mon, Jan 9, 2012 at 9:52 AM, Robert Kern <robert.kern at gmail.com> wrote:
> On Sun, Jan 8, 2012 at 06:54, Dr. Phillip M. Feldman
> <Phillip.M.Feldman at gmail.com> wrote:
>>
>> >From the SciPy documentation, it looks as though there's no way to do
>> optimization with nonlinear constraints. ?Have I overlooked something? ?If
>> not, then this seems like a fairly important omission.
>
> http://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.fmin_cobyla.html

and some more

http://docs.scipy.org/doc/scipy/reference/optimize.html#constrained-multivariate

Josef

>
> --
> Robert Kern
>
> "I have come to believe that the whole world is an enigma, a harmless
> enigma that is made terrible by our own mad attempt to interpret it as
> though it had an underlying truth."
> ? -- Umberto Eco
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user


From klonuo at gmail.com  Mon Jan  9 13:56:50 2012
From: klonuo at gmail.com (klo uo)
Date: Mon, 9 Jan 2012 19:56:50 +0100
Subject: [SciPy-User] Trouble using curve_fit
Message-ID: <CAA-8Ld8pwJp0jcqW9i=THOuU+n51Cd6csetp1f-Jod9pAbT95g@mail.gmail.com>

Example provided at the bottom of this page:
scipy.optimize.curve_fit<http://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.curve_fit.html#scipy.optimize.curve_fit>seemed
perfect for what I hoped I need, but result was bad. I don't know if
I misuse it or I don't have enough data, but as can be seen from attached
screen-shot, I did not expect problem for finding obvious exponential
function fit.

Here is snippet:
========================================
import numpy as np
from scipy.optimize import curve_fit

def func(x, a, b, c):
    return a*np.exp(-b*x)+c

x = np.array([ 0.8, 11., 12., 16., 32., 37.8, 44., 48., 56., 64., 88., 96.,
112., 128., 144., 176., 192. ])
y = np.array([0.94597685600279, 0.95856916599601, 0.96009142950541,
0.96454515552826, 0.97938932735214, 0.98252400815195, 0.98500175787242,
0.98621192462708, 0.98816995007392, 0.98964101933472, 0.99247255046129,
0.99308203517541, 0.99406737810867, 0.99480702681278, 0.99538268958706,
0.99622916581118, 0.99653501465135])

popt, pcov = curve_fit(func, x, y)
popt

Out[]: array([ 164.57396829  206.83406927    0.98251156])
========================================

I then found this page:
wolfram<http://mathworld.wolfram.com/LeastSquaresFittingExponential.html>and
quickly

========================================
def lsq_exp(x, y):
#   return A and B in y=A*exp(B*x)

    from numpy import exp, log, sum

    n = len(x)
    a_num = (log(y)).sum() * (x**2).sum() - x.sum() * (x*log(y)).sum()
    b_num = n*(x*log(y)).sum() - x.sum() * (log(y)).sum()
    den = n*(x**2).sum() - (x.sum())**2

    A = exp(a_num/den)
    b = b_num/den

    return A,b
========================================
result coefficients: (0.96677003283750318, 0.00021665429178716782)

What is wrong with this approach?
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From robert.kern at gmail.com  Mon Jan  9 14:07:24 2012
From: robert.kern at gmail.com (Robert Kern)
Date: Mon, 9 Jan 2012 19:07:24 +0000
Subject: [SciPy-User] Trouble using curve_fit
In-Reply-To: <CAA-8Ld8pwJp0jcqW9i=THOuU+n51Cd6csetp1f-Jod9pAbT95g@mail.gmail.com>
References: <CAA-8Ld8pwJp0jcqW9i=THOuU+n51Cd6csetp1f-Jod9pAbT95g@mail.gmail.com>
Message-ID: <CAF6FJiuTebF2tQVoTWGHLQPUcc6S9=KqkeyRTvyATqHY0TENAg@mail.gmail.com>

On Mon, Jan 9, 2012 at 18:56, klo uo <klonuo at gmail.com> wrote:
> Example provided at the bottom of this page: scipy.optimize.curve_fit seemed
> perfect for what I hoped I need, but result was bad. I don't know if I
> misuse it or I don't have enough data, but as can be seen from attached
> screen-shot, I did not expect problem for finding obvious exponential
> function fit.
>
> Here is snippet:
> ========================================
> import numpy as np
> from scipy.optimize import curve_fit
>
> def func(x, a, b, c):
> ??? return a*np.exp(-b*x)+c
>
> x = np.array([ 0.8, 11., 12., 16., 32., 37.8, 44., 48., 56., 64., 88., 96.,
> 112., 128., 144., 176., 192. ])
> y = np.array([0.94597685600279, 0.95856916599601, 0.96009142950541,
> 0.96454515552826, 0.97938932735214, 0.98252400815195, 0.98500175787242,
> 0.98621192462708, 0.98816995007392, 0.98964101933472, 0.99247255046129,
> 0.99308203517541, 0.99406737810867, 0.99480702681278, 0.99538268958706,
> 0.99622916581118, 0.99653501465135])
>
> popt, pcov = curve_fit(func, x, y)
> popt
>
> Out[]: array([ 164.57396829? 206.83406927??? 0.98251156])
> ========================================

The initial parameters often matter a lot, particularly when
exponentials are involved. The default is just (1, 1, 1). If you start
with a negative initial value for `a`, then you will converge to the
right answer better. Try this:

  popt, pcov = curve_fit(func, x, y, [-1, 1, 1])

> I then found this page: wolfram and quickly
>
> ========================================
> def lsq_exp(x, y):
> #?? return A and B in y=A*exp(B*x)

That's missing the constant term, so it's not even the same model.
That's why it isn't giving you an answer that makes sense for your
data.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad attempt to interpret it as
though it had an underlying truth."
? -- Umberto Eco


From klonuo at gmail.com  Mon Jan  9 14:28:51 2012
From: klonuo at gmail.com (klo uo)
Date: Mon, 9 Jan 2012 20:28:51 +0100
Subject: [SciPy-User] Trouble using curve_fit
In-Reply-To: <CAF6FJiuTebF2tQVoTWGHLQPUcc6S9=KqkeyRTvyATqHY0TENAg@mail.gmail.com>
References: <CAA-8Ld8pwJp0jcqW9i=THOuU+n51Cd6csetp1f-Jod9pAbT95g@mail.gmail.com>
	<CAF6FJiuTebF2tQVoTWGHLQPUcc6S9=KqkeyRTvyATqHY0TENAg@mail.gmail.com>
Message-ID: <CAA-8Ld92QDYpEGPaQ3Tpj0Y5DsB-tzRfooayUe1XQnaThoJ0sQ@mail.gmail.com>

On Mon, Jan 9, 2012 at 8:07 PM, Robert Kern <robert.kern at gmail.com> wrote:

> The initial parameters often matter a lot, particularly when
> exponentials are involved. The default is just (1, 1, 1). If you start
> with a negative initial value for `a`, then you will converge to the
> right answer better. Try this:
>
>  popt, pcov = curve_fit(func, x, y, [-1, 1, 1])
>
>
That, just perfect :)

Thanks for your fast reply and explanation
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From aia8v at virginia.edu  Tue Jan 10 09:10:21 2012
From: aia8v at virginia.edu (alex arsenovic)
Date: Tue, 10 Jan 2012 09:10:21 -0500
Subject: [SciPy-User] numpydoc,  show attributes in autoclass output
Message-ID: <1326204621.1927.16.camel@wang>

i am using the numpydoc sphinx extensions, and would like to modify the
way in which the autoclass feature works. right now, i am generating the
class's page using autosummary and only the class's methods are shown. i
would like to have the class's attributes displayed as well. 

 i have looked at the template in
sphinx/source/_template/autosummary/class.rst, and understand what its
doing and how to work with it, but the numpydoc appears to  be doing
something itself, modifying sphinx's autoclass behavior. 

i poked around and found the cfg option 'numpydoc_show_class_members'.
while this does control whether or not the class methods are included
when it is set in sphinx/source/conf.py, it doesnt control include the
class's attributes, even though it appears as though it should by
inspecting its usage in sphinx_ext/docscrape.py.

at the moment i have disabled the 'numpydoc_show_class_members', and
used the sphinx class.rst template to do what i need, but would be
interested to have it working through the numpydoc. 


thanks!

alex



From tim.gallagher at gatech.edu  Tue Jan 10 14:34:11 2012
From: tim.gallagher at gatech.edu (Tim Gallagher)
Date: Tue, 10 Jan 2012 14:34:11 -0500 (EST)
Subject: [SciPy-User] ODE Integration error
In-Reply-To: <251e0953-d2f1-48a4-b2a7-a9fc5b1b2fef@mail2.gatech.edu>
Message-ID: <327f55f8-ea26-455c-b15f-f6d6fc7491e3@mail2.gatech.edu>

Hi,

I'm trying to use the 'vode' solver in scipy.integrate.ode (in version 0.10.0) and I get the following error:

 DVODE--  RWORK length needed, LENRW (=I1), exceeds LRW (=I2)
      In above message,  I1 =      7328   I2 =        56

I don't see any arguments to anything I can use to determine workspace sizes. I'm sure I did something incorrectly in my calling code, but I don't know how to find out from this error. 

Any suggestions?

Tim


From telnet2 at gmail.com  Tue Jan 10 23:46:07 2012
From: telnet2 at gmail.com (Joohwi Lee)
Date: Tue, 10 Jan 2012 23:46:07 -0500
Subject: [SciPy-User] cs_graph_componets returning wrong results?
Message-ID: <CAM_upJRESKbav3h-+TcW=T27_9gO0u=Vw=UPmKmFaYeSd0GYkw@mail.gmail.com>

Hi All,

To identify connected components of a graph, I am trying to use
'scipy.sparse.cs_graph_components()' function.

The adjacency graph looks like
array([[1, 0, 0, 0, 1],
       [0, 1, 1, 1, 1],
       [0, 0, 1, 1, 1],
       [0, 0, 0, 1, 1],
       [0, 0, 0, 0, 1]])

The graph is actually consisting of (1 -> (5 = 2 = 3 = 4) ), where
(2,3,4,5) are connected each other and 1 is only connected to 5.

I expect cs_graph_components(x) should return (1, [0,0,0,0,0]) which means
that there is only one component, but it returns (2, array([0, 1, 1, 1, 0],
dtype=int32)).
(1-5) & (2-3-4).

Is this correct result?


- joohwi
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From gael.varoquaux at normalesup.org  Wed Jan 11 01:27:06 2012
From: gael.varoquaux at normalesup.org (Gael Varoquaux)
Date: Wed, 11 Jan 2012 07:27:06 +0100
Subject: [SciPy-User] cs_graph_componets returning wrong results?
In-Reply-To: <CAM_upJRESKbav3h-+TcW=T27_9gO0u=Vw=UPmKmFaYeSd0GYkw@mail.gmail.com>
References: <CAM_upJRESKbav3h-+TcW=T27_9gO0u=Vw=UPmKmFaYeSd0GYkw@mail.gmail.com>
Message-ID: <20120111062706.GA27807@phare.normalesup.org>

On Tue, Jan 10, 2012 at 11:46:07PM -0500, Joohwi Lee wrote:
>    To identify connected components of a graph, I am trying to use
>    'scipy.sparse.cs_graph_components()' function.
>    The adjacency graph looks like
>    array([[1, 0, 0, 0, 1],
>    ? ? ? ?[0, 1, 1, 1, 1],
>    ? ? ? ?[0, 0, 1, 1, 1],
>    ? ? ? ?[0, 0, 0, 1, 1],
>    ? ? ? ?[0, 0, 0, 0, 1]])
>    The graph is actually consisting of (1 -> (5 = 2 = 3 = 4) ), where
>    (2,3,4,5) are connected each other and 1 is only connected to 5.
>    I expect cs_graph_components(x) should return (1, [0,0,0,0,0]) which means
>    that there is only one component, but it returns?(2, array([0, 1, 1, 1,
>    0], dtype=int32)).

Indeed, the answer that you are getting is wrong. That said, you are
giving it a non symmetric matrix. If you give it a symmetric version of
this graph it works as it should:

In [12]: sparse.cs_graph_components(a + a.T - np.eye(5))
Out[12]: (1, array([0, 0, 0, 0, 0]))

Now the docstring says that only the upper triangular part of the matrix
is used. This docstring is clearly wrong in the current state. I'll try
and fix that.

HTH,

Gael


From klonuo at gmail.com  Wed Jan 11 02:11:34 2012
From: klonuo at gmail.com (klo uo)
Date: Wed, 11 Jan 2012 08:11:34 +0100
Subject: [SciPy-User] Lookfor in SciPy sub-packages?
Message-ID: <CAA-8Ld-=c85T48GeDy=XncFinpWz9EaN--Yf2SYOsnVk=1KWvg@mail.gmail.com>

I just discovered this nifty NumPy utils.py module.
Among various useful information retrival functions (as it can be imagined
by wrapping pydoc, inspect and re modules) there is also 'lookfor', for
which I even quickly made GTK input box ;)

However seaching for something within SciPy sub-packages seems pretty
impossible to me. I tried various combinations but nothing worked.
Can someone provide tip how to return result for 'Butterworth' for example,
without loading scipy.signal inside script then passing this module to
lookfor function, which seems lake a overkill to this function purpose
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From gael.varoquaux at normalesup.org  Wed Jan 11 06:01:15 2012
From: gael.varoquaux at normalesup.org (Gael Varoquaux)
Date: Wed, 11 Jan 2012 12:01:15 +0100
Subject: [SciPy-User] cs_graph_componets returning wrong results?
In-Reply-To: <20120111062706.GA27807@phare.normalesup.org>
References: <CAM_upJRESKbav3h-+TcW=T27_9gO0u=Vw=UPmKmFaYeSd0GYkw@mail.gmail.com>
	<20120111062706.GA27807@phare.normalesup.org>
Message-ID: <20120111110115.GB4696@phare.normalesup.org>

On Wed, Jan 11, 2012 at 07:27:06AM +0100, Gael Varoquaux wrote:
> Now the docstring says that only the upper triangular part of the matrix
> is used. This docstring is clearly wrong in the current state. I'll try
> and fix that.

I have been looking at that problem more closely, and I have pretty much
come to the conclusion that there is no good way of cheaply finding
connected components with non symmetric adjacency matrix.

Technically this boils down to the fact that connect components
algorithms do a graph traversal. With the CSR representation (used by the
algorithm) this graph traversal is cheap only in one direction (jumping
from row to columns). If the adjacency matrix is not symmetric, we are
thus doing a graph traversal on a directed graph, and the connected
component found will be the descendant of the starting nodes.

The cost of building the lookup tables to do traversal in the opposite
direction is pretty much the cost of making the matrix symmetrical. Thus
it seems to me that for such a low level algorithm it is better to simply
tell the user that the input matrix should be symmetric and leave it to
them to comply.

If people agree, I'll just modify the docstring to point this out.

Ga?l


From rob.clewley at gmail.com  Wed Jan 11 13:32:09 2012
From: rob.clewley at gmail.com (Rob Clewley)
Date: Wed, 11 Jan 2012 13:32:09 -0500
Subject: [SciPy-User] ODE Integration error
In-Reply-To: <327f55f8-ea26-455c-b15f-f6d6fc7491e3@mail2.gatech.edu>
References: <251e0953-d2f1-48a4-b2a7-a9fc5b1b2fef@mail2.gatech.edu>
	<327f55f8-ea26-455c-b15f-f6d6fc7491e3@mail2.gatech.edu>
Message-ID: <CA+7tCyQsbZv=7NOQjyEKUSOhuJbWXnxS78eXz=OqdvwXx9m+DQ@mail.gmail.com>

You'll need to post your full code to reproduce the problem for list
members to see what is wrong.
-Rob

On Tue, Jan 10, 2012 at 2:34 PM, Tim Gallagher <tim.gallagher at gatech.edu> wrote:
> Hi,
>
> I'm trying to use the 'vode' solver in scipy.integrate.ode (in version 0.10.0) and I get the following error:
>
> ?DVODE-- ?RWORK length needed, LENRW (=I1), exceeds LRW (=I2)
> ? ? ?In above message, ?I1 = ? ? ?7328 ? I2 = ? ? ? ?56
>
> I don't see any arguments to anything I can use to determine workspace sizes. I'm sure I did something incorrectly in my calling code, but I don't know how to find out from this error.
>
> Any suggestions?
>
> Tim
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user


From klonuo at gmail.com  Thu Jan 12 02:12:57 2012
From: klonuo at gmail.com (klo uo)
Date: Thu, 12 Jan 2012 08:12:57 +0100
Subject: [SciPy-User] Lookfor in SciPy sub-packages?
In-Reply-To: <CAA-8Ld-=c85T48GeDy=XncFinpWz9EaN--Yf2SYOsnVk=1KWvg@mail.gmail.com>
References: <CAA-8Ld-=c85T48GeDy=XncFinpWz9EaN--Yf2SYOsnVk=1KWvg@mail.gmail.com>
Message-ID: <CAA-8Ld-hVZqi4gcpMhr=13G5RjBPfsxOqUvqfhd8NT=mHwn9mA@mail.gmail.com>

I must have made some mistake, yesterday if possible

nympy.lib.utils.lookfor('something', 'scipy') *does* load scipy
sub-packages also (even by default) and what's more, now I don't even need
to import scipy module (I pass it as string).
I'm sure it wasn't like this yesterday for some reason

Sorry for confusion

Cheers


On Wed, Jan 11, 2012 at 8:11 AM, klo uo <klonuo at gmail.com> wrote:

> I just discovered this nifty NumPy utils.py module.
> Among various useful information retrival functions (as it can be imagined
> by wrapping pydoc, inspect and re modules) there is also 'lookfor', for
> which I even quickly made GTK input box ;)
>
> However seaching for something within SciPy sub-packages seems pretty
> impossible to me. I tried various combinations but nothing worked.
> Can someone provide tip how to return result for 'Butterworth' for
> example, without loading scipy.signal inside script then passing this
> module to lookfor function, which seems lake a overkill to this function
> purpose
>
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From hendrik.venter1 at gmail.com  Wed Jan 11 12:01:24 2012
From: hendrik.venter1 at gmail.com (Hendrik)
Date: Wed, 11 Jan 2012 09:01:24 -0800 (PST)
Subject: [SciPy-User] Scipy.optimize.fmin_slsqp problem
Message-ID: <5acee2cb-a3f5-4e18-b6d0-223ff30ff875@t13g2000vbt.googlegroups.com>

Hey Folks!! I'm new to the Forum world. I looked for a topic on
optimization, but didn't see one, so sorry if I'm duplicating...

I run Python 2.6.6.1

I'm using scipy.optimize.fmin_slsqp  to solve a non-linear function
but it only returns the function value with the initial guess
values... Can you please help???

Below this message is my program... I'm struggling with this problem
for over 3 months now, asking for advice with no success!!

I want to minimize the function "changevars(self.gibbs)" within the
constraints "changevars(self.atombalance)".

The optimization program only returns the function value with the
initial guess values... And i don't know why.
When I run the program, I can see the minimum value graphically, but
the optimization can't calculate it...

Can you please help??

Regards

*************************************************************************************************************************************
#!/usr/bin/env python

# Calculate mixture equilibriums using minimisation of the Gibbs
energy

# 201110 Originally by Hendrik Venter
# 201111 Significantly reworked by Carl Sandrock

from __future__ import division
import scipy.optimize
import scipy.linalg
import math
import numpy
import atomparser
import sys
import matplotlib.pyplot as pl
from mpl_toolkits.mplot3d import axes3d
from matplotlib import cm

smallvalue = 1e-10
fig = pl.figure()
ax = fig.add_subplot(111, projection='3d')

T = 298.15
R = 8.314
RT = R*T
mustplot = 1    # 1 for Plotting, 0 for not plotting


class compound:
    """ Basic container for compound properties """
    def __init__(self, name, DGf):
        self.name = name
        self.DGf = DGf
        self.parsed = atomparser.parseformula(name)


class mixture:
    """ Container for mixture properties """
    def __init__(self, charge):
        """ Initialise mixture - charge contains tuples of
(initialcharge, compound) """
        self.N, self.compounds = zip(*charge)
        self.N = numpy.array(self.N)
        self.compoundnames = [c.name for c in self.compounds]
        self.DGf = numpy.array([c.DGf for c in self.compounds])
        self.elements = reduce(set.union,
(c.parsed.distinctelements()
                                            for c in self.compounds))
        self.S = numpy.array([c.parsed.counts(self.elements)
                                for c in self.compounds]).T
        Srank = numpy.count_nonzero(numpy.linalg.svd(self.S,
compute_uv=False) > smallvalue)

        # Calculating the Degrees of freedom
        self.DOF = self.S.shape[1] - Srank
        print 'Degrees of Freedom =', self.DOF

        # Coefficients of the Gibbs function
        Ncomps = len(self.compounds)
        # self.A = numpy.tile(numpy.repeat([-1, 1], [1, Ncomps-1]),
[Ncomps, 1])
        # number of atoms of each element
        self.atoms = numpy.dot(self.S, self.N)


    def gibbs(self, N=None):
        """ Gibbs energy of mixture with N of each compound """
        if N is None: N = self.N
        # TODO: There is every chance that this function is not
correct. It needs to be checked.
        #return sum(N*(self.DGf/(R*T) + numpy.log(numpy.dot(self.A,
N))))
        logs = numpy.log(sum(N))
        return sum(N*(self.DGf/RT + numpy.log(N) - logs))

    def atombalance(self, N):

        """ Atom balance with N of each compound """
        #if N is None: N = self.N
        return numpy.dot(self.S, N) - self.atoms


    def conversion(self, conversionspec):
        """ Calculate the composition given a certain conversion.
        conversionspec is a list of 2-tuples containing a component
index or name and a conversion """
        #TODO: A and B should only be calculated once
        #TODO: This does not take into account any existing products
in the mixture
        #TODO: This works only for conversion specified in terms of
reagents
        if len(conversionspec) < self.DOF:
            raise Exception("Not enough conversions specified.")
        C = numpy.zeros([len(conversionspec), self.S.shape[1]])
        Ic = C.copy()
        for i, (j, c) in enumerate(conversionspec):
            if type(j) is str:
                j = self.compoundnames.index(j)
            C[i, j] = 1-c
            Ic[i, j] = 1
        A = numpy.vstack([self.S, C])
        B = numpy.vstack([self.S, Ic])
        # A ni = B nf
        nf, _, _, _ = scipy.linalg.lstsq(B, numpy.dot(A, self.N))
        # assert residuals are neglegable
        nf[nf<0] = 0
        return nf

    def equilibrium(self, initialconversion):
        """ Return equilibrium composition as minimum of Gibbs Energy
"""
        # guess initial conditions
        N0 = self.conversion(initialconversion)
        logN0 = numpy.log(N0)

        # This decorator modifies a function to be defined in terms of
new variables
        def changevars(f):
            def newf(newX):
    #         print 'newX', newX
    #         print 'X', numpy.exp(newX)
                r = f(numpy.exp(newX))
    #          print 'f(X)', r
                return r
            return newf

        # Find optimal point in terms of a change of variables
        logN = scipy.optimize.fmin_slsqp(changevars(self.gibbs),
                                        logN0,
 
f_eqcons=changevars(self.atombalance),
                                        acc = 1.0E-12)
        scipy.optimize.fmin
        N = numpy.exp(logN)
        print ''
        print 'Calculated Optimmum Values'
        print N
        print ''
        print 'Calculated Optimum Function value'
        print m.gibbs(N)

        return N

    # Here for a particular mixture:
m = mixture([[1.,  compound('MgO',                      -568343.0)],
            [0.5, compound('Al2O3',                    -1152420.0)],
            [4.,  compound('H2O',                      -237141.0)],
            [0,   compound('Mg(OH)2',                  -833644.0)],
            [0,   compound('Al(OH)3',                  -1835750.0)]])


    # find Gibbs energy surface for many conversion possibilities
Nsteps = 10
convrange = numpy.linspace(0.001, 0.999, Nsteps)
gibbssurface = numpy.zeros((Nsteps, Nsteps))
for iMgO, xMgO in enumerate(convrange):
    for iAl2O3, xAl2O3 in enumerate(convrange):
        N = m.conversion([('MgO', xMgO),
                          ('Al2O3', xAl2O3/50)])
        gibbssurface[iMgO, iAl2O3] = m.gibbs(N)



# Try to find equilibrium
# Initial conversion guess
print ''
print "***************Optimizing******************"
X0 = [0.5, 0.5]
conversionspec = zip(['MgO', 'Al2O3'], X0)
# Solve to equilibrium
N = m.equilibrium(conversionspec)

print ''
print '*************Final Values***************'
for n, init, name in zip(N, m.N, m.compoundnames):
    print name, 'initial =', init, 'final =', n


# Plot results
if mustplot:
    Xaxis, Yaxis = numpy.meshgrid(convrange, convrange)
    Zaxis = gibbssurface
    surf = ax.plot_surface(Xaxis, Yaxis, Zaxis, rstride=1, cstride=1,
cmap=cm.jet, linewidth=0, antialiased=False)
    fig.colorbar(surf, shrink=0.5, aspect=5)
    ax.set_xlabel('Conversion of MgO')
    ax.set_ylabel('Conversion of Al2O3')
    ax.set_zlabel('Gibbs free energy (G/RT)')
    pl.show()



From josef.pktd at gmail.com  Thu Jan 12 10:13:03 2012
From: josef.pktd at gmail.com (josef.pktd at gmail.com)
Date: Thu, 12 Jan 2012 10:13:03 -0500
Subject: [SciPy-User] Scipy.optimize.fmin_slsqp problem
In-Reply-To: <5acee2cb-a3f5-4e18-b6d0-223ff30ff875@t13g2000vbt.googlegroups.com>
References: <5acee2cb-a3f5-4e18-b6d0-223ff30ff875@t13g2000vbt.googlegroups.com>
Message-ID: <CAMMTP+B11VWNPkxvMy2=sem5wz25_PM3=m1-SyfA1o-MvEXKdg@mail.gmail.com>

On Wed, Jan 11, 2012 at 12:01 PM, Hendrik <hendrik.venter1 at gmail.com> wrote:
> Hey Folks!! I'm new to the Forum world. I looked for a topic on
> optimization, but didn't see one, so sorry if I'm duplicating...
>
> I run Python 2.6.6.1
>
> I'm using scipy.optimize.fmin_slsqp ?to solve a non-linear function
> but it only returns the function value with the initial guess
> values... Can you please help???
>
> Below this message is my program... I'm struggling with this problem
> for over 3 months now, asking for advice with no success!!
>
> I want to minimize the function "changevars(self.gibbs)" within the
> constraints "changevars(self.atombalance)".
>
> The optimization program only returns the function value with the
> initial guess values... And i don't know why.
> When I run the program, I can see the minimum value graphically, but
> the optimization can't calculate it...

I have no idea what might be wrong, and I don't have an atomparser
available, so I cannot run the script.

