matplotlib-devel Mailing List for matplotlib

On Fri, Dec 08, 2006 at 01:54:56PM -0600, Glen W. Mabey wrote:
> On Fri, Dec 08, 2006 at 01:44:03PM -0600, John Hunter wrote:
> > >>>>> "Glen" == Glen W Mabey <Gle...@sw...> writes:
> > 
> > Glen> Hello, I've just switched to Python 2.5 and at the same time
> > Glen> upgraded to numpy 1.0.1 with today's svn matplotlib, using
> > Glen> the QtAgg backend (PyQt3 3.17). This is on an AMD64
> > Glen> (Opteron) machine.
> > 
> > Glen> I get a segfault after these operations:
> > 
> > Glen> In [1]:import numpy as N In [2]:specgram( N.random.randn(
> > Glen> 256*500 ) ) Segmentation fault (core dumped)
> > 
> > 1) Are you sure that matplotlib's numerix setting is numpy?
> 
> Yep. It has been for a long time.
> 
> > 2) Did you do a *clean* build of mpl: ie 
> > > sudo rm -rf build
> > > sudo python setup.py install
> 
> I'm pretty sure it was clean, because I upgraded to the svn version at
> the same time. I'm rebuilding it now, though, just to make sure, and
> I'll post if there is any difference in result.
Okay, it's just my fault. Turns out there is only a segfault when I
include a patch I'm working on ...
Thanks again,
Glen

On Fri, Dec 08, 2006 at 01:44:03PM -0600, John Hunter wrote:
> >>>>> "Glen" == Glen W Mabey <Gle...@sw...> writes:
> 
> Glen> Hello, I've just switched to Python 2.5 and at the same time
> Glen> upgraded to numpy 1.0.1 with today's svn matplotlib, using
> Glen> the QtAgg backend (PyQt3 3.17). This is on an AMD64
> Glen> (Opteron) machine.
> 
> Glen> I get a segfault after these operations:
> 
> Glen> In [1]:import numpy as N In [2]:specgram( N.random.randn(
> Glen> 256*500 ) ) Segmentation fault (core dumped)
> 
> 1) Are you sure that matplotlib's numerix setting is numpy?
Yep. It has been for a long time.
> 2) Did you do a *clean* build of mpl: ie 
> > sudo rm -rf build
> > sudo python setup.py install
I'm pretty sure it was clean, because I upgraded to the svn version at
the same time. I'm rebuilding it now, though, just to make sure, and
I'll post if there is any difference in result.
Thanks for your suggestions.
Glen

>>>>> "Glen" == Glen W Mabey <Gle...@sw...> writes:
 Glen> Hello, I've just switched to Python 2.5 and at the same time
 Glen> upgraded to numpy 1.0.1 with today's svn matplotlib, using
 Glen> the QtAgg backend (PyQt3 3.17). This is on an AMD64
 Glen> (Opteron) machine.
 Glen> I get a segfault after these operations:
 Glen> In [1]:import numpy as N In [2]:specgram( N.random.randn(
 Glen> 256*500 ) ) Segmentation fault (core dumped)
1) Are you sure that matplotlib's numerix setting is numpy?
2) Did you do a *clean* build of mpl: ie 
 > sudo rm -rf build
 > sudo python setup.py install
The latter is very important when upgrading Numeric/numpy/numarray
It could be an AMD64 bit problem, though...
JDH

