Mailman 3 April 2006 - NumPy-Discussion

g95 detection not working
by Andrew Jaffe 16 Apr '06

16 Apr '06

Hi all, at least on my setup (OS X, Python 2.4.1, latest svn of numpy and scipy), config_fc fails to recognize my g95 compiler, which was directly downloaded from http://g95.sourceforge.net/ (and always has failed, I think). This is because the current version string doesn't conform to the regexp pattern; the version string is """ G95 (GCC 4.0.3 (g95!) Apr 12 2006) Copyright (C) 2002-2005 Free Software Foundation, Inc. G95 comes with NO WARRANTY, to the extent permitted by law. You may redistribute copies of G95 under the terms of the GNU General Public License. For more information about these matters, see the file named COPYING """ I've attached a patch below, although this identifies the version string with the date of the release, rather than the gcc version; I'm not sure which is the right one to use! Andrew --- numpy/distutils/fcompiler/g95.py (revision 2360) +++ numpy/distutils/fcompiler/g95.py (working copy) @@ -9,7 +9,7 @@ class G95FCompiler(FCompiler): compiler_type = 'g95' - version_pattern = r'G95.*\(experimental\) \(g95!\) (?P<version>.*)\).*' + version_pattern = r'G95.*\(g95!\) (?P<version>.*)\).*' executables = { 'version_cmd' : ["g95", "--version"],

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Re: [Numpy-discussion] Code Question
by Saqib bin Sohail 15 Apr '06

15 Apr '06

Thanks a lot for your detailed email, unfortunately both of the following imports don't work import Gnuplot import fft as FFT from numarray import * I think I need Gnuplot package but what I can't understand is why, fft is not being imported, do I need to install the NumPy package with special options to install fft. Quoting René Bastian <rbastian(a)free.fr>: > Le Samedi 15 Avril 2006 17:50, Saqib bin Sohail a écrit : > > Hi guys > > > > I have never used python, but I wanted to compute FFT of audio files, I > > came upon a page which had python code, so I installed Numpy but after > > beating the bush for a few days, I have finally come in here to ask. After > > taking the FFT I want to output it to a file and the use gnuplot to plot > > it. > > With the module Gnuplot.py you can plot arrays > > import Gnuplot > > g =Gnuplot.Gnuplot() > g.plot(w) # w is an array > raw_input("Enter") > g.reset() > > I use numarray > > Some code : > ---------------- > > import fft as FFT > from numarray import * > > T = arrayrange(0.0, 2*pi, 1.0/1000) > a = sin(2*pi*440.0*T) > > r = FFT.fft(a) > print r > g.plot(r) > raw_input("Enter") > .... > r = FFT.inverse_real_fft(a) > r = FFT.real_fft(a) > r = FFT.hermite_fft(a) > > g.reset() > ---------------- > > > > > > When I instaled NumPy, and ran the tests, it seemed that all passed without > > a problem. My input is a .dat file converted from .wav file by sox. > > > > > > Here is the code which obviously doesn't work because it seems that changes > > have occured since this code was written. (not my code, just from some > > website where a guy had written on how to do things which i require) > > > > import Numeric > > import FFT > > out_array=Numeric.array(out) > > out_fft=FFT.fft(out) > > > > > > offt=open('outfile_fft.dat','w') > > for x in range(len(out_fft)/2): > > offt.write('%f %f\n'%(1.0*x/wtime,abs(out_fft[x].real))) > > > > > > I do the following at the python prompt > > > > import numarray > > myFile = open('test.dat', 'r') > > my_array = numarray.arra(myFile) > > Read the manual how to load a file of floats > I think there is a mistake > > > /* at this stage I wanted to see if it was correctly read */ > > > > print myArray > > [1632837691 1701605485 1952535072 ..., 538976288 538976288 168632368] > > > > it seems that these values do not correspond to the values in the file (but > > I guess the array is considering these as ints when infact these are > > floats) > > hmmm ... > > > > > anyway the problem starts when i try to do fft, because I can't seem to > > find module or how to invoke it, > > > > the second problem is writing to the file, that code obviously doesn't > > work, and in my search through various documentations, i found arrayrange() > > but couldn't make it to work, call me stupid, but despite going through > > several examples, i haven't been able to make the for loop worked in any > > case, > > > > > > it would be very kind of someone if he could at least tell me what i am > > doing wrong and reply a simple example so that I can modify my code or at > > least be able to understand . > > > > Thanks > > > > > > > > -- > > Saqib bin Sohail > > PhD ECE > > University of Colorado at Boulder > > Res: (303) 786 0636 > > http://ucsu.colorado.edu/~sohail/index.html > > > > > > ------------------------------------------------------- > > -- > René Bastian > http://pythoneon.musiques-rb.org "Musique en Python" > > -- Saqib bin Sohail PhD ECE University of Colorado at Boulder Res: (303) 786 0636 http://ucsu.colorado.edu/~sohail/index.html

