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"""

An object-oriented plotting library.

A procedural interface is provided by the companion pyplot module,

which may be imported directly, e.g.::

import matplotlib.pyplot as plt

or using ipython::

ipython

at your terminal, followed by::

In [1]: %matplotlib

In [2]: import matplotlib.pyplot as plt

at the ipython shell prompt.

For the most part, direct use of the explicit object-oriented library is

encouraged when programming; the implicit pyplot interface is primarily for

working interactively. The exceptions to this suggestion are the pyplot

functions `.pyplot.figure`, `.pyplot.subplot`, `.pyplot.subplots`, and

`.pyplot.savefig`, which can greatly simplify scripting. See

:ref:`api_interfaces` for an explanation of the tradeoffs between the implicit

and explicit interfaces.

Modules include:

:mod:`matplotlib.axes`

The `~.axes.Axes` class. Most pyplot functions are wrappers for

`~.axes.Axes` methods. The axes module is the highest level of OO

access to the library.

:mod:`matplotlib.figure`

The `.Figure` class.

:mod:`matplotlib.artist`

The `.Artist` base class for all classes that draw things.

:mod:`matplotlib.lines`

The `.Line2D` class for drawing lines and markers.

:mod:`matplotlib.patches`

Classes for drawing polygons.

:mod:`matplotlib.text`

The `.Text` and `.Annotation` classes.

:mod:`matplotlib.image`

The `.AxesImage` and `.FigureImage` classes.

:mod:`matplotlib.collections`

Classes for efficient drawing of groups of lines or polygons.

:mod:`matplotlib.colors`

Color specifications and making colormaps.

:mod:`matplotlib.cm`

Colormaps, and the `.ScalarMappable` mixin class for providing color

mapping functionality to other classes.

:mod:`matplotlib.ticker`

Calculation of tick mark locations and formatting of tick labels.

:mod:`matplotlib.backends`

A subpackage with modules for various GUI libraries and output formats.

The base matplotlib namespace includes:

`~matplotlib.rcParams`

Default configuration settings; their defaults may be overridden using

a :file:`matplotlibrc` file.

`~matplotlib.use`

Setting the Matplotlib backend. This should be called before any

figure is created, because it is not possible to switch between

different GUI backends after that.

The following environment variables can be used to customize the behavior:

:envvar:`MPLBACKEND`

This optional variable can be set to choose the Matplotlib backend. See

:ref:`what-is-a-backend`.

:envvar:`MPLCONFIGDIR`

This is the directory used to store user customizations to

Matplotlib, as well as some caches to improve performance. If

:envvar:`MPLCONFIGDIR` is not defined, :file:`{HOME}/.config/matplotlib`

and :file:`{HOME}/.cache/matplotlib` are used on Linux, and

:file:`{HOME}/.matplotlib` on other platforms, if they are

writable. Otherwise, the Python standard library's `tempfile.gettempdir`

is used to find a base directory in which the :file:`matplotlib`

subdirectory is created.

Matplotlib was initially written by John D. Hunter (1968-2012) and is now

developed and maintained by a host of others.

Occasionally the internal documentation (python docstrings) will refer

to MATLAB®, a registered trademark of The MathWorks, Inc.

"""

__all__ = [

"__bibtex__",

"__version__",

"__version_info__",

"set_loglevel",

"ExecutableNotFoundError",

"get_configdir",

"get_cachedir",

"get_data_path",

"matplotlib_fname",

"MatplotlibDeprecationWarning",

"RcParams",

"rc_params",

"rc_params_from_file",

"rcParamsDefault",

"rcParams",

"rcParamsOrig",

"defaultParams",

"rc",

"rcdefaults",

"rc_file_defaults",

"rc_file",

"rc_context",

"use",

"get_backend",

"interactive",

"is_interactive",

"colormaps",

"multivar_colormaps",

"bivar_colormaps",

"color_sequences",

]

import atexit

from collections import namedtuple

from collections.abc import MutableMapping

import contextlib

import functools

import importlib

import inspect

from inspect import Parameter

import locale

import logging

import os

from pathlib import Path

import pprint

import re

import shutil

import subprocess

import sys

import tempfile

from packaging.version import parse as parse_version

# cbook must import matplotlib only within function

# definitions, so it is safe to import from it here.

from . import _api, _version, cbook, rcsetup

from matplotlib._api import MatplotlibDeprecationWarning

from matplotlib.colors import _color_sequences as color_sequences

from matplotlib.rcsetup import cycler # noqa: F401

_log = logging.getLogger(__name__)

