1. David Grote
  2. pygist



README for pygist-2.2*

Original documentation by Lee Busby and Zane Motteler, Modifications and updates by Dave Grote ------------------------------------------------------------------------

Python Gist

The Python Gist Scientific Graphics Package, version 2.2, written by Lee Busby and Zane Motteler of Lawrence Livermore National Laboratory, is a set of Python modules for production of general scientific graphics. We abbreviate the name to "PyGist" here and elsewhere.


Gist is a scientific graphics library written by David H. Munro of Lawrence Livermore National Laboratory, as part of the Yorick language. It features support for three common graphics output devices: X-Windows, (Color) PostScript, and ANSI/ISO Standard Computer Graphics Metafiles (CGM). The library is small (written directly to Xlib), portable, efficient, and full-featured. It produces x-vs-y plots with "good" tick marks and tick labels, 2-D quadrilateral mesh plots with contours, vector fields, or pseudocolor maps on such meshes, and a selection of 3-D plots.

The Python Gist module utilizes the numpy package. It is therefore fast and able to handle large datasets. The Gist module includes an X-windows event dispatcher which can be dynamically added to the Python interpreter. This makes fast mouse-controlled zoom, pan, and other graphic operations available to the researcher while maintaining the usual Python command-line interface.

Example use

>>> from gist import gistdemolow
>>> gistdemolow.run()

You can find more examples in gistdemo3d and gistdemomovie. Some useful commands:

>>> from numpy import * # numpy is needed
>>> from gist import * # To import the gist graphics package
>>> window() # To open the window where the plots will appear
>>> x = arange(100) * 0.1 # arange is from numpy
>>> y = sin(x)
>>> plg(y,x) # Now you should see a sine wave in the graphics window
             # Note that y comes first (so that the x can be optional)
>>> fma() # Frame advance to go to the next plot
>>> y = arange(10)
>>> plh(y) # To draw a histogram

Pygist allows you to make postscript files of the plots that you made:

>>> hcp_file('myplot.ps') # Opens a postscript file called myplot.ps
>>> hcpon() # From now on, write the plot to the postscript file after each frame advance
>>> fma() # Advances the frame and writes the image to the file
>>> hcpoff() # Stop writing plots to the postscript file

Similarly, files can be written using the cgm format, using hcp_file('myplot.cgm').


PyGist setups the event loop for interactive graphics by setting PyOS_inputHook (rl_event_hook) to u_wait_stdin. This approach was developed by Michiel de Hoon and implemented in PyGist. This approach works everywhere tested.


On all systems, install using the following two commands:

python setup.py config python setup.py install

This installs both the Python interface and the cgm file viewer, gist.


  • We assume that you have Python (2.6 or later) with numpy.
  • PyGist requires the Gnu readline package.

PyGist depends on portions of the Yorick library. To avoid a complete installation of Yorick, the relevant subdirectories (gist and play) have been extracted from Yorick and included in the src directory of the PyGist distribution.

In addition to installing the extension and Python modules in the appropriate place in the Python installation, the installation also installs Gist data files in a subdirectory "g" and the gist browser in the "bin" directory of the Python installation directory. In some cases, the GISTPATH environment variable will need to be set so that gist can find the style and palette files.


To test PyGist:

python import gistdemolow gistdemomlow.run() (ctrl-d)

For online help:

python from gist import * help(plm) for info on plm (plot mesh)