Source code for matplotlib

"""
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 object-oriented library is encouraged when
programming; pyplot is primarily for working interactively.  The exceptions are
the pyplot functions `.pyplot.figure`, `.pyplot.subplot`, `.pyplot.subplots`,
and `.pyplot.savefig`, which can greatly simplify scripting.

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.

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.
"""

import atexit
from collections import namedtuple
from collections.abc import MutableMapping
import contextlib
from distutils.version import LooseVersion
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
import warnings

import numpy

# cbook must import matplotlib only within function
# definitions, so it is safe to import from it here.
from . import _api, _version, cbook, docstring, rcsetup
from matplotlib.cbook import MatplotlibDeprecationWarning, sanitize_sequence
from matplotlib.cbook import mplDeprecation  # deprecated
from matplotlib.rcsetup import validate_backend, cycler


_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
}"""


def __getattr__(name):
    if name == "__version__":
        import setuptools_scm
        global __version__  # cache it.
        # Only shell out to a git subprocess if really needed, and not on 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 / ".git").exists() and not (root / ".git/shallow").exists():
            __version__ = setuptools_scm.get_version(
                root=root,
                version_scheme="post-release",
                local_scheme="node-and-date",
                fallback_version=_version.version,
            )
        else:  # Get the version from the _version.py setuptools_scm file.
            __version__ = _version.version
        return __version__
    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")


def _check_versions():

    # Quickfix to ensure Microsoft Visual C++ redistributable
    # DLLs are loaded before importing kiwisolver
    from . import ft2font

    for modname, minver in [
            ("cycler", "0.10"),
            ("dateutil", "2.7"),
            ("kiwisolver", "1.0.1"),
            ("numpy", "1.16"),
            ("pyparsing", "2.2.1"),
    ]:
        module = importlib.import_module(modname)
        if LooseVersion(module.__version__) < minver:
            raise ImportError("Matplotlib requires {}>={}; you have {}"
                              .format(modname, minver, module.__version__))


_check_versions()


# The decorator ensures this always returns the same handler (and it is only
# attached once).
@functools.lru_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


