"""

The rcsetup module contains the validation code for customization using

Matplotlib's rc settings.

Each rc setting is assigned a function used to validate any attempted changes

to that setting. The validation functions are defined in the rcsetup module,

and are used to construct the rcParams global object which stores the settings

and is referenced throughout Matplotlib.

The default values of the rc settings are set in the default matplotlibrc file.

Any additions or deletions to the parameter set listed here should also be

propagated to the :file:`lib/matplotlib/mpl-data/matplotlibrc` in Matplotlib's

root source directory.

"""

import ast

from functools import lru_cache, reduce

from numbers import Real

import operator

import os

import re

import numpy as np

from matplotlib import _api, cbook

from matplotlib.backends import BackendFilter, backend_registry

from matplotlib.cbook import ls_mapper

from matplotlib.colors import Colormap, is_color_like

from matplotlib._fontconfig_pattern import parse_fontconfig_pattern

from matplotlib._enums import JoinStyle, CapStyle

# Don't let the original cycler collide with our validating cycler

from cycler import Cycler, cycler as ccycler

@_api.caching_module_getattr

class __getattr__:

@_api.deprecated(

"3.9",

alternative="``matplotlib.backends.backend_registry.list_builtin"

"(matplotlib.backends.BackendFilter.INTERACTIVE)``")

@property

def interactive_bk(self):

return backend_registry.list_builtin(BackendFilter.INTERACTIVE)

@_api.deprecated(

"3.9",

alternative="``matplotlib.backends.backend_registry.list_builtin"

"(matplotlib.backends.BackendFilter.NON_INTERACTIVE)``")

@property

def non_interactive_bk(self):

return backend_registry.list_builtin(BackendFilter.NON_INTERACTIVE)

@_api.deprecated(

"3.9",

alternative="``matplotlib.backends.backend_registry.list_builtin()``")

@property

def all_backends(self):

return backend_registry.list_builtin()

class ValidateInStrings:

def __init__(self, key, valid, ignorecase=False, *,

_deprecated_since=None):

"""*valid* is a list of legal strings."""

self.key = key

self.ignorecase = ignorecase

self._deprecated_since = _deprecated_since

def func(s):

if ignorecase:

return s.lower()

else:

return s

self.valid = {func(k): k for k in valid}

def __call__(self, s):

if self._deprecated_since:

name, = (k for k, v in globals().items() if v is self)

_api.warn_deprecated(

self._deprecated_since, name=name, obj_type="function")

if self.ignorecase and isinstance(s, str):

s = s.lower()

if s in self.valid:

return self.valid[s]

msg = (f"{s!r} is not a valid value for {self.key}; supported values "

f"are {[*self.valid.values()]}")

if (isinstance(s, str)

and (s.startswith('"') and s.endswith('"')

or s.startswith("'") and s.endswith("'"))

and s[1:-1] in self.valid):

msg += "; remove quotes surrounding your string"

raise ValueError(msg)

@lru_cache

def _listify_validator(scalar_validator, allow_stringlist=False, *,

n=None, doc=None):

def f(s):

if isinstance(s, str):

try:

val = [scalar_validator(v.strip()) for v in s.split(',')

if v.strip()]

except Exception:

if allow_stringlist:

# Sometimes, a list of colors might be a single string

# of single-letter colornames. So give that a shot.

val = [scalar_validator(v.strip()) for v in s if v.strip()]

else:

raise

# Allow any ordered sequence type -- generators, np.ndarray, pd.Series

# -- but not sets, whose iteration order is non-deterministic.

elif np.iterable(s) and not isinstance(s, (set, frozenset)):

# The condition on this list comprehension will preserve the

# behavior of filtering out any empty strings (behavior was

# from the original validate_stringlist()), while allowing

# any non-string/text scalar values such as numbers and arrays.

val = [scalar_validator(v) for v in s

if not isinstance(v, str) or v]

else:

raise ValueError(

f"Expected str or other non-set iterable, but got {s}")

if n is not None and len(val) != n:

raise ValueError(

f"Expected {n} values, but there are {len(val)} values in {s}")

return val

try:

f.__name__ = f"{scalar_validator.__name__}list"

except AttributeError: # class instance.

