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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", "0.10"),
("dateutil", "2.7"),
("kiwisolver", "1.3.1"),
("numpy", "1.25"),
("pyparsing", "2.3.1"),
]:
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)
issue_msg = "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
# 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:
"""
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:
"""
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)
dict.update(self, other_params)
def _ensure_has_backend(self):
"""
Ensure that a "backend" entry exists.
Normally, the default matplotlibrc file contains *no* entry for "backend" (the
corresponding line starts with ##, not #; we fill in _auto_backend_sentinel
in that case. However, packagers can set a different default backend
(resulting in a normal `#backend: foo` line) in which case we should *not*
fill in _auto_backend_sentinel.
"""
dict.setdefault(self, "backend", rcsetup._auto_backend_sentinel)
def __setitem__(self, key, val):
if (key == "backend"
and val is rcsetup._auto_backend_sentinel
and "backend" in self):
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
self._set(key, cval)
def __getitem__(self, key):
# 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 key == "backend" and self is globals().get("rcParams"):
val = self._get(key)
if val is rcsetup._auto_backend_sentinel:
from matplotlib import pyplot as plt
plt.switch_backend(rcsetup._auto_backend_sentinel)
return self._get(key)
def _get_backend_or_none(self):
"""Get the requested backend, if any, without triggering resolution."""
backend = self._get("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:
%s
Please do not ask for support with these customizations active.
*****************************************************************
""", '\n'.join(config['text.latex.preamble']))
_log.debug('loaded rc file %s', fname)
return config
rcParamsDefault = _rc_params_in_file(
cbook._get_data_path("matplotlibrc"),
# Strip leading comment.
transform=lambda line: line[1:] if line.startswith("#") else line,
fail_on_error=True)
rcParamsDefault._update_raw(rcsetup._hardcoded_defaults)
rcParamsDefault._ensure_has_backend()
rcParams = RcParams() # The global instance.
rcParams._update_raw(rcParamsDefault)
rcParams._update_raw(_rc_params_in_file(matplotlib_fname()))
rcParamsOrig = rcParams.copy()
with _api.suppress_matplotlib_deprecation_warning():
# This also checks that all rcParams are indeed listed in the template.