[Numpy-discussion] RuntimeWarning: numpy.ndarray size changed
Hi all, Can someone reproduce the following message ? Python 2.7.2 (default, Aug 19 2011, 20:41:43) [GCC] on linux2 Type help, copyright, credits or license for more information. import numpy /home/nwagner/local/lib64/python2.7/site-packages/numpy/random/__init__.py:91: RuntimeWarning: numpy.ndarray size changed, may indicate binary incompatibility from mtrand import * numpy.__version__ '1.7.0.dev-9aac543' Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] Evaluate bivariate polynomials
Hi all, how do I evaluate a bivariate polynomial p(x,y)=c_0 + c_1 x + c_2 y +c_3 x**2 + c_4 x*y+ c_5 y**2 + c_6 x**3 + c_7 x**2*y + c_8 x*y**2+c_9*y**3 + \dots in numpy ? In case of univariate polynomials I can use np.polyval. Any pointer would be appreciated. Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] genfromtxt
Hi all,
How do I use genfromtxt to read a file with the following
lines
11 2.2592365264892578D+01
22 2.2592365264892578D+01
13 2.669845581055D+00
33 2.2592365264892578D+01
24 2.669845581055D+00
44 2.2592365264892578D+01
35 2.669845581055D+00
55 2.2592365264892578D+01
46 2.669845581055D+00
66 2.2592365264892578D+01
17 2.9814243316650391D+00
77 1.7259031295776367D+01
28 2.9814243316650391D+00
88 1.7259031295776367D+01
...
names =(i,j,v)
A =
np.genfromtxt('bmll.mtl',dtype=[('i','int'),('j','int'),('v','d')],names=names)
V = A[:]['v']
V
array([ NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN,
NaN, NaN, NaN,
NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN,
NaN, NaN, NaN,
NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN,
NaN, NaN, NaN,
NaN, NaN, NaN])
yields NaN, while
convertfunc = lambda x: x.replace('D','E')
names =(i,j,v)
A =
np.genfromtxt('bmll.mtl',dtype=[('i','int'),('j','int'),('v','|S24')],names=names,converters={v:convertfunc})
V = A[:]['v'].astype(float)
V
array([ 22.59236526, 22.59236526, 2.6698,
22.59236526,
2.6698, 22.59236526, 2.6698,
22.59236526,
2.6698, 22.59236526, 2.98142433,
17.2590313 ,
2.98142433, 17.2590313 , 2.98142433,
2.98142433,
2.6698, 22.59236526, 2.98142433,
2.98142433,
2.6698, 22.59236526, 2.98142433,
2.98142433,
2.6698, 22.59236526, 2.98142433,
2.98142433,
2.6698, 22.59236526, 2.98142433,
2.6698,
17.2590313 , 2.98142433, 2.6698,
17.2590313 ])
works fine.
Nils
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[Numpy-discussion] numpy.test() failure
ERROR: test_polyfit (test_polynomial.TestDocs) -- Traceback (most recent call last): File /home/nwagner/local/lib64/python2.6/site-packages/numpy/lib/tests/test_polynomial.py, line 106, in test_polyfit weights = arange(8,1,-1)**2/7.0 NameError: global name 'arange' is not defined == FAIL: Tests polyfit -- Traceback (most recent call last): File /home/nwagner/local/lib64/python2.6/site-packages/numpy/ma/tests/test_extras.py, line 622, in test_polyfit assert_almost_equal(a, a_) File /home/nwagner/local/lib64/python2.6/site-packages/numpy/ma/testutils.py, line 155, in assert_almost_equal err_msg=err_msg, verbose=verbose) File /home/nwagner/local/lib64/python2.6/site-packages/numpy/ma/testutils.py, line 221, in assert_array_almost_equal header='Arrays are not almost equal') File /home/nwagner/local/lib64/python2.6/site-packages/numpy/ma/testutils.py, line 186, in assert_array_compare verbose=verbose, header=header) File /home/nwagner/local/lib64/python2.6/site-packages/numpy/testing/utils.py, line 677, in assert_array_compare raise AssertionError(msg) AssertionError: Arrays are not almost equal (mismatch 100.0%) x: array([ 4.25134878, 1.14131297, 0.20519666, 0.01701 ]) y: array([ 1.9345248 , 0.49711011, 0.10202554, 0.00928034]) ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] ValueError: Unknown format code 'g' for object of type 'str'
numpy.__version__ '2.0.0.dev-10db259' == ERROR: Test the str.format method with NumPy scalar types -- Traceback (most recent call last): File /home/nwagner/local/lib64/python2.6/site-packages/nose-0.11.2.dev-py2.6.egg/nose/case.py, line 183, in runTest self.test(*self.arg) File /home/nwagner/local/lib64/python2.6/site-packages/numpy/testing/decorators.py, line 146, in skipper_func return f(*args, **kwargs) File /home/nwagner/local/lib64/python2.6/site-packages/numpy/core/tests/test_print.py, line 223, in test_scalar_format assert_equal(fmat.format(val), fmat.format(valtype(val)), ValueError: Unknown format code 'g' for object of type 'str' ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] NumPy speed tests by NASA
On Thu, 24 Feb 2011 14:26:01 -0500
Frédéric Bastien no...@nouiz.org wrote:
Hi,
To print the information you can do:
python -c 'import numpy;numpy.__config__.show()'
You can access the info directly with:
numpy.distutils.__config__.blas_opt_info['library_dirs']]
numpy.distutils.__config__.blas_opt_info['libraries']]
numpy.distutils.__config__.blas_opt_info['include_dirs']]
This is what I do in Theano.
Fred
You can do
from numpy import show_config
show_config()
atlas_threads_info:
libraries = ['lapack', 'ptf77blas', 'ptcblas',
'atlas']
library_dirs =
['/home/nwagner/src/ATLAS3.8.2/mybuild/lib']
define_macros = [('ATLAS_INFO', '\\3.8.2\\')]
language = f77
include_dirs =
['/home/nwagner/src/ATLAS3.8.2/include']
blas_opt_info:
libraries = ['ptf77blas', 'ptcblas', 'atlas']
library_dirs =
['/home/nwagner/src/ATLAS3.8.2/mybuild/lib']
define_macros = [('ATLAS_INFO', '\\3.8.2\\')]
language = c
include_dirs =
['/home/nwagner/src/ATLAS3.8.2/include']
atlas_blas_threads_info:
libraries = ['ptf77blas', 'ptcblas', 'atlas']
library_dirs =
['/home/nwagner/src/ATLAS3.8.2/mybuild/lib']
define_macros = [('ATLAS_INFO', '\\3.8.2\\')]
language = c
include_dirs =
['/home/nwagner/src/ATLAS3.8.2/include']
lapack_opt_info:
libraries = ['lapack', 'ptf77blas', 'ptcblas',
'atlas']
library_dirs =
['/home/nwagner/src/ATLAS3.8.2/mybuild/lib']
define_macros = [('ATLAS_INFO', '\\3.8.2\\')]
language = f77
include_dirs =
['/home/nwagner/src/ATLAS3.8.2/include']
lapack_mkl_info:
NOT AVAILABLE
blas_mkl_info:
NOT AVAILABLE
mkl_info:
NOT AVAILABLE
On Tue, Feb 22, 2011 at 7:05 PM, Eli Stevens (Gmail)
wickedg...@gmail.com wrote:
On Tue, Feb 22, 2011 at 1:48 PM, Gael Varoquaux
gael.varoqu...@normalesup.org wrote:
Probably because the numpy binary that the author was
using was compiled
without a blas implementation, and just using numpy's
internal
lapack_lite. This is a common problem in real life.
Is there an easy way to check from within numpy if it's
using a blas
iplementation or not?
Thanks,
Eli
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Re: [Numpy-discussion] numpy.test() Program received signal SIGABRT, Aborted.
On Fri, 3 Dec 2010 00:42:16 -0700 Charles R Harris charlesr.har...@gmail.com wrote: On Fri, Dec 3, 2010 at 12:29 AM, Nils Wagner nwag...@iam.uni-stuttgart.dewrote: Hi all, I have installed the latest version of numpy. numpy.__version__ '2.0.0.dev-6aacc2d' I don't see that here or on the buildbots. There was a problem with segfaults that was fixed in commit c0e1cf27b55dfd5ahttps://github.com/numpy/numpy/commit/c0e1cf27b55dfd5aa4b1674a8c1b6ac38c36Can you check that your installation is clean, etc. Also, what platform are you running on? I have removed the build directory. Is it also neccessary to remove numpy in thr installation directory ? /data/home/nwagner/local/lib/python2.5/site-packages/ Platform 2.6.18-92.el5 #1 SMP Tue Jun 10 18:51:06 EDT 2008 x86_64 x86_64 x86_64 GNU/Linux Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] numpy.test() Program received signal SIGABRT, Aborted.
On Fri, 03 Dec 2010 08:47:32 +0100 Nils Wagner nwag...@iam.uni-stuttgart.de wrote: On Fri, 3 Dec 2010 00:42:16 -0700 Charles R Harris charlesr.har...@gmail.com wrote: On Fri, Dec 3, 2010 at 12:29 AM, Nils Wagner nwag...@iam.uni-stuttgart.dewrote: Hi all, I have installed the latest version of numpy. numpy.__version__ '2.0.0.dev-6aacc2d' I don't see that here or on the buildbots. There was a problem with segfaults that was fixed in commit c0e1cf27b55dfd5ahttps://github.com/numpy/numpy/commit/c0e1cf27b55dfd5aa4b1674a8c1b6ac38c36Can you check that your installation is clean, etc. Also, what platform are you running on? I have removed the build directory. Is it also neccessary to remove numpy in thr installation directory ? /data/home/nwagner/local/lib/python2.5/site-packages/ Platform 2.6.18-92.el5 #1 SMP Tue Jun 10 18:51:06 EDT 2008 x86_64 x86_64 x86_64 GNU/Linux Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion I have also removed the numpy directory within /data/home/nwagner/local/lib/python2.5/site-packages/. Now all tests pass. Ran 3080 tests in 12.288s OK (KNOWNFAIL=4, SKIP=1) nose.result.TextTestResult run=3080 errors=0 failures=0 How is the build process implemented on the build bots ? Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] numpy.test() errors
On Tue, 23 Nov 2010 16:39:13 +0100 Gerrit Holl gerrit.h...@gmail.com wrote: 2010/11/23 Stéfan van der Walt ste...@sun.ac.za: On Tue, Nov 23, 2010 at 9:28 AM, Nils Wagner nwag...@iam.uni-stuttgart.de wrote: /data/home/nwagner/local/lib/python2.5/site-packages/numpy/lib/npyio.py, line 66, in seek_gzip_factory g.name = f.name AttributeError: GzipFile instance has no attribute 'name' This one is mine--the change was made to avoid a deprecationwarning. Which version of Python are you using? I hope 2.5, as his site-packages directory is in lib/python2.5 :) Exactly. Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] numpy.test() errors
Hi all, There are some new test errors == ERROR: Test with missing and filling values -- Traceback (most recent call last): File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/lib/tests/test_io.py, line 947, in test_user_filling_values test = np.genfromtxt(StringIO(data), **kwargs) File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/lib/npyio.py, line 1285, in genfromtxt key = names.index(key) AttributeError: 'tuple' object has no attribute 'index' == ERROR: test_user_missing_values (test_io.TestFromTxt) -- Traceback (most recent call last): File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/lib/tests/test_io.py, line 931, in test_user_missing_values **basekwargs) File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/lib/npyio.py, line 1657, in mafromtxt return genfromtxt(fname, **kwargs) File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/lib/npyio.py, line 1285, in genfromtxt key = names.index(key) AttributeError: 'tuple' object has no attribute 'index' == ERROR: test_io.test_gzip_load -- Traceback (most recent call last): File /data/home/nwagner/local/lib/python2.5/site-packages/nose-0.11.1-py2.5.egg/nose/case.py, line 183, in runTest self.test(*self.arg) File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/lib/tests/test_io.py, line 1255, in test_gzip_load assert_array_equal(np.load(f), a) File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/lib/npyio.py, line 327, in load fid = seek_gzip_factory(file) File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/lib/npyio.py, line 66, in seek_gzip_factory g.name = f.name AttributeError: GzipFile instance has no attribute 'name' -- Ran 3066 tests in 12.458s FAILED (KNOWNFAIL=4, errors=3) nose.result.TextTestResult run=3066 errors=3 failures=0 numpy.__version__ '2.0.0.dev-12d0200' Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] numpy.test() segfaults '2.0.0.dev8716'
test_duplicate_field_names_assign (test_regression.TestRegression) ... FF Program received signal SIGSEGV, Segmentation fault. 0x77b3077a in ?? () from /usr/lib64/libpython2.6.so.1.0 (gdb) bt #0 0x77b3077a in ?? () from /usr/lib64/libpython2.6.so.1.0 #1 0x77b2ea3f in _PyArg_ParseTuple_SizeT () from /usr/lib64/libpython2.6.so.1.0 #2 0x762ce02e in VOID_getitem (ip=0x1583150 , ap=0x175f160) at numpy/core/src/multiarray/arraytypes.c.src:565 #3 0x762e64eb in array_toscalar (self=0x175f160, args=value optimized out) at numpy/core/src/multiarray/methods.c:554 #4 0x77b2165c in PyEval_EvalFrameEx () from /usr/lib64/libpython2.6.so.1.0 #5 0x77b26251 in PyEval_EvalCodeEx () from /usr/lib64/libpython2.6.so.1.0 #6 0x77b2103d in PyEval_EvalFrameEx () from /usr/lib64/libpython2.6.so.1.0 #7 0x77b26431 in PyEval_EvalCodeEx () from /usr/lib64/libpython2.6.so.1.0 #8 0x77af3db2 in ?? () from /usr/lib64/libpython2.6.so.1.0 #9 0x77ae7cb2 in PyObject_Call () from /usr/lib64/libpython2.6.so.1.0 #10 0x77b1fd26 in PyEval_CallObjectWithKeywords () from /usr/lib64/libpython2.6.so.1.0 #11 0x762c2184 in array_str (self=value optimized out) at numpy/core/src/multiarray/arrayobject.c:393 #12 0x77b002e8 in _PyObject_Str () from /usr/lib64/libpython2.6.so.1.0 #13 0x77b003ea in PyObject_Str () from /usr/lib64/libpython2.6.so.1.0 ---Type return to continue, or q return to quit---q Quit ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Schedule for 1.5.1?