__bibtex__ = r"""@Article{Hunter:2007,

Author = {Hunter, J. D.},

Title = {Matplotlib: A 2D graphics environment},

Journal = {Computing in Science \& Engineering},

Volume = {9},

Number = {3},

Pages = {90--95},

abstract = {Matplotlib is a 2D graphics package used for Python

for application development, interactive scripting, and

publication-quality image generation across user

interfaces and operating systems.},

publisher = {IEEE COMPUTER SOC},

year = 2007

}"""

# modelled after sys.version_info

_VersionInfo = namedtuple('_VersionInfo',

'major, minor, micro, releaselevel, serial')

def _parse_to_version_info(version_str):

"""

Parse a version string to a namedtuple analogous to sys.version_info.

See:

https://packaging.pypa.io/en/latest/version.html#packaging.version.parse

https://docs.python.org/3/library/sys.html#sys.version_info

"""

v = parse_version(version_str)

if v.pre is None and v.post is None and v.dev is None:

return _VersionInfo(v.major, v.minor, v.micro, 'final', 0)

elif v.dev is not None:

return _VersionInfo(v.major, v.minor, v.micro, 'alpha', v.dev)

elif v.pre is not None:

releaselevel = {

'a': 'alpha',

'b': 'beta',

'rc': 'candidate'}.get(v.pre[0], 'alpha')

return _VersionInfo(v.major, v.minor, v.micro, releaselevel, v.pre[1])

else:

# fallback for v.post: guess-next-dev scheme from setuptools_scm

return _VersionInfo(v.major, v.minor, v.micro + 1, 'alpha', v.post)

def _get_version():

"""Return the version string used for __version__."""

# Only shell out to a git subprocess if really needed, i.e. when we are in

# a matplotlib git repo but not in a shallow clone, such as those used by

# CI, as the latter would trigger a warning from setuptools_scm.

root = Path(__file__).resolve().parents[2]

if ((root / ".matplotlib-repo").exists()

and (root / ".git").exists()

and not (root / ".git/shallow").exists()):

try:

import setuptools_scm

except ImportError:

pass

else:

return setuptools_scm.get_version(

root=root,

dist_name="matplotlib",

version_scheme="release-branch-semver",

local_scheme="node-and-date",

fallback_version=_version.version,

)

# Get the version from the _version.py file if not in repo or setuptools_scm is

# unavailable.

return _version.version

@_api.caching_module_getattr

class __getattr__:

__version__ = property(lambda self: _get_version())

__version_info__ = property(

lambda self: _parse_to_version_info(self.__version__))

def _check_versions():

# Quickfix to ensure Microsoft Visual C++ redistributable

# DLLs are loaded before importing kiwisolver

from . import ft2font # noqa: F401

for modname, minver in [

("cycler", "0.12.0"),

("dateutil", "2.7"),

("kiwisolver", "1.3.1"),

("numpy", "2.0"),

("pyparsing", "3.0"),

module = importlib.import_module(modname)

if parse_version(module.__version__) < parse_version(minver):

raise ImportError(f"Matplotlib requires {modname}>={minver}; "

f"you have {module.__version__}")

_check_versions()

# The decorator ensures this always returns the same handler (and it is only

# attached once).

@functools.cache

def _ensure_handler():

"""

The first time this function is called, attach a `StreamHandler` using the

same format as `logging.basicConfig` to the Matplotlib root logger.

Return this handler every time this function is called.

"""

handler = logging.StreamHandler()

handler.setFormatter(logging.Formatter(logging.BASIC_FORMAT))

_log.addHandler(handler)

return handler

def set_loglevel(level):

"""

Configure Matplotlib's logging levels.

Matplotlib uses the standard library `logging` framework under the root

logger 'matplotlib'. This is a helper function to:

- set Matplotlib's root logger level

- set the root logger handler's 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.

Users or applications that are installing their own logging handlers

may want to directly manipulate ``logging.getLogger('matplotlib')`` rather

than use this function.

