def getMunsellData(white_point=(1.0 / 3, 1.0 / 3), V=None, H=None):
target_wp = np.array(white_point)
munsell_wp = np.array([0.309, 0.319])
XYZ_ws = colour.xy_to_XYZ(munsell_wp) * 100
XYZ_wt = colour.xy_to_XYZ(target_wp) * 100
if V is None:
V = [4]
if H is None:
H = ['5R', '5Y', '10GY', '5BG', '5PB', '5P', '5RP']
def convert_xyYtoXYZ(data):
xyz = colour.xyY_to_XYZ(data)
return colour.adaptation.chromatic_adaptation_VonKries(
xyz, XYZ_ws, XYZ_wt, transform='CAT02')
result = []
for value in V:
for hue in H:
idx = np.logical_and(munsell_data_np[:, 0] == hue,
munsell_data_np[:, 1] == value)
if np.sum(idx) > 0:
data = convert_xyYtoXYZ(munsell_data_np[idx, :][:, 3:]) / 100
result.append((data, hue + '_v' + str(value)))
return result
def getHungBernsData(white_point=(1.0 / 3, 1.0 / 3)):
hung_wp = np.array([0.3127, 0.3290])
XYZ_ws = colour.xy_to_XYZ(hung_wp) * 100
XYZ_wt = colour.xy_to_XYZ(np.array(white_point)) * 100
def convertWp(data):
return colour.adaptation.chromatic_adaptation_VonKries(
data, XYZ_ws, XYZ_wt, transform='CAT02')
with open(hung_data_path, 'r') as f:
ydata = yaml.load(f, Loader=yaml.FullLoader)
data = []
names = []
for col in ydata:
names.append(col)
j = 0
ldata = np.zeros((4, 3))
for sat in ydata[col]:
ldata[j, :] = np.array(ydata[col][sat])
j += 1
data.append(convertWp(ldata) / 100)
return (data, names)
return None
def RGB_colourspace_whitepoint_axis_visual(colourspace='ITU-R BT.709',
reference_colourspace='CIE xyY',
width=2.0,
method='gl',
parent=None):
"""
Returns a :class:`vispy.scene.visuals.Line` class instance representing
a given RGB colourspace whitepoint axis.
Parameters
----------
colourspace : unicode, optional
See :func:`RGB_colourspace_volume_visual` argument for possible values.
:class:`colour.RGB_Colourspace` class instance name defining the *RGB*
colourspace whitepoint axis to draw.
reference_colourspace : unicode, optional
**{'CIE XYZ', 'CIE xyY', 'CIE Lab', 'CIE Luv', 'CIE UCS', 'CIE UVW',
'IPT', 'Hunter Lab', 'Hunter Rdab'}**,
Reference colourspace to use for colour conversions / transformations.
width : numeric, optional
Line width.
method : unicode, optional
**{'gl', 'agg'}**,
Line drawing method.
parent : Node, optional
Parent of the spectral locus visual in the `SceneGraph`.
Returns
-------
Line
RGB colourspace whitepoint axis.
"""
colourspace = first_item(filter_RGB_colourspaces(colourspace).values())
XYZ_o = xy_to_XYZ(colourspace.whitepoint + (0, ))
XYZ_f = xy_to_XYZ(colourspace.whitepoint + (1.1, ))
XYZ_l = np.vstack([XYZ_o, XYZ_f])
illuminant = DEFAULT_PLOTTING_ILLUMINANT
points = common_colourspace_model_axis_reorder(
XYZ_to_colourspace_model(XYZ_l, illuminant, reference_colourspace),
reference_colourspace)
line = Line(points, (1, 1, 1), width=width, method=method, parent=parent)
return line
def RGB_colourspace_whitepoint_axis_visual(colourspace='ITU-R BT.709',
reference_colourspace='CIE xyY',
width=2.0,
method='gl',
parent=None):
"""
Returns a :class:`vispy.scene.visuals.Line` class instance representing
a given RGB colourspace whitepoint axis.
Parameters
----------
colourspace : unicode, optional
See :func:`RGB_colourspace_volume_visual` argument for possible values.
:class:`colour.RGB_Colourspace` class instance name defining the *RGB*
colourspace whitepoint axis to draw.
reference_colourspace : unicode, optional
**{'CIE XYZ', 'CIE xyY', 'CIE Lab', 'CIE Luv', 'CIE UCS', 'CIE UVW',
'IPT', 'Hunter Lab', 'Hunter Rdab'}**,
Reference colourspace to use for colour conversions / transformations.
width : numeric, optional
Line width.
method : unicode, optional
**{'gl', 'agg'}**,
Line drawing method.
parent : Node, optional
Parent of the spectral locus visual in the `SceneGraph`.
Returns
-------
Line
RGB colourspace whitepoint axis.