On Thu, 7 Oct 2010 09:06:55 + (UTC) Pauli Virtanen p...@iki.fi wrote: Thu, 07 Oct 2010 16:34:46 +0800, Ralf Gommers wrote: [clip] A 1.5.1 release soon would be good. All the issues above are already committed, is there anything else that needs to go in? If not, I think an RC by the end of next week (10/17) and release by the end of the month should be possible. Sounds good to me. I don't remember any other critical bugs being present, but I can go through the tickets during next WE in case there are some low-hanging fruits. Pauli However, there is an everlasting ticket opened 2 years ago http://projects.scipy.org/numpy/ticket/937 Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] bug in ceil()
On Wed, 06 Oct 2010 19:55:00 +0200 Christian Fischer cfisc...@itm.uni-stuttgart.de wrote: Hi All, I use numpy 1.4.1 on Debian squeeze amd64. I noticed that ceil() is not working properly. If the input to ceil() is a float I expect a float to be returned but for inputs in (-1.0, 0.0) the result is of type integer. In [65]: np.__version__ Out[65]: '1.4.1' In [66]: np.ceil(-1.1) Out[66]: -1.0 In [67]: np.ceil(-0.734) Out[67]: -0 In [68]: np.ceil(-0.256) Out[68]: -0 In [69]: np.ceil(-0.0) Out[69]: -0 In [70]: np.ceil(0.2) Out[70]: 1.0 Best wishes Christian It's a float type(numpy.ceil(-0.4)) type 'numpy.float64' numpy.ceil(-0.4) -0 Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] python setup.py bdist --format=rpm
Hi all, I tried to build a rpm of numpy using python setup.py bdist --format=rpm removing 'numpy-2.0.0.dev8460' (and everything under it) copying dist/numpy-2.0.0.dev8460.tar.gz - build/bdist.linux-x86_64/rpm/SOURCES building RPMs rpm -ba --define _topdir /data/home/nwagner/svn/numpy/build/bdist.linux-x86_64/rpm --clean build/bdist.linux-x86_64/rpm/SPECS/numpy.spec -ba: unknown option error: command 'rpm' failed with exit status 1 How can I fix the problem ? Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Calling routines from a Fortran library using python
On Mon, 22 Feb 2010 22:18:23 +0900
David Cournapeau courn...@gmail.com wrote:
On Mon, Feb 22, 2010 at 10:01 PM, Nils Wagner
nwag...@iam.uni-stuttgart.de wrote:
ar x test.a
gfortran -shared *.o -o libtest.so -lg2c
to build a shared library. The additional option -lg2c
was
necessary due to an undefined symbol: s_cmp
You should avoid the -lg2c option at any cost if
compiling with
gfortran. I am afraid that you got a library compiled
with g77. If
that's the case, you should use g77 and not gfortran.
You cannot mix
libraries built with one with libraries with another.
Now I am able to load the shared library
from ctypes import *
my_lib = CDLL('test.so')
What are the next steps to use the library functions
within python ?
You use it as you would use a C library:
http://python.net/crew/theller/ctypes/tutorial.html
But the fortran ABI, at least for code built with g77
and gfortran,
pass everything by reference. To make sure to pass the
right
arguments, I strongly suggest to double check with the
.h you
received.
cheers,
David
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Hi all,
I tried to run the following script.
The result is a segmentation fault.
Did I use byref correctly ?
from ctypes import *
my_dsio = CDLL('libdsio20_gnu4.so') # loading dynamic
link libraries
#
# FORTRAN : CALL DSIO(JUNCAT,FDSCAT,IERR)
#
# int
I,J,K,N,IDE,IA,IE,IERR,JUNIT,JUNCAT,NDATA,NREC,LREADY,ONE=1;
# WordBUF[100],HEAD[30];
# char*PATH,*STRING;
# char*PGNAME,*DATE,*TIME,*TEXT;
# int LHEAD=30;
#
# C : DSIO(JUNCAT,FDSCAT,IERR,strlen(FDSCAT));
#
IERR= c_int()
FDSCAT = c_char_p('dscat.ds')
JUNCAT = c_int()
LDSNCAT = c_int(len(FDSCAT.value))
print
print 'LDSNCAT', LDSNCAT.value
print 'FDSCAT' , FDSCAT.value , len(FDSCAT.value)
my_dsio.dsio(byref(JUNCAT),byref(FDSCAT),byref(IERR),byref(LDSNCAT))
# segmentation fault
print IERR.value
Any idea ?
Nils
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Re: [Numpy-discussion] Calling routines from a Fortran library using python
On Thu, 11 Mar 2010 13:42:43 +0100
Dag Sverre Seljebotn da...@student.matnat.uio.no
wrote:
Nils Wagner wrote:
On Thu, 11 Mar 2010 13:01:33 +0100
Dag Sverre Seljebotn da...@student.matnat.uio.no
wrote:
Nils Wagner wrote:
On Mon, 22 Feb 2010 22:18:23 +0900
David Cournapeau courn...@gmail.com wrote:
On Mon, Feb 22, 2010 at 10:01 PM, Nils Wagner
nwag...@iam.uni-stuttgart.de wrote:
ar x test.a
gfortran -shared *.o -o libtest.so -lg2c
to build a shared library. The additional option -lg2c
was
necessary due to an undefined symbol: s_cmp
You should avoid the -lg2c option at any cost if
compiling with
gfortran. I am afraid that you got a library compiled
with g77. If
that's the case, you should use g77 and not gfortran.
You cannot mix
libraries built with one with libraries with another.
Now I am able to load the shared library
from ctypes import *
my_lib = CDLL('test.so')
What are the next steps to use the library functions
within python ?
You use it as you would use a C library:
http://python.net/crew/theller/ctypes/tutorial.html
But the fortran ABI, at least for code built with g77
and gfortran,
pass everything by reference. To make sure to pass the
right
arguments, I strongly suggest to double check with the
.h you
received.
cheers,
David
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Hi all,
I tried to run the following script.
The result is a segmentation fault.
Did I use byref correctly ?
from ctypes import *
my_dsio = CDLL('libdsio20_gnu4.so') # loading
dynamic
link libraries
#
# FORTRAN : CALL DSIO(JUNCAT,FDSCAT,IERR)
#
# int
I,J,K,N,IDE,IA,IE,IERR,JUNIT,JUNCAT,NDATA,NREC,LREADY,ONE=1;
# WordBUF[100],HEAD[30];
# char*PATH,*STRING;
# char*PGNAME,*DATE,*TIME,*TEXT;
# int LHEAD=30;
#
# C : DSIO(JUNCAT,FDSCAT,IERR,strlen(FDSCAT));
#
IERR= c_int()
FDSCAT = c_char_p('dscat.ds')
JUNCAT = c_int()
LDSNCAT = c_int(len(FDSCAT.value))
print
print 'LDSNCAT', LDSNCAT.value
print 'FDSCAT' , FDSCAT.value , len(FDSCAT.value)
my_dsio.dsio(byref(JUNCAT),byref(FDSCAT),byref(IERR),byref(LDSNCAT))
# segmentation fault
print IERR.value
Any idea ?
You shouldn't have byref on FDSCAT nor LDSNCAT, as
explained by this line:
# C : DSIO(JUNCAT,FDSCAT,IERR,strlen(FDSCAT));
Dag Sverre
Sorry, I am newbie to C. What is the correct way ?
my_dsio.dsio(byref(JUNCAT),FDSCAT,byref(IERR),LDSNCAT)
Dag
Great. It works like a charme.
How can I translate the following C-code into Python ?
I don't know how to handle HEAD and memcpy ?
Any pointer would be appreciated.
Thanks in advance.
typedef union {
int i;
float f;
charc[4];
} Word;
int
I,J,K,N,IDE,IA,IE,IERR,JUNIT,JUNCAT,NDATA,NREC,LREADY,ONE=1;
Word BUF[100],HEAD[30];
for (I=5;ILHEAD;I++)
HEAD[I].i = 0;
HEAD[ 0].i = 1;
HEAD[ 1].i = LHEAD + NDATA*7;
HEAD[ 2].i = LHEAD;
HEAD[ 3].i = NDATA;
HEAD[ 4].i = 7;
memcpy (HEAD[ 7].c,DSIO,4);
memcpy (HEAD[ 8].c,TEST,4);
memcpy (HEAD[ 9].c,NPCO,4);
memcpy (HEAD[10].c,,4);
memcpy (HEAD[11].c,DSIO,4);
HEAD[20].i = 1;
HEAD[21].i = NDATA;
STRING = MM RAD;
DSEINH(STRING,HEAD[24].i,ONE,
strlen(STRING));
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Re: [Numpy-discussion] NumPy SciPy with Snow Leopard 64-bit Py-2.6.4
On Mon, 1 Mar 2010 15:49:52 -0500
josef.p...@gmail.com wrote:
On Mon, Mar 1, 2010 at 3:23 PM, Tom Loredo
lor...@astro.cornell.edu wrote:
Just wanted to report qualified success installing NumPy
SciPy under
a 64-bit build of Python-2.6.4 (universal framework) on
OS X 10.6.2
(current Snow Leopard). I am using the current SVN
checkouts
(numpy r8270, scipy r6250).
NumPy has installed successfully for some time now and
the current
SVN maintains this:
numpy.test()
..
Ran 2521 tests in 8.518s
OK (KNOWNFAIL=4, SKIP=1)
SciPy has been causing me problems for weeks with
segfaults with
IFFT tests, as reported on scipy-dev (no one ever
responded to
this so I made no progress in diagnosing it):
http://mail.scipy.org/pipermail/scipy-dev/2010-February/013921.html
However, r6250 now runs scipy.test() without segfault,
though with
22 errors and 2 failures. The full tests give:
scipy.test('full')
..
Ran 4982 tests in 652.478s
FAILED (KNOWNFAIL=13, SKIP=27, errors=22, failures=6)
I am not familiar with what many of the tests are
covering, so I
cannot assess the severity of all the errors and
failures. Some
of them seem to be bugs in the tests (e.g., use of an
unexpected
keyword new in several histogram tests);
np.histogram(rvs,histsupp,new=True)
this still needs to be changed in scipy.stats, because
new keyword has
been removed in numpy trunk 2 weeks ago.
Josef
others are innocuous
(e.g., missing PIL, which I haven't installed yet).
I've posted
the report here:
http://www.pastie.org/848651
I'd appreciate comments on which issues are nontrivial
and
deserve attention to as a SciPy user. E.g., the first
error
is in an lapack test and involves a ValueError where
infs or
NaNs appear where they shouldn't. Is this a bug in the
test,
or does it indicate a 64-bit issue that is making
inf/NaN
appear where it shouldn't? E.g., there are arpack
errors,
but I don't know what the Error info=-8 message
signifies.
Other arpack errors are due to large solution
mismatches,
which I presume are serious and deserve attention.
Thanks,
Tom Loredo
Last but not least there is an annoying bug lurking around
for 17 months
http://projects.scipy.org/numpy/ticket/937
Nils
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Re: [Numpy-discussion] Calling routines from a Fortran library using python
On Mon, 22 Feb 2010 22:18:23 +0900
David Cournapeau courn...@gmail.com wrote:
On Mon, Feb 22, 2010 at 10:01 PM, Nils Wagner
nwag...@iam.uni-stuttgart.de wrote:
ar x test.a
gfortran -shared *.o -o libtest.so -lg2c
to build a shared library. The additional option -lg2c
was
necessary due to an undefined symbol: s_cmp
You should avoid the -lg2c option at any cost if
compiling with
gfortran. I am afraid that you got a library compiled
with g77. If
that's the case, you should use g77 and not gfortran.
You cannot mix
libraries built with one with libraries with another.
Now I am able to load the shared library
from ctypes import *
my_lib = CDLL('test.so')
What are the next steps to use the library functions
within python ?
You use it as you would use a C library:
http://python.net/crew/theller/ctypes/tutorial.html
But the fortran ABI, at least for code built with g77
and gfortran,
pass everything by reference. To make sure to pass the
right
arguments, I strongly suggest to double check with the
.h you
received.
cheers,
David
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Just to play it safe
Consider
extern void dsio(int* const,const char* const,
int* const,const size_t);
extern void dsrhed (const int* const,const int*
const,void* const,
const int* const,const int* const,int* const,
int* const,int* const,int* const,int* const,
int* const,int* const,int* const);
from ctypes import *
my_lib = CDLL('libtest.so')
How do I call the functions within python
I mean what arguments are needed ?
my_lib.dsio()
my_lib.dsrhed( )
Thank you very much for your help.
Cheers,
Nils
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Re: [Numpy-discussion] Calling routines from a Fortran library using python
On Thu, 18 Feb 2010 22:29:39 +0900
David Cournapeau courn...@gmail.com wrote:
On Thu, Feb 18, 2010 at 10:22 PM, Nils Wagner
nwag...@iam.uni-stuttgart.de wrote:
On Thu, 18 Feb 2010 11:55:07 +0100
Matthieu Brucher matthieu.bruc...@gmail.com wrote:
Ok I have extracted the *.o files from the static
library.
Applying the file command to the object files yields
ELF 64-bit LSB relocatable, AMD x86-64, version 1
(SYSV),
not stripped
What's that supposed to mean ?
It means that each object file is an object file
compiled with -fPIC,
so you just have to make a shared library (gfortran
-shared *.o -o
libmysharedlibrary.so)
Then, you can try to open the library with ctypes. If
something is
lacking, you may have to add -lsome_library to the
gfortran line.
Matthieu
--
Information System Engineer, Ph.D.
Blog: http://matt.eifelle.com
LinkedIn: http://www.linkedin.com/in/matthieubrucher
O.k. I tried
gfortran -shared *.o -o libmysharedlibrary.so
/usr/bin/ld: dxop.o: relocation R_X86_64_32 against `a
local symbol' can not be used when making a shared
object;
recompile with -fPIC
The message is pretty explicit: it is not compiled with
-fPIC, there
is nothing you can do, short of requesting a shared
library from the
software vendor.
David
Hi,
Meanwhile I received a static library (including -fPIC
support) from the software vendor.
Now I have used
ar x test.a
gfortran -shared *.o -o libtest.so -lg2c
to build a shared library. The additional option -lg2c was
necessary due to an undefined symbol: s_cmp
Now I am able to load the shared library
from ctypes import *
my_lib = CDLL('test.so')
What are the next steps to use the library functions
within python ?
Nils
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Re: [Numpy-discussion] Calling routines from a Fortran library using python
On Mon, 22 Feb 2010 22:18:23 +0900
David Cournapeau courn...@gmail.com wrote:
On Mon, Feb 22, 2010 at 10:01 PM, Nils Wagner
nwag...@iam.uni-stuttgart.de wrote:
ar x test.a
gfortran -shared *.o -o libtest.so -lg2c
to build a shared library. The additional option -lg2c
was
necessary due to an undefined symbol: s_cmp
You should avoid the -lg2c option at any cost if
compiling with
gfortran. I am afraid that you got a library compiled
with g77. If
that's the case, you should use g77 and not gfortran.
You cannot mix
libraries built with one with libraries with another.
g77 -shared *.o -o libtest.so -lg2c
failed with
/usr/lib/64/gcc-lib/x86_64-suse-linux/3.3.5/../../../../x86_64-suse-linux/bin/ld:
cannot find -lgcc_s
IIRC that is a known bug related to SuSE .
Are you aware of a solution ?
Cheers,
Nils
Now I am able to load the shared library
from ctypes import *
my_lib = CDLL('test.so')
What are the next steps to use the library functions
within python ?
