matplotlib-users Mailing List for matplotlib (Page 1425)

Hi,

Anyone is welcome to work on the SVG backend.  I didn't realize that
John thought I was hard at work on improving it, when actually I've been
happily using it.  Sorry for not communicating that... I'm not going to
have any time to work on it in the near future, so go nuts.  I'm an
amateur, so there are plenty of bugs!  :)

On Thu, 2004-07-08 at 16:16, John Hunter wrote:

> There is an SVG backend already in matplotlib.  It hasn't been
> announced because it is in development by Jared Wahlstrand.  Perhaps
> Jared can give a status report on what needs to be done, and you might
> want to help out.  He might have a more recent copy in his development
> tree than I do.
> 
> Here are the issues as I understand them:
> 
>   * image support

This is waiting on a save_image function in the Agg backend, so that we
can link to an external PNG file.

>   * font support (freetype vs afm), use of font families /
>     font_manager

Is this the issue of 'helvetica' versus 'sans serif'?

>   * mathtext

I don't know where to begin here, but the implementation is going to
look a lot like the PS backend.  It would be cool to embed MathML, but
good luck finding a viewer capable of reading it... :)

>   * some oddness when the user calls savefig with a high dpi?
>     Shouldn't SVG ignore the dpi setting?  That's what I did in
>     backend_ps.

You're right, it shouldn't need to know the dpi.  This is an artifact
from when I ported everything from the PS backend.

>   * There also appears to be some problem in centering the figure?

I haven't experienced this.

I've been using it to export to inkscape to make figures for papers and
conference talks and haven't had any major problems.  The code in 0.60
is the same as I've been using, with the exception of adding another
case to print_figure() to switch to the SVG backend when the filename
has a .svg extension.

It's not complicated code, so it should be easy to understand, but let
me know if you have any questions.

Cheers,

Jared

>>>>> "Eric" == Eric Jonas <jo...@co...> writes:

    >> touch bitmap figures again. I could do entire conference
    >> posters in SVG!  If Justin's not interested and would accept a
    >> patch, I might be willing to try and tackle this...

    Eric>  By which of course I mean John, or perhaps Dr. Hunter...

John works for me :-)

There is an SVG backend already in matplotlib.  It hasn't been
announced because it is in development by Jared Wahlstrand.  Perhaps
Jared can give a status report on what needs to be done, and you might
want to help out.  He might have a more recent copy in his development
tree than I do.

Here are the issues as I understand them:

  * image support

  * font support (freetype vs afm), use of font families /
    font_manager

  * mathtext

  * some oddness when the user calls savefig with a high dpi?
    Shouldn't SVG ignore the dpi setting?  That's what I did in
    backend_ps.

  * There also appears to be some problem in centering the figure?

I've only been testing this a bit - my SVG viewer doesn't seem to work
too well.

JDH

> touch bitmap figures again. I could do entire conference posters in SVG!
> If Justin's not interested and would accept a patch, I might be willing
> to try and tackle this... 
 By which of course I mean John, or perhaps Dr. Hunter... 
             ...Eric

I second this question / request. The inkscape (inkscape.org) people are
making a full-featured Illustrator-like replacement for vector
illustration, and if matplotlib could generate SVGs, I'd never have to
touch bitmap figures again. I could do entire conference posters in SVG!
If Justin's not interested and would accept a patch, I might be willing
to try and tackle this...=20
			...Eric


On Thu, 2004-07-08 at 11:53, Flavio Codeco Coelho wrote:
> Hi,
>=20
> Is there a way to save vectorial figs? AGG is a vectorial renderer so
> at least for this backend it should be possible...
>=20
> Fl=C3=A1vio Code=C3=A7o Coelho,
> PhD
> Programa de Computa=C3=A7=C3=A3o
> Cient=C3=ADfica
> Funda=C3=A7=C3=A3o Oswaldo Cruz
> Rio de Janeiro --
> Brasil
>=20
>=20
> ______________________________________________________________________

What is the prefered way to read in images in numarray/matplotlib?

I know of PIL but it seems like a lot of overlap with numarray just to read an 
image from file.

I really need to read only one type of file (say ppm) and then i can use 
imagemagick to convert from and to that format.

Regards
Rein

>>>>> "Nino" == Nino Cucchiara <cuc...@me...> writes:

    Nino> I want to write some greek symbols in axes legend, for
    Nino> exemple nu letters or lambda. Is it possible?  Thank you.

