"""
Palettes are the link between data values and the values along
the dimension of a scale. Before a collection of values can be
represented on a scale, they are transformed by a palette. This
transformation is knowing as mapping. Values are mapped onto a
scale by a palette.
Scales tend to have restrictions on the magnitude of quantities
that they can intelligibly represent. For example, the size of
a point should be significantly smaller than the plot panel
onto which it is plotted or else it would be hard to compare
two or more points. Therefore palettes must be created that
enforce such restrictions. This is the reason for the ``*_pal``
functions that create and return the actual palette functions.
"""
from __future__ import annotations
import colorsys
import typing
from warnings import warn
import numpy as np
import pandas as pd
from .bounds import rescale
from .external import crayon_rgb, husl, xkcd_rgb
from .utils import identity
if typing.TYPE_CHECKING:
from typing import Literal
from mizani.colors.typing import ColorScheme, ColorSchemeShort
__all__ = [
"hls_palette",
"husl_palette",
"rescale_pal",
"area_pal",
"abs_area",
"grey_pal",
"hue_pal",
"brewer_pal",
"gradient_n_pal",
"cmap_pal",
"cmap_d_pal",
"desaturate_pal",
"manual_pal",
"xkcd_palette",
"crayon_palette",
"cubehelix_pal",
]
[docs]def hls_palette(n_colors=6, h=0.01, l=0.6, s=0.65):
"""
Get a set of evenly spaced colors in HLS hue space.
h, l, and s should be between 0 and 1
Parameters
----------
n_colors : int
number of colors in the palette
h : float
first hue
l : float
lightness
s : float
saturation
Returns
-------
palette : list
List of colors as RGB hex strings.
See Also
--------
husl_palette : Make a palette using evenly spaced circular
hues in the HUSL system.
Examples
--------
>>> len(hls_palette(2))
2
>>> len(hls_palette(9))
9
"""
hues = np.linspace(0, 1, n_colors + 1)[:-1]
hues += h
hues %= 1
hues -= hues.astype(int)
palette = [colorsys.hls_to_rgb(h_i, l, s) for h_i in hues]
return palette
[docs]def husl_palette(n_colors=6, h=0.01, s=0.9, l=0.65):
"""
Get a set of evenly spaced colors in HUSL hue space.
h, s, and l should be between 0 and 1
Parameters
----------
n_colors : int
number of colors in the palette
h : float
first hue
s : float
saturation
l : float
lightness
Returns
-------
palette : list
List of colors as RGB hex strings.
See Also
--------
hls_palette : Make a palette using evenly spaced circular
hues in the HSL system.
Examples
--------
>>> len(husl_palette(3))
3
>>> len(husl_palette(11))
11
"""
hues = np.linspace(0, 1, n_colors + 1)[:-1]
hues += h
hues %= 1
hues *= 359
s *= 99
l *= 99
palette = [husl.husl_to_rgb(h_i, s, l) for h_i in hues]
return palette
[docs]def rescale_pal(range=(0.1, 1)):
"""
Rescale the input to the specific output range.
Useful for alpha, size, and continuous position.
Parameters
----------
range : tuple
Range of the scale
Returns
-------
out : function
Palette function that takes a sequence of values
in the range ``[0, 1]`` and returns values in
the specified range.
Examples
--------
>>> palette = rescale_pal()
>>> palette([0, .2, .4, .6, .8, 1])
array([0.1 , 0.28, 0.46, 0.64, 0.82, 1. ])
The returned palette expects inputs in the ``[0, 1]``
range. Any value outside those limits is clipped to
``range[0]`` or ``range[1]``.
>>> palette([-2, -1, 0.2, .4, .8, 2, 3])
array([0.1 , 0.1 , 0.28, 0.46, 0.82, 1. , 1. ])
"""
def _rescale(x):
return rescale(x, range, _from=(0, 1))
return _rescale
[docs]def area_pal(range=(1, 6)):
"""
Point area palette (continuous).
Parameters
----------
range : tuple
Numeric vector of length two, giving range of possible sizes.
Should be greater than 0.
Returns
-------
out : function
Palette function that takes a sequence of values
in the range ``[0, 1]`` and returns values in
the specified range.
