matplotlib-users Mailing List for matplotlib

Hi,

In the following example:

---

import numpy as np

import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt

fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.imshow(np.random.random((1024, 1024)), interpolation='nearest')
fig.savefig('test_1.eps')

mpl.rc('text', usetex=True)

fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.imshow(np.random.random((1024, 1024)), interpolation='nearest')
fig.savefig('test_2.eps')

---

the file test_2.eps is almost 6 times larger than test_1.eps, and takes much longer to draw. It looks like in the first case, the image is rendered as a bitmap (the way it should be), whereas in the second case each pixel is drawn individually as a polygon. Is this a bug?

I am using r8988 of matplotlib.

Thanks for any help!

Thomas

David, the preferred way to custom plots seems to be passing an Axes
instance to the plotting function. Some tricks allow use of
pylab/pyplot style:

def custom_plot(x, y, axes=None):
    ...
    if axes is None: axes = pyplot.gca()
    axes.plot(x, y)
    ....

What you don't get this way is the axes.custom_plot(x, y) sintax,
which requires subclassing Axes. But doing this is not common and not
straighforward if you want it to work well with pyplot.subplot() and
the like.

Maybe monkey patching would work but well, you know... I never tried it anyway.

Goyo

Gökhan Sever, on 2011-02-28 11:32,  wrote:
> On Mon, Feb 28, 2011 at 10:48 AM, Andrea Crotti
> <and...@gm...>wrote:
> 
> > So since I wanted some space on the borders of my graph, I did this
> > really extremely convoluted thing, which apparently works...
> > I get a 10% more area on each side, but I'm quite sure there's a better
> > way to this, right?
> >
> > I didn't find any function to pass an increment to the size that's why I
> > did this mess...
> >
> > --8<---------------cut here---------------start------------->8---
> >        old_axes = plt.axis()
> >        sizes = old_axes[1] - old_axes[0], old_axes[3] - old_axes[2]
> >        offset = lambda x: int((float(x) / 10))
> >        new_axes = []
> >
> >        for i in range(len(old_axes)):
> >            new_val = old_axes[i] + (((-1) ** (i + 1)) * offset(sizes[i %
> > 2]))
> >            new_axes.append(new_val)
> >
> >        plt.axis(new_axes)
> > --8<---------------cut here---------------end--------------->8---
> 
> You can try:
> 
> fig, ax = plt.subplots(1,1)
> ax.plot(range(10))
> fig.subplots_adjust(left=0.05, right=0.95, bottom=0.05, top=0.95)

Hi Andrea,

I think Gökhan is pointing out a different feature than the one
you want. You seem to want to adjust the x and y limits of the
plot to be some fraction larger than the data that's plotted. 

You can do this with:

ax = plt.subplot(111)
ax.plot(range(10))
ax.set_ymargin(.2)
ax.set_xmargin(.1)
# or ax.margins(.1,.2)
ax.autoscale()
plt.draw()

see also the docstring for ax.autoscale_view for more.

best,
-- 
Paul Ivanov
314 address only used for lists,  off-list direct email at:
http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7 

Boyle, Jim, on 2011-02-28 08:40,  wrote:
> I am using AxesGrid (from mpl_toolkits.axes_grid1 import
> AxesGrid) to generate multi-panel plots.  It does very well
> except I have a problem with a blank subplot.  I have 5 plots
> to display and the geometry of nrows_ncols=(3,2) produces the
> plot that I want except there is a frame placed in the last
> position - for which I did not call a plot.
> 
> I cannot figure out an elegant way to supress this frame. The
> kludge I use now is to just set the edgecolor of the last grid
> subplot to the background and so it is not visible.
> 
> All the examples  have an even number of subplot figures so the
> grid is filled and this situation does not occur.

Hi Jim,

how's this:

import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import AxesGrid
ag = AxesGrid(plt.figure(),(0,0,1,1),(2,3))
ag.axes_all[-1].set_visible(False)

best,
-- 
Paul Ivanov
314 address only used for lists,  off-list direct email at:
http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7 

On Sun, Feb 27, 2011 at 4:49 PM, David Andrews <irb...@gm...> wrote:

> Hi All,
>
> I'm looking for some suggestions about two problems:
>
> 1) I'm converting some figure generating code from IDL into
> Python/matplotlib.  Image attached showing this figure.
> IDL being a functional programming language for the most part,
> creating wrappers around various subroutines is trivial and generally
> the simplest way to modify their behavior.
> For example, in dealing with phase data (which can take values between
> 0º and 360º, and are 'wrapped' around this interval, such that 270º +
> 180º = 90º and so on), I have some stuff in IDL that instead over
> simply 'overplotting' some (x,y) data, it will do a quick loop and
> instead overplot (x, y + n * 360º) for n = -1, ..., 1 (or some other
> number of repetitions, you get the idea).
>
> Now, in matplotlib, while I can do this pretty easily, I suspect there
> are better ways?  I suppose I could write a subclass of
> matplotlib.axes.Axes for example, that does the 360º repetition itself
> across not just the plot() method but for others also?  But
> implementing a whole new class for this may be complicated, and I am
> sort of lost as to how I would then get that working with the pylab
> stateful interface?
>
> I'm reasonably new to OO programming, and I'm still getting my head
> round the 'best' way to do things like this.
>
> Alternatively, having a class that describes individual data points, I
> could define a plot() method for them?
>
> class MyData():
>    ...
>    plot(self, axes):
>        ...
>        axes.plot(self.x, self.y + n * 360)
>
> But then, that seems to 'break' some rules, as I don't see much
> matplotlib code in which you do 'data.plot()' as opposed to
> 'axes.plot()' - the order seems wrong?
>
> 2) Somewhat similar to the first question.  The figure includes (at
> the top) some ancillary data (showing lengths of orbit and year
> numbers).  In IDL its done simply by filling polygons in normal / page
> coordinates - but again, I think it could be better done using OO
> somehow?  Effectively, that top row could be thought of as a separate
> subplot.  What would be the efficient / sensible / pythonic way to go
> about reproducing this. Another subclass of Axes?
>
> Many thanks,
>
> Dave
>
>
Dave,

Generally speaking, if your first thought is "Should I subclass the Axes
class?" then you might need to take a second look at what matplotlib has to
offer out of the box.  Granted, the graph you wish to duplicate is very
complex, but let us break it down into various components.