Parameters

----------

level : {"NOTSET", "DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"}

The log level as defined in `Python logging levels

<https://docs.python.org/3/library/logging.html#logging-levels>`__.

For backwards compatibility, the levels are case-insensitive, but

the capitalized version is preferred in analogy to `logging.Logger.setLevel`.

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.

"""

_log.setLevel(level.upper())

_ensure_handler().setLevel(level.upper())

def _logged_cached(fmt, func=None):

"""

Decorator that logs a function's return value, and memoizes that value.

After ::

@_logged_cached(fmt)

def func(): ...

the first call to *func* will log its return value at the DEBUG level using

%-format string *fmt*, and memoize it; later calls to *func* will directly

return that value.

"""

if func is None: # Return the actual decorator.

return functools.partial(_logged_cached, fmt)

called = False

ret = None

@functools.wraps(func)

def wrapper(**kwargs):

nonlocal called, ret

if not called:

ret = func(**kwargs)

called = True

_log.debug(fmt, ret)

return ret

return wrapper

_ExecInfo = namedtuple("_ExecInfo", "executable raw_version version")

class ExecutableNotFoundError(FileNotFoundError):

"""

Error raised when an executable that Matplotlib optionally

depends on can't be found.

"""

pass

@functools.cache

def _get_executable_info(name):

"""

Get the version of some executable that Matplotlib optionally depends on.

.. warning::

The list of executables that this function supports is set according to

Matplotlib's internal needs, and may change without notice.

Parameters

----------

name : str

The executable to query. The following values are currently supported:

"dvipng", "gs", "inkscape", "magick", "pdftocairo", "pdftops". This

list is subject to change without notice.

Returns

-------

tuple

A namedtuple with fields ``executable`` (`str`) and ``version``

(`packaging.Version`, or ``None`` if the version cannot be determined).

Raises

------

ExecutableNotFoundError

If the executable is not found or older than the oldest version

supported by Matplotlib. For debugging purposes, it is also

possible to "hide" an executable from Matplotlib by adding it to the

:envvar:`_MPLHIDEEXECUTABLES` environment variable (a comma-separated

list), which must be set prior to any calls to this function.

ValueError

If the executable is not one that we know how to query.

"""

def impl(args, regex, min_ver=None, ignore_exit_code=False):

# Execute the subprocess specified by args; capture stdout and stderr.

# Search for a regex match in the output; if the match succeeds, the

# first group of the match is the version.

# Return an _ExecInfo if the executable exists, and has a version of

# at least min_ver (if set); else, raise ExecutableNotFoundError.

try:

output = subprocess.check_output(

args, stderr=subprocess.STDOUT,

text=True, errors="replace", timeout=30)

except subprocess.CalledProcessError as _cpe:

if ignore_exit_code:

output = _cpe.output

else:

raise ExecutableNotFoundError(str(_cpe)) from _cpe

except subprocess.TimeoutExpired as _te:

msg = f"Timed out running {cbook._pformat_subprocess(args)}"

raise ExecutableNotFoundError(msg) from _te

except OSError as _ose:

raise ExecutableNotFoundError(str(_ose)) from _ose

match = re.search(regex, output)

if match:

raw_version = match.group(1)

version = parse_version(raw_version)

if min_ver is not None and version < parse_version(min_ver):

raise ExecutableNotFoundError(

f"You have {args[0]} version {version} but the minimum "

f"version supported by Matplotlib is {min_ver}")

return _ExecInfo(args[0], raw_version, version)

else:

raise ExecutableNotFoundError(

f"Failed to determine the version of {args[0]} from "

f"{' '.join(args)}, which output {output}")

if name in os.environ.get("_MPLHIDEEXECUTABLES", "").split(","):

raise ExecutableNotFoundError(f"{name} was hidden")

if name == "dvipng":

return impl(["dvipng", "-version"], "(?m)^dvipng(?: .*)? (.+)", "1.6")

elif name == "gs":

execs = (["gswin32c", "gswin64c", "mgs", "gs"] # "mgs" for miktex.

if sys.platform == "win32" else

["gs"])

for e in execs:

try:

return impl([e, "--version"], "(.*)", "9")

except ExecutableNotFoundError:

pass

message = "Failed to find a Ghostscript installation"

raise ExecutableNotFoundError(message)

elif name == "inkscape":

try:

# Try headless option first (needed for Inkscape version < 1.0):

return impl(["inkscape", "--without-gui", "-V"],

"Inkscape ([^ ]*)")

except ExecutableNotFoundError:

pass # Suppress exception chaining.