You can use mathtext anywhere you can use text.  Just use the standard
way of specifying the string

s = r'$\lambda = 5$'

See http://matplotlib.sf.net/matplotlib.mathtext.html for more
information on mathtext.

You may be happy to hear that mathtext for postscript should be ready
soon!

Here is an example that uses mathtext in a legend

    from matplotlib.matlab import *
    t = arange(0.0, 2.0, 0.1)
    plot(t, sin(2*pi*t), '--go', t, log(1+t), '.')
    legend((r'$\nu$', r'$\lambda$'), 'upper right')
    show()

I want to write some greek symbols in axes legend, for exemple nu 
letters or lambda. Is it possible?
Thank you.

Hi,

I note that in the in the examples which display some images (e.g,
image_origin.py) the displayed images hide one of the x-axis (top one if
origin="upper" and bottom one otherwise). It seems like it may be
necessary to apply an offset before displaying the images (I looked
throughout the imshow.py code but didn't find the exact place to do it, it
may be a problem of offsetting and scaling).

Cheers,

	Eddie.

>>>>> "Leon" == Leon Brits <lj...@fa...> writes:

    Leon> Hi, I wanted to compile a old matplot program with the new
    Leon> matplotlib v0.54.2 but I get the error:

    Leon> 	NameError: name 'get_current_fig_manager' is not
    Leon> defined

    Leon> the line of code is:

    Leon> 	g_canvas = get_current_fig_manager().canvas

    Leon> This use to work with matplotlib v0.53. I use pyGtk v2.0.

    Leon> Start code: import pygtk pygtk.require('2.0') import gtk


get_current_fig_manager is definitely defined in matplotlib.matlab in
version 0.54.2.  You need to make sure you do

  from matplotlib.matlab import get_current_fig_manager

before the call to 

  g_canvas = get_current_fig_manager().canvas
  
and you should have no trouble.  If you are still having trouble,
you'll need to post a complete code example.

JDH

Hi,

I wanted to compile a old matplot program with the new matplotlib v0.54.2  
but I get the error:

	NameError: name 'get_current_fig_manager' is not defined

the line of code is:

	g_canvas = get_current_fig_manager().canvas

This use to work with matplotlib v0.53. I use pyGtk v2.0.

Start code:
	import pygtk
	pygtk.require('2.0')
	import gtk

Please help!
Leon

>>>>> "Rein" == Rein van den Boomgaard (UvA) <re...@sc...> writes:

    Rein> Dear All, as i'm new to this list let me first introduce
    Rein> myself before posting a question.

    Rein> I'm working in the field of image processing and computer
    Rein> vision for a long time now and i am a long time matlab
    Rein> user. Up to now i didn't like any of the matlab clones but
    Rein> it seems that numarray+matplotlib might be a winner here.

I've worked some with octave in the past and found it unsatisfying
(though a very impressive one man feat!), in part because I wasn't
happy with gnuplot, which it used for graphics at the time (and
perhaps still does), and in part because it really aimed at being a
matlab clone but very few of my m-files ran w/o alteration.
matplotlib tries to solve the first problem by producing better
graphics than matlab and the second by not trying to be a drop in
replacement for matlab.

I'm curious about your experiences, what you tried, and what you found
lacking.

    Rein> I started using numarray+matplotlib by coding the Gaussian
    Rein> derivative convolutions. Calculating a derivative (by
    Rein> convolving with the derivative of the Gaussian function)
    Rein> will lead to an image(array) with both positive and negative
    Rein> values. Although imshow should deal with that (as far as i
    Rein> understand the code: beware i am a Python beginner) the
    Rein> display turns black for all derivatives (except for the
    Rein> 'zero order' derivative of course).

    Rein> What is going on? Is it me (probably) or is it imshow?

In matplotlib-0.54.2, the images must be normalized to the unit
interval before color mapping or plotting.  For example, in
examples/image_demo2.py, notice that I do 

  A *= 1.0/max(A)

Your images are black, I think, because you haven't normalized them.

I've done a lot of work on matplotlib images since 0.54.2, with new
fixes and features.  Normalization is handled by default in the 0.60
release candidate.  When I run your (very nice) example with my
development version of matplotlib, it produces this image for figure 2
( I added "show" at the end of your script, but it was otherwise
unaltered)

  http://nitace.bsd.uchicago.edu:8080/files/share/fig2.png

which looks right to me.  I'm always interested in nice screenshots
for the web site, so please consider donating this example!