What I would do to debug and see whether it's a coding problem or a
problem with slsqp is to convert the atombalance constraint into a
quadratic penalty (with a penalization factor that can be increased)
and see whether an approximate "unconstraint" solution can be found.

Josef

>
> Can you please help??
>
> Regards
>
> *************************************************************************************************************************************
> #!/usr/bin/env python
>
> # Calculate mixture equilibriums using minimisation of the Gibbs
> energy
>
> # 201110 Originally by Hendrik Venter
> # 201111 Significantly reworked by Carl Sandrock
>
> from __future__ import division
> import scipy.optimize
> import scipy.linalg
> import math
> import numpy
> import atomparser
> import sys
> import matplotlib.pyplot as pl
> from mpl_toolkits.mplot3d import axes3d
> from matplotlib import cm
>
> smallvalue = 1e-10
> fig = pl.figure()
> ax = fig.add_subplot(111, projection='3d')
>
> T = 298.15
> R = 8.314
> RT = R*T
> mustplot = 1 ? ?# 1 for Plotting, 0 for not plotting
>
>
> class compound:
> ? ?""" Basic container for compound properties """
> ? ?def __init__(self, name, DGf):
> ? ? ? ?self.name = name
> ? ? ? ?self.DGf = DGf
> ? ? ? ?self.parsed = atomparser.parseformula(name)
>
>
> class mixture:
> ? ?""" Container for mixture properties """
> ? ?def __init__(self, charge):
> ? ? ? ?""" Initialise mixture - charge contains tuples of
> (initialcharge, compound) """
> ? ? ? ?self.N, self.compounds = zip(*charge)
> ? ? ? ?self.N = numpy.array(self.N)
> ? ? ? ?self.compoundnames = [c.name for c in self.compounds]
> ? ? ? ?self.DGf = numpy.array([c.DGf for c in self.compounds])
> ? ? ? ?self.elements = reduce(set.union,
> (c.parsed.distinctelements()
> ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?for c in self.compounds))
> ? ? ? ?self.S = numpy.array([c.parsed.counts(self.elements)
> ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?for c in self.compounds]).T
> ? ? ? ?Srank = numpy.count_nonzero(numpy.linalg.svd(self.S,
> compute_uv=False) > smallvalue)
>
> ? ? ? ?# Calculating the Degrees of freedom
> ? ? ? ?self.DOF = self.S.shape[1] - Srank
> ? ? ? ?print 'Degrees of Freedom =', self.DOF
>
> ? ? ? ?# Coefficients of the Gibbs function
> ? ? ? ?Ncomps = len(self.compounds)
> ? ? ? ?# self.A = numpy.tile(numpy.repeat([-1, 1], [1, Ncomps-1]),
> [Ncomps, 1])
> ? ? ? ?# number of atoms of each element
> ? ? ? ?self.atoms = numpy.dot(self.S, self.N)
>
>
> ? ?def gibbs(self, N=None):
> ? ? ? ?""" Gibbs energy of mixture with N of each compound """
> ? ? ? ?if N is None: N = self.N
> ? ? ? ?# TODO: There is every chance that this function is not
> correct. It needs to be checked.
> ? ? ? ?#return sum(N*(self.DGf/(R*T) + numpy.log(numpy.dot(self.A,
> N))))
> ? ? ? ?logs = numpy.log(sum(N))
> ? ? ? ?return sum(N*(self.DGf/RT + numpy.log(N) - logs))
>
> ? ?def atombalance(self, N):
>
> ? ? ? ?""" Atom balance with N of each compound """
> ? ? ? ?#if N is None: N = self.N
> ? ? ? ?return numpy.dot(self.S, N) - self.atoms
>
>
> ? ?def conversion(self, conversionspec):
> ? ? ? ?""" Calculate the composition given a certain conversion.
> ? ? ? ?conversionspec is a list of 2-tuples containing a component
> index or name and a conversion """
> ? ? ? ?#TODO: A and B should only be calculated once
> ? ? ? ?#TODO: This does not take into account any existing products
> in the mixture
> ? ? ? ?#TODO: This works only for conversion specified in terms of
> reagents
> ? ? ? ?if len(conversionspec) < self.DOF:
> ? ? ? ? ? ?raise Exception("Not enough conversions specified.")
> ? ? ? ?C = numpy.zeros([len(conversionspec), self.S.shape[1]])
> ? ? ? ?Ic = C.copy()
> ? ? ? ?for i, (j, c) in enumerate(conversionspec):
> ? ? ? ? ? ?if type(j) is str:
> ? ? ? ? ? ? ? ?j = self.compoundnames.index(j)
> ? ? ? ? ? ?C[i, j] = 1-c
> ? ? ? ? ? ?Ic[i, j] = 1
> ? ? ? ?A = numpy.vstack([self.S, C])
> ? ? ? ?B = numpy.vstack([self.S, Ic])
> ? ? ? ?# A ni = B nf
> ? ? ? ?nf, _, _, _ = scipy.linalg.lstsq(B, numpy.dot(A, self.N))
> ? ? ? ?# assert residuals are neglegable
> ? ? ? ?nf[nf<0] = 0
> ? ? ? ?return nf
>
> ? ?def equilibrium(self, initialconversion):
> ? ? ? ?""" Return equilibrium composition as minimum of Gibbs Energy
> """
> ? ? ? ?# guess initial conditions
> ? ? ? ?N0 = self.conversion(initialconversion)
> ? ? ? ?logN0 = numpy.log(N0)
>
> ? ? ? ?# This decorator modifies a function to be defined in terms of
> new variables
> ? ? ? ?def changevars(f):
> ? ? ? ? ? ?def newf(newX):
> ? ?# ? ? ? ? print 'newX', newX
> ? ?# ? ? ? ? print 'X', numpy.exp(newX)
> ? ? ? ? ? ? ? ?r = f(numpy.exp(newX))
> ? ?# ? ? ? ? ?print 'f(X)', r
> ? ? ? ? ? ? ? ?return r
> ? ? ? ? ? ?return newf
>
> ? ? ? ?# Find optimal point in terms of a change of variables
> ? ? ? ?logN = scipy.optimize.fmin_slsqp(changevars(self.gibbs),
> ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?logN0,
>
> f_eqcons=changevars(self.atombalance),
> ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?acc = 1.0E-12)
> ? ? ? ?scipy.optimize.fmin
> ? ? ? ?N = numpy.exp(logN)
> ? ? ? ?print ''
> ? ? ? ?print 'Calculated Optimmum Values'
> ? ? ? ?print N
> ? ? ? ?print ''
> ? ? ? ?print 'Calculated Optimum Function value'
> ? ? ? ?print m.gibbs(N)
>
> ? ? ? ?return N
>
> ? ?# Here for a particular mixture:
> m = mixture([[1., ?compound('MgO', ? ? ? ? ? ? ? ? ? ? ?-568343.0)],
> ? ? ? ? ? ?[0.5, compound('Al2O3', ? ? ? ? ? ? ? ? ? ?-1152420.0)],
> ? ? ? ? ? ?[4., ?compound('H2O', ? ? ? ? ? ? ? ? ? ? ?-237141.0)],
> ? ? ? ? ? ?[0, ? compound('Mg(OH)2', ? ? ? ? ? ? ? ? ?-833644.0)],
> ? ? ? ? ? ?[0, ? compound('Al(OH)3', ? ? ? ? ? ? ? ? ?-1835750.0)]])
>
>
> ? ?# find Gibbs energy surface for many conversion possibilities
> Nsteps = 10
> convrange = numpy.linspace(0.001, 0.999, Nsteps)
> gibbssurface = numpy.zeros((Nsteps, Nsteps))
> for iMgO, xMgO in enumerate(convrange):
> ? ?for iAl2O3, xAl2O3 in enumerate(convrange):
> ? ? ? ?N = m.conversion([('MgO', xMgO),
> ? ? ? ? ? ? ? ? ? ? ? ? ?('Al2O3', xAl2O3/50)])
> ? ? ? ?gibbssurface[iMgO, iAl2O3] = m.gibbs(N)
>
>
>
> # Try to find equilibrium
> # Initial conversion guess
> print ''
> print "***************Optimizing******************"
> X0 = [0.5, 0.5]
> conversionspec = zip(['MgO', 'Al2O3'], X0)
> # Solve to equilibrium
> N = m.equilibrium(conversionspec)
>
> print ''
> print '*************Final Values***************'
> for n, init, name in zip(N, m.N, m.compoundnames):
> ? ?print name, 'initial =', init, 'final =', n
>
>
> # Plot results
> if mustplot:
> ? ?Xaxis, Yaxis = numpy.meshgrid(convrange, convrange)
> ? ?Zaxis = gibbssurface
> ? ?surf = ax.plot_surface(Xaxis, Yaxis, Zaxis, rstride=1, cstride=1,
> cmap=cm.jet, linewidth=0, antialiased=False)
> ? ?fig.colorbar(surf, shrink=0.5, aspect=5)
> ? ?ax.set_xlabel('Conversion of MgO')
> ? ?ax.set_ylabel('Conversion of Al2O3')
> ? ?ax.set_zlabel('Gibbs free energy (G/RT)')
> ? ?pl.show()
>
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user


From mmueller at python-academy.de  Fri Jan 13 05:41:50 2012
From: mmueller at python-academy.de (=?ISO-8859-15?Q?Mike_M=FCller?=)
Date: Fri, 13 Jan 2012 11:41:50 +0100
Subject: [SciPy-User] Python for Scientists - courses in Germany and US
Message-ID: <4F100A6E.5000709@python-academy.de>

Learn NumPy and Much More
=========================

Scientists like Python. If you would like to learn more about
important libraries for scientific applications, you might be
interested in these courses.

The course in Germany covers:

- Overview of libraries
- NumPy
- Data storage with text files, Excel, netCDF and HDF5
- matplotlib
- Object oriented programming for scientists
- Problem solving session

The course in the USA covers all this plus:

- Extending Python in other languages
- Version control
- Unit testing


More details below.

If you have any questions about the courses, please contact me.

Mike


Python for Scientists and Engineers (Germany)
---------------------------------------------

A three-day course covering all the basic tools scientists and engineers need.
This course requires basic Python knowledge.

Date: 19.01.-21.01.2012
Location: Leipzig, Germany
Trainer: Mike M?ller
Course Language: English
Link: http://www.python-academy.com/courses/python_course_scientists.html


Python for Scientists and Engineers (USA)
-----------------------------------------

This is an extend version of our well-received course for
scientists and engineers. Five days of intensive training
will give you a solid basis for using Python for scientific
an technical problems.

The course is hosted by David Beazley (http://www.dabeaz.com).

Date: 27.02.-02.03.2012
Location: Chicago, IL, USA
Trainer: Mike M?ller
Course Language: English
Link: http://www.dabeaz.com/chicago/science.html


From tmp50 at ukr.net  Mon Jan 16 15:07:54 2012
From: tmp50 at ukr.net (Dmitrey)
Date: Mon, 16 Jan 2012 22:07:54 +0200
Subject: [SciPy-User] [ANN] global constrained solver with discrete variables
Message-ID: <17671.1326744474.16853089562548174848@ffe6.ukr.net>




hi all,
I've done support of discrete variables for interalg - free (license:
BSD) solver with specifiable accuracy, you can take a look at an example
here

It is written in Python + NumPy, and I hope it's speed will be
essentially increased when PyPy (Python with dynamic compilation) support
for NumPy will be done (some parts of code are not vectorized and still
use CPython cycles). Also, NumPy funcs like vstack or append produce only
copy of data, and it also slows the solver very much (for mature
problems).

Maybe some bugs still present somewhere - interalg code already became
very long, but since it already works, you could be interested in trying
to use it right now.

Regards, D.
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From cpeters at edisonmission.com  Mon Jan 16 16:01:56 2012
From: cpeters at edisonmission.com (Christopher Peters)
Date: Mon, 16 Jan 2012 16:01:56 -0500
Subject: [SciPy-User] AUTO: Christopher Peters is out of the office
	(returning 01/17/2012)
Message-ID: <OFD3F80858.453C34E2-ON85257987.007388CC-85257987.007388CC@EdisonMission.com>


I am out of the office until 01/17/2012.

I am out of the office.  Please email urgent requests to Mike McDonald.


Note: This is an automated response to your message  "[SciPy-User] [ANN]
global constrained solver with discrete variables" sent on 1/16/2012
3:07:54 PM.

This is the only notification you will receive while this person is away.




From klonuo at gmail.com  Mon Jan 16 17:13:45 2012
From: klonuo at gmail.com (klo uo)
Date: Mon, 16 Jan 2012 23:13:45 +0100
Subject: [SciPy-User] How to calculate Yulewalk with scipy.optimize.leastsq
Message-ID: <CAA-8Ld9h-FMe9wbt7+RYBVcUYXrZi+RZuRW_eiqkJuRFw2y3Tw@mail.gmail.com>

H(z) = yulewalk(N,frq,mag) - finds the N-th order iir filter:

[image:
%5Cnormalsize%5C%21H%28z%29%3D%5Cfrac%7BB%28z%29%7D%7BA%28z%29%7D%3D%5Cfrac%7Bb%281%29%20%2B%20b%282%29z%5E%7B-1%7D%2B...%2Bb%28n%29z%5E%7B-%28n-1%29%7D%7D%7B1%2Ba%281%29z%5E%7B-1%7D%2B...%2Ba%28n%29z%5E%7B-%28n-1%29%7D%7D.gif]

H(z) : filter B(z)/A(z)
N    : integer (order of desired filter)
frq  : real row vector (non-decreasing order), frequencies.
mag  : non negative real row vector (same size as frq), desired magnitudes.

----------------------------------------

yulewalk() function in "/scipy/signal/filter_design.py" is empty. It
perhaps can be calculated using scipy.optimize.leastsq() but I lack skills
to figure out how?

All I can do right now is port it quick and dirty from Matlab to Python,
but I feel it's bad idea and waste of time

Can someone provide tip how can I calculate 10-th order yulewalk with scipy?
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From josef.pktd at gmail.com  Mon Jan 16 17:56:17 2012
From: josef.pktd at gmail.com (josef.pktd at gmail.com)
Date: Mon, 16 Jan 2012 17:56:17 -0500
Subject: [SciPy-User] How to calculate Yulewalk with
	scipy.optimize.leastsq
In-Reply-To: <CAA-8Ld9h-FMe9wbt7+RYBVcUYXrZi+RZuRW_eiqkJuRFw2y3Tw@mail.gmail.com>
References: <CAA-8Ld9h-FMe9wbt7+RYBVcUYXrZi+RZuRW_eiqkJuRFw2y3Tw@mail.gmail.com>
Message-ID: <CAMMTP+DR5XW31eqXk41+VTc88KOZZQsGUmwJv_kYL-r9+O=bDg@mail.gmail.com>

On Mon, Jan 16, 2012 at 5:13 PM, klo uo <klonuo at gmail.com> wrote:

> H(z) = yulewalk(N,frq,mag) - finds the N-th order iir filter:
>
> [image:
> %5Cnormalsize%5C%21H%28z%29%3D%5Cfrac%7BB%28z%29%7D%7BA%28z%29%7D%3D%5Cfrac%7Bb%281%29%20%2B%20b%282%29z%5E%7B-1%7D%2B...%2Bb%28n%29z%5E%7B-%28n-1%29%7D%7D%7B1%2Ba%281%29z%5E%7B-1%7D%2B...%2Ba%28n%29z%5E%7B-%28n-1%29%7D%7D.gif]
>
> H(z) : filter B(z)/A(z)
> N    : integer (order of desired filter)
> frq  : real row vector (non-decreasing order), frequencies.
> mag  : non negative real row vector (same size as frq), desired magnitudes.
>
> ----------------------------------------
>
> yulewalk() function in "/scipy/signal/filter_design.py" is empty. It
> perhaps can be calculated using scipy.optimize.leastsq() but I lack skills
> to figure out how?
>
> All I can do right now is port it quick and dirty from Matlab to Python,
> but I feel it's bad idea and waste of time
>
> Can someone provide tip how can I calculate 10-th order yulewalk with
> scipy?
>

I have no idea about whether or how it can be used for filter design?

For estimation of the filter from data, the Yule Walker equations can only
estimate a autoregressive process, not an IIR filter (ARMA process).

statsmodels has yule walker for estimating the autoregressive filter, and
ARMA for estimating an IIR filter.
autoregressive can also be estimated with nitime and scikits.audiolab.
The only python package I know that can estimate an ARMA filter is
statsmodels.

Josef


>
>
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user
>
>
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From klonuo at gmail.com  Mon Jan 16 18:10:11 2012
From: klonuo at gmail.com (klo uo)
Date: Tue, 17 Jan 2012 00:10:11 +0100
Subject: [SciPy-User] How to calculate Yulewalk with
	scipy.optimize.leastsq
In-Reply-To: <CAMMTP+DR5XW31eqXk41+VTc88KOZZQsGUmwJv_kYL-r9+O=bDg@mail.gmail.com>
References: <CAA-8Ld9h-FMe9wbt7+RYBVcUYXrZi+RZuRW_eiqkJuRFw2y3Tw@mail.gmail.com>
	<CAMMTP+DR5XW31eqXk41+VTc88KOZZQsGUmwJv_kYL-r9+O=bDg@mail.gmail.com>
Message-ID: <CAA-8Ld-g673JZ+aiA010vrF+_ttMCrpf=EAgQ5X2J6ArT3oyFg@mail.gmail.com>

http://www.mathworks.com/help/toolbox/signal/ref/yulewalk.html

http://help.scilab.org/docs/5.3.3/en_US/yulewalk.html


On Mon, Jan 16, 2012 at 11:56 PM, <josef.pktd at gmail.com> wrote:

> I have no idea about whether or how it can be used for filter design?
>
> For estimation of the filter from data, the Yule Walker equations can only
> estimate a autoregressive process, not an IIR filter (ARMA process).
>
>
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From JRadinger at gmx.at  Tue Jan 17 04:35:57 2012
From: JRadinger at gmx.at (Johannes Radinger)
Date: Tue, 17 Jan 2012 10:35:57 +0100
Subject: [SciPy-User] convolution density kernel
Message-ID: <20120117093557.101680@gmx.net>

Hello,

I'd like to apply a 'convolution' on a probability density kernel.
Like in: http://graphics.stanford.edu/courses/cs178/applets/convolution.html

where f=g (for step 1)

In my case the function (base and that for the convolution) is:

def pdf(x,sigma_stat,sigma_mob):
    return (p * stats.norm.pdf(x, loc=m, scale=sigma_stat) + (1-p) * stats.norm.pdf(x, loc=m, scale=sigma_mob))

this are actually two superimposed normal distributions. Due to computational
problems I think it easier to sample finely as I just want to represent the result using matplotlib. Furthermore I'd like to do this convolution computation several times, where the output of the last convolution is the input (f) of the next step (function (g) stays the same original one).

Is there any easy applicable function in scipy to to this convolution? As I am not that familiar with scipy hopefully someone can help me in this case.

Best regards,
Johannes
    
-- 
NEU: FreePhone - 0ct/min Handyspartarif mit Geld-zur?ck-Garantie!		
Jetzt informieren: http://www.gmx.net/de/go/freephone


From scott.sinclair.za at gmail.com  Tue Jan 17 07:26:08 2012
From: scott.sinclair.za at gmail.com (Scott Sinclair)
Date: Tue, 17 Jan 2012 14:26:08 +0200
Subject: [SciPy-User] convolution density kernel
In-Reply-To: <20120117093557.101680@gmx.net>
References: <20120117093557.101680@gmx.net>
Message-ID: <CA+nsYDsKzvO6zHq3GbR7WyUSSjUiB+oMz4gSd23x6caOwnjeXA@mail.gmail.com>

On 17 January 2012 11:35, Johannes Radinger <JRadinger at gmx.at> wrote:
> I'd like to apply a 'convolution' on a probability density kernel.
> Like in: http://graphics.stanford.edu/courses/cs178/applets/convolution.html
>
> where f=g (for step 1)
>
> In my case the function (base and that for the convolution) is:
>
> def pdf(x,sigma_stat,sigma_mob):
> ? ?return (p * stats.norm.pdf(x, loc=m, scale=sigma_stat) + (1-p) * stats.norm.pdf(x, loc=m, scale=sigma_mob))
>
> this are actually two superimposed normal distributions. Due to computational
> problems I think it easier to sample finely as I just want to represent the result using matplotlib. Furthermore I'd like to do this convolution computation several times, where the output of the last convolution is the input (f) of the next step (function (g) stays the same original one).
>
> Is there any easy applicable function in scipy to to this convolution? As I am not that familiar with scipy hopefully someone can help me in this case.

You're probably looking for scipy.signal.convolve and
scipy.signal.fftconvolve. fftconvolve will be faster for larger inputs
because the convolution operation can be represented as a simple
multiplication once the inputs are transformed into the Fourier
domain.

Cheers,
Scott


From cmutel at gmail.com  Tue Jan 17 11:32:12 2012
From: cmutel at gmail.com (Christopher Mutel)
Date: Tue, 17 Jan 2012 17:32:12 +0100
Subject: [SciPy-User] [PhD position] Modeling the sustainability of the
 value chain of wood in Switzerland using Python/Scipy (German & English
 required)
Message-ID: <CAOc=QnLC7wthFC6SOHDDkxFFHQhC92FoPPsgW3-J3Z3jkj2K5Q@mail.gmail.com>

Dear all-

Please find attached an announcement for a PhD position modeling the
sustainability of the wood value chain in Switzerland at ETH Zurich.
The PhD will build upon an existing model for life cycle assessment
that uses NumPy and SciPy extensively.

This position is still open.

Note that some knowledge of German and English is required for this position.

Yours,
-Chris

-- 
############################
Chris Mutel
?kologisches Systemdesign - Ecological Systems Design
Institut f.Umweltingenieurwissenschaften - Institute for Environmental
Engineering
ETH Z?rich - HIF C 44 - Schafmattstr. 6
8093 Z?rich

Telefon: +41 44 633 71 45 - Fax: +41 44 633 10 61
############################
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From ndbecker2 at gmail.com  Tue Jan 17 13:32:44 2012
From: ndbecker2 at gmail.com (Neal Becker)
Date: Tue, 17 Jan 2012 13:32:44 -0500
Subject: [SciPy-User] How to calculate Yulewalk with
	scipy.optimize.leastsq
References: <CAA-8Ld9h-FMe9wbt7+RYBVcUYXrZi+RZuRW_eiqkJuRFw2y3Tw@mail.gmail.com>
	<CAMMTP+DR5XW31eqXk41+VTc88KOZZQsGUmwJv_kYL-r9+O=bDg@mail.gmail.com>
	<CAA-8Ld-g673JZ+aiA010vrF+_ttMCrpf=EAgQ5X2J6ArT3oyFg@mail.gmail.com>
Message-ID: <jf4esc$gr0$2@dough.gmane.org>

klo uo wrote:

> http://www.mathworks.com/help/toolbox/signal/ref/yulewalk.html
> 
> http://help.scilab.org/docs/5.3.3/en_US/yulewalk.html
> 
> 
> On Mon, Jan 16, 2012 at 11:56 PM, <josef.pktd at gmail.com> wrote:
> 
>> I have no idea about whether or how it can be used for filter design?
>>
>> For estimation of the filter from data, the Yule Walker equations can only
>> estimate a autoregressive process, not an IIR filter (ARMA process).
>>
>>

Many years ago I played around with using YuleWalker as a digital filter design 
technique.  There, I added white noise to the model (adding to the diagonal 
terms of the correlation matrix), and by varying the amount of noise, you could 
vary the filter characteristics.



From caraciol at gmail.com  Tue Jan 17 14:58:36 2012
From: caraciol at gmail.com (Marcel Caraciolo)
Date: Tue, 17 Jan 2012 16:58:36 -0300
Subject: [SciPy-User] Information about the Numerical Stability of
	Scipy/Numpy
Message-ID: <CAOosPkJW-1MVf0Jvyf7ssXMj1i6pA8vATwKuFSQineRGSxBvSw@mail.gmail.com>

Hi all,

I am studying scipy and numpy and  I decide to write some routines with
those packages for a paper submission in a scientific congress. The problem
is the validation of the results and experiments I have to show that the
libraries that I used (in this case Scipy and Numpy) provides numerical
stability, otherwise the chances that my article be approved will be
decreased.

Any further information in docs or the website about this topic ?

Regards,

-- 
Marcel Pinheiro Caraciolo
M.S.C. Candidate at CIN/UFPE
   http://www.mobideia.com
   http://aimotion.blogspot.com/
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From markbak at gmail.com  Tue Jan 17 15:58:35 2012
From: markbak at gmail.com (Mark Bakker)
Date: Tue, 17 Jan 2012 21:58:35 +0100
Subject: [SciPy-User] what happened to scipy.integrate.Inf?
Message-ID: <CAEX=yaYfSMKSSOMfXzR81G3Fs-Gz9aEwF_=hKrqzx0a29gUdZA@mail.gmail.com>

Hello  List,

After I updated to version 0.10, scipy.integrate.Inf disappeared (but it is
still in the docs of, for example, quad). Can I simply use numpy.inf?
Should the docs be updated?

Thanks,

Mark
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From david_baddeley at yahoo.com.au  Tue Jan 17 17:08:05 2012
From: david_baddeley at yahoo.com.au (David Baddeley)
Date: Tue, 17 Jan 2012 14:08:05 -0800 (PST)
Subject: [SciPy-User] Information about the Numerical Stability of
	Scipy/Numpy
In-Reply-To: <CAOosPkJW-1MVf0Jvyf7ssXMj1i6pA8vATwKuFSQineRGSxBvSw@mail.gmail.com>
References: <CAOosPkJW-1MVf0Jvyf7ssXMj1i6pA8vATwKuFSQineRGSxBvSw@mail.gmail.com>
Message-ID: <1326838085.54581.YahooMailNeo@web113407.mail.gq1.yahoo.com>

The scope of scipy / numpy is such that I think you'd be hard pressed to to prove that 'scipy is numerically stable' or something to that extent - instead you'll need to look at each algorithm (or class of algorithms)?independently.

Much of the scipy / numpy?functionality?comes from a relatively thin wrapping of underlying c or fortran libraries. These libraries e.g. lapack/blas (or Atlas or MKL) are generally industry standard libraries with well documented numerical stabilities. I think the best strategy would be to try and find out which of the c or fortran level libraries your code uses and go from there. For routines which aren't a simple wrapping of a library call, there are often references to papers describing the algorithms in the documentation or comments.

The unit testing code might also be a good place to look.

cheers,
David


________________________________
 From: Marcel Caraciolo <caraciol at gmail.com>
To: scipy-user at scipy.org 
Sent: Wednesday, 18 January 2012 8:58 AM
Subject: [SciPy-User] Information about the Numerical Stability of Scipy/Numpy
 

Hi all,

I am studying scipy and numpy and ?I decide to write some routines with those packages for a paper submission in a scientific congress. The problem is the validation of the results and experiments I have to show that the libraries that I used (in this case Scipy and Numpy) provides numerical stability, otherwise the chances that my article be approved will be decreased.