Hello,
I've just switched to Python 2.5 and at the same time upgraded to numpy
1.0.1 with today's svn matplotlib, using the QtAgg backend (PyQt3 3.17).
This is on an AMD64 (Opteron) machine.
I get a segfault after these operations:
In [1]:import numpy as N
In [2]:specgram( N.random.randn( 256*500 ) )
Segmentation fault (core dumped)
I don't know if this will help, but here is the backtrace:
(gdb) bt
#0 0x00002aaab37e2ac8 in Image::flipud_out (this=0xf9bf10, args=@0x7fffffc5d200) at _image.cpp:110
#1 0x00002aaab3829df4 in RendererAgg::draw_image (this=0xf04980, args=@0x7fffffc5d350) at _ns_backend_agg.cpp:1994
#2 0x00002aaab3840367 in Py::PythonExtension<RendererAgg>::method_varargs_call_handler (_self_and_name_tuple=<value optimized out>, _args=0x2aaab397bdb8)
 at Extensions.hxx:683
#3 0x00002aaaaac826dc in PyEval_EvalFrameEx (f=0xf76550, throwflag=<value optimized out>) at ceval.c:3566
#4 0x00002aaaaac82e00 in PyEval_EvalCodeEx (co=0x2aaab34115d0, globals=<value optimized out>, locals=<value optimized out>, args=0xf764c8, argcount=2, kws=0xf764d8, 
 kwcount=0, defs=0x0, defcount=0, closure=0x0) at ceval.c:2833
#5 0x00002aaaaac81cdc in PyEval_EvalFrameEx (f=0xf762c0, throwflag=<value optimized out>) at ceval.c:3662
#6 0x00002aaaaac82e00 in PyEval_EvalCodeEx (co=0x2aaab2a35648, globals=<value optimized out>, locals=<value optimized out>, args=0x2, argcount=2, kws=0xf08a88, 
 kwcount=0, defs=0x2aaab3679068, defcount=2, closure=0x0) at ceval.c:2833
#7 0x00002aaaaac81cdc in PyEval_EvalFrameEx (f=0xf08880, throwflag=<value optimized out>) at ceval.c:3662
#8 0x00002aaaaac81d79 in PyEval_EvalFrameEx (f=0xf069f0, throwflag=<value optimized out>) at ceval.c:3652
#9 0x00002aaaaac82e00 in PyEval_EvalCodeEx (co=0x2aaab37a5a08, globals=<value optimized out>, locals=<value optimized out>, args=0x2aaab39641e8, argcount=1, kws=0x0, 
 kwcount=0, defs=0x0, defcount=0, closure=0x0) at ceval.c:2833
#10 0x00002aaaaac21779 in function_call (func=0x2aaab3708938, arg=0x2aaab39641d0, kw=0x0) at funcobject.c:517
#11 0x00002aaaaabff8c1 in PyObject_Call (func=<value optimized out>, arg=<value optimized out>, kw=<value optimized out>) at abstract.c:1860
#12 0x00002aaaaac08144 in instancemethod_call (func=<value optimized out>, arg=0x2aaab39641d0, kw=0x0) at classobject.c:2493
#13 0x00002aaaaabff8c1 in PyObject_Call (func=<value optimized out>, arg=<value optimized out>, kw=<value optimized out>) at abstract.c:1860
#14 0x00002aaaaac80f1e in PyEval_EvalFrameEx (f=0xf06620, throwflag=<value optimized out>) at ceval.c:3777
#15 0x00002aaaaac82e00 in PyEval_EvalCodeEx (co=0x2aaaad6e3c60, globals=<value optimized out>, locals=<value optimized out>, args=0x2aaab3715c38, argcount=2, kws=0x0, 
 kwcount=0, defs=0x0, defcount=0, closure=0x0) at ceval.c:2833
#16 0x00002aaaaac21779 in function_call (func=0x2aaab3728230, arg=0x2aaab3715c20, kw=0x0) at funcobject.c:517
#17 0x00002aaaaabff8c1 in PyObject_Call (func=<value optimized out>, arg=<value optimized out>, kw=<value optimized out>) at abstract.c:1860
#18 0x00002aaaaac08144 in instancemethod_call (func=<value optimized out>, arg=0x2aaab3715c20, kw=0x0) at classobject.c:2493
#19 0x00002aaaaabff8c1 in PyObject_Call (func=<value optimized out>, arg=<value optimized out>, kw=<value optimized out>) at abstract.c:1860
I don't get the same error on a P4 machine with the same setup except
using Python 2.4.
For some reason I thought that matplotlib supported 2.5, but then I
started looking and couldn't see that documented anywhere. Does it?
Thanks,
Glen Mabey