doc/users/prev_whats_new/whats_new_1.1.rst
.. _whats-new-1-1:
.. contents:: Table of Contents :depth: 2
.. note::
matplotlib 1.1 supports Python 2.4 to 2.7
Kevin Davies has extended Yannick Copin's original Sankey example into a module
(:mod:~matplotlib.sankey) and provided new examples
(:doc:/gallery/specialty_plots/sankey_basics,
:doc:/gallery/specialty_plots/sankey_links,
:doc:/gallery/specialty_plots/sankey_rankine).
.. figure:: ../../gallery/specialty_plots/images/sphx_glr_sankey_rankine_001.png :target: ../../gallery/specialty_plots/sankey_rankine.html :align: center :scale: 50
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 :file:double pendulum <gallery/animation/double_pendulum_sgskip.py> which uses
:meth:matplotlib.animation.Animation.save to create the movie below.
.. raw:: html
<iframe width="420" height="315" src="https://www.youtube.com/embed/32cjc6V0OZY" frameborder="0" allowfullscreen></iframe>
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 philosophy of giving users complete control over the placement
of plot elements, Jae-Joon Lee created the matplotlib.tight_layout
module and introduced a new
command :func:~matplotlib.pyplot.tight_layout
to address the most common layout issues.
.. plot::
plt.style.use('classic')
plt.rcParams['savefig.facecolor'] = "0.8"
plt.rcParams['figure.figsize'] = 4, 3
fig, axes_list = plt.subplots(2, 1)
for ax in axes_list.flat:
ax.set(xlabel="x-label", ylabel="y-label", title="before tight_layout")
ax.locator_params(nbins=3)
plt.show()
plt.rcParams['savefig.facecolor'] = "0.8"
plt.rcParams['figure.figsize'] = 4, 3
fig, axes_list = plt.subplots(2, 1)
for ax in axes_list.flat:
ax.set(xlabel="x-label", ylabel="y-label", title="after tight_layout")
ax.locator_params(nbins=3)
plt.tight_layout()
plt.show()
The usage of this functionality can be as simple as ::
plt.tight_layout()
and it will adjust the spacing between subplots
so that the axis labels do not overlap with neighboring subplots. A
:ref:tight_layout_guide has been created to show how to use
this new tool.
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 <http://ipython.org>__. 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 the :ref:legend_guide for more detailed explanation and
examples.
.. figure:: ../../gallery/text_labels_and_annotations/images/sphx_glr_legend_demo_004.png :target: ../../gallery/text_labels_and_annotations/legend_demo.html :align: center :scale: 50
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:mplot3d was significantly expanded
Axis labels and orientation improved
Most 3D plotting functions now support empty inputs
Ticker offset display added:
.. figure:: ../../gallery/mplot3d/images/sphx_glr_offset_001.png :target: ../../gallery/mplot3d/offset.html :align: center :scale: 50
~mpl_toolkits.mplot3d.axes3d.Axes3D.contourf
gains zdir and offset kwargs. You can now do this:.. figure:: ../../gallery/mplot3d/images/sphx_glr_contourf3d_2_001.png :target: ../../gallery/mplot3d/contourf3d_2.html :align: center :scale: 50
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.labelweight parameter 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 ~mpl_toolkits.axes_grid1.axes_divider.HBoxDivider
and ~mpl_toolkits.axes_grid1.axes_divider.VBoxDivider 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 <color-colormaps_reference>.
Many bug fixes and documentation improvements.