Re: [Numpy-discussion] crash at prompt exit after running test
Ubuntu has a much shorter cycle of updates than Fedora, indeed. On 03/10/2010 06:27 AM, Charles R Harris wrote: On Tue, Mar 9, 2010 at 5:52 PM, Johann Cohen-Tanugi co...@lpta.in2p3.fr mailto:co...@lpta.in2p3.fr wrote: more fun : [co...@jarrett tests]$ pwd /home/cohen/sources/python/numpy/numpy/core/tests [co...@jarrett tests]$ python -c 'import test_ufunc' python: Modules/gcmodule.c:277: visit_decref: Assertion `gc-gc.gc_refs != 0' failed. Aborted (core dumped) and in the debugger: (gdb) run Starting program: /usr/bin/python warning: .dynamic section for /lib/libpthread.so.0 is not at the expected address warning: difference appears to be caused by prelink, adjusting expectations warning: .dynamic section for /lib/libdl.so.2 is not at the expected address warning: difference appears to be caused by prelink, adjusting expectations warning: .dynamic section for /lib/libc.so.6 is not at the expected address warning: difference appears to be caused by prelink, adjusting expectations [Thread debugging using libthread_db enabled] Python 2.6.2 (r262:71600, Jan 25 2010, 18:46:45) [GCC 4.4.2 20091222 (Red Hat 4.4.2-20)] on linux2 Type help, copyright, credits or license for more information. import test_ufunc python: Modules/gcmodule.c:277: visit_decref: Assertion `gc-gc.gc_refs != 0' failed. Program received signal SIGABRT, Aborted. 0x00aab416 in __kernel_vsyscall () Missing separate debuginfos, use: debuginfo-install atlas-3.8.3-12.fc12.i686 libgcc-4.4.3-4.fc12.i686 libgfortran-4.4.3-4.fc12.i686 (gdb) bt #0 0x00aab416 in __kernel_vsyscall () #1 0x00159a91 in raise (sig=6) at ../nptl/sysdeps/unix/sysv/linux/raise.c:64 #2 0x0015b35a in abort () at abort.c:92 #3 0x00152be8 in __assert_fail (assertion=value optimized out, file=value optimized out, line=value optimized out, function=value optimized out) at assert.c:81 #4 0x0050931e in visit_decref (op=value optimized out, data=value optimized out) at Modules/gcmodule.c:277 #5 0x0047c8c2 in dict_traverse (op=value optimized out, visit=value optimized out, arg=value optimized out) at Objects/dictobject.c:2003 #6 0x00509af3 in subtract_refs (generation=value optimized out) at Modules/gcmodule.c:296 #7 collect (generation=value optimized out) at Modules/gcmodule.c:817 #8 0x0050a640 in PyGC_Collect () at Modules/gcmodule.c:1292 #9 0x004fb0f0 in Py_Finalize () at Python/pythonrun.c:424 #10 0x0050868f in Py_Main (argc=value optimized out, argv=value optimized out) at Modules/main.c:625 #11 0x080485c8 in main (argc=value optimized out, argv=value optimized out) at Modules/python.c:23 which looks identical to the bt I sent to Robert earlier on. HTH, Johann On 03/10/2010 12:43 AM, Johann Cohen-Tanugi wrote: On 03/10/2010 12:33 AM, Johann Cohen-Tanugi wrote: On 03/10/2010 12:07 AM, Pauli Virtanen wrote: ti, 2010-03-09 kello 21:14 +0100, Johann Cohen-Tanugi kirjoitti: thinking about it, this morning there was a fedora update to python, so I am using 2.6.2-4.fc12. Looks like the problem is in python itself, hence this piece of info. That the problem would be in Python is not so clear to me. Can you try running it with the previous Python shipped by Fedora? Do you see the problem then? What's the previous version, btw? 2.6.2-1 IIRC. I would have to check, and I am not sure how to either query this information or step back one update up with yum :( Memory errors are somewhat difficult to debug. Can you try running only a certain subset of the tests, first nosetests numpy.core crash Be sure to set Pythonpath so that you get the correct Numpy version. If it segfaults, proceed to (under numpy/core/tests) nosetests test_multiarray.py nosetests test_multiarray.py:TestNewBufferProtocol neither crash, so the problem is not there I followed your lead and tried each script and ended up with : [co...@jarrett tests]$ nosetests test_ufunc.py . -- Ran 13 tests in 1.146s OK python: Modules/gcmodule.c:277: visit_decref: Assertion `gc-gc.gc_refs != 0' failed. Aborted (core dumped) so test_ufunc.py seems to be at stake Since the crash occurs in cyclic garbage collection, I'm doubting a bit the numpy/core/src/multiarray/numpymemoryview.c implementation, since that's the only part in Numpy that supports that. Alternatively, just replace numpymemoryview.c with the attached one which has cyclic GC stripped, and see if you still get the crash. Cheers, Pauli