f.__name__ = f"{type(scalar_validator).__name__}List"

f.__qualname__ = f.__qualname__.rsplit(".", 1)[0] + "." + f.__name__

f.__doc__ = doc if doc is not None else scalar_validator.__doc__

return f

def validate_any(s):

return s

validate_anylist = _listify_validator(validate_any)

def _validate_date(s):

try:

np.datetime64(s)

return s

except ValueError:

raise ValueError(

f'{s!r} should be a string that can be parsed by numpy.datetime64')

def validate_bool(b):

"""Convert b to ``bool`` or raise."""

if isinstance(b, str):

b = b.lower()

if b in ('t', 'y', 'yes', 'on', 'true', '1', 1, True):

return True

elif b in ('f', 'n', 'no', 'off', 'false', '0', 0, False):

return False

else:

raise ValueError(f'Cannot convert {b!r} to bool')

def validate_axisbelow(s):

try:

return validate_bool(s)

except ValueError:

if isinstance(s, str):

if s == 'line':

return 'line'

raise ValueError(f'{s!r} cannot be interpreted as'

' True, False, or "line"')

def validate_dpi(s):

"""Confirm s is string 'figure' or convert s to float or raise."""

if s == 'figure':

return s

try:

return float(s)

except ValueError as e:

raise ValueError(f'{s!r} is not string "figure" and '

f'could not convert {s!r} to float') from e

def _make_type_validator(cls, *, allow_none=False):

"""

Return a validator that converts inputs to *cls* or raises (and possibly

allows ``None`` as well).

"""

def validator(s):

if (allow_none and

(s is None or cbook._str_lower_equal(s, "none"))):

return None

if cls is str and not isinstance(s, str):

raise ValueError(f'Could not convert {s!r} to str')

try:

return cls(s)

except (TypeError, ValueError) as e:

raise ValueError(

f'Could not convert {s!r} to {cls.__name__}') from e

validator.__name__ = f"validate_{cls.__name__}"

if allow_none:

validator.__name__ += "_or_None"

validator.__qualname__ = (

validator.__qualname__.rsplit(".", 1)[0] + "." + validator.__name__)

return validator

validate_string = _make_type_validator(str)

validate_string_or_None = _make_type_validator(str, allow_none=True)

validate_stringlist = _listify_validator(

validate_string, doc='return a list of strings')

validate_int = _make_type_validator(int)

validate_int_or_None = _make_type_validator(int, allow_none=True)

validate_float = _make_type_validator(float)

validate_float_or_None = _make_type_validator(float, allow_none=True)

validate_floatlist = _listify_validator(

validate_float, doc='return a list of floats')

def _validate_marker(s):

try:

return validate_int(s)

except ValueError as e:

try:

return validate_string(s)

except ValueError as e:

raise ValueError('Supported markers are [string, int]') from e

_validate_markerlist = _listify_validator(

_validate_marker, doc='return a list of markers')

def _validate_pathlike(s):

if isinstance(s, (str, os.PathLike)):

# Store value as str because savefig.directory needs to distinguish

# between "" (cwd) and "." (cwd, but gets updated by user selections).

return os.fsdecode(s)

else:

return validate_string(s)

def validate_fonttype(s):

"""

Confirm that this is a Postscript or PDF font type that we know how to

convert to.

"""

fonttypes = {'type3': 3,

'truetype': 42}

try:

fonttype = validate_int(s)

except ValueError:

try:

return fonttypes[s.lower()]

except KeyError as e:

raise ValueError('Supported Postscript/PDF font types are %s'

% list(fonttypes)) from e

else:

if fonttype not in fonttypes.values():

raise ValueError(

'Supported Postscript/PDF font types are %s' %

list(fonttypes.values()))

return fonttype

_auto_backend_sentinel = object()

def validate_backend(s):

if s is _auto_backend_sentinel or backend_registry.is_valid_backend(s):

return s

else:

msg = (f"'{s}' is not a valid value for backend; supported values are "

f"{backend_registry.list_all()}")

raise ValueError(msg)

def _validate_toolbar(s):

s = ValidateInStrings(

'toolbar', ['None', 'toolbar2', 'toolmanager'], ignorecase=True)(s)

if s == 'toolmanager':

_api.warn_external(

"Treat the new Tool classes introduced in v1.5 as experimental "

"for now; the API and rcParam may change in future versions.")

return s

def validate_color_or_inherit(s):

"""Return a valid color arg."""

