matplotlib/lib/matplotlib/colors.py at v3.11.2 · matplotlib/matplotlib · GitHub

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"""

A module for converting numbers or color arguments to *RGB* or *RGBA*.

*RGB* and *RGBA* are sequences of, respectively, 3 or 4 floats in the

range 0-1.

This module includes functions and classes for color specification conversions,

and for mapping numbers to colors in a 1-D array of colors called a colormap.

Mapping data onto colors using a colormap typically involves two steps: a data

array is first mapped onto the range 0-1 using a subclass of `Normalize`,

then this number is mapped to a color using a subclass of `Colormap`. Two

subclasses of `Colormap` provided here: `LinearSegmentedColormap`, which uses

piecewise-linear interpolation to define colormaps, and `ListedColormap`, which

makes a colormap from a list of colors.

.. seealso::

:ref:`colormap-manipulation` for examples of how to

make colormaps and

:ref:`colormaps` for a list of built-in colormaps.

:ref:`colormapnorms` for more details about data

normalization

More colormaps are available at palettable_.

The module also provides functions for checking whether an object can be

interpreted as a color (`is_color_like`), for converting such an object

to an RGBA tuple (`to_rgba`) or to an HTML-like hex string in the

"#rrggbb" format (`to_hex`), and a sequence of colors to an (n, 4)

RGBA array (`to_rgba_array`). Caching is used for efficiency.

Colors that Matplotlib recognizes are listed at

:ref:`colors_def`.

.. _palettable: https://jiffyclub.github.io/palettable/

.. _xkcd color survey: https://xkcd.com/color/rgb/

"""

import base64

from collections.abc import Sequence, Mapping

from abc import ABC, abstractmethod

import functools

import importlib

import inspect

import io

import itertools

from numbers import Real

import re

from PIL import Image

from PIL.PngImagePlugin import PngInfo

import matplotlib as mpl

import numpy as np

from matplotlib import _api, _cm, cbook, scale

from ._color_data import BASE_COLORS, TABLEAU_COLORS, CSS4_COLORS, XKCD_COLORS

class _ColorMapping(dict):

def __init__(self, mapping):

super().__init__(mapping)

self.cache = {}

def __setitem__(self, key, value):

super().__setitem__(key, value)

self.cache.clear()

def __delitem__(self, key):

super().__delitem__(key)

self.cache.clear()

_colors_full_map = {}

# Set by reverse priority order.

_colors_full_map.update(XKCD_COLORS)

_colors_full_map.update({k.replace('grey', 'gray'): v

for k, v in XKCD_COLORS.items()

if 'grey' in k})

_colors_full_map.update(CSS4_COLORS)

_colors_full_map.update(TABLEAU_COLORS)

_colors_full_map.update({k.replace('gray', 'grey'): v

for k, v in TABLEAU_COLORS.items()

if 'gray' in k})

_colors_full_map.update(BASE_COLORS)

_colors_full_map = _ColorMapping(_colors_full_map)

_REPR_PNG_SIZE = (512, 64)

_BIVAR_REPR_PNG_SIZE = 256

def get_named_colors_mapping():

"""Return the global mapping of names to named colors."""

return _colors_full_map

class ColorSequenceRegistry(Mapping):

r"""

Container for sequences of colors that are known to Matplotlib by name.

The universal registry instance is `matplotlib.color_sequences`. There

should be no need for users to instantiate `.ColorSequenceRegistry`

themselves.

Read access uses a dict-like interface mapping names to lists of colors::

import matplotlib as mpl

colors = mpl.color_sequences['tab10']

For a list of built in color sequences, see :doc:`/gallery/color/color_sequences`.

The returned lists are copies, so that their modification does not change

the global definition of the color sequence.