"""
colourspace = first_item(filter_RGB_colourspaces(colourspace).values())
XYZ_o = xy_to_XYZ(colourspace.whitepoint + (0, ))
XYZ_f = xy_to_XYZ(colourspace.whitepoint + (1.1, ))
XYZ_l = np.vstack([XYZ_o, XYZ_f])
illuminant = DEFAULT_PLOTTING_ILLUMINANT
points = common_colourspace_model_axis_reorder(
XYZ_to_colourspace_model(XYZ_l, illuminant, reference_colourspace),
reference_colourspace)
line = Line(points, (1, 1, 1), width=width, method=method, parent=parent)
return line
def set_color(self, color):
"""Propagate user-set colors to the brush too (extension).
"""
colors.ColorManager.set_color(self, color)
if not self.__in_callback:
if not isinstance(color, lib.color.CIECAMColor):
prefs = self.get_prefs()
lightsource = prefs['color.dimension_lightsource']
if lightsource == "custom_XYZ":
lightsource = prefs['color.dimension_lightsource_XYZ']
else:
lightsource = colour.xy_to_XYZ(
colour.ILLUMINANTS['cie_2_1931'][lightsource]) * 100.0
# standard sRGB view environment except adjustable illuminant
cieaxes = prefs['color.dimension_value'] + \
prefs['color.dimension_purity'] + "h"
color = lib.color.CIECAMColor(color=color, cieaxes=cieaxes,
lightsource=lightsource)
#from gui.application import get_app
#app = get_app()
self._app.doc.last_color_target = None
self.__brush.set_ciecam_color(color)
self.__brush.set_color_hsv(color.get_hsv())
def JzAzBz(xyz, saturation, white_point):
XYZ_w = colour.xy_to_XYZ(np.array(white_point)) * 100
XYZ_wr = colour.xy_to_XYZ(np.array([0.3127, 0.3290])) * 100
data = colour.adaptation.chromatic_adaptation_VonKries(xyz * 100,
XYZ_w,
XYZ_wr,
transform='CAT02')
data[data < 0.000000001] = 0.000000001
data = colour.XYZ_to_JzAzBz(data)
data[..., 1] = saturation * data[..., 1]
data[..., 2] = saturation * data[..., 2]
data = colour.JzAzBz_to_XYZ(data)
return colour.adaptation.chromatic_adaptation_VonKries(
data, XYZ_wr, XYZ_w, transform='CAT02') * 0.01
def applyHermiteTonemap(xyz,
white_point,
spline_params=None,
rgb_space=colour.RGB_COLOURSPACES['sRGB'],
overwrite_params={}):
if spline_params is None:
spline_params = spline_curve_defaults.copy()
spline_params.update(overwrite_params)
XYZ_w = colour.xy_to_XYZ(np.array(white_point)) * 100
XYZ_wr = colour.xy_to_XYZ(rgb_space.whitepoint) * 100
xyz_d65 = colour.adaptation.chromatic_adaptation_VonKries(
xyz, XYZ_w, XYZ_wr, transform='CAT02')
rgb_pure = colour.XYZ_to_RGB(xyz_d65, rgb_space.whitepoint,
rgb_space.whitepoint,
rgb_space.XYZ_to_RGB_matrix, None, None)
rgb_pure = applySplineCurve(rgb_pure, spline_params)
ycbcr = np.zeros(xyz_d65.shape)
ycbcr[..., 0] = xyz_d65[..., 0] * XYZ_TO_YCbCr_Rec2020[0] + xyz_d65[
..., 1] * XYZ_TO_YCbCr_Rec2020[1] + xyz_d65[
..., 2] * XYZ_TO_YCbCr_Rec2020[2]
ycbcr[..., 1] = xyz_d65[..., 0] * XYZ_TO_YCbCr_Rec2020[3] + xyz_d65[
..., 1] * XYZ_TO_YCbCr_Rec2020[4] + xyz_d65[
..., 2] * XYZ_TO_YCbCr_Rec2020[5]
ycbcr[..., 2] = xyz_d65[..., 0] * XYZ_TO_YCbCr_Rec2020[6] + xyz_d65[
..., 1] * XYZ_TO_YCbCr_Rec2020[7] + xyz_d65[
..., 2] * XYZ_TO_YCbCr_Rec2020[8]
ycbcr[..., 0] = applySplineCurve(ycbcr[..., 0], spline_params)
xyz_d65[..., 0] = ycbcr[..., 0] * Rec2020_YCbCr_TO_XYZ[0] + ycbcr[
..., 1] * Rec2020_YCbCr_TO_XYZ[1] + ycbcr[...,
2] * Rec2020_YCbCr_TO_XYZ[2]
xyz_d65[..., 1] = ycbcr[..., 0] * Rec2020_YCbCr_TO_XYZ[3] + ycbcr[
..., 1] * Rec2020_YCbCr_TO_XYZ[4] + ycbcr[...,
2] * Rec2020_YCbCr_TO_XYZ[5]
xyz_d65[..., 2] = ycbcr[..., 0] * Rec2020_YCbCr_TO_XYZ[6] + ycbcr[
..., 1] * Rec2020_YCbCr_TO_XYZ[7] + ycbcr[...,
