#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
CIE Chromaticity Diagrams Plotting
==================================
Defines the *CIE* chromaticity diagrams plotting objects:
- :func:`CIE_1931_chromaticity_diagram_plot`
- :func:`CIE_1960_UCS_chromaticity_diagram_plot`
- :func:`CIE_1976_UCS_chromaticity_diagram_plot`
- :func:`spds_CIE_1931_chromaticity_diagram_plot`
- :func:`spds_CIE_1960_UCS_chromaticity_diagram_plot`
- :func:`spds_CIE_1976_UCS_chromaticity_diagram_plot`
"""
from __future__ import division
import bisect
import os
import matplotlib
import matplotlib.image
import matplotlib.path
import matplotlib.pyplot
import numpy as np
import pylab
from colour.colorimetry import spectral_to_XYZ
from colour.models import (
Luv_to_uv,
Luv_uv_to_xy,
UCS_to_uv,
UCS_uv_to_xy,
XYZ_to_Luv,
XYZ_to_UCS,
XYZ_to_sRGB,
XYZ_to_xy,
xy_to_XYZ)
from colour.plotting import (
DEFAULT_FIGURE_WIDTH,
DEFAULT_PLOTTING_ILLUMINANT,
PLOTTING_RESOURCES_DIRECTORY,
canvas,
decorate,
boundaries,
display,
get_cmfs)
from colour.utilities import is_scipy_installed, normalise, 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__ = ['CIE_1931_chromaticity_diagram_colours_plot',
'CIE_1931_chromaticity_diagram_plot',
'CIE_1960_UCS_chromaticity_diagram_colours_plot',
'CIE_1960_UCS_chromaticity_diagram_plot',
'CIE_1976_UCS_chromaticity_diagram_colours_plot',
'CIE_1976_UCS_chromaticity_diagram_plot',
'spds_CIE_1931_chromaticity_diagram_plot',
'spds_CIE_1960_UCS_chromaticity_diagram_plot',
'spds_CIE_1976_UCS_chromaticity_diagram_plot']
[docs]def CIE_1931_chromaticity_diagram_colours_plot(
surface=1,
samples=4096,
cmfs='CIE 1931 2 Degree Standard Observer',
**kwargs):
"""
Plots the *CIE 1931 Chromaticity Diagram* colours.
Parameters
----------
surface : numeric, optional
Generated markers surface.
samples : numeric, optional
Samples count on one axis.
cmfs : unicode, optional
Standard observer colour matching functions used for diagram bounds.
\*\*kwargs : \*\*
Keywords arguments.
Returns
-------
bool
Definition success.
Examples
--------
>>> CIE_1931_chromaticity_diagram_colours_plot() # doctest: +SKIP
True
"""
if is_scipy_installed(raise_exception=True):
from scipy.spatial import Delaunay
settings = {'figure_size': (64, 64)}
settings.update(kwargs)
canvas(**settings)
cmfs = get_cmfs(cmfs)
illuminant = DEFAULT_PLOTTING_ILLUMINANT
triangulation = Delaunay(XYZ_to_xy(cmfs.values, illuminant),
qhull_options='QJ')
xx, yy = np.meshgrid(np.linspace(0, 1, samples),
np.linspace(0, 1, samples))
xy = tstack((xx, yy))
xy = xy[triangulation.find_simplex(xy) > 0]
XYZ = xy_to_XYZ(xy)
RGB = normalise(XYZ_to_sRGB(XYZ, illuminant), axis=-1)
x_dot, y_dot = tsplit(xy)
pylab.scatter(x_dot, y_dot, color=RGB, s=surface)
settings.update({
'x_ticker': False,
'y_ticker': False,
'bounding_box': (0, 1, 0, 1),
'bbox_inches': 'tight',
'pad_inches': 0})
settings.update(kwargs)
ax = matplotlib.pyplot.gca()
matplotlib.pyplot.setp(ax, frame_on=False)
boundaries(**settings)
decorate(**settings)
return display(**settings)
[docs]def CIE_1931_chromaticity_diagram_plot(
cmfs='CIE 1931 2 Degree Standard Observer', **kwargs):
"""
Plots the *CIE 1931 Chromaticity Diagram*.