I've uploaded the 0.60d release candidate to 

  http://nitace.bsd.uchicago.edu:8080/files/share/matplotlib-0.60d.tar.gz

Can you compile matplotlib yourself or are you using a binary
distribution?  If you can try the development version linked above,
that would solve two problems: you'll get enhanced image support and
I'll get a tester for my image changes.  If you do so, see the updated
help for the image related commands: imshow, figimage, clim, jet, gray
and the new matplotlibrc parameters image.*

In the figure 2 image from your script, I notice that there the titles
overlap the images above.  Here is how you can control this (requires
matplotlib 0.60d)

        # pass in these keywor args to title.  The y location is the y
        # text coordinate in axes coords (0,0 is lower left, 1,1 is
        # upper right).  You can use **somedict in place of keyword
        # args in python
        offsets = {'y':1.0, 'fontsize':10}
        _gDplot(1,0,0)
        title(r'$G$', **offsets)
        _gDplot(5,1,0)
        title(r'$G_x$', **offsets)
        _gDplot(6,0,1)
        title(r'$G_y$', **offsets)
        _gDplot(9,2,0)
        title(r'$G_{xx}$', **offsets)
        _gDplot(10,1,1)
        title(r'$G_{xy}$', **offsets)
        _gDplot(11,0,2)
        title(r'$G_{yy}$', **offsets)
        _gDplot(13,3,0)
        title(r'$G_{xxx}$', **offsets)
        _gDplot(14,2,1)
        title(r'$G_{xxy}$', **offsets)
        _gDplot(15,1,2)
        title(r'$G_{xyy}$', **offsets)
        _gDplot(16,0,3)
        title(r'$G_{yyy}$', **offsets)

Cheers,
JDH

Dear All,

as i'm new to this list let me first introduce myself before posting a 
question.

I'm working in the field of image processing and computer vision for a long 
time now and i am a long time matlab user. Up to now i didn't like any of the 
matlab clones but it seems that numarray+matplotlib might be a winner here.

I started using numarray+matplotlib by coding the Gaussian derivative 
convolutions. Calculating a derivative (by convolving with the derivative of 
the Gaussian function) will lead to an image(array) with both positive and 
negative values. Although imshow should deal with that (as far as i 
understand the code: beware i am a Python beginner) the display turns black 
for all derivatives (except for the 'zero order' derivative of course).

What is going on? Is it me (probably) or is it imshow?

Attached you find the code.

Regards
Rein van den Boomgaard
University of Amsterdam
The Netherlands



# ==========================================================
# Gaussian Derivatives
#
# Copyright (c) Rein van den Boomgaard
#               Vision Consultancy & Training
#               re...@vi...
# 
# ==========================================================
import types
from numarray import *
from numarray.nd_image import *




def gD( image, scales, orders, nscales=4, mode='reflect' ):
    scales = _normalize_sequence(scales,image)
    orders = _normalize_sequence(orders,image)

    result = image.copy()
    ndims = len( image.shape )
    for i in range(0,ndims):
        N = ceil(scales[i]*nscales)
        x = arange( -N, N )
        
        w = GaussianDerivativeFunction( x, 
                                        scales[i], 
                                        orders[i] )
        result = convolve1d( result, w, i, mode = mode )
    return( result )



def HermiteH( n, x ):
    """
    Hermite Poynomial
    """
    if n==0:
        return 0*x + 1
    elif n==1:
        return 2*x
    else:
        return 2*x*HermiteH( n-1, x ) - 2*(n-1)*HermiteH(n-2,x)


def GaussianDerivativeFunction( x, scale, order ):
    scale = float(scale)
    g = 1.0 / ( scale * sqrt(2*pi) ) * exp( - x**2 / (2*scale**2) )
    return (-1.0 / (scale*sqrt(2.0)))**order * \
           HermiteH( order, x / (scale * sqrt(2)) ) * g



# the _normalize_sequence function is copied from numarray
# because i cant import it...???

def _normalize_sequence(input, array):
    """If input is a scalar, create a sequence of length equal to the
    rank of array by duplicating the input. If input is a sequence,
    check if its length is equalt to the lenght of array.

