This page just covers the highlights -- for the full story, see the CHANGELOG
Simon Ratcliffe and Ludwig Schwardt have released an HTML5/Canvas backend for matplotlib. The backend is almost feature complete, and they have done a lot of work comparing their html5 rendered images with our core renderer Agg. The backend features client/server interactive navigation of matplotlib figures in an html5 compliant browser.
Jae-Joon Lee has written :mod:`~matplotlib.gridspec`, a new module for doing complex subplot layouts, featuring row and column spans and more. See :ref:`gridspec-guide` for a tutorial overview.
.. plot:: users/plotting/examples/demo_gridspec01.py
Fernando Perez got tired of all the boilerplate code needed to create a figure and multiple subplots when using the matplotlib API, and wrote a :func:`~matplotlib.pyplot.subplots` helper function. Basic usage allows you to create the figure and an array of subplots with numpy indexing (starts with 0). Eg:
fig, axarr = plt.subplots(2, 2) axarr[0,0].plot([1,2,3]) # upper, left
See :ref:`pylab_examples-subplots_demo` for several code examples.
Ian Thomas has fixed a long-standing bug that has vexed our most talented developers for years. :func:`~matplotlib.pyplot.contourf` now handles interior masked regions, and the boundaries of line and filled contours coincide.
Additionally, he has contributed a new module matplotlib.tri and helper function :func:`~matplotlib.pyplot.triplot` for creating and plotting unstructured triangular grids.
.. plot:: mpl_examples/pylab_examples/triplot_demo.py
A long standing request is to support multiple calls to :func:`~matplotlib.pyplot.show`. This has been difficult because it is hard to get consistent behavior across operating systems, user interface toolkits and versions. Eric Firing has done a lot of work on rationalizing show across backends, with the desired behavior to make show raise all newly created figures and block execution until they are closed. Repeated calls to show should raise newly created figures since the last call. Eric has done a lot of testing on the user interface toolkits and versions and platforms he has access to, but it is not possible to test them all, so please report problems to the mailing list and bug tracker.
You can now place an mplot3d graph into an arbitrary axes location, supporting mixing of 2D and 3D graphs in the same figure, and/or multiple 3D graphs in a single figure, using the "projection" keyword argument to add_axes or add_subplot. Thanks Ben Root.
.. plot:: pyplots/whats_new_1_subplot3d.py
Eric Firing wrote tick_params, a convenience method for changing the appearance of ticks and tick labels. See pyplot function :func:`~matplotlib.pyplot.tick_params` and associated Axes method :meth:`~matplotlib.axes.Axes.tick_params`.
- Faster magnification of large images, and the ability to zoom in to a single pixel
- Local installs of documentation work better
- Improved "widgets" -- mouse grabbing is supported
- More accurate snapping of lines to pixel boundaries
- More consistent handling of color, particularly the alpha channel, throughout the API
The matplotlib trunk is probably in as good a shape as it has ever been, thanks to improved software carpentry. We now have a buildbot which runs a suite of nose regression tests on every svn commit, auto-generating a set of images and comparing them against a set of known-goods, sending emails to developers on failures with a pixel-by-pixel image comparison. Releases and release bugfixes happen in branches, allowing active new feature development to happen in the trunk while keeping the release branches stable. Thanks to Andrew Straw, Michael Droettboom and other matplotlib developers for the heavy lifting.
Eric Firing went on a bug fixing and closing marathon, closing over 100 bugs on the bug tracker with help from Jae-Joon Lee, Michael Droettboom, Christoph Gohlke and Michiel de Hoon.
Jae-Joon Lee has written two new guides :ref:`plotting-guide-legend` and :ref:`plotting-guide-annotation`. Michael Sarahan has written :ref:`image_tutorial`. John Hunter has written two new tutorials on working with paths and transformations: :ref:`path_tutorial` and :ref:`transforms_tutorial`.
Reinier Heeres has ported John Porter's mplot3d over to the new matplotlib transformations framework, and it is now available as a toolkit mpl_toolkits.mplot3d (which now comes standard with all mpl installs). See :ref:`mplot3d-examples-index` and :ref:`toolkit_mplot3d-tutorial`
.. plot:: pyplots/whats_new_99_mplot3d.py
Jae-Joon Lee has added a new toolkit to ease displaying multiple images in matplotlib, as well as some support for curvilinear grids to support the world coordinate system. The toolkit is included standard with all new mpl installs. See :ref:`axes_grid-examples-index` and :ref:`axes_grid_users-guide-index`.