Parameters
----------
cmfs : unicode, optional
Standard observer colour matching functions used for diagram bounds.
\*\*kwargs : \*\*
Keywords arguments.
Returns
-------
bool
Definition success.
Examples
--------
>>> CIE_1931_chromaticity_diagram_plot() # doctest: +SKIP
True
"""
settings = {'figure_size': (DEFAULT_FIGURE_WIDTH, DEFAULT_FIGURE_WIDTH)}
settings.update(kwargs)
canvas(**settings)
cmfs = get_cmfs(cmfs)
illuminant = DEFAULT_PLOTTING_ILLUMINANT
image = matplotlib.image.imread(
os.path.join(PLOTTING_RESOURCES_DIRECTORY,
'CIE_1931_Chromaticity_Diagram_{0}.png'.format(
cmfs.name.replace(' ', '_'))))
pylab.imshow(image, interpolation=None, extent=(0, 1, 0, 1))
labels = (
390, 460, 470, 480, 490, 500, 510, 520, 540, 560, 580, 600, 620, 700)
wavelengths = cmfs.wavelengths
equal_energy = np.array([1 / 3] * 2)
xy = XYZ_to_xy(cmfs.values, illuminant)
wavelengths_chromaticity_coordinates = dict(tuple(zip(wavelengths, xy)))
pylab.plot(xy[..., 0], xy[..., 1], color='black', linewidth=2)
pylab.plot((xy[-1][0], xy[0][0]),
(xy[-1][1], xy[0][1]),
color='black',
linewidth=2)
for label in labels:
x, y = wavelengths_chromaticity_coordinates.get(label)
pylab.plot(x, y, 'o', color='black', linewidth=2)
index = bisect.bisect(wavelengths, label)
left = wavelengths[index - 1] if index >= 0 else wavelengths[index]
right = (wavelengths[index]
if index < len(wavelengths) else
wavelengths[-1])
dx = (wavelengths_chromaticity_coordinates.get(right)[0] -
wavelengths_chromaticity_coordinates.get(left)[0])
dy = (wavelengths_chromaticity_coordinates.get(right)[1] -
wavelengths_chromaticity_coordinates.get(left)[1])
norme = lambda x: x / np.linalg.norm(x)
xy = np.array([x, y])
direction = np.array([-dy, dx])
normal = (np.array([-dy, dx])
if np.dot(norme(xy - equal_energy),
norme(direction)) > 0 else
np.array([dy, -dx]))
normal = norme(normal)
normal /= 25
pylab.plot((x, x + normal[0] * 0.75),
(y, y + normal[1] * 0.75),
color='black',
linewidth=1.5)
pylab.text(x + normal[0],
y + normal[1],
label,
clip_on=True,
ha='left' if normal[0] >= 0 else 'right',
va='center',
fontdict={'size': 'small'})
ticks = np.arange(-10, 10, 0.1)
pylab.xticks(ticks)
pylab.yticks(ticks)
settings.update({
'title': 'CIE 1931 Chromaticity Diagram - {0}'.format(cmfs.title),
'x_label': 'CIE x',
'y_label': 'CIE y',
'grid': True,
'bounding_box': (0, 1, 0, 1),
'bbox_inches': 'tight',
'pad_inches': 0})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
[docs]def CIE_1960_UCS_chromaticity_diagram_colours_plot(
surface=1,
samples=4096,
cmfs='CIE 1931 2 Degree Standard Observer',
**kwargs):
"""
Plots the *CIE 1960 UCS Chromaticity Diagram* colours.
Parameters
----------
surface : numeric, optional
Generated markers surface.
samples : numeric, optional
Samples count on one axis.
cmfs : unicode, optional
Standard observer colour matching functions used for diagram bounds.
\*\*kwargs : \*\*
Keywords arguments.
Returns
-------
bool
Definition success.