    """
    if isinstance(array, ArrayType):
        rank = len(array.shape)
    else:
        rank = 1
    if (isinstance(input, (types.IntType, types.LongType, types.FloatType))):
        normalized = [input] * rank
    else:
        if isinstance(input, numarray.numarraycore.NumArray):
            normalized = list(input)
        else:
            normalized = input
        if len(normalized) != rank:
            error = "sequence argument must have length equal to input rank"
            raise RuntimeError, error
    return normalized



if __name__ == "__main__":
    from matplotlib import use, interactive
    from matplotlib.matlab import *

    PLOT_1D_GAUSS = 1
    PLOT_GAUSSIAN_DERIVATIVES = 1
    PLOT_TIMING = 1

    if PLOT_1D_GAUSS:

        # testing the Gaussiand Derivatives
        x=arange(-5,5,.01)


        figure(1)
        clf()
        plot(x,GaussianDerivativeFunction(x,1,0))
        plot(x,GaussianDerivativeFunction(x,1,1))
        plot(x,GaussianDerivativeFunction(x,1,2))
        plot(x,GaussianDerivativeFunction(x,1,3))
        plot(x,GaussianDerivativeFunction(x,1,4))
        xlabel(r'$x$')
        ylabel(r'$G_n(x)$')
        title('Gaussian Derivatives')

    if PLOT_GAUSSIAN_DERIVATIVES:
        scale = 9
        
        def _gDplot(n,ox,oy):
            subplot(4,4,n)
            axis('off')
            imshow( gD(a,scale,(ox,oy)) )


        
        a = zeros( (64,64) ) * 1.0
        
        a[32,32] = 1.0
        figure(2)
        axis('off')
        title('Gaussian Derivatives')

        
        _gDplot(1,0,0)
        title(r'$G$')
        _gDplot(5,1,0)
        title(r'$G_x$')
        _gDplot(6,0,1)
        title(r'$G_y$')
        _gDplot(9,2,0)
        title(r'$G_{xx}$')
        _gDplot(10,1,1)
        title(r'$G_{xy}$')
        _gDplot(11,0,2)
        title(r'$G_{yy}$')
        _gDplot(13,3,0)
        title(r'$G_{xxx}$')
        _gDplot(14,2,1)
        title(r'$G_{xxy}$')
        _gDplot(15,1,2)
        title(r'$G_{xyy}$')
        _gDplot(16,0,3)
        title(r'$G_{yyy}$')
        
        

    if PLOT_TIMING:
        from timeit import Timer
        niter = 5
        
        def time_gD(scale):
            t = Timer( "b=gD(a,%d, 0)" % scale, "from __main__ import gD,a" )
            timing = t.timeit(number=niter )
            print( timing/niter )
            return( timing/niter )
            
        
        a = zeros( (256,256) ) * 1.0
        a[128,128] = 1.0
        figure(3)
        scales = array([1,3,5,7,9,11,15,19, 25,31,41,51])
        print(type(scales))
        plot( scales, map( time_gD, scales ), 'x' )
        xlabel('Scale (px)')
        ylabel('Time (s)')
        title('Gaussian Convolution Timings')

>>>>> "danny" == danny shevitz <dan...@ya...> writes:

    danny> I tried to implement a simple .matplotlibrc file. The
    danny> contents are: #figure.figsize:12,9 lines.linewidth:1.0

    danny> I get the following traceback:

You are trying to load backend gtk and don't have it installed.  You
should not implement your own rc file, but rather edit the one in

  C:\Python23\share\matplotlib\.matplotlibrc

(or wherever python is installed).  This is discussed in the rc file
header, also found at http://matplotlib.sourceforge.net/.matplotlibrc.
Once you have edited it, move it to another directory, your HOME dir.
On win32, you will need to set the HOME environment variable to point
to this dir.  If you edit it in place, it will work, but will be
overwritten next time you install matplotlib.

My best guess is you mangled the rc file and your backend is being set
to backend_gtk  or backend_gtkagg.  If indeed you want gtk or gtkagg,
my second guess is that you haven't properly installed the pygtk
prereqs.

JDH

>>>>> "danny" == danny shevitz <dan...@ya...> writes:

    danny> John, First things first. Thanks for all your help. I
    danny> wasn't aware of the figlegend command (even though it is
    danny> clearly in the documentation). I can do what I want with
    danny> figlegends althought it takes some fiddling to get the
    danny> positions right. I have to use explicit coordinates because
    danny> the legends are referenced to the figure not the axes so
    danny> the boxes don't default to lying inside the graphs and
    danny> cross over the axes boundaries.  In addition the legends
    danny> are in separate boxes with figlegend, which is acceptable,
    danny> but not necessarily optimal. I did run into another problem
    danny> using figlegend, namely that I can't get a handle to the
    danny> legend text so I'm not able to set the fontsize. I'd
    danny> appreciate it if you could illuminate me with how to set
    danny> fontsize in a figlegend.