[docs]def set_loglevel(level): """ 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. """ _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 version") class ExecutableNotFoundError(FileNotFoundError): """ Error raised when an executable that Matplotlib optionally depends on can't be found. """ pass @functools.lru_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", "pdftops". This list is subject to change without notice. Returns ------- tuple A namedtuple with fields ``executable`` (`str`) and ``version`` (`distutils.version.LooseVersion`, 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. 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, universal_newlines=True, errors="replace") except subprocess.CalledProcessError as _cpe: if ignore_exit_code: output = _cpe.output else: raise ExecutableNotFoundError(str(_cpe)) from _cpe except OSError as _ose: raise ExecutableNotFoundError(str(_ose)) from _ose match = re.search(regex, output) if match: version = LooseVersion(match.group(1)) if min_ver is not None and 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], version) else: raise ExecutableNotFoundError( f"Failed to determine the version of {args[0]} from " f"{' '.join(args)}, which output {output}") 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" info = impl([path, "--version"], r"^Version: ImageMagick (\S*)") if info.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 == "pdftops": info = impl(["pdftops", "-v"], "^pdftops version (.*)", ignore_exit_code=True) if info and not ("3.0" <= info.version # poppler version numbers. or "0.9" <= info.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("Unknown executable: {!r}".format(name)) def checkdep_usetex(s): if not s: return False if not shutil.which("tex"): _log.warning("usetex mode requires TeX.") return False try: _get_executable_info("dvipng") except ExecutableNotFoundError: _log.warning("usetex mode requires dvipng.") return False try: _get_executable_info("gs") except ExecutableNotFoundError: _log.warning("usetex mode requires ghostscript.") return False return True def _get_xdg_config_dir(): """ Return the XDG configuration directory, according to the XDG base directory spec: https://standards.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://standards.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): configdir = os.environ.get('MPLCONFIGDIR') if configdir: configdir = Path(configdir).resolve() elif sys.platform.startswith(('linux', 'freebsd')) and xdg_base: configdir = Path(xdg_base, "matplotlib") else: configdir = Path.home() / ".matplotlib" try: configdir.mkdir(parents=True, exist_ok=True) except OSError: pass else: if os.access(str(configdir), os.W_OK) and configdir.is_dir(): return str(configdir) # If the config or cache directory cannot be created or is not a writable # directory, create a temporary one. tmpdir = os.environ["MPLCONFIGDIR"] = \ tempfile.mkdtemp(prefix="matplotlib-") atexit.register(shutil.rmtree, tmpdir) _log.warning( "Matplotlib created a temporary config/cache directory at %s because " "the default path (%s) is not a writable directory; 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, configdir) return tmpdir
[docs]@_logged_cached('CONFIGDIR=%s') def get_configdir(): """ 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 ``$HOME/.matplotlib``. 3. If the chosen directory exists and is writable, use that as the configuration directory. 4. Else, create a temporary directory, and use it as the configuration directory. """ return _get_config_or_cache_dir(_get_xdg_config_dir())
[docs]@_logged_cached('CACHEDIR=%s') def get_cachedir(): """ Return the string path of the cache directory. The procedure used to find the directory is the same as for _get_config_dir, except using ``$XDG_CACHE_HOME``/``$HOME/.cache`` instead. """ return _get_config_or_cache_dir(_get_xdg_cache_dir())
[docs]@_logged_cached('matplotlib data path: %s') def get_data_path(): """Return the path to Matplotlib data.""" return str(Path(__file__).with_name("mpl-data"))
[docs]def matplotlib_fname(): """ Get the location of the config file. The file location is determined in the following order - ``$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")