Examples
--------
>>> CIE_1960_UCS_chromaticity_diagram_colours_plot() # doctest: +SKIP
True
"""
if is_scipy_installed(raise_exception=True):
from scipy.spatial import Delaunay
settings = {'figure_size': (64, 64)}
settings.update(kwargs)
canvas(**settings)
cmfs = get_cmfs(cmfs)
illuminant = DEFAULT_PLOTTING_ILLUMINANT
triangulation = Delaunay(UCS_to_uv(XYZ_to_UCS(cmfs.values)),
qhull_options='QJ')
xx, yy = np.meshgrid(np.linspace(0, 1, samples),
np.linspace(0, 1, samples))
xy = tstack((xx, yy))
xy = xy[triangulation.find_simplex(xy) > 0]
XYZ = xy_to_XYZ(UCS_uv_to_xy(xy))
RGB = normalise(XYZ_to_sRGB(XYZ, illuminant), axis=-1)
x_dot, y_dot = tsplit(xy)
pylab.scatter(x_dot, y_dot, color=RGB, s=surface)
settings.update({
'x_ticker': False,
'y_ticker': False,
'bounding_box': (0, 1, 0, 1),
'bbox_inches': 'tight',
'pad_inches': 0})
settings.update(kwargs)
ax = matplotlib.pyplot.gca()
matplotlib.pyplot.setp(ax, frame_on=False)
boundaries(**settings)
decorate(**settings)
return display(**settings)
[docs]def CIE_1960_UCS_chromaticity_diagram_plot(
cmfs='CIE 1931 2 Degree Standard Observer', **kwargs):
"""
Plots the *CIE 1960 UCS Chromaticity Diagram*.
Parameters
----------
cmfs : unicode, optional
Standard observer colour matching functions used for diagram bounds.
\*\*kwargs : \*\*
Keywords arguments.
Returns
-------
bool
Definition success.
Examples
--------
>>> CIE_1960_UCS_chromaticity_diagram_plot() # doctest: +SKIP
True
"""
settings = {'figure_size': (DEFAULT_FIGURE_WIDTH, DEFAULT_FIGURE_WIDTH)}
settings.update(kwargs)
canvas(**settings)
cmfs = get_cmfs(cmfs)
image = matplotlib.image.imread(
os.path.join(PLOTTING_RESOURCES_DIRECTORY,
'CIE_1960_UCS_Chromaticity_Diagram_{0}.png'.format(
cmfs.name.replace(' ', '_'))))
pylab.imshow(image, interpolation=None, extent=(0, 1, 0, 1))
labels = (420, 430, 440, 450, 460, 470, 480, 490, 500, 510, 520, 530,
540, 550, 560, 570, 580, 590, 600, 610, 620, 630, 640, 680)
wavelengths = cmfs.wavelengths
equal_energy = np.array([1 / 3] * 2)
uv = UCS_to_uv(XYZ_to_UCS(cmfs.values))
wavelengths_chromaticity_coordinates = dict(tuple(zip(wavelengths, uv)))
pylab.plot(uv[..., 0], uv[..., 1], color='black', linewidth=2)
pylab.plot((uv[-1][0], uv[0][0]),
(uv[-1][1], uv[0][1]),
color='black',
linewidth=2)
for label in labels:
u, v = wavelengths_chromaticity_coordinates.get(label)
pylab.plot(u, v, 'o', color='black', linewidth=2)
index = bisect.bisect(wavelengths, label)
left = wavelengths[index - 1] if index >= 0 else wavelengths[index]
right = (wavelengths[index]
if index < len(wavelengths) else
wavelengths[-1])
dx = (wavelengths_chromaticity_coordinates.get(right)[0] -
wavelengths_chromaticity_coordinates.get(left)[0])
dy = (wavelengths_chromaticity_coordinates.get(right)[1] -
wavelengths_chromaticity_coordinates.get(left)[1])
norme = lambda x: x / np.linalg.norm(x)
uv = np.array([u, v])
direction = np.array([-dy, dx])
normal = (np.array([-dy, dx])
if np.dot(norme(uv - equal_energy),
norme(direction)) > 0 else
np.array([dy, -dx]))
normal = norme(normal)
normal /= 25
pylab.plot((u, u + normal[0] * 0.75),
(v, v + normal[1] * 0.75),
color='black',
linewidth=1.5)
pylab.text(u + normal[0],
v + normal[1],
label,
clip_on=True,
ha='left' if normal[0] >= 0 else 'right',
va='center',
fontdict={'size': 'small'})
ticks = np.arange(-10, 10, 0.1)
pylab.xticks(ticks)
pylab.yticks(ticks)
settings.update({
'title': 'CIE 1960 UCS Chromaticity Diagram - {0}'.format(cmfs.title),
'x_label': 'CIE u',
'y_label': 'CIE v',
'grid': True,
'bounding_box': (0, 1, 0, 1),
'bbox_inches': 'tight',
'pad_inches': 0})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
[docs]def CIE_1976_UCS_chromaticity_diagram_colours_plot(
surface=1,
samples=4096,
cmfs='CIE 1931 2 Degree Standard Observer',
**kwargs):
"""
Plots the *CIE 1976 UCS Chromaticity Diagram* colours.