if cbook._str_equal(s, 'inherit'):

return s

return validate_color(s)

def validate_color_or_auto(s):

if cbook._str_equal(s, 'auto'):

return s

return validate_color(s)

def validate_color_for_prop_cycle(s):

# N-th color cycle syntax can't go into the color cycle.

if isinstance(s, str) and re.match("^C[0-9]$", s):

raise ValueError(f"Cannot put cycle reference ({s!r}) in prop_cycler")

return validate_color(s)

def _validate_color_or_linecolor(s):

if cbook._str_equal(s, 'linecolor'):

return s

elif cbook._str_equal(s, 'mfc') or cbook._str_equal(s, 'markerfacecolor'):

return 'markerfacecolor'

elif cbook._str_equal(s, 'mec') or cbook._str_equal(s, 'markeredgecolor'):

return 'markeredgecolor'

elif s is None:

return None

elif isinstance(s, str) and len(s) == 6 or len(s) == 8:

stmp = '#' + s

if is_color_like(stmp):

return stmp

if s.lower() == 'none':

return None

elif is_color_like(s):

return s

raise ValueError(f'{s!r} does not look like a color arg')

def validate_color(s):

"""Return a valid color arg."""

if isinstance(s, str):

if s.lower() == 'none':

return 'none'

if len(s) == 6 or len(s) == 8:

stmp = '#' + s

if is_color_like(stmp):

return stmp

if is_color_like(s):

return s

# If it is still valid, it must be a tuple (as a string from matplotlibrc).

try:

color = ast.literal_eval(s)

except (SyntaxError, ValueError):

pass

else:

if is_color_like(color):

return color

raise ValueError(f'{s!r} does not look like a color arg')

validate_colorlist = _listify_validator(

validate_color, allow_stringlist=True, doc='return a list of colorspecs')

def _validate_cmap(s):

_api.check_isinstance((str, Colormap), cmap=s)

return s

def validate_aspect(s):

if s in ('auto', 'equal'):

return s

try:

return float(s)

except ValueError as e:

raise ValueError('not a valid aspect specification') from e

def validate_fontsize_None(s):

if s is None or s == 'None':

return None

else:

return validate_fontsize(s)

def validate_fontsize(s):

fontsizes = ['xx-small', 'x-small', 'small', 'medium', 'large',

'x-large', 'xx-large', 'smaller', 'larger']

if isinstance(s, str):

s = s.lower()

if s in fontsizes:

return s

try:

return float(s)

except ValueError as e:

raise ValueError("%s is not a valid font size. Valid font sizes "

"are %s." % (s, ", ".join(fontsizes))) from e

validate_fontsizelist = _listify_validator(validate_fontsize)

def validate_fontweight(s):

weights = [

'ultralight', 'light', 'normal', 'regular', 'book', 'medium', 'roman',

'semibold', 'demibold', 'demi', 'bold', 'heavy', 'extra bold', 'black']

# Note: Historically, weights have been case-sensitive in Matplotlib

if s in weights:

return s

try:

return int(s)

except (ValueError, TypeError) as e:

raise ValueError(f'{s} is not a valid font weight.') from e

def validate_fontstretch(s):

stretchvalues = [

'ultra-condensed', 'extra-condensed', 'condensed', 'semi-condensed',

'normal', 'semi-expanded', 'expanded', 'extra-expanded',

'ultra-expanded']

# Note: Historically, stretchvalues have been case-sensitive in Matplotlib

if s in stretchvalues:

return s

try:

return int(s)

except (ValueError, TypeError) as e:

raise ValueError(f'{s} is not a valid font stretch.') from e

def validate_font_properties(s):

parse_fontconfig_pattern(s)

return s

def _validate_mathtext_fallback(s):

_fallback_fonts = ['cm', 'stix', 'stixsans']

if isinstance(s, str):

s = s.lower()

if s is None or s == 'none':

return None

elif s.lower() in _fallback_fonts:

return s

else:

raise ValueError(

f"{s} is not a valid fallback font name. Valid fallback font "

f"names are {','.join(_fallback_fonts)}. Passing 'None' will turn "

"fallback off.")

def validate_whiskers(s):

try:

return _listify_validator(validate_float, n=2)(s)

except (TypeError, ValueError):

try:

return float(s)

except ValueError as e:

raise ValueError("Not a valid whisker value [float, "