.. plot:: pyplots/whats_new_99_axes_grid.py
Andrew Straw has added the ability to place "axis spines" -- the lines that denote the data limits -- in various arbitrary locations. No longer are your axis lines constrained to be a simple rectangle around the figure -- you can turn on or off left, bottom, right and top, as well as "detach" the spine to offset it away from the data. See :ref:`pylab_examples-spine_placement_demo` and :class:`matplotlib.spines.Spine`.
.. plot:: pyplots/whats_new_99_spines.py
It's been four months since the last matplotlib release, and there are a lot of new features and bug-fixes.
Thanks to Charlie Moad for testing and preparing the source release, including binaries for OS X and Windows for python 2.4 and 2.5 (2.6 and 3.0 will not be available until numpy is available on those releases). Thanks to the many developers who contributed to this release, with contributions from Jae-Joon Lee, Michael Droettboom, Ryan May, Eric Firing, Manuel Metz, Jouni K. Seppänen, Jeff Whitaker, Darren Dale, David Kaplan, Michiel de Hoon and many others who submitted patches
Jae-Joon has rewritten the legend class, and added support for multiple columns and rows, as well as fancy box drawing. See :func:`~matplotlib.pyplot.legend` and :class:`matplotlib.legend.Legend`.
.. plot:: pyplots/whats_new_98_4_legend.py
Jae-Joon has added lot's of support to annotations for drawing fancy boxes and connectors in annotations. See :func:`~matplotlib.pyplot.annotate` and :class:`~matplotlib.patches.BoxStyle`, :class:`~matplotlib.patches.ArrowStyle`, and :class:`~matplotlib.patches.ConnectionStyle`.
.. plot:: pyplots/whats_new_98_4_fancy.py
Michiel de Hoon has provided a native Mac OSX backend that is almost completely implemented in C. The backend can therefore use Quartz directly and, depending on the application, can be orders of magnitude faster than the existing backends. In addition, no third-party libraries are needed other than Python and NumPy. The backend is interactive from the usual terminal application on Mac using regular Python. It hasn't been tested with ipython yet, but in principle it should to work there as well. Set 'backend : macosx' in your matplotlibrc file, or run your script with:
> python myfile.py -dmacosx
Ryan May did a lot of work to rationalize the amplitude scaling of :func:`~matplotlib.pyplot.psd` and friends. See :ref:`pylab_examples-psd_demo2`. and :ref:`pylab_examples-psd_demo3`. The changes should increase MATLAB compatabililty and increase scaling options.
Added a :func:`~matplotlib.pyplot.fill_between` function to make it easier to do shaded region plots in the presence of masked data. You can pass an x array and a ylower and yupper array to fill betweem, and an optional where argument which is a logical mask where you want to do the filling.
.. plot:: pyplots/whats_new_98_4_fill_between.py
Here are the 0.98.4 notes from the CHANGELOG:
Added mdehoon's native macosx backend from sf patch 2179017 - JDH Removed the prints in the set_*style commands. Return the list of pprinted strings instead - JDH Some of the changes Michael made to improve the output of the property tables in the rest docs broke of made difficult to use some of the interactive doc helpers, eg setp and getp. Having all the rest markup in the ipython shell also confused the docstrings. I added a new rc param docstring.harcopy, to format the docstrings differently for hardcopy and other use. Ther ArtistInspector could use a little refactoring now since there is duplication of effort between the rest out put and the non-rest output - JDH Updated spectral methods (psd, csd, etc.) to scale one-sided densities by a factor of 2 and, optionally, scale all densities by the sampling frequency. This gives better MATLAB compatibility. -RM Fixed alignment of ticks in colorbars. -MGD drop the deprecated "new" keyword of np.histogram() for numpy 1.2 or later. -JJL Fixed a bug in svg backend that new_figure_manager() ignores keywords arguments such as figsize, etc. -JJL Fixed a bug that the handlelength of the new legend class set too short when numpoints=1 -JJL Added support for data with units (e.g. dates) to Axes.fill_between. -RM Added fancybox keyword to legend. Also applied some changes for better look, including baseline adjustment of the multiline texts so that it is center aligned. -JJL The transmuter classes in the patches.py are reorganized as subclasses of the Style classes. A few more box and arrow styles are added. -JJL Fixed a bug in the new legend class that didn't allowed a tuple of coordinate vlaues as loc. -JJL Improve checks for external dependencies, using subprocess (instead of deprecated popen*) and distutils (for version checking) - DSD Reimplementaion of the legend which supports baseline alignement, multi-column, and expand