matplotlib-users Mailing List for matplotlib

Ernest Adrogué wrote:
> Hi,
> 
> I'm trying to plot some horizontal bars using the .bar() method:
> 
> import matplotlib.pyplot as plt
> fig=plt.figure()
> ax=fig.add_subplot(1,1,1)
> ax.bar([1,2,3],[4,6,5],orientation='horizontal')

Use

ax.barh([1,2,3], [4,5,6])

Eric

hi, i'm using the exact code pasted below, and copied from:
http://matplotlib.sourceforge.net/examples/pylab_examples/errorbar_demo.html?highlight=errorbar

i see the vertical error lines, but i'm not able to see the 'cap' as
in the codex above, i've tried changing a few parameters in my
matplotlibrc as well as
different backends.
i'm running matplotlib checked out from svn today. is there something
i can try to make the caps appear?
thanks,
-brent





from pylab import *

t = arange(0.1, 4, 0.1)
s = exp(-t)
e = 0.1*abs(randn(len(s)))
f = 0.1*abs(randn(len(s)))
g = 2*e
h = 2*f

figure()
errorbar(t, s, e, fmt='o')             # vertical symmetric
show()

I am plotting time-series 1-minute cadence data for specific 
multiple-day validation periods.

Sometimes the data have a gap between the start of the validation period 
and the start of the data. Attached is a stand-alone Python script that 
demonstrates the problem, along with the plot that the script produces.

April 20 is the start of the validation period. I want 04-20 to appear 
at the plot origin. This does not happen unless either the model or 
observed dictionary contain a key/value pair for 1998,4,20,0.
I tried adding   datetime(1998,4,20,0):None   to one or both 
dictionaries,  but it is ignored.

Also the minor tick marks do not look right, especially the ones just to 
the right of each x-axis label.

Do you have any suggestions?

Thanks,
Ann

I am working on a Windows PC; O/S is Windows XP Professional, Version 
2002, Service Pack 3.
I am running matplotlib, version  '0.99.0' which I obtained from the 
matplotlib Sourceforge site.
I have not customized matplotlibrc.
I am running python version 2.6.2.
Attached is output.txt, the result of running my script with a 
verbose-helpful

On Tue, Oct 6, 2009 at 2:24 PM, Jae-Joon Lee <lee...@gm...> wrote:
> 2) f is somehow not flushed when savefig returns (which should happen
> if file gets deleted).

I meant if the variable "f" gets dereferenced.

-JJ

I'm not sure.

In short, what savefig does is (when filename ending with "png" is
provided) is following.

def savefig(filename):
   f = open(filename,"wb")
   write_png(f)

I think there are two issue here.

1) write_png does not flush the file : this might be a bug or a
feature, I'm not sure.
2) f is somehow not flushed when savefig returns (which should happen
if file gets deleted). This only seems to happen in sage and this
seems to be the reason why savefig does not work.

As far as the second issues is concerned, I currently don't see
anything wrong in mpl's side. We may try to explicitly flush (or
close) the file after write_png, though.

I hope someone who is more knowledgeable than me take a look at this.
Meanwhile, I'll change the code to  explicitly close the opened file.

Regards,

-JJ





On Tue, Oct 6, 2009 at 1:44 PM,  <jas...@cr...> wrote:
> Jae-Joon Lee wrote:
>> I think this has nothing to do with dpi, but a file flushing issue.
>> Try something like below with sage (note that the code does not work
>> with svn version of matplotlib, i'll commit the fix soon).
>>
>> import matplotlib
>> matplotlib.use('Agg')
>> import matplotlib.pyplot as plt
>> fig=plt.figure()
>> plt.plot([1,2,3])
>> f = open("test.png", "wb")
>> plt.savefig(f, format="png", dpi=50)
>> f.flush()
>>
>> I'll report some more details later.
>>
>>
>
>
>
> This seems to have solved the problem on the two systems on which I've
> run experiments.  Now it makes perfect sense why I was always seeing a
> corrupt file size that was a multiple of 4K (e.g., 12K instead of 13K) :) .
>
> So just to confirm, is this a bug in matplotlib when using the
> plt.savefig(filename,dpi=72) form of calling savefig?
>
> Thanks,
>
> Jason
>
> ------------------------------------------------------------------------------
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>