Additional color sequences can be added via

`.ColorSequenceRegistry.register`::

mpl.color_sequences.register('rgb', ['r', 'g', 'b'])

"""

_BUILTIN_COLOR_SEQUENCES = {

'tab10': _cm._tab10_data,

'tab20': _cm._tab20_data,

'tab20b': _cm._tab20b_data,

'tab20c': _cm._tab20c_data,

'Pastel1': _cm._Pastel1_data,

'Pastel2': _cm._Pastel2_data,

'Paired': _cm._Paired_data,

'Accent': _cm._Accent_data,

'okabe_ito': _cm._okabe_ito_data,

'Dark2': _cm._Dark2_data,

'Set1': _cm._Set1_data,

'Set2': _cm._Set2_data,

'Set3': _cm._Set3_data,

'petroff6': _cm._petroff6_data,

'petroff8': _cm._petroff8_data,

'petroff10': _cm._petroff10_data,

}

def __init__(self):

self._color_sequences = {**self._BUILTIN_COLOR_SEQUENCES}

def __getitem__(self, item):

return list(_api.getitem_checked(self._color_sequences, _error_cls=KeyError,

sequence_name=item))

def __iter__(self):

return iter(self._color_sequences)

def __len__(self):

return len(self._color_sequences)

def __str__(self):

return ('ColorSequenceRegistry; available colormaps:\n' +

', '.join(f"'{name}'" for name in self))

def register(self, name, color_list):

"""

The color sequence registry stores a copy of the given *color_list*, so

that future changes to the original list do not affect the registered

color sequence. Think of this as the registry taking a snapshot

of *color_list* at registration.

Parameters

----------

name : str

The name for the color sequence.

color_list : list of :mpltype:`color`

An iterable returning valid Matplotlib colors when iterating over.

Note however that the returned color sequence will always be a

list regardless of the input type.

"""

if name in self._BUILTIN_COLOR_SEQUENCES:

raise ValueError(f"{name!r} is a reserved name for a builtin "

"color sequence")

color_list = list(color_list) # force copy and coerce type to list

for color in color_list:

try:

to_rgba(color)

except ValueError:

raise ValueError(

f"{color!r} is not a valid color specification")

self._color_sequences[name] = color_list

def unregister(self, name):

"""

Remove a sequence from the registry.

You cannot remove built-in color sequences.

If the name is not registered, returns with no error.

"""

if name in self._BUILTIN_COLOR_SEQUENCES:

raise ValueError(

f"Cannot unregister builtin color sequence {name!r}")

self._color_sequences.pop(name, None)

_color_sequences = ColorSequenceRegistry()

def _sanitize_extrema(ex):

if ex is None:

return ex

try:

ret = ex.item()

except AttributeError:

ret = float(ex)

return ret

_nth_color_re = re.compile(r"\AC[0-9]+\Z")

def _is_nth_color(c):

"""Return whether *c* can be interpreted as an item in the color cycle."""

return isinstance(c, str) and _nth_color_re.match(c)

def is_color_like(c):

"""Return whether *c* as a valid Matplotlib :mpltype:`color` specifier."""

# Special-case nth color syntax because it cannot be parsed during setup.

if _is_nth_color(c):

return True

try:

to_rgba(c)

except (TypeError, ValueError):

return False

else:

return True

def _has_alpha_channel(c):

"""

Return whether *c* is a color with an alpha channel.

If *c* is not a valid color specifier, then the result is undefined.

"""

# The following logic uses the assumption that c is a valid color spec.

# For speed and simplicity, we intentionally don't care about other inputs.

# Anything can happen with them.

# if c is a hex, it has an alpha channel when it has 4 (or 8) digits after '#'

if isinstance(c, str):

if c[0] == '#' and (len(c) == 5 or len(c) == 9):

# example: '#fff8' or '#0f0f0f80'

return True

else:

# if c isn't a string, it can be an RGB(A) or a color-alpha tuple

# if it has length 4, it has an alpha channel

if len(c) == 4:

# example: [0.5, 0.5, 0.5, 0.5]

return True

# if it has length 2, it's a color/alpha tuple

# if the second element isn't None or the first element has length = 4

if len(c) == 2 and (c[1] is not None or _has_alpha_channel(c[0])):

# example: ([0.5, 0.5, 0.5, 0.5], None) or ('r', 0.5)

return True

# otherwise it doesn't have an alpha channel

return False

def _check_color_like(**kwargs):

"""

For each *key, value* pair in *kwargs*, check that *value* is color-like.

