#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Colour Models Volume Plotting
=============================
Defines colour models volume and gamut plotting objects:
- :func:`RGB_colourspaces_gamuts_plot`
- :func:`RGB_scatter_plot`
"""
from __future__ import division
import matplotlib
import numpy as np
import pylab
from mpl_toolkits.mplot3d.art3d import Poly3DCollection
from colour.models import (
Lab_to_LCHab,
Luv_to_LCHuv,
Luv_to_uv,
UCS_to_uv,
RGB_to_XYZ,
XYZ_to_IPT,
XYZ_to_Lab,
XYZ_to_Luv,
XYZ_to_UCS,
XYZ_to_UVW,
XYZ_to_xy,
XYZ_to_xyY)
from colour.plotting import (
DEFAULT_PLOTTING_ILLUMINANT,
camera,
cube,
decorate,
display,
get_RGB_colourspace,
get_cmfs,
grid)
from colour.utilities import Structure, tsplit, tstack
__author__ = 'Colour Developers'
__copyright__ = 'Copyright (C) 2013 - 2015 - Colour Developers'
__license__ = 'New BSD License - http://opensource.org/licenses/BSD-3-Clause'
__maintainer__ = 'Colour Developers'
__email__ = 'colour-science@googlegroups.com'
__status__ = 'Production'
__all__ = ['REFERENCE_COLOURSPACES',
'REFERENCE_COLOURSPACES_TO_LABELS',
'nadir_grid',
'XYZ_to_reference_colourspace',
'RGB_identity_cube',
'RGB_colourspaces_gamuts_plot',
'RGB_scatter_plot']
REFERENCE_COLOURSPACES = (
'CIE XYZ',
'CIE xyY',
'CIE Lab',
'CIE Luv',
'CIE UCS',
'CIE UVW',
'IPT')
REFERENCE_COLOURSPACES_TO_LABELS = {
'CIE XYZ': ('X', 'Y', 'Z'),
'CIE xyY': ('x', 'y', 'Y'),
'CIE Lab': ('a', 'b', '$L^*$'),
'CIE Luv': ('$u^\prime$', '$v^\prime$', '$L^*$'),
'CIE UCS': ('U', 'V', 'W'),
'CIE UVW': ('U', 'V', 'W'),
'IPT': ('P', 'T', 'I')}
"""
Reference colourspaces to labels mapping.
REFERENCE_COLOURSPACES_TO_LABELS : dict
**{'CIE XYZ', 'CIE xyY', 'CIE Lab', 'CIE Luv', 'CIE UCS', 'CIE UVW',
'IPT'}**
"""
[docs]def nadir_grid(limits=None, segments=10, labels=None, axes=None, **kwargs):
"""
Returns a grid on *xy* plane made of quad geometric elements and its
associated faces and edges colours. Ticks and labels are added to the
given axes accordingly to the extended grid settings.
Parameters
----------
limits : array_like, optional
Extended grid limits.
segments : int, optional
Edge segments count for the extended grid.
labels : array_like, optional
Axis labels.
axes : matplotlib.axes.Axes, optional
Axes to add the grid.
\*\*kwargs : \*\*
**{'grid_face_colours', 'grid_edge_colours', 'grid_face_alpha',
'grid_edge_alpha', 'x_axis_colour', 'y_axis_colour', 'x_ticks_colour',
'y_ticks_colour', 'x_label_colour', 'y_label_colour',
'ticks_and_label_location'}**,
Arguments for the nadir grid such as ``{'grid_face_colours':
(0.25, 0.25, 0.25), 'grid_edge_colours': (0.50, 0.50, 0.50),
'grid_face_alpha': 0.1, 'grid_edge_alpha': 0.5, 'x_axis_colour':
(0.0, 0.0, 0.0, 1.0), 'y_axis_colour': (0.0, 0.0, 0.0, 1.0),
'x_ticks_colour': (0.0, 0.0, 0.0, 0.85), 'y_ticks_colour':
(0.0, 0.0, 0.0, 0.85), 'x_label_colour': (0.0, 0.0, 0.0, 0.85),
'y_label_colour': (0.0, 0.0, 0.0, 0.85), 'ticks_and_label_location':
('-x', '-y')}``
Returns
-------
tuple
Grid quads, faces colours, edges colours.