# If --without-gui is not accepted, we may be using Inkscape >= 1.0 so

# try without it:

return impl(["inkscape", "-V"], "Inkscape ([^ ]*)")

elif name == "magick":

if sys.platform == "win32":

# Check the registry to avoid confusing ImageMagick's convert with

# Windows's builtin convert.exe.

import winreg

binpath = ""

for flag in [0, winreg.KEY_WOW64_32KEY, winreg.KEY_WOW64_64KEY]:

try:

with winreg.OpenKeyEx(

winreg.HKEY_LOCAL_MACHINE,

r"Software\Imagemagick\Current",

0, winreg.KEY_QUERY_VALUE | flag) as hkey:

binpath = winreg.QueryValueEx(hkey, "BinPath")[0]

except OSError:

pass

path = None

if binpath:

for name in ["convert.exe", "magick.exe"]:

candidate = Path(binpath, name)

if candidate.exists():

path = str(candidate)

break

if path is None:

raise ExecutableNotFoundError(

"Failed to find an ImageMagick installation")

else:

path = "convert"

# Ignore deprecation warning for "convert" on IM>=7.1.1-33.

info = impl([path, "--version"], r"(?sm:.*^)Version: ImageMagick (\S*)")

if info.raw_version == "7.0.10-34":

# https://github.com/ImageMagick/ImageMagick/issues/2720

raise ExecutableNotFoundError(

f"You have ImageMagick {info.version}, which is unsupported")

return info

elif name == "pdftocairo":

return impl(["pdftocairo", "-v"], "pdftocairo version (.*)")

elif name == "pdftops":

info = impl(["pdftops", "-v"], "^pdftops version (.*)",

ignore_exit_code=True)

if info and not (

3 <= info.version.major or

# poppler version numbers.

parse_version("0.9") <= info.version < parse_version("1.0")):

raise ExecutableNotFoundError(

f"You have pdftops version {info.version} but the minimum "

f"version supported by Matplotlib is 3.0")

return info

else:

raise ValueError(f"Unknown executable: {name!r}")

def _get_xdg_config_dir():

"""

Return the XDG configuration directory, according to the XDG base

directory spec:

https://specifications.freedesktop.org/basedir-spec/basedir-spec-latest.html

"""

return os.environ.get('XDG_CONFIG_HOME') or str(Path.home() / ".config")

def _get_xdg_cache_dir():

"""

Return the XDG cache directory, according to the XDG base directory spec:

https://specifications.freedesktop.org/basedir-spec/basedir-spec-latest.html

"""

return os.environ.get('XDG_CACHE_HOME') or str(Path.home() / ".cache")

def _get_config_or_cache_dir(xdg_base_getter):

configdir = os.environ.get('MPLCONFIGDIR')

if configdir:

configdir = Path(configdir)

elif sys.platform.startswith(('linux', 'freebsd')):

# Only call _xdg_base_getter here so that MPLCONFIGDIR is tried first,

# as _xdg_base_getter can throw.

try:

configdir = Path(xdg_base_getter(), "matplotlib")

except RuntimeError: # raised if Path.home() is not available

pass

elif sys.platform == 'win32':

# On Windows, prefer %LOCALAPPDATA%\matplotlib which is the proper

# location for non-roaming application data (cache and config).

# See: https://docs.microsoft.com/en-us/windows/apps/design/app-settings/store-and-retrieve-app-data

# However, for backwards compatibility, if the old location

# (%USERPROFILE%\.matplotlib) exists, continue using it so existing

# users don't lose their config.

try:

old_configdir = Path.home() / ".matplotlib"

if old_configdir.is_dir():

configdir = old_configdir

else:

localappdata = os.environ.get('LOCALAPPDATA')

if localappdata:

configdir = Path(localappdata) / "matplotlib"

else:

configdir = old_configdir

except RuntimeError: # raised if Path.home() is not available

localappdata = os.environ.get('LOCALAPPDATA')

if localappdata:

configdir = Path(localappdata) / "matplotlib"

else:

try:

configdir = Path.home() / ".matplotlib"

except RuntimeError: # raised if Path.home() is not available

pass

if configdir:

# Resolve the path to handle potential issues with inaccessible symlinks.

configdir = configdir.resolve()

try:

configdir.mkdir(parents=True, exist_ok=True)

except OSError as exc:

_log.warning("mkdir -p failed for path %s: %s", configdir, exc)

else:

if os.access(str(configdir), os.W_OK) and configdir.is_dir():

return str(configdir)

_log.warning("%s is not a writable directory", configdir)

if os.environ.get('MPLCONFIGDIR'):

issue_msg = f"MPLCONFIGDIR ({configdir})"

else:

issue_msg = f"the default path ({configdir})"

else:

issue_msg = "resolving the home directory"

# If the config or cache directory cannot be created or is not a writable

# directory, create a temporary one.

try:

tmpdir = tempfile.mkdtemp(prefix="matplotlib-")

except OSError as exc:

raise OSError(

f"Matplotlib requires access to a writable cache directory, but there "

f"was an issue with {issue_msg}, and a temporary "

f"directory could not be created; set the MPLCONFIGDIR environment "

f"variable to a writable directory") from exc

os.environ["MPLCONFIGDIR"] = tmpdir

atexit.register(shutil.rmtree, tmpdir)

_log.warning(

"Matplotlib created a temporary cache directory at %s because there was "

"an issue with %s; it is highly recommended to set the "

"MPLCONFIGDIR environment variable to a writable directory, in particular to "

"speed up the import of Matplotlib and to better support multiprocessing.",

tmpdir, issue_msg)

return tmpdir

@_logged_cached('CONFIGDIR=%s')

def get_configdir():

"""

Return the string path of 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 Windows,

use ``%LOCALAPPDATA%\\matplotlib``. 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.

"""

return _get_config_or_cache_dir(_get_xdg_config_dir)

@_logged_cached('CACHEDIR=%s')

def get_cachedir():

"""

Return the string path of the cache directory.

The procedure used to find the directory is the same as for

`get_configdir`, except using ``$XDG_CACHE_HOME``/``$HOME/.cache`` instead

on Linux. On Windows, uses ``%LOCALAPPDATA%\\matplotlib`` (same as config).

"""

return _get_config_or_cache_dir(_get_xdg_cache_dir)

@_logged_cached('matplotlib data path: %s')

def get_data_path():

"""Return the path to Matplotlib data."""

return str(Path(__file__).with_name("mpl-data"))

def matplotlib_fname():

"""

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.

"""

def gen_candidates():

# rely on down-stream code to make absolute. This protects us

# from having to directly get the current working directory

# which can fail if the user has ended up with a cwd that is

# non-existent.

yield 'matplotlibrc'

try:

matplotlibrc = os.environ['MATPLOTLIBRC']

except KeyError:

pass

else:

yield matplotlibrc

yield os.path.join(matplotlibrc, 'matplotlibrc')

yield os.path.join(get_configdir(), 'matplotlibrc')

yield os.path.join(get_data_path(), 'matplotlibrc')

for fname in gen_candidates():

if os.path.exists(fname) and not os.path.isdir(fname):

return fname

raise RuntimeError("Could not find matplotlibrc file; your Matplotlib "

"install is broken")

class RcParams(MutableMapping, dict):

"""

A dict-like key-value store for config parameters, including validation.

This is the data structure behind `matplotlib.rcParams`.

The complete list of rcParams can be found in :doc:`/users/explain/configuration`.

"""

validate = rcsetup._validators

# Class-level backend state: shared across all RcParams instances because

# there can only be one active backend at a time.

# rcParams["backend"] remains valid API for now, but stores the values here

# and not as regular key in the underlying dict.

_backend = rcsetup._auto_backend_sentinel

# validate values on the way in

def __init__(self, *args, **kwargs):

self.update(*args, **kwargs)

def _set(self, key, val):

"""

Directly write data bypassing deprecation and validation logic.

Notes

-----

As end user or downstream library you almost always should use

``rcParams[key] = val`` and not ``_set()``.

There are only very few special cases that need direct data access.

These cases previously used ``dict.__setitem__(rcParams, key, val)``,

which is now deprecated and replaced by ``rcParams._set(key, val)``.

Even though private, we guarantee API stability for ``rcParams._set``,

i.e. it is subject to Matplotlib's API and deprecation policy.

