Re: [Matplotlib-users] Segmentation fault using imshow on large image
Anyone else have ideas on how to display large images? Thanks, Adam -- View this message in context: http://www.nabble.com/Segmentation-fault-using-imshow-on-large-image-tp23207792p24152022.html Sent from the matplotlib - users mailing list archive at Nabble.com. -- Are you an open source citizen? Join us for the Open Source Bridge conference! Portland, OR, June 17-19. Two days of sessions, one day of unconference: $250. Need another reason to go? 24-hour hacker lounge. Register today! http://ad.doubleclick.net/clk;215844324;13503038;v?http://opensourcebridge.org ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Segmentation fault using imshow on large image
Bugzilla from tkjacob...@gmail.com wrote: > > Hi > > It could be that you just have to much data for the stack. You can see/set > your stack size with ulimit -s (on linux/solaris at least). Try to set it > to > unlimited: > ulimit -s unlimited > > This has solved similar problems for me in the past. > > Best Regards > Troels Kofoed Jacobsen > Tried it, no luck. Thanks for the tip, though. -- View this message in context: http://www.nabble.com/Segmentation-fault-using-imshow-on-large-image-tp23207792p23260454.html Sent from the matplotlib - users mailing list archive at Nabble.com. -- Crystal Reports - New Free Runtime and 30 Day Trial Check out the new simplified licensign option that enables unlimited royalty-free distribution of the report engine for externally facing server and web deployment. http://p.sf.net/sfu/businessobjects ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Segmentation fault using imshow on large image
A 1x1 array reproduces the error: milkyway /data/glimpseii $ gdb /usr/local/python/bin/python GNU gdb Red Hat Linux (6.3.0.0-1.159.el4rh) Copyright 2004 Free Software Foundation, Inc. GDB is free software, covered by the GNU General Public License, and you are welcome to change it and/or distribute copies of it under certain conditions. Type "show copying" to see the conditions. There is absolutely no warranty for GDB. Type "show warranty" for details. This GDB was configured as "x86_64-redhat-linux-gnu"...Using host libthread_db library "/lib64/tls/libthread_db.so.1". (gdb) run Starting program: /usr/local/python/bin/python [Thread debugging using libthread_db enabled] [New Thread 182900715072 (LWP 19947)] Python 2.5 (r25:51908, Dec 22 2006, 16:08:43) [GCC 3.4.6 20060404 (Red Hat 3.4.6-3)] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> from pylab import * >>> x=rand(1,1) >>> imshow(x) >>> show() Program received signal SIGSEGV, Segmentation fault. [Switching to Thread 182900715072 (LWP 19947)] 0x002a9eac7ab5 in _image_module::fromarray (this=Variable "this" is not available. ) at src/image.cpp:872 872 src/image.cpp: No such file or directory. in src/image.cpp Current language: auto; currently c++ (gdb) > Could you try and create an image using random data that is the same > dimensions and datatype as the fits data you are using htat replicates the > segfault, so we can try and reproduce the error as well as add it to our > test suite? > > Thanks > JDH > > > -- Crystal Reports - New Free Runtime and 30 Day Trial Check out the new simplified licensign option that enables unlimited royalty-free distribution of the report engine for externally facing server and web deployment. http://p.sf.net/sfu/businessobjects ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Segmentation fault using imshow on large image
Hi
It could be that you just have to much data for the stack. You can see/set
your stack size with ulimit -s (on linux/solaris at least). Try to set it to
unlimited:
ulimit -s unlimited
This has solved similar problems for me in the past.
Best Regards
Troels Kofoed Jacobsen
On Saturday 25 April 2009 16:53:27 Adam Ginsburg wrote:
> Yep, I'm running on a 64 bit machine. I've been dealing with larger
> than 4GB data files in IDL, but I'd rather use python/numpy/matplotlib
> if possible.