You use it as you would use a C library:
http://python.net/crew/theller/ctypes/tutorial.html
But the fortran ABI, at least for code built with g77
and gfortran,
pass everything by reference. To make sure to pass the
right
arguments, I strongly suggest to double check with the
.h you
received.
cheers,
David
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[Numpy-discussion] numpy.test() failures in 2.0.0.dev8233
==
FAIL:
test_multiarray.TestNewBufferProtocol.test_export_endian
--
Traceback (most recent call last):
File
/home/nwagner/local/lib64/python2.6/site-packages/nose-0.11.2.dev-py2.6.egg/nose/case.py,
line 183, in runTest
self.test(*self.arg)
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/core/tests/test_multiarray.py,
line 1582, in test_export_endian
assert y.format in 'l'
AssertionError
==
FAIL:
test_multiarray.TestNewBufferProtocol.test_export_record
--
Traceback (most recent call last):
File
/home/nwagner/local/lib64/python2.6/site-packages/nose-0.11.2.dev-py2.6.egg/nose/case.py,
line 183, in runTest
self.test(*self.arg)
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/core/tests/test_multiarray.py,
line 1561, in test_export_record
assert y.format ==
'T{b:a:=h:b:=l:c:=q:d:B:e:=H:f:=L:g:=Q:h:=d:i:=d:j:=g:k:4s:l:=4w:m:3x:n:?:o:}'
AssertionError
==
FAIL:
test_multiarray.TestNewBufferProtocol.test_export_simple_1d
--
Traceback (most recent call last):
File
/home/nwagner/local/lib64/python2.6/site-packages/nose-0.11.2.dev-py2.6.egg/nose/case.py,
line 183, in runTest
self.test(*self.arg)
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/core/tests/test_multiarray.py,
line 1514, in test_export_simple_1d
assert y.format == '=l'
AssertionError
==
FAIL:
test_multiarray.TestNewBufferProtocol.test_export_subarray
--
Traceback (most recent call last):
File
/home/nwagner/local/lib64/python2.6/site-packages/nose-0.11.2.dev-py2.6.egg/nose/case.py,
line 183, in runTest
self.test(*self.arg)
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/core/tests/test_multiarray.py,
line 1576, in test_export_subarray
assert y.itemsize == 16
AssertionError
--
Ran 2519 tests in 21.494s
FAILED (KNOWNFAIL=4, failures=4)
nose.result.TextTestResult run=2519 errors=0 failures=4
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Re: [Numpy-discussion] Request for testing
On Sun, 21 Feb 2010 03:30:31 -0700
Charles R Harris charlesr.har...@gmail.com wrote:
Hi All,
I would be much obliged if some folks would run the
attached script and
report the output, numpy version, and python version. It
just runs
np.isinf(np.inf), which raises an invalid value
warning with current
numpy. As far as I can see the function itself hasn't
changed since
numpy1.3, yet numpy1.3 python2.5 gives no such
warning.
Chuck
python -i isinf.py
2.0.0.dev8233
2.6.2
import numpy as np
import warnings
import platform
print np.__version__
print platform.python_version()
warnings.simplefilter('always')
np.seterr(invalid='print')
print (np.isinf(np.inf))
Nils
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Re: [Numpy-discussion] numpy.test() failures in 2.0.0.dev8233
On Sun, 21 Feb 2010 13:22:41 +0200
Pauli Virtanen p...@iki.fi wrote:
Hi,
Please remind me what platform you are running on. Also,
please update
and re-run the tests, and check the output from
import numpy as np
from numpy.core.multiarray import memorysimpleview as
memoryview
dt = [('a', np.int8), ('b', np.int16),
('c', np.int32), ('d', np.int64),
('e', np.uint8), ('f', np.uint16),
('g', np.uint32), ('h', np.uint64),
('i', np.float), ('j', np.double),
('k', np.longdouble), ('l', 'S4'),
('m', 'U4'), ('n', 'V3'), ('o', '?')]
x = np.array([(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
'', '', ' ', True)], dtype=dt)
print memoryview(x).format
x = np.array([1,2,3], dtype='i4')
print memoryview(x).format
x = np.array(([[1,2],[3,4]],), dtype=[('a', (int,
(2,2)))])
print memoryview(x).format
print memoryview(x).itemsize
T{b:a:=h:b:=i:c:=l:d:B:e:=H:f:=I:g:=L:h:=d:i:=d:j:=g:k:4s:l:=4w:m:3x:n:?:o:}
i
T{(2,2)=l:a:}
32
Linux-2.6.31.12-0.1-default-x86_64-with-SuSE-11.2-x86_64
2.0.0.dev8235
Nils
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[Numpy-discussion] Calling routines from a Fortran library using python
Hi all, I have a static library (*.a) compiled by gfortran but no source files. How can I call routines from that library using python ? Any pointer would be appreciated. Thanks in advance. Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Calling routines from a Fortran library using python
On Thu, 18 Feb 2010 18:32:18 +0900 David Cournapeau da...@silveregg.co.jp wrote: Nils Wagner wrote: Hi all, I have a static library (*.a) compiled by gfortran but no source files. How can I call routines from that library using python ? Is there any kind of interface (.h, etc...) ? If this is a proprietary library, there has to be something so that it can be called from C, and anything that can be called from C can be called from python. If you don't know at least the functions signatures, it will be very difficult (you would have to disassemble the code to find how the functions are called, etc...). cheers, David Hi David, you are right. It's a proprietary library. I found a header file (*.h) including prototype declarations of externally callable procedures. How can I proceed ? Thank you again. Cheers, Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Calling routines from a Fortran library using python
On Thu, 18 Feb 2010 10:15:51 + (UTC) Neil Crighton neilcrigh...@gmail.com wrote: Nils Wagner nwagner at iam.uni-stuttgart.de writes: Hi David, you are right. It's a proprietary library. I found a header file (*.h) including prototype declarations of externally callable procedures. How can I proceed ? Apparently you can use ctypes to access fortran libraries. See the first paragraph of: http://www.sagemath.org/doc/numerical_sage/ctypes.html You may have to convert the .a library to a .so library. Neil How do I convert the .a library to a .so library ? Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Calling routines from a Fortran library using python
On Thu, 18 Feb 2010 19:21:03 +0900 David Cournapeau da...@silveregg.co.jp wrote: Nils Wagner wrote: On Thu, 18 Feb 2010 18:32:18 +0900 David Cournapeau da...@silveregg.co.jp wrote: Nils Wagner wrote: Hi all, I have a static library (*.a) compiled by gfortran but no source files. How can I call routines from that library using python ? Is there any kind of interface (.h, etc...) ? If this is a proprietary library, there has to be something so that it can be called from C, and anything that can be called from C can be called from python. If you don't know at least the functions signatures, it will be very difficult (you would have to disassemble the code to find how the functions are called, etc...). cheers, David Hi David, you are right. It's a proprietary library. I found a header file (*.h) including prototype declarations of externally callable procedures. How can I proceed ? Exactly as you would do for a C library (ctypes, cython, by hand, swig, etc...). Once you have the header (plus the C-Fortran ABI convention, which depend on your compilers and platforms), it is exactly as calling a C function in a C library, cheers, David To be honest that's over my head. I mean I have never used C before. Where can I find a step-by-step example for my task ? Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Calling routines from a Fortran library using python
On Thu, 18 Feb 2010 19:30:10 +0900 David Cournapeau da...@silveregg.co.jp wrote: Nils Wagner wrote: How do I convert the .a library to a .so library ? You first uncompress the .a into a temporary directory, with ar x on Linux. Then, you group the .o together with gfortran -shared $LIST_OF_OBJECT + a few options. You can also look at how Atlas does it in its makefile. As Matthieu mentioned, if the .o are not compiled with -fPIC, you are screwed on 64 bits architectures (unless you statically link numpy in your python interpreter, but I doubt you want to go that road). It would be somewhat surprising if your vendor did not shared libraries available, though. cheers, David Ok I have extracted the *.o files from the static library. Applying the file command to the object files yields ELF 64-bit LSB relocatable, AMD x86-64, version 1 (SYSV), not stripped What's that supposed to mean ? Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Calling routines from a Fortran library using python
On Thu, 18 Feb 2010 11:55:07 +0100 Matthieu Brucher matthieu.bruc...@gmail.com wrote: Ok I have extracted the *.o files from the static library. Applying the file command to the object files yields ELF 64-bit LSB relocatable, AMD x86-64, version 1 (SYSV), not stripped What's that supposed to mean ? It means that each object file is an object file compiled with -fPIC, so you just have to make a shared library (gfortran -shared *.o -o libmysharedlibrary.so) Then, you can try to open the library with ctypes. If something is lacking, you may have to add -lsome_library to the gfortran line. Matthieu -- Information System Engineer, Ph.D. Blog: http://matt.eifelle.com LinkedIn: http://www.linkedin.com/in/matthieubrucher O.k. I tried gfortran -shared *.o -o libmysharedlibrary.so /usr/bin/ld: dxop.o: relocation R_X86_64_32 against `a local symbol' can not be used when making a shared object; recompile with -fPIC dscpde.o: could not read symbols: Bad value Any idea ? Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Calling routines from a Fortran library using python
On Thu, 18 Feb 2010 15:32:12 +0100 Dag Sverre Seljebotn da...@student.matnat.uio.no wrote: David Cournapeau wrote: On Thu, Feb 18, 2010 at 10:22 PM, Nils Wagner nwag...@iam.uni-stuttgart.de wrote: On Thu, 18 Feb 2010 11:55:07 +0100 Matthieu Brucher matthieu.bruc...@gmail.com wrote: Ok I have extracted the *.o files from the static library. Applying the file command to the object files yields ELF 64-bit LSB relocatable, AMD x86-64, version 1 (SYSV), not stripped What's that supposed to mean ? It means that each object file is an object file compiled with -fPIC, so you just have to make a shared library (gfortran -shared *.o -o libmysharedlibrary.so) Then, you can try to open the library with ctypes. If something is lacking, you may have to add -lsome_library to the gfortran line. Matthieu -- Information System Engineer, Ph.D. Blog: http://matt.eifelle.com LinkedIn: http://www.linkedin.com/in/matthieubrucher O.k. I tried gfortran -shared *.o -o libmysharedlibrary.so /usr/bin/ld: dxop.o: relocation R_X86_64_32 against `a local symbol' can not be used when making a shared object; recompile with -fPIC The message is pretty explicit: it is not compiled with -fPIC, there is nothing you can do, short of requesting a shared library from the software vendor. Well, I think one can make a static executable with C or Cython and embed the Python interpreter. But it is pretty complicated stuff, and requesting a shared library is vastly preferable. Dag Sverre Can you shed light on your approach ? Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Floating exception
On Thu, 21 Jan 2010 10:04:56 +0900 David Cournapeau da...@silveregg.co.jp wrote: Nils Wagner wrote: Hi all, I found a strange problem when I try to import numpy python -v import numpy ... dlopen(/data/home/nwagner/local/lib/python2.5/site-packages/numpy/core/multiarray.so, 2); Floating exception Any idea ? Could you get a traceback (ideally making sure numpy is built with debug symbols - having -g in both CFLAGS and LDFLAGS) ? Having it happening inside the dlopen call is a bit weird, I can't see what could cause it, cheers, David Hi David, Thank you for your response. I switched from CentOS 4.2 to CentOS 5.2 Here is the output of gdb python run -v # /data/home/nwagner/local/lib/python2.5/site-packages/site.pyc has bad magic ... What is the meaning of 'bad magic' ? Should I start with a clean /data/home/nwagner/local/lib/python2.5/site-packages ? Cheers, Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Floating exception
On Thu, 21 Jan 2010 23:35:29 +0900 David Cournapeau courn...@gmail.com wrote: On Thu, Jan 21, 2010 at 8:36 PM, Nils Wagner nwag...@iam.uni-stuttgart.de wrote: On Thu, 21 Jan 2010 10:04:56 +0900 David Cournapeau da...@silveregg.co.jp wrote: Nils Wagner wrote: Hi all, I found a strange problem when I try to import numpy python -v import numpy ... dlopen(/data/home/nwagner/local/lib/python2.5/site-packages/numpy/core/multiarray.so, 2); Floating exception Any idea ? Could you get a traceback (ideally making sure numpy is built with debug symbols - having -g in both CFLAGS and LDFLAGS) ? Having it happening inside the dlopen call is a bit weird, I can't see what could cause it, cheers, David Hi David, Thank you for your response. I switched from CentOS 4.2 to CentOS 5.2 Here is the output of gdb python run -v # /data/home/nwagner/local/lib/python2.5/site-packages/site.pyc has bad magic ... What is the meaning of 'bad magic' ? It seems that the bad magic is coming from python, which would most likely mean the site.pyc bytecode is not compatible with the run python. This is independent of your problem I think, David O.k. here is some more information ... # can't create /data/home/nwagner/local/lib/python2.5/site-packages/numpy/core/info.pyc dlopen(/data/home/nwagner/local/lib/python2.5/site-packages/numpy/core/multiarray.so, 2); Program received signal SIGFPE, Arithmetic exception. [Switching to Thread 182894183648 (LWP 22301)] 0x00350e8074d7 in do_lookup_x () from /lib64/ld-linux-x86-64.so.2 (gdb) bt #0 0x00350e8074d7 in do_lookup_x () from /lib64/ld-linux-x86-64.so.2 #1 0x00350e80789e in _dl_lookup_symbol_x () from /lib64/ld-linux-x86-64.so.2 #2 0x00350e808c70 in _dl_relocate_object () from /lib64/ld-linux-x86-64.so.2 #3 0x00350f7f7ac8 in dl_open_worker () from /lib64/tls/libc.so.6 #4 0x00350e80aab0 in _dl_catch_error () from /lib64/ld-linux-x86-64.so.2 #5 0x00350f7f845a in _dl_open () from /lib64/tls/libc.so.6 #6 0x00350fc01054 in dlopen_doit () from /lib64/libdl.so.2 Any idea ? Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] Floating exception
Hi all, I found a strange problem when I try to import numpy python -v import numpy ... dlopen(/data/home/nwagner/local/lib/python2.5/site-packages/numpy/core/multiarray.so, 2); Floating exception Any idea ? Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] svn log and blank entries
Hi all, An svn log CHANGELOG in svn/numpy yields some blank entries Is that intended ? r8055 | ariver | 2010-01-15 03:02:30 +0100 (Fr, 15 Jan 2010) | 1 line _ r8054 | ariver | 2010-01-15 02:57:56 +0100 (Fr, 15 Jan 2010) | 1 line _ r8053 | ariver | 2010-01-15 02:51:02 +0100 (Fr, 15 Jan 2010) | 1 line _ Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] ipython