2] * Rec2020_YCbCr_TO_XYZ[8]
rgb_luma = colour.XYZ_to_RGB(xyz_d65, rgb_space.whitepoint,
rgb_space.whitepoint,
rgb_space.XYZ_to_RGB_matrix, None, None)
return rgb_pure * (1.0 - spline_params['luma_ratio']
) + rgb_luma * spline_params['luma_ratio']
def get_bar_amount_for_color(self, col):
# pull in CIECAM config
cm = self.get_color_manager()
prefs = cm.get_prefs()
lightsource = colour.xy_to_XYZ(
colour.ILLUMINANTS['cie_2_1931']['D65']) * 100.0
# standard sRGB view environment except adjustable illuminant
cieaxes = prefs['color.dimension_value'] + \
prefs['color.dimension_purity'] + "h"
col = CIECAMColor(color=col, cieaxes=cieaxes, lightsource=lightsource,
discount_in=False, discount_out=False)
return max(0.0, col.h) / 360
def RGB_colourspace_triangle_visual(colourspace='ITU-R BT.709',
diagram='CIE 1931',
uniform_colour=None,
uniform_opacity=1.0,
width=4.0,
parent=None):
"""
Returns a :class:`vispy.scene.visuals.Line` class instance representing
a *RGB* colourspace triangle visual.
Parameters
----------
colourspace : unicode, optional
See :func:`RGB_colourspace_volume_visual` argument for possible values.
:class:`colour.RGB_Colourspace` class instance name defining the *RGB*
colourspace triangle to draw.
diagram : unicode, optional
**{'CIE 1931', 'CIE 1960 UCS', 'CIE 1976 UCS'}**,
Chromaticity diagram to use.
uniform_colour : array_like, optional
Uniform triangle colour.
uniform_opacity : numeric, optional
Uniform mesh opacity.
width : numeric, optional
Triangle edge width.
parent : Node, optional
Parent of the *RGB* colourspace volume visual in the `SceneGraph`.
"""
if uniform_colour is None:
uniform_colour = (0.8, 0.8, 0.8)
colourspace = first_item(filter_RGB_colourspaces(colourspace).values())
illuminant = DEFAULT_PLOTTING_ILLUMINANT
XYZ_to_ij = CHROMATICITY_DIAGRAM_TRANSFORMATIONS[diagram]['XYZ_to_ij']
ij = XYZ_to_ij(xy_to_XYZ(colourspace.primaries), illuminant)
# TODO: Remove following hack dealing with 'agg' method issues.
ij = np.vstack([ij[-1, ...], ij, ij[0, ...]])
ij[np.isnan(ij)] = 0
RGB = np.hstack([uniform_colour, uniform_opacity])
line = Line(ij, RGB, width=width, method='agg', parent=parent)
return line
def RGB_colourspace_triangle_visual(colourspace='ITU-R BT.709',
diagram='CIE 1931',
uniform_colour=None,
uniform_opacity=1.0,
width=4.0,
parent=None):
"""
Returns a :class:`vispy.scene.visuals.Line` class instance representing
a *RGB* colourspace triangle visual.
Parameters
----------
colourspace : unicode, optional
See :func:`RGB_colourspace_volume_visual` argument for possible values.
:class:`colour.RGB_Colourspace` class instance name defining the *RGB*
colourspace triangle to draw.
diagram : unicode, optional
**{'CIE 1931', 'CIE 1960 UCS', 'CIE 1976 UCS'}**,
Chromaticity diagram to use.
uniform_colour : array_like, optional
Uniform triangle colour.
uniform_opacity : numeric, optional
Uniform mesh opacity.
width : numeric, optional
Triangle edge width.
parent : Node, optional
Parent of the *RGB* colourspace volume visual in the `SceneGraph`.
"""
if uniform_colour is None:
uniform_colour = (0.8, 0.8, 0.8)
colourspace = first_item(filter_RGB_colourspaces(colourspace).values())
illuminant = DEFAULT_PLOTTING_ILLUMINANT
XYZ_to_ij = CHROMATICITY_DIAGRAM_TRANSFORMATIONS[diagram]['XYZ_to_ij']
ij = XYZ_to_ij(xy_to_XYZ(colourspace.primaries), illuminant)
# TODO: Remove following hack dealing with 'agg' method issues.
ij = np.vstack([ij[-1, ...], ij, ij[0, ...]])