"""

for k, v in kwargs.items():

if not is_color_like(v):

raise ValueError(

f"{v!r} is not a valid value for {k}: supported inputs are "

f"(r, g, b) and (r, g, b, a) 0-1 float tuples; "

f"'#rrggbb', '#rrggbbaa', '#rgb', '#rgba' strings; "

f"named color strings; "

f"string reprs of 0-1 floats for grayscale values; "

f"'C0', 'C1', ... strings for colors of the color cycle; "

f"and pairs combining one of the above with an alpha value")

def same_color(c1, c2):

"""

Return whether the colors *c1* and *c2* are the same.

Parameters

----------

c1, c2 : :mpltype:`color` or list of :mpltype:`color` or RGB(A) array

If passing multiple colors, *c1* and *c2* must be of the same length. RGB(A)

arrays must be of shape (ncolors, 3) or (ncolors, 4).

Returns

-------

bool

"""

c1 = to_rgba_array(c1)

c2 = to_rgba_array(c2)

n1 = max(c1.shape[0], 1) # 'none' results in shape (0, 4), but is 1-elem

n2 = max(c2.shape[0], 1) # 'none' results in shape (0, 4), but is 1-elem

if n1 != n2:

raise ValueError('Different number of elements passed.')

# The following shape test is needed to correctly handle comparisons with

# 'none', which results in a shape (0, 4) array and thus cannot be tested

# via value comparison.

return c1.shape == c2.shape and (c1 == c2).all()

def to_rgba(c, alpha=None):

"""

Convert *c* to an RGBA color.

Parameters

----------

c : :mpltype:`color` or ``np.ma.masked``

alpha : float, optional

If *alpha* is given, force the alpha value of the returned RGBA tuple

to *alpha*.

If None, the alpha value from *c* is used. If *c* does not have an

alpha channel, then alpha defaults to 1.

*alpha* is ignored for the color value ``"none"`` (case-insensitive),

which always maps to ``(0, 0, 0, 0)``.

Returns

-------

tuple

Tuple of floats ``(r, g, b, a)``, where each channel (red, green, blue,

alpha) can assume values between 0 and 1.

"""

if isinstance(c, tuple) and len(c) == 2:

if alpha is None:

c, alpha = c

else:

c = c[0]

# Special-case nth color syntax because it should not be cached.

if _is_nth_color(c):

prop_cycler = mpl.rcParams['axes.prop_cycle']

colors = prop_cycler.by_key().get('color', ['k'])

c = colors[int(c[1:]) % len(colors)]

try:

rgba = _colors_full_map.cache[c, alpha]

except (KeyError, TypeError): # Not in cache, or unhashable.

rgba = None

if rgba is None: # Suppress exception chaining of cache lookup failure.

rgba = _to_rgba_no_colorcycle(c, alpha)

try:

_colors_full_map.cache[c, alpha] = rgba

except TypeError:

pass

return rgba

def _to_rgba_no_colorcycle(c, alpha=None):

"""

Convert *c* to an RGBA color, with no support for color-cycle syntax.

If *alpha* is given, force the alpha value of the returned RGBA tuple

to *alpha*. Otherwise, the alpha value from *c* is used, if it has alpha

information, or defaults to 1.

*alpha* is ignored for the color value ``"none"`` (case-insensitive),

which always maps to ``(0, 0, 0, 0)``.

"""

if alpha is not None and not 0 <= alpha <= 1:

raise ValueError("'alpha' must be between 0 and 1, inclusive")

orig_c = c

if c is np.ma.masked:

return (0., 0., 0., 0.)

if isinstance(c, str):

if c.lower() == "none":

return (0., 0., 0., 0.)