Parameters
----------
surface : numeric, optional
Generated markers surface.
samples : numeric, optional
Samples count on one axis.
cmfs : unicode, optional
Standard observer colour matching functions used for diagram bounds.
\*\*kwargs : \*\*
Keywords arguments.
Returns
-------
bool
Definition success.
Examples
--------
>>> CIE_1976_UCS_chromaticity_diagram_colours_plot() # doctest: +SKIP
True
"""
if is_scipy_installed(raise_exception=True):
from scipy.spatial import Delaunay
settings = {'figure_size': (64, 64)}
settings.update(kwargs)
canvas(**settings)
cmfs = get_cmfs(cmfs)
illuminant = DEFAULT_PLOTTING_ILLUMINANT
triangulation = Delaunay(
Luv_to_uv(XYZ_to_Luv(cmfs.values, illuminant), illuminant),
qhull_options='QJ Qf')
xx, yy = np.meshgrid(np.linspace(0, 1, samples),
np.linspace(0, 1, samples))
xy = tstack((xx, yy))
xy = xy[triangulation.find_simplex(xy) > 0]
XYZ = xy_to_XYZ(Luv_uv_to_xy(xy))
RGB = normalise(XYZ_to_sRGB(XYZ, illuminant), axis=-1)
x_dot, y_dot = tsplit(xy)
pylab.scatter(x_dot, y_dot, color=RGB, s=surface)
settings.update({
'x_ticker': False,
'y_ticker': False,
'bounding_box': (0, 1, 0, 1),
'bbox_inches': 'tight',
'pad_inches': 0})
settings.update(kwargs)
ax = matplotlib.pyplot.gca()
matplotlib.pyplot.setp(ax, frame_on=False)
boundaries(**settings)
decorate(**settings)
return display(**settings)
[docs]def CIE_1976_UCS_chromaticity_diagram_plot(
cmfs='CIE 1931 2 Degree Standard Observer', **kwargs):
"""
Plots the *CIE 1976 UCS Chromaticity Diagram*.
Parameters
----------
cmfs : unicode, optional
Standard observer colour matching functions used for diagram bounds.
\*\*kwargs : \*\*
Keywords arguments.
Returns
-------
bool
Definition success.