ij[np.isnan(ij)] = 0
RGB = np.hstack([uniform_colour, uniform_opacity])
line = Line(ij, RGB, width=width, method='agg', parent=parent)
return line
def temperatureChange(self):
value = self.temperatureSlider.value() +1
#range is 1100K to 11 000K
K = int(1000+ (value*120))
print("Kelvins: ", K)
xy = colour.CCT_to_xy(K)
#print("xy", xy)
xyz = colour.xy_to_XYZ(xy)
#print("xyz", xyz)
rgb = colour.XYZ_to_sRGB(xyz)
r = int(min(1,max(0,rgb[0]))*255)
g = int(min(1,max(0,rgb[1]))*255)
b = int(min(1,max(0,rgb[2]))*255)
self.color = [r, g, b]
print("rgb", self.color)
self.updateColorLabel()
def calculate_EVILS_eiY(XYZ_D65, xy_achromatic=[0.3127, 0.3290]):
# EVILS eiY Oppenent Chroma Model. Fancy words for transforming the
# CIE XYZ values into u' v' Cartesian coordinates. The true "magic" if
# there is any, is in the identification of the HK effect issues with
# the Cartesian distances offered from u' v'.
e, i, Y = np.split(calculate_eiY(XYZ_D65), 3, axis=-1)
e_a, i_a, Y_a = np.split(calculate_eiY(colour.xy_to_XYZ(xy_achromatic)),
3,
axis=-1)
eiY_output_e = e - e_a
eiY_output_i = i - i_a
eiY_output_Y = Y
eiY_output = np.vstack([eiY_output_e.T, eiY_output_i.T,
eiY_output_Y.T]).T.reshape(XYZ_D65.shape)
return eiY_output
def temperature_to_rgb(cct):
""" Convert temperature in Kelvin to sRGB.
First, we convert CCT (Kelvin) to chromaticity coordinates.
Second, we convert to tristimulus values.
Third, we convert to rgb
Parameters
----------
cct : Correlated color temperature in kelvin
Returns
-------
array : List/tuple of rgb values, e.g. [255.0, 235.0, 12.0]
"""
xy = colour.CCT_to_xy(cct)
xyz = colour.xy_to_XYZ(xy)
rgb = colour.XYZ_to_sRGB(xyz)
return rgb
def get_color_for_bar_amount(self, amt):
# pull in CIECAM config
cm = self.get_color_manager()
prefs = cm.get_prefs()
lightsource = colour.xy_to_XYZ(
colour.ILLUMINANTS['cie_2_1931']['D65']) * 100.0
cieaxes = prefs['color.dimension_value'] + \
prefs['color.dimension_purity'] + "h"
col = CIECAMColor(
color=self.get_managed_color(),
cieaxes=cieaxes,
lightsource=lightsource,
discount_in=False,
discount_out=False
)
col.limit_purity = None
col.cachedrgb = None
col.h = max(0.0, amt) * 360
col.v = 50
col.s = 35
return col
def get_normalize_rgb_value_from_small_xy(small_xy, name=cs.BT709):
"""
Examples
--------
>>> xy = calc_xy_from_white_to_primary_n_step(name=cs.BT709,
step=5, color='green')
>>> print(xy)
[[0.3127, 0.3290], [0.3095, 0.3968], [0.3064, 0.4645],
[0.3032, 0.5323], [0.3000, 0.6000]]
>>> get_normalize_rgb_value_from_small_xy(xy)
[[ 1.00000000e+00 1.00000000e+00 1.00000000e+00]
[ 5.40536717e-01 1.00000000e+00 5.40536717e-01]
[ 2.81687026e-01 1.00000000e+00 2.81687026e-01]
[ 1.15605362e-01 1.00000000e+00 1.15605362e-01]
[ 1.58799347e-16 1.00000000e+00 4.73916800e-16]]
"""
large_xyz = xy_to_XYZ(small_xy)
xyz_to_rgb_mtx = RGB_COLOURSPACES[name].XYZ_to_RGB_matrix
rgb_linear = XYZ_to_RGB(large_xyz, D65_WHITE, D65_WHITE, xyz_to_rgb_mtx)
normalize_val = np.max(rgb_linear, axis=-1)
rgb_linear /= normalize_val.reshape((rgb_linear.shape[0], 1))
return rgb_linear
__all__ = ['POINTER_GAMUT_DATA',
'POINTER_GAMUT_BOUNDARIES',
'pointer_gamut_visual',
'pointer_gamut_boundaries_visual',
'pointer_gamut_hull_visual']
POINTER_GAMUT_DATA = Lab_to_XYZ(LCHab_to_Lab(POINTER_GAMUT_DATA),
POINTER_GAMUT_ILLUMINANT)
"""
Pointer's Gamut data converted to *CIE XYZ* tristimulus values.
POINTER_GAMUT_DATA : ndarray
"""
POINTER_GAMUT_BOUNDARIES = xy_to_XYZ(POINTER_GAMUT_BOUNDARIES)
"""
Pointer's Gamut boundaries data converted to *CIE XYZ* tristimulus values.