# Named color.

try:

# This may turn c into a non-string, so we check again below.

c = _colors_full_map[c]

except KeyError:

if len(c) != 1:

try:

c = _colors_full_map[c.lower()]

except KeyError:

pass

if isinstance(c, str):

if re.fullmatch("#[a-fA-F0-9]+", c):

if len(c) == 7: # #rrggbb hex format.

return (*[n / 0xff for n in bytes.fromhex(c[1:])],

alpha if alpha is not None else 1.)

elif len(c) == 4: # #rgb hex format, shorthand for #rrggbb.

return (*[int(n, 16) / 0xf for n in c[1:]],

alpha if alpha is not None else 1.)

elif len(c) == 9: # #rrggbbaa hex format.

color = [n / 0xff for n in bytes.fromhex(c[1:])]

if alpha is not None:

color[-1] = alpha

return tuple(color)

elif len(c) == 5: # #rgba hex format, shorthand for #rrggbbaa.

color = [int(n, 16) / 0xf for n in c[1:]]

if alpha is not None:

color[-1] = alpha

return tuple(color)

else:

raise ValueError(f"Invalid hex color specifier: {orig_c!r}")

# string gray.

try:

c = float(c)

except ValueError:

pass

else:

if not (0 <= c <= 1):

raise ValueError(

f"Invalid string grayscale value {orig_c!r}. "

f"Value must be within 0-1 range")

return c, c, c, alpha if alpha is not None else 1.

raise ValueError(f"Invalid RGBA argument: {orig_c!r}")

# turn 2-D array into 1-D array

if isinstance(c, np.ndarray):

if c.ndim == 2 and c.shape[0] == 1:

c = c.reshape(-1)

# tuple color.

if not np.iterable(c):

raise ValueError(f"Invalid RGBA argument: {orig_c!r}")

if len(c) not in [3, 4]:

raise ValueError("RGBA sequence should have length 3 or 4")

if not all(isinstance(x, Real) for x in c):

# Checks that don't work: `map(float, ...)`, `np.array(..., float)` and

# `np.array(...).astype(float)` would all convert "0.5" to 0.5.

raise ValueError(f"Invalid RGBA argument: {orig_c!r}")

# Return a tuple to prevent the cached value from being modified.

c = tuple(map(float, c))

if len(c) == 3 and alpha is None:

alpha = 1

if alpha is not None:

c = c[:3] + (alpha,)

if any(elem < 0 or elem > 1 for elem in c):

raise ValueError("RGBA values should be within 0-1 range")

return c

def to_rgba_array(c, alpha=None):

"""

Convert *c* to a (n, 4) array of RGBA colors.

Parameters

----------

c : :mpltype:`color` or list of :mpltype:`color` or RGB(A) array

If *c* is a masked array, an `~numpy.ndarray` is returned with a

(0, 0, 0, 0) row for each masked value or row in *c*.

alpha : float or sequence of floats, optional

If *alpha* is given, force the alpha value of the returned RGBA tuple

to *alpha*.

If None, the alpha value from *c* is used. If *c* does not have an

alpha channel, then alpha defaults to 1.

*alpha* is ignored for the color value ``"none"`` (case-insensitive),

which always maps to ``(0, 0, 0, 0)``.

If *alpha* is a sequence and *c* is a single color, *c* will be

repeated to match the length of *alpha*.

Returns

-------

array

(n, 4) array of RGBA colors, where each channel (red, green, blue,

alpha) can assume values between 0 and 1.

"""

if isinstance(c, tuple) and len(c) == 2 and isinstance(c[1], Real):

if alpha is None:

c, alpha = c

else:

c = c[0]

# Special-case inputs that are already arrays, for performance. (If the

# array has the wrong kind or shape, raise the error during one-at-a-time

# conversion.)

if np.iterable(alpha):

alpha = np.asarray(alpha).ravel()

if (isinstance(c, np.ndarray) and c.dtype.kind in "if"

and c.ndim == 2 and c.shape[1] in [3, 4]):

mask = c.mask.any(axis=1) if np.ma.is_masked(c) else None

c = np.ma.getdata(c)

if np.iterable(alpha):

if c.shape[0] == 1 and alpha.shape[0] > 1:

c = np.tile(c, (alpha.shape[0], 1))

elif c.shape[0] != alpha.shape[0]:

raise ValueError("The number of colors must match the number"

" of alpha values if there are more than one"

" of each.")