The way to come to this knowledge is:

  1) look at the return value of the figlegend command - in this case
     the docs don't say what they are, but you can always print
     type(ret) or simply print(ret) where ret is the return value of
     figlegend to get an idea.  I've updated the docs to state

    A matplotlib.legend.Legend instance is returned

  2) Go to the class documentation, either by doing

     help(ret) from the python shell or going to
     http://matplotlib.sourceforge.net/classdocs.html and clicking on
     the legend link
     http://matplotlib.sourceforge.net/matplotlib.legend.html.

  3) Peruse the docs for Legend: in this case you'll see

        get_frame(self)
           return the Rectangle instance used to frame the legend

        get_lines(self)
           return a list of lines.Line2D instances in the legend

        get_patches(self)
           return a list of patch instances in the legend

        get_texts(self)
           return a list of text.Text instance in the legend


So you can do

  leg = figlegend(blah, blah)
  texts = leg.get_texts()  # get a sequence of legend texts
  lines = leg.get_lines()  # get a sequence of legend lines
  patches = leg.get_patches()  # get a sequence of legend patches

I don't mind you asking - I'm just trying to give you some pointers
for future reference.

    danny> In addition the legends are in separate boxes with
    danny> figlegend, which is acceptable, but not necessarily
    danny> optimal.

Not sure exactly what you mean.  You can put them in the same box by
controlling the list of handles and text strings you pass figlegend,
or you can turn the legend frames off....

  leg.draw_frame(False)

    danny> So, on to other things. I cooked up an example that shows
    danny> what I was originally trying to do. I have two routines,
    danny> doPlots1 and doPlots2, that do exactly the same thing. The
    danny> only difference is in the default arguments, which I don't
    danny> actually set, I just use the default. Figure 1 has the
    danny> effect I was looking for, although I for the life of me
    danny> don't understand why the two routines give difference
    danny> answers, or for that matter, why figure 1 works the way it
    danny> does.

    danny> In any case. Figure 1 is what I was shooting for. If you
    danny> want to post some reliable code that does this, I'd
    danny> appreciate it.

See my comments below:

from matplotlib.matlab import *
import Numeric as N

# It is bad form to import Numeric or numarray after importing
# matplotlib.  This is what numerix is for.  You should use import
# matplotlib.numerix as N if you want to namespace Numeric.  The
# command from matplotlib.matlab import * already imports all the
# numerix symbols.

def doPlots1(const,color,legendList=[],legendTextList=[]):

# In passing the empty list as a default argument, you are sharing the
# list between function calls.  This explains why doPlots1 *works* and
# doPlots2 doesn't.  This is a well know gotcha.  The default
# arguments are evaluated *only once* at module load time, so
# legendList and legendText list are *the same* lists between function
# calls

	y1=N.arange(0., 10, 1)+ const
	x = arange(len(y1))
	
 	ln1 = plot(x,y1,color+'+-')
	legendList.append(ln1)

# ln1 is a length 1 list, not a line! You should do (note the comma)
#
#   ln1, = plot(x,y1,color+'+-')
#
# to unpack the length one sequence.  You only get a way with it
# because legend flattens the list for you

	legendTextList.append('line1')
	
	y2 = y1 + 1
	ln2 = plot(x,y2,color+'^-')
	legendList.append(ln2)
	legendTextList.append('line2')

	legend(legendList,legendTextList)
	show()

# You should only call "show" once per script.  I repeat, you should
# only call "show" once per script.  If you want to force a redraw use
# get_current_fig_manager().canvas.draw().  The next matplotlib
# release defines a "draw" function for this purpose.
	
def doPlots2(const,color):
	legendList=[]
	legendTextList=[]	

# Here legendList and legendTextList are local to the function, not
# shared between function calls

	y1=N.arange(0., 10, 1)+ const
	x = arange(len(y1))
	
	ln1 = plot(x,y1,color+'+-')
	legendList.append(ln1)
	legendTextList.append('line1')
	
	y2 = y1 + 1
	ln2 = plot(x,y2,color+'^-')
	legendList.append(ln2)
	legendTextList.append('line2')

	legend(legendList,legendTextList)
	show()

figure(1)	
doPlots1(0,'r')
doPlots1(5,'b')

figure(2)	
doPlots2(0,'r')
doPlots2(5,'b')

    danny> In any case. Figure 1 is what I was shooting for. If you
    danny> want to post some reliable code that does this, I'd
    danny> appreciate it.