mode. - JJL Fixed histogram autoscaling bug when bins or range are given explicitly (fixes Debian bug 503148) - MM Added rcParam axes.unicode_minus which allows plain hypen for minus when False - JDH Added scatterpoints support in Legend. patch by Erik Tollerud - JJL Fix crash in log ticking. - MGD Added static helper method BrokenHBarCollection.span_where and Axes/pyplot method fill_between. See examples/pylab/fill_between.py - JDH Add x_isdata and y_isdata attributes to Artist instances, and use them to determine whether either or both coordinates are used when updating dataLim. This is used to fix autoscaling problems that had been triggered by axhline, axhspan, axvline, axvspan. - EF Update the psd(), csd(), cohere(), and specgram() methods of Axes and the csd() cohere(), and specgram() functions in mlab to be in sync with the changes to psd(). In fact, under the hood, these all call the same core to do computations. - RM Add 'pad_to' and 'sides' parameters to mlab.psd() to allow controlling of zero padding and returning of negative frequency components, respecitively. These are added in a way that does not change the API. - RM Fix handling of c kwarg by scatter; generalize is_string_like to accept numpy and numpy.ma string array scalars. - RM and EF Fix a possible EINTR problem in dviread, which might help when saving pdf files from the qt backend. - JKS Fix bug with zoom to rectangle and twin axes - MGD Added Jae Joon's fancy arrow, box and annotation enhancements -- see examples/pylab_examples/annotation_demo2.py Autoscaling is now supported with shared axes - EF Fixed exception in dviread that happened with Minion - JKS set_xlim, ylim now return a copy of the viewlim array to avoid modify inplace surprises Added image thumbnail generating function matplotlib.image.thumbnail. See examples/misc/image_thumbnail.py - JDH Applied scatleg patch based on ideas and work by Erik Tollerud and Jae-Joon Lee. - MM Fixed bug in pdf backend: if you pass a file object for output instead of a filename, e.g. in a wep app, we now flush the object at the end. - JKS Add path simplification support to paths with gaps. - EF Fix problem with AFM files that don't specify the font's full name or family name. - JKS Added 'scilimits' kwarg to Axes.ticklabel_format() method, for easy access to the set_powerlimits method of the major ScalarFormatter. - EF Experimental new kwarg borderpad to replace pad in legend, based on suggestion by Jae-Joon Lee. - EF Allow spy to ignore zero values in sparse arrays, based on patch by Tony Yu. Also fixed plot to handle empty data arrays, and fixed handling of markers in figlegend. - EF Introduce drawstyles for lines. Transparently split linestyles like 'steps--' into drawstyle 'steps' and linestyle '--'. Legends always use drawstyle 'default'. - MM Fixed quiver and quiverkey bugs (failure to scale properly when resizing) and added additional methods for determining the arrow angles - EF Fix polar interpolation to handle negative values of theta - MGD Reorganized cbook and mlab methods related to numerical calculations that have little to do with the goals of those two modules into a separate module numerical_methods.py Also, added ability to select points and stop point selection with keyboard in ginput and manual contour labeling code. Finally, fixed contour labeling bug. - DMK Fix backtick in Postscript output. - MGD [ 2089958 ] Path simplification for vector output backends Leverage the simplification code exposed through path_to_polygons to simplify certain well-behaved paths in the vector backends (PDF, PS and SVG). "path.simplify" must be set to True in matplotlibrc for this to work. - MGD Add "filled" kwarg to Path.intersects_path and Path.intersects_bbox. - MGD Changed full arrows slightly to avoid an xpdf rendering problem reported by Friedrich Hagedorn. - JKS Fix conversion of quadratic to cubic Bezier curves in PDF and PS backends. Patch by Jae-Joon Lee. - JKS Added 5-point star marker to plot command q- EF Fix hatching in PS backend - MGD Fix log with base 2 - MGD Added support for bilinear interpolation in NonUniformImage; patch by Gregory Lielens. - EF Added support for multiple histograms with data of different length - MM Fix step plots with log scale - MGD Fix masked arrays with markers in non-Agg backends - MGD Fix clip_on kwarg so it actually works correctly - MGD Fix locale problems in SVG backend - MGD fix quiver so masked values are not plotted - JSW improve interactive pan/zoom in qt4 backend on windows - DSD Fix more bugs in NaN/inf handling. In particular, path simplification (which does not handle NaNs or infs) will be turned off automatically when infs or NaNs are present. Also masked arrays are now converted to arrays with NaNs for consistent handling of masks and NaNs - MGD and EF