"(float, float)]") from e

def validate_ps_distiller(s):

if isinstance(s, str):

s = s.lower()

if s in ('none', None, 'false', False):

return None

else:

return ValidateInStrings('ps.usedistiller', ['ghostscript', 'xpdf'])(s)

# A validator dedicated to the named line styles, based on the items in

# ls_mapper, and a list of possible strings read from Line2D.set_linestyle

_validate_named_linestyle = ValidateInStrings(

'linestyle',

[*ls_mapper.keys(), *ls_mapper.values(), 'None', 'none', ' ', ''],

ignorecase=True)

def _validate_linestyle(ls):

"""

A validator for all possible line styles, the named ones *and*

the on-off ink sequences.

"""

if isinstance(ls, str):

try: # Look first for a valid named line style, like '--' or 'solid'.

return _validate_named_linestyle(ls)

except ValueError:

pass

try:

ls = ast.literal_eval(ls) # Parsing matplotlibrc.

except (SyntaxError, ValueError):

pass # Will error with the ValueError at the end.

def _is_iterable_not_string_like(x):

# Explicitly exclude bytes/bytearrays so that they are not

# nonsensically interpreted as sequences of numbers (codepoints).

return np.iterable(x) and not isinstance(x, (str, bytes, bytearray))

if _is_iterable_not_string_like(ls):

if len(ls) == 2 and _is_iterable_not_string_like(ls[1]):

# (offset, (on, off, on, off, ...))

offset, onoff = ls

else:

# For backcompat: (on, off, on, off, ...); the offset is implicit.

offset = 0

onoff = ls

if (isinstance(offset, Real)

and len(onoff) % 2 == 0

and all(isinstance(elem, Real) for elem in onoff)):

return (offset, onoff)

raise ValueError(f"linestyle {ls!r} is not a valid on-off ink sequence.")

validate_fillstyle = ValidateInStrings(

'markers.fillstyle', ['full', 'left', 'right', 'bottom', 'top', 'none'])

validate_fillstylelist = _listify_validator(validate_fillstyle)

def validate_markevery(s):

"""

Validate the markevery property of a Line2D object.

Parameters

----------

s : None, int, (int, int), slice, float, (float, float), or list[int]

Returns

-------

None, int, (int, int), slice, float, (float, float), or list[int]

"""

# Validate s against type slice float int and None

if isinstance(s, (slice, float, int, type(None))):

return s

# Validate s against type tuple

if isinstance(s, tuple):

if (len(s) == 2

and (all(isinstance(e, int) for e in s)

or all(isinstance(e, float) for e in s))):

return s

else:

raise TypeError(

"'markevery' tuple must be pair of ints or of floats")

# Validate s against type list

if isinstance(s, list):

if all(isinstance(e, int) for e in s):

return s

else:

raise TypeError(

"'markevery' list must have all elements of type int")

raise TypeError("'markevery' is of an invalid type")

validate_markeverylist = _listify_validator(validate_markevery)

def validate_bbox(s):

if isinstance(s, str):

s = s.lower()

if s == 'tight':

return s

if s == 'standard':

return None

raise ValueError("bbox should be 'tight' or 'standard'")

elif s is not None:

# Backwards compatibility. None is equivalent to 'standard'.

raise ValueError("bbox should be 'tight' or 'standard'")

return s

def validate_sketch(s):

if isinstance(s, str):

s = s.lower().strip()

if s.startswith("(") and s.endswith(")"):

s = s[1:-1]

if s == 'none' or s is None:

return None

try:

return tuple(_listify_validator(validate_float, n=3)(s))

except ValueError as exc:

raise ValueError("Expected a (scale, length, randomness) tuple") from exc

def _validate_greaterthan_minushalf(s):

s = validate_float(s)

if s > -0.5:

return s

else:

raise RuntimeError(f'Value must be >-0.5; got {s}')

def _validate_greaterequal0_lessequal1(s):

s = validate_float(s)

if 0 <= s <= 1:

return s

else:

raise RuntimeError(f'Value must be >=0 and <=1; got {s}')

def _validate_int_greaterequal0(s):

s = validate_int(s)

if s >= 0:

return s

else:

raise RuntimeError(f'Value must be >=0; got {s}')

def validate_hatch(s):

r"""

Validate a hatch pattern.

A hatch pattern string can have any sequence of the following

characters: ``\ / | - + * . x o O``.