Examples
--------
>>> CIE_1976_UCS_chromaticity_diagram_plot() # doctest: +SKIP
True
"""
settings = {'figure_size': (DEFAULT_FIGURE_WIDTH, DEFAULT_FIGURE_WIDTH)}
settings.update(kwargs)
canvas(**settings)
cmfs = get_cmfs(cmfs)
illuminant = DEFAULT_PLOTTING_ILLUMINANT
image = matplotlib.image.imread(
os.path.join(PLOTTING_RESOURCES_DIRECTORY,
'CIE_1976_UCS_Chromaticity_Diagram_{0}.png'.format(
cmfs.name.replace(' ', '_'))))
pylab.imshow(image, interpolation=None, extent=(0, 1, 0, 1))
labels = (420, 430, 440, 450, 460, 470, 480, 490, 500, 510, 520, 530,
540, 550, 560, 570, 580, 590, 600, 610, 620, 630, 640, 680)
wavelengths = cmfs.wavelengths
equal_energy = np.array([1 / 3] * 2)
uv = Luv_to_uv(XYZ_to_Luv(cmfs.values, illuminant), illuminant)
wavelengths_chromaticity_coordinates = dict(zip(wavelengths, uv))
pylab.plot(uv[..., 0], uv[..., 1], color='black', linewidth=2)
pylab.plot((uv[-1][0], uv[0][0]),
(uv[-1][1], uv[0][1]),
color='black',
linewidth=2)
for label in labels:
u, v = wavelengths_chromaticity_coordinates.get(label)
pylab.plot(u, v, 'o', color='black', linewidth=2)
index = bisect.bisect(wavelengths, label)
left = wavelengths[index - 1] if index >= 0 else wavelengths[index]
right = (wavelengths[index]
if index < len(wavelengths) else
wavelengths[-1])
dx = (wavelengths_chromaticity_coordinates.get(right)[0] -
wavelengths_chromaticity_coordinates.get(left)[0])
dy = (wavelengths_chromaticity_coordinates.get(right)[1] -
wavelengths_chromaticity_coordinates.get(left)[1])
norme = lambda x: x / np.linalg.norm(x)
uv = np.array([u, v])
direction = np.array([-dy, dx])
normal = (np.array([-dy, dx])
if np.dot(norme(uv - equal_energy),
norme(direction)) > 0 else
np.array([dy, -dx]))
normal = norme(normal)
normal /= 25
pylab.plot((u, u + normal[0] * 0.75),
(v, v + normal[1] * 0.75),
color='black',
linewidth=1.5)
pylab.text(u + normal[0],
v + normal[1],
label,
clip_on=True,
ha='left' if normal[0] >= 0 else 'right',
va='center',
fontdict={'size': 'small'})
ticks = np.arange(-10, 10, 0.1)
pylab.xticks(ticks)
pylab.yticks(ticks)
settings.update({
'title': 'CIE 1976 UCS Chromaticity Diagram - {0}'.format(cmfs.title),
'x_label': 'CIE u\'',
'y_label': 'CIE v\'',
'grid': True,
'bounding_box': (0, 1, 0, 1),
'bbox_inches': 'tight',
'pad_inches': 0})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
[docs]def spds_CIE_1931_chromaticity_diagram_plot(
spds,
cmfs='CIE 1931 2 Degree Standard Observer',
annotate=True,
**kwargs):
"""
Plots given spectral power distribution chromaticity coordinates into the
*CIE 1931 Chromaticity Diagram*.
Parameters
----------
spds : array_like, optional
Spectral power distributions to plot.
cmfs : unicode, optional
Standard observer colour matching functions used for diagram bounds.
annotate : bool
Should resulting chromaticity coordinates annotated with their
respective spectral power distribution names.
\*\*kwargs : \*\*
Keywords arguments.
Returns
-------
bool
Definition success.
Examples
--------
>>> from colour import ILLUMINANTS_RELATIVE_SPDS
>>> A = ILLUMINANTS_RELATIVE_SPDS['A']
>>> D65 = ILLUMINANTS_RELATIVE_SPDS['D65']
>>> spds_CIE_1931_chromaticity_diagram_plot([A, D65]) # doctest: +SKIP
True
"""
settings = {}
settings.update(kwargs)
settings.update({'standalone': False})
CIE_1931_chromaticity_diagram_plot(**settings)
cmfs = get_cmfs(cmfs)
cmfs_shape = cmfs.shape
for spd in spds:
spd = spd.clone().align(cmfs_shape)
XYZ = spectral_to_XYZ(spd) / 100
xy = XYZ_to_xy(XYZ)
pylab.plot(xy[0], xy[1], 'o', color='white')
if spd.name is not None and annotate:
pylab.annotate(spd.name,
xy=xy,
xytext=(50, 30),
textcoords='offset points',
arrowprops=dict(arrowstyle='->',
connectionstyle='arc3, rad=0.2'))
settings.update({
'x_tighten': True,
'y_tighten': True,
'limits': (-0.1, 0.9, -0.1, 0.9),
'standalone': True})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
[docs]def spds_CIE_1960_UCS_chromaticity_diagram_plot(
spds,
cmfs='CIE 1931 2 Degree Standard Observer',
annotate=True,
**kwargs):
"""
Plots given spectral power distribution chromaticity coordinates into the
*CIE 1960 UCS Chromaticity Diagram*.
