matplotlib-users Mailing List for matplotlib

I am displaying some images and overlaying a scalebar. The image on the screen 
displays the requested white text and bar, but they are black in the eps image.

text(1,1,'Hi John!',color=1) ---> black text in eps
text(1,1,'Hi Jochen!',color='w') ---> black text in eps

text(1,1,'I thought this would work...',color=[1,1,1]) ---> black text in eps
text(1,1,'but it didnt, so I tried this...',color='y') ---> yellow text in eps
text(1,1,'and this...',color=[1,1,0]) ---> yellow text in eps

text(1,1,'and finally this.',color=[1,1,.99]) ---> white text in eps

I tried to track this through backend_ps.py, where:
@ line 103:
    def set_color(self, r, g, b, store=1):
        if (r,g,b) != self.color:
            if r==g and r==b:
                self._pswriter.write("%1.3f setgray\n"%r)
                print "%1.3f setgray"%r

>>> 1.000 setgray

becomes this in the eps file: 0.000 setgray

I think there is too much going on behind the scenes for me to follow. This is as far as I could get.

-- 

Darren

>>>>> "Jan" == Jan Rienyer Gadil <jr...@gm...> writes:

    Jan> i am trying the table_demo.py on IDLE and i am getting this
    Jan> error message: Traceback (most recent call last): File
    Jan> "C:\Python23\practices\table.py", line 5, in -toplevel- from
    Jan> colours import get_colours ImportError: No module named
    Jan> colours

You have to download the examples directory which contains
table_demo.py -- it is available as a zip file at
http://matplotlib.sourceforge.net/matplotlib_examples_0.72.zip 

This dir contains colours.py, which table_demo imports.

JDH

>>>>> "Alex" == Alex Rada <ale...@gm...> writes:

    Alex> HI, and now I can load pylab but have problems to see
    Alex> images, infact if I try:

    >>>> from pylab import * plot([1,2,3])

There are a number of subtleties in trying to get matplotlib working
from the python shell, as described at
http://matplotlib.sf.net/interactive.html .

Try running a script

  from pylab import plot, show
  plot([1,2,3])
  show()

from the bash shell with

> python myscript.py --verbose-helpful

Do you get a plot?  If not, please post the output generated by the
script.  

JDH

HI,

and now I can load pylab but have problems to see images, infact if I try:

 >>> from pylab import *
 >>> plot([1,2,3])

I get:

art_render_invoke: no image source given
art_render_invoke: no image source given
art_render_invoke: no image source given
art_render_invoke: no image source given
art_render_invoke: no image source given
art_render_invoke: no image source given
*** attempt to put segment in horiz list twice
*** attempt to put segment in horiz list twice
*** attempt to put segment in horiz list twice
*** attempt to put segment in horiz list twice
*** attempt to put segment in horiz list twice
*** attempt to put segment in horiz list twice
*** attempt to put segment in horiz list twice
*** attempt to put segment in horiz list twice
*** attempt to put segment in horiz list twice
art_render_invoke: no image source given
[<matplotlib.lines.Line2D instance at 0xb7bea96c>]

maybe I have not the right backend settings!? I'm using GTK (backend : 
GTK, in my .matplotlibrc), I tried to install agg, but I have problems 
with the makefile...

Alex...

Alex Rada wrote:
> ImportError: No module named Numeric

You need to tell Matplotlib that you are using numarray instead of Numeric.

It can be specified in your matplotlibrc file or at runtime:

 > python myscript.py --numarray # use numarray
 > python myscript.py --Numeric # use Numeric

See section 1.2.1 of the users guide.

Robert

Hi all,

I newly installed matplotlib 0.71 on my slackware 10 with numarray 1.1 
and python 2.4, the installation goes well, but when I try to launch 
pylab I get the following error:
-------------------------------------------------------------------------------------------------------------------
Python 2.4 (#1, Feb 19 2005, 22:46:12)
[GCC 3.3.4] on linux2
Type "help", "copyright", "credits" or "license" for more information.
 >>> from pylab import *
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
  File "/usr/lib/python2.4/site-packages/pylab.py", line 1, in ?
    from matplotlib.pylab import *
  File "/usr/lib/python2.4/site-packages/matplotlib/pylab.py", line 186, 
in ?
    import cm
  File "/usr/lib/python2.4/site-packages/matplotlib/cm.py", line 5, in ?
    import colors
  File "/usr/lib/python2.4/site-packages/matplotlib/colors.py", line 32, 
in ?
    from numerix import array, arange, take, put, Float, Int, where, \
  File 
"/usr/lib/python2.4/site-packages/matplotlib/numerix/__init__.py", line 
59, in ?
    from Numeric import *
ImportError: No module named Numeric
-------------------------------------------------------------------------------------------------------------------------

thanks for the help,

Alex

i am trying the table_demo.py on IDLE and i am getting this error message:

Traceback (most recent call last):
  File "C:\Python23\practices\table.py", line 5, in -toplevel-
    from colours import get_colours
ImportError: No module named colours

i am using python 2.3 (enthought edition) with matplotlib 0.71 on Win XP.
here's the demo code by the way (copy/pasted):

#!/usr/bin/env python
import matplotlib

from pylab import *
from colours import get_colours

axes([0.2, 0.2, 0.7, 0.6])   # leave room below the axes for the table

data = [[  66386,  174296,   75131,  577908,   32015],
        [  58230,  381139,   78045,   99308,  160454],
        [  89135,   80552,  152558,  497981,  603535],
        [  78415,   81858,  150656,  193263,   69638],
        [ 139361,  331509,  343164,  781380,   52269]]

colLabels = ('Freeze', 'Wind', 'Flood', 'Quake', 'Hail')
rowLabels = ['%d year' % x for x in (100, 50, 20, 10, 5)]

# Get some pastel shades for the colours
colours = get_colours(len(colLabels))
colours.reverse()
rows = len(data)

ind = arange(len(colLabels)) + 0.3  # the x locations for the groups
cellText = []
width = 0.4     # the width of the bars
yoff = array([0.0] * len(colLabels)) # the bottom values for stacked bar chart
for row in xrange(rows):
    bar(ind, data[row], width, bottom=yoff, color=colours[row])
    yoff = yoff + data[row]
    cellText.append(['%1.1f' % (x/1000.0) for x in yoff])

# Add a table at the bottom of the axes
colours.reverse()
cellText.reverse()
the_table = table(cellText=cellText,
                  rowLabels=rowLabels, rowColours=colours,
                  colLabels=colLabels,
                  loc='bottom')
ylabel("Loss $1000's")
vals = arange(0, 2500, 500)
yticks(vals*1000, ['%d' % val for val in vals])
xticks([])
title('Loss by Disaster')
#savefig('table_demo_small', dpi=75)
#savefig('table_demo_large', dpi=300)

show()

John et al.,

I would like to phase in matplotlib to replace Matlab ASAP for plotting 
physical oceanographic observations, primarily current profile 
measurements.  I (and many other physical oceanographers) primarily use 
contourf to plot filled contours; I only rarely use line contours.  It 
looks to me like gcntr.c has the necessary functionality--the ability to 
output polygons enclosing regions between a pair of specified levels. 
Is someone already working on exposing that functionality in matplotlib, 
or is it planned?

It appears that gcntr.c also has the ability to handle missing data via 
setting elements of the reg array to zero, and that this could be 
exposed fairly easily in the contour method in axes.py by adding "reg" 
to the set of kwargs.  Correct?  If so, is this also planned?

The question of missing data handling in contour plotting brings up the 
more general issue of how to handle data gaps in plots.  For example, 
the ocean current profiles that I measure using a Doppler profiler 
extend to varying depths, and sometimes have holes in the middle where 
there are not enough acoustic scatterers to give a signal.  This sort of 
thing--data gaps--is universal in physical oceanography.  One of 
Matlab's major strengths is the way it handles them, using nan as a bad 
value flag.  Plotting a line with the plot command, the line is broken 
at each nan; so if there is a hole in the data, the plot shows exactly 
that.  The same for contouring: nans are automatically used as a mask.

Obviously, not everyone needs this kind of automatic handling of data 
gaps, but I think it would be very useful for many applications, so I 
hope it can be considered as a possible goal.  At the plotting level, 
collections may make it easier to implement than would have been the 
case in the early days of matplotlib.  At the array manipulation level, 
the implementation could involve either masked arrays or nans.  I would 
greatly prefer the Matlab-style nan approach, but I don't know whether 
this would work with Numeric.  Maybe in Numeric3?  Numarray appears 
better equipped, with its ieeespecial.py module.

Thanks for the enormous amount of beautiful work you have already done!

Eric