Hello everyone,
I would like to draw the attention on the slow startup of matplotlib.
Indeed, running matplotlib takes a long time.
I performed the following sequence :
```bash
#!/bin/bash
for i in * ; do python2 -c "from temp import * ; plot_(\"${i}\") " ; done
```
with temp.py like this :
```python
#!/usr/bin/env python2
import sys
import matplotlib.pyplot as plt
import read_data as rd
import numpy
def plot_( fname ):
P,I = rd.read_data(fname)
Iprime = [ l / k for k , l in zip( numpy.diff(P) , numpy.diff(I) ) ]
fig = plt.figure()
ax1 = fig.add_subplot(211)
ax2 = fig.add_subplot(212)
ax1.plot(P,I)
ax2.plot(P[:-1],Iprime)
fig.savefig( fname + ".pdf", format='pdf' )
```
And it seems the longer operation is to import matplotlib.pyplot.
Does something could be done to improve the loading time of this module ?
Thank you very much.
greatings,
David Kremer
I would recommend running the import in the Python profiler to determine
where most of the time is going. When I investigated this a few years
back, it was mainly due to loading the GUI toolkits, which are
understandably quite large. You can avoid most of that by using the Agg
backend. If you're using the Agg backend and still experiencing
slowness, it may be that load-up issues have crept back into matplotlib
since then -- but we need profiling data to figure out where and how.
Mike
________________________________________
From: David Kremer [dav...@gm...]
Sent: Monday, March 28, 2011 9:36 AM
To: Matplotlib Users
Subject: [Matplotlib-users] matplotlib is slow
Hello everyone,
I would like to draw the attention on the slow startup of matplotlib.
Indeed, running matplotlib takes a long time.
I performed the following sequence :
```bash
#!/bin/bash
for i in * ; do python2 -c "from temp import * ; plot_(\"${i}\") " ; done
```
with temp.py like this :
```python
#!/usr/bin/env python2
import sys
import matplotlib.pyplot as plt
import read_data as rd
import numpy
def plot_( fname ):
P,I = rd.read_data(fname)
Iprime = [ l / k for k , l in zip( numpy.diff(P) , numpy.diff(I) ) ]
fig = plt.figure()
ax1 = fig.add_subplot(211)
ax2 = fig.add_subplot(212)
ax1.plot(P,I)
ax2.plot(P[:-1],Iprime)
fig.savefig( fname + ".pdf", format='pdf' )
```
And it seems the longer operation is to import matplotlib.pyplot.
Does something could be done to improve the loading time of this module ?
Thank you very much.
greatings,
David Kremer
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> I would recommend running the import in the Python profiler to determine > where most of the time is going. When I investigated this a few years > back, it was mainly due to loading the GUI toolkits, which are > understandably quite large. You can avoid most of that by using the Agg > backend. If you're using the Agg backend and still experiencing > slowness, it may be that load-up issues have crept back into matplotlib > since then -- but we need profiling data to figure out where and how. > > Mike Thank you a lot for your answer. I noticed than _matplotlib.pyplot_ is longer to be imported the first time than if it has already been imported previously (maybe things are already loaded in ram memory), and we don't need to fetch it from the hard drive thanks to the kernel. As far I see, the function calls are the same for the two logs I obtained, except than the first took 6s instead of 1.4s. The two logs have been obtained using : <code> python -m cProfile temp.py </code> where temp.py consist of two lines : <code> #!/usr/bin/env python2 import matplotlib.pyplot </code>
Resurrecting an old thread here....
On Tue, Mar 29, 2011 at 3:23 PM, David Kremer <da...@da...> wrote:
> > I would recommend running the import in the Python profiler to determine
> > where most of the time is going. When I investigated this a few years
> > back, it was mainly due to loading the GUI toolkits, which are
> > understandably quite large. You can avoid most of that by using the Agg
> > backend. If you're using the Agg backend and still experiencing
> > slowness, it may be that load-up issues have crept back into matplotlib
> > since then -- but we need profiling data to figure out where and how.
>
Importing Matplotlib is very slow for me, too. For a wxPython application
with embedded Matplotlib, I am getting "load" times of > 20 seconds when
"cold" importing matplotlib, with this (circa mid 2004) computer setup:
Windows XP, sp3, Intel Pentium, 1.70 Ghz, 1 GB RAM.
This is, by the way, an import well after Python and wxPython have already
been loaded into RAM, as it happens by a user action, so none of the time
involved here is due to loading Python or wxPython (they both load more
quickly--about 10 seconds to cold import them, my code, images, and some
other libraries).
First of all: does that amount of time seem appropriate for that fast of a
system--or is that too long? It definitely *feels* way too long from a
user perspective (for comparison Word or PowerPoint loads on this computer
in about 2.5 seconds).
Trying to improve it and following this old thread, I have switched to
matplotlib.use('Agg')
instead of
matplotlib.use('wxAgg')
as suggested to speed things up...but it is no faster.