Examples
--------
>>> c = 'Rec. 709'
>>> RGB_scatter_plot(c) # doctest: +SKIP
True
"""
if limits is None:
limits = np.array([[-1, 1], [-1, 1]])
if labels is None:
labels = ('x', 'y')
extent = np.max(np.abs(limits[..., 1] - limits[..., 0]))
settings = Structure(
**{'grid_face_colours': (0.25, 0.25, 0.25),
'grid_edge_colours': (0.50, 0.50, 0.50),
'grid_face_alpha': 0.1,
'grid_edge_alpha': 0.5,
'x_axis_colour': (0.0, 0.0, 0.0, 1.0),
'y_axis_colour': (0.0, 0.0, 0.0, 1.0),
'x_ticks_colour': (0.0, 0.0, 0.0, 0.85),
'y_ticks_colour': (0.0, 0.0, 0.0, 0.85),
'x_label_colour': (0.0, 0.0, 0.0, 0.85),
'y_label_colour': (0.0, 0.0, 0.0, 0.85),
'ticks_and_label_location': ('-x', '-y')})
settings.update(**kwargs)
# Outer grid.
quads_g = grid(origin=(-extent / 2, -extent / 2),
width=extent,
height=extent,
height_segments=segments,
width_segments=segments)
RGB_g = np.ones((quads_g.shape[0], quads_g.shape[-1]))
RGB_gf = RGB_g * settings.grid_face_colours
RGB_gf = np.hstack((RGB_gf,
np.full((RGB_gf.shape[0], 1),
settings.grid_face_alpha)))
RGB_ge = RGB_g * settings.grid_edge_colours
RGB_ge = np.hstack((RGB_ge,
np.full((RGB_ge.shape[0], 1),
settings.grid_edge_alpha)))
# Inner grid.
quads_gs = grid(origin=(-extent / 2, -extent / 2),
width=extent,
height=extent,
height_segments=segments * 2,
width_segments=segments * 2)
RGB_gs = np.ones((quads_gs.shape[0], quads_gs.shape[-1]))
RGB_gsf = RGB_gs * 0
RGB_gsf = np.hstack((RGB_gsf, np.full((RGB_gsf.shape[0], 1), 0)))
RGB_gse = np.clip(RGB_gs *
settings.grid_edge_colours * 1.5, 0, 1)
RGB_gse = np.hstack((RGB_gse,
np.full((RGB_gse.shape[0], 1),
settings.grid_edge_alpha / 2)))
# Axis.
thickness = extent / 1000
quad_x = grid(origin=(limits[0, 0], -thickness / 2),
width=extent,
height=thickness)
RGB_x = np.ones((quad_x.shape[0], quad_x.shape[-1] + 1))
RGB_x = RGB_x * settings.x_axis_colour
quad_y = grid(origin=(-thickness / 2, limits[1, 0]),
width=thickness,
height=extent)
RGB_y = np.ones((quad_y.shape[0], quad_y.shape[-1] + 1))
RGB_y = RGB_y * settings.y_axis_colour
# Ticks.
x_s = 1 if '+x' in settings.ticks_and_label_location else -1
y_s = 1 if '+y' in settings.ticks_and_label_location else -1
for i, axis in enumerate('xy'):
h_a = 'center' if axis == 'x' else 'left' if x_s == 1 else 'right'
v_a = 'center'
ticks = list(sorted(set(quads_g[..., 0, i])))
ticks += [ticks[-1] + ticks[-1] - ticks[-2]]
for tick in ticks:
x = (limits[1, 1 if x_s == 1 else 0] + (x_s * extent / 25)
if i else tick)
y = (tick if i else
limits[0, 1 if y_s == 1 else 0] + (y_s * extent / 25))
tick = int(tick) if float(tick).is_integer() else tick
c = settings['{0}_ticks_colour'.format(axis)]
axes.text(x, y, 0, tick, 'x',
horizontalalignment=h_a,
verticalalignment=v_a,
color=c,
clip_on=True)