Re: [Numpy-discussion] crash at prompt exit after running test
On 03/10/2010 01:55 AM, Pauli Virtanen wrote: more fun : [co...@jarrett tests]$ pwd /home/cohen/sources/python/numpy/numpy/core/tests [co...@jarrett tests]$ python -c 'import test_ufunc' python: Modules/gcmodule.c:277: visit_decref: Assertion `gc-gc.gc_refs != 0' failed. Aborted (core dumped) What happens if you only import the umath_tests module (or something, it's a .so under numpy.core)? [co...@jarrett core]$ export PYTHONPATH=/home/cohen/.local/lib/python2.6/site-packages/numpy/core:$PYTHONPATH [co...@jarrett core]$ python Python 2.6.2 (r262:71600, Jan 25 2010, 18:46:45) [GCC 4.4.2 20091222 (Red Hat 4.4.2-20)] on linux2 Type help, copyright, credits or license for more information. import umath_tests python: Modules/gcmodule.c:277: visit_decref: Assertion `gc-gc.gc_refs != 0' failed. Aborted (core dumped) so this import also trigger the crash at exit... Just importing test_ufunc.py probably doesn't run a lot of extension code. Since you don't get crashes only by importing numpy, I really don't see many alternatives any more... Thanks, Pauli ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] Backwards slicing including the first element
Dear all, Is there a way to give an integer value to j when using a[i:j:-1] so that the first element of the array can be included in the slice ? I would like to use some code like a[i:i-k:-1] to get a slice of length k. The numpy documentation seems to suggest that j=-1 should work: Assume n is the number of elements in the dimension being sliced. Then, if i is not given it defaults to 0 for k 0 and n for k 0 . If j is not given it defaults to n for k 0 and -1 for k 0 . If k is not given it defaults to 1. But a[i:i-k:-1] is empty if i-k is -1. The workaround is a[i::-1][:k], is there something simpler ? Many thanks in advance, Jerome. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] How to apply a function to an ndarray over a given dimension
Hi, First, excuse me if I am over-optimizing, but I am curious if there exist a way to apply a function to an ndarray over a given dimension. In case I don't make myself clear, I have an array of shape( n,2,2) where each row represents a 2 by 2 covariance matrix, and I want to perform the eigenvalue decomposition of each row. Right now I do it with list comprehensions: import numpy as np import scipy as sp C = np.arange(10*2*2).reshape(10,2,2) ed = [sp.linalg.eig(r) for r in C[:]] Is there a better way, along the lines of vectorize, of doing this? Cheers, Jorge ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] printing structured arrays
On 10/03/10 10:09, Bruce Schultz wrote: On Sat, Mar 6, 2010 at 8:35 AM, Gökhan Sever gokhanse...@gmail.com wrote: On Fri, Mar 5, 2010 at 8:00 AM, Bruce Schultz bruce.schu...@gmail.com wrote: Output is: ### ndarray [[ 1. 2. ] [ 3. 4.1]] ### structured array [(1.0, 2.0) (3.0, 4.0996)] I still couldn't figure out how floating point numbers look nicely on screen in cases like yours (i.e., trying numpy.array2string()) but you can make sure by using numpy.savetxt(file, array, fmt=%.1f) you will always have specified precision in the written file. Using numpy.array2string() gives the same format as the output above. I started looking at how array2string() is implemented, and came up with this patch which formats my structured array nicely, the same as an unstructured array. It was mainly done as a proof of concept, so it only works for floats and I'm probably doing the wrong thing to detect a structured array by comparing the dtype to void. Maybe someone with more numpy experience can tell me if I'm on the right track... === modified file 'numpy/core/arrayprint.py' --- numpy/core/arrayprint.py2010-02-21 16:16:34 + +++ numpy/core/arrayprint.py2010-03-10 13:48:22 + @@ -219,6 +219,10 @@ elif issubclass(dtypeobj, _nt.unicode_) or \ issubclass(dtypeobj, _nt.string_): format_function = repr +elif issubclass(dtypeobj, _nt.void): +#XXX this is for structured arrays +format_function = StructuredFormatter(a) +separator = '\n ' else: format_function = str @@ -231,6 +235,17 @@ return lst +class StructuredFormatter: +def __init__(self, a): +self.data = a +self.dtype = a.dtype #XXX use the dtype to build column formatters + +def __call__(self, x): +ff = FloatFormat(self.data.view(float), _float_output_precision, + _float_output_suppress_small) +return '[' + ' '.join([ff(n) for n in x]) + ']' + + def _convert_arrays(obj): import numeric as _nc newtup = [] Cheers Bruce ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] crash at prompt exit after running test
