What's new in matplotlib
This page just covers the highlights -- for the full story, see the CHANGELOG
Matplotlib version 1.1 is the last major release compatible with Python versions 2.4 to 2.7. matplotlib 1.2 and later require versions 2.6, 2.7, and 3.1 and higher.
new in matplotlib-1.2
Philip Elson exposed the intelligence behind the tick Locator classes with a simple interface. For instance, to get no more than 5 sensible steps which span the values 10 and 19.5:
>>> import matplotlib.ticker as mticker >>> locator = mticker.MaxNLocator(nbins=5) >>> print(locator.tick_values(10, 19.5)) [ 10. 12. 14. 16. 18. 20.]
Damon McDougall added a new plotting method for the :mod:`~mpl_toolkits.mplot3d` toolkit called :meth:`~mpl_toolkits.mplot3d.axes3d.Axes3D.plot_trisurf`.
Control the lengths of colorbar extensions
Andrew Dawson added a new keyword argument extendfrac to :meth:`~matplotlib.pyplot.colorbar` to control the length of minimum and maximum colorbar extensions.
Set default bounding box in matplotlibrc
Two new defaults are available in the matplotlibrc configuration file. These are savefig.bbox, which can be set to 'standard' or 'tight,' and savefig.pad_inches, which controls the bounding box padding.
New Boxplot Functionality
Users can now incorporate their own methods for computing the median and its confidence intervals into the boxplot method. For every column of data passed to boxplot, the user can specify an accompanying median and confidence interval. :meth: matplotlib.axes.boxplot .. plot:: examples/pylab_examples/boxplot_demo3.py
new in matplotlib-1.1
Kevin Davies has extended Yannick Copin's original Sankey example into a module (:mod:`~matplotlib.sankey`) and provided new examples (:ref:`api-sankey_demo_basics`, :ref:`api-sankey_demo_links`, :ref:`api-sankey_demo_rankine`).
Ryan May has written a backend-independent framework for creating animated figures. The :mod:`~matplotlib.animation` module is intended to replace the backend-specific examples formerly in the :ref:`examples-index` listings. Examples using the new framework are in :ref:`animation-examples-index`; see the entrancing :ref:`double pendulum <animation-double_pendulum_animated>` which uses :meth:`matplotlib.animation.Animation.save` to create the movie below.
This should be considered as a beta release of the framework; please try it and provide feedback.
A frequent issue raised by users of matplotlib is the lack of a layout engine to nicely space out elements of the plots. While matplotlib still adheres to the philosphy of giving users complete control over the placement of plot elements, Jae-Joon Lee created the :mod:`~matplotlib.tight_layout` module and introduced a new command :func:`~matplotlib.pyplot.tight_layout` to address the most common layout issues.
The usage of this functionality can be as simple as
and it will adjust the spacing between subplots so that the axis labels do not overlap with neighboring subplots. A :ref:`plotting-guide-tight-layout` has been created to show how to use this new tool.
PyQT4, PySide, and IPython
Gerald Storer made the Qt4 backend compatible with PySide as well as PyQT4. At present, however, PySide does not support the PyOS_InputHook mechanism for handling gui events while waiting for text input, so it cannot be used with the new version 0.11 of IPython. Until this feature appears in PySide, IPython users should use the PyQT4 wrapper for QT4, which remains the matplotlib default.
An rcParam entry, "backend.qt4", has been added to allow users to select PyQt4, PyQt4v2, or PySide. The latter two use the Version 2 Qt API. In most cases, users can ignore this rcParam variable; it is available to aid in testing, and to provide control for users who are embedding matplotlib in a PyQt4 or PySide app.
Jae-Joon Lee has improved plot legends. First, legends for complex plots such as :meth:`~matplotlib.pyplot.stem` plots will now display correctly. Second, the 'best' placement of a legend has been improved in the presence of NANs.
See :ref:`legend-complex-plots` for more detailed explanation and examples.
In continuing the efforts to make 3D plotting in matplotlib just as easy as 2D plotting, Ben Root has made several improvements to the :mod:`~mpl_toolkits.mplot3d` module.
- :class:`~mpl_toolkits.mplot3d.axes3d.Axes3D` has been improved to bring the class towards feature-parity with regular Axes objects
- Documentation for :ref:`toolkit_mplot3d-index` was significantly expanded
- Axis labels and orientation improved
- Most 3D plotting functions now support empty inputs
- Ticker offset display added:
- :meth:`~mpl_toolkits.mplot3d.axes3d.Axes3D.contourf` gains zdir and offset kwargs. You can now do this:
Numerix support removed
After more than two years of deprecation warnings, Numerix support has now been completely removed from matplotlib.
The list of available markers for :meth:`~matplotlib.pyplot.plot` and :meth:`~matplotlib.pyplot.scatter` has now been merged. While they were mostly similar, some markers existed for one function, but not the other. This merge did result in a conflict for the 'd' diamond marker. Now, 'd' will be interpreted to always mean "thin" diamond while 'D' will mean "regular" diamond.
Thanks to Michael Droettboom for this effort.
- Unit support for polar axes and :func:`~matplotlib.axes.Axes.arrow`
- :class:`~matplotlib.projections.polar.PolarAxes` gains getters and setters for "theta_direction", and "theta_offset" to allow for theta to go in either the clock-wise or counter-clockwise direction and to specify where zero degrees should be placed. :meth:`~matplotlib.projections.polar.PolarAxes.set_theta_zero_location` is an added convenience function.
- Fixed error in argument handling for tri-functions such as :meth:`~matplotlib.pyplot.tripcolor`
axes.labelweightparameter added to rcParams.
- For :meth:`~matplotlib.pyplot.imshow`, interpolation='nearest' will now always perform an interpolation. A "none" option has been added to indicate no interpolation at all.
- An error in the Hammer projection has been fixed.
- clabel for :meth:`~matplotlib.pyplot.contour` now accepts a callable. Thanks to Daniel Hyams for the original patch.
- Jae-Joon Lee added the :class:`~mpl_toolkits.axes_grid1.axes_divider.HBox` and :class:`~mpl_toolkits.axes_grid1.axes_divider.VBox` classes.
- Christoph Gohlke reduced memory usage in :meth:`~matplotlib.pyplot.imshow`.
- :meth:`~matplotlib.pyplot.scatter` now accepts empty inputs.
- The behavior for 'symlog' scale has been fixed, but this may result in some minor changes to existing plots. This work was refined by ssyr.
- Peter Butterworth added named figure support to :func:`~matplotlib.pyplot.figure`.
- Michiel de Hoon has modified the MacOSX backend to make its interactive behavior consistent with the other backends.
- Pim Schellart added a new colormap called "cubehelix". Sameer Grover also added a colormap called "coolwarm". See it and all other colormaps :ref:`here <pylab_examples-show_colormaps>`.
- Many bug fixes and documentation improvements.
new in matplotlib-1.0
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.
Sophisticated subplot grid layout
Easy pythonic subplots
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.
Contour fixes and and triplot
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.
multiple calls to show supported
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.
mplot3d graphs can be embedded in arbitrary axes
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.
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`.
Lots of performance and feature enhancements
- 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
Much improved software carpentry
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.
new in matplotlib-0.99
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`
axes grid toolkit
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`.
Axis spine placement
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`.
new in 0.98.4
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
Fancy annotations and arrows
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`.
Native OS X backend
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
psd amplitude scaling
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.
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