>
> Here's the gdb session. The error didn't happen in imshow, only when
> I specified show(); I guess that means I must have had ioff() set
> although I don't think that was my default choice last time I used
> matplotlib.
>
>
> milkyway /data/glimpseii $ gdb /usr/local/python/bin/python
> GNU gdb Red Hat Linux (6.3.0.0-1.159.el4rh)
> Copyright 2004 Free Software Foundation, Inc.
> GDB is free software, covered by the GNU General Public License, and you
> are welcome to change it and/or distribute copies of it under certain
> conditions. Type "show copying" to see the conditions.
> There is absolutely no warranty for GDB. Type "show warranty" for details.
> This GDB was configured as "x86_64-redhat-linux-gnu"...Using host
> libthread_db library "/lib64/tls/libthread_db.so.1".
>
> (gdb) run
> Starting program: /usr/local/python/bin/python
> [Thread debugging using libthread_db enabled]
> [New Thread 182900715072 (LWP 18039)]
> Python 2.5 (r25:51908, Dec 22 2006, 16:08:43)
> [GCC 3.4.6 20060404 (Red Hat 3.4.6-3)] on linux2
> Type "help", "copyright", "credits" or "license" for more information.
>
> >>> import matplotlib,scipy,numpy,pyfits
> >>> from pylab import *
> >>> f = pyfits.open('GLM_00600+_mosaic_I3.fits')
> >>> imshow(f[0].data)
>
>
>
> >>> show()
>
> Program received signal SIGSEGV, Segmentation fault.
> [Switching to Thread 182900715072 (LWP 18039)]
> 0x002aa3170ab5 in _image_module::fromarray (this=Variable "this"
> is not available.
> ) at src/image.cpp:872
> 872 src/image.cpp: No such file or directory.
> in src/image.cpp
> Current language: auto; currently c++
> (gdb)
>
>
> I've never used gdb before, so is there anything else I should be
> doing at this point?
>
> Thanks,
> Adam
>
> On Fri, Apr 24, 2009 at 7:52 AM, Michael Droettboom
wrote:
> > On my machine (32-bit Fedora 10 with 2GB RAM), it chugs along swapping
> > for a lng time and then fails with a Python MemoryError exception --
> > which is at least reasonable.
> >
> > I suspect you're running on a 64-bit machine and we're running into some
> > sort of non-64-bit-clean issue. We try to be 64-bit clean, but it
> > doesn't get verified on a regular basis, and not all of us (myself
> > included) are running 64-bit OSes.
> >
> > Can you try running python inside of gdb and getting a traceback? That
> > might provide some clues.
> >
> > We can estimate a little bit as to the memory requirements -- though it's
> > hard to account for everything.
> >
> > Input array is (10370, 9320) x 4 = 386MB
> > This array is always converted to doubles to convert to colors (this is
> > probably a place ripe for opimtization) so you get also 786MB. Then this
> > gets converted to an RGBA array for another 386MB
> >
> > Mike
> >
> > Adam Ginsburg wrote:
> >> Hi, I've been getting a segmentation fault when trying to display
> >> large images. A transcript of a sample session is below. I'm using
> >> the TkAgg backend, and I am using numpy, but otherwise I have made no
> >> modifications to the matplotlib setup.
> >>
> >>
> >> milkyway /data/glimpseii $ alias pylab
> >> alias pylab='/usr/local/adm/config/python/bin/ipython -pylab -log'
> >> milkyway /data/glimpseii $ pylab
> >> Activating auto-logging. Current session state plus future input saved.
> >> Filename : ipython_log.py
> >> Mode : rotate
> >> Output logging : False
> >> Raw input log : False
> >> Timestamping : False
> >> State : active
> >> Python 2.5 (r25:51908, Dec 22 2006, 16:08:43)
> >> Type "copyright", "credits" or "license" for more information.
> >>
> >> IPython 0.9.1 -- An enhanced Interactive Python.
> >> ? -> Introduction and overview of IPython's features.