Hi all, I tried to install ipython via bzr If I run iypthon I get ipython Traceback (most recent call last): File /home/nwagner/local/bin/ipython, line 4, in module from IPython.core.ipapp import launch_new_instance ImportError: No module named ipapp Any idea ? Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] numpy.test() failures
numpy.__version__ '1.5.0.dev7980' FAIL: test_buffer_hashlib (test_regression.TestRegression) -- Traceback (most recent call last): File /home/nwagner/local/lib64/python2.6/site-packages/numpy/core/tests/test_regression.py, line 1246, in test_buffer_hashlib assert_equal(md5(x).hexdigest(), '2a1dd1e1e59d0a384c26951e316cd7e6') File /home/nwagner/local/lib64/python2.6/site-packages/numpy/testing/utils.py, line 307, in assert_equal raise AssertionError(msg) AssertionError: Items are not equal: ACTUAL: 'aa341a15f5ade44faafbe190f98c2587' DESIRED: '2a1dd1e1e59d0a384c26951e316cd7e6' -- Ran 2485 tests in 14.328s FAILED (KNOWNFAIL=5, failures=1) nose.result.TextTestResult run=2485 errors=0 failures=1 ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] boolean arrays
Hi all, is the following behaviour correct a = array(([True,True],[True,True])) b = array(([False,False],[False,False])) a+b array([[ True, True], [ True, True]]) I have expected False. Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] boolean arrays
On Thu, 26 Nov 2009 15:14:04 +0100 Fabrice Silva si...@lma.cnrs-mrs.fr wrote: Le jeudi 26 novembre 2009 à 14:44 +0100, Gael Varoquaux a écrit : On Thu, Nov 26, 2009 at 02:43:14PM +0100, Fabrice Silva wrote: Le jeudi 26 novembre 2009 à 18:26 +0200, Nadav Horesh a écrit : It is obvious to me that True+False == True,. Why do you think it should be False? I would understand it is not obvious that '+' stands for logical 'or', and '*' for logical 'and'... In Bool's algebra, this is the common convention. The reason being that only 'or' can correspond to the additive law of an algebra: its null element is absorbant for 'and'. In other words, if you map '+' and '*' to the opposite, you'll get suprising behaviors. I fully agree with you. My point was to complete Nadav's comment with potentially missing information, trying to figrue why Nils was expected False... -- Fabrice Silva si...@lma.cnrs-mrs.fr LMA UPR CNRS 7051 Sorry, I mixed up '+' and '' a = array(([True,True],[True,True])) b = array(([False,False],[False,False])) a b array([[False, False], [False, False]], dtype=bool) Cheers, Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] NameError: global name 'matrix' is not defined
Ran 2235 tests in 25.593s FAILED (KNOWNFAIL=1, errors=28, failures=1) nose.result.TextTestResult run=2235 errors=28 failures=1 import numpy numpy.__version__ '1.4.0.dev7400' == ERROR: test_basic (test_defmatrix.TestAlgebra) -- Traceback (most recent call last): File /home/nwagner/local/lib64/python2.6/site-packages/numpy/core/tests/test_defmatrix.py, line 190, in test_basic mA = matrix(A) NameError: global name 'matrix' is not defined ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] NameError: global name 'matrix' is not defined
On Wed, 16 Sep 2009 11:41:15 -0500 Robert Kern robert.k...@gmail.com wrote: On Wed, Sep 16, 2009 at 11:39, Nils Wagnernwag...@iam.uni-stuttgart.de wrote: Ran 2235 tests in 25.593s FAILED (KNOWNFAIL=1, errors=28, failures=1) nose.result.TextTestResult run=2235 errors=28 failures=1 import numpy numpy.__version__ '1.4.0.dev7400' == ERROR: test_basic (test_defmatrix.TestAlgebra) -- Traceback (most recent call last): File /home/nwagner/local/lib64/python2.6/site-packages/numpy/core/tests/test_defmatrix.py, line 190, in test_basic mA = matrix(A) NameError: global name 'matrix' is not defined Clean out old files before reinstalling. -- Robert Kern Thank you very much. Works for me ... rm -rf /home/nwagner/local/lib64/python2.6/site-packages/numpy Ran 2196 tests in 16.713s OK (KNOWNFAIL=1) nose.result.TextTestResult run=2196 errors=0 failures=0 Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] Ticket 1216
Hi all, Ticket http://projects.scipy.org/numpy/ticket/1216 can be closed. Cheers, Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] DumbArray, LoadArray, Numeric -- numpy
Hi all, how can I import arrays in numpy which are stored by DumpArray in the old Numeric package ? Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] New test failures
numpy.__version__ '1.4.0.dev7270' Python 2.5.1 on 64-bit box == FAIL: test_umath.TestComplexFunctions.test_precisions_consistent -- Traceback (most recent call last): File /data/home/nwagner/local/lib/python2.5/site-packages/nose-0.10.4-py2.5.egg/nose/case.py, line 182, in runTest self.test(*self.arg) File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/core/tests/test_umath.py, line 545, in test_precisions_consistent assert_almost_equal(fcf, fcd, decimal=6, err_msg='fch-fcd %s'%f) File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/testing/utils.py, line 383, in assert_almost_equal DESIRED: %s\n % (str(actual), str(desired))) AssertionError: Items are not equal: ACTUAL: (0.666239+1.06128j) DESIRED: (0.666239432493+1.06127506191j) == FAIL: test_csingle (test_linalg.TestEig) -- Traceback (most recent call last): File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/linalg/tests/test_linalg.py, line 39, in test_csingle self.do(a, b) File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/linalg/tests/test_linalg.py, line 94, in do assert_almost_equal(dot(a, evectors), multiply(evectors, evalues)) File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/linalg/tests/test_linalg.py, line 23, in assert_almost_equal old_assert_almost_equal(a, b, decimal=decimal, **kw) File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/testing/utils.py, line 383, in assert_almost_equal DESIRED: %s\n % (str(actual), str(desired))) AssertionError: Items are not equal: ACTUAL: [[-0.28785625-0.21230127j 2.13664055+3.62986112j] [ 0.20296739+0.16528448j 4.73750353+6.42351294j]] DESIRED: [[-0.28785625-0.21230127j 2.13664031+3.62986112j] [ 0.20296741+0.16528448j 4.73750353+6.42351341j]] == FAIL: test_csingle (test_linalg.TestPinv) -- Traceback (most recent call last): File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/linalg/tests/test_linalg.py, line 39, in test_csingle self.do(a, b) File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/linalg/tests/test_linalg.py, line 124, in do assert_almost_equal(dot(a, a_ginv), identity(asarray(a).shape[0])) File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/linalg/tests/test_linalg.py, line 23, in assert_almost_equal old_assert_almost_equal(a, b, decimal=decimal, **kw) File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/testing/utils.py, line 383, in assert_almost_equal DESIRED: %s\n % (str(actual), str(desired))) AssertionError: Items are not equal: ACTUAL: [[ 1.0024e+00 +2.38418579e-07j -5.96046448e-08 +0.e+00j] [ 5.36441803e-07 +3.57627869e-07j 9.9821e-01 +0.e+00j]] DESIRED: [[ 1. 0.] [ 0. 1.]] == FAIL: test_csingle (test_linalg.TestSVD) -- Traceback (most recent call last): File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/linalg/tests/test_linalg.py, line 39, in test_csingle self.do(a, b) File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/linalg/tests/test_linalg.py, line 100, in do assert_almost_equal(a, dot(multiply(u, s), vt)) File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/linalg/tests/test_linalg.py, line 23, in assert_almost_equal old_assert_almost_equal(a, b, decimal=decimal, **kw) File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/testing/utils.py, line 383, in assert_almost_equal DESIRED: %s\n % (str(actual), str(desired))) AssertionError: Items are not equal: ACTUAL: [[ 1.+2.j 2.+3.j] [ 3.+4.j 4.+5.j]] DESIRED: [[ 1.0012+2.0024j 2.0024+3.0024j] [ 3.0048+4.0048j 4.0048+5.j]] -- Ran 2179 tests in 67.754s FAILED (KNOWNFAIL=1, failures=4) nose.result.TextTestResult run=2179 errors=0 failures=4 ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] numpy/core/code_generators/../src/multiarray/iterators.c:1778:could not find function name
Hi all,
I cannot build numpy from svn.
...
adding
'build/src.linux-x86_64-2.5/numpy/core/include/numpy/numpyconfig.h'
to sources.
executing numpy/core/code_generators/generate_numpy_api.py
numpy/core/code_generators/../src/multiarray/iterators.c
1778
Traceback (most recent call last):
File setup.py, line 186, in module
setup_package()
File setup.py, line 179, in setup_package
configuration=configuration )
File
/data/home/nwagner/svn/numpy/numpy/distutils/core.py,
line 184, in setup
return old_setup(**new_attr)
File
/data/home/nwagner/local/lib/python2.5/distutils/core.py,
line 151, in setup
dist.run_commands()
File
/data/home/nwagner/local/lib/python2.5/distutils/dist.py,
line 974, in run_commands
self.run_command(cmd)
File
/data/home/nwagner/local/lib/python2.5/distutils/dist.py,
line 994, in run_command
cmd_obj.run()
File
/data/home/nwagner/svn/numpy/numpy/distutils/command/install.py,
line 49, in run
r = old_install.run(self)
File
/data/home/nwagner/local/lib/python2.5/distutils/command/install.py,
line 506, in run
self.run_command('build')
File
/data/home/nwagner/local/lib/python2.5/distutils/cmd.py,
line 333, in run_command
self.distribution.run_command(command)
File
/data/home/nwagner/local/lib/python2.5/distutils/dist.py,
line 994, in run_command
cmd_obj.run()
File
/data/home/nwagner/svn/numpy/numpy/distutils/command/build.py,
line 37, in run
old_build.run(self)
File
/data/home/nwagner/local/lib/python2.5/distutils/command/build.py,
line 112, in run
self.run_command(cmd_name)
File
/data/home/nwagner/local/lib/python2.5/distutils/cmd.py,
line 333, in run_command
self.distribution.run_command(command)
File
/data/home/nwagner/local/lib/python2.5/distutils/dist.py,
line 994, in run_command
cmd_obj.run()
File
/data/home/nwagner/svn/numpy/numpy/distutils/command/build_src.py,
line 130, in run
self.build_sources()
File
/data/home/nwagner/svn/numpy/numpy/distutils/command/build_src.py,
line 147, in build_sources
self.build_extension_sources(ext)
File
/data/home/nwagner/svn/numpy/numpy/distutils/command/build_src.py,
line 250, in build_extension_sources
sources = self.generate_sources(sources, ext)
File
/data/home/nwagner/svn/numpy/numpy/distutils/command/build_src.py,
line 307, in generate_sources
source = func(extension, build_dir)
File numpy/core/setup.py, line 484, in generate_api
h_file, c_file, doc_file =
m.generate_api(os.path.join(build_dir, header_dir))
File
numpy/core/code_generators/generate_numpy_api.py, line
185, in generate_api
do_generate_api(targets, sources)
File
numpy/core/code_generators/generate_numpy_api.py, line
194, in do_generate_api
numpyapi_list = genapi.get_api_functions('NUMPY_API',
sources[0])
File numpy/core/code_generators/genapi.py, line 267,
in get_api_functions
functions.extend(find_functions(f, tagname))
File numpy/core/code_generators/genapi.py, line 220,
in find_functions
'could not find function name')
genapi.ParseError:
numpy/core/code_generators/../src/multiarray/iterators.c:1778:could
not find function name
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Re: [Numpy-discussion] numpy/core/code_generators/../src/multiarray/iterators.c:1778:could not find function name
On Tue, 21 Jul 2009 15:05:02 +0900 David Cournapeau da...@ar.media.kyoto-u.ac.jp wrote: Nils Wagner wrote: Hi all, I cannot build numpy from svn. Yes, I don't know why I did not caught this error on my machine. In any case, it is fixed in r7175. cheers, David Great. Works for me. Nils numpy.test() == ERROR: Failure: ImportError (No module named multiarray_tests) -- Traceback (most recent call last): File /data/home/nwagner/local/lib/python2.5/site-packages/nose-0.10.4-py2.5.egg/nose/loader.py, line 364, in loadTestsFromName addr.filename, addr.module) File /data/home/nwagner/local/lib/python2.5/site-packages/nose-0.10.4-py2.5.egg/nose/importer.py, line 39, in importFromPath return self.importFromDir(dir_path, fqname) File /data/home/nwagner/local/lib/python2.5/site-packages/nose-0.10.4-py2.5.egg/nose/importer.py, line 84, in importFromDir mod = load_module(part_fqname, fh, filename, desc) File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/core/tests/test_multiarray.py, line 7, in module from numpy.core.multiarray_tests import test_neighborhood_iterator ImportError: No module named multiarray_tests -- Ran 2028 tests in 10.917s FAILED (KNOWNFAIL=1, errors=1) ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] String manipulation
On Mon, 20 Jul 2009 12:44:23 -0700
Christopher Barker chris.bar...@noaa.gov wrote:
Nils Wagner wrote:
How can I split the second line in such a way that I get
['-1.00E+00', '-1.00E+00', '-1.00E+00',
'-1.00E+00', '1.25E+00', '1.25E+00']
instead of
['-1.00E+00-1.00E+00-1.00E+00-1.00E+00',
'1.25E+00', '1.25E+00']
It looks like you have fixed-length fields.
Yes. See
http://www.sdrl.uc.edu/universal-file-formats-for-modal-analysis-testing-1/file-format-storehouse/unv_0734.htm/
The naive
way do do this is simple string slicing:
def line2array1(line, field_len=10):
nums = []
i = 0
while i len(line):
nums.append(float(line[i:i+field_len]))
i += field_len
return np.array(nums)
Then I saw the nifty list comprehension posted by
Alan(?), which led me to the one (long) liner:
def line2array2(line, field_len=10):
return np.array(map(float,
[line[i*field_len:(i+1)*field_len] for i
in range(len(line)/field_len)]))
But it seems I should be able to do this using numpy
arrays manipulating the data as characters. However, I
had a little trouble getting a string into a numpy array
as characters. This didn't work:
In [55]: s
Out[55]:
'-1.00E+00-1.00E+00-1.00E+00-1.00E+00
1.25E+00 1.25E+00'
In [57]: np.array(s, 'S13')
Out[57]:
array('-1.00E+00',
dtype='|S13')
so I tried single characters:
In [56]: np.array(s, 'S1')
Out[56]:
array('-',
dtype='|S1')
I still only got the first one.
closer, but not quite:
In [61]: np.array(tuple(s), 'S13')
Out[61]:
array(['-', '1', '.', '0', '0', '0', '0', '0', '0', 'E',
'+', '0', '0',
'-', '1', '.', '0', '0', '0', '0', '0', '0', 'E',
'+', '0', '0',
'-', '1', '.', '0', '0', '0', '0', '0', '0', 'E',
'+', '0', '0',
'-', '1', '.', '0', '0', '0', '0', '0', '0', 'E',
'+', '0', '0',
' ', '1', '.', '2', '5', '0', '0', '0', '0', 'E',
'+', '0', '0',
' ', '1', '.', '2', '5', '0', '0', '0', '0', 'E',
'+', '0', '0'],
dtype='|S13')
So I ended up with this:
s_array = np.array(tuple(line),
dtype='S1').view(dtype='S%i'%field_len)
which seems uglier than it should be, but did lead so
this one-liner:
np.array(tuple(line),dtype='S1').view(dtype='S%i'%field_len).astype(np.float)
Is there a cleaner way to do this?
(test code attached)
-Chris
Fixed-length fields are quite common e.g. in the area of
Finite Element pre/postprocessing.