# Labels.
for i, axis in enumerate('xy'):
h_a = 'center' if axis == 'x' else 'left' if x_s == 1 else 'right'
v_a = 'center'
x = (limits[1, 1 if x_s == 1 else 0] + (x_s * extent / 10)
if i else 0)
y = (0 if i else
limits[0, 1 if y_s == 1 else 0] + (y_s * extent / 10))
c = settings['{0}_label_colour'.format(axis)]
axes.text(x, y, 0, labels[i], 'x',
horizontalalignment=h_a,
verticalalignment=v_a,
color=c,
size=20,
clip_on=True)
quads = np.vstack((quads_g, quads_gs, quad_x, quad_y))
RGB_f = np.vstack((RGB_gf, RGB_gsf, RGB_x, RGB_y))
RGB_e = np.vstack((RGB_ge, RGB_gse, RGB_x, RGB_y))
return quads, RGB_f, RGB_e
[docs]def XYZ_to_reference_colourspace(XYZ,
illuminant,
reference_colourspace):
"""
Converts from *CIE XYZ* tristimulus values to given reference colourspace.
Parameters
----------
XYZ : array_like
*CIE XYZ* tristimulus values.
illuminant : array_like
*CIE XYZ* tristimulus values *illuminant* *xy* chromaticity
coordinates.
reference_colourspace : unicode
**{'CIE XYZ', 'CIE xyY', 'CIE xy', 'CIE Lab', 'CIE Luv', 'CIE Luv uv',
'CIE UCS', 'CIE UCS uv', 'CIE UVW', 'IPT'}**,
Reference colourspace to convert the *CIE XYZ* tristimulus values to.
Returns
-------
ndarray
Reference colourspace values.
Examples
--------
>>> import numpy as np
>>> XYZ = np.array([0.07049534, 0.10080000, 0.09558313])
>>> W = np.array([0.34567, 0.35850])
>>> XYZ_to_reference_colourspace( # doctest: +ELLIPSIS
... XYZ, W, 'CIE XYZ')
array([ 0.0704953..., 0.1008 , 0.0955831...])
>>> XYZ_to_reference_colourspace( # doctest: +ELLIPSIS
... XYZ, W, 'CIE xyY')
array([ 0.2641477..., 0.3777000..., 0.1008 ])
>>> XYZ_to_reference_colourspace( # doctest: +ELLIPSIS
... XYZ, W, 'CIE xy')
array([ 0.2641477..., 0.3777000...])
>>> XYZ_to_reference_colourspace( # doctest: +ELLIPSIS
... XYZ, W, 'CIE Lab')
array([-23.6230288..., -4.4141703..., 37.9856291...])
>>> XYZ_to_reference_colourspace( # doctest: +ELLIPSIS
... XYZ, W, 'CIE LCHab')
array([ 24.0319036..., 190.5841597..., 37.9856291...])
>>> XYZ_to_reference_colourspace( # doctest: +ELLIPSIS
... XYZ, W, 'CIE Luv')
array([-28.7922944..., -1.3558195..., 37.9856291...])
>>> XYZ_to_reference_colourspace( # doctest: +ELLIPSIS
... XYZ, W, 'CIE Luv uv')
array([ 0.1508531..., 0.4853297...])
>>> XYZ_to_reference_colourspace( # doctest: +ELLIPSIS
... XYZ, W, 'CIE LCHuv')
array([ 28.82419932, 182.69604747, 37.9856291 ])
>>> XYZ_to_reference_colourspace( # doctest: +ELLIPSIS
... XYZ, W, 'CIE UCS uv')
array([ 0.1508531..., 0.32355314...])