Jae-Joon Lee wrote:
> I think this has nothing to do with dpi, but a file flushing issue.
> Try something like below with sage (note that the code does not work
> with svn version of matplotlib, i'll commit the fix soon).
>
> import matplotlib
> matplotlib.use('Agg')
> import matplotlib.pyplot as plt
> fig=plt.figure()
> plt.plot([1,2,3])
> f = open("test.png", "wb")
> plt.savefig(f, format="png", dpi=50)
> f.flush()
>
> I'll report some more details later.
>
>   



This seems to have solved the problem on the two systems on which I've 
run experiments.  Now it makes perfect sense why I was always seeing a 
corrupt file size that was a multiple of 4K (e.g., 12K instead of 13K) :) .

So just to confirm, is this a bug in matplotlib when using the 
plt.savefig(filename,dpi=72) form of calling savefig?

Thanks,

Jason

I think this has nothing to do with dpi, but a file flushing issue.
Try something like below with sage (note that the code does not work
with svn version of matplotlib, i'll commit the fix soon).

import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
fig=plt.figure()
plt.plot([1,2,3])
f = open("test.png", "wb")
plt.savefig(f, format="png", dpi=50)
f.flush()

I'll report some more details later.

Regards,

-JJ

Hi Jeff,

I had already tried area_thresh, but suffered from the limitation that you
pointed out, namely that although the inland waterways disappear, it is at
the expense of a lot of land. That's why I wondered if the function might be
splittable to avoid such issues. 

But thanks anyway.

Ringo



Jeff Whitaker wrote:
> 
> Scott Sinclair wrote:
>>> 2009/10/1 ringobelingo <rin...@gm...>:
>>> I would like to add coastlines to a map but do not want interior
>>> 'coastlines'. At present, without them my continents are not distinct
>>> enough
>>> from the data I am plotting in the background. But, when I draw them
>>> using
>>> drawcoastlines(), I also get e.g. the great lakes showing up, and this
>>> just
>>> makes my world maps look messy and distracts from my data which should
>>> be
>>> the main focus. Does anyone know of a way to force this to happen, or is
>>> it
>>> something that might be added, i.e. splitting the function into
>>> drawcoastlines() and drawicoastlines() ... ?
>>>     
>>
>> The easiest way to address this is to obtain (or make) a GIS shapefile
>> that has the coastlines you'd like to see. Then use the
>> readshapefile() method on your Basemap object instead of the
>> drawcoastlines() method.
>>
>> my_map = Basemap(...)
>> my_map.readshapefile(my_shpfile_name)
>>
>> Cheers,
>> Scott
>>
>>   
> 
> You can also use the 'area_thresh' keyword to control the minimum size 
> of coastline features that are drawn.  area_thresh=1000000 makes the 
> Great Lakes disappear, at the expense of making all the islands except 
> Greenland disappear too.  If that's unacceptable, you'll have to do as 
> Scott suggests and create a shapfile without the lakes.
> 
> -Jeff
> 
> 
> ------------------------------------------------------------------------------
> Come build with us! The BlackBerry&reg; Developer Conference in SF, CA
> is the only developer event you need to attend this year. Jumpstart your
> developing skills, take BlackBerry mobile applications to market and stay 
> ahead of the curve. Join us from November 9&#45;12, 2009. Register
> now&#33;
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> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> 
> 

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Hi Scott,

thanks for your response. This seems like the way to go!