I see, though, that I also have lines such as:
from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg
from matplotlib.backends.backend_wxagg import NavigationToolbar2WxAgg
Would the presence of these imports obviate the fact that I switched to
using the Agg instead of the wxAgg? If so, is there any way to use
something faster here (I suspect not but thought I'd ask).
Also, what else should I consider doing to reduce the import time
significantly? (I have to learn how to use the profiler, so I haven't done
that yet).
Thanks,
Che
>
> > Mike
>
> Thank you a lot for your answer.
>
> I noticed than _matplotlib.pyplot_ is longer to be imported the first time
> than
> if it has already been imported previously (maybe things are already
> loaded in
> ram memory), and we don't need to fetch it from the hard drive thanks to
> the
> kernel.
>
> As far I see, the function calls are the same for the two logs I obtained,
> except than the first took 6s instead of 1.4s.
>
>
>
>
> The two logs have been obtained using :
> <code>
> python -m cProfile temp.py
> </code>
>
> where temp.py consist of two lines :
>
> <code>
> #!/usr/bin/env python2
>
> import matplotlib.pyplot
> </code>
>
>
>
>
>
>
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> smartphone on the nation's most reliable network.
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> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>
I think using the profiler is the best bet here. We've used that in the
past to track down things that take a long time to import quite
successfully. I'm not seeing any slowness here, so that is likely do to
an environmental difference on your machine, implying you'll really need
to run the profiler yourself. I recommend runsnakerun to examine the
profile output -- if you have trouble interpreting it, feel free to send
me your raw profiler data to me off list.
Mike
On 12/31/2012 02:21 PM, C M wrote:
> Resurrecting an old thread here....
>
> On Tue, Mar 29, 2011 at 3:23 PM, David Kremer <da...@da...
> <mailto:da...@da...>> wrote:
>
> > I would recommend running the import in the Python profiler to
> determine
> > where most of the time is going. When I investigated this a few
> years
> > back, it was mainly due to loading the GUI toolkits, which are
> > understandably quite large. You can avoid most of that by using
> the Agg
> > backend. If you're using the Agg backend and still experiencing
> > slowness, it may be that load-up issues have crept back into
> matplotlib
> > since then -- but we need profiling data to figure out where and
> how.
>
>
> Importing Matplotlib is very slow for me, too. For a wxPython
> application with embedded Matplotlib, I am getting "load" times of >
> 20 seconds when "cold" importing matplotlib, with this (circa mid
> 2004) computer setup: Windows XP, sp3, Intel Pentium, 1.70 Ghz, 1 GB
> RAM.
>
> This is, by the way, an import well after Python and wxPython have
> already been loaded into RAM, as it happens by a user action, so none
> of the time involved here is due to loading Python or wxPython (they
> both load more quickly--about 10 seconds to cold import them, my code,
> images, and some other libraries).
>
> First of all: does that amount of time seem appropriate for that fast
> of a system--or is that too long? It definitely *feels* way too long
> from a user perspective (for comparison Word or PowerPoint loads on
> this computer in about 2.5 seconds).
>
> Trying to improve it and following this old thread, I have switched to
>
> matplotlib.use('Agg')
>
> instead of
>
> matplotlib.use('wxAgg')
>
> as suggested to speed things up...but it is no faster.
>
> I see, though, that I also have lines such as:
>
> from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg
> from matplotlib.backends.backend_wxagg import NavigationToolbar2WxAgg
>
> Would the presence of these imports obviate the fact that I switched
> to using the Agg instead of the wxAgg? If so, is there any way to use
> something faster here (I suspect not but thought I'd ask).
>
> Also, what else should I consider doing to reduce the import time
> significantly? (I have to learn how to use the profiler, so I haven't
> done that yet).
>
> Thanks,
> Che
>
> >
> > Mike
>
> Thank you a lot for your answer.
>
> I noticed than _matplotlib.pyplot_ is longer to be imported the
> first time than
> if it has already been imported previously (maybe things are
> already loaded in
> ram memory), and we don't need to fetch it from the hard drive
> thanks to the
> kernel.
>
> As far I see, the function calls are the same for the two logs I
> obtained,
> except than the first took 6s instead of 1.4s.
>
>
>
>
> The two logs have been obtained using :
> <code>
> python -m cProfile temp.py
> </code>
>
> where temp.py consist of two lines :
>
> <code>
> #!/usr/bin/env python2
>
> import matplotlib.pyplot
> </code>
>
>
>
>
>
> ------------------------------------------------------------------------------
> Xperia(TM) PLAY
> It's a major breakthrough. An authentic gaming
> smartphone on the nation's most reliable network.
> And it wants your games.
> http://p.sf.net/sfu/verizon-sfdev
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> <mailto:Mat...@li...>
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>
>
>
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