>>> XYZ_to_reference_colourspace( # doctest: +ELLIPSIS
... XYZ, W, 'CIE UVW')
array([-28.0483277..., -0.8805242..., 37.0041149...])
>>> XYZ_to_reference_colourspace( # doctest: +ELLIPSIS
... XYZ, W, 'IPT')
array([-0.1111479..., 0.0159474..., 0.3657112...])
"""
value = None
if reference_colourspace == 'CIE XYZ':
value = XYZ
if reference_colourspace == 'CIE xyY':
value = XYZ_to_xyY(XYZ, illuminant)
if reference_colourspace == 'CIE xy': # Used for Chromaticity Diagram.
value = XYZ_to_xy(XYZ, illuminant)
if reference_colourspace == 'CIE Lab':
L, a, b = tsplit(XYZ_to_Lab(XYZ, illuminant))
value = tstack((a, b, L))
if reference_colourspace == 'CIE LCHab':
L, CH, ab = tsplit(Lab_to_LCHab(XYZ_to_Lab(XYZ, illuminant)))
value = tstack((CH, ab, L))
if reference_colourspace == 'CIE Luv':
L, u, v = tsplit(XYZ_to_Luv(XYZ, illuminant))
value = tstack((u, v, L))
if reference_colourspace == 'CIE Luv uv': # Used for Chromaticity Diagram.
u, v = tsplit(Luv_to_uv(XYZ_to_Luv(XYZ, illuminant), illuminant))
value = tstack((u, v))
if reference_colourspace == 'CIE LCHuv':
L, CH, uv = tsplit(Luv_to_LCHuv(XYZ_to_Luv(XYZ, illuminant)))
value = tstack((CH, uv, L))
if reference_colourspace == 'CIE UCS':
value = XYZ_to_UCS(XYZ)
if reference_colourspace == 'CIE UCS uv': # Used for Chromaticity Diagram.
u, v = tsplit(UCS_to_uv(XYZ_to_UCS(XYZ)))
value = tstack((u, v))
if reference_colourspace == 'CIE UVW':
value = XYZ_to_UVW(XYZ * 100, illuminant)
if reference_colourspace == 'IPT':
I, P, T = tsplit(XYZ_to_IPT(XYZ))
value = tstack((P, T, I))
if value is None:
raise ValueError(
('"{0}" not found in reference colourspace models: '
'"{1}".').format(reference_colourspace,
', '.join(REFERENCE_COLOURSPACES)))
return value
[docs]def RGB_identity_cube(plane=None,
width_segments=16,
height_segments=16,
depth_segments=16):
"""
Returns an *RGB* identity cube made of quad geometric elements and its
associated *RGB* colours.
Parameters
----------
plane : array_like, optional
Any combination of **{'+x', '-x', '+y', '-y', '+z', '-z'}**,
Included grids in the cube construction.
width_segments: int, optional
Cube segments, quad counts along the width.
height_segments: int, optional
Cube segments, quad counts along the height.
depth_segments: int, optional
Cube segments, quad counts along the depth.
Returns
-------
tuple
Cube quads, *RGB* colours.
Examples
--------
>>> vertices, RGB = RGB_identity_cube(None, 1, 1, 1)
>>> vertices
array([[[ 0., 0., 0.],
[ 1., 0., 0.],
[ 1., 1., 0.],
[ 0., 1., 0.]],
<BLANKLINE>
[[ 0., 0., 1.],
[ 1., 0., 1.],
[ 1., 1., 1.],
[ 0., 1., 1.]],
<BLANKLINE>
[[ 0., 0., 0.],
[ 1., 0., 0.],
[ 1., 0., 1.],
[ 0., 0., 1.]],
<BLANKLINE>
[[ 0., 1., 0.],
[ 1., 1., 0.],
[ 1., 1., 1.],
[ 0., 1., 1.]],
<BLANKLINE>
[[ 0., 0., 0.],
[ 0., 1., 0.],
[ 0., 1., 1.],
[ 0., 0., 1.]],
<BLANKLINE>
[[ 1., 0., 0.],
[ 1., 1., 0.],
[ 1., 1., 1.],
[ 1., 0., 1.]]])