First, you want multiple subplots to appear vertically "stacked" and share
the same x-axis.  Here is an example of how to do that:

http://matplotlib.sourceforge.net/examples/pylab_examples/ganged_plots.html

(Note that I personally advocate against the "from pylab import *" code
style, and this example could easily be redone from the pyplot interface
instead.)

Here is another example where the person used LineCollections with defined
offsets.  This has the advantage of using a single axes object, but might be
difficult to handle the y-axis.

http://matplotlib.sourceforge.net/examples/pylab_examples/mri_with_eeg.html


To have multiple x-axis tick labels for a common y-axis is a concept called
twiny.  The following is an example of doing twinx (multiple y-axis tick
labels for a common x-axis), but the concept is the same:

http://matplotlib.sourceforge.net/examples/api/two_scales.html

This is another example showing a different way of doing that:

http://matplotlib.sourceforge.net/examples/axes_grid/simple_axisline4.html

As for some of the markings around the graph, I am not entirely certain how
to implement that.  I will leave that for others to suggest ideas for.

I hope this is helpful!
Ben Root

On Mon, Feb 28, 2011 at 10:48 AM, Andrea Crotti
<and...@gm...>wrote:

> So since I wanted some space on the borders of my graph, I did this
> really extremely convoluted thing, which apparently works...
> I get a 10% more area on each side, but I'm quite sure there's a better
> way to this, right?
>
> I didn't find any function to pass an increment to the size that's why I
> did this mess...
>
> --8<---------------cut here---------------start------------->8---
>        old_axes = plt.axis()
>        sizes = old_axes[1] - old_axes[0], old_axes[3] - old_axes[2]
>        offset = lambda x: int((float(x) / 10))
>        new_axes = []
>
>        for i in range(len(old_axes)):
>            new_val = old_axes[i] + (((-1) ** (i + 1)) * offset(sizes[i %
> 2]))
>            new_axes.append(new_val)
>
>        plt.axis(new_axes)
> --8<---------------cut here---------------end--------------->8---
>
>
>
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>

Hi,

You can try:

fig, ax = plt.subplots(1,1)
ax.plot(range(10))
fig.subplots_adjust(left=0.05, right=0.95, bottom=0.05, top=0.95)

If you choose WXAgg as your backend you get a nice config tool to adjust
spacing in the figure. Then just pass those numbers into .subplots_adjust
method once you are satisfied.


-- 
Gökhan

So since I wanted some space on the borders of my graph, I did this
really extremely convoluted thing, which apparently works...
I get a 10% more area on each side, but I'm quite sure there's a better
way to this, right?

I didn't find any function to pass an increment to the size that's why I
did this mess...

--8<---------------cut here---------------start------------->8---
        old_axes = plt.axis()
        sizes = old_axes[1] - old_axes[0], old_axes[3] - old_axes[2]
        offset = lambda x: int((float(x) / 10))
        new_axes = []

        for i in range(len(old_axes)):
            new_val = old_axes[i] + (((-1) ** (i + 1)) * offset(sizes[i % 2]))
            new_axes.append(new_val)

        plt.axis(new_axes)
--8<---------------cut here---------------end--------------->8---

I am using AxesGrid (from mpl_toolkits.axes_grid1 import AxesGrid) to generate multi-panel plots.
It does very well except I have a problem with a blank subplot.
I have 5 plots to display and the geometry of nrows_ncols=(3,2) produces the plot that I want 
except there is a frame placed in the last position - for which I did not call a plot.

I cannot figure out an elegant way to supress this frame. The kludge I use now is to just set the
edgecolor of the last grid subplot to the background and so it is not visible.

All the examples  have an even number of subplot figures so the grid is filled and this situation does not occur.

--Jim

Hi,

I usually plot my multichannel-EEG data using a constant offset for
each channel and then setting the channel-names as yticks on the
y-axis.

I stumbled across
http://www.scipy.org/Cookbook/Matplotlib/MultilinePlots
where exactly this problem is addressed, and I tried the example using
transformations. Sadly, it doesn't work anymore as the
transforms-module has changed. I know that the old methods all have
new versions, so it shouldn't be too hard to get it working again, but
I have a different question.

It is mentioned that this functionality was planned to (maybe)
encapsulate in a method plot_signal, but I didn't find it in current
mpl. Does such a method exist or was it somehow else implemented?

Greetings,

Thorsten

Jouni Seppänen <jk...@ik...> writes:

> pbkdo8y URWBookmanL-DemiBold ".167 SlantFont TeXnANSIEncoding ReEncodeFont" <texnansi.enc <8r.enc <ubkd8a.pfb
>
> I guess we will need to implement slightly more of a PostScript
> interpreter inside matplotlib to figure out which file is to be used
> for re-encoding the font, unless this really means some kind of a
> combination of the two encodings. I'll try to find out what pdftex
> does with this.

The author of pdftex reports that pdftex just takes the last encoding
file specified (so this font probably gets encoded wrong):

http://thread.gmane.org/gmane.comp.tex.pdftex/4913/focus=4914

This is very likely a bug in TeX Live, or whatever software caused that
line to be added to the pdftex.map file.

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