# rcParams deprecated and automatically mapped to another key. # Values are tuples of (version, new_name, f_old2new, f_new2old). _deprecated_map = {} # rcParams deprecated; some can manually be mapped to another key. # Values are tuples of (version, new_name_or_None). _deprecated_ignore_map = { 'mpl_toolkits.legacy_colorbar': ('3.4', None), } # rcParams deprecated; can use None to suppress warnings; remain actually # listed in the rcParams (not included in _all_deprecated). # Values are tuples of (version,) _deprecated_remain_as_none = { 'animation.avconv_path': ('3.3',), 'animation.avconv_args': ('3.3',), 'animation.html_args': ('3.3',), } _all_deprecated = {*_deprecated_map, *_deprecated_ignore_map}
[docs]@docstring.Substitution("\n".join(map("- {}".format, rcsetup._validators))) class RcParams(MutableMapping, dict): """ A dictionary object including validation. Validating functions are defined and associated with rc parameters in :mod:`matplotlib.rcsetup`. The list of rcParams is: %s See Also -------- :ref:`customizing-with-matplotlibrc-files` """ validate = rcsetup._validators # validate values on the way in def __init__(self, *args, **kwargs): self.update(*args, **kwargs) def __setitem__(self, key, val): try: if key in _deprecated_map: version, alt_key, alt_val, inverse_alt = _deprecated_map[key] _api.warn_deprecated( version, name=key, obj_type="rcparam", alternative=alt_key) key = alt_key val = alt_val(val) elif key in _deprecated_remain_as_none and val is not None: version, = _deprecated_remain_as_none[key] _api.warn_deprecated(version, name=key, obj_type="rcparam") elif key in _deprecated_ignore_map: version, alt_key = _deprecated_ignore_map[key] _api.warn_deprecated( version, name=key, obj_type="rcparam", alternative=alt_key) return elif key == 'backend': if val is rcsetup._auto_backend_sentinel: if 'backend' in self: return try: cval = self.validate[key](val) except ValueError as ve: raise ValueError(f"Key {key}: {ve}") from None dict.__setitem__(self, key, cval) except KeyError as err: raise KeyError( f"{key} is not a valid rc parameter (see rcParams.keys() for " f"a list of valid parameters)") from err def __getitem__(self, key): if key in _deprecated_map: version, alt_key, alt_val, inverse_alt = _deprecated_map[key] _api.warn_deprecated( version, name=key, obj_type="rcparam", alternative=alt_key) return inverse_alt(dict.__getitem__(self, alt_key)) elif key in _deprecated_ignore_map: version, alt_key = _deprecated_ignore_map[key] _api.warn_deprecated( version, name=key, obj_type="rcparam", alternative=alt_key) return dict.__getitem__(self, alt_key) if alt_key else None elif key == "backend": val = dict.__getitem__(self, key) if val is rcsetup._auto_backend_sentinel: from matplotlib import pyplot as plt plt.switch_backend(rcsetup._auto_backend_sentinel) return dict.__getitem__(self, key) 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 '{}({})'.format(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.""" with _api.suppress_matplotlib_deprecation_warning(): yield from sorted(dict.__iter__(self)) def __len__(self): return dict.__len__(self)
[docs] 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 RcParams((key, value) for key, value in self.items() if pattern_re.search(key))
def copy(self): return {k: dict.__getitem__(self, k) for k in self}
[docs]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)
# Deprecated in Matplotlib 3.5. URL_REGEX = re.compile(r'^http://|^https://|^ftp://|^file:') @_api.deprecated("3.5") def is_url(filename): """Return whether *filename* is an http, https, ftp, or file URL path.""" return URL_REGEX.match(filename) is not None @functools.lru_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) encoding = locale.getpreferredencoding(do_setlocale=False) if encoding is None: encoding = "utf-8" with open(fname, encoding=encoding) 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 = line.split('#', 1)[0].strip() 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 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 %s with encoding ' '%s, check LANG and LC_* variables.', fname, locale.getpreferredencoding(do_setlocale=False) or 'utf-8 (default)') 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) elif key in _deprecated_ignore_map: version, alt_key = _deprecated_ignore_map[key] _api.warn_deprecated( version, name=key, alternative=alt_key, obj_type='rcparam', addendum="Please update your matplotlibrc.") else: # __version__ must be looked up as an attribute to trigger the # module-level __getattr__. version = ('master' 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/matplotlibrc.template or from the matplotlib source distribution""", dict(key=key, fname=fname, line_no=line_no, line=line.rstrip('\n'), version=version)) return config
[docs]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