Examples
--------
>>> x = np.arange(0, .6, .1)**2
>>> palette = area_pal()
>>> palette(x)
array([1. , 1.5, 2. , 2.5, 3. , 3.5])
The results are equidistant because the input ``x`` is in
area space, i.e it is squared.
"""
def area_palette(x):
return rescale(np.sqrt(x), to=range, _from=(0, 1))
return area_palette
[docs]def abs_area(max):
"""
Point area palette (continuous), with area proportional to value.
Parameters
----------
max : float
A number representing the maximum size
Returns
-------
out : function
Palette function that takes a sequence of values
in the range ``[0, 1]`` and returns values in the range
``[0, max]``.
Examples
--------
>>> x = np.arange(0, .8, .1)**2
>>> palette = abs_area(5)
>>> palette(x)
array([0. , 0.5, 1. , 1.5, 2. , 2.5, 3. , 3.5])
Compared to :func:`area_pal`, :func:`abs_area` will handle values
in the range ``[-1, 0]`` without returning ``np.nan``. And values
whose absolute value is greater than 1 will be clipped to the
maximum.
"""
def abs_area_palette(x):
return rescale(np.sqrt(np.abs(x)), to=(0, max), _from=(0, 1))
return abs_area_palette
[docs]def grey_pal(start=0.2, end=0.8):
"""
Utility for creating continuous grey scale palette
Parameters
----------
start : float
grey value at low end of palette
end : float
grey value at high end of palette
Returns
-------
out : function
Continuous color palette that takes a single
:class:`int` parameter ``n`` and returns ``n``
equally spaced colors.
Examples
--------
>>> palette = grey_pal()
>>> palette(5)
['#333333', '#737373', '#989898', '#b5b5b5', '#cccccc']
"""
import matplotlib.colors as mcolors
gamma = 2.2
ends = ((0.0, start, start), (1.0, end, end))
cdict = {"red": ends, "green": ends, "blue": ends}
grey_cmap = mcolors.LinearSegmentedColormap("grey", cdict)
def continuous_grey_palette(n):
# The grey scale points are linearly separated in
# gamma encoded space
x = np.linspace(start**gamma, end**gamma, n)
# Map points onto the [0, 1] palette domain
vals = (x ** (1.0 / gamma) - start) / (end - start)
return ratios_to_colors(vals, grey_cmap)
return continuous_grey_palette
[docs]def hue_pal(h=0.01, l=0.6, s=0.65, color_space="hls"):
"""
Utility for making hue palettes for color schemes.
Parameters
----------
h : float
first hue. In the [0, 1] range
l : float
lightness. In the [0, 1] range
s : float
saturation. In the [0, 1] range
color_space : 'hls' | 'husl'
Color space to use for the palette
Returns
-------
out : function
A discrete color palette that takes a single
:class:`int` parameter ``n`` and returns ``n``
equally spaced colors. Though the palette
is continuous, since it is varies the hue it
is good for categorical data. However if ``n``
is large enough the colors show continuity.
Examples
--------
>>> hue_pal()(5)
['#db5f57', '#b9db57', '#57db94', '#5784db', '#c957db']
>>> hue_pal(color_space='husl')(5)
['#e0697e', '#9b9054', '#569d79', '#5b98ab', '#b675d7']
"""
import matplotlib.colors as mcolors
if not all(0 <= val <= 1 for val in (h, l, s)):
msg = (
"hue_pal expects values to be between 0 and 1. "
" I got h={}, l={}, s={}".format(h, l, s)
)
raise ValueError(msg)
if color_space not in ("hls", "husl"):
msg = "color_space should be one of ['hls', 'husl']"
raise ValueError(msg)
name = "{}_palette".format(color_space)
palette = globals()[name]
def _hue_pal(n):
colors = palette(n, h=h, l=l, s=s)
return [mcolors.rgb2hex(c) for c in colors]
return _hue_pal
[docs]def brewer_pal(
type: ColorScheme | ColorSchemeShort = "seq",
palette: int = 1,
direction: Literal[1, -1] = 1,
):
"""
Utility for making a brewer palette
Parameters
----------
type : 'sequential' | 'qualitative' | 'diverging'
Type of palette. Sequential, Qualitative or
Diverging. The following abbreviations may
be used, ``seq``, ``qual`` or ``div``.
palette : int | str
Which palette to choose from. If is an integer,
it must be in the range ``[0, m]``, where ``m``
depends on the number sequential, qualitative or
diverging palettes. If it is a string, then it
is the name of the palette.
direction : int
The order of colours in the scale. If -1 the order
of colors is reversed. The default is 1.