Any further information in docs or the website about this topic ?

Regards,

--?Marcel Pinheiro Caraciolo
M.S.C. Candidate at CIN/UFPE
???http://www.mobideia.com
?? http://aimotion.blogspot.com/

_______________________________________________
SciPy-User mailing list
SciPy-User at scipy.org
http://mail.scipy.org/mailman/listinfo/scipy-user
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From josef.pktd at gmail.com  Tue Jan 17 19:33:07 2012
From: josef.pktd at gmail.com (josef.pktd at gmail.com)
Date: Tue, 17 Jan 2012 19:33:07 -0500
Subject: [SciPy-User] How to calculate Yulewalk with
	scipy.optimize.leastsq
In-Reply-To: <jf4esc$gr0$2@dough.gmane.org>
References: <CAA-8Ld9h-FMe9wbt7+RYBVcUYXrZi+RZuRW_eiqkJuRFw2y3Tw@mail.gmail.com>
	<CAMMTP+DR5XW31eqXk41+VTc88KOZZQsGUmwJv_kYL-r9+O=bDg@mail.gmail.com>
	<CAA-8Ld-g673JZ+aiA010vrF+_ttMCrpf=EAgQ5X2J6ArT3oyFg@mail.gmail.com>
	<jf4esc$gr0$2@dough.gmane.org>
Message-ID: <CAMMTP+DqPOZ6jC8fnPuvYZWiCYgVeFwc8bvzfZpdpyjugh8OLg@mail.gmail.com>

On Tue, Jan 17, 2012 at 1:32 PM, Neal Becker <ndbecker2 at gmail.com> wrote:
> klo uo wrote:
>
>> http://www.mathworks.com/help/toolbox/signal/ref/yulewalk.html
>>
>> http://help.scilab.org/docs/5.3.3/en_US/yulewalk.html

Thanks for the references, the paper on the matlab help has some
interesting parts.

I haven't seen anything like this in python, maybe it's work for the
new scikits.signal developers.

The idea of the modified yule walker equations to get the ar
coefficients for an ARMA looked interesting so I coded that part. I
didn't manage to get equation 54 to get the MA coefficients to work.

(Instead I just use a deconvolution to go from autocovariance function
& AR coefficients to MA coefficients. It looks like it's possible to
go from the autocovariance function to recover the ARMA coefficients
with one yule walker, one modified yule walker and one deconvolution.
I just wrote some toy code for this to see if round tripping works. I
still have no idea about filter design. )

------------
import numpy as np
from scipy import linalg

def modified_yule_walker(acov, n_ar, n_ma):
    '''estimate AR part of ARMA from modified Yule-Walker equations

    The autocovariance of an ARMA process for lags greater than n_ma is
    independent of the MA part and can be used to estimate the AR part.
    (If I remember correctly.)

    Parameters
    ----------
    acov : array_like
        autocovariance, needs to have at least n_ar+n_ma terms and start with
        the zero lag, i.e. variance.
    n_ar : int
        length of autoregressive lagpolynomial, including counting the leading
        one.
    n_ma : int
        length of moving-average lagpolynomial, including counting the leading
        one. lagpolynomials with leading (zero lag) value different from one
        have not been tested.

    Returns
    -------
    ar_coefs : ndarray
        the estimated AR coefficients. the autoregressive lag-polynomial is
        [1, -arcoeffs]

    References
    ----------
    Friedlander, B., and B. Porat, 1984, equation (2)

    '''

    p, q = n_ar - 1, n_ma #Friedlander/Porat convention

    r_idx = np.arange(q,q+p+1)  #easier with index than slices
    r2_idx = np.abs(r_idx[0] - 1 - np.arange(p))

    R = linalg.toeplitz(acov[r_idx-1], acov[r2_idx])
    return linalg.lstsq(R, acov[r_idx])[0]
---------

Josef

>>
>>
>> On Mon, Jan 16, 2012 at 11:56 PM, <josef.pktd at gmail.com> wrote:
>>
>>> I have no idea about whether or how it can be used for filter design?
>>>
>>> For estimation of the filter from data, the Yule Walker equations can only
>>> estimate a autoregressive process, not an IIR filter (ARMA process).
>>>
>>>
>
> Many years ago I played around with using YuleWalker as a digital filter design
> technique. ?There, I added white noise to the model (adding to the diagonal
> terms of the correlation matrix), and by varying the amount of noise, you could
> vary the filter characteristics.
>
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user


From scott.sinclair.za at gmail.com  Wed Jan 18 01:23:53 2012
From: scott.sinclair.za at gmail.com (Scott Sinclair)
Date: Wed, 18 Jan 2012 08:23:53 +0200
Subject: [SciPy-User] what happened to scipy.integrate.Inf?
In-Reply-To: <CAEX=yaYfSMKSSOMfXzR81G3Fs-Gz9aEwF_=hKrqzx0a29gUdZA@mail.gmail.com>
References: <CAEX=yaYfSMKSSOMfXzR81G3Fs-Gz9aEwF_=hKrqzx0a29gUdZA@mail.gmail.com>
Message-ID: <CA+nsYDsPh3zkM8q48SzvYgzaFboLtXCE=e0gsaF9YZX49ftvjg@mail.gmail.com>

On 17 January 2012 22:58, Mark Bakker <markbak at gmail.com> wrote:
> After I updated to version 0.10, scipy.integrate.Inf disappeared (but it is
> still in the docs of, for example, quad). Can I simply use numpy.inf? Should
> the docs be updated?

I'd say that the answer is Yes, you can use numpy.inf instead.

It seems that scipy.integrate.Inf and scipy.integrate.inf both came
from numpy anyway. They were imported and added to __all__ in
scipy/integrate/quadpack.py, but were removed in this commit
https://github.com/scipy/scipy/commit/fd9cb84ddaae3eb6713ce9930c26baa290108a1f.

Doc update at https://github.com/scipy/scipy/pull/137

Cheers,
Scott


From silva at lma.cnrs-mrs.fr  Wed Jan 18 02:50:09 2012
From: silva at lma.cnrs-mrs.fr (Fabrice Silva)
Date: Wed, 18 Jan 2012 08:50:09 +0100
Subject: [SciPy-User] How to calculate Yulewalk with
 scipy.optimize.leastsq
In-Reply-To: <CAMMTP+DqPOZ6jC8fnPuvYZWiCYgVeFwc8bvzfZpdpyjugh8OLg@mail.gmail.com>
References: <CAA-8Ld9h-FMe9wbt7+RYBVcUYXrZi+RZuRW_eiqkJuRFw2y3Tw@mail.gmail.com>
	<CAMMTP+DR5XW31eqXk41+VTc88KOZZQsGUmwJv_kYL-r9+O=bDg@mail.gmail.com>
	<CAA-8Ld-g673JZ+aiA010vrF+_ttMCrpf=EAgQ5X2J6ArT3oyFg@mail.gmail.com>
	<jf4esc$gr0$2@dough.gmane.org>
	<CAMMTP+DqPOZ6jC8fnPuvYZWiCYgVeFwc8bvzfZpdpyjugh8OLg@mail.gmail.com>
Message-ID: <1326873009.1991.2.camel@amilo.coursju>

Note that talkbox seems to have some stuff on Yule-Walker
http://www.ar.media.kyoto-u.ac.jp/members/david/softwares/talkbox/talkbox_doc/index.html 

in python for educational purpose, and C for performance.

bye



From cournape at gmail.com  Wed Jan 18 03:32:46 2012
From: cournape at gmail.com (David Cournapeau)
Date: Wed, 18 Jan 2012 08:32:46 +0000
Subject: [SciPy-User] Information about the Numerical Stability of
	Scipy/Numpy
In-Reply-To: <CAOosPkJW-1MVf0Jvyf7ssXMj1i6pA8vATwKuFSQineRGSxBvSw@mail.gmail.com>
References: <CAOosPkJW-1MVf0Jvyf7ssXMj1i6pA8vATwKuFSQineRGSxBvSw@mail.gmail.com>
Message-ID: <CAGY4rcU-Z0yMf3ecKonPoe7zrsu+86epxELrSSJRvC74U0N4Jw@mail.gmail.com>

Hi Marcel,

On Tue, Jan 17, 2012 at 7:58 PM, Marcel Caraciolo <caraciol at gmail.com> wrote:
> Hi all,
>
> I am studying scipy and numpy and ?I decide to write some routines with
> those packages for a paper submission in a scientific congress. The problem
> is the validation of the results and experiments I have to show that the
> libraries that I used (in this case Scipy and Numpy) provides numerical
> stability, otherwise the chances that my article be approved will be
> decreased.

Are you referring to a precise guideline of the publication you have
in mind, and if so, could you point to it ?

Depending on the meaning you put behind numerical stability, numpy may
or may not be stable. I would say it is not fundamentally different
than any similar numerical package (e.g. matlab, octave, etc...), as
they share a lot of the same underlying implementation for fundamental
algorithms. Incidentally, a lot of this common implementation is taken
from netlib, and the quality of the code there is variable.

If you are implementing new algorithms, I think it is fair to say that
the stability depends as much if not more from how you use a library
than the library itself.

cheers,

David


From deshpande.jaidev at gmail.com  Wed Jan 18 14:54:06 2012
From: deshpande.jaidev at gmail.com (Jaidev Deshpande)
Date: Thu, 19 Jan 2012 01:24:06 +0530
Subject: [SciPy-User] Creating smaller .mat files
Message-ID: <CAB=suEm5+vR==OQeXRWPveAJ7bw18NzqxqCNFJfh8x59EOQ3ag@mail.gmail.com>

Hi

I use the savemat function in the scipy.io module quite often.

Suppose you create a .mat file through Python. Most often this file is
unnecessarily large.

Even more interesting - when you open that file into a MATLAB workspace

>> load myfile.mat

And then save it back,

>> save myfile.mat

the size reduces dramatically! (Even though the data types and
precision are kept the same)

Why does this happen?

If this means we can do something to reduce array sizes in the Python
workspace (since MATLAB can recreate the same data from a much smaller
size-on-disk), it would be a great advantage when dealing with large
data.

Thanks


From josef.pktd at gmail.com  Wed Jan 18 16:30:00 2012
From: josef.pktd at gmail.com (josef.pktd at gmail.com)
Date: Wed, 18 Jan 2012 16:30:00 -0500
Subject: [SciPy-User] OT: wikipedia
Message-ID: <CAMMTP+DsxrvnqOap-hA8UPhjzb_ALwUaH3SPQMKjjjKCxNaEnA@mail.gmail.com>

maybe north america only,

I'm not able to get a quick summary of Savitzky?Golay_smoothing

http://en.wikipedia.org/wiki/Savitzky%E2%80%93Golay_smoothing_filter

Josef


From jsseabold at gmail.com  Wed Jan 18 16:32:02 2012
From: jsseabold at gmail.com (Skipper Seabold)
Date: Wed, 18 Jan 2012 16:32:02 -0500
Subject: [SciPy-User] OT: wikipedia
In-Reply-To: <CAMMTP+DsxrvnqOap-hA8UPhjzb_ALwUaH3SPQMKjjjKCxNaEnA@mail.gmail.com>
References: <CAMMTP+DsxrvnqOap-hA8UPhjzb_ALwUaH3SPQMKjjjKCxNaEnA@mail.gmail.com>
Message-ID: <CAKF=Djs3TOLdRcuvPhc+MUCc1A9qH_6m+aB-hozcTX+Fq3_NqQ@mail.gmail.com>

On Wed, Jan 18, 2012 at 4:30 PM,  <josef.pktd at gmail.com> wrote:
> maybe north america only,
>
> I'm not able to get a quick summary of Savitzky?Golay_smoothing
>
> http://en.wikipedia.org/wiki/Savitzky%E2%80%93Golay_smoothing_filter
>

Hit escape while the page is loading.

Skipper


From tim.gallagher at gatech.edu  Wed Jan 18 16:32:26 2012
From: tim.gallagher at gatech.edu (Tim Gallagher)
Date: Wed, 18 Jan 2012 16:32:26 -0500 (EST)
Subject: [SciPy-User] OT: wikipedia
In-Reply-To: <CAMMTP+DsxrvnqOap-hA8UPhjzb_ALwUaH3SPQMKjjjKCxNaEnA@mail.gmail.com>
Message-ID: <7f8620f0-b15d-4fe9-bc45-2d3a8d83cea6@mail2.gatech.edu>

Put 

?banner=none

after your URL and it will show up. ie.

http://en.wikipedia.org/wiki/Savitzky%E2%80%93Golay_smoothing_filter?banner=none

Tim

----- Original Message -----
From: "josef pktd" <josef.pktd at gmail.com>
To: "SciPy Users List" <scipy-user at scipy.org>
Sent: Wednesday, January 18, 2012 4:30:00 PM
Subject: [SciPy-User] OT: wikipedia

maybe north america only,

I'm not able to get a quick summary of Savitzky?Golay_smoothing

http://en.wikipedia.org/wiki/Savitzky%E2%80%93Golay_smoothing_filter

Josef
_______________________________________________
SciPy-User mailing list
SciPy-User at scipy.org
http://mail.scipy.org/mailman/listinfo/scipy-user


From josef.pktd at gmail.com  Wed Jan 18 16:45:21 2012
From: josef.pktd at gmail.com (josef.pktd at gmail.com)
Date: Wed, 18 Jan 2012 16:45:21 -0500
Subject: [SciPy-User] OT: wikipedia
In-Reply-To: <7f8620f0-b15d-4fe9-bc45-2d3a8d83cea6@mail2.gatech.edu>
References: <CAMMTP+DsxrvnqOap-hA8UPhjzb_ALwUaH3SPQMKjjjKCxNaEnA@mail.gmail.com>
	<7f8620f0-b15d-4fe9-bc45-2d3a8d83cea6@mail2.gatech.edu>
Message-ID: <CAMMTP+DOUh-H5Dqy2=NZK=_VMSD=dNJ1_WmgDhYNX0Uz=YmBSA@mail.gmail.com>

thanks, both ways work  (the filter requires equally spaced in the series)

But, that's cheating, you are supposed to call your congress-(wo)man

Josef

On Wed, Jan 18, 2012 at 4:32 PM, Tim Gallagher <tim.gallagher at gatech.edu> wrote:
> Put
>
> ?banner=none
>
> after your URL and it will show up. ie.
>
> http://en.wikipedia.org/wiki/Savitzky%E2%80%93Golay_smoothing_filter?banner=none
>
> Tim
>
> ----- Original Message -----
> From: "josef pktd" <josef.pktd at gmail.com>
> To: "SciPy Users List" <scipy-user at scipy.org>
> Sent: Wednesday, January 18, 2012 4:30:00 PM
> Subject: [SciPy-User] OT: wikipedia
>
> maybe north america only,
>
> I'm not able to get a quick summary of Savitzky?Golay_smoothing
>
> http://en.wikipedia.org/wiki/Savitzky%E2%80%93Golay_smoothing_filter
>
> Josef
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user


From aronne.merrelli at gmail.com  Wed Jan 18 16:48:16 2012
From: aronne.merrelli at gmail.com (Aronne Merrelli)
Date: Wed, 18 Jan 2012 15:48:16 -0600
Subject: [SciPy-User] Creating smaller .mat files
In-Reply-To: <CAB=suEm5+vR==OQeXRWPveAJ7bw18NzqxqCNFJfh8x59EOQ3ag@mail.gmail.com>
References: <CAB=suEm5+vR==OQeXRWPveAJ7bw18NzqxqCNFJfh8x59EOQ3ag@mail.gmail.com>
Message-ID: <CAHNdQ4++ZG6C5mO51pn-Y__6ZhnMWYMvhws-_SfSB2tmg1sBnQ@mail.gmail.com>

On Wed, Jan 18, 2012 at 1:54 PM, Jaidev Deshpande <
deshpande.jaidev at gmail.com> wrote:

> Hi
>
> I use the savemat function in the scipy.io module quite often.
>
> Suppose you create a .mat file through Python. Most often this file is
> unnecessarily large.
>
> Even more interesting - when you open that file into a MATLAB workspace
>
> >> load myfile.mat
>
> And then save it back,
>
> >> save myfile.mat
>
> the size reduces dramatically! (Even though the data types and
> precision are kept the same)
>
> Why does this happen?
>
>
By default, MATLAB compresses the arrays that are written into the file. I
don't often write MATLAB format files from scipy, but the help for
scipy.io.matlab.savemat shows this keyword:

    do_compression : bool, optional
       Whether to compress matrices on write. Default is False.

I would assume that would be equivalent what MATLAB is doing. Perhaps try
that keyword first? Otherwise, you could look at PyTables, and write HDF5
files (which also support compression), or have a look at savez_compressed
in NumPy.

Cheers,
Aronne
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From jason-sage at creativetrax.com  Wed Jan 18 16:57:02 2012
From: jason-sage at creativetrax.com (Jason Grout)
Date: Wed, 18 Jan 2012 15:57:02 -0600
Subject: [SciPy-User] OT: wikipedia
In-Reply-To: <7f8620f0-b15d-4fe9-bc45-2d3a8d83cea6@mail2.gatech.edu>
References: <7f8620f0-b15d-4fe9-bc45-2d3a8d83cea6@mail2.gatech.edu>
Message-ID: <4F17402E.1060503@creativetrax.com>

On 1/18/12 3:32 PM, Tim Gallagher wrote:
> Put
>
> ?banner=none
>
> after your URL and it will show up. ie.
>
> http://en.wikipedia.org/wiki/Savitzky%E2%80%93Golay_smoothing_filter?banner=none
>

Or using the NoScript extension in Firefox to turn off javascript also 
seems to work (but is harder than the other two solutions mentioned)

Jason



> Tim
>
> ----- Original Message -----
> From: "josef pktd"<josef.pktd at gmail.com>
> To: "SciPy Users List"<scipy-user at scipy.org>
> Sent: Wednesday, January 18, 2012 4:30:00 PM
> Subject: [SciPy-User] OT: wikipedia
>
> maybe north america only,
>
> I'm not able to get a quick summary of Savitzky?Golay_smoothing
>
> http://en.wikipedia.org/wiki/Savitzky%E2%80%93Golay_smoothing_filter
>
> Josef
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user



From matthew.brett at gmail.com  Wed Jan 18 17:05:53 2012
From: matthew.brett at gmail.com (Matthew Brett)
Date: Wed, 18 Jan 2012 22:05:53 +0000
Subject: [SciPy-User] Creating smaller .mat files
In-Reply-To: <CAHNdQ4++ZG6C5mO51pn-Y__6ZhnMWYMvhws-_SfSB2tmg1sBnQ@mail.gmail.com>
References: <CAB=suEm5+vR==OQeXRWPveAJ7bw18NzqxqCNFJfh8x59EOQ3ag@mail.gmail.com>
	<CAHNdQ4++ZG6C5mO51pn-Y__6ZhnMWYMvhws-_SfSB2tmg1sBnQ@mail.gmail.com>
Message-ID: <CAH6Pt5qazJCpeTBG0055uxJkUn_d0X4mrieXAeFiGnacosn_aA@mail.gmail.com>

Hi,

On Wed, Jan 18, 2012 at 9:48 PM, Aronne Merrelli
<aronne.merrelli at gmail.com> wrote:
>
>
> On Wed, Jan 18, 2012 at 1:54 PM, Jaidev Deshpande
> <deshpande.jaidev at gmail.com> wrote:
>>
>> Hi
>>
>> I use the savemat function in the scipy.io module quite often.
>>
>> Suppose you create a .mat file through Python. Most often this file is
>> unnecessarily large.
>>
>> Even more interesting - when you open that file into a MATLAB workspace
>>
>> >> load myfile.mat
>>
>> And then save it back,
>>
>> >> save myfile.mat
>>
>> the size reduces dramatically! (Even though the data types and
>> precision are kept the same)
>>
>> Why does this happen?
>>
>
> By default, MATLAB compresses the arrays that are written into the file. I
> don't often write MATLAB format files from scipy, but the help for
> scipy.io.matlab.savemat shows this keyword:
>
> ??? do_compression : bool, optional
> ?????? Whether to compress matrices on write. Default is False.
>
> I would assume that would be equivalent what MATLAB is doing. Perhaps try
> that keyword first? Otherwise, you could look at PyTables, and write HDF5
> files (which also support compression), or have a look at savez_compressed
> in NumPy.

Also, matlab will work out whether your floats are in fact all
integers and store them as such, but the scipy writer does not try and
do that.  It wouldn't be that hard to do, but it could obviously have
an impact on speed.  I guess that would depend on the size of the
arrays.

Best,

Matthew


From josef.pktd at gmail.com  Wed Jan 18 17:14:04 2012
From: josef.pktd at gmail.com (josef.pktd at gmail.com)
Date: Wed, 18 Jan 2012 17:14:04 -0500
Subject: [SciPy-User] a reference: signal splines
Message-ID: <CAMMTP+DBjCooc9e4oBa4dazBom8hbA2zP-dLX0_42-1tz=HAdw@mail.gmail.com>

I'm still looking at smoothing splines.

This reference looks good for equal spaced data (which I'm not really
interested in). Includes matlab code in paper.
(as aside: The spline code in scipy.signal has a single test, as far
as I have seen.)

http://www.sciencedirect.com/science/article/pii/S0167947308005045

A fast compact algorithm for cubic spline smoothing
Computational Statistics & Data Analysis, Volume 53, Issue 4, 15
February 2009, Pages 932?940

'''
Abstract

An efficient algorithm is presented for computing discrete or
continuous cubic smoothing splines with uniformly spaced and uniformly
weighted measurements. The algorithm computes both the spline values
and the generalized cross-validation score. Execution time and memory
use are reduced by carefully exploiting the problem?s rich structure.
The frequency domain properties of the steady-state cubic spline
smoother are also examined.

    Table 2. Execution time and memory use.
    n, r	Our algorithm	MATLAB spline toolbox
    105, 2	36 ms/4.8 MB	1.00 s/19.2 MB
    106, 2	367 ms/48 MB	12.2 s/192 MB
    105, 10	117 ms/11.2 MB	1.51 s/25.6 MB
    106, 10	1.19 s/112 MB	17.8 s/256 MB

'''

Josef


From klonuo at gmail.com  Thu Jan 19 08:25:52 2012
From: klonuo at gmail.com (klo uo)
Date: Thu, 19 Jan 2012 14:25:52 +0100
Subject: [SciPy-User] How to calculate Yulewalk with
	scipy.optimize.leastsq
In-Reply-To: <1326873009.1991.2.camel@amilo.coursju>
References: <CAA-8Ld9h-FMe9wbt7+RYBVcUYXrZi+RZuRW_eiqkJuRFw2y3Tw@mail.gmail.com>
	<CAMMTP+DR5XW31eqXk41+VTc88KOZZQsGUmwJv_kYL-r9+O=bDg@mail.gmail.com>
	<CAA-8Ld-g673JZ+aiA010vrF+_ttMCrpf=EAgQ5X2J6ArT3oyFg@mail.gmail.com>
	<jf4esc$gr0$2@dough.gmane.org>
	<CAMMTP+DqPOZ6jC8fnPuvYZWiCYgVeFwc8bvzfZpdpyjugh8OLg@mail.gmail.com>
	<1326873009.1991.2.camel@amilo.coursju>
Message-ID: <CAA-8Ld_2fd=o+xXzHAVRHoTXL-MKX==aHGjRdAAgrLg9G+NyTQ@mail.gmail.com>

Thanks Fabrice, I'll check talkbox later today and reply if that approach
is working for me

Josef, thanks for your snippet, thou I have no idea how to use it

I tried to translate Matlab's yulewalk.m, and it kinda works but with an
issue. Code is here: http://paste.pocoo.org/show/537224/

Main problem is on lines 79-80 when impulse response is computed. FFT/IFFT
functions result is different. Everything to that point gives correct
result in respect to Matlab function. I don't know why is that, is it
precision in question or else, but I had enough hard time to produce linked
and not so representative code.

I attached example image to show how results differ slightly.
Any comment is appreciated

Cheers
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From vincefn at users.sourceforge.net  Thu Jan 19 11:16:50 2012
From: vincefn at users.sourceforge.net (Vincent Favre-Nicolin)
Date: Thu, 19 Jan 2012 17:16:50 +0100
Subject: [SciPy-User] FortranFile and large records
Message-ID: <4F1841F2.1030100@users.sourceforge.net>

        Hi,

    This week I had to import large data from a Fortran 'record' file.
For this I naturally used FortranFile
(http://www.scipy.org/Cookbook/FortranIO/FortranFile).

    Unfortunately, it turned out that when a record is larger than
2,147,483,639 bytes (a bit short of 2^31), the 'record' where the data
is stored is split into sub-records.
    This took me some time to figure out, since I don't use Fortran that
much, and the only symptom was a negative size for the record... Which I
originally interpreted as a type (signed/unsigned) or byteswapping issue....

    Anyway, once I got what was going wrong (from Intel's
documentation),  I modified the "readRecord" function in FortranFile to
be able to read a complete record when such a case is encountered. The
corresponding code is below (not very efficient memorywise but working
as long as you have >=24Gb of memory, to perform directly a readReals()).

    I'm not sure if there is another way to do this (in numpy),
hopefully it will be useful for someone else. Neil if you think it is
OK, maybe the wiki page can be updated. And thanks again for FortranFile
which is really useful !


            Vincent


    def readRecord(self):
        """Read a single fortran record"""
        l = self._read_check()
        data_str=''
        while l<0:
          # Handle sub-records, for lengths>2,147,483,639 bytes
          # cf: Intel Fortran Compiler User and Reference Guides, page
217-218
          # (doc number 304970-006US)
          data_str+=self._read_exactly(abs(l))
          check_size = self._read_check()
          if abs(check_size) != abs(l):
              raise IOError('Error reading record from data file')
          l = self._read_check()
        data_str += self._read_exactly(abs(l))
        check_size = self._read_check()
        if abs(check_size) != abs(l):
            raise IOError('Error reading record from data file')
        return data_str

-- 
Vincent Favre-Nicolin                    http://inac.cea.fr

CEA/Grenoble              Institut Nanosciences & Cryog?nie
Laboratoire SP2M/Nano-structures et Rayonnement Synchrotron
17, rue des Martyrs
38054 Grenoble Cedex 9 - France

Universit? Joseph Fourier        http://www.ujf-grenoble.fr

t?l: (+33) 4 38 78 95 40           fax: (+33) 4 38 78 51 38



From wesmckinn at gmail.com  Fri Jan 20 00:00:45 2012
From: wesmckinn at gmail.com (Wes McKinney)
Date: Fri, 20 Jan 2012 00:00:45 -0500
Subject: [SciPy-User] pandas 0.7.0 release candidate
Message-ID: <CAJPUwMBrvST2QQBDdgvo0YNq_qOqOiigE2w67Gxb8qer94awqA@mail.gmail.com>

I just tagged and uploaded a release candidate for pandas 0.7.0. This
is a huge release including a ton of new and improved functionality as
well as a host of bug fixes. It also includes a handful of API changes
that veteran pandas users will want to pay close attention to.