# When constructing the global instances, we need to perform certain updates # by explicitly calling the superclass (dict.update, dict.items) to avoid # triggering resolution of _auto_backend_sentinel. 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) dict.update(rcParamsDefault, rcsetup._hardcoded_defaults) # Normally, the default matplotlibrc file contains *no* entry for backend (the # corresponding line starts with ##, not #; we fill on _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(rcParamsDefault, "backend", rcsetup._auto_backend_sentinel) rcParams = RcParams() # The global instance. dict.update(rcParams, dict.items(rcParamsDefault)) dict.update(rcParams, _rc_params_in_file(matplotlib_fname())) with _api.suppress_matplotlib_deprecation_warning(): rcParamsOrig = RcParams(rcParams.copy()) # This also checks that all rcParams are indeed listed in the template. # Assigning to rcsetup.defaultParams is left only for backcompat. defaultParams = rcsetup.defaultParams = { # We want to resolve deprecated rcParams, but not backend... key: [(rcsetup._auto_backend_sentinel if key == "backend" else rcParamsDefault[key]), validator] for key, validator in rcsetup._validators.items()} if rcParams['axes.formatter.use_locale']: locale.setlocale(locale.LC_ALL, '')
[docs]def rc(group, **kwargs): """ 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 :func:`~matplotlib.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). """ aliases = { 'lw': 'linewidth', 'ls': 'linestyle', 'c': 'color', 'fc': 'facecolor', 'ec': 'edgecolor', 'mew': 'markeredgewidth', 'aa': 'antialiased', } if isinstance(group, str): group = (group,) for g in group: for k, v in kwargs.items(): name = aliases.get(k) or k key = '%s.%s' % (g, name) try: rcParams[key] = v except KeyError as err: raise KeyError(('Unrecognized key "%s" for group "%s" and ' 'name "%s"') % (key, g, name)) from err
[docs]def rcdefaults(): """ 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. """ # Deprecation warnings were already handled when creating rcParamsDefault, # no need to reemit them here. with _api.suppress_matplotlib_deprecation_warning(): from .style.core import STYLE_BLACKLIST rcParams.clear() rcParams.update({k: v for k, v in rcParamsDefault.items() if k not in STYLE_BLACKLIST})
[docs]def rc_file_defaults(): """ Restore the `.rcParams` from the original rc file loaded by Matplotlib. Style-blacklisted `.rcParams` (defined in `matplotlib.style.core.STYLE_BLACKLIST`) are not updated. """ # Deprecation warnings were already handled when creating rcParamsOrig, no # need to reemit them here. with _api.suppress_matplotlib_deprecation_warning(): from .style.core import STYLE_BLACKLIST rcParams.update({k: rcParamsOrig[k] for k in rcParamsOrig if k not in STYLE_BLACKLIST})
[docs]def rc_file(fname, *, use_default_template=True): """ Update `.rcParams` from file. Style-blacklisted `.rcParams` (defined in `matplotlib.style.core.STYLE_BLACKLIST`) are not updated. Parameters ---------- fname : str or path-like A file with Matplotlib rc settings. use_default_template : bool 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. """ # Deprecation warnings were already handled in rc_params_from_file, no need # to reemit them here. with _api.suppress_matplotlib_deprecation_warning(): from .style.core import STYLE_BLACKLIST rc_from_file = rc_params_from_file( fname, use_default_template=use_default_template) rcParams.update({k: rc_from_file[k] for k in rc_from_file if k not in STYLE_BLACKLIST})
[docs]@contextlib.contextmanager def rc_context(rc=None, fname=None): """ Return a context manager for temporarily changing rcParams. Parameters ---------- rc : dict The rcParams to temporarily set. fname : str or path-like A file with Matplotlib rc settings. If both *fname* and *rc* are given, settings from *rc* take precedence. See Also -------- :ref:`customizing-with-matplotlibrc-files` 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' """ orig = rcParams.copy() try: if fname: rc_file(fname) if rc: rcParams.update(rc) yield finally: dict.update(rcParams, orig) # Revert to the original rcs.