> >> %quickref -> Quick reference.
> >> help -> Python's own help system.
> >> object? -> Details about 'object'. ?object also works, ?? prints more.
> >>
> >> Welcome to pylab, a matplotlib-based Python environment.
> >> For more information, type 'help(pylab)'.
> >>
> >> In [1]: import matplotlib,pyfits,numpy,scipy
> >>
> >> In [2]: scipy.__version__
> >> Out[2]: '0.7.0'
> >>
> >> In [3]: numpy.__version__
> >> Out[3]: '1.3.0'
> >>
> >> In [4]: matplotlib.__version__
> >> Out[4]: '0.98.5.2'
> >>
> >> In [5]: f = pyfits.open('GLM_00600+_mosaic_I3.fits')
> >>
> >> In [6]: f[0].data.shape
> >> Out[6]: (10370, 9320)
> >>
> >> In [7]: f[0].data.dtype
> >> Out[7]: dtype('>f4')
> >>
> >> In [8]: imshow(f[0].data)
> >> Segmentation fault
> >>
> >>
> >> Any ideas?
> >>
>
Re: [Matplotlib-users] Segmentation fault using imshow on large image
On Sat, Apr 25, 2009 at 9:53 AM, Adam Ginsburg
wrote:
> Yep, I'm running on a 64 bit machine. I've been dealing with larger
> than 4GB data files in IDL, but I'd rather use python/numpy/matplotlib
> if possible.
>
> Here's the gdb session. The error didn't happen in imshow, only when
> I specified show(); I guess that means I must have had ioff() set
> although I don't think that was my default choice last time I used
> matplotlib.
>
>
> milkyway /data/glimpseii $ gdb /usr/local/python/bin/python
> GNU gdb Red Hat Linux (6.3.0.0-1.159.el4rh)
> Copyright 2004 Free Software Foundation, Inc.
> GDB is free software, covered by the GNU General Public License, and you
> are
> welcome to change it and/or distribute copies of it under certain
> conditions.
> Type "show copying" to see the conditions.
> There is absolutely no warranty for GDB. Type "show warranty" for details.
> This GDB was configured as "x86_64-redhat-linux-gnu"...Using host
> libthread_db library "/lib64/tls/libthread_db.so.1".
>
> (gdb) run
> Starting program: /usr/local/python/bin/python
> [Thread debugging using libthread_db enabled]
> [New Thread 182900715072 (LWP 18039)]
> Python 2.5 (r25:51908, Dec 22 2006, 16:08:43)
> [GCC 3.4.6 20060404 (Red Hat 3.4.6-3)] on linux2
> Type "help", "copyright", "credits" or "license" for more information.
> >>> import matplotlib,scipy,numpy,pyfits
> >>> from pylab import *
> >>> f = pyfits.open('GLM_00600+_mosaic_I3.fits')
> >>> imshow(f[0].data)
>
> >>> show()
>
> Program received signal SIGSEGV, Segmentation fault.
> [Switching to Thread 182900715072 (LWP 18039)]
> 0x002aa3170ab5 in _image_module::fromarray (this=Variable "this"
> is not available.
> ) at src/image.cpp:872
> 872 src/image.cpp: No such file or directory.
> in src/image.cpp
> Current language: auto; currently c++
> (gdb)
>
Could you try and create an image using random data that is the same
dimensions and datatype as the fits data you are using htat replicates the
segfault, so we can try and reproduce the error as well as add it to our
test suite?
Thanks
JDH
--
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Re: [Matplotlib-users] Segmentation fault using imshow on large image
Yep, I'm running on a 64 bit machine. I've been dealing with larger
than 4GB data files in IDL, but I'd rather use python/numpy/matplotlib
if possible.
Here's the gdb session. The error didn't happen in imshow, only when
I specified show(); I guess that means I must have had ioff() set
although I don't think that was my default choice last time I used
matplotlib.
milkyway /data/glimpseii $ gdb /usr/local/python/bin/python
GNU gdb Red Hat Linux (6.3.0.0-1.159.el4rh)
Copyright 2004 Free Software Foundation, Inc.