Barring major issues I'll make the final release around this time next
week. Please beat on it and report any issues on GitHub:

Repository: http://github.com/wesm/pandas
Issue tracker: http://github.com/wesm/pandas/issues
What's new in 0.7.0: http://pandas.sourceforge.net/whatsnew.html
Windows Installers and Sources: http://pypi.python.org/pypi/pandas

Still some lingering documentation items that will get finished over
the next week.

The official pandas repository will be migrating to the newly formed
PyData GitHub organization shortly after the 0.7.0 release.

best,
Wes


From christian at prinoth.name  Fri Jan 20 04:20:26 2012
From: christian at prinoth.name (Christian Prinoth)
Date: Fri, 20 Jan 2012 10:20:26 +0100
Subject: [SciPy-User] [pystatsmodels] pandas 0.7.0 release candidate
In-Reply-To: <CAJPUwMBrvST2QQBDdgvo0YNq_qOqOiigE2w67Gxb8qer94awqA@mail.gmail.com>
References: <CAJPUwMBrvST2QQBDdgvo0YNq_qOqOiigE2w67Gxb8qer94awqA@mail.gmail.com>
Message-ID: <CAP3UiZ1DLVEk6j4qYFsjae2kAZT1pjn3Wh8tarYeizM_P+rz_g@mail.gmail.com>

Just a minor note:
on 0.6, Series(None,index=[0]) would return a Series of type object, with
0.7rc1 it returns a float object. No big issue, but in my case it caused an
error ;)

On Fri, Jan 20, 2012 at 06:00, Wes McKinney <wesmckinn at gmail.com> wrote:

> I just tagged and uploaded a release candidate for pandas 0.7.0. This
> is a huge release including a ton of new and improved functionality as
> well as a host of bug fixes. It also includes a handful of API changes
> that veteran pandas users will want to pay close attention to.
>
> Barring major issues I'll make the final release around this time next
> week. Please beat on it and report any issues on GitHub:
>
> Repository: http://github.com/wesm/pandas
> Issue tracker: http://github.com/wesm/pandas/issues
> What's new in 0.7.0: http://pandas.sourceforge.net/whatsnew.html
> Windows Installers and Sources: http://pypi.python.org/pypi/pandas
>
> Still some lingering documentation items that will get finished over
> the next week.
>
> The official pandas repository will be migrating to the newly formed
> PyData GitHub organization shortly after the 0.7.0 release.
>
> best,
> Wes
>



-- 
Christian Prinoth
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From sturla at molden.no  Fri Jan 20 05:25:40 2012
From: sturla at molden.no (Sturla Molden)
Date: Fri, 20 Jan 2012 11:25:40 +0100
Subject: [SciPy-User] FortranFile and large records
In-Reply-To: <4F1841F2.1030100@users.sourceforge.net>
References: <4F1841F2.1030100@users.sourceforge.net>
Message-ID: <4F194124.2060101@molden.no>

Den 19.01.2012 17:16, skrev Vincent Favre-Nicolin:
>          Hi,
>
>      This week I had to import large data from a Fortran 'record' file.
> For this I naturally used FortranFile
> (http://www.scipy.org/Cookbook/FortranIO/FortranFile).
>


Why? The FortranFile cookbook receipe is based on fundamentally wrong 
assumptions. If it works it is by pure accident. I suggest it is removed 
from the wiki.

Fortran does not specify a binary layout for record files. It is 
implementation dependent.  Consequently, a Fortran record file should be 
read by a Fortran program -- compiled with the same Fortran 
implementation that was used by the program that wrote the file.

Sturla


From d.s.seljebotn at astro.uio.no  Fri Jan 20 07:29:38 2012
From: d.s.seljebotn at astro.uio.no (Dag Sverre Seljebotn)
Date: Fri, 20 Jan 2012 13:29:38 +0100
Subject: [SciPy-User] FortranFile and large records
In-Reply-To: <4F194124.2060101@molden.no>
References: <4F1841F2.1030100@users.sourceforge.net>
	<4F194124.2060101@molden.no>
Message-ID: <4F195E32.8060504@astro.uio.no>

On 01/20/2012 11:25 AM, Sturla Molden wrote:
> Den 19.01.2012 17:16, skrev Vincent Favre-Nicolin:
>>           Hi,
>>
>>       This week I had to import large data from a Fortran 'record' file.
>> For this I naturally used FortranFile
>> (http://www.scipy.org/Cookbook/FortranIO/FortranFile).
>>
>
>
> Why? The FortranFile cookbook receipe is based on fundamentally wrong
> assumptions. If it works it is by pure accident. I suggest it is removed
> from the wiki.
>
> Fortran does not specify a binary layout for record files. It is
> implementation dependent.  Consequently, a Fortran record file should be
> read by a Fortran program -- compiled with the same Fortran
> implementation that was used by the program that wrote the file.

It would be good with a Python package that took care of this by 
interfacing with compiled Fortran code though (generating and compiling 
it on the fly if necesarry). I do remember reading about something like 
that here, but I don't have time to look it up myself.

Dag Sverre


From sturla at molden.no  Fri Jan 20 07:45:31 2012
From: sturla at molden.no (Sturla Molden)
Date: Fri, 20 Jan 2012 13:45:31 +0100
Subject: [SciPy-User] How to calculate Yulewalk with
	scipy.optimize.leastsq
In-Reply-To: <1326873009.1991.2.camel@amilo.coursju>
References: <CAA-8Ld9h-FMe9wbt7+RYBVcUYXrZi+RZuRW_eiqkJuRFw2y3Tw@mail.gmail.com>
	<CAMMTP+DR5XW31eqXk41+VTc88KOZZQsGUmwJv_kYL-r9+O=bDg@mail.gmail.com>
	<CAA-8Ld-g673JZ+aiA010vrF+_ttMCrpf=EAgQ5X2J6ArT3oyFg@mail.gmail.com>
	<jf4esc$gr0$2@dough.gmane.org>
	<CAMMTP+DqPOZ6jC8fnPuvYZWiCYgVeFwc8bvzfZpdpyjugh8OLg@mail.gmail.com>
	<1326873009.1991.2.camel@amilo.coursju>
Message-ID: <4F1961EB.5040403@molden.no>

Den 18.01.2012 08:50, skrev Fabrice Silva:
> Note that talkbox seems to have some stuff on Yule-Walker
> http://www.ar.media.kyoto-u.ac.jp/members/david/softwares/talkbox/talkbox_doc/index.html
>
> in python for educational purpose, and C for performance.
>

No need to use C for performance here.

Computing the autocovariance for Yule-Walker can be vectorized with 
np.dot, which lets BLAS do the work. Something like this:

def covmtx_yulewalker(x,p):
     ''' autocorrelation method '''
     x = np.ascontiguousarray(x)
     n = x.shape[0]
     Rxx = np.zeros(p+1)
     for k in range(0,p+1):
         Rxx[k] = np.dot(x[:n-k],x[k:])/(n-k-1.0)
     return Rxx

Later on, in the code Josef posted, the next bulk of the computation is 
done by LAPACK (linalg.lstsq).

With NumPy linked against optimized BLAS and LAPACK libraries (e.g. MKL, 
ACML, GotoBLAS2, Cray libsci), doing this in C might actually end up 
being slower. Don't waste your time on C before (1) NumPy is proven to 
be too slow and (2) you have good reasons to believe that C will be 
substantially faster. (NumPy users familiar with MATLAB make the latter 
assumption far too often.)

Sturla



From scipy at samueljohn.de  Fri Jan 20 08:23:12 2012
From: scipy at samueljohn.de (Samuel John)
Date: Fri, 20 Jan 2012 14:23:12 +0100
Subject: [SciPy-User] SciPy 0.10:  8 failures on OS X Lion
Message-ID: <8AB8D94B-FCA2-425B-B5AE-116C9BA2F71F@samueljohn.de>

Hi SciPy devs, 

I just want to report the following failures. Does anybody on OSX get the same/similar?
Are they "known" ?
Should I try scipy 0.11 because they are fixed there, perhaps?
Six out of eight are related to arpack.
I have installed numpy, scipy with gfortran provided by homebrew and I set the CC, CXX to use the non-llvm compilers of the 4.2 series.


> Python 2.7.2 (default, Jan 13 2012, 15:00:18) 
> [GCC 4.2.1 (Based on Apple Inc. build 5658) (LLVM build 2336.1.00)] on darwin
> >>> import scipy
> >>> scipy.test()
> Running unit tests for scipy
> NumPy version 2.0.0.dev-55472ca
> NumPy is installed in /usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy
> SciPy version 0.10.0
> SciPy is installed in /usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy
> Python version 2.7.2 (default, Jan 13 2012, 15:00:18) [GCC 4.2.1 (Based on Apple Inc. build 5658) (LLVM build 2336.1.00)]
> nose version 1.1.2
> .
> .
> .
> ======================================================================
> FAIL: test_arpack.test_symmetric_modes(True, <std-symmetric>, 'f', 2, 'LM', None, 0.5, <function aslinearoperator at 0x103a58f50>, None, 'normal')
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py", line 197, in runTest
>     self.test(*self.arg)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py", line 235, in eval_evec
>     assert_allclose(LHS, RHS, rtol=rtol, atol=atol, err_msg=err)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 1213, in assert_allclose
>     verbose=verbose, header=header)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 677, in assert_array_compare
>     raise AssertionError(msg)
> AssertionError: 
> Not equal to tolerance rtol=0.00178814, atol=0.000357628
> error for eigsh:standard, typ=f, which=LM, sigma=0.5, mattype=aslinearoperator, OPpart=None, mode=normal
> (mismatch 100.0%)
>  x: array([[ 0.23815642,  0.1763755 ],
>        [-0.10785346, -0.32103487],
>        [ 0.12468303, -0.11230416],...
>  y: array([[ 0.23815642,  0.24814051],
>        [-0.10785347, -0.15634772],
>        [ 0.12468302,  0.05671416],...
> 
> ======================================================================
> FAIL: test_arpack.test_symmetric_modes(True, <std-symmetric>, 'f', 2, 'LM', None, 0.5, <function aslinearoperator at 0x103a58f50>, None, 'cayley')
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py", line 197, in runTest
>     self.test(*self.arg)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py", line 235, in eval_evec
>     assert_allclose(LHS, RHS, rtol=rtol, atol=atol, err_msg=err)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 1213, in assert_allclose
>     verbose=verbose, header=header)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 677, in assert_array_compare
>     raise AssertionError(msg)
> AssertionError: 
> Not equal to tolerance rtol=0.00178814, atol=0.000357628
> error for eigsh:standard, typ=f, which=LM, sigma=0.5, mattype=aslinearoperator, OPpart=None, mode=cayley
> (mismatch 100.0%)
>  x: array([[ 0.23815693, -0.33630507],
>        [-0.10785286,  0.02168   ],
>        [ 0.12468344, -0.11036437],...
>  y: array([[ 0.23815643, -0.2405392 ],
>        [-0.10785349,  0.14390968],
>        [ 0.12468311, -0.04574991],...
> 
> ======================================================================
> FAIL: test_arpack.test_symmetric_modes(True, <std-symmetric>, 'f', 2, 'LA', None, 0.5, <function aslinearoperator at 0x103a58f50>, None, 'normal')
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py", line 197, in runTest
>     self.test(*self.arg)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py", line 235, in eval_evec
>     assert_allclose(LHS, RHS, rtol=rtol, atol=atol, err_msg=err)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 1213, in assert_allclose
>     verbose=verbose, header=header)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 677, in assert_array_compare
>     raise AssertionError(msg)
> AssertionError: 
> Not equal to tolerance rtol=0.00178814, atol=0.000357628
> error for eigsh:standard, typ=f, which=LA, sigma=0.5, mattype=aslinearoperator, OPpart=None, mode=normal
> (mismatch 100.0%)
>  x: array([[  28.80129188,   -0.6379945 ],
>        [  34.79312355,    0.27066791],
>        [-270.23255444,    0.4851834 ],...
>  y: array([[  3.93467650e+03,  -6.37994494e-01],
>        [  3.90913859e+03,   2.70667916e-01],
>        [ -3.62176382e+04,   4.85183382e-01],...
> 
> ======================================================================
> FAIL: test_arpack.test_symmetric_modes(True, <std-symmetric>, 'f', 2, 'SA', None, 0.5, <function aslinearoperator at 0x103a58f50>, None, 'normal')
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py", line 197, in runTest
>     self.test(*self.arg)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py", line 235, in eval_evec
>     assert_allclose(LHS, RHS, rtol=rtol, atol=atol, err_msg=err)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 1213, in assert_allclose
>     verbose=verbose, header=header)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 677, in assert_array_compare
>     raise AssertionError(msg)
> AssertionError: 
> Not equal to tolerance rtol=0.00178814, atol=0.000357628
> error for eigsh:standard, typ=f, which=SA, sigma=0.5, mattype=aslinearoperator, OPpart=None, mode=normal
> (mismatch 100.0%)
>  x: array([[ 0.26260981,  0.23815559],
>        [-0.09760907, -0.10785484],
>        [ 0.06149647,  0.12468203],...
>  y: array([[ 0.23744165,  0.2381564 ],
>        [-0.13633069, -0.10785359],
>        [ 0.03132561,  0.12468301],...
> 
> ======================================================================
> FAIL: test_arpack.test_symmetric_modes(True, <std-symmetric>, 'f', 2, 'SA', None, 0.5, <function aslinearoperator at 0x103a58f50>, None, 'cayley')
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py", line 197, in runTest
>     self.test(*self.arg)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py", line 235, in eval_evec
>     assert_allclose(LHS, RHS, rtol=rtol, atol=atol, err_msg=err)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 1213, in assert_allclose
>     verbose=verbose, header=header)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 677, in assert_array_compare
>     raise AssertionError(msg)
> AssertionError: 
> Not equal to tolerance rtol=0.00178814, atol=0.000357628
> error for eigsh:standard, typ=f, which=SA, sigma=0.5, mattype=aslinearoperator, OPpart=None, mode=cayley
> (mismatch 100.0%)
>  x: array([[ 0.29524244, -0.2381569 ],
>        [-0.08169955,  0.10785299],
>        [ 0.06645597, -0.12468332],...
>  y: array([[ 0.24180251, -0.23815646],
>        [-0.14191195,  0.10785349],
>        [ 0.03568392, -0.12468307],...
> 
> ======================================================================
> FAIL: test_arpack.test_symmetric_modes(True, <gen-symmetric>, 'f', 2, 'SM', None, 0.5, <function aslinearoperator at 0x103a58f50>, None, 'buckling')
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py", line 197, in runTest
>     self.test(*self.arg)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py", line 235, in eval_evec
>     assert_allclose(LHS, RHS, rtol=rtol, atol=atol, err_msg=err)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 1213, in assert_allclose
>     verbose=verbose, header=header)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 677, in assert_array_compare
>     raise AssertionError(msg)
> AssertionError: 
> Not equal to tolerance rtol=0.00178814, atol=0.000357628
> error for eigsh:general, typ=f, which=SM, sigma=0.5, mattype=aslinearoperator, OPpart=None, mode=buckling
> (mismatch 100.0%)
>  x: array([[-0.10940548,  0.01676016],
>        [-0.07154097,  0.4628113 ],
>        [ 0.06895222,  0.49206394],...
>  y: array([[-0.10940547,  0.05459438],
>        [-0.07154103,  0.31407543],
>        [ 0.06895217,  0.37578294],...
> 
> ======================================================================
> FAIL: test_arpack.test_symmetric_modes(True, <gen-symmetric>, 'f', 2, 'SA', None, 0.5, <function aslinearoperator at 0x103a58f50>, None, 'cayley')
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py", line 197, in runTest
>     self.test(*self.arg)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py", line 235, in eval_evec
>     assert_allclose(LHS, RHS, rtol=rtol, atol=atol, err_msg=err)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 1213, in assert_allclose
>     verbose=verbose, header=header)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 677, in assert_array_compare
>     raise AssertionError(msg)
> AssertionError: 
> Not equal to tolerance rtol=0.00178814, atol=0.000357628
> error for eigsh:general, typ=f, which=SA, sigma=0.5, mattype=aslinearoperator, OPpart=None, mode=cayley
> (mismatch 100.0%)
>  x: array([[-0.4404992 , -0.01935683],
>        [-0.25650678, -0.11053132],
>        [-0.36893024, -0.13223556],...
>  y: array([[-0.44017013, -0.0193569 ],
>        [-0.25525379, -0.11053158],
>        [-0.36818443, -0.13223571],...
> 
> ======================================================================
> FAIL: test_contingency.test_expected_freq
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py", line 197, in runTest
>     self.test(*self.arg)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/stats/tests/test_contingency.py", line 45, in test_expected_freq
>     assert_array_equal(e, np.ones_like(observed))
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 753, in assert_array_equal
>     verbose=verbose, header='Arrays are not equal')
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 677, in assert_array_compare
>     raise AssertionError(msg)
> AssertionError: 
> Arrays are not equal
> 
> (mismatch 100.0%)
>  x: array([[[ 0.,  0.],
>         [ 0.,  0.]],
> ...
>  y: array([[[1, 1],
>         [1, 1]],
> ...
> 
> ======================================================================
> FAIL: test_distributions.test_frozen_fit_ticket_1536
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py", line 197, in runTest
>     self.test(*self.arg)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/stats/tests/test_distributions.py", line 747, in test_frozen_fit_ticket_1536
>     assert_almost_equal(params, true, decimal=2)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 451, in assert_almost_equal
>     return assert_array_almost_equal(actual, desired, decimal, err_msg)
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 846, in assert_array_almost_equal
>     header=('Arrays are not almost equal to %d decimals' % decimal))
>   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 677, in assert_array_compare
>     raise AssertionError(msg)
> AssertionError: 
> Arrays are not almost equal to 2 decimals
> 
> (mismatch 66.6666666667%)
>  x: array([ 1.416,  0.   ,  0.061])
>  y: array([ 0.25,  0.  ,  0.5 ])
> 
> ----------------------------------------------------------------------
> Ran 5095 tests in 54.587s
> 
> FAILED (KNOWNFAIL=12, SKIP=36, failures=9)
> <nose.result.TextTestResult run=5095 errors=0 failures=9>
> 




And some warning that look strange (at least to me):
> site-packages/scipy/spatial/__init__.py:26: RuntimeWarning: numpy.ndarray size changed, may indicate binary incompatibility
> site-packages/scipy/spatial/__init__.py:26: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility


cheers,
 Samuel

From josef.pktd at gmail.com  Fri Jan 20 10:18:31 2012
From: josef.pktd at gmail.com (josef.pktd at gmail.com)
Date: Fri, 20 Jan 2012 10:18:31 -0500
Subject: [SciPy-User] How to calculate Yulewalk with
	scipy.optimize.leastsq
In-Reply-To: <CAA-8Ld_2fd=o+xXzHAVRHoTXL-MKX==aHGjRdAAgrLg9G+NyTQ@mail.gmail.com>
References: <CAA-8Ld9h-FMe9wbt7+RYBVcUYXrZi+RZuRW_eiqkJuRFw2y3Tw@mail.gmail.com>
	<CAMMTP+DR5XW31eqXk41+VTc88KOZZQsGUmwJv_kYL-r9+O=bDg@mail.gmail.com>
	<CAA-8Ld-g673JZ+aiA010vrF+_ttMCrpf=EAgQ5X2J6ArT3oyFg@mail.gmail.com>
	<jf4esc$gr0$2@dough.gmane.org>
	<CAMMTP+DqPOZ6jC8fnPuvYZWiCYgVeFwc8bvzfZpdpyjugh8OLg@mail.gmail.com>
	<1326873009.1991.2.camel@amilo.coursju>
	<CAA-8Ld_2fd=o+xXzHAVRHoTXL-MKX==aHGjRdAAgrLg9G+NyTQ@mail.gmail.com>
Message-ID: <CAMMTP+CLOXLWCt46UUJ49GbKa5SeLaqFDrC_3WzoD4yqWkwn-Q@mail.gmail.com>

On Thu, Jan 19, 2012 at 8:25 AM, klo uo <klonuo at gmail.com> wrote:
> Thanks Fabrice, I'll check talkbox later today and reply if that approach is
> working for me
>
> Josef, thanks for your snippet, thou I have no idea how to use it

a quick guess is that it's the same as the denf function, but given
only the one sided autocovariance function.

> I tried to translate Matlab's yulewalk.m, and it kinda works but with an
> issue. Code is here: http://paste.pocoo.org/show/537224/
>
> Main problem is on lines 79-80 when impulse response is computed. FFT/IFFT
> functions result is different. Everything to that point gives correct result
> in respect to Matlab function. I don't know why is that, is it precision in
> question or else, but I had enough hard time to produce linked and not so
> representative code.

No help from my side, I don't understand the code.

I'm curious why they use log and exp during fft
ifft(exp(fft(hf)))
The only other mention of this that I found is on the octave mailing list.

numf looks interesting if I find a reference to avoid license problems.

Josef

>
> I attached example image to show how results differ slightly.
> Any comment is appreciated
>
> Cheers
>
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user
>


From josef.pktd at gmail.com  Fri Jan 20 10:23:48 2012
From: josef.pktd at gmail.com (josef.pktd at gmail.com)
Date: Fri, 20 Jan 2012 10:23:48 -0500
Subject: [SciPy-User] How to calculate Yulewalk with
	scipy.optimize.leastsq
In-Reply-To: <4F1961EB.5040403@molden.no>
References: <CAA-8Ld9h-FMe9wbt7+RYBVcUYXrZi+RZuRW_eiqkJuRFw2y3Tw@mail.gmail.com>
	<CAMMTP+DR5XW31eqXk41+VTc88KOZZQsGUmwJv_kYL-r9+O=bDg@mail.gmail.com>
	<CAA-8Ld-g673JZ+aiA010vrF+_ttMCrpf=EAgQ5X2J6ArT3oyFg@mail.gmail.com>
	<jf4esc$gr0$2@dough.gmane.org>
	<CAMMTP+DqPOZ6jC8fnPuvYZWiCYgVeFwc8bvzfZpdpyjugh8OLg@mail.gmail.com>
	<1326873009.1991.2.camel@amilo.coursju>
	<4F1961EB.5040403@molden.no>
Message-ID: <CAMMTP+ANzvEs46xTcrM+b3wWps1DHoi=2K5NcvHm5yRAUmocSw@mail.gmail.com>

On Fri, Jan 20, 2012 at 7:45 AM, Sturla Molden <sturla at molden.no> wrote:
> Den 18.01.2012 08:50, skrev Fabrice Silva:
>> Note that talkbox seems to have some stuff on Yule-Walker
>> http://www.ar.media.kyoto-u.ac.jp/members/david/softwares/talkbox/talkbox_doc/index.html
>>
>> in python for educational purpose, and C for performance.
>>
>
> No need to use C for performance here.
>
> Computing the autocovariance for Yule-Walker can be vectorized with
> np.dot, which lets BLAS do the work. Something like this:
>
> def covmtx_yulewalker(x,p):
> ? ? ''' autocorrelation method '''
> ? ? x = np.ascontiguousarray(x)
> ? ? n = x.shape[0]
> ? ? Rxx = np.zeros(p+1)
> ? ? for k in range(0,p+1):
> ? ? ? ? Rxx[k] = np.dot(x[:n-k],x[k:])/(n-k-1.0)
> ? ? return Rxx
>
> Later on, in the code Josef posted, the next bulk of the computation is
> done by LAPACK (linalg.lstsq).
>
> With NumPy linked against optimized BLAS and LAPACK libraries (e.g. MKL,
> ACML, GotoBLAS2, Cray libsci), doing this in C might actually end up
> being slower. Don't waste your time on C before (1) NumPy is proven to
> be too slow and (2) you have good reasons to believe that C will be
> substantially faster. (NumPy users familiar with MATLAB make the latter
> assumption far too often.)

I think the main argument is that levinson-durbin uses fewer
calculations, which might matter if the AR polynomial is very large.

I've read conflicting comments about numerical stability, some argue
in favor of levinson-durbin, some in favor of least squares, but Burg
seems to be generally considered to be numerically better that either
of the other two.

Josef


>
> Sturla
>
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user


From clirakis at gmail.com  Fri Jan 20 15:03:04 2012
From: clirakis at gmail.com (Chris Lirakis)
Date: Fri, 20 Jan 2012 15:03:04 -0500
Subject: [SciPy-User] matrix multiplication
Message-ID: <CAKCnadchRmhCTVTm6+pHQ6kypdk5yjeEot9hMeUbw08yu3qw8w@mail.gmail.com>

I have tried the following and they all yield the same result.

A = zeros(3,1)
B = A * A.T
B = [[ 0 0 0]
       [0 0 0]
       [0  0 0]]

A = matrix(zeros(3,1)
B = A * A.T
B = [[ 0 0 0]
       [0 0 0]
       [0  0 0]]

I would have thought that the result should have been [[0]]
if I do the following:
A = matrix([[0 0 0]]) Then A * A.T yields [[0]]

Can someone tell me why and how I might fix this?
Chris

-- 
Chris Lirakis
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From josh.k.lawrence at gmail.com  Fri Jan 20 15:07:38 2012
From: josh.k.lawrence at gmail.com (Josh Lawrence)
Date: Fri, 20 Jan 2012 15:07:38 -0500
Subject: [SciPy-User] matrix multiplication
In-Reply-To: <CAKCnadchRmhCTVTm6+pHQ6kypdk5yjeEot9hMeUbw08yu3qw8w@mail.gmail.com>
References: <CAKCnadchRmhCTVTm6+pHQ6kypdk5yjeEot9hMeUbw08yu3qw8w@mail.gmail.com>
Message-ID: <053CEEDA-186C-4DE3-9419-CAD95C749282@gmail.com>

You need to specify the first argument of zeros as a tuple:

A = matrix(zeros((3,1)))

That will result in a 3x1 matrix. So

B = A * A.T

will be a 3x3 matrix (3x1 * 1x3).

If you are looking to get a scalar back, you want

A = matrix(zeros((1,3)))
B = A *A.T

When you are not working with matrices, use np.dot(A,A.T).

Cheers,

--Josh

On Jan 20, 2012, at 3:03 PM, Chris Lirakis wrote:

> I have tried the following and they all yield the same result. 
> 
> A = zeros(3,1) 
> B = A * A.T
> B = [[ 0 0 0]
>        [0 0 0]
>        [0  0 0]]
> 
> A = matrix(zeros(3,1) 
> B = A * A.T
> B = [[ 0 0 0]
>        [0 0 0]
>        [0  0 0]]
> 
> I would have thought that the result should have been [[0]]
> if I do the following:
> A = matrix([[0 0 0]]) Then A * A.T yields [[0]] 
> 
> Can someone tell me why and how I might fix this?
> Chris
> 
> -- 
> Chris Lirakis
> 
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user

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From vincefn at users.sourceforge.net  Fri Jan 20 15:33:09 2012
From: vincefn at users.sourceforge.net (Vincent Favre-Nicolin)
Date: Fri, 20 Jan 2012 21:33:09 +0100
Subject: [SciPy-User] FortranFile and large records
In-Reply-To: <86c3c9603fae4b0abf44778785406209@EXCAH-B3.intra.cea.fr>
References: <4F1841F2.1030100@users.sourceforge.net>
	<86c3c9603fae4b0abf44778785406209@EXCAH-B3.intra.cea.fr>
Message-ID: <4F19CF85.6090207@users.sourceforge.net>

Le 20/01/2012 11:25, Sturla Molden a ?crit :
> Why? The FortranFile cookbook receipe is based on fundamentally wrong 
> assumptions. If it works it is by pure accident. I suggest it is removed 
> from the wiki.