While I don't know exactly what you are shooting for, the code below
replicates what Figure 1 looks like after your second call to
doPlots1.


from matplotlib.matlab import *

handles = []
labels = []	

for const, color in ( (0, 'r'), (5, 'b') ):
    y1 = arange(0., 10, 1)+ const
    x  = arange(len(y1))

    y2 = y1 + 1
    lines = plot(x, y1, color+'+-', x, y2, color+'^-' )
    handles.extend(lines)
    labels.extend(('line1', 'line2'))

legend(handles, labels, 'upper left')
show()

Here's another approach using the label keyword arg

from matplotlib.matlab import *

handles = []
labels = []	

for const, color in ( (0, 'r'), (5, 'b') ):
    y1 = arange(0., 10, 1)+ const
    x  = arange(len(y1))
    y2 = y1 + 1
    plot(x, y1, color+'+-', label='line1')
    plot(x, y2, color+'^-', label='line2' )

legend()
show()

Hope this helps!

JDH

I tried to implement a simple .matplotlibrc file. The contents are:

#figure.figsize:12,9
lines.linewidth:1.0

I get the following traceback:


No module named pygtk
matplotlib requires pygtk-1.99.16 or greater -- trying anyway.  Please
hold on
Traceback (most recent call last):
  File
"E:\projects\GeoFrag\sampleSimulations\cylinderTarget\cylinderTarget.py",
 line 10, in ?
    from nbe.simulation import Simulation
  File "E:\projects\geoFrag\nbe\simulation\__init__.py", line 1, in ?
    from simulation import Simulation
  File "E:\projects\geoFrag\nbe\simulation\simulation.py", line 1, in ?
    from nbe.treeFragments import cylinderFragmentationFactory
  File "E:\projects\geoFrag\nbe\treeFragments\__init__.py", line 10, in
?
    from cylinderFragmentation import CylinderFragmentation
  File
"E:\projects\geoFrag\nbe\treeFragments\cylinderFragmentation.py", line
7,
 in ?
    from nbe.fragments import fragmentFactory
  File "E:\projects\geoFrag\nbe\fragments\__init__.py", line 8, in ?
    from fragmentLists import FragmentLists
  File "E:\projects\geoFrag\nbe\fragments\fragmentLists.py", line 9, in
?
    from matplotlib.matlab import *
  File "D:\ENTHOU~1\Lib\site-packages\matplotlib\matlab.py", line 134,
in ?
    from backends import new_figure_manager, error_msg, \
  File "D:\ENTHOU~1\Lib\site-packages\matplotlib\backends\__init__.py",
line 16,
 in ?
    from backend_gtk import  \
  File
"D:\ENTHOU~1\Lib\site-packages\matplotlib\backends\backend_gtk.py",
line
13, in ?
    import gobject
ImportError: No module named gobject

Any help would be appreciated.

thanks,
Danny



		
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John, 

First things first. Thanks for all your help. I wasn't aware of the
figlegend command (even though it is clearly in the documentation). I
can do what I want with figlegends althought it takes some fiddling to
get the positions right. I have to use explicit coordinates because the
legends are referenced to the figure not the axes so the boxes don't
default to lying inside the graphs and cross over the axes boundaries.
In addition the legends are in separate boxes with figlegend, which is
acceptable, but not necessarily optimal. I did run into another problem
using figlegend, namely that I can't get a handle to the legend text so
I'm not able to set the fontsize. I'd appreciate it if you could
illuminate me with how to set fontsize in a figlegend.

So, on to other things. I cooked up an example that shows what I was
originally trying to do. I have two routines, doPlots1 and doPlots2,
that do exactly the same thing. The only difference is in the default
arguments, which I don't actually set, I just use the default. Figure 1
has the effect I was looking for, although I for the life of me don't
understand why the two routines give difference answers, or for that
matter, why figure 1 works the way it does. 

In any case. Figure 1 is what I was shooting for. If you want to post
some reliable code that does this, I'd appreciate it.

