J
jdh2358
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.
Homepage: http://matplotlib.sourceforge.net/
Downloads: http://sourceforge.net/project/showfiles.php?group_id=80706&package_id=278194&release_id=617552
Screenshots: http://matplotlib.sourceforge.net/screenshots.html
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
http://matplotlib.sourceforge.net/whats_new.html.
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
http://matplotlib.sf.net/matplotlib.mlab.html#-griddata 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
http://matplotlib.sf.net/screenshots.html#path_patch_demo. Thanks to
Michael Droettboom and http://www.stsci.edu (STScI).
better transformations
In what has been described as open-heart surgery on matplotlib,
Michael Droettboom, supported by http://www.stsci.edu (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
http://matplotlib.sf.net/doc/devel/add_new_projection.rst and the
http://matplotlib.sf.net/matplotlib.transforms.html module
documentation.
histogram enhancements
hist (http://matplotlib.sf.net/matplotlib.pyplot.html#-hist) can
handle 2D arrays and create side-by-side or stacked histograms, as
well as cumulative filled and unfilled histograms; see
http://matplotlib.sf.net/examples/pylab_examples/histogram_demo_extended.py
ginput function
ginput (http://matplotlib.sf.net/matplotlib.pyplot.html#-ginput) is
a blocking function for interactive use to get input from the user.
A long requested feature submitted by Gael Varoquaux. See
http://matplotlib.sf.net/examples/pylab_examples/ginput_demo.py
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
http://matplotlib.sf.net/examples/pylab_examples/barb_demo.py
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
findobj
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
http://matplotlib.sf.net/examples/pylab_examples/findobj_demo.py
saving transparent figures
http://matplotlib.sf.net/matplotlib.pyplot.html#-savefig 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
http://matplotlib.sf.net/examples/api/mathtext_asarray.py
image optimizations
enhancements to speed up color mapping and panning and zooming on
dense images
better savefig
http://matplotlib.sf.net/matplotlib.pyplot.html#-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:
http://matplotlib.sf.net/matplotlib.mlab.html#-rec_groupby,
http://matplotlib.sf.net/matplotlib.mlab.html#-rec2txt,
http://matplotlib.sf.net/matplotlib.mlab.html#-rec_summarize
accurate elliptical arcs
In support of the http://www.jpl.nasa.gov/news/phoenix/main.php
(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
http://matplotlib.sf.net/matplotlib.patches.html#Arc-draw in the
viewport. This provides a scale free, accurate graph of the arc
regardless of zoom level. See
http://matplotlib.sf.net/screenshots.html#ellipse_demo
imread enhanced
imread (http://matplotlib.sf.net/matplotlib.image.html) 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
plots
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
http://matplotlib.sf.net/matplotlib.pyplot.html#-pie chart label
alignment, better baseline text alignment support, support for image
downsampling, more better
http://matplotlib.sf.net/matplotlib.pyplot.html#-hist functionality,
image rendering fixes... For details, see
http://matplotlib.sf.net/CHANGELOG
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.
Homepage: http://matplotlib.sourceforge.net/
Downloads: http://sourceforge.net/project/showfiles.php?group_id=80706&package_id=278194&release_id=617552
Screenshots: http://matplotlib.sourceforge.net/screenshots.html
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
http://matplotlib.sourceforge.net/whats_new.html.
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
http://matplotlib.sf.net/matplotlib.mlab.html#-griddata 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
http://matplotlib.sf.net/screenshots.html#path_patch_demo. Thanks to
Michael Droettboom and http://www.stsci.edu (STScI).
better transformations
In what has been described as open-heart surgery on matplotlib,
Michael Droettboom, supported by http://www.stsci.edu (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
http://matplotlib.sf.net/doc/devel/add_new_projection.rst and the
http://matplotlib.sf.net/matplotlib.transforms.html module
documentation.
histogram enhancements
hist (http://matplotlib.sf.net/matplotlib.pyplot.html#-hist) can
handle 2D arrays and create side-by-side or stacked histograms, as
well as cumulative filled and unfilled histograms; see
http://matplotlib.sf.net/examples/pylab_examples/histogram_demo_extended.py
ginput function
ginput (http://matplotlib.sf.net/matplotlib.pyplot.html#-ginput) is
a blocking function for interactive use to get input from the user.
A long requested feature submitted by Gael Varoquaux. See
http://matplotlib.sf.net/examples/pylab_examples/ginput_demo.py
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
http://matplotlib.sf.net/examples/pylab_examples/barb_demo.py
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
findobj
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
http://matplotlib.sf.net/examples/pylab_examples/findobj_demo.py
saving transparent figures
http://matplotlib.sf.net/matplotlib.pyplot.html#-savefig 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
http://matplotlib.sf.net/examples/api/mathtext_asarray.py
image optimizations
enhancements to speed up color mapping and panning and zooming on
dense images
better savefig
http://matplotlib.sf.net/matplotlib.pyplot.html#-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:
http://matplotlib.sf.net/matplotlib.mlab.html#-rec_groupby,
http://matplotlib.sf.net/matplotlib.mlab.html#-rec2txt,
http://matplotlib.sf.net/matplotlib.mlab.html#-rec_summarize
accurate elliptical arcs
In support of the http://www.jpl.nasa.gov/news/phoenix/main.php
(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
http://matplotlib.sf.net/matplotlib.patches.html#Arc-draw in the
viewport. This provides a scale free, accurate graph of the arc
regardless of zoom level. See
http://matplotlib.sf.net/screenshots.html#ellipse_demo
imread enhanced
imread (http://matplotlib.sf.net/matplotlib.image.html) 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
plots
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
http://matplotlib.sf.net/matplotlib.pyplot.html#-pie chart label
alignment, better baseline text alignment support, support for image
downsampling, more better
http://matplotlib.sf.net/matplotlib.pyplot.html#-hist functionality,
image rendering fixes... For details, see
http://matplotlib.sf.net/CHANGELOG