if c.shape[1] == 3:

result = np.column_stack([c, np.zeros(len(c))])

result[:, -1] = alpha if alpha is not None else 1.

elif c.shape[1] == 4:

result = c.copy()

if alpha is not None:

result[:, -1] = alpha

if mask is not None:

result[mask] = 0

if np.any((result < 0) | (result > 1)):

raise ValueError("RGBA values should be within 0-1 range")

return result

# Handle single values.

# Note that this occurs *after* handling inputs that are already arrays, as

# `to_rgba(c, alpha)` (below) is expensive for such inputs, due to the need

# to format the array in the ValueError message(!).

if cbook._str_lower_equal(c, "none"):

return np.zeros((0, 4), float)

try:

if np.iterable(alpha):

return np.array([to_rgba(c, a) for a in alpha], float)

else:

return np.array([to_rgba(c, alpha)], float)

except TypeError:

pass

except ValueError as e:

if e.args == ("'alpha' must be between 0 and 1, inclusive", ):

# ValueError is from _to_rgba_no_colorcycle().

raise e

if isinstance(c, str):

raise ValueError(f"{c!r} is not a valid color value.")

if len(c) == 0:

return np.zeros((0, 4), float)

# Quick path if the whole sequence can be directly converted to a numpy

# array in one shot.

if isinstance(c, Sequence):

lens = {len(cc) if isinstance(cc, (list, tuple)) else -1 for cc in c}

if lens == {3}:

rgba = np.column_stack([c, np.ones(len(c))])

elif lens == {4}:

rgba = np.array(c)

else:

rgba = np.array([to_rgba(cc) for cc in c])

else:

rgba = np.array([to_rgba(cc) for cc in c])

if alpha is not None:

rgba[:, 3] = alpha

if isinstance(c, Sequence):

# ensure that an explicit alpha does not overwrite full transparency

# for "none"

none_mask = [cbook._str_equal(cc, "none") for cc in c]

rgba[:, 3][none_mask] = 0

return rgba

def to_rgb(c):

"""

Convert the :mpltype:`color` *c* to an RGB color tuple.

If c has an alpha channel value specified, that is silently dropped.

"""

return to_rgba(c)[:3]

def to_hex(c, keep_alpha=False):

"""

Convert *c* to a hex color.

Parameters

----------

c : :mpltype:`color` or `numpy.ma.masked`

keep_alpha : bool, default: False

If False, use the ``#rrggbb`` format, otherwise use ``#rrggbbaa``.

Returns

-------

str

``#rrggbb`` or ``#rrggbbaa`` hex color string

"""

c = to_rgba(c)

if not keep_alpha:

c = c[:3]

return "#" + "".join(format(round(val * 255), "02x") for val in c)

### Backwards-compatible color-conversion API

cnames = CSS4_COLORS #: :meta private:

hexColorPattern = re.compile(r"\A#[a-fA-F0-9]{6}\Z") #: :meta private:

rgb2hex = to_hex #: :meta private:

hex2color = to_rgb #: :meta private:

class ColorConverter:

"""

A class only kept for backwards compatibility.

Its functionality is entirely provided by module-level functions.

:meta private:

"""

colors = _colors_full_map

cache = _colors_full_map.cache

to_rgb = staticmethod(to_rgb)

to_rgba = staticmethod(to_rgba)

to_rgba_array = staticmethod(to_rgba_array)

colorConverter = ColorConverter()

### End of backwards-compatible color-conversion API

def _create_lookup_table(N, data, gamma=1.0):

r"""

Create an *N* -element 1D lookup table.

This assumes a mapping :math:`f : [0, 1] \rightarrow [0, 1]`. The returned

data is an array of N values :math:`y = f(x)` where x is sampled from

[0, 1].

By default (*gamma* = 1) x is equidistantly sampled from [0, 1]. The

*gamma* correction factor :math:`\gamma` distorts this equidistant

sampling by :math:`x \rightarrow x^\gamma`.

Parameters

----------

N : int

The number of elements of the created lookup table; at least 1.

data : (M, 3) array-like or callable

Defines the mapping :math:`f`.