"""

if not isinstance(s, str):

raise ValueError("Hatch pattern must be a string")

_api.check_isinstance(str, hatch_pattern=s)

unknown = set(s) - {'\\', '/', '|', '-', '+', '*', '.', 'x', 'o', 'O'}

if unknown:

raise ValueError("Unknown hatch symbol(s): %s" % list(unknown))

return s

validate_hatchlist = _listify_validator(validate_hatch)

validate_dashlist = _listify_validator(validate_floatlist)

def _validate_minor_tick_ndivs(n):

"""

Validate ndiv parameter related to the minor ticks.

It controls the number of minor ticks to be placed between

two major ticks.

"""

if cbook._str_lower_equal(n, 'auto'):

return n

try:

n = _validate_int_greaterequal0(n)

return n

except (RuntimeError, ValueError):

pass

raise ValueError("'tick.minor.ndivs' must be 'auto' or non-negative int")

_prop_validators = {

'color': _listify_validator(validate_color_for_prop_cycle,

allow_stringlist=True),

'linewidth': validate_floatlist,

'linestyle': _listify_validator(_validate_linestyle),

'facecolor': validate_colorlist,

'edgecolor': validate_colorlist,

'joinstyle': _listify_validator(JoinStyle),

'capstyle': _listify_validator(CapStyle),

'fillstyle': validate_fillstylelist,

'markerfacecolor': validate_colorlist,

'markersize': validate_floatlist,

'markeredgewidth': validate_floatlist,

'markeredgecolor': validate_colorlist,

'markevery': validate_markeverylist,

'alpha': validate_floatlist,

'marker': _validate_markerlist,

'hatch': validate_hatchlist,

'dashes': validate_dashlist,

}

_prop_aliases = {

'c': 'color',

'lw': 'linewidth',

'ls': 'linestyle',

'fc': 'facecolor',

'ec': 'edgecolor',

'mfc': 'markerfacecolor',

'mec': 'markeredgecolor',

'mew': 'markeredgewidth',

'ms': 'markersize',

}

def cycler(*args, **kwargs):

"""

Create a `~cycler.Cycler` object much like :func:`cycler.cycler`,

but includes input validation.

Call signatures::

cycler(cycler)

cycler(label=values, label2=values2, ...)

cycler(label, values)

Form 1 copies a given `~cycler.Cycler` object.

Form 2 creates a `~cycler.Cycler` which cycles over one or more

properties simultaneously. If multiple properties are given, their

value lists must have the same length.

Form 3 creates a `~cycler.Cycler` for a single property. This form

exists for compatibility with the original cycler. Its use is

discouraged in favor of the kwarg form, i.e. ``cycler(label=values)``.

Parameters

----------

cycler : Cycler

Copy constructor for Cycler.

label : str

The property key. Must be a valid `.Artist` property.

For example, 'color' or 'linestyle'. Aliases are allowed,

such as 'c' for 'color' and 'lw' for 'linewidth'.

values : iterable

Finite-length iterable of the property values. These values

are validated and will raise a ValueError if invalid.

Returns

-------

Cycler

A new :class:`~cycler.Cycler` for the given properties.

Examples

--------

Creating a cycler for a single property:

>>> c = cycler(color=['red', 'green', 'blue'])

Creating a cycler for simultaneously cycling over multiple properties

(e.g. red circle, green plus, blue cross):

>>> c = cycler(color=['red', 'green', 'blue'],

... marker=['o', '+', 'x'])

"""

if args and kwargs:

raise TypeError("cycler() can only accept positional OR keyword "

"arguments -- not both.")

elif not args and not kwargs:

raise TypeError("cycler() must have positional OR keyword arguments")

if len(args) == 1:

if not isinstance(args[0], Cycler):

raise TypeError("If only one positional argument given, it must "

"be a Cycler instance.")

return validate_cycler(args[0])

elif len(args) == 2:

pairs = [(args[0], args[1])]

elif len(args) > 2:

raise _api.nargs_error('cycler', '0-2', len(args))

else:

pairs = kwargs.items()

validated = []

for prop, vals in pairs:

norm_prop = _prop_aliases.get(prop, prop)

validator = _prop_validators.get(norm_prop, None)

if validator is None:

raise TypeError("Unknown artist property: %s" % prop)

vals = validator(vals)