Wed, 10 Mar 2010 10:28:07 +0100, Johann Cohen-Tanugi wrote: On 03/10/2010 01:55 AM, Pauli Virtanen wrote: more fun : [co...@jarrett tests]$ pwd /home/cohen/sources/python/numpy/numpy/core/tests [co...@jarrett tests]$ python -c 'import test_ufunc' python: Modules/gcmodule.c:277: visit_decref: Assertion `gc-gc.gc_refs != 0' failed. Aborted (core dumped) What happens if you only import the umath_tests module (or something, it's a .so under numpy.core)? [co...@jarrett core]$ export PYTHONPATH=/home/cohen/.local/lib/python2.6/site-packages/numpy/core: $PYTHONPATH [co...@jarrett core]$ python Python 2.6.2 (r262:71600, Jan 25 2010, 18:46:45) [GCC 4.4.2 20091222 (Red Hat 4.4.2-20)] on linux2 Type help, copyright, credits or license for more information. import umath_tests python: Modules/gcmodule.c:277: visit_decref: Assertion `gc-gc.gc_refs != 0' failed. Aborted (core dumped) so this import also trigger the crash at exit... Then it is clear that the umath_tests module does something that is not permitted. It's possible that there is a some sort of a refcount error somewhere in the generalized ufuncs mechanisms -- that part of Numpy is not heavily used. Bug spotting challenge: Start from umath_tests.c.src:initumath_tests, follow the execution, and spot the bug (if any). Pauli PS. it might be a good idea to file a bug ticket now ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] crash at prompt exit after running test
http://projects.scipy.org/numpy/ticket/1425 for the bug trac well, I do feel challenged now... ;) J On 03/10/2010 03:11 PM, Pauli Virtanen wrote: Wed, 10 Mar 2010 10:28:07 +0100, Johann Cohen-Tanugi wrote: On 03/10/2010 01:55 AM, Pauli Virtanen wrote: more fun : [co...@jarrett tests]$ pwd /home/cohen/sources/python/numpy/numpy/core/tests [co...@jarrett tests]$ python -c 'import test_ufunc' python: Modules/gcmodule.c:277: visit_decref: Assertion `gc-gc.gc_refs != 0' failed. Aborted (core dumped) What happens if you only import the umath_tests module (or something, it's a .so under numpy.core)? [co...@jarrett core]$ export PYTHONPATH=/home/cohen/.local/lib/python2.6/site-packages/numpy/core: $PYTHONPATH [co...@jarrett core]$ python Python 2.6.2 (r262:71600, Jan 25 2010, 18:46:45) [GCC 4.4.2 20091222 (Red Hat 4.4.2-20)] on linux2 Type help, copyright, credits or license for more information. import umath_tests python: Modules/gcmodule.c:277: visit_decref: Assertion `gc-gc.gc_refs != 0' failed. Aborted (core dumped) so this import also trigger the crash at exit... Then it is clear that the umath_tests module does something that is not permitted. It's possible that there is a some sort of a refcount error somewhere in the generalized ufuncs mechanisms -- that part of Numpy is not heavily used. Bug spotting challenge: Start from umath_tests.c.src:initumath_tests, follow the execution, and spot the bug (if any). Pauli PS. it might be a good idea to file a bug ticket now ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Backwards slicing including the first element
Jerome Esteve wrote: Dear all, Is there a way to give an integer value to j when using a[i:j:-1] so that the first element of the array can be included in the slice ? I would like to use some code like a[i:i-k:-1] to get a slice of length k. The numpy documentation seems to suggest that j=-1 should work: Assume n is the number of elements in the dimension being sliced. Then, if i is not given it defaults to 0 for k 0 and n for k 0 . If j is not given it defaults to n for k 0 and -1 for k 0 . If k is not given it defaults to 1. But a[i:i-k:-1] is empty if i-k is -1. The workaround is a[i::-1][:k], is there something simpler ? You could use a[i:i-(len(a)+k):-1]. This works because a[-len(a)] is the same as a[0]. For example: - In [57]: a Out[57]: array([10, 11, 12, 13, 14, 15, 16, 17, 18, 19]) In [58]: i = 3 In [59]: for k in range(5): : print k, a[i:i-(len(a)+k):-1] : : 0 [] 1 [13] 2 [13 12] 3 [13 12 11] 4 [13 12 11 10] - Warren Many thanks in advance, Jerome. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] crash at prompt exit after running test