[docs]def use(backend, *, force=True): """ Select the backend used for rendering and GUI integration. Parameters ---------- backend : str 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``. force : bool, 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 -------- :ref:`backends` matplotlib.get_backend """ name = validate_backend(backend) # we need to use the base-class method here to avoid (prematurely) # resolving the "auto" backend setting if dict.__getitem__(rcParams, 'backend') == name: # Nothing to do if the requested backend is already set pass else: # if pyplot is not already imported, do not import it. Doing # so may trigger a `plt.switch_backend` to the _default_ backend # before we get a chance to change to the one the user just requested plt = sys.modules.get('matplotlib.pyplot') # if pyplot is imported, then try to change backends if plt is not None: try: # we need this import check here to re-raise if the # user does not have the libraries to support their # chosen backend installed. plt.switch_backend(name) except ImportError: if force: raise # if we have not imported pyplot, then we can set the rcParam # value which will be respected when the user finally imports # pyplot else: rcParams['backend'] = backend # if the user has asked for a given backend, do not helpfully # fallback rcParams['backend_fallback'] = False
if os.environ.get('MPLBACKEND'): rcParams['backend'] = os.environ.get('MPLBACKEND')
[docs]def get_backend(): """ Return the name of the current backend. See Also -------- matplotlib.use """ return rcParams['backend']
[docs]def interactive(b): """ Set whether to redraw after every plotting command (e.g. `.pyplot.xlabel`). """ rcParams['interactive'] = b
[docs]def is_interactive(): """ Return whether to redraw after every plotting command. .. note:: This function is only intended for use in backends. End users should use `.pyplot.isinteractive` instead. """ return rcParams['interactive']
default_test_modules = [ 'matplotlib.tests', 'mpl_toolkits.tests', ] def _init_tests(): # The version of FreeType to install locally for running the # tests. This must match the value in `setupext.py` LOCAL_FREETYPE_VERSION = '2.6.1' from matplotlib import ft2font if (ft2font.__freetype_version__ != LOCAL_FREETYPE_VERSION or ft2font.__freetype_build_type__ != 'local'): _log.warning( f"Matplotlib is not built with the correct FreeType version to " f"run tests. Rebuild without setting system_freetype=1 in " f"setup.cfg. Expect many image comparison failures below. " f"Expected freetype version {LOCAL_FREETYPE_VERSION}. " f"Found freetype version {ft2font.__freetype_version__}. " "Freetype build type is {}local".format( "" if ft2font.__freetype_build_type__ == 'local' else "not "))
[docs]@_api.delete_parameter("3.3", "recursionlimit") def test(verbosity=None, coverage=False, *, recursionlimit=0, **kwargs): """Run the matplotlib test suite.""" try: import pytest except ImportError: print("matplotlib.test requires pytest to run.") return -1 if not os.path.isdir(os.path.join(os.path.dirname(__file__), 'tests')): print("Matplotlib test data is not installed") return -1 old_backend = get_backend() old_recursionlimit = sys.getrecursionlimit() try: use('agg') if recursionlimit: sys.setrecursionlimit(recursionlimit) args = kwargs.pop('argv', []) provide_default_modules = True use_pyargs = True for arg in args: if any(arg.startswith(module_path) for module_path in default_test_modules): provide_default_modules = False break if os.path.exists(arg): provide_default_modules = False use_pyargs = False break if use_pyargs: args += ['--pyargs'] if provide_default_modules: args += default_test_modules if coverage: args += ['--cov'] if verbosity: args += ['-' + 'v' * verbosity] retcode = pytest.main(args, **kwargs) finally: if old_backend.lower() != 'agg': use(old_backend) if recursionlimit: sys.setrecursionlimit(old_recursionlimit) return retcode
test.__test__ = False # pytest: this function is not a test def _replacer(data, value): """ Either returns ``data[value]`` or passes ``data`` back, converts either to a sequence. """ try: # if key isn't a string don't bother if isinstance(value, str): # try to use __getitem__ value = data[value] except Exception: # key does not exist, silently fall back to key pass return sanitize_sequence(value) def _label_from_arg(y, default_name): try: return y.name except AttributeError: if isinstance(default_name, str): return default_name return None _DATA_DOC_TITLE = """ Notes ----- """ _DATA_DOC_APPENDIX = """ .. note:: In addition to the above described arguments, this function can take a *data* keyword argument. If such a *data* argument is given, {replaced} Objects passed as **data** must support item access (``data[s]``) and membership test (``s in data``). """ def _add_data_doc(docstring, replace_names): """ Add documentation for a *data* field to the given docstring. Parameters ---------- docstring : str The input docstring. replace_names : list of str or None The list of parameter names which arguments should be replaced by ``data[name]`` (if ``data[name]`` does not throw an exception). If None, replacement is attempted for all arguments. Returns ------- str The augmented docstring. """ if (docstring is None or replace_names is not None and len(replace_names) == 0): return docstring docstring = inspect.cleandoc(docstring) repl = ( (" every other argument can also be string ``s``, which is\n" " interpreted as ``data[s]`` (unless this raises an exception).") if replace_names is None else (" the following arguments can also be string ``s``, which is\n" " interpreted as ``data[s]`` (unless this raises an exception):\n" " " + ", ".join(map("*{}*".format, replace_names))) + ".") addendum = _DATA_DOC_APPENDIX.format(replaced=repl) if _DATA_DOC_TITLE not in docstring: addendum = _DATA_DOC_TITLE + addendum return docstring + addendum def _preprocess_data(func=None, *, replace_names=None, label_namer=None): """ A decorator to add a 'data' kwarg to a function. When applied:: @_preprocess_data() def func(ax, *args, **kwargs): ... the signature is modified to ``decorated(ax, *args, data=None, **kwargs)`` with the following behavior: - if called with ``data=None``, forward the other arguments to ``func``; - otherwise, *data* must be a mapping; for any argument passed in as a string ``name``, replace the argument by ``data[name]`` (if this does not throw an exception), then forward the arguments to ``func``. In either case, any argument that is a `MappingView` is also converted to a list. Parameters ---------- replace_names : list of str or None, default: None The list of parameter names for which lookup into *data* should be attempted. If None, replacement is attempted for all arguments. label_namer : str, default: None If set e.g. to "namer" (which must be a kwarg in the function's signature -- not as ``**kwargs``), if the *namer* argument passed in is a (string) key of *data* and no *label* kwarg is passed, then use the (string) value of the *namer* as *label*. :: @_preprocess_data(label_namer="foo") def func(foo, label=None): ... func("key", data={"key": value}) # is equivalent to func.__wrapped__(value, label="key") """ if func is None: # Return the actual decorator. return functools.partial( _preprocess_data, replace_names=replace_names, label_namer=label_namer) sig = inspect.signature(func) varargs_name = None varkwargs_name = None arg_names = [] params = list(sig.parameters.values()) for p in params: if p.kind is Parameter.VAR_POSITIONAL: varargs_name = p.name elif p.kind is Parameter.VAR_KEYWORD: varkwargs_name = p.name else: arg_names.append(p.name) data_param = Parameter("data", Parameter.KEYWORD_ONLY, default=None) if varkwargs_name: params.insert(-1, data_param) else: params.append(data_param) new_sig = sig.replace(parameters=params) arg_names = arg_names[1:] # remove the first "ax" / self arg assert {*arg_names}.issuperset(replace_names or []) or varkwargs_name, ( "Matplotlib internal error: invalid replace_names ({!r}) for {!r}" .format(replace_names, func.__name__)) assert label_namer is None or label_namer in arg_names, ( "Matplotlib internal error: invalid label_namer ({!r}) for {!r}" .format(label_namer, func.__name__)) @functools.wraps(func) def inner(ax, *args, data=None, **kwargs): if data is None: return func(ax, *map(sanitize_sequence, args), **kwargs) bound = new_sig.bind(ax, *args, **kwargs) auto_label = (bound.arguments.get(label_namer) or bound.kwargs.get(label_namer)) for k, v in bound.arguments.items(): if k == varkwargs_name: for k1, v1 in v.items(): if replace_names is None or k1 in replace_names: v[k1] = _replacer(data, v1) elif k == varargs_name: if replace_names is None: bound.arguments[k] = tuple(_replacer(data, v1) for v1 in v) else: if replace_names is None or k in replace_names: bound.arguments[k] = _replacer(data, v) new_args = bound.args new_kwargs = bound.kwargs args_and_kwargs = {**bound.arguments, **bound.kwargs} if label_namer and "label" not in args_and_kwargs: new_kwargs["label"] = _label_from_arg( args_and_kwargs.get(label_namer), auto_label) return func(*new_args, **new_kwargs) inner.__doc__ = _add_data_doc(inner.__doc__, replace_names) inner.__signature__ = new_sig return inner _log.debug('interactive is %s', is_interactive()) _log.debug('platform is %s', sys.platform) _log.debug('loaded modules: %s', list(sys.modules))