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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"

"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">

<head>

<title>matplotlib.colors — Matplotlib 3.3.1 documentation</title>

title="Search within Matplotlib 3.3.1 documentation"

href="../../_static/opensearch.xml"/>

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<div style="float: left; position: absolute; width: 496px; bottom: 0; padding-bottom: 24px">Version 3.3.1</div>

<div id="forkongithub"><a href="https://github.com/matplotlib/matplotlib">Fork me on GitHub</a></div>

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<h1>Source code for matplotlib.colors</h1><div class="highlight"><pre>

"""

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

sublasses 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::

:doc:`/tutorials/colors/colormap-manipulation` for examples of how to

make colormaps and

:doc:`/tutorials/colors/colormaps` for a list of built-in colormaps.

:doc:`/tutorials/colors/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.

Matplotlib recognizes the following formats to specify a color:

* an RGB or RGBA (red, green, blue, alpha) tuple of float values in closed

interval ``[0, 1]`` (e.g., ``(0.1, 0.2, 0.5)`` or ``(0.1, 0.2, 0.5, 0.3)``);

* a hex RGB or RGBA string (e.g., ``'#0f0f0f'`` or ``'#0f0f0f80'``;

case-insensitive);

* a shorthand hex RGB or RGBA string, equivalent to the hex RGB or RGBA

string obtained by duplicating each character, (e.g., ``'#abc'``, equivalent

to ``'#aabbcc'``, or ``'#abcd'``, equivalent to ``'#aabbccdd'``;

case-insensitive);

* a string representation of a float value in ``[0, 1]`` inclusive for gray

level (e.g., ``'0.5'``);

* one of the characters ``{'b', 'g', 'r', 'c', 'm', 'y', 'k', 'w'}``, which

are short-hand notations for shades of blue, green, red, cyan, magenta,

yellow, black, and white. Note that the colors ``'g', 'c', 'm', 'y'`` do not

coincide with the X11/CSS4 colors. Their particular shades were chosen for

better visibility of colored lines against typical backgrounds.

* a X11/CSS4 color name (case-insensitive);

* a name from the `xkcd color survey`_, prefixed with ``'xkcd:'`` (e.g.,

``'xkcd:sky blue'``; case insensitive);

* one of the Tableau Colors from the 'T10' categorical palette (the default

color cycle): ``{'tab:blue', 'tab:orange', 'tab:green', 'tab:red',

'tab:purple', 'tab:brown', 'tab:pink', 'tab:gray', 'tab:olive', 'tab:cyan'}``

(case-insensitive);

* a "CN" color spec, i.e. 'C' followed by a number, which is an index into the

default property cycle (:rc:`axes.prop_cycle`); the indexing is intended to

occur at rendering time, and defaults to black if the cycle does not include

color.

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

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

"""

from collections.abc import Sized

import functools

import itertools

from numbers import Number

import re

import numpy as np

import matplotlib.cbook as cbook

from matplotlib import docstring

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)

<div class="viewcode-block" id="get_named_colors_mapping"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.get_named_colors_mapping.html#matplotlib.colors.get_named_colors_mapping">[docs]</a>def get_named_colors_mapping():

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

return _colors_full_map</div>

def _sanitize_extrema(ex):

if ex is None:

return ex

try:

ret = ex.item()

except AttributeError:

ret = float(ex)

return ret

def _is_nth_color(c):

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

return isinstance(c, str) and re.match(r"\AC[0-9]+\Z", c)

<div class="viewcode-block" id="is_color_like"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.is_color_like.html#matplotlib.colors.is_color_like">[docs]</a>def is_color_like(c):

"""Return whether *c* can be interpreted as an RGB(A) color."""

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

if _is_nth_color(c):

return True

try:

to_rgba(c)

except ValueError:

return False

else:

return True</div>

<div class="viewcode-block" id="same_color"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.same_color.html#matplotlib.colors.same_color">[docs]</a>def same_color(c1, c2):

"""

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

*c1*, *c2* can be single colors or lists/arrays of colors.

"""

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()</div>

<div class="viewcode-block" id="to_rgba"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.to_rgba.html#matplotlib.colors.to_rgba">[docs]</a>def to_rgba(c, alpha=None):

"""

Convert *c* to an RGBA color.