POINTER_GAMUT_BOUNDARIES : ndarray
"""
def pointer_gamut_visual(reference_colourspace='CIE xyY',
size=4.0,
edge_size=0.5,
uniform_colour=(0.9, 0.9, 0.9),
uniform_opacity=0.8,
uniform_edge_colour=(0.9, 0.9, 0.9),
uniform_edge_opacity=0.8,
parent=None):
from colour import (Luv_to_uv, Luv_uv_to_xy, UCS_to_uv, UCS_uv_to_xy,
xy_to_XYZ, XYZ_to_Luv, XYZ_to_UCS, XYZ_to_xy)
__author__ = 'Colour Developers'
__copyright__ = 'Copyright (C) 2013-2019 - Colour Developers'
__license__ = 'New BSD License - https://opensource.org/licenses/BSD-3-Clause'
__maintainer__ = 'Colour Developers'
__email__ = '*****@*****.**'
__status__ = 'Production'
__all__ = ['CHROMATICITY_DIAGRAM_TRANSFORMATIONS', 'Cycle']
CHROMATICITY_DIAGRAM_TRANSFORMATIONS = {
'CIE 1931': {
'XYZ_to_ij': lambda a, i: XYZ_to_xy(a, i),
'ij_to_XYZ': lambda a, i: xy_to_XYZ(a)
},
'CIE 1960 UCS': {
'XYZ_to_ij': lambda a, i: UCS_to_uv(XYZ_to_UCS(a)),
'ij_to_XYZ': lambda a, i: xy_to_XYZ(UCS_uv_to_xy(a))
},
'CIE 1976 UCS': {
'XYZ_to_ij': lambda a, i: Luv_to_uv(XYZ_to_Luv(a, i), i),
'ij_to_XYZ': lambda a, i: xy_to_XYZ(Luv_uv_to_xy(a))
}
}
"""
Chromaticity diagram specific helper conversion objects.
CHROMATICITY_DIAGRAM_TRANSFORMATIONS : dict
**{'CIE 1931', 'CIE 1960 UCS', 'CIE 1976 UCS'}**
colourspace = colour.RGB_COLOURSPACES['ACES RGB']
print('Name:\n"{0}"'.format(colourspace.name))
print('\nPrimaries:\n{0}'.format(colourspace.primaries))
print('\nNormalised primary matrix to "CIE XYZ":\n{0}'.format(
colourspace.to_XYZ))
print('\nNormalised primary matrix to "ACES RGB":\n{0}'.format(
colourspace.to_RGB))
print('\nTransfer function from linear to colourspace:\n{0}'.format(
colourspace.transfer_function))
print('\nInverse transfer function from colourspace to linear:\n{0}'.format(
colourspace.inverse_transfer_function))
print('\n')
message_box('Computing "ACES RGB" colourspace to "sRGB" colourspace matrix.')
cat = colour.chromatic_adaptation_matrix(
colour.xy_to_XYZ(colour.RGB_COLOURSPACES['ACES RGB'].whitepoint),
colour.xy_to_XYZ(colour.RGB_COLOURSPACES['sRGB'].whitepoint))
print(np.dot(colour.RGB_COLOURSPACES['sRGB'].to_RGB,
np.dot(cat, colour.RGB_COLOURSPACES['ACES RGB'].to_XYZ)))
print('\n')
RGB = [0.35521588, 0.41, 0.24177934]
message_box(('Converting from "sRGB" colourspace to "ProPhoto RGB" '
'colourspace given "RGB" values:\n'
'\n\t{0}'.format(RGB)))
print(colour.RGB_to_RGB(RGB,
colour.RGB_COLOURSPACES['sRGB'],
colour.RGB_COLOURSPACES['ProPhoto RGB']))
print('\nPrimaries:\n{0}'.format(colourspace.primaries))
print(('\nNormalised primary matrix to "CIE XYZ" '
'tristimulus values:\n{0}').format(colourspace.RGB_to_XYZ_matrix))
print('\nNormalised primary matrix to "ACES2065-1":\n{0}'.format(
colourspace.XYZ_to_RGB_matrix))
print('\nOpto-electronic transfer function from '
'linear to colourspace:\n{0}'.format(colourspace.encoding_cctf))
print('\nElectro-optical transfer function from '
'colourspace to linear:\n{0}'.format(colourspace.decoding_cctf))
print('\n')
message_box(('Computing "ACES2065-1" colourspace to "Rec. 709" colourspace '
'matrix.'))
cat = colour.chromatic_adaptation_matrix_VonKries(
colour.xy_to_XYZ(colour.RGB_COLOURSPACES['ACES2065-1'].whitepoint),
colour.xy_to_XYZ(colour.RGB_COLOURSPACES['Rec. 709'].whitepoint))
print(
np.dot(
colour.RGB_COLOURSPACES['Rec. 709'].XYZ_to_RGB_matrix,
np.dot(cat, colour.RGB_COLOURSPACES['ACES2065-1'].RGB_to_XYZ_matrix)))
print('\n')
RGB = (0.35521588, 0.41000000, 0.24177934)
message_box(('Converting from "Rec. 709" colourspace to "ACEScg" colourspace '
'given "RGB" values:\n'
'\n\t{0}'.format(RGB)))
print(
colour.RGB_to_RGB(RGB, colour.RGB_COLOURSPACES['Rec. 709'],
colour.RGB_COLOURSPACES['ACEScg']))
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Showcases correlated colour temperature computations.
