.. _whats-new-1-0:

What's new in Matplotlib 1.0 (Jul 06, 2010)

.. contents:: Table of Contents

:depth: 2

.. _whats-new-html5:

HTML5/Canvas backend

Simon Ratcliffe and Ludwig Schwardt have released an `HTML5/Canvas

<https://code.google.com/archive/p/mplh5canvas>`__ 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

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:`arranging_axes` for a tutorial

overview.

.. figure:: ../../gallery/userdemo/images/sphx_glr_demo_gridspec01_001.png

:target: ../../gallery/userdemo/demo_gridspec01.html

:align: center

:scale: 50

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). e.g.::

See :doc:`/gallery/subplots_axes_and_figures/subplot` for several code examples.

Contour fixes 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.

Additionally, he has contributed a new module :mod:`~matplotlib.tri` and

helper function :func:`~matplotlib.pyplot.triplot` for creating and

plotting unstructured triangular grids.

.. figure:: ../../gallery/images_contours_and_fields/images/sphx_glr_triplot_demo_001.png

:target: ../../gallery/images_contours_and_fields/triplot_demo.html

:align: center

:scale: 50

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

<https://mail.python.org/mailman/listinfo/matplotlib-users>`__

and `bug tracker

<https://github.com/matplotlib/matplotlib/issues>`__.

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.

.. plot::

from mpl_toolkits.mplot3d.axes3d import get_test_data

fig = plt.figure()

X = np.arange(-5, 5, 0.25)

Y = np.arange(-5, 5, 0.25)

X, Y = np.meshgrid(X, Y)

R = np.sqrt(X**2 + Y**2)

Z = np.sin(R)

ax = fig.add_subplot(1, 2, 1, projection='3d')

surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap='viridis',

linewidth=0, antialiased=False)

ax.set_zlim3d(-1.01, 1.01)

fig.colorbar(surf, shrink=0.5, aspect=5)

X, Y, Z = get_test_data(0.05)

ax = fig.add_subplot(1, 2, 2, projection='3d')

ax.plot_wireframe(X, Y, Z, rstride=10, cstride=10)

plt.show()

tick_params

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

<https://software-carpentry.org/>`__. We now have a `buildbot

<https://buildbot.net>`__ which runs a suite of `nose

<http://code.google.com/p/python-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.

Bugfix marathon

Eric Firing went on a bug fixing and closing marathon, closing over 100 bugs on

the (now-closed) SourceForge bug tracker with help from Jae-Joon Lee, Michael

Droettboom, Christoph Gohlke and Michiel de Hoon.