matplotlib

Backend management

matplotlib.use(backend, *, force=True) [source]

Select the backend used for rendering and GUI integration.

Parameters:

backendstr The backend to switch to. This can either be one of the standard backend names, which are case-insensitive: interactive backends: GTK3Agg, GTK3Cairo, MacOSX, nbAgg, Qt4Agg, Qt4Cairo, Qt5Agg, Qt5Cairo, TkAgg, TkCairo, WebAgg, WX, WXAgg, WXCairo non-interactive backends: agg, cairo, pdf, pgf, ps, svg, template or a string of the form: module://my.module.name. forcebool, default: True If True (the default), raise an ImportError if the backend cannot be set up (either because it fails to import, or because an incompatible GUI interactive framework is already running); if False, ignore the failure.

See also

Backends

matplotlib.get_backend

matplotlib.get_backend() [source]

Return the name of the current backend.

See also

matplotlib.use

matplotlib.interactive(b) [source]

Set whether to redraw after every plotting command (e.g. pyplot.xlabel).

matplotlib.is_interactive() [source]

Return whether to redraw after every plotting command.

Default values and styling

matplotlib.rcParams

An instance of RcParams for handling default Matplotlib values.

class matplotlib.RcParams(*args, **kwargs) [source]

A dictionary object including validation.

Validating functions are defined and associated with rc parameters in matplotlib.rcsetup.

See also

The matplotlibrc file

find_all(self, pattern) [source]

Return the subset of this RcParams dictionary whose keys match, using re.search(), the given pattern.

Note

Changes to the returned dictionary are not propagated to the parent RcParams dictionary.

matplotlib.rc_context(rc=None, fname=None) [source]

Return a context manager for temporarily changing rcParams.

Parameters:	rcdict The rcParams to temporarily set. fnamestr or path-like A file with Matplotlib rc settings. If both fname and rc are given, settings from rc take precedence.

See also

The matplotlibrc file

Examples

Passing explicit values via a dict:

with mpl.rc_context({'interactive': False}):
    fig, ax = plt.subplots()
    ax.plot(range(3), range(3))
    fig.savefig('example.png')
    plt.close(fig)

Loading settings from a file:

with mpl.rc_context(fname='print.rc'):
    plt.plot(x, y)  # uses 'print.rc'

matplotlib.rc(group, **kwargs) [source]

Set the current rcParams. group is the grouping for the rc, e.g., for lines.linewidth the group is lines, for axes.facecolor, the group is axes, and so on. Group may also be a list or tuple of group names, e.g., (xtick, ytick). kwargs is a dictionary attribute name/value pairs, e.g.,:

rc('lines', linewidth=2, color='r')

sets the current rcParams and is equivalent to:

rcParams['lines.linewidth'] = 2
rcParams['lines.color'] = 'r'

The following aliases are available to save typing for interactive users:

Alias	Property
'lw'	'linewidth'
'ls'	'linestyle'
'c'	'color'
'fc'	'facecolor'
'ec'	'edgecolor'
'mew'	'markeredgewidth'
'aa'	'antialiased'

Thus you could abbreviate the above call as:

rc('lines', lw=2, c='r')

Note you can use python's kwargs dictionary facility to store dictionaries of default parameters. e.g., you can customize the font rc as follows:

font = {'family' : 'monospace',
        'weight' : 'bold',
        'size'   : 'larger'}
rc('font', **font)  # pass in the font dict as kwargs

This enables you to easily switch between several configurations. Use matplotlib.style.use('default') or rcdefaults() to restore the default rcParams after changes.

Notes

Similar functionality is available by using the normal dict interface, i.e. rcParams.update({"lines.linewidth": 2, ...}) (but rcParams.update does not support abbreviations or grouping).

matplotlib.rcdefaults() [source]

Restore the rcParams from Matplotlib's internal default style.

Style-blacklisted rcParams (defined in matplotlib.style.core.STYLE_BLACKLIST) are not updated.

See also

matplotlib.rc_file_defaults

Restore the rcParams from the rc file originally loaded by Matplotlib.

matplotlib.style.use

Use a specific style file. Call style.use('default') to restore the default style.

matplotlib.rc_file_defaults() [source]

Restore the rcParams from the original rc file loaded by Matplotlib.

Style-blacklisted rcParams (defined in matplotlib.style.core.STYLE_BLACKLIST) are not updated.

matplotlib.rc_file(fname, *, use_default_template=True) [source]

Update rcParams from file.

Style-blacklisted rcParams (defined in matplotlib.style.core.STYLE_BLACKLIST) are not updated.

Parameters:	fnamestr or path-like A file with Matplotlib rc settings. use_default_templatebool If True, initialize with default parameters before updating with those in the given file. If False, the current configuration persists and only the parameters specified in the file are updated.

matplotlib.rc_params(fail_on_error=False) [source]

Construct a RcParams instance from the default Matplotlib rc file.

matplotlib.rc_params_from_file(fname, fail_on_error=False, use_default_template=True) [source]

Construct a RcParams from file fname.

Parameters:	fnamestr or path-like A file with Matplotlib rc settings. fail_on_errorbool If True, raise an error when the parser fails to convert a parameter. use_default_templatebool If True, initialize with default parameters before updating with those in the given file. If False, the configuration class only contains the parameters specified in the file. (Useful for updating dicts.)

matplotlib.get_configdir() [source]

Return the string path of the the configuration directory.

The directory is chosen as follows:

1. If the MPLCONFIGDIR environment variable is supplied, choose that.
2. On Linux, follow the XDG specification and look first in $XDG_CONFIG_HOME, if defined, or $HOME/.config. On other platforms, choose $HOME/.matplotlib.
3. If the chosen directory exists and is writable, use that as the configuration directory.
4. Else, create a temporary directory, and use it as the configuration directory.

matplotlib.matplotlib_fname() [source]

Get the location of the config file.

The file location is determined in the following order

• $PWD/matplotlibrc
• $MATPLOTLIBRC if it is not a directory
• $MATPLOTLIBRC/matplotlibrc
• $MPLCONFIGDIR/matplotlibrc

• On Linux,

  • $XDG_CONFIG_HOME/matplotlib/matplotlibrc (if $XDG_CONFIG_HOME is defined)
  • or $HOME/.config/matplotlib/matplotlibrc (if $XDG_CONFIG_HOME is not defined)

• On other platforms, - $HOME/.matplotlib/matplotlibrc if $HOME is defined
• Lastly, it looks in $MATPLOTLIBDATA/matplotlibrc, which should always exist.

matplotlib.get_data_path(*, _from_rc=None) [source]

Return the path to Matplotlib data.

Logging

matplotlib.set_loglevel(level) [source]

Set Matplotlib's root logger and root logger handler level, creating the handler if it does not exist yet.

Typically, one should call set_loglevel("info") or set_loglevel("debug") to get additional debugging information.

Parameters:	level{"notset", "debug", "info", "warning", "error", "critical"} The log level of the handler.

Notes

The first time this function is called, an additional handler is attached to Matplotlib's root handler; this handler is reused every time and this function simply manipulates the logger and handler's level.

Miscellaneous

matplotlib.get_cachedir() [source]

Return the string path of the cache directory.

The procedure used to find the directory is the same as for _get_config_dir, except using $XDG_CACHE_HOME/$HOME/.cache instead.