  Even if it is not a complete solution, at least it allows many people
to read their files.
  If there is another solution to import more fortran record file into
numpy, then fine ! But until then, this code remains a very good help to
anyone who does not want to bother writing a fortran program just to
read fortran data (even if it does not work with data from /every/ f
compiler).

	Vincent


From sturla at molden.no  Fri Jan 20 22:48:30 2012
From: sturla at molden.no (Sturla Molden)
Date: Sat, 21 Jan 2012 04:48:30 +0100
Subject: [SciPy-User] matrix multiplication
In-Reply-To: <CAKCnadchRmhCTVTm6+pHQ6kypdk5yjeEot9hMeUbw08yu3qw8w@mail.gmail.com>
References: <CAKCnadchRmhCTVTm6+pHQ6kypdk5yjeEot9hMeUbw08yu3qw8w@mail.gmail.com>
Message-ID: <27988685-B7DF-487A-9D80-CAC51FBA2FE3@molden.no>


Den 20. jan. 2012 kl. 21:03 skrev Chris Lirakis <clirakis at gmail.com>:

> I have tried the following and they all yield the same result. 
> 
> A = zeros(3,1) 
> B = A * A.T
> B = [[ 0 0 0]
>        [0 0 0]
>        [0  0 0]]


This is due to NumPy's array broadcasting rules (arrays are not matrices). Fortran 90 would do this as well, MATLAB would not (.* does not broadcast).

Use np.dot for vector dot product and matrix multiplication when working with arrays.


> 
> A = matrix(zeros(3,1) 
> B = A * A.T
> B = [[ 0 0 0]
>        [0 0 0]
>        [0  0 0]]

Outer-product, 3x1 * 1x3 --> 3x3


> 
> I would have thought that the result should have been [[0]]
> if I do the following:
> A = matrix([[0 0 0]]) Then A * A.T yields [[0]] 

Inner-product, 1x3 * 3x1 --> 1x1

> 
> Can someone tell me why and how I might fix this?
> Chris
> 

Nothing to fix, just repeat matrix multiplication rules from your linear algebra textbook.

Sturla

From silva at lma.cnrs-mrs.fr  Sat Jan 21 05:29:34 2012
From: silva at lma.cnrs-mrs.fr (silva at lma.cnrs-mrs.fr)
Date: Sat, 21 Jan 2012 11:29:34 +0100
Subject: [SciPy-User] How to calculate Yulewalk
	with	scipy.optimize.leastsq
In-Reply-To: <CAMMTP+CLOXLWCt46UUJ49GbKa5SeLaqFDrC_3WzoD4yqWkwn-Q@mail.gmail.com>
References: <CAA-8Ld9h-FMe9wbt7+RYBVcUYXrZi+RZuRW_eiqkJuRFw2y3Tw@mail.gmail.com>
	<CAMMTP+DR5XW31eqXk41+VTc88KOZZQsGUmwJv_kYL-r9+O=bDg@mail.gmail.com>
	<CAA-8Ld-g673JZ+aiA010vrF+_ttMCrpf=EAgQ5X2J6ArT3oyFg@mail.gmail.com>
	<jf4esc$gr0$2@dough.gmane.org>
	<CAMMTP+DqPOZ6jC8fnPuvYZWiCYgVeFwc8bvzfZpdpyjugh8OLg@mail.gmail.com>
	<1326873009.1991.2.camel@amilo.coursju>
	<CAA-8Ld_2fd=o+xXzHAVRHoTXL-MKX==aHGjRdAAgrLg9G+NyTQ@mail.gmail.com>
	<CAMMTP+CLOXLWCt46UUJ49GbKa5SeLaqFDrC_3WzoD4yqWkwn-Q@mail.gmail.com>
Message-ID: <20120121112934.3372596tba7igvwg@www.lma.cnrs-mrs.fr>

> I'm curious why they use log and exp during fft
> ifft(exp(fft(hf)))
> The only other mention of this that I found is on the octave mailing list.

Looks like cepstrum, a quite common tool in speech analysis, but in  
fact it is not the same think

Cepstrum would be
log |ft(f)|
see http://en.wikipedia.org/wiki/Cepstrum


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From ralf.gommers at googlemail.com  Sat Jan 21 07:53:27 2012
From: ralf.gommers at googlemail.com (Ralf Gommers)
Date: Sat, 21 Jan 2012 20:53:27 +0800
Subject: [SciPy-User] SciPy 0.10: 8 failures on OS X Lion
In-Reply-To: <8AB8D94B-FCA2-425B-B5AE-116C9BA2F71F@samueljohn.de>
References: <8AB8D94B-FCA2-425B-B5AE-116C9BA2F71F@samueljohn.de>
Message-ID: <CABL7CQh0mxTFNEb0Gc7duW=wWY5O-gwsq-RnU9Jx_JX8ZuC4ng@mail.gmail.com>

On Fri, Jan 20, 2012 at 9:23 PM, Samuel John <scipy at samueljohn.de> wrote:

> Hi SciPy devs,
>
> I just want to report the following failures. Does anybody on OSX get the
> same/similar?
>

The Arpack ones are causing problems on several platforms, they should be
disabled. It's on my (way too long) TODO list.

The test_contingency failure I've seen before on OS X, but usually just
once. Since I can't reproduce it I suspect it's a nose bug. The frozen_fit
one I'm not sure about. Does it fail consistently for you? If so, can you
run the test as standalone script and have it still failing?

Ralf



> Are they "known" ?
> Should I try scipy 0.11 because they are fixed there, perhaps?
> Six out of eight are related to arpack.
> I have installed numpy, scipy with gfortran provided by homebrew and I set
> the CC, CXX to use the non-llvm compilers of the 4.2 series.
>
>
> > Python 2.7.2 (default, Jan 13 2012, 15:00:18)
> > [GCC 4.2.1 (Based on Apple Inc. build 5658) (LLVM build 2336.1.00)] on
> darwin
> > >>> import scipy
> > >>> scipy.test()
> > Running unit tests for scipy
> > NumPy version 2.0.0.dev-55472ca
> > NumPy is installed in
> /usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy
> > SciPy version 0.10.0
> > SciPy is installed in
> /usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy
> > Python version 2.7.2 (default, Jan 13 2012, 15:00:18) [GCC 4.2.1 (Based
> on Apple Inc. build 5658) (LLVM build 2336.1.00)]
> > nose version 1.1.2
> > .
> > .
> > .
> > ======================================================================
> > FAIL: test_arpack.test_symmetric_modes(True, <std-symmetric>, 'f', 2,
> 'LM', None, 0.5, <function aslinearoperator at 0x103a58f50>, None, 'normal')
> > ----------------------------------------------------------------------
> > Traceback (most recent call last):
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> >     self.test(*self.arg)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py",
> line 235, in eval_evec
> >     assert_allclose(LHS, RHS, rtol=rtol, atol=atol, err_msg=err)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py",
> line 1213, in assert_allclose
> >     verbose=verbose, header=header)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py",
> line 677, in assert_array_compare
> >     raise AssertionError(msg)
> > AssertionError:
> > Not equal to tolerance rtol=0.00178814, atol=0.000357628
> > error for eigsh:standard, typ=f, which=LM, sigma=0.5,
> mattype=aslinearoperator, OPpart=None, mode=normal
> > (mismatch 100.0%)
> >  x: array([[ 0.23815642,  0.1763755 ],
> >        [-0.10785346, -0.32103487],
> >        [ 0.12468303, -0.11230416],...
> >  y: array([[ 0.23815642,  0.24814051],
> >        [-0.10785347, -0.15634772],
> >        [ 0.12468302,  0.05671416],...
> >
> > ======================================================================
> > FAIL: test_arpack.test_symmetric_modes(True, <std-symmetric>, 'f', 2,
> 'LM', None, 0.5, <function aslinearoperator at 0x103a58f50>, None, 'cayley')
> > ----------------------------------------------------------------------
> > Traceback (most recent call last):
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> >     self.test(*self.arg)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py",
> line 235, in eval_evec
> >     assert_allclose(LHS, RHS, rtol=rtol, atol=atol, err_msg=err)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py",
> line 1213, in assert_allclose
> >     verbose=verbose, header=header)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py",
> line 677, in assert_array_compare
> >     raise AssertionError(msg)
> > AssertionError:
> > Not equal to tolerance rtol=0.00178814, atol=0.000357628
> > error for eigsh:standard, typ=f, which=LM, sigma=0.5,
> mattype=aslinearoperator, OPpart=None, mode=cayley
> > (mismatch 100.0%)
> >  x: array([[ 0.23815693, -0.33630507],
> >        [-0.10785286,  0.02168   ],
> >        [ 0.12468344, -0.11036437],...
> >  y: array([[ 0.23815643, -0.2405392 ],
> >        [-0.10785349,  0.14390968],
> >        [ 0.12468311, -0.04574991],...
> >
> > ======================================================================
> > FAIL: test_arpack.test_symmetric_modes(True, <std-symmetric>, 'f', 2,
> 'LA', None, 0.5, <function aslinearoperator at 0x103a58f50>, None, 'normal')
> > ----------------------------------------------------------------------
> > Traceback (most recent call last):
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> >     self.test(*self.arg)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py",
> line 235, in eval_evec
> >     assert_allclose(LHS, RHS, rtol=rtol, atol=atol, err_msg=err)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py",
> line 1213, in assert_allclose
> >     verbose=verbose, header=header)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py",
> line 677, in assert_array_compare
> >     raise AssertionError(msg)
> > AssertionError:
> > Not equal to tolerance rtol=0.00178814, atol=0.000357628
> > error for eigsh:standard, typ=f, which=LA, sigma=0.5,
> mattype=aslinearoperator, OPpart=None, mode=normal
> > (mismatch 100.0%)
> >  x: array([[  28.80129188,   -0.6379945 ],
> >        [  34.79312355,    0.27066791],
> >        [-270.23255444,    0.4851834 ],...
> >  y: array([[  3.93467650e+03,  -6.37994494e-01],
> >        [  3.90913859e+03,   2.70667916e-01],
> >        [ -3.62176382e+04,   4.85183382e-01],...
> >
> > ======================================================================
> > FAIL: test_arpack.test_symmetric_modes(True, <std-symmetric>, 'f', 2,
> 'SA', None, 0.5, <function aslinearoperator at 0x103a58f50>, None, 'normal')
> > ----------------------------------------------------------------------
> > Traceback (most recent call last):
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> >     self.test(*self.arg)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py",
> line 235, in eval_evec
> >     assert_allclose(LHS, RHS, rtol=rtol, atol=atol, err_msg=err)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py",
> line 1213, in assert_allclose
> >     verbose=verbose, header=header)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py",
> line 677, in assert_array_compare
> >     raise AssertionError(msg)
> > AssertionError:
> > Not equal to tolerance rtol=0.00178814, atol=0.000357628
> > error for eigsh:standard, typ=f, which=SA, sigma=0.5,
> mattype=aslinearoperator, OPpart=None, mode=normal
> > (mismatch 100.0%)
> >  x: array([[ 0.26260981,  0.23815559],
> >        [-0.09760907, -0.10785484],
> >        [ 0.06149647,  0.12468203],...
> >  y: array([[ 0.23744165,  0.2381564 ],
> >        [-0.13633069, -0.10785359],
> >        [ 0.03132561,  0.12468301],...
> >
> > ======================================================================
> > FAIL: test_arpack.test_symmetric_modes(True, <std-symmetric>, 'f', 2,
> 'SA', None, 0.5, <function aslinearoperator at 0x103a58f50>, None, 'cayley')
> > ----------------------------------------------------------------------
> > Traceback (most recent call last):
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> >     self.test(*self.arg)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py",
> line 235, in eval_evec
> >     assert_allclose(LHS, RHS, rtol=rtol, atol=atol, err_msg=err)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py",
> line 1213, in assert_allclose
> >     verbose=verbose, header=header)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py",
> line 677, in assert_array_compare
> >     raise AssertionError(msg)
> > AssertionError:
> > Not equal to tolerance rtol=0.00178814, atol=0.000357628
> > error for eigsh:standard, typ=f, which=SA, sigma=0.5,
> mattype=aslinearoperator, OPpart=None, mode=cayley
> > (mismatch 100.0%)
> >  x: array([[ 0.29524244, -0.2381569 ],
> >        [-0.08169955,  0.10785299],
> >        [ 0.06645597, -0.12468332],...
> >  y: array([[ 0.24180251, -0.23815646],
> >        [-0.14191195,  0.10785349],
> >        [ 0.03568392, -0.12468307],...
> >
> > ======================================================================
> > FAIL: test_arpack.test_symmetric_modes(True, <gen-symmetric>, 'f', 2,
> 'SM', None, 0.5, <function aslinearoperator at 0x103a58f50>, None,
> 'buckling')
> > ----------------------------------------------------------------------
> > Traceback (most recent call last):
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> >     self.test(*self.arg)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py",
> line 235, in eval_evec
> >     assert_allclose(LHS, RHS, rtol=rtol, atol=atol, err_msg=err)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py",
> line 1213, in assert_allclose
> >     verbose=verbose, header=header)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py",
> line 677, in assert_array_compare
> >     raise AssertionError(msg)
> > AssertionError:
> > Not equal to tolerance rtol=0.00178814, atol=0.000357628
> > error for eigsh:general, typ=f, which=SM, sigma=0.5,
> mattype=aslinearoperator, OPpart=None, mode=buckling
> > (mismatch 100.0%)
> >  x: array([[-0.10940548,  0.01676016],
> >        [-0.07154097,  0.4628113 ],
> >        [ 0.06895222,  0.49206394],...
> >  y: array([[-0.10940547,  0.05459438],
> >        [-0.07154103,  0.31407543],
> >        [ 0.06895217,  0.37578294],...
> >
> > ======================================================================
> > FAIL: test_arpack.test_symmetric_modes(True, <gen-symmetric>, 'f', 2,
> 'SA', None, 0.5, <function aslinearoperator at 0x103a58f50>, None, 'cayley')
> > ----------------------------------------------------------------------
> > Traceback (most recent call last):
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> >     self.test(*self.arg)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py",
> line 235, in eval_evec
> >     assert_allclose(LHS, RHS, rtol=rtol, atol=atol, err_msg=err)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py",
> line 1213, in assert_allclose
> >     verbose=verbose, header=header)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py",
> line 677, in assert_array_compare
> >     raise AssertionError(msg)
> > AssertionError:
> > Not equal to tolerance rtol=0.00178814, atol=0.000357628
> > error for eigsh:general, typ=f, which=SA, sigma=0.5,
> mattype=aslinearoperator, OPpart=None, mode=cayley
> > (mismatch 100.0%)
> >  x: array([[-0.4404992 , -0.01935683],
> >        [-0.25650678, -0.11053132],
> >        [-0.36893024, -0.13223556],...
> >  y: array([[-0.44017013, -0.0193569 ],
> >        [-0.25525379, -0.11053158],
> >        [-0.36818443, -0.13223571],...
> >
> > ======================================================================
> > FAIL: test_contingency.test_expected_freq
> > ----------------------------------------------------------------------
> > Traceback (most recent call last):
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> >     self.test(*self.arg)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/stats/tests/test_contingency.py",
> line 45, in test_expected_freq
> >     assert_array_equal(e, np.ones_like(observed))
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py",
> line 753, in assert_array_equal
> >     verbose=verbose, header='Arrays are not equal')
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py",
> line 677, in assert_array_compare
> >     raise AssertionError(msg)
> > AssertionError:
> > Arrays are not equal
> >
> > (mismatch 100.0%)
> >  x: array([[[ 0.,  0.],
> >         [ 0.,  0.]],
> > ...
> >  y: array([[[1, 1],
> >         [1, 1]],
> > ...
> >
> > ======================================================================
> > FAIL: test_distributions.test_frozen_fit_ticket_1536
> > ----------------------------------------------------------------------
> > Traceback (most recent call last):
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> >     self.test(*self.arg)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/stats/tests/test_distributions.py",
> line 747, in test_frozen_fit_ticket_1536
> >     assert_almost_equal(params, true, decimal=2)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py",
> line 451, in assert_almost_equal
> >     return assert_array_almost_equal(actual, desired, decimal, err_msg)
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py",
> line 846, in assert_array_almost_equal
> >     header=('Arrays are not almost equal to %d decimals' % decimal))
> >   File
> "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py",
> line 677, in assert_array_compare
> >     raise AssertionError(msg)
> > AssertionError:
> > Arrays are not almost equal to 2 decimals
> >
> > (mismatch 66.6666666667%)
> >  x: array([ 1.416,  0.   ,  0.061])
> >  y: array([ 0.25,  0.  ,  0.5 ])
> >
> > ----------------------------------------------------------------------
> > Ran 5095 tests in 54.587s
> >
> > FAILED (KNOWNFAIL=12, SKIP=36, failures=9)
> > <nose.result.TextTestResult run=5095 errors=0 failures=9>
> >
>
>
>
>
> And some warning that look strange (at least to me):
> > site-packages/scipy/spatial/__init__.py:26: RuntimeWarning:
> numpy.ndarray size changed, may indicate binary incompatibility
> > site-packages/scipy/spatial/__init__.py:26: RuntimeWarning: numpy.ufunc
> size changed, may indicate binary incompatibility
>
>
> cheers,
>  Samuel
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user
>
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From evilper at gmail.com  Sat Jan 21 08:14:49 2012
From: evilper at gmail.com (Per Nielsen)
Date: Sat, 21 Jan 2012 14:14:49 +0100
Subject: [SciPy-User] Sparse jacobian in scipy ODE solver
Message-ID: <CAGtYnKgd9SfqOCJ8RdXYg7GWV1eFB3ZyZy235JttUkzwO_AUYg@mail.gmail.com>

Hi all

I am working with large linear system 1st order ODE systems of the form

dydt = M * y

where M is very sparse complex valued matrix. I currently use the ode class
from scipy.integrator like:

from scipy.integrate import ode
r = ode(f)
r.set_integrator('zvode', method='adams')

and calculate f = dydt as M.dot(y). I would like to make use of the
jacobian of dydt, which for my linear problem is simply M, to speed up my
simulations. However, when I supply a sparse matrix as the jacobian I get
the following error (see attached script):

rv_cb_arr is NULL
Call-back cb_jac_in_zvode__user__routines failed.
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
/Users/per/Dropbox/DTU/python/tryouts/ode_jac_test.py in <module>()
     61
     62     while r.successful() and r.t < t1:
---> 63         r.integrate(r.t + dt)
     64         ts.append(r.t)
     65         ys.append(r.y)

/Library/Frameworks/EPD64.framework/Versions/7.1/lib/python2.7/site-packages/scipy/integrate/ode.py
in integrate(self, t, step, relax)
    324         self.y,self.t = mth(self.f,self.jac or (lambda :None),
    325                             self.y,self.t,t,
--> 326                             self.f_params,self.jac_params)
    327         return self.y
    328

/Library/Frameworks/EPD64.framework/Versions/7.1/lib/python2.7/site-packages/scipy/integrate/ode.py
in run(self, *args)
    684
    685     def run(self,*args):
--> 686         y1,t,istate =
self.runner(*(args[:5]+tuple(self.call_args)+args[5:]))
    687         if istate < 0:
    688             warnings.warn('zvode: ' +

TypeError: a float is required

It seems that the jacobian can not be sparse. But is this a fundamental
problem or could one somehow work around it and still use ode from scipy?

Any help or comments would be appreciated.

Best,

Per
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From pav at iki.fi  Sat Jan 21 08:30:59 2012
From: pav at iki.fi (Pauli Virtanen)
Date: Sat, 21 Jan 2012 14:30:59 +0100
Subject: [SciPy-User] Sparse jacobian in scipy ODE solver
In-Reply-To: <CAGtYnKgd9SfqOCJ8RdXYg7GWV1eFB3ZyZy235JttUkzwO_AUYg@mail.gmail.com>
References: <CAGtYnKgd9SfqOCJ8RdXYg7GWV1eFB3ZyZy235JttUkzwO_AUYg@mail.gmail.com>
Message-ID: <jfeemj$lt0$1@dough.gmane.org>

21.01.2012 14:14, Per Nielsen kirjoitti:
[clip: zvode]
> It seems that the jacobian can not be sparse. But is this a fundamental
> problem or could one somehow work around it and still use ode from scipy?

The solvers don't support sparse matrices (they support banded matrices, 
though). I don't think there's a way around this, as they are mostly 
Fortran code.

-- 
Pauli Virtanen



From yyc at solvcon.net  Sat Jan 21 09:54:13 2012
From: yyc at solvcon.net (Yung-Yu Chen)
Date: Sat, 21 Jan 2012 22:54:13 +0800
Subject: [SciPy-User] ANN: SOLVCON 0.1.1
Message-ID: <CACHrFq2FP9SH9DGk7b-E=D5XkD7gxXvn=UvRFwKqdNrgLnqEKA@mail.gmail.com>

Hello,

I am pleased to announce version 0.1.1 of SOLVCON.  SOLVCON is a
Python-based,
multi-physics software framework for solving first-order hyperbolic PDEs.

The source tarball can be downloaded at
http://bitbucket.org/yungyuc/solvcon/downloads .  More information can be
found at http://solvcon.net/ .

This release adds a loader of Gmsh mesh format and fixes several bugs.

New features:

- Add a loader for Gmsh ASCII mesh format.  The loader locates in
  solvcon.io.gmsh and is implemented as pure Python code.  ``scg mesh``
command
  line tool can recognize the format.  Issue #52.
- Revamp the dependency building system to support older OSes and proxies
that
  need authentication.  Issue #53.
- Extract the SCons commands for building the Epydoc and Sphinx document
from
  SConstruct into standalone SCons tools.  Two new tools are added in the
  directory ``site_scons/site_tools/``: ``sphinx.py`` and
``scons_epydoc.py``.
  Note that the SCons tool for Epydoc cannot be named as ``epydoc.py`` or
the
  name collides with the real ``epydoc`` package.
- Add Gmsh and Sphinx into ground/.

Bug-fix:

- Issue #49: "No Vtk for final time step".  Output timing of CollectHook and
  MarchSave.
- Issue #54: "Shared objects are not found under Mac OS X".  Thank you
Nathan.
- Issue #38: "soln/dsoln shouldn't be hard-coded".

-- 
Yung-Yu Chen
http://solvcon.net/yyc/
+886 (99) 129 4763
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From dineshbvadhia at hotmail.com  Sat Jan 21 13:34:35 2012
From: dineshbvadhia at hotmail.com (Dinesh B Vadhia)
Date: Sat, 21 Jan 2012 10:34:35 -0800
Subject: [SciPy-User] save/load scipy sparse csr_matrix in a portable data
	format
Message-ID: <COL103-DS9D9D4BBDE73FA1E8459A0A3840@phx.gbl>

How do you save/load a scipy sparse csr_matrix in a portable format? The sparse matrix is created in Python 3.2.2 (Windows 64-bit) to run on Python 2.7.2 (Linux 64-bit) . I've tried numpy.save and numpy.load as well as scipy.io.mmwrite() and scipy.io.mmread() and none of the methods work.
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From evilper at gmail.com  Sun Jan 22 06:16:24 2012
From: evilper at gmail.com (Per Nielsen)
Date: Sun, 22 Jan 2012 12:16:24 +0100
Subject: [SciPy-User] Sparse jacobian in scipy ODE solver
In-Reply-To: <jfeemj$lt0$1@dough.gmane.org>
References: <CAGtYnKgd9SfqOCJ8RdXYg7GWV1eFB3ZyZy235JttUkzwO_AUYg@mail.gmail.com>
	<jfeemj$lt0$1@dough.gmane.org>
Message-ID: <CAGtYnKg6ubWoWi5FyYcM8VvceZ+yr1WWOAnY28wyoNGB-AuZ+A@mail.gmail.com>

Thanks for your fast reply.

Is the support for banded jacobians available from the current scipy
implementation or should I get my hands dirty in fortran code? =)

Per

On Sat, Jan 21, 2012 at 14:30, Pauli Virtanen <pav at iki.fi> wrote:

> 21.01.2012 14:14, Per Nielsen kirjoitti:
> [clip: zvode]
> > It seems that the jacobian can not be sparse. But is this a fundamental
> > problem or could one somehow work around it and still use ode from scipy?
>
> The solvers don't support sparse matrices (they support banded matrices,
> though). I don't think there's a way around this, as they are mostly
> Fortran code.
>
> --
> Pauli Virtanen
>
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user
>
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From pav at iki.fi  Sun Jan 22 06:27:46 2012
From: pav at iki.fi (Pauli Virtanen)
Date: Sun, 22 Jan 2012 11:27:46 +0000 (UTC)
Subject: [SciPy-User] Sparse jacobian in scipy ODE solver
References: <CAGtYnKgd9SfqOCJ8RdXYg7GWV1eFB3ZyZy235JttUkzwO_AUYg@mail.gmail.com>
	<jfeemj$lt0$1@dough.gmane.org>
	<CAGtYnKg6ubWoWi5FyYcM8VvceZ+yr1WWOAnY28wyoNGB-AuZ+A@mail.gmail.com>
Message-ID: <loom.20120122T122647-146@post.gmane.org>

Per Nielsen <evilper <at> gmail.com> writes:
> Is the support for banded jacobians available from the current scipy
> implementation or should I get my hands dirty in fortran code? =)

Yes, check the documentation for `l/rband`:
http://docs.scipy.org/doc/scipy/reference/generated/scipy.integrate.ode.html#scip
y.integrate.ode

-- 
Pauli Virtanen



From cournape at gmail.com  Sun Jan 22 07:12:53 2012
From: cournape at gmail.com (David Cournapeau)
Date: Sun, 22 Jan 2012 12:12:53 +0000
Subject: [SciPy-User] How to calculate Yulewalk with
	scipy.optimize.leastsq
In-Reply-To: <4F1961EB.5040403@molden.no>
References: <CAA-8Ld9h-FMe9wbt7+RYBVcUYXrZi+RZuRW_eiqkJuRFw2y3Tw@mail.gmail.com>
	<CAMMTP+DR5XW31eqXk41+VTc88KOZZQsGUmwJv_kYL-r9+O=bDg@mail.gmail.com>
	<CAA-8Ld-g673JZ+aiA010vrF+_ttMCrpf=EAgQ5X2J6ArT3oyFg@mail.gmail.com>
	<jf4esc$gr0$2@dough.gmane.org>
	<CAMMTP+DqPOZ6jC8fnPuvYZWiCYgVeFwc8bvzfZpdpyjugh8OLg@mail.gmail.com>
	<1326873009.1991.2.camel@amilo.coursju>
	<4F1961EB.5040403@molden.no>
Message-ID: <CAGY4rcWfpeAasoFKtTR80V2PDBOtb8QysLfugOkBzw7hC3s0jQ@mail.gmail.com>

On Fri, Jan 20, 2012 at 12:45 PM, Sturla Molden <sturla at molden.no> wrote:
> Den 18.01.2012 08:50, skrev Fabrice Silva:
>> Note that talkbox seems to have some stuff on Yule-Walker
>> http://www.ar.media.kyoto-u.ac.jp/members/david/softwares/talkbox/talkbox_doc/index.html
>>
>> in python for educational purpose, and C for performance.
>>
>
> No need to use C for performance here.