If a (M, 3) array-like, the rows define values (x, y0, y1). The x

values must start with x=0, end with x=1, and all x values be in

increasing order.

A value between :math:`x_i` and :math:`x_{i+1}` is mapped to the range

:math:`y^1_{i-1} \ldots y^0_i` by linear interpolation.

For the simple case of a y-continuous mapping, y0 and y1 are identical.

The two values of y are to allow for discontinuous mapping functions.

E.g. a sawtooth with a period of 0.2 and an amplitude of 1 would be::

[(0, 1, 0), (0.2, 1, 0), (0.4, 1, 0), ..., [(1, 1, 0)]

In the special case of ``N == 1``, by convention the returned value

is y0 for x == 1.

If *data* is a callable, it must accept and return numpy arrays::

data(x : ndarray) -> ndarray

and map values between 0 - 1 to 0 - 1.

gamma : float

Gamma correction factor for input distribution x of the mapping.

See also https://en.wikipedia.org/wiki/Gamma_correction.

Returns

-------

array

The lookup table where ``lut[x * (N-1)]`` gives the closest value

for values of x between 0 and 1.

Notes

-----

This function is internally used for `.LinearSegmentedColormap`.

"""

if callable(data):

xind = np.linspace(0, 1, N) ** gamma

lut = np.clip(np.array(data(xind), dtype=float), 0, 1)

return lut

try:

adata = np.array(data)

except Exception as err:

raise TypeError("data must be convertible to an array") from err

_api.check_shape((None, 3), data=adata)

x = adata[:, 0]

y0 = adata[:, 1]

y1 = adata[:, 2]

if x[0] != 0. or x[-1] != 1.0:

raise ValueError(

"data mapping points must start with x=0 and end with x=1")

if (np.diff(x) < 0).any():

raise ValueError("data mapping points must have x in increasing order")

# begin generation of lookup table

if N == 1:

# convention: use the y = f(x=1) value for a 1-element lookup table

lut = np.array(y0[-1])

else:

x = x * (N - 1)

xind = (N - 1) * np.linspace(0, 1, N) ** gamma

ind = np.searchsorted(x, xind)[1:-1]

distance = (xind[1:-1] - x[ind - 1]) / (x[ind] - x[ind - 1])

lut = np.concatenate([

[y1[0]],

distance * (y0[ind] - y1[ind - 1]) + y1[ind - 1],

[y0[-1]],

])

# ensure that the lut is confined to values between 0 and 1 by clipping it

return np.clip(lut, 0.0, 1.0)

class Colormap:

"""

Baseclass for all scalar to RGBA mappings.

Typically, Colormap instances are used to convert data values (floats)

from the interval ``[0, 1]`` to the RGBA color that the respective

Colormap represents. For scaling of data into the ``[0, 1]`` interval see

`matplotlib.colors.Normalize`. Subclasses of `matplotlib.cm.ScalarMappable`

make heavy use of this ``data -> normalize -> map-to-color`` processing

chain.

"""

def __init__(self, name, N=256, *, bad=None, under=None, over=None):

"""

Parameters

----------

name : str

The name of the colormap.

N : int

The number of RGB quantization levels.

bad : :mpltype:`color`, default: transparent

The color for invalid values (NaN or masked).

.. versionadded:: 3.11

under : :mpltype:`color`, default: color of the lowest value

The color for low out-of-range values.

.. versionadded:: 3.11

over : :mpltype:`color`, default: color of the highest value

The color for high out-of-range values.

.. versionadded:: 3.11

"""

self.name = name

self.N = int(N) # ensure that N is always int

self._rgba_bad = (0.0, 0.0, 0.0, 0.0) if bad is None else to_rgba(bad)

self._rgba_under = None if under is None else to_rgba(under)

self._rgba_over = None if over is None else to_rgba(over)

self._i_under = self.N

self._i_over = self.N + 1

self._i_bad = self.N + 2

self._isinit = False

self.n_variates = 1

#: When this colormap exists on a scalar mappable and colorbar_extend

#: is not False, colorbar creation will pick up ``colorbar_extend`` as

#: the default value for the ``extend`` keyword in the

#: `matplotlib.colorbar.Colorbar` constructor.

self.colorbar_extend = False

def __call__(self, X, alpha=None, bytes=False):

r"""

Parameters

----------

X : float or int or array-like

The data value(s) to convert to RGBA.

