New in matplotlib 1.2 ¶

Table of Contents

New in matplotlib 1.2

Note

matplotlib 1.2 supports Python 2.6, 2.7, and 3.1

Python 3.x support ¶

Matplotlib 1.2 is the first version to support Python 3.x, specifically Python 3.1 and 3.2. To make this happen in a reasonable way, we also had to drop support for Python versions earlier than 2.6.

This work was done by Michael Droettboom, the Cape Town Python Users’ Group, many others and supported financially in part by the SAGE project.

The following GUI backends work under Python 3.x: Gtk3Cairo, Qt4Agg, TkAgg and MacOSX. The other GUI backends do not yet have adequate bindings for Python 3.x, but continue to work on Python 2.6 and 2.7, particularly the Qt and QtAgg backends (which have been deprecated). The non-GUI backends, such as PDF, PS and SVG, work on both Python 2.x and 3.x.

Features that depend on the Python Imaging Library, such as JPEG handling, do not work, since the version of PIL for Python 3.x is not sufficiently mature.

PGF/TikZ backend ¶

Peter Würtz wrote a backend that allows matplotlib to export figures as drawing commands for LaTeX. These can be processed by PdfLaTeX, XeLaTeX or LuaLaTeX using the PGF/TikZ package. Usage examples and documentation are found in Typesetting With XeLaTeX/LuaLaTeX.

Locator interface ¶

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.]

Tri-Surface Plots ¶

Damon McDougall added a new plotting method for the mplot3d toolkit called plot_trisurf().

(Source code, png, pdf)

Control the lengths of colorbar extensions ¶

Andrew Dawson added a new keyword argument extendfrac to colorbar() to control the length of minimum and maximum colorbar extensions.

(Source code, png, pdf)

Figures are picklable ¶

Philip Elson added an experimental feature to make figures picklable for quick and easy short-term storage of plots. Pickle files are not designed for long term storage, are unsupported when restoring a pickle saved in another matplotlib version and are insecure when restoring a pickle from an untrusted source. Having said this, they are useful for short term storage for later modification inside matplotlib.

Set default bounding box in matplotlibrc ¶

Two new defaults are available in the matplotlibrc configuration file: 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.

(Source code, png, pdf)

New RC parameter functionality ¶

Matthew Emmett added a function and a context manager to help manage RC parameters: rc_file() and rc_context. To load RC parameters from a file:

>>> mpl.rc_file('mpl.rc')

To temporarily use RC parameters:

>>> with mpl.rc_context(fname='mpl.rc', rc={'text.usetex': True}):
>>>     ...

Streamplot ¶

Tom Flannaghan and Tony Yu have added a new streamplot() function to plot the streamlines of a vector field. This has been a long-requested feature and complements the existing quiver() function for plotting vector fields. In addition to simply plotting the streamlines of the vector field, streamplot() allows users to map the colors and/or line widths of the streamlines to a separate parameter, such as the speed or local intensity of the vector field.

(Source code)

../../_images/streamplot_demo_features_001.png

(png, pdf)

../../_images/streamplot_demo_features_011.png

(png, pdf)

New hist functionality ¶

Nic Eggert added a new stacked kwarg to hist() that allows creation of stacked histograms using any of the histogram types. Previously, this functionality was only available by using the barstacked histogram type. Now, when stacked=True is passed to the function, any of the histogram types can be stacked. The barstacked histogram type retains its previous functionality for backwards compatibility.