Danny

# %< -----------------------------------------------------
from matplotlib.matlab import *
import Numeric as N

def doPlots1(const,color,legendList=[],legendTextList=[]):
	y1=N.arange(0., 10, 1)+ const
	x = arange(len(y1))
	
	ln1 = plot(x,y1,color+'+-')
	legendList.append(ln1)
	legendTextList.append('line1')
	
	y2 = y1 + 1
	ln2 = plot(x,y2,color+'^-')
	legendList.append(ln2)
	legendTextList.append('line2')

	legend(legendList,legendTextList)
	show()
	
def doPlots2(const,color):
	legendList=[]
	legendTextList=[]	
	
	y1=N.arange(0., 10, 1)+ const
	x = arange(len(y1))
	
	ln1 = plot(x,y1,color+'+-')
	legendList.append(ln1)
	legendTextList.append('line1')
	
	y2 = y1 + 1
	ln2 = plot(x,y2,color+'^-')
	legendList.append(ln2)
	legendTextList.append('line2')

	legend(legendList,legendTextList)
	show()

figure(1)	
doPlots1(0,'r')
doPlots1(5,'b')

figure(2)	
doPlots2(0,'r')
doPlots2(5,'b')




		
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Hello,

Just wanted to report an error message.

file "...\dynamic_demo_wx.py" line 109, in onTimer
    self.lines[0].setdata(self.ind,self.X[:,self.count])
IndexError: Index out of range

I am running WinXP, Matplotlib 0.54.2, wx 2.4.2.4, and started the 
example from windows explorer. This error message repeats for some time, 
then the example will run for a while, then the error message again, 
back and forth.

-- 
Darren S. Dale
dd...@co...

PGP public key available

On Sat, 3 Jul 2004, John Hunter wrote:

> Make that
> 
>         l = Legend(self, handles, labels, loc)
> 
> Should work - let me know if you have any more troubles.
> 

Thanks John...i did actually try that before i sent my
previous email...sorry that the error messages were buried 
under a bunch of other stuff. I did have a problem after 
i added the self. Here is what i get (my hacked up legendDemp.py follows 
the error messages):

floyd:/home/jbenson/python>python legendDemo.py
Traceback (most recent call last):
  File "legendDemo.py", line 30, in ?
    'upper left')
  File "/usr/local/lib/python2.3/site-packages/matplotlib/figure.py", line 
179, in legend
    l = Legend(self, handles, labels, loc)
  File "/usr/local/lib/python2.3/site-packages/matplotlib/legend.py", line 
107, in __init__
    self._texts = self._get_texts(labels, textleft, upper)
  File "/usr/local/lib/python2.3/site-packages/matplotlib/legend.py", line 
215, in _get_texts
    HEIGHT = self._approx_text_height()
  File "/usr/local/lib/python2.3/site-packages/matplotlib/legend.py", line 
126, in _approx_text_height
    return 
self.FONTSIZE/72.0*self.figure.dpi.get()/self.parent.bbox.height()
AttributeError: 'NoneType' object has no attribute 'dpi'
floyd:/home/jbenson/python>
                                                   
# legendDemo.py
                                                            
from matplotlib.matlab import *
                                                                                                           
a = arange(0,3,.02)
b = arange(0,3,.02)
c=exp(a)
d=c.tolist()
d.reverse()
d = array(d)
                                                                                                           
ax = subplot(111)
lines = plot(a,c,'k--',a,d,'k:',a,c+d,'k')
                                                                                                           
bNotHacked = False
                                                                                                           
if bNotHacked:
                                                                                                           
    legend(('Model length', 'Data length', 'Total message length'), 'upper 
left')
                                                                                                           
else:
                                                                                                           
    fig = gcf()
                                                                                                           
    line1 = lines[0]
    line2 = lines[1]
    line3 = lines[2]
                                                                                                           
    fig.legend((line1, line2, line3),
               ('Model length', 'Data length', 'Total message length'),
               'upper left')
                                                                                                           
ax.set_ylim([-1,20])
ax.grid(0)
xlabel('Model complexity --->')
ylabel('Message length --->')
title('Minimum Message Length')
set(gca(), 'yticklabels', [])
set(gca(), 'xticklabels', [])
                                                                                                           
savefig('legend_demo_small', dpi=60)
savefig('legend_demo_large', dpi=120)
                                                                                                           
show()
~

Jim
 

>>>>> "danny" == danny shevitz <dan...@ya...> writes:

    danny> I have a main routine that calls a subroutine twice. In the
    danny> subroutine, a plot is drawn. If the active figure is the
    danny> same, both plots are shown at the same time in the same
    danny> figure. The problem is that both plots have legends, and it
    danny> appears as if a figure can only have one legend, so one of
    danny> the legends is overwritten (the first). The question is,
    danny> what is the best way to get the legends to be appended so
    danny> that all graph lines have legends.

I don't really understand what your problem is, but I have a few
comments.

For "figure legends" you want to use the figlegend command, as opposed
to axes legends which use the legend command.  You can have an
arbitrary number of figure legends on the same figure.

