matplotlib Code

190 lines (163 with data), 7.4 kB

FAQs = (
    ('NUMARRAY',
    'Does matplotlib work with numarray?',
    """\
matplotlib can work with numarray.  Currently, there is no conditional
import of numarray versus numeric.  But if you recursively replace all
occurances of 'from Numeric' with 'from numarray', and all occurances
of 'typecode' with 'type', matplotlib will work.  In the not too
distant future, I hope to automatically detect numarray or Numeric.
"""),
	
    ('GTKPATH',
    'I cannot import gtk / gdk / gobject',
    """\
95 times out of 100 this is a PATH issue.  Follow the instructions on
this <a
href=http://www.async.com.br/faq/pygtk/index.py?req=show&file=faq21.012.htp>pygtk
FAQ entry</a>.  There is a long thread on the pygtk mailing list where
Cousing Stanley got his gtk corrupted by installing glade, which
writes some older libgtk versions into the windows system dir.  Do a
file search for libgtk and make sure nothing shows up outside of your
GTK install tree.  Read <a
href=http://www.mail-archive.com/pygtk@daa.com.au/msg07324.html>this
thread</a>, which is filled with good advice.  """
    ),
    
    ('BATCHMODE',
     'Can I just generate images without having a window popup?',
     """\
The easiest way to do this is use an image backend, either <a
href=backends.html#GD>GD</a> or <a href=backends.html#Paint>Paint</a>
if you want to generate PNG images, eg, for use in a web page, or PS
if you want publication quality, scalable images.  All of these
backends run on all of the major platforms.  One additional option on
an X windows platform is to run the GTK backend under an Xvfb, which
works nicely and is not too hard to setup.  Contact
jdhunter@ace.bsd.uchicago.edu for more information if you are
interested setting this up."""),

    ('APPSERVER',
     'Can I just matplotlib in a web application server?',
     """\
Yes.  matplotlb can be used with any web application server that can
call python.  It has been used with mod_python, xml_rpc, and other
frameworks.  You'll want to use one of the image backends; <a
href=faq.html#BATCHMODE>see batch mode</a>.  Also to make small images
appropriate for use on a web page, you may want to consider the GD
backend, since it renders small font rasters using freetype2 better
than Agg or Paint, which currently use freetype1.  You can work around
the problem of small raster sizes by making your fonts appear larger
for a given by decreasing the figure size and increasing the dpi.  Eg,

<pre>
figure(figsize=(6,4))
plot(blah, blah)
savefig('myfile', dpi=75)
</pre>

See <a href=fonts.html#TTFFONTS>ttf fonts</a> for more information.
"""

     ),

    ('SHOW',
     "What's up with 'show'?  Do I have to use it?",
     """\
The use of show is probably the biggest source of confusion and
vexation among new users of matplotlib.  First of all, you do not
need this function with the image backends (Paint, GD, PS) but you do
need it with the GUI (GTK, WX) backends (unless you are running
matplotlib in <a href=interactive.html>interactive mode</a>).  <p>

The GUIs have 'mainloops' which need to be entered to do event
handling.  Unless you have threading enabled ala gui_thread (on the
TODO list), entering the mainloop is the last command you execute.
Because it is expensive to draw, I want to avoid redrawing the figure
many times in a batch script such as the following<p>

<pre>
  plot([1,2,3])            # draw here ?
  xlabel('time')           # and here ?
  ylabel('volts')          # and here ?
  title(''a simple plot')  # and here ?
  show()            
</pre>

It is possible to force matplotlib to draw after every command, which
is what you want in <a href=interactive.html>interactive mode</a>, but
in a script you want to defer all drawing until the script has
executed.  This is especially important for complex figures that take
some time to draw.  'show' is designed to tell matplotlib that you're
all done issuing commands and you want to draw the figure now.  """),
 
    ('PSGUI',
     'Can I save PS/EPS from a GUI backend?',
     """\
Yep.  Just choose a filename that contains ps in the extension, eg
<tt>somefile.ps</tt> or <tt>somefile.eps</tt> and matplotlib will try
and do the right thing.  That is, if it's an eps file, it will include
a bounding box, if it's a ps file it will output plain postscript.  It
is recommended you use matplotlib-0.50 or later for this feature to
work properly."""),

  ('TEXTOVERLAP',
   'My title or ticklabel or whatever is overlapping some other figure element, what should I do?',
   """
The default subplots take up a lot of room.  If you need extra space
for particularly large labels and titles, consider using custom <a
href=matplotlib.matlab.html#-axes>axes</a>, eg, <tt>axes([0.3, 0.3, 0.6,
0.6])</tt> gives you more room to the left and at the bottom than the
standard axes.</p>

Other things to consider.  With multiple subplots, eg, multiple rows,
turn off the xticklabels for all but the lowest subplot if they are
the same in all subplots <tt>set(gca(), 'xticklabels', [])</tt>.  You
can make the fontsizes smaller, as in <tt>xlabel('time (s)',
fontsize=8)</tt> or, for the tick labels

<pre>
t = gca().get_xticklabels()
set(t, 'fontsize', 8)
</pre>
 """),

    ('DYNAMIC',
     'Can matplotlib do dynamic plots, like digital oscilloscopes or animations?', 
    """\
Absolutely.  See for example, <a href=examples/anim.py>anim.py</a> and <a
href=examples/system_monitor.py>system_monitor.py</a>"""),

    ('PERFORMANCE',
     'Is matplotlib fast enough for very large data sets?',
     """\
The answer, of course, is "it depends".  I've worked hard to make
matplotlib work well with very large data sets (100s of MB), because
these are the kinds of data I need to handle at work.  It is very good
at handling data sets where the x axis is contiguous (eg, time) and
only a small portion of data in displayed in the viewport; see for
example <a href=examples/stock_demo.py>stock_demo.py<a/> where you can
scroll through 2 months of minute-by-minute stock quote data.  The
performance with higher dimensional data, eg, pseudocolor plots with
x, y, and intensity parameters, leaves sometime to be desired.  I'm
looking into ways to improve these cases.  Several people with high
bandwidth requirements have reported being happy with matplotlib's
performance.  If you find areas that need improvement, let me know.
"""),

    ('IMAGES',
    'Can matplotlib handle image data?',
     """\
Not currently, except as pcolor data.  It's in the works; stay tuned."""),

    ('ROTATETICKS',
     'How do I make vertical xticklabels',
     """\
You can set the rotation of any text instance to vertical

<pre>
    from matplotlib.matlab import *
    plot([1,2,3,4], [1,4,9,16])
    set(gca(), 'xticks', [1,2,3,4])
    labels = set(gca(), 'xticklabels', ['Frogs', 'Hogs', 'Bogs', 'Slogs'])
    set(labels, 'rotation', 'vertical')
    show()
</pre>
"""),

     ('WINFONTS',
      "On windows with GTK, I'm getting lots of messages about not finding the  Times font",
    """\
Apparently GTK changed the default pango font file, because this is a new problem.  You can set font aliases in C:\GTK\etc\pango\pango.aliases.  Add a line like<pre>
times = "times new roman,angsana new,mingliu,simsun,gulimche,ms gothic,latha,mangal,code2000"
</pre>
""" ),
     
     
    
     )
@header@
<h2> matplotlib FAQ </h2>

 + for name,q,a, in FAQs:
   <h4><a name=@name@>@q@</a></h4>
     @a@
   <p>
 -

@footer@