Ringo



Scott Sinclair-4 wrote:
> 
>>2009/10/1 ringobelingo <rin...@gm...>:
>> I would like to add coastlines to a map but do not want interior
>> 'coastlines'. At present, without them my continents are not distinct
>> enough
>> from the data I am plotting in the background. But, when I draw them
>> using
>> drawcoastlines(), I also get e.g. the great lakes showing up, and this
>> just
>> makes my world maps look messy and distracts from my data which should be
>> the main focus. Does anyone know of a way to force this to happen, or is
>> it
>> something that might be added, i.e. splitting the function into
>> drawcoastlines() and drawicoastlines() ... ?
> 
> The easiest way to address this is to obtain (or make) a GIS shapefile
> that has the coastlines you'd like to see. Then use the
> readshapefile() method on your Basemap object instead of the
> drawcoastlines() method.
> 
> my_map = Basemap(...)
> my_map.readshapefile(my_shpfile_name)
> 
> Cheers,
> Scott
> 
> ------------------------------------------------------------------------------
> Come build with us! The BlackBerry&reg; Developer Conference in SF, CA
> is the only developer event you need to attend this year. Jumpstart your
> developing skills, take BlackBerry mobile applications to market and stay 
> ahead of the curve. Join us from November 9&#45;12, 2009. Register
> now&#33;
> http://p.sf.net/sfu/devconf
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> 
> 

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Hello,

I'm new to matplotlib, but have made great progress in using it over
the past few days (thanks in no small part to this list). However, I
am stuck on trying to determine the width of a y tick label (either in
inches or figure space). I know I can get 'Text instances' of the tick
labels using 'get_yticklabels'. However, a Text object doesn't appear
to have a width field. Now, it would make sense that the width of a
label depends on the rendered so I expect I need to take my text
string and pass it through an appropriate transformation using
something like 'get_yaxis_text1_transform'. Can anyone point me to an
example of obtaining the width of a label and/or some code indicating
how this can be done?

I realize I can approximate the width of a label simply by considering
how many characters it contains, the font size, and the DPI of the
figure, but this will be rather crude as I am not using a fixed-width
font.

Much thanks.

Cheers,
Donovan

Hi,

I'm trying to plot some horizontal bars using the .bar() method:

import matplotlib.pyplot as plt
fig=plt.figure()
ax=fig.add_subplot(1,1,1)
ax.bar([1,2,3],[4,6,5],orientation='horizontal')

raises an AssertionError:

AssertionError                            Traceback (most recent call last)

/home/ernest/<ipython console> in <module>()

/usr/lib/pymodules/python2.5/matplotlib/axes.py in bar(self, left, height, width, bottom, color, edgecolor, linewidth, yerr, xerr, ecolor, capsize, align, orientation, log, **kwargs)
   4230         # FIXME: convert the following to proper input validation
   4231         # raising ValueError; don't use assert for this.
-> 4232         assert len(left)==nbars, "incompatible sizes: argument 'left' must be length %d or scalar" % nbars
   4233         assert len(height)==nbars, ("incompatible sizes: argument 'height' must be length %d or scalar" %
   4234                                     nbars)

AssertionError: incompatible sizes: argument 'left' must be length 1 or scalar

using scalars doesn't help:

ax.bar(1,5,orientation='horizontal')

TypeError: unsupported operand type(s) for +: 'NoneType' and 'int'

Am I doing something wrong??

-- 
Ernest

Does anyone know if it possible to annotate the axes with strings?

I've tried a hundred combinations of set_xticklabels with and without
set_xticks but absolutely nothing seems to have any effect.

Perhaps this is a bug? Perhaps labelling 3d axes is not supported? There's
no documentation on this matter and I'm at my wits end - any help is
appreciated.

per freem <per...@gm...> writes:

> i am trying to install the recent matplotlib (0.99.1.1) but i am
> getting an error about wxPython not being available.  

The problem is that the tar.gz file includes setup.cfg, and the fix is
to delete that file. This is also filed on sourceforge:

https://sourceforge.net/tracker/?func=detail&aid=2871530&group_id=80706&atid=560720

-- 
Jouni K. Seppänen
http://www.iki.fi/jks

> 2009/10/5 Ernest Adrogué <ead...@gm...>:
> is it possible to draw unfilled scatter points?