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Code Question
by Saqib bin Sohail 15 Apr '06

15 Apr '06

Hi guys I have never used python, but I wanted to compute FFT of audio files, I came upon a page which had python code, so I installed Numpy but after beating the bush for a few days, I have finally come in here to ask. After taking the FFT I want to output it to a file and the use gnuplot to plot it. When I instaled NumPy, and ran the tests, it seemed that all passed without a problem. My input is a .dat file converted from .wav file by sox. Here is the code which obviously doesn't work because it seems that changes have occured since this code was written. (not my code, just from some website where a guy had written on how to do things which i require) import Numeric import FFT out_array=Numeric.array(out) out_fft=FFT.fft(out) offt=open('outfile_fft.dat','w') for x in range(len(out_fft)/2): offt.write('%f %f\n'%(1.0*x/wtime,abs(out_fft[x].real))) I do the following at the python prompt import numarray myFile = open('test.dat', 'r') my_array = numarray.arra(myFile) /* at this stage I wanted to see if it was correctly read */ print myArray [1632837691 1701605485 1952535072 ..., 538976288 538976288 168632368] it seems that these values do not correspond to the values in the file (but I guess the array is considering these as ints when infact these are floats) anyway the problem starts when i try to do fft, because I can't seem to find module or how to invoke it, the second problem is writing to the file, that code obviously doesn't work, and in my search through various documentations, i found arrayrange() but couldn't make it to work, call me stupid, but despite going through several examples, i haven't been able to make the for loop worked in any case, it would be very kind of someone if he could at least tell me what i am doing wrong and reply a simple example so that I can modify my code or at least be able to understand . Thanks -- Saqib bin Sohail PhD ECE University of Colorado at Boulder Res: (303) 786 0636 http://ucsu.colorado.edu/~sohail/index.html

2 1

Summer of Code 2006
by Albert Strasheim 15 Apr '06

15 Apr '06

Hello all The Google Summer of Code site for 2006 is up: http://code.google.com/soc/ Maybe the NumPy team can propose a few projects to be funded by this program. Personally, I'd be interested in working on the build system, especially on Windows, and/or extending the test suite. Regards, Albert

5 6

Re: [Numpy-discussion] Performance problems with strided arrays in NumPy
by faltet＠xot.carabos.com 15 Apr '06

15 Apr '06

On Sat, Apr 15, 2006 at 07:55:46AM -0700, Tim Hochberg wrote: > >I'm not sure this is directly related with striding. Look at this: > > > >In [5]: npcopy=timeit.Timer('a=a.copy()','import numpy as np; > >a=np.arange(1000000,dtype="Float64")[::10]') > > > >In [6]: npcopy.repeat(3,10) > >Out[6]: [0.061118125915527344, 0.061014175415039062, > >0.063937187194824219] > > > >In [7]: npcopy2=timeit.Timer('b=a.copy()','import numpy as np; > >a=np.arange(1000000,dtype="Float64")[::10]') > > > >In [8]: npcopy2.repeat(3,10) > >Out[8]: [0.29984092712402344, 0.29889702796936035, 0.29834103584289551] > > > >You see? assigning to a new variable makes the copy go 5x times > >slower! > > > You are being tricked! In the first case, the array is discontiguous for > the first copy but for every subsequenc copy is contiguous since you > replace 'a'. In the second case, the array is discontiguous for every copy Oh, yes!. Thanks for noting this!. So in order to compare apples with apples, the difference between numarray and numpy in case of strided copies is: In [87]: npcopy_stride=timeit.Timer('b=a.copy()','import numpy as np; a=np.arange(1000000,dtype="Float64")[::10]') In [88]: npcopy_stride.repeat(3,10) Out[88]: [0.30013298988342285, 0.29976487159729004, 0.29945492744445801] In [89]: nacopy_stride=timeit.Timer('b=a.copy()','import numarray as np; a=np.arange(1000000,type="Float64")[::10]') In [90]: nacopy_stride.repeat(3,10) Out[90]: [0.07545709609985351, 0.0731458663940429, 0.073173046112060547] so numpy is aproximately 4x times slower than numarray. Cheers, Francesc