Wed, 10 Mar 2010 15:40:04 +0100, Johann Cohen-Tanugi wrote: Pauli, isn't it hopeless to follow the execution of the source code when the crash actually occurs when I exit, and not when I execute. I would have to understand enough of this umath_tests.c.src to spot a refcount error or things like that Yeah, it's not easy, and requires knowing how to track this type of errors. I didn't actually mean that you should try do it, just posed it as a general challenge to all interested parties :) On a more serious note, maybe there's a compilation flag or something in Python that warns when refcounts go negative (or something). Cheers, Pauli ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] crash at prompt exit after running test
On 03/10/2010 08:40 AM, Johann Cohen-Tanugi wrote: Pauli, isn't it hopeless to follow the execution of the source code when the crash actually occurs when I exit, and not when I execute. I would have to understand enough of this umath_tests.c.src to spot a refcount error or things like that On 03/10/2010 03:11 PM, Pauli Virtanen wrote: Wed, 10 Mar 2010 10:28:07 +0100, Johann Cohen-Tanugi wrote: On 03/10/2010 01:55 AM, Pauli Virtanen wrote: more fun : [co...@jarrett tests]$ pwd /home/cohen/sources/python/numpy/numpy/core/tests [co...@jarrett tests]$ python -c 'import test_ufunc' python: Modules/gcmodule.c:277: visit_decref: Assertion `gc-gc.gc_refs != 0' failed. Aborted (core dumped) What happens if you only import the umath_tests module (or something, it's a .so under numpy.core)? [co...@jarrett core]$ export PYTHONPATH=/home/cohen/.local/lib/python2.6/site-packages/numpy/core: $PYTHONPATH [co...@jarrett core]$ python Python 2.6.2 (r262:71600, Jan 25 2010, 18:46:45) [GCC 4.4.2 20091222 (Red Hat 4.4.2-20)] on linux2 Type help, copyright, credits or license for more information. import umath_tests python: Modules/gcmodule.c:277: visit_decref: Assertion `gc-gc.gc_refs != 0' failed. Aborted (core dumped) so this import also trigger the crash at exit... Then it is clear that the umath_tests module does something that is not permitted. It's possible that there is a some sort of a refcount error somewhere in the generalized ufuncs mechanisms -- that part of Numpy is not heavily used. Bug spotting challenge: Start from umath_tests.c.src:initumath_tests, follow the execution, and spot the bug (if any). Pauli PS. it might be a good idea to file a bug ticket now ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion Hi, I can say that I have the same problem with Fedora 11 and Python 2.6 (both Fedora version and Unladen Swallow versions) with numpy 2.0.0.dev8272. However, I first noticed it with scipy but I see it with numpy. It does not appear to be with Python 2.5 with an svn version and I did not see it with numpy 1.3 or the removed numpy 1.4. Bruce ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Backwards slicing including the first element
Warren Weckesser wrote: Jerome Esteve wrote: Dear all, Is there a way to give an integer value to j when using a[i:j:-1] so that the first element of the array can be included in the slice ? I would like to use some code like a[i:i-k:-1] to get a slice of length k. The numpy documentation seems to suggest that j=-1 should work: Assume n is the number of elements in the dimension being sliced. Then, if i is not given it defaults to 0 for k 0 and n for k 0 . If j is not given it defaults to n for k 0 and -1 for k 0 . If k is not given it defaults to 1. But a[i:i-k:-1] is empty if i-k is -1. The workaround is a[i::-1][:k], is there something simpler ? You could use a[i:i-(len(a)+k):-1]. This works because a[-len(a)] is the same as a[0]. I'm going to be pedantic and amend that last sentence. While it is true the a[-len(a)] is the same as a[0], that is not why this works. A better explanation is that Python is lenient about handling the value given as the end position in a slice. It does not have to be a valid index. If the value is out of range, Python will include everything up to the end of the actual data, and it will not raise an error. So you can do slices like the following: - In [101]: w Out[101]: [10, 11, 12, 13, 14] In [102]: w[2:-5:-1] Out[102]: [12, 11] In [103]: w[2:-6:-1] Out[103]: [12, 11, 10] In [104]: w[2:-7:-1] Out[104]: [12, 11, 10] - Note that -6 and -7 are not valid indices; using w[-6] will raise an IndexError. Warren For example: - In [57]: a Out[57]: array([10, 11, 12, 13, 14, 15, 16, 17, 18, 19]) In [58]: i = 3 In [59]: for k in range(5): : print k, a[i:i-(len(a)+k):-1] : : 0 [] 1 [13] 2 [13 12] 3 [13 12 11] 4 [13 12 11 10] - Warren Many thanks in advance, Jerome. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Backwards slicing including the first element