"""
import colour
from colour.utilities.verbose import message_box
message_box('Correlated Colour Temperature Computations')
cmfs = colour.CMFS['CIE 1931 2 Degree Standard Observer']
illuminant = colour.ILLUMINANTS_RELATIVE_SPDS['D65']
xy = colour.XYZ_to_xy(colour.spectral_to_XYZ(illuminant, cmfs))
uv = colour.UCS_to_uv(colour.XYZ_to_UCS(colour.xy_to_XYZ(xy)))
message_box(('Converting to "CCT" and "D_uv" from given "CIE UCS" colourspace '
'"uv" chromaticity coordinates using "Ohno (2013)" method:\n'
'\n\t{0}'.format(uv)))
print(colour.uv_to_CCT_Ohno2013(uv, cmfs=cmfs))
print(colour.uv_to_CCT(uv, cmfs=cmfs))
print('\n')
message_box('Faster computation with 3 iterations but a lot less precise.')
print(colour.uv_to_CCT_Ohno2013(uv, cmfs=cmfs, iterations=3))
print('\n')
message_box(('Converting to "CCT" and "D_uv" from given "CIE UCS" colourspace '
'"uv" chromaticity coordinates using "Robertson (1968)" method:\n'
'\n\t{0}'.format(uv)))
print('\n')
message_box('Using "Bradford" CAT.')
print(colour.chromatic_adaptation_matrix_VonKries(
XYZ_w, XYZ_wr, transform='Bradford'))
print('\n')
message_box(('Computing the chromatic adaptation matrix from '
'"CIE Standard Illuminant A" to '
'"CIE Standard Illuminant D Series D65" using "Von Kries" CAT.'))
A = colour.ILLUMINANTS['CIE 1931 2 Degree Standard Observer']['A']
D65 = colour.ILLUMINANTS['CIE 1931 2 Degree Standard Observer']['D65']
print(colour.chromatic_adaptation_matrix_VonKries(
colour.xy_to_XYZ(A),
colour.xy_to_XYZ(D65),
transform='Von Kries'))
print('\n')
XYZ = (1.14176346, 1.00000000, 0.49815206)
message_box(('Adapting given "CIE XYZ" tristimulus values from '
'"CIE Standard Illuminant A" to '
'"CIE Standard Illuminant D Series D65" using "Sharp" CAT.\n'
'\n\t"XYZ":\n\t\t{0}'.format(XYZ)))
print(colour.chromatic_adaptation_VonKries(
XYZ,
colour.xy_to_XYZ(A),
colour.xy_to_XYZ(D65),
transform='Sharp'))
/ 100
)
)
print("\n")
RGB = np.array([0.45675795, 0.30986982, 0.24861924])
message_box(
f'Converting to the "CAM16-UCS" colourspace from given "Output-Referred" '
f'"sRGB" colourspace values:\n\n\t{RGB}'
)
print(colour.convert(RGB, "Output-Referred RGB", "CAM16UCS"))
specification = colour.XYZ_to_CAM16(
colour.sRGB_to_XYZ(RGB) * 100,
XYZ_w=colour.xy_to_XYZ(
colour.CCS_ILLUMINANTS["CIE 1931 2 Degree Standard Observer"]["D65"]
)
* 100,
L_A=64 / np.pi * 0.2,
Y_b=20,
)
print(
colour.JMh_CAM16_to_CAM16UCS(
colour.utilities.tstack(
[
specification.J,
specification.M,
specification.h,
]
)
)
message_box('Using "Bradford" CAT.')
print(
colour.chromatic_adaptation_matrix_VonKries(XYZ_w,
XYZ_wr,
transform='Bradford'))
print('\n')
message_box(('Computing the chromatic adaptation matrix from '
'"CIE Standard Illuminant A" to '
'"CIE Standard Illuminant D Series D65" using Von Kries CAT.'))