# We will normalize the property names as well to reduce

# the amount of alias handling code elsewhere.

validated.append((norm_prop, vals))

return reduce(operator.add, (ccycler(k, v) for k, v in validated))

class _DunderChecker(ast.NodeVisitor):

def visit_Attribute(self, node):

if node.attr.startswith("__") and node.attr.endswith("__"):

raise ValueError("cycler strings with dunders are forbidden")

self.generic_visit(node)

# A validator dedicated to the named legend loc

_validate_named_legend_loc = ValidateInStrings(

'legend.loc',

[

"best",

"upper right", "upper left", "lower left", "lower right", "right",

"center left", "center right", "lower center", "upper center",

"center"],

ignorecase=True)

def _validate_legend_loc(loc):

"""

Confirm that loc is a type which rc.Params["legend.loc"] supports.

.. versionadded:: 3.8

Parameters

----------

loc : str | int | (float, float) | str((float, float))

The location of the legend.

Returns

-------

loc : str | int | (float, float) or raise ValueError exception

The location of the legend.

"""

if isinstance(loc, str):

try:

return _validate_named_legend_loc(loc)

except ValueError:

pass

try:

loc = ast.literal_eval(loc)

except (SyntaxError, ValueError):

pass

if isinstance(loc, int):

if 0 <= loc <= 10:

return loc

if isinstance(loc, tuple):

if len(loc) == 2 and all(isinstance(e, Real) for e in loc):

return loc

raise ValueError(f"{loc} is not a valid legend location.")

def validate_cycler(s):

"""Return a Cycler object from a string repr or the object itself."""

if isinstance(s, str):

# TODO: We might want to rethink this...

# While I think I have it quite locked down, it is execution of

# arbitrary code without sanitation.

# Combine this with the possibility that rcparams might come from the

# internet (future plans), this could be downright dangerous.

# I locked it down by only having the 'cycler()' function available.

# UPDATE: Partly plugging a security hole.

# I really should have read this:

# https://nedbatchelder.com/blog/201206/eval_really_is_dangerous.html

# We should replace this eval with a combo of PyParsing and

# ast.literal_eval()

try:

_DunderChecker().visit(ast.parse(s))

s = eval(s, {'cycler': cycler, '__builtins__': {}})

except BaseException as e:

raise ValueError(f"{s!r} is not a valid cycler construction: {e}"

) from e

# Should make sure what comes from the above eval()

# is a Cycler object.

if isinstance(s, Cycler):

cycler_inst = s

else:

raise ValueError(f"Object is not a string or Cycler instance: {s!r}")

unknowns = cycler_inst.keys - (set(_prop_validators) | set(_prop_aliases))

if unknowns:

raise ValueError("Unknown artist properties: %s" % unknowns)

# Not a full validation, but it'll at least normalize property names

# A fuller validation would require v0.10 of cycler.

checker = set()

for prop in cycler_inst.keys:

norm_prop = _prop_aliases.get(prop, prop)

if norm_prop != prop and norm_prop in cycler_inst.keys:

raise ValueError(f"Cannot specify both {norm_prop!r} and alias "

f"{prop!r} in the same prop_cycle")

if norm_prop in checker:

raise ValueError(f"Another property was already aliased to "

f"{norm_prop!r}. Collision normalizing {prop!r}.")

checker.update([norm_prop])

# This is just an extra-careful check, just in case there is some

# edge-case I haven't thought of.

assert len(checker) == len(cycler_inst.keys)

# Now, it should be safe to mutate this cycler

for prop in cycler_inst.keys:

norm_prop = _prop_aliases.get(prop, prop)

cycler_inst.change_key(prop, norm_prop)

for key, vals in cycler_inst.by_key().items():

_prop_validators[key](vals)

return cycler_inst

def validate_hist_bins(s):

valid_strs = ["auto", "sturges", "fd", "doane", "scott", "rice", "sqrt"]

if isinstance(s, str) and s in valid_strs:

return s

try:

return int(s)

except (TypeError, ValueError):

pass

try:

return validate_floatlist(s)

except ValueError:

pass

raise ValueError(f"'hist.bins' must be one of {valid_strs}, an int or"

" a sequence of floats")

class _ignorecase(list):

"""A marker class indicating that a list-of-str is case-insensitive."""