:meta public:

"""

if key == "backend":

RcParams._backend = val

return

dict.__setitem__(self, key, val)

def _get(self, key):

"""

Directly read data bypassing deprecation, backend and validation

logic.

Notes

-----

As end user or downstream library you almost always should use

``val = rcParams[key]`` and not ``_get()``.

There are only very few special cases that need direct data access.

These cases previously used ``dict.__getitem__(rcParams, key, val)``,

which is now deprecated and replaced by ``rcParams._get(key)``.

Even though private, we guarantee API stability for ``rcParams._get``,

i.e. it is subject to Matplotlib's API and deprecation policy.

:meta public:

"""

if key == "backend":

return RcParams._backend

return dict.__getitem__(self, key)

def _update_raw(self, other_params):

"""

Directly update the data from *other_params*, bypassing deprecation,

backend and validation logic on both sides.

This ``rcParams._update_raw(params)`` replaces the previous pattern

``dict.update(rcParams, params)``.

Parameters

----------

other_params : dict or `.RcParams`

The input mapping from which to update.

"""

if isinstance(other_params, RcParams):

other_params = dict.items(other_params)

else:

if "backend" in other_params:

# should not happen because we aim to not use "backend" as a regular

# key anymore, but keep to ensure we have not overlooked a code path.

raise RuntimeError("'backend' must not be passed to _update_raw()")

dict.update(self, other_params)

def __setitem__(self, key, val):

if (key == "backend" and val is rcsetup._auto_backend_sentinel):

# Don't let caller silently overwrite a real backend with the auto-sentinel

# (only internal code via _set() may do that).

# The primary reason for existence was covering internal rcParams logic

# since end-users do not have direct access to

# rcsetup._auto_backend_sentinel. It is likely that this is not needed

# anymore due to removing "backend" from the dict and making it

# a class attribute RcParams._backend`. But to be on the safe side, we

# keep this as long as "backend" is a valid key for rcParams.

return

valid_key = _api.getitem_checked(

self.validate, rcParam=key, _error_cls=KeyError

)

try:

cval = valid_key(val)

except ValueError as ve:

raise ValueError(f"Key {key}: {ve}") from None

if key in {"text.hinting_factor", "text.kerning_factor"} and cval is not None:

_api.warn_deprecated("3.11", name=key, obj_type="rcParam")

self._set(key, cval)

def __getitem__(self, key):

if key == "backend":

# In theory, this should only ever be used after the global rcParams

# has been set up, but better be safe e.g. in presence of breakpoints.

if (self is globals().get("rcParams")

and RcParams._backend is rcsetup._auto_backend_sentinel):

from matplotlib import pyplot as plt

plt.switch_backend(rcsetup._auto_backend_sentinel)

return RcParams._backend

return self._get(key)

def _get_backend_or_none(self):

"""Get the requested backend, if any, without triggering resolution."""

backend = RcParams._backend

return None if backend is rcsetup._auto_backend_sentinel else backend

def __repr__(self):

class_name = self.__class__.__name__

indent = len(class_name) + 1

with _api.suppress_matplotlib_deprecation_warning():

repr_split = pprint.pformat(dict(self), indent=1,

width=80 - indent).split('\n')

repr_indented = ('\n' + ' ' * indent).join(repr_split)

return f'{class_name}({repr_indented})'

def __str__(self):

return '\n'.join(map('{0[0]}: {0[1]}'.format, sorted(self.items())))

def __iter__(self):

"""Yield sorted list of keys."""

# Deprecation warnings are silenced to cover the case where some

# rcParams entries are being deprecated.

with _api.suppress_matplotlib_deprecation_warning():

yield from sorted(dict.__iter__(self))

def __len__(self):

return dict.__len__(self)

def find_all(self, pattern):

"""

Return the subset of this RcParams dictionary whose keys match,

using :func:`re.search`, the given ``pattern``.

.. note::

Changes to the returned dictionary are *not* propagated to

the parent RcParams dictionary.