Parameters
----------
spds : array_like, optional
Spectral power distributions to plot.
cmfs : unicode, optional
Standard observer colour matching functions used for diagram bounds.
annotate : bool
Should resulting chromaticity coordinates annotated with their
respective spectral power distribution names.
\*\*kwargs : \*\*
Keywords arguments.
Returns
-------
bool
Definition success.
Examples
--------
>>> from colour import ILLUMINANTS_RELATIVE_SPDS
>>> A = ILLUMINANTS_RELATIVE_SPDS['A']
>>> D65 = ILLUMINANTS_RELATIVE_SPDS['D65']
>>> spds_CIE_1960_UCS_chromaticity_diagram_plot([A, D65]) # doctest: +SKIP
True
"""
settings = {}
settings.update(kwargs)
settings.update({'standalone': False})
CIE_1960_UCS_chromaticity_diagram_plot(**settings)
cmfs = get_cmfs(cmfs)
cmfs_shape = cmfs.shape
for spd in spds:
spd = spd.clone().align(cmfs_shape)
XYZ = spectral_to_XYZ(spd) / 100
uv = UCS_to_uv(XYZ_to_UCS(XYZ))
pylab.plot(uv[0], uv[1], 'o', color='white')
if spd.name is not None and annotate:
pylab.annotate(spd.name,
xy=uv,
xytext=(50, 30),
textcoords='offset points',
arrowprops=dict(arrowstyle='->',
connectionstyle='arc3, rad=0.2'))
settings.update({
'x_tighten': True,
'y_tighten': True,
'limits': (-0.1, 0.7, -0.2, 0.6),
'standalone': True})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
[docs]def spds_CIE_1976_UCS_chromaticity_diagram_plot(
spds,
cmfs='CIE 1931 2 Degree Standard Observer',
annotate=True,
**kwargs):
"""
Plots given spectral power distribution chromaticity coordinates into the
*CIE 1976 UCS Chromaticity Diagram*.
Parameters
----------
spds : array_like, optional
Spectral power distributions to plot.
cmfs : unicode, optional
Standard observer colour matching functions used for diagram bounds.
annotate : bool
Should resulting chromaticity coordinates annotated with their
respective spectral power distribution names.
\*\*kwargs : \*\*
Keywords arguments.
Returns
-------
bool
Definition success.
Examples
--------
>>> from colour import ILLUMINANTS_RELATIVE_SPDS
>>> A = ILLUMINANTS_RELATIVE_SPDS['A']
>>> D65 = ILLUMINANTS_RELATIVE_SPDS['D65']
>>> spds_CIE_1976_UCS_chromaticity_diagram_plot([A, D65]) # doctest: +SKIP
True
"""
settings = {}
settings.update(kwargs)
settings.update({'standalone': False})
CIE_1976_UCS_chromaticity_diagram_plot(**settings)
cmfs = get_cmfs(cmfs)
cmfs_shape = cmfs.shape
for spd in spds:
spd = spd.clone().align(cmfs_shape)
XYZ = spectral_to_XYZ(spd) / 100
uv = Luv_to_uv(XYZ_to_Luv(XYZ))
pylab.plot(uv[0], uv[1], 'o', color='white')
if spd.name is not None and annotate:
pylab.annotate(spd.name,
xy=uv,
xytext=(50, 30),
textcoords='offset points',
arrowprops=dict(arrowstyle='->',
connectionstyle='arc3, rad=0.2'))
settings.update({
'x_tighten': True,
'y_tighten': True,
'limits': (-0.1, 0.7, -0.1, 0.7),
'standalone': True})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
Colour 0.3