def _convert_validator_spec(key, conv):

if isinstance(conv, list):

ignorecase = isinstance(conv, _ignorecase)

return ValidateInStrings(key, conv, ignorecase=ignorecase)

else:

return conv

# Mapping of rcParams to validators.

# Converters given as lists or _ignorecase are converted to ValidateInStrings

# immediately below.

# The rcParams defaults are defined in lib/matplotlib/mpl-data/matplotlibrc, which

# gets copied to matplotlib/mpl-data/matplotlibrc by the setup script.

_validators = {

"backend": validate_backend,

"backend_fallback": validate_bool,

"figure.hooks": validate_stringlist,

"toolbar": _validate_toolbar,

"interactive": validate_bool,

"timezone": validate_string,

"webagg.port": validate_int,

"webagg.address": validate_string,

"webagg.open_in_browser": validate_bool,

"webagg.port_retries": validate_int,

# line props

"lines.linewidth": validate_float, # line width in points

"lines.linestyle": _validate_linestyle, # solid line

"lines.color": validate_color, # first color in color cycle

"lines.marker": _validate_marker, # marker name

"lines.markerfacecolor": validate_color_or_auto, # default color

"lines.markeredgecolor": validate_color_or_auto, # default color

"lines.markeredgewidth": validate_float,

"lines.markersize": validate_float, # markersize, in points

"lines.antialiased": validate_bool, # antialiased (no jaggies)

"lines.dash_joinstyle": JoinStyle,

"lines.solid_joinstyle": JoinStyle,

"lines.dash_capstyle": CapStyle,

"lines.solid_capstyle": CapStyle,

"lines.dashed_pattern": validate_floatlist,

"lines.dashdot_pattern": validate_floatlist,

"lines.dotted_pattern": validate_floatlist,

"lines.scale_dashes": validate_bool,

# marker props

"markers.fillstyle": validate_fillstyle,

## pcolor(mesh) props:

"pcolor.shading": ["auto", "flat", "nearest", "gouraud"],

"pcolormesh.snap": validate_bool,

## patch props

"patch.linewidth": validate_float, # line width in points

"patch.edgecolor": validate_color,

"patch.force_edgecolor": validate_bool,

"patch.facecolor": validate_color, # first color in cycle

"patch.antialiased": validate_bool, # antialiased (no jaggies)

## hatch props

"hatch.color": validate_color,

"hatch.linewidth": validate_float,

## Histogram properties

"hist.bins": validate_hist_bins,

## Boxplot properties

"boxplot.notch": validate_bool,

"boxplot.vertical": validate_bool,

"boxplot.whiskers": validate_whiskers,

"boxplot.bootstrap": validate_int_or_None,

"boxplot.patchartist": validate_bool,

"boxplot.showmeans": validate_bool,

"boxplot.showcaps": validate_bool,

"boxplot.showbox": validate_bool,

"boxplot.showfliers": validate_bool,

"boxplot.meanline": validate_bool,

"boxplot.flierprops.color": validate_color,

"boxplot.flierprops.marker": _validate_marker,

"boxplot.flierprops.markerfacecolor": validate_color_or_auto,

"boxplot.flierprops.markeredgecolor": validate_color,

"boxplot.flierprops.markeredgewidth": validate_float,

"boxplot.flierprops.markersize": validate_float,

"boxplot.flierprops.linestyle": _validate_linestyle,

"boxplot.flierprops.linewidth": validate_float,

"boxplot.boxprops.color": validate_color,

"boxplot.boxprops.linewidth": validate_float,

"boxplot.boxprops.linestyle": _validate_linestyle,

"boxplot.whiskerprops.color": validate_color,

"boxplot.whiskerprops.linewidth": validate_float,

"boxplot.whiskerprops.linestyle": _validate_linestyle,

"boxplot.capprops.color": validate_color,

"boxplot.capprops.linewidth": validate_float,

"boxplot.capprops.linestyle": _validate_linestyle,

"boxplot.medianprops.color": validate_color,

"boxplot.medianprops.linewidth": validate_float,

"boxplot.medianprops.linestyle": _validate_linestyle,

"boxplot.meanprops.color": validate_color,

"boxplot.meanprops.marker": _validate_marker,

"boxplot.meanprops.markerfacecolor": validate_color,

"boxplot.meanprops.markeredgecolor": validate_color,

"boxplot.meanprops.markersize": validate_float,