Returns
-------
out : function
A color palette that takes a single
:class:`int` parameter ``n`` and returns ``n``
colors. The maximum value of ``n`` varies
depending on the parameters.
Examples
--------
>>> brewer_pal()(5)
['#EFF3FF', '#BDD7E7', '#6BAED6', '#3182BD', '#08519C']
>>> brewer_pal('qual')(5)
['#7FC97F', '#BEAED4', '#FDC086', '#FFFF99', '#386CB0']
>>> brewer_pal('qual', 2)(5)
['#1B9E77', '#D95F02', '#7570B3', '#E7298A', '#66A61E']
>>> brewer_pal('seq', 'PuBuGn')(5)
['#F6EFF7', '#BDC9E1', '#67A9CF', '#1C9099', '#016C59']
The available color names for each palette type can be
obtained using the following code::
from mizani.colors.brewer import get_palette_names
print(get_palette_names("sequential"))
print(get_palette_names("qualitative"))
print(get_palette_names("diverging"))
"""
from .colors import brewer
if direction != 1 and direction != -1:
raise ValueError("direction should be 1 or -1.")
pal = brewer.get_color_palette(type, palette)
def _brewer_pal(n):
# Only draw the maximum allowable colors from the palette
# and fill any remaining spots with None
_n = min(max(n, pal.min_colors), pal.max_colors)
color_map = pal.get_hex_swatch(_n)
colors = color_map[:n]
if n > pal.max_colors:
msg = (
"Warning message:"
f"Brewer palette {pal.name} has a maximum "
f"of {pal.max_colors} colors Returning the palette you "
"asked for with that many colors"
)
warn(msg)
colors = colors + [None] * (n - pal.max_colors)
return colors[::direction]
return _brewer_pal
def ratios_to_colors(values, colormap):
"""
Map values in the range [0, 1] onto colors
Parameters
----------
values : array_like | float
Numeric(s) in the range [0, 1]
colormap : cmap
Matplotlib colormap to use for the mapping
Returns
-------
out : list | float
Color(s) corresponding to the values
"""
import matplotlib.colors as mcolors
iterable = True
try:
iter(values)
except TypeError:
iterable = False
values = [values]
color_tuples = colormap(values)
hex_colors = [mcolors.rgb2hex(t) for t in color_tuples]
nan_bool_idx = pd.isnull(values) | np.isinf(values)
if any(nan_bool_idx):
hex_colors = [
np.nan if is_nan else color
for color, is_nan in zip(hex_colors, nan_bool_idx)
]
return hex_colors if iterable else hex_colors[0]
[docs]def gradient_n_pal(colors, values=None, name="gradientn"):
"""
Create a n color gradient palette
Parameters
----------
colors : list
list of colors
values : list, optional
list of points in the range [0, 1] at which to
place each color. Must be the same size as
`colors`. Default to evenly space the colors
name : str
Name to call the resultant MPL colormap
Returns
-------
out : function
Continuous color palette that takes a single
parameter either a :class:`float` or a sequence
of floats maps those value(s) onto the palette
and returns color(s). The float(s) must be
in the range [0, 1].
Examples
--------
>>> palette = gradient_n_pal(['red', 'blue'])
>>> palette([0, .25, .5, .75, 1])
['#ff0000', '#bf0040', '#7f0080', '#3f00c0', '#0000ff']
>>> palette([-np.inf, 0, np.nan, 1, np.inf])
[nan, '#ff0000', nan, '#0000ff', nan]
"""
import matplotlib.colors as mcolors
# Note: For better results across devices and media types,
# it would be better to do the interpolation in
# Lab color space.
if values is None:
colormap = mcolors.LinearSegmentedColormap.from_list(name, colors)
else:
colormap = mcolors.LinearSegmentedColormap.from_list(
name, list(zip(values, colors))
)
def _gradient_n_pal(vals):
return ratios_to_colors(vals, colormap)
return _gradient_n_pal
[docs]def cmap_pal(name, lut=None):
"""
Create a continuous palette using an MPL colormap
Parameters
----------
name : str
Name of colormap
lut : None | int
This is the number of entries desired in the lookup table.