Yes, try the following

>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>> x = np.random.rand(10)
>>> y = np.random.rand(10)
>>> plt.scatter(x, y, facecolor='none')
>>> plt.show()

Also take a look at
http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.scatter

Cheers,
Scott

Jae-Joon Lee wrote:
> On Mon, Oct 5, 2009 at 10:25 PM,  <jas...@cr...> wrote:
>   
>> Jae-Joon Lee wrote:
>>     
>>> As one of who never used Sage, I don't think I'll be any help here.
>>> Anyhow, can you tell us what kind of backed is used by default in the
>>> two environment? I mean the type of the canvas that is initially
>>> created.
>>>
>>>       
>> Thanks for following up on this.  Is there an easy way to ask matplotlib
>> what its default canvas is (i.e., what canvas pyplot will use for savefig)?
>>  I believe it's probably using the FigureCanvasAgg canvas, but I'm not sure.
>>  Since I've reproduced the problem with pure matplotlib code, I'm not sure
>> where the canvas is set up and initialized.
>>
>>     
>
> In [17]: fig = plt.figure()
>
> In [18]: print type(fig.canvas)
> <class 'matplotlib.backends.backend_gtkagg.FigureCanvasGTKAgg'>
>
> See if matplotlib session and sage session uses different backend.
>
>   
>>> It seems to be some dpi issue, but MPL supposed to handle this correctly.
>>> I guess it also works fine if the figure is initially created with the
>>> matching dpi as the savefig (72),?
>>>
>>>       
>> I'm not sure what you're asking here or how to test your assumption.  I
>> posted the code that gave the problem in a Sage session, but worked fine in
>> a normal python session.  I also saw the problem (cut-off bottom in firefox,
>> which looked like a transparent bottom portion of the figure in gimp) with
>> varying amounts when I specified other dpi values.  Is there something I can
>> insert into my script to test what you're asking?
>>
>>     
>
> plt.figure takes dpi parameter. This is the dpi of the figure instance
> (not the output).  Set this to same value as one you use for savefig.
>
>   
>> Again, I'm really puzzled by this.  We are using just pure matplotlib, and
>> yet, there seems to be something in the Sage configuration or environment or
>> something that is causing pure matplotlib code to generate these erroneous
>> figures, but the exact same installation of matplotlib, when run under
>> python, generates perfectly fine figures.
>>     
>
> I do not have any clue either. However, one possibility I can think of
> is that it is a bug in certain backend whose savefig command does not
> take care of changing dpi correctly. If it turns out that the sage
> session and ipython session uses a same backend, then, I have no idea.
> I hope some other developer who uses sage take a look at this.
>
>   


I ran some more tests, this time on sage.math.washington.edu, which is a 
64-bit Ubuntu system.  This time, instead of errors, all I saw were 
zero-length files! (i.e., the file was there, but it was completely 
empty, i.e., zero bytes).  I consistently produced a zero-length file 
the first time I used the dpi keyword argument to savefig.  If I called 
savefig again, the correct figure was saved to the file.  Any ideas 
about what in the world could be going on here?  The logs of my trials 
are below.

Using Sage's copy of python (2.6.2), the code printed out the exact same 
values for fig.canvas and fig.dpi each time, but there were no erroneous 
figures (i.e., all of the figures were saved to images correctly the 
first time savefig was called and the dpi was specified in savefig).