On Wed, Mar 10, 2010 at 10:19 AM, Warren Weckesser warren.weckes...@enthought.com wrote: Warren Weckesser wrote: Jerome Esteve wrote: Dear all, Is there a way to give an integer value to j when using a[i:j:-1] so that the first element of the array can be included in the slice ? I would like to use some code like a[i:i-k:-1] to get a slice of length k. The numpy documentation seems to suggest that j=-1 should work: Assume n is the number of elements in the dimension being sliced. Then, if i is not given it defaults to 0 for k 0 and n for k 0 . If j is not given it defaults to n for k 0 and -1 for k 0 . If k is not given it defaults to 1. But a[i:i-k:-1] is empty if i-k is -1. The workaround is a[i::-1][:k], is there something simpler ? You could use a[i:i-(len(a)+k):-1]. This works because a[-len(a)] is the same as a[0]. I'm going to be pedantic and amend that last sentence. While it is true the a[-len(a)] is the same as a[0], that is not why this works. A better explanation is that Python is lenient about handling the value given as the end position in a slice. It does not have to be a valid index. If the value is out of range, Python will include everything up to the end of the actual data, and it will not raise an error. So you can do slices like the following: - In [101]: w Out[101]: [10, 11, 12, 13, 14] In [102]: w[2:-5:-1] Out[102]: [12, 11] In [103]: w[2:-6:-1] Out[103]: [12, 11, 10] In [104]: w[2:-7:-1] Out[104]: [12, 11, 10] - Note that -6 and -7 are not valid indices; using w[-6] will raise an IndexError. Warren For example: - In [57]: a Out[57]: array([10, 11, 12, 13, 14, 15, 16, 17, 18, 19]) In [58]: i = 3 In [59]: for k in range(5): : print k, a[i:i-(len(a)+k):-1] : : 0 [] 1 [13] 2 [13 12] 3 [13 12 11] 4 [13 12 11 10] - I thought, I had also used the -1 before, but it only works with range, e.g. [(i,i-k,np.arange(5)[range(i,i-k,-1)]) for i in range(1,5)] [(1, -1, array([1, 0])), (2, 0, array([2, 1])), (3, 1, array([3, 2])), (4, 2, array([4, 3]))] the or None trick is more complicated when counting down [(i,i-k,np.arange(5)[i:(i-k if (i-k!=-1) else None):-1]) for i in range(1,5)] [(1, -1, array([1, 0])), (2, 0, array([2, 1])), (3, 1, array([3, 2])), (4, 2, array([4, 3]))] I will mark Warrens solution as something to remember. Josef Warren Many thanks in advance, Jerome. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] crash at prompt exit after running test
On 03/10/2010 08:59 AM, Pauli Virtanen wrote: Wed, 10 Mar 2010 15:40:04 +0100, Johann Cohen-Tanugi wrote: Pauli, isn't it hopeless to follow the execution of the source code when the crash actually occurs when I exit, and not when I execute. I would have to understand enough of this umath_tests.c.src to spot a refcount error or things like that Yeah, it's not easy, and requires knowing how to track this type of errors. I didn't actually mean that you should try do it, just posed it as a general challenge to all interested parties :) On a more serious note, maybe there's a compilation flag or something in Python that warns when refcounts go negative (or something). Cheers, Pauli ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion Hi, I think I managed to find this. I reverted back my svn versions ($svn update -r 8262) and cleaned both the build and installation directories. It occurred with changeset 8262 (earlier changesets appear okay but later ones do not) http://projects.scipy.org/numpy/changeset/8262 Specifically in the file: numpy/core/code_generators/generate_ufunc_api.py There is an extra call to that should have been deleted on line 54(?). Py_DECREF(numpy); Attached a patch to ticket 1425 http://projects.scipy.org/numpy/ticket/1425 Bruce ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Backwards slicing including the first element