A = colour.ILLUMINANTS['CIE 1931 2 Degree Standard Observer']['A']
D65 = colour.ILLUMINANTS['CIE 1931 2 Degree Standard Observer']['D65']
print(
colour.chromatic_adaptation_matrix_VonKries(colour.xy_to_XYZ(A),
colour.xy_to_XYZ(D65),
transform='Von Kries'))
print('\n')
XYZ = (1.14176346, 1.00000000, 0.49815206)
message_box(('Adapting given "CIE XYZ" tristimulus values from '
'"CIE Standard Illuminant A" to '
'"CIE Standard Illuminant D Series D65" using "Sharp" CAT.\n'
'\n\t"XYZ":\n\t\t{0}'.format(XYZ)))
print(
colour.chromatic_adaptation_VonKries(XYZ,
colour.xy_to_XYZ(A),
colour.xy_to_XYZ(D65),
transform='Sharp'))
})
if not result.success:
raise RuntimeError(
'Optimization failed for {0} after {1} iterations: "{2}".'.format(
XYZ, result.nit, result.message))
return SpectralDistribution(
from_range_100(np.exp(result.x) * 100),
wavelengths,
name='Meng (2015) - {0}'.format(XYZ))
# Define our illuminant and color space matrices
D65_xy = colour.ILLUMINANTS['cie_2_1931']['D65']
D65 = colour.xy_to_XYZ(D65_xy)
CMFS = colour.CMFS['cie_2_1931']
D65_SPD = colour.ILLUMINANTS_SDS['D65']/100.
# illuminant_SPD = colour.XYZ_to_spectral_Meng2015(D65, cmfs=CMFS, interval=shape.interval)
illuminant_SPD = D65_SPD
np.set_printoptions(formatter={"float": "{:0.15f}".format}, threshold=np.nan)
colorspace = colour.models.BT709_COLOURSPACE
colorspace.use_derived_transformation_matrices(True)
RGB_to_XYZ_m = colorspace.RGB_to_XYZ_matrix
XYZ_to_RGB_m = colorspace.XYZ_to_RGB_matrix
def plot_jzazbz(lines = [], scatter = [], hue_lines = [], white_point = (1.0/3, 1.0/3),
filename = None, save_only = False):
XYZ_w = colour.xy_to_XYZ(np.array(white_point)) * 100
XYZ_wr = colour.xy_to_XYZ(np.array([0.3127, 0.3290])) * 100
def convertData(xyz):
xyz_d65 = colour.adaptation.chromatic_adaptation_VonKries(xyz * 100, XYZ_w, XYZ_wr, transform='CAT02')
return colour.XYZ_to_JzAzBz(xyz_d65)
ax = [None] * 3
fig = [None] * 3
for i in range(3):
fig[i], ax[i] = plt.subplots()
plotHull(jzazbz_hull[:,[1,0]], ax[0])
plotHull(jzazbz_hull[:,[2,0]], ax[1])
plotHull(jzazbz_hull[:,[1,2]], ax[2])
ax[0].set_xlim(-0.45, 0.45)
ax[0].set_ylim(-0.05, 1.05)
ax[0].set_aspect('equal')
ax[0].set_xlabel('Az')
ax[0].set_ylabel('Jz')
ax[1].set_xlim(-0.45, 0.45)
ax[1].set_ylim(-0.05, 1.05)
ax[1].set_aspect('equal')
ax[1].set_xlabel('Bz')
ax[1].set_ylabel('Jz')
ax[2].set_xlim(-0.45, 0.45)
ax[2].set_ylim(-0.45, 0.45)
ax[2].set_aspect('equal')
ax[2].set_xlabel('Az')
ax[2].set_ylabel('Bz')
for line,label in hue_lines:
data = convertData(line)
ax[0].plot(data[:,1], data[:,0], label=label, color=hue_line_color, linestyle=hue_line_style, marker=hue_point_style)
ax[1].plot(data[:,2], data[:,0], label=label, color=hue_line_color, linestyle=hue_line_style, marker=hue_point_style)
ax[2].plot(data[:,1], data[:,2], label=label, color=hue_line_color, linestyle=hue_line_style, marker=hue_point_style)
cnt = 0
for line,label in lines:
data = convertData(line)
lstyle = lineStyle(cnt)
ax[0].plot(data[:,1], data[:,0], label=label, color=lstyle[0], linestyle=lstyle[2], marker=lstyle[1])
ax[1].plot(data[:,2], data[:,0], label=label, color=lstyle[0], linestyle=lstyle[2], marker=lstyle[1])
ax[2].plot(data[:,1], data[:,2], label=label, color=lstyle[0], linestyle=lstyle[2], marker=lstyle[1])
cnt += 1
for points,label in scatter:
data = convertData(points)
c,m = scatterStyle(cnt)
ax[0].scatter(data[:,1], data[:,0], label=label, c=c, marker=m)
ax[1].scatter(data[:,2], data[:,0], label=label, c=c, marker=m)
ax[2].scatter(data[:,1], data[:,2], label=label, c=c, marker=m)
cnt += 1
modes = ['Jz-Az', 'Jz-Bz', 'Bz-Az']
for i in range(3):
if filename:
fig[i].savefig(filename.format('jaz-' + modes[i]), bbox_inches='tight')
if not filename or not save_only:
fig[i].show()
print(('\nNormalised primary matrix to "CIE XYZ" '
'tristimulus values:\n{0}').format(
colourspace.RGB_to_XYZ_matrix))
print('\nNormalised primary matrix to "ACES2065-1":\n{0}'.format(
colourspace.XYZ_to_RGB_matrix))
print('\nOpto-electronic transfer function from '
'linear to colourspace:\n{0}'.format(colourspace.encoding_cctf))
print('\nElectro-optical transfer function from '
'colourspace to linear:\n{0}'.format(colourspace.decoding_cctf))
print('\n')
message_box(('Computing "ACES2065-1" colourspace to "Rec. 709" colourspace '
'matrix.'))
