Hi, I'm using ipython 0.9.1 with the svn version of matplotlib on 64 bit
python on mac os x 10.5.7.
I have only been able to get python-64 running with the MacOSX backend; all
of the others (wxpython, gtk, qt, tk) have failed for one reason or another.
I've tried ipython without any flags and
OK, thanks. I don't really know why it's failing, but I'm going to continue
trying to get other backends installed to test them.
I also now have independent reasons not to use the MacOSX backend:
Thu Jul 2 14:51:48 Python-64[56094] Error: CGContextSetLineDash: invalid
dash array: negative
Hi, I'm trying to make a large grid of subplots with no spacing between. The
following code fails for any grid size larger than 6x6 by skipping a row and
a column.
for i in xrange(1,65):
subplot(8,8,i)
plot( [0,1] )
subplots_adjust(hspace=0,wspace=0)
Is there a way around this
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.
Since there don't seem to be any forthcoming answers, I have a somewhat
different question. In the matplotlib FAQ, it states that using 'show()'
puts you in the GUI mainloop
(http://matplotlib.sourceforge.net/faq/howto_faq.html#use-show). However,
using plot commands on the ipython command line
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.
Hi, I'm trying to plot a series of ~30-50 small plots, each of which contains
3 plots of ~10-20 points (one plot is data, one plot is errorbars, one plot
is a model fit). I've tried using GtkAgg and Qt4Agg as backends, and both
are extremely slow - they take ~5-10 seconds for the first plot
Jouni K. Seppänen wrote:
keflavich keflav...@gmail.com writes:
I tried the same series of plot commands using the SVG, PS, and PDF
backends
and the whole series of 50 plots takes ~1s.
Did you produce any output with savefig? 50 plots per second sounds
pretty fast - at least on my
John Hunter-4 wrote:
That does sound exceedingly slow -- it looks like you are having some
problems with the GUI or environment and not just the mpl component. How
are you running and profiling your script? Can you post some
free-standing
example code which exposes the problem? Can
So, as the Matplotlib help page suggests, working through a test problem
helped me narrow down my problem... but it still hasn't solved it. If I set
ioff() at the main level, rather than in a function I call, it works.
However, when I show() the plot, the code halts until I close it, which is
John Hunter-4 wrote:
Ahh, mixing matplotlib.use from an interactive ipython session -- that is
an
important detail :-) What is your backend (import matplotlib; print
matplotlib.rcParams['backend']) It is quite likely that you are getting
cross GUI / cross threading problems from
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