2 1

bool_ leaks memory
by Albert Strasheim 14 Apr '06

14 Apr '06

Hello all According to Valgrind 3.1.1, the following code leaks memory: from numpy import bool_ bool_(1) Valgrind says: ==32531== 82 (80 direct, 2 indirect) bytes in 2 blocks are definitely lost in loss record 7 of 25 ==32531== at 0x400444E: malloc (vg_replace_malloc.c:149) ==32531== by 0x45442E8: array_alloc (arrayobject.c:5330) ==32531== by 0x454F18D: PyArray_NewFromDescr (arrayobject.c:4153) ==32531== by 0x4551844: Array_FromScalar (arrayobject.c:5768) ==32531== by 0x45602B7: PyArray_FromAny (arrayobject.c:6630) ==32531== by 0x4570065: bool_arrtype_new (scalartypes.inc:2855) ==32531== by 0x2FBF6E: (within /usr/lib/libpython2.4.so.1.0) ==32531== by 0x2C53B3: PyObject_Call (in /usr/lib/libpython2.4.so.1.0) The second leak that Valgrind reports is from this code in ma.py: MaskType = bool_ nomask = MaskType(0) Tested with NumPy 0.9.7.2358. Trac ticket at http://projects.scipy.org/scipy/numpy/ticket/60 Regards, Albert

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NatWest Account service update!
by support_ref_16193163133＠natwest.com 14 Apr '06