Therefore It would be nice to have a function like
line2array in numpy.
Comments ?
Nils
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Re: [Numpy-discussion] String manipulation
On Tue, 21 Jul 2009 02:56:28 -0400 Pierre GM pgmdevl...@gmail.com wrote: On Jul 21, 2009, at 2:42 AM, Nils Wagner wrote: Fixed-length fields are quite common e.g. in the area of Finite Element pre/postprocessing. Therefore It would be nice to have a function like line2array in numpy. Comments ? Er, there's already something like that: np.lib._iotools.LineSplitter Initialize it with either a character or an integer as delimiter, and call your instance with a string as input. When you use an integer as delimiter, it corresponds to the length of your field. eg: s = '-1.00E+00-1.00E+00 1.00E+00-1.00E+00' conv = np.lib._iotools.LineConverter(13) np.array(conv(s)) array(['-1.00E+00', '-1.00E+00', '1.00E+00', '-1.00E +00'], dtype='|S13') np.array([float(_) for _ in conv(s)]) array([-1., -1., 1., -1.]) Note that LineSplitter is already used in np.genfromtxt: import StringIO np.genfromtxt(StringIO.StringIO(s),delimiter=13) array([-1., -1., 1., -1.]) Great. I didn't know about that. Your examples are very useful. IMHO the examples should be added to http://www.scipy.org/Cookbook/InputOutput to attract interest. Nils ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] String manipulation
On Mon, 11 May 2009 10:48:14 -0400
Alan G Isaac ais...@american.edu wrote:
On 5/11/2009 8:36 AM Nils Wagner apparently wrote:
I would like to split strings made of digits after eight
characters each.
[l[i*8:(i+1)*8] for i in range(len(l)/8)]
Alan Isaac
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1.00E+00 0.00E+00 1.00E+00 1.00E+00
1.00E+00 1.00E+00
-1.00E+00-1.00E+00-1.00E+00-1.00E+00
1.25E+00 1.25E+00
ifile = open('mydata','r')
lines = ifile.readlines()
for line in lines:
print line.split()
How can I split the second line in such a way that I get
['-1.00E+00', '-1.00E+00', '-1.00E+00',
'-1.00E+00', '1.25E+00', '1.25E+00']
instead of
['-1.00E+00-1.00E+00-1.00E+00-1.00E+00',
'1.25E+00', '1.25E+00']
Thanks in advance
Nils
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[Numpy-discussion] Universal file format
Hi all, Is there a Python tool to read and write files in the so-called universal format ? I found a Matlab implementation http://www.mathworks.com/matlabcentral/fileexchange/6395 Any pointer would be appreciated. Thanks in advance Nils http://www.sdrl.uc.edu/universal-file-formats-for-modal-analysis-testing-1 http://zone.ni.com/devzone/cda/tut/p/id/4463 ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] roots and high-order polynomial
On Mon, 06 Jul 2009 16:53:42 +0200 Fabrice Silva si...@lma.cnrs-mrs.fr wrote: Le lundi 06 juillet 2009 à 08:16 -0600, Charles R Harris a écrit : Double precision breaks down at about degree 25 if things are well scaled, so that is suspicious in itself. Also, the companion matrix isn't Hermitean so that property of the roots isn't preserved by the algorithm. If it were Hermitian then eigh would be used instead of eig. That said, there are other ways of computing polynomial roots that might preserve the Hermitean property, but I don't know that that would solve your problem. I think there is a misunderstanding: I was referring to the fact the solution had to be real or complex conjugate, and not that the companion matrix would be a hermitian matrix (which it isn't due to its construction). IIRC, the coefficients of your polynomial are complex. So, you cannot guarantee that the roots are complex conjugate pairs. Nils Something I forgot to tell is that the roots are complex eigenfrequencies of a physical system, the real and imaginary parts expressing the damping and the frequency, respectively. If a positive frequency is solution then the opposite negative is solution too but with the «same-signed» damping. The problem is floating point round off error in representing the coefficients. Even if you know the coefficients exactly they can't generally be represented exactly in double precision. Any computational roundoff error just adds to that. If the coefficients were all integers I would have more confidence in the no error claim. Where do the coefficients come from? Perhaps there are options there. Here is the construction: the coefficients are obtained from a modal analysis of a subsystem of a bigger system. A quantity called impedance depending of a variable X is the result of the combination of several terms: Z(X) = C1/(X-X1)+C1*/(X-X1*)+...+CN/(X-XN)+CN*/(X-XN*) where * denotes the complex conjugate. I have to get the solutions X of an equation Ze(X)=N(X)/D(X) with N and D are very-low order polynomial (orders 1 and 2). An alternative of using iterative root finding (for example with scipy.optimize.fsolve) is to expand the equation as a polynomial of order close to 2N. I do understand this approach might seem non-obvious but it is rather efficient for a low value of N (10)... -- Fabrice Silva Laboratory of Mechanics and Acoustics - CNRS 31 chemin Joseph Aiguier, 13402 Marseille, France. ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] roots and high-order polynomial
On Fri, 03 Jul 2009 11:48:45 +0200 Fabrice Silva si...@lma.cnrs-mrs.fr wrote: Hello Has anyone looked at the behaviour of the (polynomial) roots function for high-order polynomials ? I have an application which internally searches for the roots of a polynomial. It works nicely for order less than 20, and then has an erratic behaviour for upper values... You will need multiprecision arithmetic in that case. It's an ill-conditioned problem. I looked into the source and I wondered that roots is based on the eigenvalues of the companion matrix. For high-order, this latter is rather sparse. Would it improve anything to compute the eigenvalues using sparse solvers? No. Cheers, Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] permutation symbol
On Tue, 30 Jun 2009 13:51:15 -0600
Charles R Harris charlesr.har...@gmail.com wrote:
On Tue, Jun 30, 2009 at 12:26 PM, Nils Wagner
nwag...@iam.uni-stuttgart.dewrote:
On Tue, 30 Jun 2009 11:10:39 -0600
Charles R Harris charlesr.har...@gmail.com wrote:
On Tue, Jun 30, 2009 at 10:56 AM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Tue, Jun 30, 2009 at 10:40 AM, Nils Wagner
nwag...@iam.uni-stuttgart.de wrote:
On Tue, 30 Jun 2009 10:27:05 -0600
Charles R Harris charlesr.har...@gmail.com wrote:
On Tue, Jun 30, 2009 at 5:11 AM, Nils Wagner
nwag...@iam.uni-stuttgart.dewrote:
On Tue, 30 Jun 2009 11:22:34 +0200
Nils Wagner nwag...@iam.uni-stuttgart.de
wrote:
Hi all,
How can I build the following product with numpy
q_i = \varepsilon_{ijk} q_{kj}
where \varepsilon_{ijk} denotes the permutation
symbol.
Nils
Sorry for replying to myself.
The permutation symbol is also known as the
Levi-Civita
symbol.
I found an explicit expression at
http://en.wikipedia.org/wiki/Levi-Civita_symbol
How do I build the product of the Levi-Civita
symbol
\varepsilon_{ijk} and
the two dimensional array
q_{kj}, i,j,k = 1,2,3 ?
Write it out explicitly. It essentially
antisymmetrizes
q and the three off
diagonal elements can then be treated as a vector.
Depending on how q is
formed and the resulting vector is used there may
be
other things you can do
when you use it in a more general expression. If
this
is
part of a general
calculation there might be other ways of
expressing
it.
Chuck
Hi Chuck,
Thank you for your response.
The problem at hand is described in a paper by
Angeles
namely equation (17c) in
Automatic computation of the screw parameters of
rigid-body motions.
Part I: Finitely-separated positions
Journal of Dynamic systems, Measurement and Control,
Vol.
108 (1986) pp. 32-38
You can solve this problem using quaternions also, in
which case it reduces
to an eigenvalue problem. You will note that such
things
as PCA are used in
the papers that reference the cited work so you can't
really get around that
bit of inefficiency.
Here's a reference to the quaternion approach:
http://people.csail.mit.edu/bkph/papers/Absolute_Orientation.pdf.
You can
get the translation part from the motion of the
centroid.
If you are into abstractions you will note that the
problem reduces to
minimising a quadratic form in the quaternion
components. The rest is just
algebra ;)
Chuck
It turns out that the product is simply an invariant of
a
3 \times 3 matrix.
from numpy import array, zeros, identity
from numpy.linalg import norm
def vect(A):
linear invariant of a 3 x 3 matrix
tmp = zeros(3,float)
tmp[0] = 0.5*(A[2,1]-A[1,2])
tmp[1] = 0.5*(A[0,2]-A[2,0])
tmp[2] = 0.5*(A[1,0]-A[0,1])
return tmp
Out of curiosity, where did the .5 come from? It is not
normally part of the
Levi-Civita symbol.
Chuck
Hi Chuck,
It's my fault. The components of the invariant q are given
by
q_i = 0.5 \varepsilon_{ijk} q_{kj}
Nils
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[Numpy-discussion] make html
Hi all, I am using numpy.__version__ '1.4.0.dev7094' make html yields /home/nwagner/svn/numpy/doc/source/reference/generated/numpy.trunc.rst:: WARNING: document isn't included in any toctree done preparing documents... done Exception occurred: 2%] reference/generalized_ufuncs ures File /home/nwagner/local/lib64/python2.6/site-packages/Sphinx-0.6.1-py2.6.egg/sphinx/environment.py, line 921, in get_toc_for toc = self.tocs[docname].deepcopy() KeyError: 'reference/generalized_ufuncs' The full traceback has been saved in /tmp/sphinx-err-wlA8vA.log, if you want to report the issue to the author. Please also report this if it was a user error, so that a better error message can be provided next time. Send reports to sphinx-...@googlegroups.com. Thanks! make: *** [html] Fehler 1 Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] permutation symbol
Hi all,
How can I build the following product with numpy
q_i = \varepsilon_{ijk} q_{kj}
where \varepsilon_{ijk} denotes the permutation symbol.
Nils
http://mathworld.wolfram.com/PermutationSymbol.html
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Re: [Numpy-discussion] permutation symbol
On Tue, 30 Jun 2009 11:22:34 +0200
Nils Wagner nwag...@iam.uni-stuttgart.de wrote:
Hi all,
How can I build the following product with numpy
q_i = \varepsilon_{ijk} q_{kj}
where \varepsilon_{ijk} denotes the permutation symbol.
Nils
Sorry for replying to myself.
The permutation symbol is also known as the Levi-Civita
symbol.
I found an explicit expression at
http://en.wikipedia.org/wiki/Levi-Civita_symbol
How do I build the product of the Levi-Civita symbol
\varepsilon_{ijk} and the two dimensional array
q_{kj}, i,j,k = 1,2,3 ?
Nils
from numpy import zeros
def levi_civita():
Levi-Civita symbol
http://en.wikipedia.org/wiki/Levi-Civita_symbol
eps = zeros((3,3,3),float)
for i in range(1,4):
for j in range(1,4):
for k in range(1,4):
eps[i-1,j-1,k-1] = -((i-j)**2%3)*((i-k)**2%3)*((j-k)**2%3)*((j-(i%3)-0.5)**2-5/4.)
return eps.astype(int)
eps = levi_civita()
print eps
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Re: [Numpy-discussion] permutation symbol
On Tue, 30 Jun 2009 10:27:05 -0600
Charles R Harris charlesr.har...@gmail.com wrote:
On Tue, Jun 30, 2009 at 5:11 AM, Nils Wagner
nwag...@iam.uni-stuttgart.dewrote:
On Tue, 30 Jun 2009 11:22:34 +0200
Nils Wagner nwag...@iam.uni-stuttgart.de wrote:
Hi all,
How can I build the following product with numpy
q_i = \varepsilon_{ijk} q_{kj}
where \varepsilon_{ijk} denotes the permutation symbol.
Nils
Sorry for replying to myself.
The permutation symbol is also known as the Levi-Civita
symbol.
I found an explicit expression at
http://en.wikipedia.org/wiki/Levi-Civita_symbol
How do I build the product of the Levi-Civita symbol
\varepsilon_{ijk} and
the two dimensional array
q_{kj}, i,j,k = 1,2,3 ?
Write it out explicitly. It essentially antisymmetrizes
q and the three off
diagonal elements can then be treated as a vector.
Depending on how q is
formed and the resulting vector is used there may be
other things you can do
when you use it in a more general expression. If this is
part of a general
calculation there might be other ways of expressing it.
Chuck
Hi Chuck,
Thank you for your response.
The problem at hand is described in a paper by Angeles
namely equation (17c) in
Automatic computation of the screw parameters of
rigid-body motions.
Part I: Finitely-separated positions
Journal of Dynamic systems, Measurement and Control, Vol.
108 (1986) pp. 32-38
I am looking for a pythonic implementation of the
algorithm.
Nils
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Re: [Numpy-discussion] permutation symbol
On Tue, 30 Jun 2009 11:10:39 -0600
Charles R Harris charlesr.har...@gmail.com wrote:
On Tue, Jun 30, 2009 at 10:56 AM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Tue, Jun 30, 2009 at 10:40 AM, Nils Wagner
nwag...@iam.uni-stuttgart.de wrote:
On Tue, 30 Jun 2009 10:27:05 -0600
Charles R Harris charlesr.har...@gmail.com wrote:
On Tue, Jun 30, 2009 at 5:11 AM, Nils Wagner
nwag...@iam.uni-stuttgart.dewrote:
On Tue, 30 Jun 2009 11:22:34 +0200
Nils Wagner nwag...@iam.uni-stuttgart.de wrote:
Hi all,
How can I build the following product with numpy
q_i = \varepsilon_{ijk} q_{kj}
where \varepsilon_{ijk} denotes the permutation
symbol.
Nils
Sorry for replying to myself.
The permutation symbol is also known as the
Levi-Civita
symbol.
I found an explicit expression at
http://en.wikipedia.org/wiki/Levi-Civita_symbol
How do I build the product of the Levi-Civita symbol
\varepsilon_{ijk} and
the two dimensional array
q_{kj}, i,j,k = 1,2,3 ?
Write it out explicitly. It essentially
antisymmetrizes
q and the three off
diagonal elements can then be treated as a vector.
Depending on how q is
formed and the resulting vector is used there may be
other things you can do
when you use it in a more general expression. If this
is
part of a general
calculation there might be other ways of expressing
it.
Chuck
Hi Chuck,
Thank you for your response.
The problem at hand is described in a paper by Angeles
namely equation (17c) in
Automatic computation of the screw parameters of
rigid-body motions.
Part I: Finitely-separated positions
Journal of Dynamic systems, Measurement and Control,
Vol.
108 (1986) pp. 32-38
You can solve this problem using quaternions also, in
which case it reduces
to an eigenvalue problem. You will note that such things
as PCA are used in
the papers that reference the cited work so you can't
really get around that
bit of inefficiency.
Here's a reference to the quaternion approach:
http://people.csail.mit.edu/bkph/papers/Absolute_Orientation.pdf.
You can
get the translation part from the motion of the
centroid.
