matplotlib 0.98.0 is released ============================= This is a milestone release of matplotlib with a significant internal refactoring to support better transformations, path drawing, and readily extensible coordinate projections and scales. Michael Droettboom of STScI did the lion's share of the work, but a large number of developers have made many significant contributions. This is such a significant improvement of the matplotlib code base that we are jumping from the 0.91 series to the 0.98 series, in anticipation of rapid progress to 1.0.
Downloads are available at http://sourceforge.net/project/platformdownload.php?group_id=80706 with binary installers for windows and OS X. Thanks to Charlie Moad for the builds and release. See the migration document at http://matplotlib.sf.net/MIGRATION.txt, the API changes at http://matplotlib.sf.net/API_CHANGES, and the full CHANGELOG at http://matplotlib.sf.net/CHANGELOG . You should manually any old install of site-packages/matplotlib since the new version will not properly install over it. We've also done some work on the look and feel of the web site, with a new logo an a less jarring color scheme, and are in the midst of a fairly significant documentation effort, so if you have any interest in writing documentation or doing website design, join us on the developers list and ash how you can contribute. What's new in matplotlib 0.98 ============================= This is also available on the website at http://matplotlib.sourceforge.net/whats_new.html 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 http://matplotlib.sf.net/doc/devel/add_new_projection.rst and the http://matplotlib.sf.net/matplotlib.transforms.html module documentation proper paths ------------ For the first time, matplotlib supports spine paths across backends, so you can pretty much draw anything. See the http://matplotlib.sf.net/creenshots.html#path_patch_demo screenshot . Thanks again to Michael Droettboom and STScI. histogram enhancements ---------------------- hist can handle 2D arrays and create side-by-side or stacked histograms, as well as cumulative filled and unfilled histograms http://matplotlib.sf.net/examples/pylab/histogram_demo_extended.py 2D histogram hexbin ------------------- 2D hexagonal bin histogramming with optional log colorscales: http://matplotlib.sourceforge.net/examples/pylab/hexbin_demo.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/ginput_demo.py. image optimizations ------------------- Enhancements to speed up color mapping and panning and zooming on dense images better savefig -------------- 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: rec_groupby, rec2txt, and rec_summarize. These are found in matplotlib.mlab (http://matplotlib.sf.net/matplotlib.mlab.html) 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 (see http://matplotlib.sf.net/matplotlib.patches.html#Arc-draw)win the viewport. This provides a scale free, accurate graph of the arc regardless of zoom level. See the screenshot and example at http://matplotlib.sf.net/screenshots.html#ellipse_demo imread enhanced --------------- imread (http://matplotlib.sf.net/matplotlib.image.html#-imread) now will use PIL when available to load images and return numpy arrays backend enhancements -------------------- * postscript : the postscript backend has clipping to paths (useful for polar plots) * PDF : the PDF backend handles composite glyphs properly, usetex fixes * SVG : clip to path (useful for polar plots), inkscape cut-and-paste fixes. * QT : Fixed a duplicate draw bug that slowed performance. Native qt toolbars and status bars used for the toolbar controls ------------------------------------------------------------------------- This SF.net email is sponsored by: Microsoft Defy all challenges. Microsoft(R) Visual Studio 2008. http://clk.atdmt.com/MRT/go/vse0120000070mrt/direct/01/ _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users