[SciPy-user] ANN matplotlib-0.60.2: python graphs and charts

John Hunter jdhunter at ace.bsd.uchicago.edu
Wed Jul 14 11:32:39 CDT 2004

matplotlib is a 2D plotting library for python.  You can use
matplotlib interactively from a python shell or IDE, or embed it in
GUI applications (WX, GTK, and Tkinter).  matplotlib supports many
plot types: line plots, bar charts, log plots, images, pseudocolor
plots, legends, date plots, finance charts and more.  

What's new since matplotlib 0.50

  This is the first wide release in 5 months and there has been a
  tremendous amount of development since then, with new backends, many
  optimizations, new plotting types, new backends and enhanced text
  support. See http://matplotlib.sourceforge.net/whats_new.html for

 * Todd Miller's tkinter backend (tkagg) with good support for
   interactive plotting using the standard python shell, ipython or
   others.  matplotlib now runs on windows out of the box with python
   + numeric/numarry

 * Full Numeric / numarray integration with Todd Miller's numerix
   module.  Prebuilt installers for numeric and numarray on win32.
   Others, please set your numerix settings before building
   matplotlib, as described on

 * Mathtext: you can write TeX style math expressions anywhere in your

 * Images - figure and axes images with optional interpolated
   resampling, alpha blending of multiple images, and more with the
   imshow and figimage commands.  Interactive control of colormaps,
   intensity scaling and colorbars -

 * Text: freetype2 support, newline separated strings with arbitrary
   rotations, Paul Barrett's cross platform font

 * Jared Wahlstrand's SVG backend (alpha)

 * Support for popular financial plot types -

 * Many optimizations and extension code to remove performance
   bottlenecks.  pcolors and scatters are an order of magnitude

 * GTKAgg, WXAgg, TkAgg backends for http://antigrain.com (agg)
   rendering in the GUI canvas.  Now all the major GUIs (WX, GTK, Tk)
   can be used with a common (agg) renderer.

 * Many new examples and demos - see http://matplotlib.sf.net/examples
   or download the src distribution and look in the examples dir.

Documentation and downloads available at

John Hunter

More information about the SciPy-user mailing list