Parameters

----------

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

alpha : float, optional

If *alpha* is not ``None``, it forces the alpha value, except if *c* is

``"none"`` (case-insensitive), which always maps to ``(0, 0, 0, 0)``.

Returns

-------

tuple

Tuple of ``(r, g, b, a)`` scalars.

"""

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

if _is_nth_color(c):

from matplotlib import rcParams

prop_cycler = 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</div>

def _to_rgba_no_colorcycle(c, alpha=None):

"""

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

If *alpha* is not ``None``, it forces the alpha value, except if *c* is

``"none"`` (case-insensitive), which always maps to ``(0, 0, 0, 0)``.

"""

orig_c = c

if c is np.ma.masked:

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

if isinstance(c, str):

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

# 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(orig_c) != 1:

try:

c = _colors_full_map[c.lower()]

except KeyError:

pass

if isinstance(c, str):

# hex color in #rrggbb format.

match = re.match(r"\A#[a-fA-F0-9]{6}\Z", c)

if match:

return (tuple(int(n, 16) / 255

+ (alpha if alpha is not None else 1.,))

# hex color in #rgb format, shorthand for #rrggbb.

match = re.match(r"\A#[a-fA-F0-9]{3}\Z", c)

if match:

for n in [c[1]*2, c[2]*2, c[3]*2])

# hex color with alpha in #rrggbbaa format.

match = re.match(r"\A#[a-fA-F0-9]{8}\Z", c)

if match:

color = [int(n, 16) / 255

for n in [c[1:3], c[3:5], c[5:7], c[7:9]]]

if alpha is not None:

color[-1] = alpha

return tuple(color)

# hex color with alpha in #rgba format, shorthand for #rrggbbaa.

match = re.match(r"\A#[a-fA-F0-9]{4}\Z", c)

if match:

if alpha is not None:

color[-1] = alpha

return tuple(color)

# 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}")

# tuple color.

if not np.iterable(c):

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

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

if not all(isinstance(x, Number) 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.

# 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

<div class="viewcode-block" id="to_rgba_array"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.to_rgba_array.html#matplotlib.colors.to_rgba_array">[docs]</a>def to_rgba_array(c, alpha=None):

"""

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

If *alpha* is not ``None``, it forces the alpha value. If *c* is

``"none"`` (case-insensitive) or an empty list, an empty array is returned.

If *c* is a masked array, an ndarray is returned with a (0, 0, 0, 0)

row for each masked value or row in *c*.

"""

# 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 (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 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:

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

except (ValueError, TypeError):

pass

# Convert one at a time.

if isinstance(c, str):

# Single string as color sequence.

# This is deprecated and will be removed in the future.

try:

result = np.array([to_rgba(cc, alpha) for cc in c])

except ValueError as err:

raise ValueError(

"'%s' is neither a valid single color nor a color sequence "

"consisting of single character color specifiers such as "

"'rgb'. Note also that the latter is deprecated." % c) from err

else:

cbook.warn_deprecated(

"3.2", message="Using a string of single character colors as "

"a color sequence is deprecated since %(since)s and will be "

"removed %(removal)s. Use an explicit list instead.")

return result

else:

return np.array([to_rgba(cc, alpha) for cc in c])</div>

<div class="viewcode-block" id="to_rgb"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.to_rgb.html#matplotlib.colors.to_rgb">[docs]</a>def to_rgb(c):

"""Convert *c* to an RGB color, silently dropping the alpha channel."""

return to_rgba(c)[:3]</div>

<div class="viewcode-block" id="to_hex"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.to_hex.html#matplotlib.colors.to_hex">[docs]</a>def to_hex(c, keep_alpha=False):

"""

Convert *c* to a hex color.

Uses the ``#rrggbb`` format if *keep_alpha* is False (the default),

``#rrggbbaa`` otherwise.

"""

c = to_rgba(c)

if not keep_alpha:

c = c[:3]

return "#" + "".join(format(int(round(val * 255)), "02x") for val in c)</div>

### Backwards-compatible color-conversion API

cnames = CSS4_COLORS

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

rgb2hex = to_hex

hex2color = to_rgb

class ColorConverter:

"""

A class only kept for backwards compatibility.

Its functionality is entirely provided by module-level functions.