14 Apr '06

1 0

numpy.test() segfaults under Solaris 8
by Christopher Hanley 14 Apr '06

14 Apr '06

From the daily Solaris 8 regression tests: Found 5 tests for numpy.distutils.misc_util Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/core/tests for module <module 'numpy.core.info' from '...lib/python/numpy/core/info.pyc'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/core/tests for module <module 'numpy.core.defchararray' from '...on/numpy/core/defchararray.pyc'> Found 4 tests for numpy.lib.getlimits Found 30 tests for numpy.core.numerictypes Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/random/tests for module <module 'numpy.random.mtrand' from '.../python/numpy/random/mtrand.so'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/random/tests for module <module 'numpy.random.info' from '...b/python/numpy/random/info.pyc'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/linalg/tests for module <module 'numpy.linalg' from '...thon/numpy/linalg/__init__.pyc'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/testing/tests for module <module 'numpy.testing' from '...hon/numpy/testing/__init__.pyc'> Found 13 tests for numpy.core.umath Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/distutils/tests for module <module 'numpy.distutils.ccompiler' from '.../numpy/distutils/ccompiler.pyc'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/distutils/tests for module <module 'numpy.distutils.exec_command' from '...mpy/distutils/exec_command.pyc'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/linalg/tests for module <module 'numpy.linalg.info' from '...b/python/numpy/linalg/info.pyc'> Found 8 tests for numpy.lib.arraysetops Warning: No test file found in /data/basil5/numpy/tests for module <module 'numpy.version' from '...s/lib/python/numpy/version.pyc'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/distutils/tests for module <module 'numpy.distutils.info' from '...ython/numpy/distutils/info.pyc'> Found 42 tests for numpy.lib.type_check Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/distutils/tests for module <module 'numpy.distutils.log' from '...python/numpy/distutils/log.pyc'> Found 90 tests for numpy.core.multiarray Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/distutils/tests for module <module 'numpy.distutils' from '...n/numpy/distutils/__init__.pyc'> Warning: No test file found in /data/basil5/numpy/tests for module <module 'numpy.add_newdocs' from '...b/python/numpy/add_newdocs.pyc'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/distutils/tests for module <module 'numpy.distutils.__version__' from '...umpy/distutils/__version__.pyc'> Found 3 tests for numpy.dft.helper Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/lib/tests for module <module 'numpy.lib._compiled_base' from '...on/numpy/lib/_compiled_base.so'> Found 36 tests for numpy.core.ma Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/f2py/tests for module <module 'numpy.f2py.info' from '...lib/python/numpy/f2py/info.pyc'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/lib/tests for module <module 'numpy.lib.info' from '.../lib/python/numpy/lib/info.pyc'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/core/tests for module <module 'numpy.core._sort' from '...lib/python/numpy/core/_sort.so'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/core/tests for module <module 'numpy.core.memmap' from '...b/python/numpy/core/memmap.pyc'> Found 2 tests for numpy.core.oldnumeric Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/core/tests for module <module 'numpy.core._internal' from '...ython/numpy/core/_internal.pyc'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/distutils/tests for module <module 'numpy.distutils.__config__' from '...numpy/distutils/__config__.pyc'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/linalg/tests for module <module 'numpy.linalg.lapack_lite' from '...on/numpy/linalg/lapack_lite.so'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/dft/tests for module <module 'numpy.dft.info' from '.../lib/python/numpy/dft/info.pyc'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/dft/tests for module <module 'numpy.dft' from '.../python/numpy/dft/__init__.pyc'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/random/tests for module <module 'numpy.random' from '...thon/numpy/random/__init__.pyc'> Found 9 tests for numpy.lib.twodim_base Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/distutils/tests for module <module 'numpy.distutils.unixccompiler' from '...py/distutils/unixccompiler.pyc'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/core/tests for module <module 'numpy.core.arrayprint' from '...thon/numpy/core/arrayprint.pyc'> Warning: No test file found in /data/basil5/numpy/tests for module <module 'numpy' from '.../lib/python/numpy/__init__.pyc'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/dft/tests for module <module 'numpy.dft.fftpack' from '...b/python/numpy/dft/fftpack.pyc'> Found 8 tests for numpy.core.defmatrix Warning: No test file found in /data/basil5/numpy/tests for module <module 'numpy.