If you are into abstractions you will note that the
problem reduces to
minimising a quadratic form in the quaternion
components. The rest is just
algebra ;)
Chuck
It turns out that the product is simply an invariant of a
3 \times 3 matrix.
from numpy import array, zeros, identity
from numpy.linalg import norm
def vect(A):
linear invariant of a 3 x 3 matrix
tmp = zeros(3,float)
tmp[0] = 0.5*(A[2,1]-A[1,2])
tmp[1] = 0.5*(A[0,2]-A[2,0])
tmp[2] = 0.5*(A[1,0]-A[0,1])
return tmp
Q = array([[0,0,-1],[-1,0,0],[0,1,0]])
q = vect(Q)
print q
Nils
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Re: [Numpy-discussion] permutation symbol
On Tue, 30 Jun 2009 11:30:51 -0700 (PDT) David Goldsmith d_l_goldsm...@yahoo.com wrote: Great, Nils! Now, can you generalize it to N-D for us? ;-) DG Just curious - Do you have any application for N-D case in mind ? Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] Test bug in reduceat with structured arrays copied for speed.
Hi all, Is this a known failure ? I am using 1.4.0.dev7069 == FAIL: Test bug in reduceat with structured arrays copied for speed. -- Traceback (most recent call last): File /data/home/nwagner/local/lib/python2.5/site-packages/nose-0.10.4-py2.5.egg/nose/case.py, line 182, in runTest self.test(*self.arg) File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/core/tests/test_umath.py, line 700, in test_reduceat assert_array_almost_equal(h1, h2) File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/testing/utils.py, line 537, in assert_array_almost_equal header='Arrays are not almost equal') File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/testing/utils.py, line 395, in assert_array_compare raise AssertionError(msg) AssertionError: Arrays are not almost equal (mismatch 100.0%) x: array([ 4.61621844e+24, 4.61621844e+24, 4.61621844e+24, 4.61621844e+24], dtype=float32) y: array([ 700., 800., 1000., 7500.], dtype=float32) -- Ran 2065 tests in 200.909s FAILED (KNOWNFAIL=1, failures=1) Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] numpy port to Jython
Hi all, Is there a port of numpy/scipy to Jython ? Any pointer would be appreciated. Thanks in advance Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] numpy port to Jython
On Wed, 17 Jun 2009 15:00:23 -0400 David Warde-Farley d...@cs.toronto.edu wrote: On 17-Jun-09, at 2:18 PM, Nils Wagner wrote: Is there a port of numpy/scipy to Jython ? Any pointer would be appreciated. Folks have successfully gotten it working from IronPython (the .NET CLR) via Ironclad ( http://code.google.com/p/ironclad/ )... not Jython though. David David, Thank you for your reply. Unfortunately, Ironclad currently only works on 32-bit Windows ... Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] skiprows option in loadtxt
Hi all, Is the value of skiprows in loadtxt restricted to values in [0-10] ? It doesn't work for skiprows=11. Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] skiprows option in loadtxt
On Wed, 20 May 2009 10:16:08 -0500 Ryan May rma...@gmail.com wrote: On Wed, May 20, 2009 at 10:04 AM, Nils Wagner nwag...@iam.uni-stuttgart.dewrote: Hi all, Is the value of skiprows in loadtxt restricted to values in [0-10] ? It doesn't work for skiprows=11. Works for me: s = '\n'.join(map(str,range(20))) from StringIO import StringIO np.loadtxt(StringIO(s), skiprows=11) The last line yields, as expected: array([ 11., 12., 13., 14., 15., 16., 17., 18., 19.]) This is with 1.4.0.dev6983. Can we see code and data file? Ryan -- Ryan May Graduate Research Assistant School of Meteorology University of Oklahoma Sent from Norman, Oklahoma, United States Hi all, My fault. Sorry for the noise. Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] linear algebra help
On Sat, 16 May 2009 16:01:00 +0300 Quilby qui...@gmail.com wrote: Hi- This is what I need to do- I have this equation- Ax = y Where A is a rational m*n matrix (m=n), and x and y are vectors of the right size. I know A and y, I don't know what x is equal to. I also know that there is no x where Ax equals exactly y. I want to find the vector x' such that Ax' is as close as possible to y. Meaning that (Ax' - y) is as close as possible to (0,0,0,...0). I know that I need to use either the lstsq function: http://www.scipy.org/doc/numpy_api_docs/numpy.linalg.linalg.html#lstsq or the svd function: http://www.scipy.org/doc/numpy_api_docs/numpy.linalg.linalg.html#svd I don't understand the documentation at all. Can someone please show me how to use these functions to solve my problem. Thanks a lot!!! -quilby ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion I guess you meant a rectangular matrix http://mathworld.wolfram.com/RectangularMatrix.html from numpy.random import rand, seed from numpy import dot, shape from numpy.linalg import lstsq, norm seed(1) m = 10 n = 20 A = rand(m,n) # random matrix b = rand(m) # rhs x,residues,rank,s = lstsq(A,b) print 'Singular values',s print 'Numerical rank of A',rank print 'Solution',x r=dot(A,x)-b print 'residual',norm(r) Cheers, Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] List of arrays
Hi all, How can I convert a list of arrays into one array ? Nils data [array([ 40. , 285.6, 45. , 285.3, 50. , 285.1, 55. , 284.8]), array([ 60. , 284.5, 65. , 282.8, 70. , 281.1, 75. , 280. ]), array([ 80. , 278.8, 85. , 278.1, 90. , 277.4, 95. , 276.9]), array([ 100. , 276.3, 105. , 276.1, 110. , 275.9, 115. , 275.7]), array([ 120. , 275.5, 125. , 275.2, 130. , 274.8, 135. , 274.5]), array([ 140. , 274.1, 145. , 273.7, 150. , 273.2, 155. , 272.7]), array([ 160. , 272.2, 165. , 272.1, 170. , 272. , 175. , 271.8]), array([ 180. , 271.6, 185. , 271. , 190. , 270.3, 195. , 269.5]), array([ 200. , 268.5, 205. , 267.4, 210. , 266.1, 215. , 263.5]), array([ 220. , 260.1, 225. , 256.1, 230. , 249.9, 235. , 239.3]), array([ 238.7, 186.2, 240., 160. , 245. , 119.7, 250. , 111.3])] newdata=array([ 40. , 285.6, 45. , 285.3, 50. , 285.1, 55. , 284.8, 60. , 284.5, 65. , 282.8, ..., 111.3]) Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] List of arrays
On Mon, 11 May 2009 06:54:45 -0400 Alan G Isaac ais...@american.edu wrote: On 5/11/2009 6:28 AM Nils Wagner apparently wrote: How can I convert a list of arrays into one array ? Do you mean one long array, so that ``concatenate`` is appropriate, or a 2d array, in which case you can just use ``array``. But your example looks like you should preallocate the larger array and fill it as the data arrive, if that's possible. Alan Isaac Hi Alan, concatenate works fine for me. The problem is that the arrays within the list vary in length. Thank you very much. Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] String manipulation
Hi all, Please consider two strings line_a '12345678abcdefgh12345678' line_b '12345678 abcdefgh 12345678' line_b.split() ['12345678', 'abcdefgh', '12345678'] Is it possible to split line_a such that the output is ['12345678', 'abcdefgh', '12345678'] Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] FAIL: Test bug in reduceat with structured arrays
Hi all, Can someone reproduce the following failure ? I am using numpy.__version__ '1.4.0.dev6983' == FAIL: Test bug in reduceat with structured arrays copied for speed. -- Traceback (most recent call last): File /data/home/nwagner/local/lib/python2.5/site-packages/nose-0.10.4-py2.5.egg/nose/case.py, line 182, in runTest self.test(*self.arg) File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/core/tests/test_umath.py, line 664, in test_reduceat assert np.all(h1 == h2) AssertionError Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] String manipulation
On Mon, 11 May 2009 14:25:46 +0200 Francesc Alted fal...@pytables.org wrote: A Monday 11 May 2009, Nils Wagner escrigué: Hi all, Please consider two strings line_a '12345678abcdefgh12345678' line_b '12345678 abcdefgh 12345678' line_b.split() ['12345678', 'abcdefgh', '12345678'] Is it possible to split line_a such that the output is ['12345678', 'abcdefgh', '12345678'] Mmh, your question is a bit too generic. Indeed. I would like to split strings made of digits after eight characters each. line_a '11.122.233.3' line_b '11.1 22.2 33.3' line_b.split() ['11.1', '22.2', '33.3'] How can I accomplish that ? Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] FAIL: Test bug in reduceat with structured arrays
On Mon, 11 May 2009 14:05:13 + (UTC) Pauli Virtanen p...@iki.fi wrote: Mon, 11 May 2009 14:06:07 +0200, Nils Wagner kirjoitti: Can someone reproduce the following failure ? I am using numpy.__version__ '1.4.0.dev6983' == FAIL: Test bug in reduceat with structured arrays copied for speed. -- [clip] Buildbot can't. I'd suggest removing your build/ directory and rebuilding, to see if it's caused by some file not rebuilding properly. Otherwise, what is the platform you are using? -- Pauli Virtanen Everytime I rebuild numpy I remove the build directory before. CentOS release 4.6 x86_64 Python 2.5.1 Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] cannot build numpy from trunk
... In file included from numpy/core/src/multiarray/ctors.c:16, from numpy/core/src/multiarray/multiarraymodule_onefile.c:13: numpy/core/src/multiarray/ctors.h: At top level: numpy/core/src/multiarray/ctors.h:68: warning: conflicting types for byte_swap_vector numpy/core/src/multiarray/ctors.h:68: error: static declaration of byte_swap_vector follows non-static declaration numpy/core/src/multiarray/scalarapi.c:640: error: previous implicit declaration of byte_swap_vector was here error: Command /usr/bin/gcc -fno-strict-aliasing -DNDEBUG -fmessage-length=0 -O2 -Wall -D_FORTIFY_SOURCE=2 -fstack-protector -funwind-tables -fasynchronous-unwind-tables -g -fwrapv -fPIC -Inumpy/core/include -Ibuild/src.linux-x86_64-2.6/numpy/core/include/numpy -Inumpy/core/src/multiarray -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6 -Ibuild/src.linux-x86_64-2.6/numpy/core/src/multiarray -Ibuild/src.linux-x86_64-2.6/numpy/core/src/umath -c numpy/core/src/multiarray/multiarraymodule_onefile.c -o build/temp.linux-x86_64-2.6/numpy/core/src/multiarray/multiarraymodule_onefile.o failed with exit status 1 Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] cannot build numpy from trunk
On Tue, 5 May 2009 10:04:11 -0600 Charles R Harris charlesr.har...@gmail.com wrote: On Tue, May 5, 2009 at 9:50 AM, Nils Wagner nwag...@iam.uni-stuttgart.dewrote: ... In file included from numpy/core/src/multiarray/ctors.c:16, from numpy/core/src/multiarray/multiarraymodule_onefile.c:13: numpy/core/src/multiarray/ctors.h: At top level: numpy/core/src/multiarray/ctors.h:68: warning: conflicting types for ‘byte_swap_vector’ numpy/core/src/multiarray/ctors.h:68: error: static declaration of ‘byte_swap_vector’ follows non-static declaration numpy/core/src/multiarray/scalarapi.c:640: error: previous implicit declaration of ‘byte_swap_vector’ was here error: Command /usr/bin/gcc -fno-strict-aliasing -DNDEBUG -fmessage-length=0 -O2 -Wall -D_FORTIFY_SOURCE=2 -fstack-protector -funwind-tables -fasynchronous-unwind-tables -g -fwrapv -fPIC -Inumpy/core/include -Ibuild/src.linux-x86_64-2.6/numpy/core/include/numpy -Inumpy/core/src/multiarray -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6 -Ibuild/src.linux-x86_64-2.6/numpy/core/src/multiarray -Ibuild/src.linux-x86_64-2.6/numpy/core/src/umath -c numpy/core/src/multiarray/multiarraymodule_onefile.c -o build/temp.linux-x86_64-2.6/numpy/core/src/multiarray/multiarraymodule_onefile.o failed with exit status 1 What happens if you delete the build directory first? Chuck I have done that before ;-) Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] cannot build numpy from trunk
On Tue, 5 May 2009 12:44:31 -0600 Charles R Harris charlesr.har...@gmail.com wrote: On Tue, May 5, 2009 at 10:12 AM, Nils Wagner nwag...@iam.uni-stuttgart.dewrote: On Tue, 5 May 2009 10:04:11 -0600 Charles R Harris charlesr.har...@gmail.com wrote: On Tue, May 5, 2009 at 9:50 AM, Nils Wagner nwag...@iam.uni-stuttgart.dewrote: ... In file included from numpy/core/src/multiarray/ctors.c:16, from numpy/core/src/multiarray/multiarraymodule_onefile.c:13: numpy/core/src/multiarray/ctors.h: At top level: numpy/core/src/multiarray/ctors.h:68: warning: conflicting types for ‘byte_swap_vector’ numpy/core/src/multiarray/ctors.h:68: error: static declaration of ‘byte_swap_vector’ follows non-static declaration numpy/core/src/multiarray/scalarapi.c:640: error: previous implicit declaration of ‘byte_swap_vector’ was here error: Command /usr/bin/gcc -fno-strict-aliasing -DNDEBUG -fmessage-length=0 -O2 -Wall -D_FORTIFY_SOURCE=2 -fstack-protector -funwind-tables -fasynchronous-unwind-tables -g -fwrapv -fPIC -Inumpy/core/include -Ibuild/src.linux-x86_64-2.6/numpy/core/include/numpy -Inumpy/core/src/multiarray -Inumpy/core/src/umath -Inumpy/core/include -I/usr/include/python2.6 -Ibuild/src.linux-x86_64-2.6/numpy/core/src/multiarray -Ibuild/src.linux-x86_64-2.6/numpy/core/src/umath -c numpy/core/src/multiarray/multiarraymodule_onefile.c -o build/temp.linux-x86_64-2.6/numpy/core/src/multiarray/multiarraymodule_onefile.o failed with exit status 1 What happens if you delete the build directory first? Chuck I have done that before ;-) Is this from the latest svn? Chuck r6955 | cdavid | 2009-05-05 13:10:29 +0200 (Di, 05. Mai 2009) | 1 line Put buffer protocol in separate file. Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] stop criterion for an alternating signal
Hi all,
How can I define a stop criterion for an alternating
series ?
Any pointer would be appreciated.