"""

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 1-d 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 : Mx3 array-like or callable

Defines the mapping :math:`f`.

If a Mx3 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

shape = adata.shape

if len(shape) != 2 or shape[1] != 3:

raise ValueError("data must be nx3 format")

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)

<div class="viewcode-block" id="makeMappingArray"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.makeMappingArray.html#matplotlib.colors.makeMappingArray">[docs]</a>@cbook.deprecated("3.2",

addendum='This is not considered public API any longer.')

@docstring.copy(_create_lookup_table)

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

return _create_lookup_table(N, data, gamma)</div>

def _warn_if_global_cmap_modified(cmap):

if getattr(cmap, '_global', False):

cbook.warn_deprecated(

"3.3",

message="You are modifying the state of a globally registered "

"colormap. In future versions, you will not be able to "

"modify a registered colormap in-place. To remove this "

"warning, you can make a copy of the colormap first. "

f'cmap = copy.copy(mpl.cm.get_cmap("{cmap.name}"))'

)

<div class="viewcode-block" id="Colormap"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.Colormap.html#matplotlib.colors.Colormap">[docs]</a>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.

"""

<div class="viewcode-block" id="Colormap.__init__"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.Colormap.html#matplotlib.colors.Colormap.__init__">[docs]</a> def __init__(self, name, N=256):

"""

Parameters

----------

name : str

The name of the colormap.

N : int

The number of rgb quantization levels.

"""

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, don't paint anything.

self._rgba_under = None

self._rgba_over = None

self._i_under = self.N

self._i_over = self.N + 1

self._i_bad = self.N + 2

self._isinit = False

#: 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</div>

<div class="viewcode-block" id="Colormap.__call__"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.Colormap.html#matplotlib.colors.Colormap.__call__">[docs]</a> def __call__(self, X, alpha=None, bytes=False):

"""

Parameters

----------

X : float or int, ndarray or scalar

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, None

Alpha must be a scalar between 0 and 1, or None.

bytes : bool

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

interval ``[0, 1]`` otherwise they will be uint8s 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, )``.

"""

if not self._isinit:

self._init()

mask_bad = X.mask if np.ma.is_masked(X) else np.isnan(X) # Mask nan's.

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

if not xa.dtype.isnative:

xa = xa.byteswap().newbyteorder() # Native byteorder is faster.

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

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

xa *= self.N

# Negative values are out of range, but astype(int) would

# truncate them towards zero.

xa[xa < 0] = -1

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

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

# Avoid converting large positive values to negative integers.

np.clip(xa, -1, self.N, out=xa)

xa = xa.astype(int)

# Set the over-range indices before the under-range;

# otherwise the under-range values get converted to over-range.

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

xa[mask_bad] = self._i_bad

if bytes:

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

else:

lut = self._lut.copy() # Don't let alpha modify original _lut.

if alpha is not None:

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

if bytes:

alpha = int(alpha * 255)

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

lut[:-1, -1] = alpha

# All zeros is taken as a flag for the default bad

# color, which is no color--fully transparent. We

# don't want to override this.

else:

lut[:, -1] = alpha

# If the bad value is set to have a color, then we

# override its alpha just as for any other value.

rgba = lut[xa]

# Return a tuple if the input was a scalar

rgba = tuple(rgba)

return rgba</div>

<div class="viewcode-block" id="Colormap.__copy__"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.Colormap.html#matplotlib.colors.Colormap.__copy__">[docs]</a> def __copy__(self):

cls = self.__class__

cmapobject = cls.__new__(cls)

cmapobject.__dict__.update(self.__dict__)

if self._isinit:

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

cmapobject._global = False

return cmapobject</div>

<div class="viewcode-block" id="Colormap.set_bad"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.Colormap.html#matplotlib.colors.Colormap.set_bad">[docs]</a> def set_bad(self, color='k', alpha=None):

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

_warn_if_global_cmap_modified(self)

self._rgba_bad = to_rgba(color, alpha)

if self._isinit:

self._set_extremes()</div>

<div class="viewcode-block" id="Colormap.set_under"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.Colormap.html#matplotlib.colors.Colormap.set_under">[docs]</a> def set_under(self, color='k', alpha=None):

"""

Set the color for low out-of-range values when ``norm.clip = False``.