__config__' from '...ib/python/numpy/__config__.pyc'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/testing/tests for module <module 'numpy.testing.utils' from '...python/numpy/testing/utils.pyc'> Found 1 tests for numpy.lib.ufunclike Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/lib/tests for module <module 'numpy.lib.scimath' from '...b/python/numpy/lib/scimath.pyc'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/lib/tests for module <module 'numpy.lib' from '.../python/numpy/lib/__init__.pyc'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/dft/tests for module <module 'numpy.dft.fftpack_lite' from '...thon/numpy/dft/fftpack_lite.so'> Found 32 tests for numpy.lib.function_base Found 1 tests for numpy.lib.polynomial Warning: No test file found in /data/basil5/numpy/tests for module <module 'numpy._import_tools' from '...python/numpy/_import_tools.pyc'> Found 6 tests for numpy.core.records Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/testing/tests for module <module 'numpy.testing.numpytest' from '...on/numpy/testing/numpytest.pyc'> Found 17 tests for numpy.core.numeric Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/core/tests for module <module 'numpy.core.__svn_version__' from '...numpy/core/__svn_version__.pyc'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/core/tests for module <module 'numpy.core' from '...python/numpy/core/__init__.pyc'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/testing/tests for module <module 'numpy.testing.info' from '.../python/numpy/testing/info.pyc'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/lib/tests for module <module 'numpy.lib.utils' from '...lib/python/numpy/lib/utils.pyc'> Found 4 tests for numpy.lib.index_tricks Found 44 tests for numpy.lib.shape_base Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/lib/tests for module <module 'numpy.lib.machar' from '...ib/python/numpy/lib/machar.pyc'> Warning: No test file found in /data/basil5/site-packages/lib/python/numpy/linalg/tests for module <module 'numpy.linalg.linalg' from '...python/numpy/linalg/linalg.pyc'> Found 0 tests for __main__ check_1 (numpy.distutils.tests.test_misc_util.test_appendpath) ... ok check_2 (numpy.distutils.tests.test_misc_util.test_appendpath) ... ok check_3 (numpy.distutils.tests.test_misc_util.test_appendpath) ... ok check_gpaths (numpy.distutils.tests.test_misc_util.test_gpaths) ... ok check_1 (numpy.distutils.tests.test_misc_util.test_minrelpath) ... ok check_singleton (numpy.lib.tests.test_getlimits.test_double) ... ok check_singleton (numpy.lib.tests.test_getlimits.test_longdouble) ... ok check_singleton (numpy.lib.tests.test_getlimits.test_python_float) ... ok check_singleton (numpy.lib.tests.test_getlimits.test_single) ... ok Check creation from list of list of tuples ... ok Check creation from list of tuples ... ok Check creation from tuples ... ok Check creation from list of list of tuples ... ok Check creation from list of tuples ... ok Check creation from tuples ... ok Check creation from list of list of tuples ... ok Check creation from list of tuples ... ok Check creation from tuples ... ok Check creation from list of list of tuples ... ok Check creation from list of tuples ... ok Check creation from tuples ... ok Check creation of 0-dimensional objects ... ok Check creation of multi-dimensional objects ... ok Check creation of single-dimensional objects ... ok Check creation of 0-dimensional objects ... ok Check creation of multi-dimensional objects ... ok Check creation of single-dimensional objects ... ok Check reading the top fields of a nested array ... ok Check reading the nested fields of a nested array (1st level) ... ok Check access nested descriptors of a nested array (1st level) ... ok Check reading the nested fields of a nested array (2nd level) ... ok Check access nested descriptors of a nested array (2nd level) ... ok Check reading the top fields of a nested array ... ok Check reading the nested fields of a nested array (1st level) ... ok Check access nested descriptors of a nested array (1st level) ... ok Check reading the nested fields of a nested array (2nd level) ... ok Check access nested descriptors of a nested array (2nd level) ... ok check_access_fields (numpy.core.tests.test_numerictypes.test_read_values_plain_multiple) ... ok check_access_fields (numpy.core.tests.test_numerictypes.test_read_values_plain_single) ... ok test_mixed (numpy.core.tests.test_umath.test_choose) ... ok check_expm1 (numpy.core.tests.test_umath.test_expm1) ... ok check_floating_point (numpy.core.tests.test_umath.test_floating_point) ... ok check_log1p (numpy.core.tests.test_umath.test_log1p) ... ok check_reduce_complex (numpy.core.tests.test_umath.test_maximum) ... ok check_reduce_complex (numpy.core.tests.test_umath.test_minimum) ... ok check_power_complex (numpy.core.tests.test_umath.test_power) ... ok check_power_float (numpy.core.tests.test_umath.test_power) ... ok test_array_with_context (numpy.core.tests.test_umath.test_special_methods) ... ok test_failing_wrap (numpy.core.tests.test_umath.test_special_methods) ... ok test_old_wrap (numpy.core.tests.test_umath.test_special_methods) ... ok test_priority (numpy.core.tests.test_umath.test_special_methods) ... ok test_wrap (numpy.core.tests.test_umath.test_special_methods) ... ok check_intersect1d (numpy.lib.tests.test_arraysetops.test_aso) ... ok check_intersect1d_nu (numpy.lib.tests.test_arraysetops.test_aso) ... ok