Default is ``None``, leave it up Matplotlib.
Returns
-------
out : function
Continuous color palette that takes a single
parameter either a :class:`float` or a sequence
of floats maps those value(s) onto the palette
and returns color(s). The float(s) must be
in the range [0, 1].
Examples
--------
>>> palette = cmap_pal('viridis')
>>> palette([.1, .2, .3, .4, .5])
['#482475', '#414487', '#355f8d', '#2a788e', '#21918c']
"""
import matplotlib as mpl
colormap = mpl.colormaps[name]
if lut is not None:
warn(
"The lut parameter has been deprecated and will "
"be removed in a future version.",
FutureWarning,
)
resample = getattr(
colormap, "resampled", getattr(colormap, "_resample", None)
)
colormap = resample(lut)
def _cmap_pal(vals):
return ratios_to_colors(vals, colormap)
return _cmap_pal
[docs]def cmap_d_pal(name, lut=None):
"""
Create a discrete palette using an MPL Listed colormap
Parameters
----------
name : str
Name of colormap
lut : None | int
This is the number of entries desired in the lookup table.
Default is ``None``, leave it up Matplotlib.
Returns
-------
out : function
A discrete color palette that takes a single
:class:`int` parameter ``n`` and returns ``n``
colors. The maximum value of ``n`` varies
depending on the parameters.
Examples
--------
>>> palette = cmap_d_pal('viridis')
>>> palette(5)
['#440154', '#3b528b', '#21918c', '#5cc863', '#fde725']
"""
import matplotlib as mpl
import matplotlib.colors as mcolors
colormap = mpl.colormaps[name]
if lut is not None:
warn(
"The lut parameter has been deprecated and will "
"be removed in a future version.",
FutureWarning,
)
resample = getattr(
colormap, "resampled", getattr(colormap, "_resample", None)
)
colormap = resample(lut)
if not isinstance(colormap, mcolors.ListedColormap):
raise ValueError(
"For a discrete palette, cmap must be of type "
"matplotlib.colors.ListedColormap"
)
ncolors = len(colormap.colors)
def _cmap_d_pal(n):
if n > ncolors:
raise ValueError(
"cmap `{}` has {} colors you requested {} "
"colors.".format(name, ncolors, n)
)
if ncolors < 256:
return [mcolors.rgb2hex(c) for c in colormap.colors[:n]]
else:
# Assume these are continuous and get colors equally spaced
# intervals e.g. viridis is defined with 256 colors
idx = np.linspace(0, ncolors - 1, n).round().astype(int)
return [mcolors.rgb2hex(colormap.colors[i]) for i in idx]
return _cmap_d_pal
[docs]def desaturate_pal(color, prop, reverse=False):
"""
Create a palette that desaturate a color by some proportion
Parameters
----------
color : matplotlib color
hex, rgb-tuple, or html color name
prop : float
saturation channel of color will be multiplied by
this value
reverse : bool
Whether to reverse the palette.
Returns
-------
out : function
Continuous color palette that takes a single
parameter either a :class:`float` or a sequence
of floats maps those value(s) onto the palette
and returns color(s). The float(s) must be
in the range [0, 1].
Examples
--------
>>> palette = desaturate_pal('red', .1)
>>> palette([0, .25, .5, .75, 1])
['#ff0000', '#e21d1d', '#c53a3a', '#a95656', '#8c7373']
"""
import matplotlib.colors as mcolors
if not 0 <= prop <= 1:
raise ValueError("prop must be between 0 and 1")
# Get rgb tuple rep
# Convert to hls
# Desaturate the saturation channel
# Convert back to rgb
rgb = mcolors.colorConverter.to_rgb(color)
h, l, s = colorsys.rgb_to_hls(*rgb)
s *= prop
desaturated_color = colorsys.hls_to_rgb(h, l, s)
colors = [color, desaturated_color]
if reverse:
colors = colors[::-1]
return gradient_n_pal(colors, name="desaturated")
[docs]def manual_pal(values):
"""
Create a palette from a list of values
Parameters
----------
values : sequence
Values that will be returned by the palette function.