Nils
from numpy import loadtxt, arange
from pylab import plot, show
A = loadtxt('alternate.dat')
m = len(A)
x = arange(0,m)
plot(x,A)
show()
alternate.dat
Description: MPEG movie
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Re: [Numpy-discussion] stop criterion for an alternating signal
On Mon, 4 May 2009 10:52:59 -0600 Charles R Harris charlesr.har...@gmail.com wrote: On Mon, May 4, 2009 at 10:48 AM, Nils Wagner nwag...@iam.uni-stuttgart.dewrote: Hi all, How can I define a stop criterion for an alternating series ? Any pointer would be appreciated. Where does the series come from and what are you trying to do? Chuck The data come from an iterative process. I am looking for convergence criteria. It should be possible to stop the process after 10-15 iterations. Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] String manipulation
Hi all, How can I obtain the position of the minus sign within the following string ? liste[1] '1.5-te' Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] numpy.test() errors r6862
On Sun, 12 Apr 2009 12:56:46 -0600
Charles R Harris charlesr.har...@gmail.com wrote:
On Sun, Apr 12, 2009 at 12:52 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Sun, Apr 12, 2009 at 12:17 PM, Nils Wagner
nwag...@iam.uni-stuttgart.de wrote:
==
ERROR: test suite
--
Traceback (most recent call last):
File
/home/nwagner/local/lib64/python2.6/site-packages/nose-0.10.4-py2.6.egg/nose/suite.py,
line 154, in run
self.setUp()
File
/home/nwagner/local/lib64/python2.6/site-packages/nose-0.10.4-py2.6.egg/nose/suite.py,
line 180, in setUp
if not self:
File
/home/nwagner/local/lib64/python2.6/site-packages/nose-0.10.4-py2.6.egg/nose/suite.py,
line 65, in __nonzero__
test = self.test_generator.next()
File
/home/nwagner/local/lib64/python2.6/site-packages/nose-0.10.4-py2.6.egg/nose/loader.py,
line 221, in generate
for test in g():
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/lib/tests/test_format.py,
line 440, in test_memmap_roundtrip
shape=arr.shape, fortran_order=fortran_order)
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/lib/format.py,
line 484, in open_memmap
mode=mode, offset=offset)
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/core/memmap.py,
line 231, in __new__
mm = mmap.mmap(fid.fileno(), bytes, access=acc,
offset=offset)
error: [Errno 22] Invalid argument
==
ERROR: test_mmap (test_io.TestSaveLoad)
--
Traceback (most recent call last):
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/testing/decorators.py,
line 169, in knownfailer
return f(*args, **kwargs)
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/lib/tests/test_io.py,
line 92, in test_mmap
self.roundtrip(a, file_on_disk=True,
load_kwds={'mmap_mode': 'r'})
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/lib/tests/test_io.py,
line 100, in roundtrip
RoundtripTest.roundtrip(self, np.save, *args,
**kwargs)
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/lib/tests/test_io.py,
line 67, in roundtrip
arr_reloaded = np.load(load_file, **load_kwds)
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/lib/io.py,
line 193, in load
return format.open_memmap(file, mode=mmap_mode)
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/lib/format.py,
line 484, in open_memmap
mode=mode, offset=offset)
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/core/memmap.py,
line 231, in __new__
mm = mmap.mmap(fid.fileno(), bytes, access=acc,
offset=offset)
error: [Errno 22] Invalid argument
--
Ran 1889 tests in 12.656s
FAILED (KNOWNFAIL=1, errors=2)
Hmm, I'll guess that the problem is this:
*offset* must be a multiple of the
ALLOCATIONGRANULARITY.
This conflicts with the current intent of offset. Looks
like we need to fix
up the patch to use the nearest multiple of
ALLOCATIONGRANULARITY and then
offset the usual way. Or, since ALLOCATIONGRANULARITY is
likely to be
platform dependent, maybe we should just revert the
patch.
Can you import mmap, then do a dir(mmap) and see if
ALLOCATIONGRANULARITY
is available?
TIA,
Chuck
Hi Chuck,
import mmap
dir (mmap)
['ACCESS_COPY', 'ACCESS_READ', 'ACCESS_WRITE',
'ALLOCATIONGRANULARITY', 'MAP_ANON', 'MAP_ANONYMOUS',
'MAP_DENYWRITE', 'MAP_EXECUTABLE', 'MAP_PRIVATE',
'MAP_SHARED', 'PAGESIZE', 'PROT_EXEC', 'PROT_READ',
'PROT_WRITE', '__doc__', '__file__', '__name__',
'__package__', 'error', 'mmap']
All tests pass with '1.4.0.dev6864'. Thank you very much.
Cheers,
Nils
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[Numpy-discussion] survey of freely available software for the solution of linear algebra problems
FWIW, From: Jack Dongarra donga...@cs.utk.edu Date: Tue, 7 Apr 2009 12:00:01 -0400 Subject: Survey of linear algebra software We have updated the survey of freely available software for the solution of linear algebra problems. Send us comments if you see a problem. http://www.netlib.org/utk/people/JackDongarra/la-sw.html Regards, Jack and Hatem ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] numpy.test() errors r6862
==
ERROR: test suite
--
Traceback (most recent call last):
File
/home/nwagner/local/lib64/python2.6/site-packages/nose-0.10.4-py2.6.egg/nose/suite.py,
line 154, in run
self.setUp()
File
/home/nwagner/local/lib64/python2.6/site-packages/nose-0.10.4-py2.6.egg/nose/suite.py,
line 180, in setUp
if not self:
File
/home/nwagner/local/lib64/python2.6/site-packages/nose-0.10.4-py2.6.egg/nose/suite.py,
line 65, in __nonzero__
test = self.test_generator.next()
File
/home/nwagner/local/lib64/python2.6/site-packages/nose-0.10.4-py2.6.egg/nose/loader.py,
line 221, in generate
for test in g():
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/lib/tests/test_format.py,
line 440, in test_memmap_roundtrip
shape=arr.shape, fortran_order=fortran_order)
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/lib/format.py,
line 484, in open_memmap
mode=mode, offset=offset)
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/core/memmap.py,
line 231, in __new__
mm = mmap.mmap(fid.fileno(), bytes, access=acc,
offset=offset)
error: [Errno 22] Invalid argument
==
ERROR: test_mmap (test_io.TestSaveLoad)
--
Traceback (most recent call last):
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/testing/decorators.py,
line 169, in knownfailer
return f(*args, **kwargs)
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/lib/tests/test_io.py,
line 92, in test_mmap
self.roundtrip(a, file_on_disk=True,
load_kwds={'mmap_mode': 'r'})
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/lib/tests/test_io.py,
line 100, in roundtrip
RoundtripTest.roundtrip(self, np.save, *args,
**kwargs)
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/lib/tests/test_io.py,
line 67, in roundtrip
arr_reloaded = np.load(load_file, **load_kwds)
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/lib/io.py,
line 193, in load
return format.open_memmap(file, mode=mmap_mode)
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/lib/format.py,
line 484, in open_memmap
mode=mode, offset=offset)
File
/home/nwagner/local/lib64/python2.6/site-packages/numpy/core/memmap.py,
line 231, in __new__
mm = mmap.mmap(fid.fileno(), bytes, access=acc,
offset=offset)
error: [Errno 22] Invalid argument
--
Ran 1889 tests in 12.656s
FAILED (KNOWNFAIL=1, errors=2)
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[Numpy-discussion] cannot build numpy from trunk
Hi all, I cannot build numpy from trunk compile options: '-Inumpy/core/src -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 /usr/bin/gcc _configtest.o -o _configtest _configtest.o: In function `main': /home/nwagner/svn/numpy/_configtest.c:44: undefined reference to `sin' /home/nwagner/svn/numpy/_configtest.c:45: undefined reference to `cos' /home/nwagner/svn/numpy/_configtest.c:46: undefined reference to `tan' /home/nwagner/svn/numpy/_configtest.c:47: undefined reference to `sinh' /home/nwagner/svn/numpy/_configtest.c:48: undefined reference to `cosh' /home/nwagner/svn/numpy/_configtest.c:49: undefined reference to `tanh' /home/nwagner/svn/numpy/_configtest.c:50: undefined reference to `fabs' /home/nwagner/svn/numpy/_configtest.c:51: undefined reference to `floor' /home/nwagner/svn/numpy/_configtest.c:52: undefined reference to `ceil' /home/nwagner/svn/numpy/_configtest.c:53: undefined reference to `sqrt' /home/nwagner/svn/numpy/_configtest.c:54: undefined reference to `log10' /home/nwagner/svn/numpy/_configtest.c:55: undefined reference to `log' /home/nwagner/svn/numpy/_configtest.c:56: undefined reference to `exp' /home/nwagner/svn/numpy/_configtest.c:57: undefined reference to `asin' /home/nwagner/svn/numpy/_configtest.c:58: undefined reference to `acos' /home/nwagner/svn/numpy/_configtest.c:59: undefined reference to `atan' /home/nwagner/svn/numpy/_configtest.c:60: undefined reference to `fmod' collect2: ld returned 1 exit status _configtest.o: In function `main': /home/nwagner/svn/numpy/_configtest.c:44: undefined reference to `sin' /home/nwagner/svn/numpy/_configtest.c:45: undefined reference to `cos' /home/nwagner/svn/numpy/_configtest.c:46: undefined reference to `tan' /home/nwagner/svn/numpy/_configtest.c:47: undefined reference to `sinh' /home/nwagner/svn/numpy/_configtest.c:48: undefined reference to `cosh' /home/nwagner/svn/numpy/_configtest.c:49: undefined reference to `tanh' /home/nwagner/svn/numpy/_configtest.c:50: undefined reference to `fabs' /home/nwagner/svn/numpy/_configtest.c:51: undefined reference to `floor' /home/nwagner/svn/numpy/_configtest.c:52: undefined reference to `ceil' /home/nwagner/svn/numpy/_configtest.c:53: undefined reference to `sqrt' /home/nwagner/svn/numpy/_configtest.c:54: undefined reference to `log10' /home/nwagner/svn/numpy/_configtest.c:55: undefined reference to `log' /home/nwagner/svn/numpy/_configtest.c:56: undefined reference to `exp' /home/nwagner/svn/numpy/_configtest.c:57: undefined reference to `asin' /home/nwagner/svn/numpy/_configtest.c:58: undefined reference to `acos' /home/nwagner/svn/numpy/_configtest.c:59: undefined reference to `atan' /home/nwagner/svn/numpy/_configtest.c:60: undefined reference to `fmod' collect2: ld returned 1 exit status failure. removing: _configtest.c _configtest.o Traceback (most recent call last): File setup.py, line 172, in module setup_package() File setup.py, line 165, in setup_package configuration=configuration ) File /home/nwagner/svn/numpy/numpy/distutils/core.py, line 184, in setup return old_setup(**new_attr) File /usr/lib64/python2.6/distutils/core.py, line 152, in setup dist.run_commands() File /usr/lib64/python2.6/distutils/dist.py, line 975, in run_commands self.run_command(cmd) File /usr/lib64/python2.6/distutils/dist.py, line 995, in run_command cmd_obj.run() File /home/nwagner/svn/numpy/numpy/distutils/command/install.py, line 49, in
[Numpy-discussion] manipulating lists
Hi all, How can I extract the numbers from the following list ['', '-1.878722E-08,', '3.835992E-11', '1.192970E-03,-5.080192E-06'] It is easy to extract liste[1] '-1.878722E-08,' liste[2] '3.835992E-11' but liste[3] '1.192970E-03,-5.080192E-06' How can I accomplish that ? Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] manipulating lists
On Tue, 24 Mar 2009 10:27:18 -0400
josef.p...@gmail.com wrote:
On Tue, Mar 24, 2009 at 10:14 AM, Nils Wagner
nwag...@iam.uni-stuttgart.de wrote:
Hi all,
How can I extract the numbers from the following list
['', '-1.878722E-08,', '3.835992E-11',
'1.192970E-03,-5.080192E-06']
It is easy to extract
liste[1]
'-1.878722E-08,'
liste[2]
'3.835992E-11'
but
liste[3]
'1.192970E-03,-5.080192E-06'
How can I accomplish that ?
in python I would do this:
ss=['', '-1.878722E-08,',
'3.835992E-11','1.192970E-03,-5.080192E-06']
li = []
for j in ss:
for ii in j.split(','): # assumes , is delimiter
try: li.append(float(ii));
except ValueError: pass
li
[-1.87872199e-008, 3.83599203e-011,
0.00119297,
-5.08019199e-006]
np.array(li)
array([ -1.87872200e-08, 3.83599200e-11,
1.19297000e-03,
-5.08019200e-06])
Josef
Thank you. Works like a charm.
Nils
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Re: [Numpy-discussion] test failure in numpy trunk
On Tue, 24 Mar 2009 11:20:53 -0600 Charles R Harris charlesr.har...@gmail.com wrote: 2009/3/24 Darren Dale dsdal...@gmail.com Hello, I just performed an svn update, deleted my old build/ and site-packages/numpy*, reinstalled, and I see a new test failure on a 64 bit linux machine: == FAIL: test_umath.TestComplexFunctions.test_loss_of_precision_longcomplex -- Traceback (most recent call last): File /usr/lib64/python2.6/site-packages/nose/case.py, line 182, in runTest self.test(*self.arg) File /usr/lib64/python2.6/site-packages/numpy/testing/decorators.py, line 169, in knownfailer return f(*args, **kwargs) File /usr/lib64/python2.6/site-packages/numpy/core/tests/test_umath.py, line 557, in test_loss_of_precision_longcomplex self.check_loss_of_precision(np.longcomplex) File /usr/lib64/python2.6/site-packages/numpy/core/tests/test_umath.py, line 510, in check_loss_of_precision check(x_series, 2*eps) File /usr/lib64/python2.6/site-packages/numpy/core/tests/test_umath.py, line 497, in check 'arctanh') AssertionError: (135, 3.4039637354191726288e-09, 3.9031278209478159624e-18, 'arctanh') What machine is it? Chuck I can reproduce the failure. Linux linux-mogv 2.6.27.19-3.2-default #1 SMP 2009-02-25 15:40:44 +0100 x86_64 x86_64 x86_64 GNU/Linux cat /proc/cpuinfo processor : 0 vendor_id : GenuineIntel cpu family : 6 model : 15 model name : Intel(R) Pentium(R) Dual CPU T3200 @ 2.00GHz stepping: 13 cpu MHz : 1000.000 cache size : 1024 KB physical id : 0 siblings: 2 core id : 0 cpu cores : 2 apicid : 0 initial apicid : 0 fpu : yes fpu_exception : yes cpuid level : 10 wp : yes flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx lm constant_tsc arch_perfmon pebs bts rep_good nopl pni monitor ds_cpl est tm2 ssse3 cx16 xtpr lahf_lm bogomips: 3996.80 clflush size: 64 cache_alignment : 64 address sizes : 36 bits physical, 48 bits virtual power management: processor : 1 vendor_id : GenuineIntel cpu family : 6 model : 15 model name : Intel(R) Pentium(R) Dual CPU T3200 @ 2.00GHz stepping: 13 cpu MHz : 1000.000 cache size : 1024 KB physical id : 0 siblings: 2 core id : 1 cpu cores : 2 apicid : 1 initial apicid : 1 fpu : yes fpu_exception : yes cpuid level : 10 wp : yes flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx lm constant_tsc arch_perfmon pebs bts rep_good nopl pni monitor ds_cpl est tm2 ssse3 cx16 xtprlahf_lm bogomips: 3996.82 clflush size: 64 cache_alignment : 64 address sizes : 36 bits physical, 48 bits virtual power management: == FAIL: test_umath.TestComplexFunctions.test_loss_of_precision_longcomplex -- Traceback (most recent call last): File /home/nwagner/local/lib64/python2.6/site-packages/nose-0.10.4-py2.6.egg/nose/case.py, line 182, in runTest self.test(*self.arg) File /home/nwagner/local/lib64/python2.6/site-packages/numpy/testing/decorators.py, line 169, in knownfailer return f(*args, **kwargs) File /home/nwagner/local/lib64/python2.6/site-packages/numpy/core/tests/test_umath.py, line 557, in test_loss_of_precision_longcomplex self.check_loss_of_precision(np.longcomplex) File /home/nwagner/local/lib64/python2.6/site-packages/numpy/core/tests/test_umath.py, line 510, in check_loss_of_precision check(x_series, 2*eps) File /home/nwagner/local/lib64/python2.6/site-packages/numpy/core/tests/test_umath.py, line 497, in check 'arctanh') AssertionError: (135, 3.4039637354191726288e-09, 3.9031278209478159624e-18, 'arctanh') -- Ran 2031 tests in 15.923s FAILED (KNOWNFAIL=1, failures=1) nose.result.TextTestResult run=2031 errors=0 failures=1 ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] numpy for 64 bits machine
On Fri, 20 Mar 2009 11:09:49 +0100 Vincent Thierion vincent.thier...@ema.fr wrote: Hello, Is there an easy way to build numpy on remote 64 bits machines on which I don't have any roots privilege ? python setup.py install --prefix=$HOME/local Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] dot product
Hi all, The dot product can be defined for two vectors x and y by x·y=|x||y| \cos(\theta), where theta is the angle between the vectors and |x| is the norm. Now assume that we have arrays(matrices) X = [x_1, ..., x_m] Y = [y_1, ..., y_s] m s Is there a built-in function to compute the following matrix for i in arange(0,m): for j in arange(0,s): MAC[i,j] = dot(X[:,i],Y[:,j])**2/(dot(X[:,i],X[:,i])*dot(Y[:,j],Y[:,j])) Each element of the matrix represents the corresponding angle squared. Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] AttributeError: 'str' object has no attribute 'seek'
Hi all,
I encountered a problem wrt loadtxt.