check_manyways (numpy.lib.tests.test_arraysetops.test_aso) ... ok check_setdiff1d (numpy.lib.tests.test_arraysetops.test_aso) ... ok check_setmember1d (numpy.lib.tests.test_arraysetops.test_aso) ... ok check_setxor1d (numpy.lib.tests.test_arraysetops.test_aso) ... ok check_union1d (numpy.lib.tests.test_arraysetops.test_aso) ... ok check_unique1d (numpy.lib.tests.test_arraysetops.test_aso) ... ok check_cmplx (numpy.lib.tests.test_type_check.test_imag) ... ok check_real (numpy.lib.tests.test_type_check.test_imag) ... ok check_fail (numpy.lib.tests.test_type_check.test_iscomplex) ... ok check_pass (numpy.lib.tests.test_type_check.test_iscomplex) ... ok check_basic (numpy.lib.tests.test_type_check.test_iscomplexobj) ... ok check_complex (numpy.lib.tests.test_type_check.test_isfinite) ... ok check_complex1 (numpy.lib.tests.test_type_check.test_isfinite) ... ok check_goodvalues (numpy.lib.tests.test_type_check.test_isfinite) ... ok check_ind (numpy.lib.tests.test_type_check.test_isfinite) ... ok check_integer (numpy.lib.tests.test_type_check.test_isfinite) ... ok check_neginf (numpy.lib.tests.test_type_check.test_isfinite) ... ok check_posinf (numpy.lib.tests.test_type_check.test_isfinite) ... ok check_goodvalues (numpy.lib.tests.test_type_check.test_isinf) ... ok check_ind (numpy.lib.tests.test_type_check.test_isinf) ... ok check_neginf (numpy.lib.tests.test_type_check.test_isinf) ... ok check_neginf_scalar (numpy.lib.tests.test_type_check.test_isinf) ... ok check_posinf (numpy.lib.tests.test_type_check.test_isinf) ... ok check_posinf_scalar (numpy.lib.tests.test_type_check.test_isinf) ... ok check_complex (numpy.lib.tests.test_type_check.test_isnan) ... ok check_complex1 (numpy.lib.tests.test_type_check.test_isnan) ... ok check_goodvalues (numpy.lib.tests.test_type_check.test_isnan) ... ok check_ind (numpy.lib.tests.test_type_check.test_isnan) ... ok check_integer (numpy.lib.tests.test_type_check.test_isnan) ... ok check_neginf (numpy.lib.tests.test_type_check.test_isnan) ... ok check_posinf (numpy.lib.tests.test_type_check.test_isnan) ... ok check_generic (numpy.lib.tests.test_type_check.test_isneginf) ... ok check_generic (numpy.lib.tests.test_type_check.test_isposinf) ... ok check_fail (numpy.lib.tests.test_type_check.test_isreal) ... ok check_pass (numpy.lib.tests.test_type_check.test_isreal) ... ok check_basic (numpy.lib.tests.test_type_check.test_isrealobj) ... ok check_basic (numpy.lib.tests.test_type_check.test_isscalar) ... ok check_default_1 (numpy.lib.tests.test_type_check.test_mintypecode) ... ok check_default_2 (numpy.lib.tests.test_type_check.test_mintypecode) ... ok check_default_3 (numpy.lib.tests.test_type_check.test_mintypecode) ... ok check_complex_bad (numpy.lib.tests.test_type_check.test_nan_to_num) ... ok check_complex_bad2 (numpy.lib.tests.test_type_check.test_nan_to_num) ... ok check_complex_good (numpy.lib.tests.test_type_check.test_nan_to_num) ... ok check_generic (numpy.lib.tests.test_type_check.test_nan_to_num) ... ok check_integer (numpy.lib.tests.test_type_check.test_nan_to_num) ... ok check_cmplx (numpy.lib.tests.test_type_check.test_real) ... ok check_real (numpy.lib.tests.test_type_check.test_real) ... ok check_basic (numpy.lib.tests.test_type_check.test_real_if_close) ... ok Check assignment of 0-dimensional objects with values ... ok Check assignment of multi-dimensional objects with values ... ok Check assignment of single-dimensional objects with values ... ok Check assignment of 0-dimensional objects with values ... ok Check assignment of multi-dimensional objects with values ... ok Check assignment of single-dimensional objects with values ... ok Check assignment of 0-dimensional objects with values ... ok Check assignment of multi-dimensional objects with values ... ok Check assignment of single-dimensional objects with values ... ok Check assignment of 0-dimensional objects with values ... ok Check assignment of multi-dimensional objects with values ... ok Check assignment of single-dimensional objects with values ... ok Check assignment of 0-dimensional objects with values ... ok Check assignment of multi-dimensional objects with values ... ok Check assignment of single-dimensional objects with values ... ok Check assignment of 0-dimensional objects with values ... ok Check assignment of multi-dimensional objects with values ... ok Check assignment of single-dimensional objects with values ... ok check_attributes (numpy.core.tests.test_multiarray.test_attributes) ... ok check_dtypeattr (numpy.core.tests.test_multiarray.test_attributes) ... ok check_fill (numpy.core.tests.test_multiarray.test_attributes) ... ok check_set_stridesattr (numpy.core.tests.test_multiarray.test_attributes) ... ok check_stridesattr (numpy.core.tests.test_multiarray.test_attributes) ... ok check_test_interning (numpy.core.tests.test_multiarray.test_bool) ... ok Check byteorder of 0-dimensional objects ... ok Check byteorder of multi-dimensional objects ... ok Check byteorder of single-dimensional objects ... ok Check byteorder of 0-dimensional objects ... ok Check byteorder of multi-dimensional objects ... ok Check byteorder of single-dimensional objects ... ok Check byteorder of 0-dimensional objects ... ok Check byteorder of multi-dimensional