Thanks,

Jason



<new Sage session>
sage: import matplotlib.pyplot as plt;import numpy
sage: fig=plt.figure()
sage: print fig.canvas
<matplotlib.backends.backend_agg.FigureCanvasAgg instance at 0x4ad8440>
sage: print fig.dpi
80
sage: plt.plot(numpy.arange(0,1.1,0.01))
[<matplotlib.lines.Line2D object at 0x51275d0>]
sage: plt.savefig('foo.png',dpi=72)  # zero-length file generated
sage: plt.savefig('foo.png',dpi=72)  # correct figure generated

<new Sage session>
sage: import matplotlib.pyplot as plt;import numpy
sage: fig=plt.figure(dpi=72)
sage: print fig.canvas
<matplotlib.backends.backend_agg.FigureCanvasAgg instance at 0x4ad94d0>
sage: print fig.dpi
72
sage: plt.plot(numpy.arange(0,1.1,0.01))
[<matplotlib.lines.Line2D object at 0x51285d0>]
sage: plt.savefig('foo.png',dpi=72) # zero-length file generated
sage: plt.savefig('foo.png',dpi=72) # correct figure generated


<new Sage Session>
sage: import matplotlib.pyplot as plt;import numpy
sage: fig=plt.figure()
sage: print fig.canvas
<matplotlib.backends.backend_agg.FigureCanvasAgg instance at 0x4ad7440>
sage: print fig.dpi
80
sage: plt.plot(numpy.arange(0,1.1,0.01))
[<matplotlib.lines.Line2D object at 0x51305d0>]
sage: plt.savefig('foo.png',dpi=80) # zero-length file generated
sage: plt.savefig('foo.png',dpi=80) # correct figure generated


<new Sage Session>
sage: import matplotlib.pyplot as plt;import numpy
sage: fig=plt.figure(dpi=72)
sage: print fig.canvas
<matplotlib.backends.backend_agg.FigureCanvasAgg instance at 0x4ad94d0>
sage: print fig.dpi
72
sage: plt.plot(numpy.arange(0,1.1,0.01))
[<matplotlib.lines.Line2D object at 0x51325d0>]
sage: plt.savefig('foo.png') # correct figure generated


<new Sage session>
sage: import matplotlib.pyplot as plt;import numpy
sage: fig=plt.figure()
sage: print fig.canvas
<matplotlib.backends.backend_agg.FigureCanvasAgg instance at 0x4ad8440>
sage: print fig.dpi
80
sage: plt.plot(numpy.arange(0,1.1,0.01))
[<matplotlib.lines.Line2D object at 0x51275d0>]
sage: plt.savefig('foo.png') # correct figure generated

On Mon, Oct 5, 2009 at 10:25 PM,  <jas...@cr...> wrote:
> Jae-Joon Lee wrote:
>>
>> As one of who never used Sage, I don't think I'll be any help here.
>> Anyhow, can you tell us what kind of backed is used by default in the
>> two environment? I mean the type of the canvas that is initially
>> created.
>>
>
> Thanks for following up on this.  Is there an easy way to ask matplotlib
> what its default canvas is (i.e., what canvas pyplot will use for savefig)?
>  I believe it's probably using the FigureCanvasAgg canvas, but I'm not sure.
>  Since I've reproduced the problem with pure matplotlib code, I'm not sure
> where the canvas is set up and initialized.
>

In [17]: fig = plt.figure()

In [18]: print type(fig.canvas)
<class 'matplotlib.backends.backend_gtkagg.FigureCanvasGTKAgg'>

See if matplotlib session and sage session uses different backend.

>
>> It seems to be some dpi issue, but MPL supposed to handle this correctly.
>> I guess it also works fine if the figure is initially created with the
>> matching dpi as the savefig (72),?
>>
>
> I'm not sure what you're asking here or how to test your assumption.  I
> posted the code that gave the problem in a Sage session, but worked fine in
> a normal python session.  I also saw the problem (cut-off bottom in firefox,
> which looked like a transparent bottom portion of the figure in gimp) with
> varying amounts when I specified other dpi values.  Is there something I can
> insert into my script to test what you're asking?
>

plt.figure takes dpi parameter. This is the dpi of the figure instance
(not the output).  Set this to same value as one you use for savefig.