>>> RGB
array([[ 0.5, 0.5, 0. ],
[ 0.5, 0.5, 1. ],
[ 0.5, 0. , 0.5],
[ 0.5, 1. , 0.5],
[ 0. , 0.5, 0.5],
[ 1. , 0.5, 0.5]])
"""
quads = cube(plane=plane,
width=1,
height=1,
depth=1,
width_segments=width_segments,
height_segments=height_segments,
depth_segments=depth_segments)
RGB = np.average(quads, axis=-2)
return quads, RGB
[docs]def RGB_colourspaces_gamuts_plot(colourspaces=None,
reference_colourspace='CIE xyY',
segments=8,
grid=True,
grid_segments=10,
spectral_locus=False,
spectral_locus_colour=None,
cmfs='CIE 1931 2 Degree Standard Observer',
**kwargs):
"""
Plots given *RGB* colourspaces gamuts in given reference colourspace.
Parameters
----------
colourspaces : array_like, optional
*RGB* colourspaces to plot the gamuts.
reference_colourspace : unicode, optional
**{'CIE XYZ', 'CIE xyY', 'CIE Lab', 'CIE Luv', 'CIE UCS', 'CIE UVW',
'IPT'}**,
Reference colourspace to plot the gamuts into.
segments : int, optional
Edge segments count for each *RGB* colourspace cubes.
grid : bool, optional
Display a grid at the bottom of the *RGB* colourspace cubes.
grid_segments : bool, optional
Edge segments count for the grid.
spectral_locus : bool, optional
Is spectral locus line plotted.
spectral_locus_colour : array_like, optional
Spectral locus line colour.
cmfs : unicode, optional
Standard observer colour matching functions used for spectral locus.
\*\*kwargs : \*\*
**{'face_colours', 'edge_colours', 'edge_alpha', 'face_alpha'}**,
Arguments for each given colourspace where each key has an array_like
value such as: ``{ 'face_colours': (None, (0.5, 0.5, 1.0)),
'edge_colours': (None, (0.5, 0.5, 1.0)), 'edge_alpha': (0.5, 1.0),
'face_alpha': (0.0, 1.0)}``
**{'grid_face_colours', 'grid_edge_colours', 'grid_face_alpha',
'grid_edge_alpha', 'x_axis_colour', 'y_axis_colour', 'x_ticks_colour',
'y_ticks_colour', 'x_label_colour', 'y_label_colour',
'ticks_and_label_location'}**,
Arguments for the nadir grid such as ``{'grid_face_colours':
(0.25, 0.25, 0.25), 'grid_edge_colours': (0.50, 0.50, 0.50),
'grid_face_alpha': 0.1, 'grid_edge_alpha': 0.5, 'x_axis_colour':
(0.0, 0.0, 0.0, 1.0), 'y_axis_colour': (0.0, 0.0, 0.0, 1.0),
'x_ticks_colour': (0.0, 0.0, 0.0, 0.85), 'y_ticks_colour':
(0.0, 0.0, 0.0, 0.85), 'x_label_colour': (0.0, 0.0, 0.0, 0.85),
'y_label_colour': (0.0, 0.0, 0.0, 0.85), 'ticks_and_label_location':
('-x', '-y')}``
Returns
-------
bool
Definition success.