Returns
-------
out : function
A function palette that takes a single
:class:`int` parameter ``n`` and returns ``n`` values.
Examples
--------
>>> palette = manual_pal(['a', 'b', 'c', 'd', 'e'])
>>> palette(3)
['a', 'b', 'c']
"""
max_n = len(values)
def _manual_pal(n):
if n > max_n:
msg = (
"Palette can return a maximum of {} values. "
"{} values requested."
)
warn(msg.format(max_n, n))
return values[:n]
return _manual_pal
[docs]def xkcd_palette(colors):
"""
Make a palette with color names from the xkcd color survey.
See xkcd for the full list of colors: http://xkcd.com/color/rgb/
Parameters
----------
colors : list of strings
List of keys in the ``mizani.external.xkcd_rgb`` dictionary.
Returns
-------
palette : list
List of colors as RGB hex strings.
Examples
--------
>>> palette = xkcd_palette(['red', 'green', 'blue'])
>>> palette
['#e50000', '#15b01a', '#0343df']
>>> from mizani.external import xkcd_rgb
>>> list(sorted(xkcd_rgb.keys()))[:5]
['acid green', 'adobe', 'algae', 'algae green', 'almost black']
"""
return [xkcd_rgb[name] for name in colors]
[docs]def crayon_palette(colors):
"""
Make a palette with color names from Crayola crayons.
The colors come from
http://en.wikipedia.org/wiki/List_of_Crayola_crayon_colors
Parameters
----------
colors : list of strings
List of keys in the ``mizani.external.crayloax_rgb`` dictionary.
Returns
-------
palette : list
List of colors as RGB hex strings.
Examples
--------
>>> palette = crayon_palette(['almond', 'silver', 'yellow'])
>>> palette
['#eed9c4', '#c9c0bb', '#fbe870']
>>> from mizani.external import crayon_rgb
>>> list(sorted(crayon_rgb.keys()))[:5]
['almond', 'antique brass', 'apricot', 'aquamarine', 'asparagus']
"""
return [crayon_rgb[name] for name in colors]
[docs]def cubehelix_pal(
start=0, rot=0.4, gamma=1.0, hue=0.8, light=0.85, dark=0.15, reverse=False
):
"""
Utility for creating continuous palette from the cubehelix system.
This produces a colormap with linearly-decreasing (or increasing)
brightness. That means that information will be preserved if printed to
black and white or viewed by someone who is colorblind.
Parameters
----------
start : float (0 <= start <= 3)
The hue at the start of the helix.
rot : float
Rotations around the hue wheel over the range of the palette.
gamma : float (0 <= gamma)
Gamma factor to emphasize darker (gamma < 1) or lighter (gamma > 1)
colors.
hue : float (0 <= hue <= 1)
Saturation of the colors.
dark : float (0 <= dark <= 1)
Intensity of the darkest color in the palette.
light : float (0 <= light <= 1)
Intensity of the lightest color in the palette.
reverse : bool
If True, the palette will go from dark to light.
Returns
-------
out : function
Continuous color palette that takes a single
:class:`int` parameter ``n`` and returns ``n``
equally spaced colors.
References
----------
Green, D. A. (2011). "A colour scheme for the display of astronomical
intensity images". Bulletin of the Astromical Society of India, Vol. 39,
p. 289-295.
Examples
--------
>>> palette = cubehelix_pal()
>>> palette(5)
['#edd1cb', '#d499a7', '#aa688f', '#6e4071', '#2d1e3e']
"""
import matplotlib as mpl
import matplotlib.colors as mcolors
cdict = mpl._cm.cubehelix(gamma, start, rot, hue)
cubehelix_cmap = mcolors.LinearSegmentedColormap("cubehelix", cdict)
def cubehelix_palette(n):
values = np.linspace(light, dark, n)
return [mcolors.rgb2hex(cubehelix_cmap(x)) for x in values]
return cubehelix_palette
def identity_pal():
"""
Create palette that maps values onto themselves
Returns
-------
out : function
Palette function that takes a value or sequence of values
and returns the same values.
Examples
--------
>>> palette = identity_pal()
>>> palette(9)
9
>>> palette([2, 4, 6])
[2, 4, 6]
"""
return identity