GDB is free software, covered by the GNU General Public License, and you are
welcome to change it and/or distribute copies of it under certain conditions.
Type "show copying" to see the conditions.
There is absolutely no warranty for GDB. Type "show warranty" for details.
This GDB was configured as "x86_64-redhat-linux-gnu"...Using host
libthread_db library "/lib64/tls/libthread_db.so.1".
(gdb) run
Starting program: /usr/local/python/bin/python
[Thread debugging using libthread_db enabled]
[New Thread 182900715072 (LWP 18039)]
Python 2.5 (r25:51908, Dec 22 2006, 16:08:43)
[GCC 3.4.6 20060404 (Red Hat 3.4.6-3)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import matplotlib,scipy,numpy,pyfits
>>> from pylab import *
>>> f = pyfits.open('GLM_00600+_mosaic_I3.fits')
>>> imshow(f[0].data)
>>> show()
Program received signal SIGSEGV, Segmentation fault.
[Switching to Thread 182900715072 (LWP 18039)]
0x002aa3170ab5 in _image_module::fromarray (this=Variable "this"
is not available.
) at src/image.cpp:872
872 src/image.cpp: No such file or directory.
in src/image.cpp
Current language: auto; currently c++
(gdb)
I've never used gdb before, so is there anything else I should be
doing at this point?
Thanks,
Adam
On Fri, Apr 24, 2009 at 7:52 AM, Michael Droettboom wrote:
>
> On my machine (32-bit Fedora 10 with 2GB RAM), it chugs along swapping for a
> lng time and then fails with a Python MemoryError exception -- which is
> at least reasonable.
>
> I suspect you're running on a 64-bit machine and we're running into some sort
> of non-64-bit-clean issue. We try to be 64-bit clean, but it doesn't get
> verified on a regular basis, and not all of us (myself included) are running
> 64-bit OSes.
>
> Can you try running python inside of gdb and getting a traceback? That might
> provide some clues.
>
> We can estimate a little bit as to the memory requirements -- though it's
> hard to account for everything.
>
> Input array is (10370, 9320) x 4 = 386MB
> This array is always converted to doubles to convert to colors (this is
> probably a place ripe for opimtization) so you get also 786MB.
> Then this gets converted to an RGBA array for another 386MB
>
> Mike
>
> Adam Ginsburg wrote:
>>
>> Hi, I've been getting a segmentation fault when trying to display
>> large images. A transcript of a sample session is below. I'm using
>> the TkAgg backend, and I am using numpy, but otherwise I have made no
>> modifications to the matplotlib setup.
>>
>>
>> milkyway /data/glimpseii $ alias pylab
>> alias pylab='/usr/local/adm/config/python/bin/ipython -pylab -log'
>> milkyway /data/glimpseii $ pylab
>> Activating auto-logging. Current session state plus future input saved.
>> Filename : ipython_log.py
>> Mode : rotate
>> Output logging : False
>> Raw input log : False
>> Timestamping : False
>> State : active
>> Python 2.5 (r25:51908, Dec 22 2006, 16:08:43)
>> Type "copyright", "credits" or "license" for more information.
>>
>> IPython 0.9.1 -- An enhanced Interactive Python.
>> ? -> Introduction and overview of IPython's features.
>> %quickref -> Quick reference.
>> help -> Python's own help system.
>> object? -> Details about 'object'. ?object also works, ?? prints more.
>>
>> Welcome to pylab, a matplotlib-based Python environment.
>> For more information, type 'help(pylab)'.