> Again, I'm really puzzled by this.  We are using just pure matplotlib, and
> yet, there seems to be something in the Sage configuration or environment or
> something that is causing pure matplotlib code to generate these erroneous
> figures, but the exact same installation of matplotlib, when run under
> python, generates perfectly fine figures.

I do not have any clue either. However, one possibility I can think of
is that it is a bug in certain backend whose savefig command does not
take care of changing dpi correctly. If it turns out that the sage
session and ipython session uses a same backend, then, I have no idea.
I hope some other developer who uses sage take a look at this.

Regards,

-JJ


>
> Thanks,
>
> Jason
>
>
>
>
>
>

Jae-Joon Lee wrote:
> As one of who never used Sage, I don't think I'll be any help here.
> Anyhow, can you tell us what kind of backed is used by default in the
> two environment? I mean the type of the canvas that is initially
> created.
>   

Thanks for following up on this.  Is there an easy way to ask matplotlib 
what its default canvas is (i.e., what canvas pyplot will use for 
savefig)?  I believe it's probably using the FigureCanvasAgg canvas, but 
I'm not sure.  Since I've reproduced the problem with pure matplotlib 
code, I'm not sure where the canvas is set up and initialized.


> It seems to be some dpi issue, but MPL supposed to handle this correctly.
> I guess it also works fine if the figure is initially created with the
> matching dpi as the savefig (72),?
>   

I'm not sure what you're asking here or how to test your assumption.  I 
posted the code that gave the problem in a Sage session, but worked fine 
in a normal python session.  I also saw the problem (cut-off bottom in 
firefox, which looked like a transparent bottom portion of the figure in 
gimp) with varying amounts when I specified other dpi values.  Is there 
something I can insert into my script to test what you're asking?

Again, I'm really puzzled by this.  We are using just pure matplotlib, 
and yet, there seems to be something in the Sage configuration or 
environment or something that is causing pure matplotlib code to 
generate these erroneous figures, but the exact same installation of 
matplotlib, when run under python, generates perfectly fine figures.

Thanks,

Jason

with hold=False, the axes is reset whenever something new is added to
the axes. Instead of using pylab.hold(False), clear the figure or axes
explicitly (clf() or cla())

-JJ


On Mon, Oct 5, 2009 at 9:58 PM, Ross Anderson <rpa...@gm...> wrote:
> Hi all,
>
> I'm making multiple semilogy histograms, which for now are on separate
> figures and not in subplots. Here's something patched together:
> def makehistogram(data,strtitle, filename):
>     fig = Figure()
>     pylab.hold(False)
>     pylab.semilogy(base=10)
>     n, bins, patches = pylab.hist(data, 50, normed=1)
>     pylab.setp(patches, 'facecolor', 'g', 'alpha', 0.75)
>     pylab.xlabel('bins')
>     pylab.ylabel('logP')
>     pylab.title(strtitle)
>     pylab.grid(True)
>     pylab.savefig(filename,dpi=72)
>
> The first call to makehistogram() saves the semilogy histogram I want, but
> the subsequent calls create regular cartesian histograms. Am I missing
> something?
>
> Thanks
>
> ------------------------------------------------------------------------------
> Come build with us! The BlackBerry&reg; Developer Conference in SF, CA
> is the only developer event you need to attend this year. Jumpstart your
> developing skills, take BlackBerry mobile applications to market and stay
> ahead of the curve. Join us from November 9&#45;12, 2009. Register now&#33;
> http://p.sf.net/sfu/devconf
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>

I just want to mention that axes size in mpl, by design, is supposed
to be proportional to the figure size, so there could be cases when a
fixed-sized axes messes up something. Furthermore, using axes_grid
toolkit can be a bit tricky, so I (as an author of the axes_grid
toolkit) personally do no recommend it for someone new to matplotlib.
Having said that, add below after the make_axes_locatable call.

from mpl_toolkits.axes_grid import Size
divider.get_horizontal()[0] = Size.Fixed(3.0) # 3 inch
divider.get_vertical()[0] = Size.Fixed(2.0) # 2 inch

The axes will have a fixed size regardless of the figure size. Also,
take a look at the below  example of fixed size axes.

http://matplotlib.sourceforge.net/examples/axes_grid/demo_fixed_size_axes.html

FYI, if you want your output automatically clipped according to the
axes size and label etc., try savefig with bbox_inches="tight" option
(it does not affect the displayed figure size). Although the current
algorithm is not perfect, it seems to work okay for a simple case as
yours.

