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Improve docs of toplevel module.
Hiding the huge RcParams.validators list, putting some sections, and reordering some functions in a more logical order?
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doc/api/matplotlib_configuration_api.rst

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.. py:currentmodule:: matplotlib
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Backend management
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==================
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.. autofunction:: use
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.. autofunction:: get_backend
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.. autofunction:: interactive
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.. autofunction:: is_interactive
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Default values and styling
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==========================
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.. py:data:: rcParams
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An instance of :class:`RcParams` for handling default matplotlib values.
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An instance of `RcParams` for handling default Matplotlib values.
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.. autoclass:: RcParams
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:no-members:
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.. automethod:: find_all
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.. autofunction:: rc_context
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.. autofunction:: rc
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.. autofunction:: rc_file
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.. autofunction:: rcdefaults
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.. autofunction:: rc_file_defaults
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.. autoclass:: RcParams
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.. autofunction:: rc_file
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.. autofunction:: rc_params
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.. autofunction:: rc_params_from_file
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.. autofunction:: matplotlib_fname
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.. autofunction:: interactive
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.. autofunction:: is_interactive
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Logging
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=======
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.. autofunction:: set_loglevel

lib/matplotlib/__init__.py

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@@ -688,7 +688,7 @@ def matplotlib_fname():
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- or ``$HOME/.config/matplotlib/matplotlibrc`` (if ``$XDG_CONFIG_HOME``
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is not defined)
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- On other platforms,
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- ``$HOME/.matplotlib/matplotlibrc`` if ``$HOME`` is defined
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- ``$HOME/.matplotlib/matplotlibrc`` if ``$HOME`` is defined
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- Lastly, it looks in ``$MATPLOTLIBDATA/matplotlibrc``, which should always
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exist.
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"""
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Validating functions are defined and associated with rc parameters in
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:mod:`matplotlib.rcsetup`.
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See Also
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--------
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:ref:`customizing-with-matplotlibrc-files`
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"""
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validate = {key: converter
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def rc_params(fail_on_error=False):
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"""Return a :class:`matplotlib.RcParams` instance from the
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default matplotlib rc file.
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"""
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"""Construct a `RcParams` instance from the default Matplotlib rc file."""
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return rc_params_from_file(matplotlib_fname(), fail_on_error)
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def _rc_params_in_file(fname, fail_on_error=False):
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"""Return :class:`matplotlib.RcParams` from the contents of the given file.
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"""
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Construct a `RcParams` instance from file *fname*.
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Unlike `rc_params_from_file`, the configuration class only contains the
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parameters specified in the file (i.e. default values are not filled in).
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def rc_params_from_file(fname, fail_on_error=False, use_default_template=True):
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"""Return :class:`matplotlib.RcParams` from the contents of the given file.
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"""
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Construct a `RcParams` from file *fname*.
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Parameters
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----------
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fname : str
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Name of file parsed for matplotlib settings.
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Name of file parsed for Matplotlib settings.
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fail_on_error : bool
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If True, raise an error when the parser fails to convert a parameter.
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use_default_template : bool
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rcParams['lines.linewidth'] = 2
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rcParams['lines.color'] = 'r'
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The following aliases are available to save typing for interactive
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users:
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The following aliases are available to save typing for interactive users:
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===== =================
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Alias Property
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rc('lines', lw=2, c='r')
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Note you can use python's kwargs dictionary facility to store
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dictionaries of default parameters. e.g., you can customize the
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font rc as follows::
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font = {'family' : 'monospace',
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'weight' : 'bold',
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'size' : 'larger'}
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rc('font', **font) # pass in the font dict as kwargs
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This enables you to easily switch between several configurations. Use
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``matplotlib.style.use('default')`` or :func:`~matplotlib.rcdefaults` to
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restore the default rc params after changes.
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Notes
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-----
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Similar functionality is available by using the normal dict interface, i.e.
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``rcParams.update({"lines.linewidth": 2, ...})`` (but ``rcParams.update``
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does not support abbreviations or grouping).
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"""
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aliases = {
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If True, initialize with default parameters before updating with those
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in the given file. If False, the current configuration persists
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and only the parameters specified in the file are updated.
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"""
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# Deprecation warnings were already handled in rc_params_from_file, no need
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# to reemit them here.
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This allows one to do::
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with mpl.rc_context(fname='screen.rc'):
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plt.plot(x, a)
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plt.plot(x, a) # uses 'screen.rc'
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with mpl.rc_context(fname='print.rc'):
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plt.plot(x, b)
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plt.plot(x, c)
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The 'a' vs. 'x' and 'c' vs. 'x' plots would have settings from
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'screen.rc', while the 'b' vs. 'x' plot would have settings from
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'print.rc'.
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plt.plot(x, b) # uses 'print.rc'
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plt.plot(x, c) # uses 'screen.rc'
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A dictionary can also be passed to the context manager::
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