For floats, *X* should be in the interval ``[0.0, 1.0]`` to

return the RGBA values ``X*100`` percent along the Colormap line.

For integers, *X* should be in the interval ``[0, Colormap.N)`` to

return RGBA values *indexed* from the Colormap with index ``X``.

alpha : float or array-like or None

Alpha must be a scalar between 0 and 1, a sequence of such

floats with shape matching X, or None.

bytes : bool, default: False

If False (default), the returned RGBA values will be floats in the

interval ``[0, 1]`` otherwise they will be `numpy.uint8`\s in the

interval ``[0, 255]``.

Returns

-------

Tuple of RGBA values if X is scalar, otherwise an array of

RGBA values with a shape of ``X.shape + (4, )``.

"""

rgba, mask = self._get_rgba_and_mask(X, alpha=alpha, bytes=bytes)

if not np.iterable(X):

rgba = tuple(rgba)

return rgba

def _get_rgba_and_mask(self, X, alpha=None, bytes=False):

r"""

Parameters

----------

X : float or int or array-like

The data value(s) to convert to RGBA.

For floats, *X* should be in the interval ``[0.0, 1.0]`` to

return the RGBA values ``X*100`` percent along the Colormap line.

For integers, *X* should be in the interval ``[0, Colormap.N)`` to

return RGBA values *indexed* from the Colormap with index ``X``.

alpha : float or array-like or None

Alpha must be a scalar between 0 and 1, a sequence of such

floats with shape matching X, or None.

bytes : bool, default: False

If False (default), the returned RGBA values will be floats in the

interval ``[0, 1]`` otherwise they will be `numpy.uint8`\s in the

interval ``[0, 255]``.

Returns

-------

colors : np.ndarray

Array of RGBA values with a shape of ``X.shape + (4, )``.

mask : np.ndarray

Boolean array with True where the input is ``np.nan`` or masked.

"""

self._ensure_inited()

xa = np.array(X, copy=True)

if not xa.dtype.isnative:

# Native byteorder is faster.

xa = xa.byteswap().view(xa.dtype.newbyteorder())

if xa.dtype.kind == "f":

xa *= self.N

# xa == 1 (== N after multiplication) is not out of range.

xa[xa == self.N] = self.N - 1

# Pre-compute the masks before casting to int (which can truncate

# negative values to zero or wrap large floats to negative ints).

mask_under = xa < 0

mask_over = xa >= self.N

# If input was masked, get the bad mask from it; else mask out nans.

mask_bad = X.mask if np.ma.is_masked(X) else np.isnan(xa)

with np.errstate(invalid="ignore"):

# We need this cast for unsigned ints as well as floats

xa = xa.astype(int)

xa[mask_under] = self._i_under

xa[mask_over] = self._i_over

xa[mask_bad] = self._i_bad

lut = self._lut

if bytes:

lut = (lut * 255).astype(np.uint8)

rgba = lut.take(xa, axis=0, mode='clip')

if alpha is not None:

alpha = np.clip(alpha, 0, 1)

if bytes:

alpha *= 255 # Will be cast to uint8 upon assignment.

if alpha.shape not in [(), xa.shape]:

raise ValueError(

f"alpha is array-like but its shape {alpha.shape} does "

f"not match that of X {xa.shape}")

rgba[..., -1] = alpha

# If the "bad" color is all zeros, then ignore alpha input.

if (lut[-1] == 0).all():

rgba[mask_bad] = (0, 0, 0, 0)

return rgba, mask_bad

def __copy__(self):

cls = self.__class__

cmapobject = cls.__new__(cls)

cmapobject.__dict__.update(self.__dict__)

if self._isinit:

cmapobject._lut = np.copy(self._lut)

return cmapobject

def __eq__(self, other):

if (not isinstance(other, Colormap) or

self.colorbar_extend != other.colorbar_extend):

return False

# To compare lookup tables the Colormaps have to be initialized

self._ensure_inited()

other._ensure_inited()

return np.array_equal(self._lut, other._lut)

def get_bad(self):