We are not talking about the same algorithm here. Because the
correlation matrix has a very specific structure (toeplitz), it can be
inverted in O(N^2) instead of O(N^3), this is what the Levinson Durbin
algorithm is all about. You cannot easily implement Levinson-Durbin in
numpy, because of its recursive nature.

I think you can also reasonably expect talkbox author to know one
thing or two about numpy ;)

David


From sturla at molden.no  Sun Jan 22 08:05:18 2012
From: sturla at molden.no (Sturla Molden)
Date: Sun, 22 Jan 2012 14:05:18 +0100
Subject: [SciPy-User] How to calculate Yulewalk with
	scipy.optimize.leastsq
In-Reply-To: <CAGY4rcWfpeAasoFKtTR80V2PDBOtb8QysLfugOkBzw7hC3s0jQ@mail.gmail.com>
References: <CAA-8Ld9h-FMe9wbt7+RYBVcUYXrZi+RZuRW_eiqkJuRFw2y3Tw@mail.gmail.com>
	<CAMMTP+DR5XW31eqXk41+VTc88KOZZQsGUmwJv_kYL-r9+O=bDg@mail.gmail.com>
	<CAA-8Ld-g673JZ+aiA010vrF+_ttMCrpf=EAgQ5X2J6ArT3oyFg@mail.gmail.com>
	<jf4esc$gr0$2@dough.gmane.org>
	<CAMMTP+DqPOZ6jC8fnPuvYZWiCYgVeFwc8bvzfZpdpyjugh8OLg@mail.gmail.com>
	<1326873009.1991.2.camel@amilo.coursju>
	<4F1961EB.5040403@molden.no>
	<CAGY4rcWfpeAasoFKtTR80V2PDBOtb8QysLfugOkBzw7hC3s0jQ@mail.gmail.com>
Message-ID: <4F1C098E.5040703@molden.no>

Den 22.01.2012 13:12, skrev David Cournapeau:
> We are not talking about the same algorithm here. Because the
> correlation matrix has a very specific structure (toeplitz), it can be
> inverted in O(N^2) instead of O(N^3), this is what the Levinson Durbin
> algorithm is all about. You cannot easily implement Levinson-Durbin in
> numpy, because of its recursive nature.
>
> I think you can also reasonably expect talkbox author to know one
> thing or two about numpy ;)

Sure :)

But whenever I have used autoregression, it seems the expensive part is 
estimating the covariance, not inverting it.

Levinson-Durbin would belong in scipy.linalg though, it's not just for 
Yule-Walker.

Sturla


From wardefar at iro.umontreal.ca  Mon Jan 23 08:14:22 2012
From: wardefar at iro.umontreal.ca (David Warde-Farley)
Date: Mon, 23 Jan 2012 08:14:22 -0500
Subject: [SciPy-User] save/load scipy sparse csr_matrix in a portable
	data format
In-Reply-To: <COL103-DS9D9D4BBDE73FA1E8459A0A3840@phx.gbl>
References: <COL103-DS9D9D4BBDE73FA1E8459A0A3840@phx.gbl>
Message-ID: <B5751591-4FA4-4F53-8D6C-7F96BAF9856B@iro.umontreal.ca>

On 2012-01-21, at 1:34 PM, Dinesh B Vadhia wrote:

> How do you save/load a scipy sparse csr_matrix in a portable format? The sparse matrix is created in Python 3.2.2 (Windows 64-bit) to run on Python 2.7.2 (Linux 64-bit) . I've tried numpy.save and numpy.load as well as scipy.io.mmwrite() and scipy.io.mmread() and none of the methods work.

A csr_matrix really has only 3 data attributes that matter: .data, .indices, and .indptr. They are all simple ndarrays, so numpy.save will work on them. Save those three arrays with numpy.save or numpy.savez, load them back with numpy.load, and then recreate the sparse matrix object with

	new_csr = csr_matrix((data, indices, indptr), shape=(M, N))

Could be smoother but it gets the job done.

David

From dineshbvadhia at hotmail.com  Mon Jan 23 14:26:32 2012
From: dineshbvadhia at hotmail.com (Dinesh B Vadhia)
Date: Mon, 23 Jan 2012 11:26:32 -0800
Subject: [SciPy-User] save/load scipy sparse csr_matrix in a portable
	data format
Message-ID: <COL103-DS178FB0C8BAFCE150B685D0A38A0@phx.gbl>

Ah, thank-you David.  Didn't see any doc mentioning re-creating the sparse matrix.  Brill!


--------------------------------------------------------------------------------
Date: Mon, 23 Jan 2012 08:14:22 -0500
From: David Warde-Farley <wardefar at iro.umontreal.ca>
Subject: Re: [SciPy-User] save/load scipy sparse csr_matrix in a
portable data format
To: SciPy Users List <scipy-user at scipy.org>
Message-ID: <B5751591-4FA4-4F53-8D6C-7F96BAF9856B at iro.umontreal.ca>
Content-Type: text/plain; charset=us-ascii

On 2012-01-21, at 1:34 PM, Dinesh B Vadhia wrote:

> How do you save/load a scipy sparse csr_matrix in a portable format? The sparse matrix is created in Python 3.2.2 (Windows 64-bit) to run on Python 2.7.2 (Linux 64-bit) . I've tried numpy.save and numpy.load as well as scipy.io.mmwrite() and scipy.io.mmread() and none of the methods work.

A csr_matrix really has only 3 data attributes that matter: .data, .indices, and .indptr. They are all simple ndarrays, so numpy.save will work on them. Save those three arrays with numpy.save or numpy.savez, load them back with numpy.load, and then recreate the sparse matrix object with

new_csr = csr_matrix((data, indices, indptr), shape=(M, N))

Could be smoother but it gets the job done.

David

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From wardefar at iro.umontreal.ca  Mon Jan 23 15:07:12 2012
From: wardefar at iro.umontreal.ca (David Warde-Farley)
Date: Mon, 23 Jan 2012 15:07:12 -0500
Subject: [SciPy-User] save/load scipy sparse csr_matrix in a portable
 data format
In-Reply-To: <COL103-DS178FB0C8BAFCE150B685D0A38A0@phx.gbl>
References: <COL103-DS178FB0C8BAFCE150B685D0A38A0@phx.gbl>
Message-ID: <20120123200711.GB28091@ravage>

On Mon, Jan 23, 2012 at 11:26:32AM -0800, Dinesh B Vadhia wrote:
> Ah, thank-you David.  Didn't see any doc mentioning re-creating the sparse matrix.  Brill!

If you have a look at the csr_matrix docstring there are a whole bunch of
different constructors for it. Ditto with csc and coo, at least.

Cheers,

David


From johann.cohentanugi at gmail.com  Mon Jan 23 18:12:18 2012
From: johann.cohentanugi at gmail.com (Johann Cohen-Tanugi)
Date: Tue, 24 Jan 2012 00:12:18 +0100
Subject: [SciPy-User] special.kv goes from 0 to nan for large numbers
Message-ID: <4F1DE952.7030402@gmail.com>

Hi there, I have scipy 0.10 vanilla from the packages distributed with 
Ubuntu 11.10, and I see the following :

In [1]: import scipy

In [2]: scipy.__version__
Out[2]: '0.10.0'

In [3]: import scipy.special as sp

In [4]: sp.kv(1./3.,1.08e+09)
Out[4]: nan

In [5]: sp.kv(1./3.,1.07e+09)
Out[5]: 0.0

I guess this has to dow with a cephes and big numbers.... Is it fixed on 
github already, or is it a known bug? Or is it a feature and not a bug? 
My machine is 64bit BTW.
Best,
johann


From pav at iki.fi  Mon Jan 23 19:59:51 2012
From: pav at iki.fi (Pauli Virtanen)
Date: Tue, 24 Jan 2012 00:59:51 +0000 (UTC)
Subject: [SciPy-User] special.kv goes from 0 to nan for large numbers
References: <4F1DE952.7030402@gmail.com>
Message-ID: <loom.20120124T015733-933@post.gmane.org>

Johann Cohen-Tanugi <johann.cohentanugi <at> gmail.com> writes:
[clip]
> In [4]: sp.kv(1./3.,1.08e+09)
> Out[4]: nan
[clip]
> I guess this has to dow with a cephes and big numbers.... Is it fixed on 
> github already, or is it a known bug? Or is it a feature and not a bug? 

No, it's not a known bug, please file a ticket.

The code for KV actually comes from Boost, so it's better quality than Cephes, 
but apparently it wasn't perfect. There's no asymptotic expansion for KV, and it 
seems the continued fraction or something else fails to converge in this limit.

-- 
Pauli Virtanen



From johann.cohentanugi at gmail.com  Tue Jan 24 00:28:24 2012
From: johann.cohentanugi at gmail.com (Johann Cohen-Tanugi)
Date: Tue, 24 Jan 2012 06:28:24 +0100
Subject: [SciPy-User] special.kv goes from 0 to nan for large numbers
In-Reply-To: <loom.20120124T015733-933@post.gmane.org>
References: <4F1DE952.7030402@gmail.com>
	<loom.20120124T015733-933@post.gmane.org>
Message-ID: <4F1E4178.3010201@gmail.com>

done : http://projects.scipy.org/scipy/ticket/1589
thanks,
Johann


On 01/24/2012 01:59 AM, Pauli Virtanen wrote:
> Johann Cohen-Tanugi<johann.cohentanugi<at>  gmail.com>  writes:
> [clip]
>> In [4]: sp.kv(1./3.,1.08e+09)
>> Out[4]: nan
> [clip]
>> I guess this has to dow with a cephes and big numbers.... Is it fixed on
>> github already, or is it a known bug? Or is it a feature and not a bug?
>
> No, it's not a known bug, please file a ticket.
>
> The code for KV actually comes from Boost, so it's better quality than Cephes,
> but apparently it wasn't perfect. There's no asymptotic expansion for KV, and it
> seems the continued fraction or something else fails to converge in this limit.
>


From johann.cohen-tanugi at univ-montp2.fr  Tue Jan 24 00:27:02 2012
From: johann.cohen-tanugi at univ-montp2.fr (Johann Cohen-Tanugi)
Date: Tue, 24 Jan 2012 06:27:02 +0100
Subject: [SciPy-User] special.kv goes from 0 to nan for large numbers
In-Reply-To: <loom.20120124T015733-933@post.gmane.org>
References: <4F1DE952.7030402@gmail.com>
	<loom.20120124T015733-933@post.gmane.org>
Message-ID: <4F1E4126.6030008@univ-montp2.fr>

done : http://projects.scipy.org/scipy/ticket/1589
thanks,
Johann

On 01/24/2012 01:59 AM, Pauli Virtanen wrote:
> Johann Cohen-Tanugi<johann.cohentanugi<at>  gmail.com>  writes:
> [clip]
>> In [4]: sp.kv(1./3.,1.08e+09)
>> Out[4]: nan
> [clip]
>> I guess this has to dow with a cephes and big numbers.... Is it fixed on
>> github already, or is it a known bug? Or is it a feature and not a bug?
>
> No, it's not a known bug, please file a ticket.
>
> The code for KV actually comes from Boost, so it's better quality than Cephes,
> but apparently it wasn't perfect. There's no asymptotic expansion for KV, and it
> seems the continued fraction or something else fails to converge in this limit.
>


From mmueller at python-academy.de  Tue Jan 24 15:50:43 2012
From: mmueller at python-academy.de (=?ISO-8859-15?Q?Mike_M=FCller?=)
Date: Tue, 24 Jan 2012 21:50:43 +0100
Subject: [SciPy-User] Course "Python for Scientists and Engineers" in Chicago
Message-ID: <4F1F19A3.5010802@python-academy.de>

Course "Python for Scientists and Engineers" in Chicago
=======================================================

There will be a comprehensive Python course for scientists and engineers
in Chicago end of February / beginning of March 2012. It consists of a 3-day
intro and a 2-day advanced section. Both sections can be taken separately
or combined.

More details below and here: http://www.dabeaz.com/chicago/science.html

Please let friends or colleagues who might be interested in such a
course know about it.


3-Day Intro Section
-------------------

- Overview of Scientific and Technical Libraries for Python.
- Numerical Calculations with NumPy
- Storage and Processing of Large Amounts of Data
- Graphical Presentation of Scientific Data with matplotlib
- Object Oriented Programming for Scientific and Technical Projects
- Open Time for Problem Solving


2-Day Advanced Section
----------------------

- Extending Python with Other Languages
- Unit Testing
- Version Control with Mercurial


The Details
-----------

The course is hosted by David Beazley (http://www.dabeaz.com).

Date: Feb 27 - Mar 2, 2012
Location: Chicago, IL, USA
Trainer: Mike M?ller
Course Language: English
Link: http://www.dabeaz.com/chicago/science.html


From johnl at cs.wisc.edu  Thu Jan 26 00:46:34 2012
From: johnl at cs.wisc.edu (J. David Lee)
Date: Wed, 25 Jan 2012 23:46:34 -0600
Subject: [SciPy-User] Stack corruption in extension module.
Message-ID: <4F20E8BA.7000007@cs.wisc.edu>

Hi,

Sorry that this is a bit off-topic, but I'm having an interesting 
problem with a C extension module. Here is a simple test module, 
stack_test.c:

#define PY_ARRAY_UNIQUE_SYMBOL __np_inline_stack_test
#include<Python.h>
#include<numpy/arrayobject.h>
#include<math.h>

// Forward declarations of our function.
static PyObject *function(PyObject *self, PyObject *args);


// Boilerplate: function list.
static PyMethodDef methods[] = {
     { "function", function, METH_VARARGS, "Doc string."},
     { NULL, NULL, 0, NULL } /* Sentinel */
};

// Boilerplate: Module initialization.
PyMODINIT_FUNC initstack_test(void) {
         (void) Py_InitModule("stack_test", methods);
         import_array();
}

static void calc_A(npy_int64 i, npy_int64 P, npy_int64 Q,
             npy_float64 *R, npy_float64 *A , npy_float64 b) {
   printf("Start : i: %li P: %f Q: %f R: %f A: %f b: %f\n", i, P, Q, *R, *A, b);
   *R = 6.0;
   *A = 7.0;
   printf("End   : i: %li P: %f Q: %f R: %f A: %f b: %f\n", i, P, Q, *R, *A, b);
}

static PyObject *function(PyObject *self, PyObject *args) {

   long th;
   long return_val = 34;


   if (!PyArg_ParseTuple(args, "l",&th)) {
     return NULL;
   }

   npy_float64 P=0;
   npy_float64 Q=0;
   npy_float64 R=0;
   npy_float64 A=0;
   npy_float64 b=0;
   npy_int64 i = 0;

   P = 1;
   Q = 2;
   R = 3;
   A = 4;
   b = 5;

   printf("Before: i: %li P: %f Q: %f R: %f A: %f b: %f\n", i, P, Q, R, A, b);
   calc_A(i, P, Q,&R,&A, b);
   printf("After : i: %li P: %f Q: %f R: %f A: %f b: %f\n", i, P, Q, R, A, b);

   return PyLong_FromLong(return_val);

}



I compile with:

gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -fPIC -UNDEBUG -I/usr/lib/pymodules/python2.7/numpy/core/include -I/usr/include/python2.7 -c stack_test.c -o stack_test.o
gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-function stack_test.o stack_test.so


Now when I run the function:

stack_test.function(1)
Before: i: 0 P: 1.000000 Q: 2.000000 R: 3.000000 A: 4.000000 b: 5.000000
Start : i: 0 P: 3.000000 Q: 4.000000 R: 5.000000 A: 4.000000 b: 5.000000
End   : i: 0 P: 6.000000 Q: 7.000000 R: 5.000000 A: 4.000000 b: 5.000000
After : i: 0 P: 1.000000 Q: 2.000000 R: 6.000000 A: 7.000000 b: 5.000000


which is clearly wrong.

I'm using python 2.7.2 built with gcc 4.6.2.

If you have any suggestions, I'd love to hear them.

Thanks,

David

PS The numpy stuff is in there because this used to be doing some array 
calculations. I cut it down to a minimum that still had bad behavior.
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From johnl at cs.wisc.edu  Thu Jan 26 00:59:00 2012
From: johnl at cs.wisc.edu (J. David Lee)
Date: Wed, 25 Jan 2012 23:59:00 -0600
Subject: [SciPy-User] Stack corruption in extension module.
In-Reply-To: <4F20E8BA.7000007@cs.wisc.edu>
References: <4F20E8BA.7000007@cs.wisc.edu>
Message-ID: <4F20EBA4.9070601@cs.wisc.edu>

On 01/25/2012 11:46 PM, J. David Lee wrote:
> Hi,
>
> Sorry that this is a bit off-topic, but I'm having an interesting 
> problem with a C extension module. Here is a simple test module, 
> stack_test.c:
>
Sorry, I figured it out. I was passing two of the variables in as the 
wrong type.

Thanks,

David


From cpeters at edisonmission.com  Thu Jan 26 04:00:25 2012
From: cpeters at edisonmission.com (Christopher Peters)
Date: Thu, 26 Jan 2012 04:00:25 -0500
Subject: [SciPy-User] AUTO: Christopher Peters is out of the office
	(returning 01/30/2012)
Message-ID: <OF0EC7C32D.60E30127-ON85257991.00317A22-85257991.00317A22@EdisonMission.com>


I am out of the office until 01/30/2012.

I am out of the office.  Please email urgent requests to Mike McDonald.


Note: This is an automated response to your message  "[SciPy-User] Stack
corruption in extension module." sent on 1/26/2012 12:46:34 AM.

This is the only notification you will receive while this person is away.




From scipy at samueljohn.de  Thu Jan 26 13:41:38 2012
From: scipy at samueljohn.de (Samuel John)
Date: Thu, 26 Jan 2012 19:41:38 +0100
Subject: [SciPy-User] SciPy 0.10: 8 failures on OS X Lion
In-Reply-To: <CABL7CQh0mxTFNEb0Gc7duW=wWY5O-gwsq-RnU9Jx_JX8ZuC4ng@mail.gmail.com>
References: <8AB8D94B-FCA2-425B-B5AE-116C9BA2F71F@samueljohn.de>
	<CABL7CQh0mxTFNEb0Gc7duW=wWY5O-gwsq-RnU9Jx_JX8ZuC4ng@mail.gmail.com>
Message-ID: <331FA959-8A7A-420E-896F-74EAF08E95EE@samueljohn.de>

Update:

Only 7 arpack related fails. So looks pretty good. The tests should then be marked as to be skipped, I guess.

NumPy version 1.6.1
SciPy version 0.10.0
Python version 2.7.2 (default, Jan 13 2012, 15:00:18) [GCC 4.2.1 (Based on Apple Inc. build 5658) (LLVM build 2336.1.00)]
nose version 1.1.2

:-)

Samuel


On 21.01.2012, at 13:53, Ralf Gommers wrote:

> 
> 
> On Fri, Jan 20, 2012 at 9:23 PM, Samuel John <scipy at samueljohn.de> wrote:
> Hi SciPy devs,
> 
> I just want to report the following failures. Does anybody on OSX get the same/similar?
>  
> The Arpack ones are causing problems on several platforms, they should be disabled. It's on my (way too long) TODO list.
>  
> The test_contingency failure I've seen before on OS X, but usually just once. Since I can't reproduce it I suspect it's a nose bug. The frozen_fit one I'm not sure about. Does it fail consistently for you? If so, can you run the test as standalone script and have it still failing?
>  
> Ralf
>  
>  
> Are they "known" ?
> Should I try scipy 0.11 because they are fixed there, perhaps?
> Six out of eight are related to arpack.
> I have installed numpy, scipy with gfortran provided by homebrew and I set the CC, CXX to use the non-llvm compilers of the 4.2 series.
> 
> 
> > Python 2.7.2 (default, Jan 13 2012, 15:00:18)
> > [GCC 4.2.1 (Based on Apple Inc. build 5658) (LLVM build 2336.1.00)] on darwin
> > >>> import scipy
> > >>> scipy.test()
> > Running unit tests for scipy
> > NumPy version 2.0.0.dev-55472ca
> > NumPy is installed in /usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy
> > SciPy version 0.10.0
> > SciPy is installed in /usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy
> > Python version 2.7.2 (default, Jan 13 2012, 15:00:18) [GCC 4.2.1 (Based on Apple Inc. build 5658) (LLVM build 2336.1.00)]
> > nose version 1.1.2
> > .
> > .
> > .
> > ======================================================================
> > FAIL: test_arpack.test_symmetric_modes(True, <std-symmetric>, 'f', 2, 'LM', None, 0.5, <function aslinearoperator at 0x103a58f50>, None, 'normal')
> > ----------------------------------------------------------------------
> > Traceback (most recent call last):
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py", line 197, in runTest
> >     self.test(*self.arg)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py", line 235, in eval_evec
> >     assert_allclose(LHS, RHS, rtol=rtol, atol=atol, err_msg=err)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 1213, in assert_allclose
> >     verbose=verbose, header=header)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 677, in assert_array_compare
> >     raise AssertionError(msg)
> > AssertionError:
> > Not equal to tolerance rtol=0.00178814, atol=0.000357628
> > error for eigsh:standard, typ=f, which=LM, sigma=0.5, mattype=aslinearoperator, OPpart=None, mode=normal
> > (mismatch 100.0%)
> >  x: array([[ 0.23815642,  0.1763755 ],
> >        [-0.10785346, -0.32103487],
> >        [ 0.12468303, -0.11230416],...
> >  y: array([[ 0.23815642,  0.24814051],
> >        [-0.10785347, -0.15634772],
> >        [ 0.12468302,  0.05671416],...
> >
> > ======================================================================
> > FAIL: test_arpack.test_symmetric_modes(True, <std-symmetric>, 'f', 2, 'LM', None, 0.5, <function aslinearoperator at 0x103a58f50>, None, 'cayley')
> > ----------------------------------------------------------------------
> > Traceback (most recent call last):
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py", line 197, in runTest
> >     self.test(*self.arg)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py", line 235, in eval_evec
> >     assert_allclose(LHS, RHS, rtol=rtol, atol=atol, err_msg=err)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 1213, in assert_allclose
> >     verbose=verbose, header=header)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 677, in assert_array_compare
> >     raise AssertionError(msg)
> > AssertionError:
> > Not equal to tolerance rtol=0.00178814, atol=0.000357628
> > error for eigsh:standard, typ=f, which=LM, sigma=0.5, mattype=aslinearoperator, OPpart=None, mode=cayley
> > (mismatch 100.0%)
> >  x: array([[ 0.23815693, -0.33630507],
> >        [-0.10785286,  0.02168   ],
> >        [ 0.12468344, -0.11036437],...
> >  y: array([[ 0.23815643, -0.2405392 ],
> >        [-0.10785349,  0.14390968],
> >        [ 0.12468311, -0.04574991],...
> >
> > ======================================================================
> > FAIL: test_arpack.test_symmetric_modes(True, <std-symmetric>, 'f', 2, 'LA', None, 0.5, <function aslinearoperator at 0x103a58f50>, None, 'normal')
> > ----------------------------------------------------------------------
> > Traceback (most recent call last):
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py", line 197, in runTest
> >     self.test(*self.arg)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py", line 235, in eval_evec
> >     assert_allclose(LHS, RHS, rtol=rtol, atol=atol, err_msg=err)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 1213, in assert_allclose
> >     verbose=verbose, header=header)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 677, in assert_array_compare
> >     raise AssertionError(msg)
> > AssertionError:
> > Not equal to tolerance rtol=0.00178814, atol=0.000357628
> > error for eigsh:standard, typ=f, which=LA, sigma=0.5, mattype=aslinearoperator, OPpart=None, mode=normal
> > (mismatch 100.0%)
> >  x: array([[  28.80129188,   -0.6379945 ],
> >        [  34.79312355,    0.27066791],
> >        [-270.23255444,    0.4851834 ],...
> >  y: array([[  3.93467650e+03,  -6.37994494e-01],
> >        [  3.90913859e+03,   2.70667916e-01],
> >        [ -3.62176382e+04,   4.85183382e-01],...
> >
> > ======================================================================
> > FAIL: test_arpack.test_symmetric_modes(True, <std-symmetric>, 'f', 2, 'SA', None, 0.5, <function aslinearoperator at 0x103a58f50>, None, 'normal')
> > ----------------------------------------------------------------------
> > Traceback (most recent call last):
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py", line 197, in runTest
> >     self.test(*self.arg)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py", line 235, in eval_evec
> >     assert_allclose(LHS, RHS, rtol=rtol, atol=atol, err_msg=err)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 1213, in assert_allclose
> >     verbose=verbose, header=header)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 677, in assert_array_compare
> >     raise AssertionError(msg)
> > AssertionError:
> > Not equal to tolerance rtol=0.00178814, atol=0.000357628
> > error for eigsh:standard, typ=f, which=SA, sigma=0.5, mattype=aslinearoperator, OPpart=None, mode=normal
> > (mismatch 100.0%)
> >  x: array([[ 0.26260981,  0.23815559],
> >        [-0.09760907, -0.10785484],
> >        [ 0.06149647,  0.12468203],...
> >  y: array([[ 0.23744165,  0.2381564 ],
> >        [-0.13633069, -0.10785359],
> >        [ 0.03132561,  0.12468301],...
> >
> > ======================================================================
> > FAIL: test_arpack.test_symmetric_modes(True, <std-symmetric>, 'f', 2, 'SA', None, 0.5, <function aslinearoperator at 0x103a58f50>, None, 'cayley')
> > ----------------------------------------------------------------------
> > Traceback (most recent call last):
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py", line 197, in runTest
> >     self.test(*self.arg)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py", line 235, in eval_evec
> >     assert_allclose(LHS, RHS, rtol=rtol, atol=atol, err_msg=err)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 1213, in assert_allclose
> >     verbose=verbose, header=header)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 677, in assert_array_compare
> >     raise AssertionError(msg)
> > AssertionError:
> > Not equal to tolerance rtol=0.00178814, atol=0.000357628
> > error for eigsh:standard, typ=f, which=SA, sigma=0.5, mattype=aslinearoperator, OPpart=None, mode=cayley
> > (mismatch 100.0%)
> >  x: array([[ 0.29524244, -0.2381569 ],
> >        [-0.08169955,  0.10785299],
> >        [ 0.06645597, -0.12468332],...
> >  y: array([[ 0.24180251, -0.23815646],
> >        [-0.14191195,  0.10785349],
> >        [ 0.03568392, -0.12468307],...
> >
> > ======================================================================
> > FAIL: test_arpack.test_symmetric_modes(True, <gen-symmetric>, 'f', 2, 'SM', None, 0.5, <function aslinearoperator at 0x103a58f50>, None, 'buckling')
> > ----------------------------------------------------------------------
> > Traceback (most recent call last):
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py", line 197, in runTest
> >     self.test(*self.arg)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py", line 235, in eval_evec
> >     assert_allclose(LHS, RHS, rtol=rtol, atol=atol, err_msg=err)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 1213, in assert_allclose
> >     verbose=verbose, header=header)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 677, in assert_array_compare
> >     raise AssertionError(msg)
> > AssertionError:
> > Not equal to tolerance rtol=0.00178814, atol=0.000357628
> > error for eigsh:general, typ=f, which=SM, sigma=0.5, mattype=aslinearoperator, OPpart=None, mode=buckling
> > (mismatch 100.0%)
> >  x: array([[-0.10940548,  0.01676016],
> >        [-0.07154097,  0.4628113 ],
> >        [ 0.06895222,  0.49206394],...
> >  y: array([[-0.10940547,  0.05459438],
> >        [-0.07154103,  0.31407543],
> >        [ 0.06895217,  0.37578294],...
> >
> > ======================================================================
> > FAIL: test_arpack.test_symmetric_modes(True, <gen-symmetric>, 'f', 2, 'SA', None, 0.5, <function aslinearoperator at 0x103a58f50>, None, 'cayley')
> > ----------------------------------------------------------------------
> > Traceback (most recent call last):
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py", line 197, in runTest
> >     self.test(*self.arg)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py", line 235, in eval_evec
> >     assert_allclose(LHS, RHS, rtol=rtol, atol=atol, err_msg=err)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 1213, in assert_allclose
> >     verbose=verbose, header=header)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 677, in assert_array_compare
> >     raise AssertionError(msg)
> > AssertionError:
> > Not equal to tolerance rtol=0.00178814, atol=0.000357628
> > error for eigsh:general, typ=f, which=SA, sigma=0.5, mattype=aslinearoperator, OPpart=None, mode=cayley
> > (mismatch 100.0%)
> >  x: array([[-0.4404992 , -0.01935683],
> >        [-0.25650678, -0.11053132],
> >        [-0.36893024, -0.13223556],...
> >  y: array([[-0.44017013, -0.0193569 ],
> >        [-0.25525379, -0.11053158],
> >        [-0.36818443, -0.13223571],...
> >
> > ======================================================================
> > FAIL: test_contingency.test_expected_freq
> > ----------------------------------------------------------------------
> > Traceback (most recent call last):
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py", line 197, in runTest
> >     self.test(*self.arg)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/stats/tests/test_contingency.py", line 45, in test_expected_freq
> >     assert_array_equal(e, np.ones_like(observed))
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 753, in assert_array_equal
> >     verbose=verbose, header='Arrays are not equal')
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 677, in assert_array_compare
> >     raise AssertionError(msg)
> > AssertionError:
> > Arrays are not equal
> >
> > (mismatch 100.0%)
> >  x: array([[[ 0.,  0.],
> >         [ 0.,  0.]],
> > ...
> >  y: array([[[1, 1],
> >         [1, 1]],
> > ...
> >
> > ======================================================================
> > FAIL: test_distributions.test_frozen_fit_ticket_1536
> > ----------------------------------------------------------------------
> > Traceback (most recent call last):
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/nose/case.py", line 197, in runTest
> >     self.test(*self.arg)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/stats/tests/test_distributions.py", line 747, in test_frozen_fit_ticket_1536
> >     assert_almost_equal(params, true, decimal=2)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 451, in assert_almost_equal
> >     return assert_array_almost_equal(actual, desired, decimal, err_msg)
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 846, in assert_array_almost_equal
> >     header=('Arrays are not almost equal to %d decimals' % decimal))
> >   File "/usr/local/Cellar/python/2.7.2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/testing/utils.py", line 677, in assert_array_compare
> >     raise AssertionError(msg)
> > AssertionError:
> > Arrays are not almost equal to 2 decimals
> >
> > (mismatch 66.6666666667%)
> >  x: array([ 1.416,  0.   ,  0.061])
> >  y: array([ 0.25,  0.  ,  0.5 ])
> >
> > ----------------------------------------------------------------------
> > Ran 5095 tests in 54.587s
> >
> > FAILED (KNOWNFAIL=12, SKIP=36, failures=9)
> > <nose.result.TextTestResult run=5095 errors=0 failures=9>
> >
> 
> 
> 
> 
> And some warning that look strange (at least to me):
> > site-packages/scipy/spatial/__init__.py:26: RuntimeWarning: numpy.ndarray size changed, may indicate binary incompatibility
> > site-packages/scipy/spatial/__init__.py:26: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility
> 
> 
> cheers,
>  Samuel
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user
> 
> _______________________________________________
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> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user