Traceback (most recent call last):
File mac.py, line 9, in module
mac =
loadtxt('mac_diff.pmat.gz',skiprows=27,comments='!',usecols=(0,2,4),dtype='|S40')
File
/data/home/nwagner/local/lib/python2.5/site-packages/numpy/lib/io.py,
line 384, in loadtxt
fh = seek_gzip_factory(fname)
File
/data/home/nwagner/local/lib/python2.5/site-packages/numpy/lib/io.py,
line 51, in seek_gzip_factory
f.seek = new.instancemethod(seek, f)
AttributeError: 'str' object has no attribute 'seek'
numpy.__version__
'1.3.0.dev6520'
Nils
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Re: [Numpy-discussion] AttributeError: 'str' object has no attribute 'seek'
On Mon, 2 Mar 2009 22:08:22 +0200 Stéfan van der Walt ste...@sun.ac.za wrote: Nils, 2009/3/2 Nils Wagner nwag...@iam.uni-stuttgart.de: I encountered a problem wrt loadtxt. File /data/home/nwagner/local/lib/python2.5/site-packages/numpy/lib/io.py, line 384, in loadtxt fh = seek_gzip_factory(fname) Would you mind trying latest SVN? Thanks Stéfan Hi Stéfan, Works for me. Thank you very much ! BTW, is it possible to use more than one character to indicate the start of a comment ? I would like to use both '!' and '$'. Cheers, Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] ValueError: invalid literal for float()
Hi all, Is it possible to modify the behaviour of float wrt the following situation permas_M[0,2] '1.569809265137D+01' float(permas_M[0,2]) Traceback (most recent call last): File stdin, line 1, in module ValueError: invalid literal for float(): 1.569809265137D+01 The following works. permas_M[0,2] = '1.569809265137E+01' permas_M[0,2] '1.569809265137E+01' float(permas_M[0,2]) 15.69809265137 Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] RFR: 995 - numpy.load can't handle gzip file handles
On Sat, 21 Feb 2009 12:58:14 +0200 Stéfan van der Walt ste...@sun.ac.za wrote: Hi, Based on an example on Effbot, I implemented a workaround for reverse seeking in gzip files. I need someone with Python 2.4 to review: http://www.scipy.org/scipy/numpy/ticket/995 Thanks! Stéfan Done. See http://www.scipy.org/scipy/numpy/ticket/995 for details. Cheers, Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] RFR: 995 - numpy.load can't handle gzip file handles
On Sun, 22 Feb 2009 13:03:03 +0200 Stéfan van der Walt ste...@sun.ac.za wrote: Hi Nils, 2009/2/22 Nils Wagner nwag...@iam.uni-stuttgart.de: Done. See http://www.scipy.org/scipy/numpy/ticket/995 for details. Thanks. Did you have a NumPy array stored with numpy.save in test.gz? I finally got access to a 2.4 machine and the patch works there. Cheers Stéfan ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion The attachment is missing. Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] RFR: 991 - Make savez able to write ZIP64 files
On Sun, 22 Feb 2009 18:37:05 +0200 Stéfan van der Walt ste...@sun.ac.za wrote: Hi all, Please review the patch attached to http://scipy.org/scipy/numpy/ticket/991 which enables ZIP64 extensions when saving and loading zipped data under Python = 2.5 Thanks, Stéfan Hi Stefan, Please can you provide a short test ? Thanks in advance Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] RFR: 991 - Make savez able to write ZIP64 files
On Sun, 22 Feb 2009 22:18:32 +0200 Stéfan van der Walt ste...@sun.ac.za wrote: Hi Nils 2009/2/22 Nils Wagner nwag...@iam.uni-stuttgart.de: http://scipy.org/scipy/numpy/ticket/991 which enables ZIP64 extensions when saving and loading zipped data under Python = 2.5 You can just run nosetests numpy.lib on both a 2.4 and a 2.5 installation to see if it works. Thanks! Stéfan ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion Done. I am using python2.6 now. patch io.py 0001-Add-ZIP64-support.patch nosetests numpy.lib .. -- Ran 938 tests in 8.616s OK Cheers, Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] RFR: 995 - numpy.load can't handle gzip file handles
On Sat, 21 Feb 2009 12:58:14 +0200 Stéfan van der Walt ste...@sun.ac.za wrote: Hi, Based on an example on Effbot, I implemented a workaround for reverse seeking in gzip files. I need someone with Python 2.4 to review: http://www.scipy.org/scipy/numpy/ticket/995 Thanks! Stéfan _ Hi Stefan, I would like to help but I failed to install numpy (python2.4 Suse Linux 9.3) In file included from numpy/core/src/multiarraymodule.c:96: numpy/core/src/umath_funcs_c99.inc.src:269: warning: conflicting types for built-in function `sinl' numpy/core/src/umath_funcs_c99.inc.src:269: warning: conflicting types for built-in function `cosl' numpy/core/src/umath_funcs_c99.inc.src:269: error: conflicting types for `tanl' /usr/include/bits/mathcalls.h:68: error: previous declaration of `tanl' numpy/core/src/umath_funcs_c99.inc.src:269: error: conflicting types for `sinhl' /usr/include/bits/mathcalls.h:75: error: previous declaration of `sinhl' numpy/core/src/umath_funcs_c99.inc.src:269: error: conflicting types for `coshl' /usr/include/bits/mathcalls.h:73: error: previous declaration of `coshl' numpy/core/src/umath_funcs_c99.inc.src:269: error: conflicting types for `tanhl' /usr/include/bits/mathcalls.h:77: error: previous declaration of `tanhl' numpy/core/src/umath_funcs_c99.inc.src:269: error: conflicting types for `fabsl' /usr/include/bits/mathinline.h:476: error: previous declaration of `fabsl' numpy/core/src/umath_funcs_c99.inc.src:269: error: conflicting types for `floorl' /usr/include/bits/mathinline.h:530: error: previous declaration of `floorl' numpy/core/src/umath_funcs_c99.inc.src:269: error: conflicting types for `ceill' /usr/include/bits/mathinline.h:541: error: previous declaration of `ceill' numpy/core/src/umath_funcs_c99.inc.src:269: error: conflicting types for `rintl' /usr/include/bits/mathcalls.h:280: error: previous declaration of `rintl' numpy/core/src/umath_funcs_c99.inc.src:269: warning: conflicting types for built-in function `truncl' numpy/core/src/umath_funcs_c99.inc.src:269: warning: conflicting types for built-in function `sqrtl' numpy/core/src/umath_funcs_c99.inc.src:269: error: conflicting types for `log10l' /usr/include/bits/mathcalls.h:113: error: previous declaration of `log10l' numpy/core/src/umath_funcs_c99.inc.src:269: warning: conflicting types for built-in function `logl' numpy/core/src/umath_funcs_c99.inc.src:269: warning: conflicting types for built-in function `expl' numpy/core/src/umath_funcs_c99.inc.src:269: error: conflicting types for `expm1l' /usr/include/bits/mathcalls.h:129: error: previous declaration of `expm1l' numpy/core/src/umath_funcs_c99.inc.src:269: error: conflicting types for `asinl' /usr/include/bits/mathcalls.h:57: error: previous declaration of `asinl' numpy/core/src/umath_funcs_c99.inc.src:269: error: conflicting types for `acosl' /usr/include/bits/mathcalls.h:55: error: previous declaration of `acosl' numpy/core/src/umath_funcs_c99.inc.src:269: error: conflicting types for `atanl' /usr/include/bits/mathcalls.h:59: error: previous declaration of `atanl' numpy/core/src/umath_funcs_c99.inc.src:269: error: conflicting types for `asinhl' /usr/include/bits/mathcalls.h:91: error: previous declaration of `asinhl' numpy/core/src/umath_funcs_c99.inc.src:269: error: conflicting types for `acoshl' /usr/include/bits/mathcalls.h:89: error: previous declaration of `acoshl' numpy/core/src/umath_funcs_c99.inc.src:269: error: conflicting types for `atanhl' /usr/include/bits/mathcalls.h:93: error: previous declaration of `atanhl' numpy/core/src/umath_funcs_c99.inc.src:269: error: conflicting types for `log1pl' /usr/include/bits/mathcalls.h:132: error: previous declaration of `log1pl' numpy/core/src/umath_funcs_c99.inc.src:269: error: conflicting types for `exp2l' /usr/include/bits/mathcalls.h:142: error: previous declaration of `exp2l' numpy/core/src/umath_funcs_c99.inc.src:269: error: conflicting types for `log2l' /usr/include/bits/mathcalls.h:145: error: previous declaration of `log2l' numpy/core/src/umath_funcs_c99.inc.src:285: error: conflicting types for `atan2l' /usr/include/bits/mathcalls.h:61: error: previous declaration of `atan2l' numpy/core/src/umath_funcs_c99.inc.src:285: error: conflicting types for `hypotl' /usr/include/bits/mathcalls.h:163: error: previous declaration of `hypotl' numpy/core/src/umath_funcs_c99.inc.src:285: error: conflicting types for `powl' /usr/include/bits/mathcalls.h:154: error: previous declaration of `powl' numpy/core/src/umath_funcs_c99.inc.src:285: error: conflicting types for `fmodl' /usr/include/bits/mathcalls.h:188: error: previous declaration of `fmodl' numpy/core/src/umath_funcs_c99.inc.src:296: error: conflicting types for `modfl' /usr/include/bits/mathcalls.h:116: error: previous declaration of `modfl' In file included from numpy/core/src/scalartypes.inc.src:8, from numpy/core/src/arrayobject.c:545, from
[Numpy-discussion] Summary of ticket 937
Hi all, The summary of ticket 937 is incomplete. It should be Complex matrices and lstsq. http://projects.scipy.org/scipy/numpy/ticket/937 Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] astype
Hi all, How can I convert an array with string elements to an array with float entries ? coord_info[:,1] array(['0,0', '100,0', '200,0', '300,0', '400,0', '500,0', '600,0', '700,0', '800,0', '0.0', '100.0', '200.0', '300.0', '400.0', '500.0', '600.0', '700.0', '800.0', '0.0', '100.0', '200.0', '300.0', '400.0', '500.0', '600.0', '700.0', '800.0', '0.0', '100.0', '200.0', '300.0', '400.0', '500.0', '600.0', '700.0', '800.0', '0.0', '100.0', '200.0', '300.0', '400.0', '500.0', '600.0', '700.0', '800.0'], dtype='|S50') coord_info[:,1].astype(float) Traceback (most recent call last): File stdin, line 1, in module ValueError: invalid literal for float(): 0,0 Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] astype
On Sat, 14 Feb 2009 17:22:43 +0100 Nils Wagner nwag...@iam.uni-stuttgart.de wrote: Hi all, How can I convert an array with string elements to an array with float entries ? coord_info[:,1] array(['0,0', '100,0', '200,0', '300,0', '400,0', '500,0', '600,0', '700,0', '800,0', '0.0', '100.0', '200.0', '300.0', '400.0', '500.0', '600.0', '700.0', '800.0', '0.0', '100.0', '200.0', '300.0', '400.0', '500.0', '600.0', '700.0', '800.0', '0.0', '100.0', '200.0', '300.0', '400.0', '500.0', '600.0', '700.0', '800.0', '0.0', '100.0', '200.0', '300.0', '400.0', '500.0', '600.0', '700.0', '800.0'], dtype='|S50') coord_info[:,1].astype(float) Traceback (most recent call last): File stdin, line 1, in module ValueError: invalid literal for float(): 0,0 Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion Sorry for the noise - dots and commas were mixed up in the input file. ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] Comparison of arrays
Hi all, I have two integer arrays of different shape, e.g. a array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) b array([ 3, 4, 5, 6, 7, 8, 9, 10]) How can I extract the values that belong to the array a exclusively i.e. array([1,2]) ? Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Comparison of arrays
On Mon, 9 Feb 2009 09:45:02 +0100 Francesc Alted fal...@pytables.org wrote: A Monday 09 February 2009, Nils Wagner escrigué: Hi all, I have two integer arrays of different shape, e.g. a array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) b array([ 3, 4, 5, 6, 7, 8, 9, 10]) How can I extract the values that belong to the array a exclusively i.e. array([1,2]) ? One possible, fast solution is using Python sets: In [45]: np.array(list(set(a) ^ set(b))) Out[45]: array([1, 2]) Although this is suboptimal for very large arrays as it needs temporary space. Cheers, -- Francesc Alted Thank you very much for your prompt response. Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] ERROR: Test flat on masked_matrices
== ERROR: Test flat on masked_matrices -- Traceback (most recent call last): File /usr/local/lib64/python2.5/site-packages/numpy/ma/tests/test_core.py, line 1127, in test_flat test = ma.array(np.matrix([[1, 2, 3]]), mask=[0, 0, 1]) NameError: global name 'ma' is not defined -- Ran 1897 tests in 14.713s FAILED (KNOWNFAIL=9, errors=1) nose.result.TextTestResult run=1897 errors=1 failures=0 ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] xblas and numpy
Hi all, Just curious. Is it possible to use xblas with numpy ? http://www.netlib.org/xblas/ Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