"""

_warn_if_global_cmap_modified(self)

self._rgba_under = to_rgba(color, alpha)

if self._isinit:

self._set_extremes()</div>

<div class="viewcode-block" id="Colormap.set_over"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.Colormap.html#matplotlib.colors.Colormap.set_over">[docs]</a> def set_over(self, color='k', alpha=None):

"""

Set the color for high out-of-range values when ``norm.clip = False``.

"""

_warn_if_global_cmap_modified(self)

self._rgba_over = to_rgba(color, alpha)

if self._isinit:

self._set_extremes()</div>

def _set_extremes(self):

if self._rgba_under:

else:

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

if self._rgba_over:

else:

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

def _init(self):

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

raise NotImplementedError("Abstract class only")

<div class="viewcode-block" id="Colormap.is_gray"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.Colormap.html#matplotlib.colors.Colormap.is_gray">[docs]</a> def is_gray(self):

if not self._isinit:

self._init()

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

np.all(self._lut[:, 0] == self._lut[:, 2]))</div>

def _resample(self, lutsize):

"""Return a new color map with *lutsize* entries."""

raise NotImplementedError()

<div class="viewcode-block" id="Colormap.reversed"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.Colormap.html#matplotlib.colors.Colormap.reversed">[docs]</a> def reversed(self, name=None):

"""

Return a reversed instance of the Colormap.

.. note:: This function is not implemented for base class.

Parameters

----------

name : str, optional

The name for the reversed colormap. If it's None the

name will be the name of the parent colormap + "_r".

See Also

--------

LinearSegmentedColormap.reversed

ListedColormap.reversed

"""

raise NotImplementedError()</div></div>

<div class="viewcode-block" id="LinearSegmentedColormap"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.LinearSegmentedColormap.html#matplotlib.colors.LinearSegmentedColormap">[docs]</a>class LinearSegmentedColormap(Colormap):

"""

Colormap objects based on lookup tables using linear segments.

The lookup table is generated using linear interpolation for each

primary color, with the 0-1 domain divided into any number of

segments.

"""

<div class="viewcode-block" id="LinearSegmentedColormap.__init__"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.LinearSegmentedColormap.html#matplotlib.colors.LinearSegmentedColormap.__init__">[docs]</a> def __init__(self, name, segmentdata, N=256, gamma=1.0):

"""

Create color map from linear mapping segments

segmentdata argument is a dictionary with a red, green and blue

entries. Each entry should be a list of *x*, *y0*, *y1* tuples,

forming rows in a table. Entries for alpha are optional.

Example: suppose you want red to increase from 0 to 1 over

the bottom half, green to do the same over the middle half,

and blue over the top half. Then you would use::

cdict = {'red': [(0.0, 0.0, 0.0),

(0.5, 1.0, 1.0),

(1.0, 1.0, 1.0)],

'green': [(0.0, 0.0, 0.0),

(0.25, 0.0, 0.0),

(0.75, 1.0, 1.0),

(1.0, 1.0, 1.0)],

'blue': [(0.0, 0.0, 0.0),

(0.5, 0.0, 0.0),

(1.0, 1.0, 1.0)]}

Each row in the table for a given color is a sequence of

*x*, *y0*, *y1* tuples. In each sequence, *x* must increase

monotonically from 0 to 1. For any input value *z* falling

between *x[i]* and *x[i+1]*, the output value of a given color

will be linearly interpolated between *y1[i]* and *y0[i+1]*::

row i: x y0 y1

/

row i+1: x y0 y1

Hence y0 in the first row and y1 in the last row are never used.

See Also

--------

LinearSegmentedColormap.from_list

Static method; factory function for generating a smoothly-varying

LinearSegmentedColormap.

makeMappingArray

For information about making a mapping array.