From lafont.fabien at gmail.com  Fri Jan 27 11:49:49 2012
From: lafont.fabien at gmail.com (Fabien Lafont)
Date: Fri, 27 Jan 2012 17:49:49 +0100
Subject: [SciPy-User] [scipy-user] How to remove a value from an np array?
Message-ID: <CAC9H_chGjgm+A5dxpdsn-dH6R_d5ViroC-4t0vAhH2-Px_oByw@mail.gmail.com>

I have that [3,2,4,8,7,8,9] and I want [3,2,8,7,8] how can I do?  I've
tried remove() but it works only on lists not on np.array.


From warren.weckesser at enthought.com  Fri Jan 27 11:52:23 2012
From: warren.weckesser at enthought.com (Warren Weckesser)
Date: Fri, 27 Jan 2012 10:52:23 -0600
Subject: [SciPy-User] [scipy-user] How to remove a value from an np
	array?
In-Reply-To: <CAC9H_chGjgm+A5dxpdsn-dH6R_d5ViroC-4t0vAhH2-Px_oByw@mail.gmail.com>
References: <CAC9H_chGjgm+A5dxpdsn-dH6R_d5ViroC-4t0vAhH2-Px_oByw@mail.gmail.com>
Message-ID: <CAM-+wY_c9HhxfWRH46BkaPJK9jc2t2nTL1+B=wGhQmsAQqfweg@mail.gmail.com>

On Fri, Jan 27, 2012 at 10:49 AM, Fabien Lafont <lafont.fabien at gmail.com>wrote:

> I have that [3,2,4,8,7,8,9] and I want [3,2,8,7,8] how can I do?  I've
> tried remove() but it works only on lists not on np.array.
>


In [21]: a = array([3,2,4,8,7,8,9])

In [22]: b = a[(a != 4) & (a != 9)]

In [23]: b
Out[23]: array([3, 2, 8, 7, 8])


Warren
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From lafont.fabien at gmail.com  Fri Jan 27 11:56:38 2012
From: lafont.fabien at gmail.com (Fabien Lafont)
Date: Fri, 27 Jan 2012 17:56:38 +0100
Subject: [SciPy-User] [scipy-user] How to remove a value from an np
	array?
In-Reply-To: <CAM-+wY_c9HhxfWRH46BkaPJK9jc2t2nTL1+B=wGhQmsAQqfweg@mail.gmail.com>
References: <CAC9H_chGjgm+A5dxpdsn-dH6R_d5ViroC-4t0vAhH2-Px_oByw@mail.gmail.com>
	<CAM-+wY_c9HhxfWRH46BkaPJK9jc2t2nTL1+B=wGhQmsAQqfweg@mail.gmail.com>
Message-ID: <CAC9H_ci6OqeK3bA+UWSDaES4MxOm2FD5vknDejqxDkfSp62nxw@mail.gmail.com>

thanks a lot. Is there a way to do so but acting on elements array? I
explain you why. I have a vector with some 'nan' elements. I want to
remove them and to know the position on the array to remove another
element on another array but at the same 'place(position number)'


2012/1/27 Warren Weckesser <warren.weckesser at enthought.com>:
>
>
> On Fri, Jan 27, 2012 at 10:49 AM, Fabien Lafont <lafont.fabien at gmail.com>
> wrote:
>>
>> I have that [3,2,4,8,7,8,9] and I want [3,2,8,7,8] how can I do? ?I've
>> tried remove() but it works only on lists not on np.array.
>
>
>
> In [21]: a = array([3,2,4,8,7,8,9])
>
> In [22]: b = a[(a != 4) & (a != 9)]
>
> In [23]: b
> Out[23]: array([3, 2, 8, 7, 8])
>
>
> Warren
>
>
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user
>


From warren.weckesser at enthought.com  Fri Jan 27 12:02:20 2012
From: warren.weckesser at enthought.com (Warren Weckesser)
Date: Fri, 27 Jan 2012 11:02:20 -0600
Subject: [SciPy-User] [scipy-user] How to remove a value from an np
	array?
In-Reply-To: <CAC9H_ci6OqeK3bA+UWSDaES4MxOm2FD5vknDejqxDkfSp62nxw@mail.gmail.com>
References: <CAC9H_chGjgm+A5dxpdsn-dH6R_d5ViroC-4t0vAhH2-Px_oByw@mail.gmail.com>
	<CAM-+wY_c9HhxfWRH46BkaPJK9jc2t2nTL1+B=wGhQmsAQqfweg@mail.gmail.com>
	<CAC9H_ci6OqeK3bA+UWSDaES4MxOm2FD5vknDejqxDkfSp62nxw@mail.gmail.com>
Message-ID: <CAM-+wY_5Jt+VJDaRXgCPB68yVe3YqwPn_xartvHQanMwQcxXKg@mail.gmail.com>

On Fri, Jan 27, 2012 at 10:56 AM, Fabien Lafont <lafont.fabien at gmail.com>wrote:

> thanks a lot. Is there a way to do so but acting on elements array? I
> explain you why. I have a vector with some 'nan' elements. I want to
> remove them and to know the position on the array to remove another
> element on another array but at the same 'place(position number)'
>
>

Perhaps something like this:

In [29]: a
Out[29]: array([  1.,   2.,  nan,   4.,  nan])

In [30]: b
Out[30]: array([10, 20, 30, 40, 50])

In [31]: clean_a = a[isfinite(a)]

In [32]: clean_b = b[isfinite(a)]

In [33]: clean_a
Out[33]: array([ 1.,  2.,  4.])

In [34]: clean_b
Out[34]: array([10, 20, 40])


If you really need the indices of the values that are not nan, you can use
the 'where' function:

In [35]: where(isfinite(a))
Out[35]: (array([0, 1, 3]),)


Warren




>
> 2012/1/27 Warren Weckesser <warren.weckesser at enthought.com>:
> >
> >
> > On Fri, Jan 27, 2012 at 10:49 AM, Fabien Lafont <lafont.fabien at gmail.com
> >
> > wrote:
> >>
> >> I have that [3,2,4,8,7,8,9] and I want [3,2,8,7,8] how can I do?  I've
> >> tried remove() but it works only on lists not on np.array.
> >
> >
> >
> > In [21]: a = array([3,2,4,8,7,8,9])
> >
> > In [22]: b = a[(a != 4) & (a != 9)]
> >
> > In [23]: b
> > Out[23]: array([3, 2, 8, 7, 8])
> >
> >
> > Warren
> >
> >
> > _______________________________________________
> > SciPy-User mailing list
> > SciPy-User at scipy.org
> > http://mail.scipy.org/mailman/listinfo/scipy-user
> >
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user
>
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From russel at appliedminds.com  Fri Jan 27 12:12:30 2012
From: russel at appliedminds.com (russel)
Date: Fri, 27 Jan 2012 09:12:30 -0800
Subject: [SciPy-User] [scipy-user] How to remove a value from an np
	array?
In-Reply-To: <CAC9H_ci6OqeK3bA+UWSDaES4MxOm2FD5vknDejqxDkfSp62nxw@mail.gmail.com>
References: <CAC9H_chGjgm+A5dxpdsn-dH6R_d5ViroC-4t0vAhH2-Px_oByw@mail.gmail.com>
	<CAM-+wY_c9HhxfWRH46BkaPJK9jc2t2nTL1+B=wGhQmsAQqfweg@mail.gmail.com>
	<CAC9H_ci6OqeK3bA+UWSDaES4MxOm2FD5vknDejqxDkfSp62nxw@mail.gmail.com>
Message-ID: <4F22DAFE.1050401@appliedminds.com>

In [12]: a=np.arange(10)

In [13]: b=np.ones((10,))

In [14]: b[[3,4,7,8]] = np.nan

In [15]: a
Out[15]: array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])

In [16]: b
Out[16]: array([  1.,   1.,   1.,  nan,  nan,   1.,   1.,  nan,  nan,   1.])

In [17]: nans = np.isnan(b)

In [18]: a[~nans]
Out[18]: array([0, 1, 2, 5, 6, 9])

In [19]: b[~nans]
Out[19]: array([ 1.,  1.,  1.,  1.,  1.,  1.])



On 01/27/2012 08:56 AM, Fabien Lafont wrote:
> thanks a lot. Is there a way to do so but acting on elements array? I
> explain you why. I have a vector with some 'nan' elements. I want to
> remove them and to know the position on the array to remove another
> element on another array but at the same 'place(position number)'
>
>
> 2012/1/27 Warren Weckesser<warren.weckesser at enthought.com>:
>>
>>
>> On Fri, Jan 27, 2012 at 10:49 AM, Fabien Lafont<lafont.fabien at gmail.com>
>> wrote:
>>>
>>> I have that [3,2,4,8,7,8,9] and I want [3,2,8,7,8] how can I do?  I've
>>> tried remove() but it works only on lists not on np.array.
>>
>>
>>
>> In [21]: a = array([3,2,4,8,7,8,9])
>>
>> In [22]: b = a[(a != 4)&  (a != 9)]
>>
>> In [23]: b
>> Out[23]: array([3, 2, 8, 7, 8])
>>
>>
>> Warren
>>
>>
>> _______________________________________________
>> SciPy-User mailing list
>> SciPy-User at scipy.org
>> http://mail.scipy.org/mailman/listinfo/scipy-user
>>
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user


From lafont.fabien at gmail.com  Fri Jan 27 12:48:45 2012
From: lafont.fabien at gmail.com (Fabien Lafont)
Date: Fri, 27 Jan 2012 18:48:45 +0100
Subject: [SciPy-User] [scipy-user] How to remove a value from an np
	array?
In-Reply-To: <4F22DAFE.1050401@appliedminds.com>
References: <CAC9H_chGjgm+A5dxpdsn-dH6R_d5ViroC-4t0vAhH2-Px_oByw@mail.gmail.com>
	<CAM-+wY_c9HhxfWRH46BkaPJK9jc2t2nTL1+B=wGhQmsAQqfweg@mail.gmail.com>
	<CAC9H_ci6OqeK3bA+UWSDaES4MxOm2FD5vknDejqxDkfSp62nxw@mail.gmail.com>
	<4F22DAFE.1050401@appliedminds.com>
Message-ID: <CAC9H_cjLsdtbzDTp5GXDKBxBNqPUKmtBGjuLwL4Hf33YK4CUCA@mail.gmail.com>

And how can I remove a specific element designated by its position
numer? like remove(a[8]) for exemple.

thx

Fabien

2012/1/27 russel <russel at appliedminds.com>:
> In [12]: a=np.arange(10)
>
> In [13]: b=np.ones((10,))
>
> In [14]: b[[3,4,7,8]] = np.nan
>
> In [15]: a
> Out[15]: array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
>
> In [16]: b
> Out[16]: array([ ?1., ? 1., ? 1., ?nan, ?nan, ? 1., ? 1., ?nan, ?nan, ? 1.])
>
> In [17]: nans = np.isnan(b)
>
> In [18]: a[~nans]
> Out[18]: array([0, 1, 2, 5, 6, 9])
>
> In [19]: b[~nans]
> Out[19]: array([ 1., ?1., ?1., ?1., ?1., ?1.])
>
>
>
> On 01/27/2012 08:56 AM, Fabien Lafont wrote:
>> thanks a lot. Is there a way to do so but acting on elements array? I
>> explain you why. I have a vector with some 'nan' elements. I want to
>> remove them and to know the position on the array to remove another
>> element on another array but at the same 'place(position number)'
>>
>>
>> 2012/1/27 Warren Weckesser<warren.weckesser at enthought.com>:
>>>
>>>
>>> On Fri, Jan 27, 2012 at 10:49 AM, Fabien Lafont<lafont.fabien at gmail.com>
>>> wrote:
>>>>
>>>> I have that [3,2,4,8,7,8,9] and I want [3,2,8,7,8] how can I do? ?I've
>>>> tried remove() but it works only on lists not on np.array.
>>>
>>>
>>>
>>> In [21]: a = array([3,2,4,8,7,8,9])
>>>
>>> In [22]: b = a[(a != 4)& ?(a != 9)]
>>>
>>> In [23]: b
>>> Out[23]: array([3, 2, 8, 7, 8])
>>>
>>>
>>> Warren
>>>
>>>
>>> _______________________________________________
>>> SciPy-User mailing list
>>> SciPy-User at scipy.org
>>> http://mail.scipy.org/mailman/listinfo/scipy-user
>>>
>> _______________________________________________
>> SciPy-User mailing list
>> SciPy-User at scipy.org
>> http://mail.scipy.org/mailman/listinfo/scipy-user
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user


From wardefar at iro.umontreal.ca  Fri Jan 27 13:20:48 2012
From: wardefar at iro.umontreal.ca (David Warde-Farley)
Date: Fri, 27 Jan 2012 13:20:48 -0500
Subject: [SciPy-User] [scipy-user] How to remove a value from an np
 array?
In-Reply-To: <CAC9H_cjLsdtbzDTp5GXDKBxBNqPUKmtBGjuLwL4Hf33YK4CUCA@mail.gmail.com>
References: <CAC9H_chGjgm+A5dxpdsn-dH6R_d5ViroC-4t0vAhH2-Px_oByw@mail.gmail.com>
	<CAM-+wY_c9HhxfWRH46BkaPJK9jc2t2nTL1+B=wGhQmsAQqfweg@mail.gmail.com>
	<CAC9H_ci6OqeK3bA+UWSDaES4MxOm2FD5vknDejqxDkfSp62nxw@mail.gmail.com>
	<4F22DAFE.1050401@appliedminds.com>
	<CAC9H_cjLsdtbzDTp5GXDKBxBNqPUKmtBGjuLwL4Hf33YK4CUCA@mail.gmail.com>
Message-ID: <20120127182047.GA10301@ravage>

On Fri, Jan 27, 2012 at 06:48:45PM +0100, Fabien Lafont wrote:
> And how can I remove a specific element designated by its position
> numer? like remove(a[8]) for exemple.

This is generally not something you want to be doing with NumPy arrays. NumPy
arrays represent fixed blocks of memory, removing an element means
reallocating the array and copying values before and after position 8 is the
only way.

If a is one-dimensional, then np.concatenate(a[:8], a[9:]) will do the job,
but if you are going to be frequently performing this kind of operation you
will get better performance out of a plain Python list.

David


From lafont.fabien at gmail.com  Fri Jan 27 13:28:38 2012
From: lafont.fabien at gmail.com (Fabien Lafont)
Date: Fri, 27 Jan 2012 19:28:38 +0100
Subject: [SciPy-User] [scipy-user] How to remove a value from an np
	array?
In-Reply-To: <20120127182047.GA10301@ravage>
References: <CAC9H_chGjgm+A5dxpdsn-dH6R_d5ViroC-4t0vAhH2-Px_oByw@mail.gmail.com>
	<CAM-+wY_c9HhxfWRH46BkaPJK9jc2t2nTL1+B=wGhQmsAQqfweg@mail.gmail.com>
	<CAC9H_ci6OqeK3bA+UWSDaES4MxOm2FD5vknDejqxDkfSp62nxw@mail.gmail.com>
	<4F22DAFE.1050401@appliedminds.com>
	<CAC9H_cjLsdtbzDTp5GXDKBxBNqPUKmtBGjuLwL4Hf33YK4CUCA@mail.gmail.com>
	<20120127182047.GA10301@ravage>
Message-ID: <CAC9H_ciP3GMdB-jOAne3LBtukK-QQnwBAq9AMZjQ5t1Xy2gCWw@mail.gmail.com>

Thx,

I have another. First I expose my problem I have datas like that. Is
it possible to create an array with two columns and then do something
to erase the entire line(both time and points) where nan appears?


X(Time)     Points
1                  5
2                 nan
3                  3
4                  4
5                 nan
...


2012/1/27 David Warde-Farley <wardefar at iro.umontreal.ca>:
> On Fri, Jan 27, 2012 at 06:48:45PM +0100, Fabien Lafont wrote:
>> And how can I remove a specific element designated by its position
>> numer? like remove(a[8]) for exemple.
>
> This is generally not something you want to be doing with NumPy arrays. NumPy
> arrays represent fixed blocks of memory, removing an element means
> reallocating the array and copying values before and after position 8 is the
> only way.
>
> If a is one-dimensional, then np.concatenate(a[:8], a[9:]) will do the job,
> but if you are going to be frequently performing this kind of operation you
> will get better performance out of a plain Python list.
>
> David
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user


From chria at maths.lth.se  Mon Jan 30 06:39:15 2012
From: chria at maths.lth.se (Christian Andersson)
Date: Mon, 30 Jan 2012 12:39:15 +0100
Subject: [SciPy-User] Assimulo
Message-ID: <012401ccdf43$cc2dac90$648905b0$@maths.lth.se>

Hello All,

 

I would like to make you aware of that we have released a new version of

Assimulo, which is a Python package for solving both ordinary differential 

equations and differential algebraic equations. Current interfaces include

access to the Sundials solvers CVode and IDA with both sensitivity 

capabilities and event handling. Additionally, access to Radau5, 

Dopri5 and Rodas [by Hairer] are available, where Radau5 can also be used to
solve 

differential algebraic equations. There are also plans to implement event

handling for solvers that are missing the feature and include interfaces 

for more solvers.

 

Assimulo is used as a teaching tool at Lund University and included as

the default simulation environment in the platform JModelica.org where it
has

been used to solve industrial related problems with hundreds of states.
Also, 

it can be used together with PyFMI, http://www.pyfmi.org, to simulate 

"Functional Mock-up Units".

 

Assimulo can be found for download on http://www.assimulo.org and the 

documentation can be found on http://www.jmodelica.org/assimulo.

 

Any suggestions and comments are very welcome!

 

Best

/Christian

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From lafont.fabien at gmail.com  Mon Jan 30 09:22:01 2012
From: lafont.fabien at gmail.com (Fabien Lafont)
Date: Mon, 30 Jan 2012 15:22:01 +0100
Subject: [SciPy-User] [scipy-user] How to remove a value from an np
	array?
In-Reply-To: <CAC9H_ciP3GMdB-jOAne3LBtukK-QQnwBAq9AMZjQ5t1Xy2gCWw@mail.gmail.com>
References: <CAC9H_chGjgm+A5dxpdsn-dH6R_d5ViroC-4t0vAhH2-Px_oByw@mail.gmail.com>
	<CAM-+wY_c9HhxfWRH46BkaPJK9jc2t2nTL1+B=wGhQmsAQqfweg@mail.gmail.com>
	<CAC9H_ci6OqeK3bA+UWSDaES4MxOm2FD5vknDejqxDkfSp62nxw@mail.gmail.com>
	<4F22DAFE.1050401@appliedminds.com>
	<CAC9H_cjLsdtbzDTp5GXDKBxBNqPUKmtBGjuLwL4Hf33YK4CUCA@mail.gmail.com>
	<20120127182047.GA10301@ravage>
	<CAC9H_ciP3GMdB-jOAne3LBtukK-QQnwBAq9AMZjQ5t1Xy2gCWw@mail.gmail.com>
Message-ID: <CAC9H_cgWjbdrRxF6ripjBzOpHJPjoJv8r+WXpw7bTyOmaVztyQ@mail.gmail.com>

Sorry to be boring but do you have any idea?

I want to have an array with 2 columns and erase the entire line when
it find a "nan" in the second column?