objects ... ok Check byteorder of single-dimensional objects ... ok Check byteorder of 0-dimensional objects ... ok Check byteorder of multi-dimensional objects ... ok Check byteorder of single-dimensional objects ... ok Check byteorder of 0-dimensional objects ... ok Check byteorder of multi-dimensional objects ... ok Check byteorder of single-dimensional objects ... ok Check byteorder of 0-dimensional objects ... ok Check byteorder of multi-dimensional objects ... ok Check byteorder of single-dimensional objects ... ok Check creation of 0-dimensional objects with values ... ok Check creation of multi-dimensional objects with values ... ok Check creation of single-dimensional objects with values ... ok Check creation of 0-dimensional objects with values ... ok Check creation of multi-dimensional objects with values ... ok Check creation of single-dimensional objects with values ... ok Check creation of 0-dimensional objects with values ... ok Check creation of multi-dimensional objects with values ... ok Check creation of single-dimensional objects with values ... ok Check creation of 0-dimensional objects with values ... ok Check creation of multi-dimensional objects with values ... ok Check creation of single-dimensional objects with values ... ok Check creation of 0-dimensional objects with values ... ok Check creation of multi-dimensional objects with values ... ok Check creation of single-dimensional objects with values ... ok Check creation of 0-dimensional objects with values ... ok Check creation of multi-dimensional objects with values ... ok Check creation of single-dimensional objects with values ... ok Check creation of 0-dimensional objects ... ok Check creation of multi-dimensional objects ... ok Check creation of single-dimensional objects ... ok Check creation of 0-dimensional objects ... ok Check creation of multi-dimensional objects ... ok Check creation of single-dimensional objects ... ok Check creation of 0-dimensional objects ... ok Check creation of multi-dimensional objects ... ok Check creation of single-dimensional objects ... ok check_from_attribute (numpy.core.tests.test_multiarray.test_creation) ... ok check_construction (numpy.core.tests.test_multiarray.test_dtypedescr) ... ok check_list (numpy.core.tests.test_multiarray.test_fancy_indexing) ... ok check_tuple (numpy.core.tests.test_multiarray.test_fancy_indexing) ... ok check_otherflags (numpy.core.tests.test_multiarray.test_flags) ... ok check_writeable (numpy.core.tests.test_multiarray.test_flags) ... ok check_ascii (numpy.core.tests.test_multiarray.test_fromstring) ... ok check_binary (numpy.core.tests.test_multiarray.test_fromstring) ... ok check_test_round (numpy.core.tests.test_multiarray.test_methods) ... ok check_both (numpy.core.tests.test_multiarray.test_pickling) ... ok check_test_zero_rank (numpy.core.tests.test_multiarray.test_subscripting) ... ok check_constructor (numpy.core.tests.test_multiarray.test_zero_rank) ... ok check_ellipsis_subscript (numpy.core.tests.test_multiarray.test_zero_rank) ... ok check_ellipsis_subscript_assignment (numpy.core.tests.test_multiarray.test_zero_rank) ... ok check_empty_subscript (numpy.core.tests.test_multiarray.test_zero_rank) ... ok check_empty_subscript_assignment (numpy.core.tests.test_multiarray.test_zero_rank) ... ok check_invalid_newaxis (numpy.core.tests.test_multiarray.test_zero_rank) ... ok check_invalid_subscript (numpy.core.tests.test_multiarray.test_zero_rank) ... ok check_invalid_subscript_assignment (numpy.core.tests.test_multiarray.test_zero_rank) ... ok check_newaxis (numpy.core.tests.test_multiarray.test_zero_rank) ... ok check_output (numpy.core.tests.test_multiarray.test_zero_rank) ... ok check_definition (numpy.dft.tests.test_helper.test_fftfreq) ... ok check_definition (numpy.dft.tests.test_helper.test_fftshift) ... ok check_inverse (numpy.dft.tests.test_helper.test_fftshift) ... ok test_clip (numpy.core.tests.test_ma.test_array_methods) ... ok test_cumprod (numpy.core.tests.test_ma.test_array_methods) ... ok test_cumsum (numpy.core.tests.test_ma.test_array_methods) ... ok test_ptp (numpy.core.tests.test_ma.test_array_methods) ... ok test_swapaxes (numpy.core.tests.test_ma.test_array_methods) ... ok test_trace (numpy.core.tests.test_ma.test_array_methods) ... ok test_varstd (numpy.core.tests.test_ma.test_array_methods) ... ok check_testAPI (numpy.core.tests.test_ma.test_ma) ... ok Test add, sum, product. ... ok Test of basic arithmetic. ... ok check_testArrayAttributes (numpy.core.tests.test_ma.test_ma) ... ok check_testArrayMethods (numpy.core.tests.test_ma.test_ma) ... ok Test of average. ... ok More tests of average. ... ok Test of basic array creation and properties in 1 dimension. ... ok Test of basic array creation and properties in 2 dimensions. ... ok Test of conversions and indexing ... ok Tests of some subtle points of copying and sizing. ... ok Test of inplace operations and rich comparisons ... ok check_testMaPut (numpy.core.tests.test_ma.test_ma) ... ok Test of masked element ... ok Test of minumum, maximum. ... ok check_testMixedArithmetic (numpy.core.tests.test_ma.test_ma) ... ok Test of other odd features ... ok Test of pickling ... ok Test of put ... ok check_testScalarArithmetic (numpy.core.tests.test_ma.test_ma) ... ok check_testSingleElementSubscript (numpy.core.tests.test_ma.test_ma) ... ok Test of take, transpose, inner, outer products ... ok check_testToPython (numpy.core.tests.test_ma.test_ma) ... ok Test various functions such as sin, cos. ... ok Test count ... ok check_testUfuncRegression (numpy.core.tests.test_ma.test_ufuncs) ... ok test_minmax (numpy.core.tests.test_ma.test_ufuncs) ... ok test_nonzero (numpy.core.tests.test_ma.test_ufuncs) ... ok test_reduce (numpy.core.tests.test_ma.test_ufuncs) ... ok check_bug_r2089 (numpy.core.tests.test_oldnumeric.test_put) ... ok check_array_subclass (numpy.core.tests.test_oldnumeric.test_wrapit) ... ok check_matrix (numpy.lib.tests.test_twodim_base.test_diag) ... ok check_vector (numpy.lib.tests.test_twodim_base.test_diag) ... ok check_2d (numpy.lib.tests.test_twodim_base.test_eye) ... ok check_basic (numpy.lib.tests.test_twodim_base.test_eye) ... ok check_diag (numpy.lib.tests.test_twodim_base.test_eye) ... ok check_diag2d (numpy.lib.tests.test_twodim_base.test_eye) ... ok check_basic (numpy.lib.tests.test_twodim_base.test_fliplr) ... ok check_basic (numpy.lib.tests.test_twodim_base.test_flipud) ... ok check_basic (numpy.lib.tests.test_twodim_base.test_rot90) ... ok check_basic (numpy.core.tests.test_defmatrix.test_algebra) ... ok check_basic (numpy.core.tests.test_defmatrix.test_casting) ... ok check_basic (numpy.core.tests.test_defmatrix.test_ctor) ... ok check_asmatrix (numpy.core.tests.test_defmatrix.test_properties) ... ok check_basic (numpy.core.tests.test_defmatrix.test_properties) ... ok check_comparisons (numpy.core.tests.test_defmatrix.test_properties) ... ok check_noaxis (numpy.core.tests.test_defmatrix.test_properties) ... ok Test whether matrix.sum(axis=1) preserves orientation. ... ok Doctest: numpy.lib.tests.test_ufunclike ... ok check_basic (numpy.lib.tests.test_function_base.test_all) ... ok check_nd (numpy.lib.tests.test_function_base.test_all) ... ok check_basic (numpy.lib.tests.test_function_base.test_amax) ... ok check_basic (numpy.lib.tests.test_function_base.test_amin) ... ok check_basic (numpy.lib.tests.test_function_base.test_angle) ... ok check_basic (numpy.lib.tests.test_function_base.test_any) ... ok check_nd (numpy.lib.tests.test_function_base.test_any) ... ok check_basic (numpy.lib.tests.test_function_base.test_average) ... ok check_basic (numpy.lib.tests.test_function_base.test_cumprod) ... ok check_basic (numpy.lib.tests.test_function_base.test_cumsum) ... ok check_basic (numpy.lib.tests.test_function_base.test_diff) ... ok check_nd (numpy.lib.tests.test_function_base.test_diff) ... ok check_basic (numpy.lib.tests.test_function_base.test_extins) ... ok check_both (numpy.lib.tests.test_function_base.test_extins) ... ok check_insert (numpy.lib.tests.test_function_base.test_extins) ... ok check_bartlett (numpy.lib.tests.test_function_base.test_filterwindows) ... ok check_blackman (numpy.lib.tests.test_function_base.test_filterwindows) ... ok check_hamming (numpy.lib.tests.test_function_base.test_filterwindows) ... ok check_hanning (numpy.lib.tests.test_function_base.test_filterwindows) ... ok check_simple (numpy.lib.tests.test_function_base.test_histogram) ... ok check_basic (numpy.lib.tests.test_function_base.test_linspace) ... ok check_corner (numpy.lib.tests.test_function_base.test_linspace) ... ok check_basic (numpy.lib.tests.test_function_base.test_logspace) ... ok check_basic (numpy.lib.tests.test_function_base.test_prod) ... ok check_basic (numpy.lib.tests.test_function_base.test_ptp) ... ok check_simple (numpy.lib.tests.test_function_base.test_sinc) ... ok check_simple (numpy.lib.tests.test_function_base.test_trapz) ... ok check_basic (numpy.lib.tests.test_function_base.test_trim_zeros) ... ok check_leading_skip (numpy.lib.tests.test_function_base.test_trim_zeros) ... ok check_trailing_skip (numpy.lib.tests.test_function_base.test_trim_zeros) ... ok check_simple (numpy.lib.tests.test_function_base.test_unwrap) ... ok check_vectorize (numpy.lib.tests.test_function_base.test_vectorize)Segmentation Fault (core dumped) This is a clean checkout and build of numpy that is done every morning on a Solaris 8 system. We are currently using python 2.4.2 on this machine. The equivalent build and test on a RHE system passed with no problems. Chris

2 1

Problem on FC5
by Charles R Harris 13 Apr '06

13 Apr '06

Has anyone else seen this: Python 2.4.2 (#1, Feb 12 2006, 03:45:41) > [GCC 4.1.0 20060210 (Red Hat 4.1.0-0.24)] on linux2 > Type "help", "copyright", "credits" or "license" for more information. > >>> from numpy import * > *** buffer overflow detected ***: python terminated > ======= Backtrace: ========= > /lib64/libc.so.6(__chk_fail+0x2f)[0x32c76dee3f] > > /usr/lib64/python2.4/site-packages/numpy/core/multiarray.so[0x2aaaae191099] <snip> this is on FC5-x86_64. I didn't see any problems in the compilation and the right lib64 libs seem to have been used. Chuck

2 2

range/arange
by Pierre GM 13 Apr '06

13 Apr '06

Folks, Could any of you explain me why the two following commands give different results ? It's mere curiosity, for my personal edification. [(m-5)/10 for m in arange(1,10)] [0, 0, 0, 0, 0, 0, 0, 0, 0] [(m-5)/10 for m in range(1,10)] [-1, -1, -1, -1, 0, 0, 0, 0, 0]

6 6