ANN: matplotlib-0.98.3 - plotting for python



matplotlib is a 2D plotting library for python for use in scripts,
applications, interactive shell work or web application servers.
matplotlib 0.98.3 is a major but stable release which brings
many new features detailed below.




Thanks to Charlie Moad for the release and for all the matplotlib
developers for the feature enhancements and bug fixes.

The following "what's new" summary is also online at

What's new

delaunay triangularization

Jeffrey Whitaker has added support for gridding irregularly spaced
data using the Matlab (TM) equivalent griddata function. This is a
long-standing feature request for matplotlib and a major
enhancement. matplotlib now ships with Robert Kern's delaunay
triangularization code (BSD license), which supports the default
griddata implementation, but there are some known corner cases where
this routine fails. As such, Jeff has provided a python wrapper to
the NCAR natgrid routines, whose licensing terms are a bit murkier,
for those who need bullet proof gridding routines. If the NCAR
toolkit is installed, griddata will detect it and use it. See for details.
Thanks Robert and Jeff.

proper paths

For the first time, matplotlib supports spline paths across
backends, so you can pretty much draw anything. See the Thanks to
Michael Droettboom and (STScI).

better transformations

In what has been described as open-heart surgery on matplotlib,
Michael Droettboom, supported by (STSci) , has
rewritten the transformation infrastructure from the ground up,
which not only makes the code more intuitive, it supports custom
user projections and scales. See and the module

histogram enhancements

hist ( can
handle 2D arrays and create side-by-side or stacked histograms, as
well as cumulative filled and unfilled histograms; see

ginput function

ginput ( is
a blocking function for interactive use to get input from the user.
A long requested feature submitted by Gael Varoquaux. See

wind barbs

Ryan May has added support for wind barbs, which are popular among
meterologists. These are similar to direction fields or quiver
plots but contain extra information about wind speed and other
attributes. See

external backends

backend developers and users can now use custom backends outside the
matplotlib tree, by using the special syntax
module://my_backend for the backend setting in the rc
file, the use directive, or in -d command line argument to
pylab/pyplot scripts


Introduced a recursive object search method to find all objects that
meet some matching criterion, ef to find all text instances in a
figure. See

saving transparent figures now
supports a *transparent* keyword argument to set the figure an axes
backgrounds transparent. Useful when you want to embed matplotlib
figures with transparent backgrounds into other documents

axes3d support removed

Amid considerable controversy from the users, we decided to pull the
experimental 3D support from matplotlib. Although basic 3D support
remains a goal, the 3D support we had was mainly orphaned, and we
need a developer with interest to step up and maintain it.

mathtext outside matplotlib

The mathtext support in matplotlib is very good, and some folks want
to be able to use it outside of matplotlib figures. We added some
helper functions to get the mathtext rendered pixel buffer as a
numpy array, with an example at

image optimizations

enhancements to speed up color mapping and panning and zooming on
dense images

better savefig now
supports save to file handles (great for web app servers) or unicode
filenames on all backends

record array functions

some more helper functions to facilitate work with record arrays:,,

accurate elliptical arcs

In support of the
(Phoenix mission) to Mars, which used matplotlib in ground tracking
of the spacecraft, Michael Droettboom built on work by Charlie Moad
to provide an extremely accurate 8-spline approximation to
elliptical arcs in the
viewport. This provides a scale free, accurate graph of the arc
regardless of zoom level. See

imread enhanced

imread ( now will use
PIL when available to load images and return numpy arrays

postscript enhancements

the postscript backend has clipping to paths (useful for polar

PDF enhancements

The PDF backend handles composite glyphs properly, usetex fixes

SVG enhancements

clip to path (useful for polar plots), inkscape cut-and-paste fixes.

QT enhancements

Fixed a duplicate draw bug that slowed performance. Native qt
toolbars and status bars used for the toolbar controls.

bug fixes and minor enhancements

Lots of bug fixes and feature enhancements: memory leaks, math
rendering, UI specific problems, dpi scaling problems, better
support for relative font sizes, patch collections, better chart label
alignment, better baseline text alignment support, support for image
downsampling, more better functionality,
image rendering fixes... For details, see




delaunay triangularization
[and more amazing things]

I'm impressed, it's growing very well, congratulations, I use it now
and then. I know people in University that use Python only/mostly
because of matplotlib.


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