"""

# True only if all colors in map are identical; needed for contouring.

self.monochrome = False

Colormap.__init__(self, name, N)

self._segmentdata = segmentdata

self._gamma = gamma</div>

def _init(self):

self._lut = np.ones((self.N + 3, 4), float)

self._lut[:-3, 0] = _create_lookup_table(

self.N, self._segmentdata['red'], self._gamma)

self._lut[:-3, 1] = _create_lookup_table(

self.N, self._segmentdata['green'], self._gamma)

self._lut[:-3, 2] = _create_lookup_table(

self.N, self._segmentdata['blue'], self._gamma)

if 'alpha' in self._segmentdata:

self._lut[:-3, 3] = _create_lookup_table(

self.N, self._segmentdata['alpha'], 1)

self._isinit = True

self._set_extremes()

<div class="viewcode-block" id="LinearSegmentedColormap.set_gamma"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.LinearSegmentedColormap.html#matplotlib.colors.LinearSegmentedColormap.set_gamma">[docs]</a> def set_gamma(self, gamma):

"""Set a new gamma value and regenerate color map."""

self._gamma = gamma

self._init()</div>

<div class="viewcode-block" id="LinearSegmentedColormap.from_list"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.LinearSegmentedColormap.html#matplotlib.colors.LinearSegmentedColormap.from_list">[docs]</a> @staticmethod

def from_list(name, colors, N=256, gamma=1.0):

"""

Create a `LinearSegmentedColormap` from a list of colors.

Parameters

----------

name : str

The name of the colormap.

colors : array-like of colors or array-like of (value, color)

If only colors are given, they are equidistantly mapped from the

range :math:`[0, 1]`; i.e. 0 maps to ``colors[0]`` and 1 maps to

``colors[-1]``.

If (value, color) pairs are given, the mapping is from *value*

to *color*. This can be used to divide the range unevenly.

N : int

The number of rgb quantization levels.

gamma : float

"""

raise ValueError('colors must be iterable')

if (isinstance(colors[0], Sized) and len(colors[0]) == 2

and not isinstance(colors[0], str)):

# List of value, color pairs

vals, colors = zip(*colors)

else:

vals = np.linspace(0, 1, len(colors))

cdict = dict(red=[], green=[], blue=[], alpha=[])

for val, color in zip(vals, colors):

r, g, b, a = to_rgba(color)

cdict['red'].append((val, r, r))

cdict['green'].append((val, g, g))

cdict['blue'].append((val, b, b))

cdict['alpha'].append((val, a, a))

return LinearSegmentedColormap(name, cdict, N, gamma)</div>

def _resample(self, lutsize):

"""Return a new color map with *lutsize* entries."""

new_cmap = LinearSegmentedColormap(self.name, self._segmentdata,

lutsize)

new_cmap._rgba_over = self._rgba_over

new_cmap._rgba_under = self._rgba_under

new_cmap._rgba_bad = self._rgba_bad

return new_cmap

# Helper ensuring picklability of the reversed cmap.

@staticmethod

def _reverser(func, x):

return func(1 - x)

<div class="viewcode-block" id="LinearSegmentedColormap.reversed"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.LinearSegmentedColormap.html#matplotlib.colors.LinearSegmentedColormap.reversed">[docs]</a> def reversed(self, name=None):

"""

Return a reversed instance of the Colormap.

Parameters

----------

name : str, optional

The name for the reversed colormap. If it's None the

name will be the name of the parent colormap + "_r".

Returns

-------

LinearSegmentedColormap

The reversed colormap.

"""

if name is None:

name = self.name + "_r"

# Using a partial object keeps the cmap picklable.

data_r = {key: (functools.partial(self._reverser, data)

if callable(data) else

[(1.0 - x, y1, y0) for x, y0, y1 in reversed(data)])

for key, data in self._segmentdata.items()}

new_cmap = LinearSegmentedColormap(name, data_r, self.N, self._gamma)

# Reverse the over/under values too

new_cmap._rgba_over = self._rgba_under

new_cmap._rgba_bad = self._rgba_bad

return new_cmap</div></div>

<div class="viewcode-block" id="ListedColormap"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.colors.ListedColormap.html#matplotlib.colors.ListedColormap">[docs]</a>class ListedColormap(Colormap):

"""

Colormap object generated from a list of colors.

This may be most useful when indexing directly into a colormap,

but it can also be used to generate special colormaps for ordinary

mapping.

Parameters

----------

colors : list, array

List of Matplotlib color specifications, or an equivalent Nx3 or Nx4

floating point array (*N* rgb or rgba values).

name : str, optional

String to identify the colormap.

N : int, optional

Number of entries in the map. The default is *None*, in which case

there is one colormap entry for each element in the list of colors.

If ::

N < len(colors)

the list will be truncated at *N*. If ::

N > len(colors)

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