"""

pattern_re = re.compile(pattern)

return self.__class__(

(key, value) for key, value in self.items() if pattern_re.search(key)

)

def copy(self):

"""Copy this RcParams instance."""

rccopy = self.__class__()

for k in self: # Skip deprecations and revalidation.

rccopy._set(k, self._get(k))

return rccopy

def rc_params(fail_on_error=False):

"""Construct a `RcParams` instance from the default Matplotlib rc file."""

return rc_params_from_file(matplotlib_fname(), fail_on_error)

@functools.cache

def _get_ssl_context():

try:

import certifi

except ImportError:

_log.debug("Could not import certifi.")

return None

import ssl

return ssl.create_default_context(cafile=certifi.where())

@contextlib.contextmanager

def _open_file_or_url(fname):

if (isinstance(fname, str)

and fname.startswith(('http://', 'https://', 'ftp://', 'file:'))):

import urllib.request

ssl_ctx = _get_ssl_context()

if ssl_ctx is None:

_log.debug(

"Could not get certifi ssl context, https may not work."

)

with urllib.request.urlopen(fname, context=ssl_ctx) as f:

yield (line.decode('utf-8') for line in f)

else:

fname = os.path.expanduser(fname)

with open(fname, encoding='utf-8') as f:

yield f

def _rc_params_in_file(fname, transform=lambda x: x, fail_on_error=False):

"""

Construct a `RcParams` instance from file *fname*.

Unlike `rc_params_from_file`, the configuration class only contains the

parameters specified in the file (i.e. default values are not filled in).

Parameters

----------

fname : path-like

The loaded file.

transform : callable, default: the identity function

A function called on each individual line of the file to transform it,

before further parsing.

fail_on_error : bool, default: False

Whether invalid entries should result in an exception or a warning.

"""

import matplotlib as mpl

rc_temp = {}

with _open_file_or_url(fname) as fd:

try:

for line_no, line in enumerate(fd, 1):

line = transform(line)

strippedline = cbook._strip_comment(line)

if not strippedline:

continue

tup = strippedline.split(':', 1)

if len(tup) != 2:

_log.warning('Missing colon in file %r, line %d (%r)',

fname, line_no, line.rstrip('\n'))

continue

key, val = tup

key = key.strip()

val = val.strip()

if val.startswith('"') and val.endswith('"'):

val = val[1:-1] # strip double quotes

if key in rc_temp:

_log.warning('Duplicate key in file %r, line %d (%r)',

fname, line_no, line.rstrip('\n'))

rc_temp[key] = (val, line, line_no)

except UnicodeDecodeError:

_log.warning('Cannot decode configuration file %r as utf-8.',

fname)

raise

config = RcParams()

for key, (val, line, line_no) in rc_temp.items():

if key in rcsetup._validators:

if fail_on_error:

config[key] = val # try to convert to proper type or raise

else:

try:

config[key] = val # try to convert to proper type or skip

except Exception as msg:

_log.warning('Bad value in file %r, line %d (%r): %s',

fname, line_no, line.rstrip('\n'), msg)

else:

# __version__ must be looked up as an attribute to trigger the

# module-level __getattr__.

version = ('main' if '.post' in mpl.__version__

else f'v{mpl.__version__}')

_log.warning("""

Bad key %(key)s in file %(fname)s, line %(line_no)s (%(line)r)

You probably need to get an updated matplotlibrc file from

https://github.com/matplotlib/matplotlib/blob/%(version)s/lib/matplotlib/mpl-data/matplotlibrc

or from the matplotlib source distribution""",

dict(key=key, fname=fname, line_no=line_no,

line=line.rstrip('\n'), version=version))

return config

def rc_params_from_file(fname, fail_on_error=False, use_default_template=True):

"""

Construct a `RcParams` from file *fname*.

Parameters

----------

fname : str or path-like

A file with Matplotlib rc settings.

fail_on_error : bool

If True, raise an error when the parser fails to convert a parameter.

use_default_template : bool

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.)

"""

config_from_file = _rc_params_in_file(fname, fail_on_error=fail_on_error)

if not use_default_template:

return config_from_file

with _api.suppress_matplotlib_deprecation_warning():

config = RcParams({**rcParamsDefault, **config_from_file})

if "".join(config['text.latex.preamble']):

_log.info("""

*****************************************************************

You have the following UNSUPPORTED LaTeX preamble customizations:

Please do not ask for support with these customizations active.

*****************************************************************

""", '\n'.join(config['text.latex.preamble']))

_log.debug('loaded rc file %s', fname)

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