Examples
--------
>>> c = ['Rec. 709', 'ACEScg', 'S-Gamut']
>>> RGB_colourspaces_gamuts_plot(c) # doctest: +SKIP
True
"""
if colourspaces is None:
colourspaces = ('Rec. 709', 'ACEScg')
count_c = len(colourspaces)
settings = Structure(
**{'face_colours': [None] * count_c,
'edge_colours': [None] * count_c,
'face_alpha': [1] * count_c,
'edge_alpha': [1] * count_c,
'title': '{0} - {1} Reference Colourspace'.format(
', '.join(colourspaces), reference_colourspace)})
settings.update(kwargs)
figure = matplotlib.pyplot.figure()
axes = figure.add_subplot(111, projection='3d')
illuminant = DEFAULT_PLOTTING_ILLUMINANT
points = np.zeros((4, 3))
if spectral_locus:
cmfs = get_cmfs(cmfs)
XYZ = cmfs.values
points = XYZ_to_reference_colourspace(XYZ,
illuminant,
reference_colourspace)
points[np.isnan(points)] = 0
c = ((0.0, 0.0, 0.0, 0.5)
if spectral_locus_colour is None else
spectral_locus_colour)
pylab.plot(points[..., 0],
points[..., 1],
points[..., 2],
color=c,
linewidth=2,
zorder=1)
pylab.plot((points[-1][0], points[0][0]),
(points[-1][1], points[0][1]),
(points[-1][2], points[0][2]),
color=c,
linewidth=2,
zorder=1)
quads, RGB_f, RGB_e = [], [], []
for i, colourspace in enumerate(colourspaces):
colourspace = get_RGB_colourspace(colourspace)
quads_c, RGB = RGB_identity_cube(width_segments=segments,
height_segments=segments,
depth_segments=segments)
XYZ = RGB_to_XYZ(
quads_c,
colourspace.whitepoint,
colourspace.whitepoint,
colourspace.RGB_to_XYZ_matrix)
quads.extend(XYZ_to_reference_colourspace(XYZ,
colourspace.whitepoint,
reference_colourspace))
if settings.face_colours[i] is not None:
RGB = np.ones(RGB.shape) * settings.face_colours[i]
RGB_f.extend(np.hstack(
(RGB, np.full((RGB.shape[0], 1), settings.face_alpha[i]))))
if settings.edge_colours[i] is not None:
RGB = np.ones(RGB.shape) * settings.edge_colours[i]
RGB_e.extend(np.hstack(
(RGB, np.full((RGB.shape[0], 1), settings.edge_alpha[i]))))
quads = np.asarray(quads)
quads[np.isnan(quads)] = 0
if quads.size != 0:
for i, axis in enumerate('xyz'):
min_a = np.min(np.vstack((quads[..., i], points[..., i])))
max_a = np.max(np.vstack((quads[..., i], points[..., i])))
getattr(axes, 'set_{}lim'.format(axis))((min_a, max_a))
labels = REFERENCE_COLOURSPACES_TO_LABELS[reference_colourspace]
for i, axis in enumerate('xyz'):
getattr(axes, 'set_{}label'.format(axis))(labels[i])
if grid:
if reference_colourspace == 'CIE Lab':
limits = np.array([[-450, 450], [-450, 450]])
elif reference_colourspace == 'CIE Luv':
limits = np.array([[-650, 650], [-650, 650]])
elif reference_colourspace == 'CIE UVW':
limits = np.array([[-850, 850], [-850, 850]])
else:
limits = np.array([[-1.5, 1.5], [-1.5, 1.5]])
quads_g, RGB_gf, RGB_ge = nadir_grid(
limits, grid_segments, labels, axes, **settings)
quads = np.vstack((quads_g, quads))
RGB_f = np.vstack((RGB_gf, RGB_f))
RGB_e = np.vstack((RGB_ge, RGB_e))
collection = Poly3DCollection(quads)
collection.set_facecolors(RGB_f)
collection.set_edgecolors(RGB_e)
axes.add_collection3d(collection)
settings.update({
'camera_aspect': 'equal',
'no_axes3d': True})
settings.update(kwargs)
camera(**settings)
decorate(**settings)
return display(**settings)
[docs]def RGB_scatter_plot(RGB,
colourspace,
reference_colourspace='CIE xyY',
colourspaces=None,
segments=8,
grid=True,
grid_segments=10,
spectral_locus=False,
spectral_locus_colour=None,
points_size=12,
cmfs='CIE 1931 2 Degree Standard Observer',
**kwargs):
"""
Plots given *RGB* colourspace array in a scatter plot.