Regards,

-JJ


On Mon, Oct 5, 2009 at 8:59 PM, Donovan Parks <don...@gm...> wrote:
> Hello,
>
> I am new to matplotlib and am having trouble understanding how to set
> the size of a subplot when a figure contains multiple subplots. In
> particular, I have been playing around with the scatter_hist.py demo
> at http://matplotlib.sourceforge.net/examples/axes_grid/scatter_hist.html.
> A simplified version of this code is given below:
>
> *****************
>
> import numpy as np
> import matplotlib.pyplot as plt
> from mpl_toolkits.axes_grid import make_axes_locatable
>
> fig = plt.figure(1, figsize=(4,4))
>
> axScatter = plt.subplot(111)
> divider = make_axes_locatable(axScatter)
> axHisty = divider.new_horizontal(1.2, pad=0.5, sharey=axScatter)
> fig.add_axes(axHisty)
>
> x = np.random.randn(1000)
> y = np.random.randn(1000)
> axScatter.scatter(x, y)
> axHisty.hist(x, orientation='horizontal')
>
> plt.draw()
> plt.show()
>
> *****************
>
> I'd like to have direct control over the size of the scatter plot in
> this figure. As it stands, I can 'sort of' control its size by
> changing the figsize property of the figure. I say 'sort of' since the
> size of any labels also come into play here. Is it possible to
> directly make the scatter plot a certain size (say, 3 x 2 inches), set
> the figure size independently (say, 5 x 4 inches), and have the
> histogram size be set based on the scatter plot height and width set
> in divider.new_horizontal (in this case to 3 x 1.2 inches)?
>
> I realize that in this example, it probably seems silly to not just
> change figsize, but I am working with a more complicated plot in
> reality where I'd like precise control over the size of the initial
> subplot since the aspect ratio is important to me. I can then adjust
> the figsize to make sure all the labels fit in nicely.
>
> Thanks for any and all help.
>
> Cheers,
> Donovan
>
> ------------------------------------------------------------------------------
> Come build with us! The BlackBerry&reg; Developer Conference in SF, CA
> is the only developer event you need to attend this year. Jumpstart your
> developing skills, take BlackBerry mobile applications to market and stay
> ahead of the curve. Join us from November 9&#45;12, 2009. Register now&#33;
> http://p.sf.net/sfu/devconf
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Hi all,

I'm making multiple semilogy histograms, which for now are on separate
figures and not in subplots. Here's something patched together:
def makehistogram(data,strtitle, filename):
    fig = Figure()
    pylab.hold(False)
    pylab.semilogy(base=10)
    n, bins, patches = pylab.hist(data, 50, normed=1)
    pylab.setp(patches, 'facecolor', 'g', 'alpha', 0.75)
    pylab.xlabel('bins')
    pylab.ylabel('logP')
    pylab.title(strtitle)
    pylab.grid(True)
    pylab.savefig(filename,dpi=72)

The first call to makehistogram() saves the semilogy histogram I want, but
the subsequent calls create regular cartesian histograms. Am I missing
something?

Thanks

You will probably want to add axes explicitly (not with subplot), e.g.

fig.add_axes([.1,.1,.71,.8])

specifies the coordinates of one corner and the width and height (in  
proportions of the figure size). When doing this explicitly, you will  
probably need to do some extra adjustments to fit the axis labels and  
so forth.