Jerome Esteve wrote: Is there a way to give an integer value to j when using a[i:j:-1] so that the first element of the array can be included in the slice ? Is this what you are looking for? In [11]: a = np.arange(10) In [12]: a[6::-1] Out[12]: array([6, 5, 4, 3, 2, 1, 0]) I know it's not an integer, but it does indicate the last (or first) element of the array -Chris -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/ORR(206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception chris.bar...@noaa.gov ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] crash at prompt exit after running test
On Wed, Mar 10, 2010 at 10:39 AM, Bruce Southey bsout...@gmail.com wrote: On 03/10/2010 08:59 AM, Pauli Virtanen wrote: Wed, 10 Mar 2010 15:40:04 +0100, Johann Cohen-Tanugi wrote: Pauli, isn't it hopeless to follow the execution of the source code when the crash actually occurs when I exit, and not when I execute. I would have to understand enough of this umath_tests.c.src to spot a refcount error or things like that Yeah, it's not easy, and requires knowing how to track this type of errors. I didn't actually mean that you should try do it, just posed it as a general challenge to all interested parties :) On a more serious note, maybe there's a compilation flag or something in Python that warns when refcounts go negative (or something). Cheers, Pauli ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion Hi, I think I managed to find this. I reverted back my svn versions ($svn update -r 8262) and cleaned both the build and installation directories. It occurred with changeset 8262 (earlier changesets appear okay but later ones do not) http://projects.scipy.org/numpy/changeset/8262 Specifically in the file: numpy/core/code_generators/generate_ufunc_api.py There is an extra call to that should have been deleted on line 54(?). Py_DECREF(numpy); Attached a patch to ticket 1425 http://projects.scipy.org/numpy/ticket/1425 Look like my bad. I'm out of town at the moment so someone else needs to apply the patch. That whole bit of code could probably use a daylight audit. Chuck ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] numarray iterator question
This is a bit confusing to me: import numpy as np u = np.ones ((3,3)) for u_row in u: u_row = u_row * 2 doesn't work print u [[ 1. 1. 1.] [ 1. 1. 1.] [ 1. 1. 1.]] for u_row in u: u_row *= 2 does work [[ 2. 2. 2.] [ 2. 2. 2.] [ 2. 2. 2.]] Naively, I'm thinking a *= b === a = a * b. Is this behavior expected? I'm asking because I really want: u_row = my_func (u_row) ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] numarray iterator question
On Wed, Mar 10, 2010 at 18:19, Neal Becker ndbeck...@gmail.com wrote: This is a bit confusing to me: import numpy as np u = np.ones ((3,3)) for u_row in u: u_row = u_row * 2 doesn't work print u [[ 1. 1. 1.] [ 1. 1. 1.] [ 1. 1. 1.]] for u_row in u: u_row *= 2 does work [[ 2. 2. 2.] [ 2. 2. 2.] [ 2. 2. 2.]] Naively, I'm thinking a *= b === a = a * b. http://docs.python.org/reference/simple_stmts.html#augmented-assignment-statements An augmented assignment expression like x += 1 can be rewritten as x = x + 1 to achieve a similar, but not exactly equal effect. In the augmented version, x is only evaluated once. Also, when possible, the actual operation is performed in-place, meaning that rather than creating a new object and assigning that to the target, the old object is modified instead. Is this behavior expected? I'm asking because I really want: u_row = my_func (u_row) Iterate over indices instead: for i in range(len(u)): u[i] = my_func(u[i]) -- Robert Kern I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth. -- Umberto Eco ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] numarray iterator question
Neal Becker wrote: This is a bit confusing to me: import numpy as np u = np.ones ((3,3)) for u_row in u: u_row = u_row * 2 doesn't work Try this instead: for u_row in u: u_row[:] = u_row * 2 Warren print u [[ 1. 1. 1.] [ 1. 1. 1.] [ 1. 1. 1.]] for u_row in u: u_row *= 2 does work [[ 2. 2. 2.] [ 2. 2. 2.] [ 2. 2. 2.]] Naively, I'm thinking a *= b === a = a * b. Is this behavior expected? I'm asking because I really want: u_row = my_func (u_row) ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