Parameters
----------
RGB : array_like
*RGB* colourspace array.
colourspace : RGB_Colourspace
*RGB* colourspace of the *RGB* array.
reference_colourspace : unicode, optional
**{'CIE XYZ', 'CIE xyY', 'CIE Lab', 'CIE Luv', 'CIE UCS', 'CIE UVW',
'IPT'}**,
Reference colourspace for colour conversion.
colourspaces : array_like, optional
*RGB* colourspaces to plot the gamuts.
segments : int, optional
Edge segments count for each *RGB* colourspace cubes.
grid : bool, optional
Display a grid at the bottom of the *RGB* colourspace cubes.
grid_segments : bool, optional
Edge segments count for the grid.
spectral_locus : bool, optional
Is spectral locus line plotted.
spectral_locus_colour : array_like, optional
Spectral locus line colour.
points_size : numeric, optional
Scatter points size.
cmfs : unicode, optional
Standard observer colour matching functions used for spectral locus.
\*\*kwargs : \*\*
**{'face_colours', 'edge_colours', 'edge_alpha', 'face_alpha'}**,
Arguments for each given colourspace where each key has an array_like
value such as: ``{ 'face_colours': (None, (0.5, 0.5, 1.0)),
'edge_colours': (None, (0.5, 0.5, 1.0)), 'edge_alpha': (0.5, 1.0),
'face_alpha': (0.0, 1.0)}``
**{'grid_face_colours', 'grid_edge_colours', 'grid_face_alpha',
'grid_edge_alpha', 'x_axis_colour', 'y_axis_colour', 'x_ticks_colour',
'y_ticks_colour', 'x_label_colour', 'y_label_colour',
'ticks_and_label_location'}**,
Arguments for the nadir grid such as ``{'grid_face_colours':
(0.25, 0.25, 0.25), 'grid_edge_colours': (0.50, 0.50, 0.50),
'grid_face_alpha': 0.1, 'grid_edge_alpha': 0.5, 'x_axis_colour':
(0.0, 0.0, 0.0, 1.0), 'y_axis_colour': (0.0, 0.0, 0.0, 1.0),
'x_ticks_colour': (0.0, 0.0, 0.0, 0.85), 'y_ticks_colour':
(0.0, 0.0, 0.0, 0.85), 'x_label_colour': (0.0, 0.0, 0.0, 0.85),
'y_label_colour': (0.0, 0.0, 0.0, 0.85), 'ticks_and_label_location':
('-x', '-y')}``
Returns
-------
bool
Definition success.
Examples
--------
>>> c = 'Rec. 709'
>>> RGB_scatter_plot(c) # doctest: +SKIP
True
"""
colourspace = get_RGB_colourspace(colourspace)
if colourspaces is None:
colourspaces = (colourspace.name,)
count_c = len(colourspaces)
settings = Structure(
**{'face_colours': [None] * count_c,
'edge_colours': [(0.25, 0.25, 0.25)] * count_c,
'face_alpha': [0.0] * count_c,
'edge_alpha': [0.1] * count_c,
'standalone': False})
settings.update(kwargs)
RGB_colourspaces_gamuts_plot(
colourspaces=colourspaces,
reference_colourspace=reference_colourspace,
segments=segments,
grid=grid,
grid_segments=grid_segments,
spectral_locus=spectral_locus,
spectral_locus_colour=spectral_locus_colour,
cmfs=cmfs,
**settings)
XYZ = RGB_to_XYZ(
RGB,
colourspace.whitepoint,
colourspace.whitepoint,
colourspace.RGB_to_XYZ_matrix)
points = XYZ_to_reference_colourspace(XYZ,
colourspace.whitepoint,
reference_colourspace)
axes = matplotlib.pyplot.gca()
axes.scatter(points[..., 0],
points[..., 1],
points[..., 2],
color=np.reshape(RGB, (-1, 3)),
s=points_size)
settings.update({'standalone': True})
settings.update(kwargs)
camera(**settings)
decorate(**settings)
return display(**settings)
Colour 0.3