"""Get the color for masked values."""

self._ensure_inited()

return np.array(self._lut[self._i_bad])

@_api.deprecated(

"3.11",

pending=True,

alternative="cmap.with_extremes(bad=...) or Colormap(bad=...)")

def set_bad(self, color='k', alpha=None):

"""Set the color for masked values."""

self._set_extremes(bad=(color, alpha))

def get_under(self):

"""Get the color for low out-of-range values."""

self._ensure_inited()

return np.array(self._lut[self._i_under])

@_api.deprecated(

"3.11",

pending=True,

alternative="cmap.with_extremes(under=...) or Colormap(under=...)")

def set_under(self, color='k', alpha=None):

"""Set the color for low out-of-range values."""

self._set_extremes(under=(color, alpha))

def get_over(self):

"""Get the color for high out-of-range values."""

self._ensure_inited()

return np.array(self._lut[self._i_over])

@_api.deprecated(

"3.11",

pending=True,

alternative="cmap.with_extremes(over=...) or Colormap(over=...)")

def set_over(self, color='k', alpha=None):

"""Set the color for high out-of-range values."""

self._set_extremes(over=(color, alpha))

@_api.deprecated(

"3.11",

pending=True,

alternative="cmap.with_extremes(bad=..., under=..., over=...) or "

"Colormap(bad=..., under=..., over=...)")

def set_extremes(self, *, bad=None, under=None, over=None):

"""

Set the colors for masked (*bad*) values and, when ``norm.clip =

False``, low (*under*) and high (*over*) out-of-range values.

"""

self._set_extremes(bad=bad, under=under, over=over)

def with_extremes(self, *, bad=None, under=None, over=None):

"""

Return a copy of the colormap, for which the colors for masked (*bad*)

values and, when ``norm.clip = False``, low (*under*) and high (*over*)

out-of-range values, have been set accordingly.

"""

new_cm = self.copy()

new_cm._set_extremes(bad=bad, under=under, over=over)

return new_cm

def _set_extremes(self, bad=None, under=None, over=None):

"""

Set the colors for masked (*bad*) and out-of-range (*under* and *over*) values.

Parameters that are None are left unchanged.

"""

if bad is not None:

self._rgba_bad = to_rgba(bad)

if under is not None:

self._rgba_under = to_rgba(under)

if over is not None:

self._rgba_over = to_rgba(over)

if self._isinit:

self._update_lut_extremes()

def _update_lut_extremes(self):

"""Ensure than an existing lookup table has the correct extreme values."""

if self._rgba_under:

self._lut[self._i_under] = self._rgba_under

else:

self._lut[self._i_under] = self._lut[0]

if self._rgba_over:

self._lut[self._i_over] = self._rgba_over

else:

self._lut[self._i_over] = self._lut[self.N - 1]

self._lut[self._i_bad] = self._rgba_bad

def with_alpha(self, alpha):

"""

Return a copy of the colormap with a new uniform transparency.

Parameters

----------

alpha : float

The alpha blending value, between 0 (transparent) and 1 (opaque).

"""

if not isinstance(alpha, Real):

raise TypeError(f"'alpha' must be numeric or None, not {type(alpha)}")

if not 0 <= alpha <= 1:

raise ValueError("'alpha' must be between 0 and 1, inclusive")

new_cm = self.copy()

new_cm._ensure_inited()

new_cm._lut[:, 3] = alpha

return new_cm

def _init(self):

"""Generate the lookup table, ``self._lut``."""

raise NotImplementedError("Abstract class only")

def _ensure_inited(self):

if not self._isinit:

self._init()

def is_gray(self):

"""Return whether the colormap is grayscale."""

self._ensure_inited()

return (np.all(self._lut[:, 0] == self._lut[:, 1]) and

np.all(self._lut[:, 0] == self._lut[:, 2]))

def resampled(self, lutsize):

"""Return a new colormap with *lutsize* entries."""

if hasattr(self, '_resample'):

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