Thx again,

Fabien

2012/1/27 Fabien Lafont <lafont.fabien at gmail.com>:
> Thx,
>
> I have another. First I expose my problem I have datas like that. Is
> it possible to create an array with two columns and then do something
> to erase the entire line(both time and points) where nan appears?
>
>
> X(Time) ? ? Points
> 1 ? ? ? ? ? ? ? ? ?5
> 2 ? ? ? ? ? ? ? ? nan
> 3 ? ? ? ? ? ? ? ? ?3
> 4 ? ? ? ? ? ? ? ? ?4
> 5 ? ? ? ? ? ? ? ? nan
> ...
>
>
> 2012/1/27 David Warde-Farley <wardefar at iro.umontreal.ca>:
>> On Fri, Jan 27, 2012 at 06:48:45PM +0100, Fabien Lafont wrote:
>>> And how can I remove a specific element designated by its position
>>> numer? like remove(a[8]) for exemple.
>>
>> This is generally not something you want to be doing with NumPy arrays. NumPy
>> arrays represent fixed blocks of memory, removing an element means
>> reallocating the array and copying values before and after position 8 is the
>> only way.
>>
>> If a is one-dimensional, then np.concatenate(a[:8], a[9:]) will do the job,
>> but if you are going to be frequently performing this kind of operation you
>> will get better performance out of a plain Python list.
>>
>> David
>> _______________________________________________
>> SciPy-User mailing list
>> SciPy-User at scipy.org
>> http://mail.scipy.org/mailman/listinfo/scipy-user


From robert.kern at gmail.com  Mon Jan 30 09:35:45 2012
From: robert.kern at gmail.com (Robert Kern)
Date: Mon, 30 Jan 2012 14:35:45 +0000
Subject: [SciPy-User] [scipy-user] How to remove a value from an np
	array?
In-Reply-To: <CAC9H_cgWjbdrRxF6ripjBzOpHJPjoJv8r+WXpw7bTyOmaVztyQ@mail.gmail.com>
References: <CAC9H_chGjgm+A5dxpdsn-dH6R_d5ViroC-4t0vAhH2-Px_oByw@mail.gmail.com>
	<CAM-+wY_c9HhxfWRH46BkaPJK9jc2t2nTL1+B=wGhQmsAQqfweg@mail.gmail.com>
	<CAC9H_ci6OqeK3bA+UWSDaES4MxOm2FD5vknDejqxDkfSp62nxw@mail.gmail.com>
	<4F22DAFE.1050401@appliedminds.com>
	<CAC9H_cjLsdtbzDTp5GXDKBxBNqPUKmtBGjuLwL4Hf33YK4CUCA@mail.gmail.com>
	<20120127182047.GA10301@ravage>
	<CAC9H_ciP3GMdB-jOAne3LBtukK-QQnwBAq9AMZjQ5t1Xy2gCWw@mail.gmail.com>
	<CAC9H_cgWjbdrRxF6ripjBzOpHJPjoJv8r+WXpw7bTyOmaVztyQ@mail.gmail.com>
Message-ID: <CAF6FJitgNaQN4_S9+3JZa6VCQk3bA8QzyFAZY3JbAHOJK7DE_A@mail.gmail.com>

On Mon, Jan 30, 2012 at 14:22, Fabien Lafont <lafont.fabien at gmail.com> wrote:
> Sorry to be boring but do you have any idea?
>
> I want to have an array with 2 columns and erase the entire line when
> it find a "nan" in the second column?

y = x[~np.isnan(x[:,1])]

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad attempt to interpret it as
though it had an underlying truth."
? -- Umberto Eco


From e.antero.tammi at gmail.com  Mon Jan 30 09:37:43 2012
From: e.antero.tammi at gmail.com (eat)
Date: Mon, 30 Jan 2012 16:37:43 +0200
Subject: [SciPy-User] [scipy-user] How to remove a value from an np
	array?
In-Reply-To: <CAC9H_cgWjbdrRxF6ripjBzOpHJPjoJv8r+WXpw7bTyOmaVztyQ@mail.gmail.com>
References: <CAC9H_chGjgm+A5dxpdsn-dH6R_d5ViroC-4t0vAhH2-Px_oByw@mail.gmail.com>
	<CAM-+wY_c9HhxfWRH46BkaPJK9jc2t2nTL1+B=wGhQmsAQqfweg@mail.gmail.com>
	<CAC9H_ci6OqeK3bA+UWSDaES4MxOm2FD5vknDejqxDkfSp62nxw@mail.gmail.com>
	<4F22DAFE.1050401@appliedminds.com>
	<CAC9H_cjLsdtbzDTp5GXDKBxBNqPUKmtBGjuLwL4Hf33YK4CUCA@mail.gmail.com>
	<20120127182047.GA10301@ravage>
	<CAC9H_ciP3GMdB-jOAne3LBtukK-QQnwBAq9AMZjQ5t1Xy2gCWw@mail.gmail.com>
	<CAC9H_cgWjbdrRxF6ripjBzOpHJPjoJv8r+WXpw7bTyOmaVztyQ@mail.gmail.com>
Message-ID: <CAKa=AYQ1orHfvO6=jBHLL4o63cqHDKUNVj20imk2Oj4xwokuEQ@mail.gmail.com>

Hi,

On Mon, Jan 30, 2012 at 4:22 PM, Fabien Lafont <lafont.fabien at gmail.com>wrote:

> Sorry to be boring but do you have any idea?
>
> I want to have an array with 2 columns and erase the entire line when
> it find a "nan" in the second column?
>
> Thx again,
>
> Fabien
>
> 2012/1/27 Fabien Lafont <lafont.fabien at gmail.com>:
> > Thx,
> >
> > I have another. First I expose my problem I have datas like that. Is
> > it possible to create an array with two columns and then do something
> > to erase the entire line(both time and points) where nan appears?
> >
> >
> > X(Time)     Points
> > 1                  5
> > 2                 nan
> > 3                  3
> > 4                  4
> > 5                 nan
> > ...
> >
>
I think you have got already many answers to tackle this, but perhaps an
example demonstrates the point:

In []: data_old
Out[]:
array([[  1.,   5.],
       [  2.,  nan],
       [  3.,   3.],
       [  4.,   4.],
       [  5.,  nan]])

In []: data_new= data_old[~isnan(data_old[:, 1])]

In []: data_new
Out[]:
array([[ 1.,  5.],
       [ 3.,  3.],
       [ 4.,  4.]])


My 2 cents,
-eat

> >
> > 2012/1/27 David Warde-Farley <wardefar at iro.umontreal.ca>:
> >> On Fri, Jan 27, 2012 at 06:48:45PM +0100, Fabien Lafont wrote:
> >>> And how can I remove a specific element designated by its position
> >>> numer? like remove(a[8]) for exemple.
> >>
> >> This is generally not something you want to be doing with NumPy arrays.
> NumPy
> >> arrays represent fixed blocks of memory, removing an element means
> >> reallocating the array and copying values before and after position 8
> is the
> >> only way.
> >>
> >> If a is one-dimensional, then np.concatenate(a[:8], a[9:]) will do the
> job,
> >> but if you are going to be frequently performing this kind of operation
> you
> >> will get better performance out of a plain Python list.
> >>
> >> David
> >> _______________________________________________
> >> SciPy-User mailing list
> >> SciPy-User at scipy.org
> >> http://mail.scipy.org/mailman/listinfo/scipy-user
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user
>
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From lafont.fabien at gmail.com  Mon Jan 30 10:04:11 2012
From: lafont.fabien at gmail.com (Fabien Lafont)
Date: Mon, 30 Jan 2012 16:04:11 +0100
Subject: [SciPy-User] [scipy_user] How to keep only the x first terms of an
	1D array?
Message-ID: <CAC9H_cjB6DhN+D1383WrWp68Sy4Eq6B+1GxYDxcD5V1YpYgbKA@mail.gmail.com>

Hello,

Do somebody knows how to keep only the x first terms of an array?

Fabien


From zachary.pincus at yale.edu  Mon Jan 30 10:11:04 2012
From: zachary.pincus at yale.edu (Zachary Pincus)
Date: Mon, 30 Jan 2012 10:11:04 -0500
Subject: [SciPy-User] [scipy_user] How to keep only the x first terms of
	an 1D array?
In-Reply-To: <CAC9H_cjB6DhN+D1383WrWp68Sy4Eq6B+1GxYDxcD5V1YpYgbKA@mail.gmail.com>
References: <CAC9H_cjB6DhN+D1383WrWp68Sy4Eq6B+1GxYDxcD5V1YpYgbKA@mail.gmail.com>
Message-ID: <B199EA1D-1381-41AA-96ED-D98673461512@yale.edu>

Same as a python list: arr[:x]

Or along other axes, arr[:,:x], etc.

Zach


On Jan 30, 2012, at 10:04 AM, Fabien Lafont wrote:

> Hello,
> 
> Do somebody knows how to keep only the x first terms of an array?
> 
> Fabien
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user



From opossumnano at gmail.com  Tue Jan 31 07:42:37 2012
From: opossumnano at gmail.com (Tiziano Zito)
Date: Tue, 31 Jan 2012 13:42:37 +0100
Subject: [SciPy-User] [ANN] Summer School "Advanced Scientific Programming
 in Python" in Kiel, Germany
Message-ID: <20120131124237.GE12374@multivac.zonafranca>

Advanced Scientific Programming in Python
=========================================
a Summer School by the G-Node and the Institute of Experimental and
Applied Physics, Christian-Albrechts-Universit?t zu Kiel

Scientists spend more and more time writing, maintaining, and
debugging software. While techniques for doing this efficiently have
evolved, only few scientists actually use them. As a result, instead
of doing their research, they spend far too much time writing
deficient code and reinventing the wheel. In this course we will
present a selection of advanced programming techniques,
incorporating theoretical lectures and practical exercises tailored
to the needs of a programming scientist. New skills will be tested
in a real programming project: we will team up to develop an
entertaining scientific computer game.

We use the Python programming language for the entire course. Python
works as a simple programming language for beginners, but more
importantly, it also works great in scientific simulations and data
analysis. We show how clean language design, ease of extensibility,
and the great wealth of open source libraries for scientific
computing and data visualization are driving Python to become a
standard tool for the programming scientist.

This school is targeted at Master or PhD students and Post-docs from
all areas of science. Competence in Python or in another language
such as Java, C/C++, MATLAB, or Mathematica is absolutely required.
Basic knowledge of Python is assumed. Participants without any prior
experience with Python should work through the proposed introductory
materials before the course. 

Date and Location
=================
September 2?7, 2012. Kiel, Germany.

Preliminary Program
===================
Day 0 (Sun Sept 2) ? Best Programming Practices
  - Best Practices, Development Methodologies and the Zen of Python
  - Version control with git
  - Object-oriented programming & design patterns
Day 1 (Mon Sept 3) ? Software Carpentry
  - Test-driven development, unit testing & quality assurance
  - Debugging, profiling and benchmarking techniques
  - Best practices in data visualization
  - Programming in teams
Day 2 (Tue Sept 4) ? Scientific Tools for Python
  - Advanced NumPy
  - The Quest for Speed (intro): Interfacing to C with Cython
  - Advanced Python I: idioms, useful built-in data structures, 
    generators
Day 3 (Wed Sept 5) ? The Quest for Speed
  - Writing parallel applications in Python
  - Programming project
Day 4 (Thu Sept 6) ? Efficient Memory Management
  - When parallelization does not help:
    the starving CPUs problem
  - Advanced Python II: decorators and context managers
  - Programming project
Day 5 (Fri Sept 7) ? Practical Software Development
  - Programming project
  - The Pelita Tournament

Every evening we will have the tutors' consultation hour: Tutors
will answer your questions and give suggestions for your own
projects.

Applications
============
You can apply on-line at http://python.g-node.org

Applications must be submitted before 23:59 UTC, May 1, 2012.
Notifications of acceptance will be sent by June 1, 2012.

No fee is charged but participants should take care of travel,
living, and accommodation expenses.  Candidates will be selected on
the basis of their profile. Places are limited: acceptance rate last
time was around 20%.  Prerequisites: You are supposed to know the
basics of Python to participate in the lectures. You are encouraged
to go through the introductory material available on the website.

Faculty
=======
  - Francesc Alted, Continuum Analytics Inc., USA
  - Pietro Berkes, Enthought Inc., UK
  - Valentin Haenel,  Blue Brain Project, ?cole Polytechnique
    F?d?rale de Lausanne, Switzerland
  - Zbigniew J?drzejewski-Szmek, Faculty of Physics, University of
    Warsaw, Poland
  - Eilif Muller, Blue Brain Project, ?cole Polytechnique F?d?rale
    de Lausanne, Switzerland
  - Emanuele Olivetti, NeuroInformatics Laboratory, Fondazione Bruno
    Kessler and University of Trento, Italy
  - Rike-Benjamin Schuppner,  Technologit GbR, Germany
  - Bartosz Tele?czuk, Unit? de Neurosciences Information et
    Complexit?, Centre National de la Recherche Scientifique, France
  - St?fan van der Walt, Helen Wills Neuroscience Institute,
    University of California Berkeley, USA
  - Bastian Venthur, Berlin Institute of Technology and Bernstein
    Focus Neurotechnology, Germany
  - Niko Wilbert, TNG Technology Consulting GmbH, Germany
  - Tiziano Zito, Institute for Theoretical Biology,
    Humboldt-Universit?t zu Berlin, Germany

Organized by Christian T. Steigies and Christian Drews of the
Institute of Experimental and Applied Physics,
Christian-Albrechts-Universit?t zu Kiel , and by Zbigniew
J?drzejewski-Szmek and Tiziano Zito for the German Neuroinformatics
Node of the INCF. 

Website:  http://python.g-node.org
Contact:  python-info at g-node.org



From gustavo.goretkin at gmail.com  Tue Jan 31 03:36:06 2012
From: gustavo.goretkin at gmail.com (Gustavo Goretkin)
Date: Tue, 31 Jan 2012 03:36:06 -0500
Subject: [SciPy-User] masked recarray,
	recarray with one field of type "ndarray"
Message-ID: <CAD+Uu3OnLdmwe9pFMOotrkGa4dmf-8zACfzdB9VOmc70=xRMmA@mail.gmail.com>

Does a recarray support masking?

Can I have a recarray where one of the fields is an M-by-N ndarray
(not recarray) of some dtype?
ex: a = np.recarray(shape=(10),formats=['i4','f8','3-by-3 ndarray of
dtype=float64'])


From warren.weckesser at enthought.com  Tue Jan 31 09:33:48 2012
From: warren.weckesser at enthought.com (Warren Weckesser)
Date: Tue, 31 Jan 2012 08:33:48 -0600
Subject: [SciPy-User] masked recarray,
	recarray with one field of type "ndarray"
In-Reply-To: <CAD+Uu3OnLdmwe9pFMOotrkGa4dmf-8zACfzdB9VOmc70=xRMmA@mail.gmail.com>
References: <CAD+Uu3OnLdmwe9pFMOotrkGa4dmf-8zACfzdB9VOmc70=xRMmA@mail.gmail.com>
Message-ID: <CAM-+wY_Eh4X4dgF8EVo5cQsDzVpPoFTDf_6nApZS3=vTFS3p5g@mail.gmail.com>

On Tue, Jan 31, 2012 at 2:36 AM, Gustavo Goretkin <
gustavo.goretkin at gmail.com> wrote:

> Does a recarray support masking?
>
> Can I have a recarray where one of the fields is an M-by-N ndarray
> (not recarray) of some dtype?
> ex: a = np.recarray(shape=(10),formats=['i4','f8','3-by-3 ndarray of
> dtype=float64'])
>


Here's how it can be done with the dtype argument (in this case, the
"sub-arrays" are 3x5 float32):

In [21]: dt = np.dtype([('id', int32), ('values', float32, (3,5))])

In [22]: a = np.recarray(shape=(3,), dtype=dt)

In [23]: a.id
Out[23]: array([      7, 2345536, 8585218])

In [24]: a[0].id
Out[24]: 7

In [25]: a[0].values
Out[25]:
array([[  9.80908925e-45,   2.15997513e-37,   3.16079124e-39,
          1.18408375e-38,   2.81552923e-38],
       [  2.13004362e-37,  -7.69011974e-02,   9.80908925e-45,
          9.80908925e-45,   3.62636667e-21],
       [  5.67059093e-24,   5.67095065e-24,   5.64768872e-24,
          7.86448908e+11,   0.00000000e+00]], dtype=float32)

In [26]: a[0].values.shape
Out[26]: (3, 5)


Warren
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From ckkart at hoc.net  Tue Jan 31 11:27:25 2012
From: ckkart at hoc.net (Christian K.)
Date: Tue, 31 Jan 2012 16:27:25 +0000 (UTC)
Subject: [SciPy-User] distribution confidence interval for any percentile
Message-ID: <loom.20120131T170812-247@post.gmane.org>

Hi,

dist.lognorm.interval provides the confidence interval for the median of a 
lognorm distribution. How can I get the confidence interval for any 
percentile, not only the median?

Thanks in advance, Christian



From sturla at molden.no  Tue Jan 31 11:54:04 2012
From: sturla at molden.no (Sturla Molden)
Date: Tue, 31 Jan 2012 17:54:04 +0100
Subject: [SciPy-User] [scipy-user] How to remove a value from an np
	array?
In-Reply-To: <20120127182047.GA10301@ravage>
References: <CAC9H_chGjgm+A5dxpdsn-dH6R_d5ViroC-4t0vAhH2-Px_oByw@mail.gmail.com>	<CAM-+wY_c9HhxfWRH46BkaPJK9jc2t2nTL1+B=wGhQmsAQqfweg@mail.gmail.com>	<CAC9H_ci6OqeK3bA+UWSDaES4MxOm2FD5vknDejqxDkfSp62nxw@mail.gmail.com>	<4F22DAFE.1050401@appliedminds.com>	<CAC9H_cjLsdtbzDTp5GXDKBxBNqPUKmtBGjuLwL4Hf33YK4CUCA@mail.gmail.com>
	<20120127182047.GA10301@ravage>
Message-ID: <4F281CAC.5010405@molden.no>

On 27.01.2012 19:20, David Warde-Farley wrote:

> This is generally not something you want to be doing with NumPy arrays. NumPy
> arrays represent fixed blocks of memory, removing an element means
> reallocating the array and copying values before and after position 8 is the
> only way.
>
> If a is one-dimensional, then np.concatenate(a[:8], a[9:]) will do the job,
> but if you are going to be frequently performing this kind of operation you
> will get better performance out of a plain Python list.

Python lists are also implemented as arrays. Removing an element will be 
O(N) in both cases, except for the tail of a Python list where removal 
is O(1).

Also a linked list will not help here. Remving an element would be O(1), 
but looking it up would be O(N). That is why Python's collections.deque 
will not help, even though it is a linked list of short arrays.

An alternative to removing elements is using NumPy's masked array. 
Setting one up would be O(n), but once it is allocated, "removing" 
elements by masking them out is O(1). It is the fastest data structure 
if you need to remove (or "mask out") arbitrary elements from an array.


Sturla


From alec.kalinin at gmail.com  Tue Jan 31 15:34:28 2012
From: alec.kalinin at gmail.com (Alexander Kalinin)
Date: Tue, 31 Jan 2012 23:34:28 +0300
Subject: [SciPy-User] Accumulation sum using indirect indexes
Message-ID: <CACL-BpEbRSE=_TShy7udPH3s3N3K7Y_h_qb8D9RibOaTSNHtZQ@mail.gmail.com>

Hello!

I use SciPy in computer graphics applications. My task is to calculate
vertex normals by averaging faces normals. In other words I want to
accumulate vectors with the same ids. For example,

ids = numpy.array([0, 1, 1, 2])
n = numpy.array([ [0.1, 0.1, 0.1], [0.1, 0.1, 0.1], [0.1, 0.1, 0.1], [0.1,
0.1 0.1] ])

I need result:
nv = ([ [0.1, 0.1, 0.1], [0.2, 0.2, 0.2], [0.1, 0.1, 0.1]])

The most simple code:
nv[ids] += n
does not work, I know about this. For 1D arrays I use numpy.bincount(...)
function. But this function does not work for 2D arrays.

So, my question. What is the best way calculate accumulation sum for 2D
arrays using indirect indexes?

Sincerely,
Alexander
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From wesmckinn at gmail.com  Tue Jan 31 16:32:59 2012
From: wesmckinn at gmail.com (Wes McKinney)
Date: Tue, 31 Jan 2012 16:32:59 -0500
Subject: [SciPy-User] Accumulation sum using indirect indexes
In-Reply-To: <CACL-BpEbRSE=_TShy7udPH3s3N3K7Y_h_qb8D9RibOaTSNHtZQ@mail.gmail.com>
References: <CACL-BpEbRSE=_TShy7udPH3s3N3K7Y_h_qb8D9RibOaTSNHtZQ@mail.gmail.com>
Message-ID: <CAJPUwMDaKjgAg0LGv1HjkELgosGtHgi9ngbMfYx68YASUqwzCw@mail.gmail.com>

On Tue, Jan 31, 2012 at 3:34 PM, Alexander Kalinin
<alec.kalinin at gmail.com> wrote:
> Hello!
>
> I use SciPy in computer graphics applications. My task is to calculate
> vertex normals by averaging faces normals. In other words I want to
> accumulate vectors with the same ids. For example,
>
> ids = numpy.array([0, 1, 1, 2])
> n = numpy.array([ [0.1, 0.1, 0.1], [0.1, 0.1, 0.1], [0.1, 0.1, 0.1], [0.1,
> 0.1 0.1] ])
>
> I need result:
> nv = ([ [0.1, 0.1, 0.1], [0.2, 0.2, 0.2], [0.1, 0.1, 0.1]])
>
> The most simple code:
> nv[ids] += n
> does not work, I know about this. For 1D arrays I use numpy.bincount(...)
> function. But this function does not work for 2D arrays.
>
> So, my question. What is the best way calculate accumulation sum for 2D
> arrays using indirect indexes?
>
> Sincerely,
> Alexander
>
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user
>

It's long been on the pandas (http://pandas.sf.net) feature queue to
expose the GroupBy engine to NumPy arrays generally:
https://github.com/wesm/pandas/issues/123

for this you could certainly use a pandas.DataFrame:


In [19]: n
Out[19]:
array([[ 0.1,  0.1,  0.1],
       [ 0.1,  0.1,  0.1],
       [ 0.1,  0.1,  0.1],
       [ 0.1,  0.1,  0.1]])

In [20]: df = DataFrame(n)

In [21]: df.groupby(ids).sum()
Out[21]:
       0    1    2
key_0
0      0.1  0.1  0.1
1      0.2  0.2  0.2
2      0.1  0.1  0.1

if you want the ndarray back you can just get the .values attribute:

In [22]: df.groupby(ids).sum().values
Out[22]:
array([[ 0.1,  0.1,  0.1],
       [ 0.2,  0.2,  0.2],
       [ 0.1,  0.1,  0.1]])

hope this helps,
Wes


From travis at continuum.io  Tue Jan 31 17:26:14 2012
From: travis at continuum.io (Travis Oliphant)
Date: Tue, 31 Jan 2012 16:26:14 -0600
Subject: [SciPy-User] Accumulation sum using indirect indexes
In-Reply-To: <CACL-BpEbRSE=_TShy7udPH3s3N3K7Y_h_qb8D9RibOaTSNHtZQ@mail.gmail.com>
References: <CACL-BpEbRSE=_TShy7udPH3s3N3K7Y_h_qb8D9RibOaTSNHtZQ@mail.gmail.com>
Message-ID: <19963FB0-C327-4A20-B4EB-6FD37251455F@continuum.io>

This is the purpose of the group by NEP in NumPy.   It is on the roadmap.  In the mean time, you will need to either use Pandas group by or code something using indexing coupled with sum().

Thanks,

Travis 

--
Travis Oliphant
(on a mobile)
512-826-7480


On Jan 31, 2012, at 2:34 PM, Alexander Kalinin <alec.kalinin at gmail.com> wrote:

> Hello!
> 
> I use SciPy in computer graphics applications. My task is to calculate vertex normals by averaging faces normals. In other words I want to accumulate vectors with the same ids. For example,
> 
> ids = numpy.array([0, 1, 1, 2])
> n = numpy.array([ [0.1, 0.1, 0.1], [0.1, 0.1, 0.1], [0.1, 0.1, 0.1], [0.1, 0.1 0.1] ])
> 
> I need result:
> nv = ([ [0.1, 0.1, 0.1], [0.2, 0.2, 0.2], [0.1, 0.1, 0.1]])
> 
> The most simple code:
> nv[ids] += n
> does not work, I know about this. For 1D arrays I use numpy.bincount(...) function. But this function does not work for 2D arrays.
> 
> So, my question. What is the best way calculate accumulation sum for 2D arrays using indirect indexes?
> 
> Sincerely,
> Alexander
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user


From travis at vaught.net  Tue Jan 31 17:34:03 2012
From: travis at vaught.net (Travis Vaught)
Date: Tue, 31 Jan 2012 16:34:03 -0600
Subject: [SciPy-User] scipy interpolate issues
Message-ID: <742DC631-A7D7-4547-B974-C353A305BA38@vaught.net>

Greetings,

I'm experimenting with getting a smooth surface from a set of 3D points.  With the attached CME (requires mayavi for the visualization) I'm getting unexpected results.  The generated surface does not pass through the "known" points.  When I transpose the results, it looks correct.  Note: I also show the points connected by a Delaunay triangulation, whose surface is shown as contour lines.

Am I using scipy.interpolate.Rbf inappropriately?

TIA,

Travis


With transposing:

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without transposing:

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From pav at iki.fi  Tue Jan 31 17:41:51 2012
From: pav at iki.fi (Pauli Virtanen)
Date: Tue, 31 Jan 2012 23:41:51 +0100
Subject: [SciPy-User] scipy interpolate issues
In-Reply-To: <742DC631-A7D7-4547-B974-C353A305BA38@vaught.net>
References: <742DC631-A7D7-4547-B974-C353A305BA38@vaught.net>
Message-ID: <jg9qnf$ml4$1@dough.gmane.org>

31.01.2012 23:34, Travis Vaught kirjoitti:
> I'm experimenting with getting a smooth surface from a set of 3D points.
 > With the attached CME (requires mayavi for the visualization) I'm getting
 > unexpected results.  The generated surface does not pass through the 
"known"
 > points.  When I transpose the results, it looks correct.
 > Note: I also show the points connected by a Delaunay triangulation,
> whose surface is shown as contour lines.

np.meshgrid works like in Matlab, and returns "transposed" arrays. Maybe 
that's the problem here?

-- 
Pauli Virtanen



From srey at asu.edu  Tue Jan 31 22:50:40 2012
From: srey at asu.edu (Serge Rey)
Date: Tue, 31 Jan 2012 20:50:40 -0700
Subject: [SciPy-User] ANN: PySAL 1.3
Message-ID: <CAHrqYX2jFGMSmEnukFChh-ShbpCr3Nr-VL-971rPOjVu0FSEVg@mail.gmail.com>

On behalf of the PySAL development team, I'm happy to announce the
official release of PySAL 1.3.

PySAL is a library of tools for spatial data analysis and
geocomputation written in Python. PySAL 1.3, the fourth official
release of PySAL, includes a number of new features and enhancements:

    - The spatial regression module (spreg) has added:
        - Two Stage Least Squares
        - Spatial Two Stage Least Squares
        - GM Error (KP 98-99)
        - GM Error Homoskedasticity (Drukker et. al, 2010)
        - GM Error Heteroskedasticity (Arraiz et. al, 2010)
        - Spatial HAC variance-covariance estimation
        - Anselin-Kelejian test for residual spatial autocorrelation
of residuals from
        IV regression
        - New utility functions and other helper classes
    - A new contrib module to support user contributed modules. The first
      contrib modules are:
        - Weights Viewer ? A Graphical tool for examining spatial weights
        - World To View Transform ? A class for modeling viewing
windows, used by Weights Viewer
        - Shapely Extension ? Exposes shapely methods as standalone functions
        - Shared Perimeter Weights ? calculate shared perimeters weights


along with many bug fixes and smaller enhancements.

PySAL modules
-------------

    - pysal.core ? Core Data Structures and IO
    - pysal.cg ? Computational Geometry
    - pysal.esda ? Exploratory Spatial Data Analysis
    - pysal.inequality ? Spatial Inequality Analysis
    - pysal.spatial_dynamics ? Spatial Dynamics
    - pysal.spreg - Regression and Diagnostics
    - pysal.region ? Spatially Constrained Clustering
    - pysal.weights ? Spatial Weights
    - pysal.FileIO ? PySAL FileIO: Module for reading and writing
various file types in a Pythonic way
    - pysal.contrib ? Contributed Modules

Downloads
--------------
Binary installers and source distributions are available for download at
http://code.google.com/p/pysal/downloads/list

Documentation
-------------
The documentation site is here
 http://pysal.org/1.3/contents.html

Web sites
---------
PySAL's home is here
 http://pysal.org/

The developer's site is here
 http://code.google.com/p/pysal/

Mailing Lists
-------------
Please see the developer's list here
 http://groups.google.com/group/pysal-dev

Help for users is here
 http://groups.google.com/group/openspace-list

Bug reports
-----------
To search for or report bugs, please see
http://code.google.com/p/pysal/issues/list

License information
-------------------
See the file "LICENSE.txt" for information on the history of this
software, terms & conditions for usage, and a DISCLAIMER OF ALL
WARRANTIES.


Many thanks to all who contributed!

Serge, on behalf of the PySAL development team.


-- 
Sergio (Serge) Rey
Professor, School of Geographical Sciences and Urban Planning
GeoDa Center for Geospatial Analysis and Computation
Arizona State University
http://geoplan.asu.edu/rey

Editor, International Regional Science Review
http://irx.sagepub.com