>>
>> In [1]: import matplotlib,pyfits,numpy,scipy
>>
>> In [2]: scipy.__version__
>> Out[2]: '0.7.0'
>>
>> In [3]: numpy.__version__
>> Out[3]: '1.3.0'
>>
>> In [4]: matplotlib.__version__
>> Out[4]: '0.98.5.2'
>>
>> In [5]: f = pyfits.open('GLM_00600+_mosaic_I3.fits')
>>
>> In [6]: f[0].data.shape
>> Out[6]: (10370, 9320)
>>
>> In [7]: f[0].data.dtype
>> Out[7]: dtype('>f4')
>>
>> In [8]: imshow(f[0].data)
>> Segmentation fault
>>
>>
>> Any ideas?
>>
>> Thanks,
>> Adam
>>
--
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royalty-free distribution of the report engine for externally facing
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Re: [Matplotlib-users] Segmentation fault using imshow on large image
On my machine (32-bit Fedora 10 with 2GB RAM), it chugs along swapping
for a lng time and then fails with a Python MemoryError exception --
which is at least reasonable.
I suspect you're running on a 64-bit machine and we're running into some
sort of non-64-bit-clean issue. We try to be 64-bit clean, but it
doesn't get verified on a regular basis, and not all of us (myself
included) are running 64-bit OSes.
Can you try running python inside of gdb and getting a traceback? That
might provide some clues.
We can estimate a little bit as to the memory requirements -- though
it's hard to account for everything.
Input array is (10370, 9320) x 4 = 386MB
This array is always converted to doubles to convert to colors (this is
probably a place ripe for opimtization) so you get also 786MB.
Then this gets converted to an RGBA array for another 386MB
Mike
Adam Ginsburg wrote:
> Hi, I've been getting a segmentation fault when trying to display
> large images. A transcript of a sample session is below. I'm using
> the TkAgg backend, and I am using numpy, but otherwise I have made no
> modifications to the matplotlib setup.
>
>
> milkyway /data/glimpseii $ alias pylab
> alias pylab='/usr/local/adm/config/python/bin/ipython -pylab -log'
> milkyway /data/glimpseii $ pylab
> Activating auto-logging. Current session state plus future input saved.
> Filename : ipython_log.py
> Mode : rotate
> Output logging : False
> Raw input log : False
> Timestamping : False
> State : active
> Python 2.5 (r25:51908, Dec 22 2006, 16:08:43)
> Type "copyright", "credits" or "license" for more information.
>
> IPython 0.9.1 -- An enhanced Interactive Python.
> ? -> Introduction and overview of IPython's features.
> %quickref -> Quick reference.
> help -> Python's own help system.
> object? -> Details about 'object'. ?object also works, ?? prints more.
>
> Welcome to pylab, a matplotlib-based Python environment.
> For more information, type 'help(pylab)'.
>
> In [1]: import matplotlib,pyfits,numpy,scipy
>
> In [2]: scipy.__version__
> Out[2]: '0.7.0'
>
> In [3]: numpy.__version__
> Out[3]: '1.3.0'
>
> In [4]: matplotlib.__version__
> Out[4]: '0.98.5.2'
>
> In [5]: f = pyfits.open('GLM_00600+_mosaic_I3.fits')
>
> In [6]: f[0].data.shape
> Out[6]: (10370, 9320)
>
> In [7]: f[0].data.dtype
> Out[7]: dtype('>f4')
>
> In [8]: imshow(f[0].data)
> Segmentation fault
>
>
> Any ideas?
>
> Thanks,
> Adam
>
> --
> Crystal Reports - New Free Runtime and 30 Day Trial
> Check out the new simplified licensign option that enables unlimited
> royalty-free distribution of the report engine for externally facing
> server and web deployment.
> http://p.sf.net/sfu/businessobjects
> ___
> Matplotlib-users mailing list
> Matplotlib-users@lists.sourceforge.net
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
--
Crystal Reports - New Free Runtime and 30 Day Trial
Check out the new simplified licensign option that enables unlimited
royalty-free distribution of the report engine for externally facing
server and web deployment.
http://p.sf.net/sfu/businessobjects
___
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