However, there is a bug in the figure legend code in matplotlib-0.54.2
that Jim Benson discovered.  In matplotlib/figure.py, you need to
replace the line that reads

        l = Legend(handles, labels, loc)

with

        l = Legend(self, handles, labels, loc)

If you have more troubles, please post some code as that might help me
understand what you are trying to do.

JDH

		
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>>>>> "Jim" == Jim Benson <jb...@se...> writes:


    Jim> Any more hints?

Make that

        l = Legend(self, handles, labels, loc)

Should work - let me know if you have any more troubles.

JDH

I have a main routine that calls a subroutine twice. In the subroutine,
a plot is drawn. If the active figure is the same, both plots are shown
at the same time in the same figure. The problem is that both plots
have legends, and it appears as if a figure can only have one legend,
so one of the legends is overwritten (the first). The question is, what
is the best way to get the legends to be appended so that all graph
lines have legends.

Thanks,
Danny


		
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>-----Original Message-----
>From: mat...@li...
>[mailto:mat...@li...]On Behalf Of John
>Hunter
> [...]
>For independent reasons, I already did away with numeric limits in
>_transforms.cpp a couple of weeks ago and these changes are in CVS.
>If one of you would be willing to try and compile CVS against gcc
>2.95.2, I would be interested to hear how it works,


I just checked out CVS: _transforms.cpp compiles fine.  There were only =
2 other minor things.  In _backend_agg.cpp, line 880 has a typo:

<<< if (origin!=3D"lower" and origin!=3D"upper")
>>> if (origin!=3D"lower" && origin!=3D"upper")

Also, for FreeBSD, in setupext.py you need an additional entry in the =
basedir dict like:

    'darwin' : [os.getenv('MPLIB_BASE') or '/usr/local', '/usr', '/sw'],
+   'freebsd4' : [os.getenv('MBLIB_BASE') or '/usr/local', '/usr'],
    'sunos5' : [os.getenv('MPLIB_BASE') or '/usr/local',],


Trevor

>>>>> "Sebastian" == Sebastian Haase <ha...@ms...> writes:

    Sebastian> and didn't have any problem.  I running debian, where
    Sebastian> 2.95 is still the "standard". Maybe this could be
    Sebastian> changed in CVS - just for one more year or so ;-)

For independent reasons, I already did away with numeric limits in
_transforms.cpp a couple of weeks ago and these changes are in CVS.
If one of you would be willing to try and compile CVS against gcc
2.95.2, I would be interested to hear how it works, and will be happy
to make any required changes.

Thanks,
JDH

I just released numarray-1.0 and wanted to give you a heads up in case
you miss it in the release notes:   numarray-1.0 needs a new windows
binary for matplotlib which is now up on source forge here:

http://prdownloads.sourceforge.net/matplotlib/matplotlib-0.54.2-numarray1.0.win32-py2.3.exe?download

Likewise, UNIX and Mac users that want to use numarray-1.0 need to
reinstall matplotlib (make sure you delete the matplotlib build
directory).

I attached the numarray-1.0 release notes in case you're interested...

Regards,
Todd

>>>>> "danny" == danny shevitz <dan...@ya...> writes:

    danny> another newbie question. BTW I am learning where to find
    danny> documentation.  Most of this stuff isn't in the
    danny> documentation per se, but in the class library, but please
    danny> bare with me.

One place to look is http://matplotlib.sf.net/matlab_interface.html
and the help for the plotting commands listed there.  If this case,
you want to see the help for the figure command:

    figure(num = 1, figsize=(8, 6), dpi=80, facecolor='w', edgecolor='k')


    Create a new figure and return a handle to it

    If figure(num) already exists, make it active and return the
    handle to it.

      figure(1)

    figsize - width in height x inches; defaults to rc figure.figsize
    dpi     - resolution; defaults to rc figure.dpi
    facecolor - the background color; defaults to rc figure.facecolor
    edgecolor - the border color; defaults to rc figure.edgecolor


One day, hopefully in the not too distant future, I'll have a user's
guide.

JDH

    danny> I am aving big troubles setting figure sizes.

    danny> In a plot command. I have tried plot(...,figsize=(6,8)) and
    danny> plot(...,figsize_inches=(6,8) set(gcf(),'figsize',(6,8))
    danny> set(gcf(),'figsize_inches',(6,8))

    danny> none work for me. OK I'm stumped, what's the right way.

    danny> thanks, Danny


		
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