&C

On Oct 5, 2009, at 5:59 PM, Donovan Parks wrote:

> Hello,
>
> I am new to matplotlib and am having trouble understanding how to set
> the size of a subplot when a figure contains multiple subplots. In
> particular, I have been playing around with the scatter_hist.py demo
> at http://matplotlib.sourceforge.net/examples/axes_grid/scatter_hist.html 
> .
> A simplified version of this code is given below:
>
> *****************
>
> import numpy as np
> import matplotlib.pyplot as plt
> from mpl_toolkits.axes_grid import make_axes_locatable
>
> fig = plt.figure(1, figsize=(4,4))
>
> axScatter = plt.subplot(111)
> divider = make_axes_locatable(axScatter)
> axHisty = divider.new_horizontal(1.2, pad=0.5, sharey=axScatter)
> fig.add_axes(axHisty)
>
> x = np.random.randn(1000)
> y = np.random.randn(1000)
> axScatter.scatter(x, y)
> axHisty.hist(x, orientation='horizontal')
>
> plt.draw()
> plt.show()
>
> *****************
>
> I'd like to have direct control over the size of the scatter plot in
> this figure. As it stands, I can 'sort of' control its size by
> changing the figsize property of the figure. I say 'sort of' since the
> size of any labels also come into play here. Is it possible to
> directly make the scatter plot a certain size (say, 3 x 2 inches), set
> the figure size independently (say, 5 x 4 inches), and have the
> histogram size be set based on the scatter plot height and width set
> in divider.new_horizontal (in this case to 3 x 1.2 inches)?
>
> I realize that in this example, it probably seems silly to not just
> change figsize, but I am working with a more complicated plot in
> reality where I'd like precise control over the size of the initial
> subplot since the aspect ratio is important to me. I can then adjust
> the figsize to make sure all the labels fit in nicely.
>
> Thanks for any and all help.
>
> Cheers,
> Donovan
>
> ------------------------------------------------------------------------------
> Come build with us! The BlackBerry® Developer Conference in SF, CA
> is the only developer event you need to attend this year. Jumpstart  
> your
> developing skills, take BlackBerry mobile applications to market and  
> stay
> ahead of the curve. Join us from November 9-12, 2009. Register  
> now!
> http://p.sf.net/sfu/devconf
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

Hello,

I am new to matplotlib and am having trouble understanding how to set
the size of a subplot when a figure contains multiple subplots. In
particular, I have been playing around with the scatter_hist.py demo
at http://matplotlib.sourceforge.net/examples/axes_grid/scatter_hist.html.
A simplified version of this code is given below:

*****************

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid import make_axes_locatable

fig = plt.figure(1, figsize=(4,4))

axScatter = plt.subplot(111)
divider = make_axes_locatable(axScatter)
axHisty = divider.new_horizontal(1.2, pad=0.5, sharey=axScatter)
fig.add_axes(axHisty)

x = np.random.randn(1000)
y = np.random.randn(1000)
axScatter.scatter(x, y)
axHisty.hist(x, orientation='horizontal')

plt.draw()
plt.show()

*****************

I'd like to have direct control over the size of the scatter plot in
this figure. As it stands, I can 'sort of' control its size by
changing the figsize property of the figure. I say 'sort of' since the
size of any labels also come into play here. Is it possible to
directly make the scatter plot a certain size (say, 3 x 2 inches), set
the figure size independently (say, 5 x 4 inches), and have the
histogram size be set based on the scatter plot height and width set
in divider.new_horizontal (in this case to 3 x 1.2 inches)?

I realize that in this example, it probably seems silly to not just
change figsize, but I am working with a more complicated plot in
reality where I'd like precise control over the size of the initial
subplot since the aspect ratio is important to me. I can then adjust
the figsize to make sure all the labels fit in nicely.

Thanks for any and all help.

Cheers,
Donovan

Whenever I run the statement:

from pylab import randn, hist

 

OR

 

import matplotlib.pyplot as plt

 

Python crashes, no error ... nothing

 

Running under Python 2.5

 

Any ideas?

 
 		 	   		  
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