cat = colour.chromatic_adaptation_matrix_VonKries(
colour.xy_to_XYZ(colour.RGB_COLOURSPACES['ACES2065-1'].whitepoint),
colour.xy_to_XYZ(colour.RGB_COLOURSPACES['Rec. 709'].whitepoint))
print(np.dot(colour.RGB_COLOURSPACES['Rec. 709'].XYZ_to_RGB_matrix,
np.dot(cat,
colour.RGB_COLOURSPACES['ACES2065-1'].RGB_to_XYZ_matrix)))
print('\n')
RGB = (0.35521588, 0.41000000, 0.24177934)
message_box(('Converting from "Rec. 709" colourspace to "ACEScg" colourspace '
'given "RGB" values:\n'
'\n\t{0}'.format(RGB)))
print(colour.RGB_to_RGB(RGB,
colour.RGB_COLOURSPACES['Rec. 709'],
colour.RGB_COLOURSPACES['ACEScg']))
print('\n')
message_box('Using "Bradford" CAT.')
print(colour.chromatic_adaptation_matrix_VonKries(
XYZ_w, XYZ_wr, transform='Bradford'))
print('\n')
message_box(('Computing the chromatic adaptation matrix from '
'"CIE Standard Illuminant A" to '
'"CIE Standard Illuminant D Series D65" using Von Kries CAT.'))
A = colour.ILLUMINANTS['CIE 1931 2 Degree Standard Observer']['A']
D65 = colour.ILLUMINANTS['CIE 1931 2 Degree Standard Observer']['D65']
print(colour.chromatic_adaptation_matrix_VonKries(
colour.xy_to_XYZ(A),
colour.xy_to_XYZ(D65),
transform='Von Kries'))
print('\n')
XYZ = [1.14176346, 1., 0.49815206]
message_box(('Adapting given "CIE XYZ" matrix from '
'"CIE Standard Illuminant A" to '
'"CIE Standard Illuminant D Series D65" using "Sharp" CAT.\n'
'\n\t"XYZ":\n\t\t{0}'.format(XYZ)))
print(colour.chromatic_adaptation_VonKries(
XYZ,
colour.xy_to_XYZ(A),
colour.xy_to_XYZ(D65),
transform='Von Kries'))
message_box('Using "Bradford" CAT.')
print(
colour.adaptation.chromatic_adaptation_matrix_VonKries(
XYZ_w, XYZ_wr, transform='Bradford'))
print('\n')
message_box(('Computing the chromatic adaptation matrix from '
'"CIE Standard Illuminant A" to '
'"CIE Standard Illuminant D Series D65" using "Von Kries" CAT.'))
A = colour.ILLUMINANTS['CIE 1931 2 Degree Standard Observer']['A']
D65 = colour.ILLUMINANTS['CIE 1931 2 Degree Standard Observer']['D65']
print(
colour.adaptation.chromatic_adaptation_matrix_VonKries(
colour.xy_to_XYZ(A), colour.xy_to_XYZ(D65), transform='Von Kries'))
print('\n')
XYZ = np.array([1.14176346, 1.00000000, 0.49815206])
message_box(('Adapting given "CIE XYZ" tristimulus values from '
'"CIE Standard Illuminant A" to '
'"CIE Standard Illuminant D Series D65" using "Sharp" CAT.\n'
'\n\t"XYZ":\n\t\t{0}'.format(XYZ)))
print(
colour.chromatic_adaptation(
XYZ, colour.xy_to_XYZ(A), colour.xy_to_XYZ(D65), transform='Sharp'))
print(
colour.adaptation.chromatic_adaptation_VonKries(
XYZ, colour.xy_to_XYZ(A), colour.xy_to_XYZ(D65), transform='Sharp'))
from colour import (Luv_to_uv, Luv_uv_to_xy, UCS_to_uv, UCS_uv_to_xy,
xy_to_XYZ, XYZ_to_Luv, XYZ_to_UCS, XYZ_to_xy)
__author__ = 'Colour Developers'
__copyright__ = 'Copyright (C) 2013-2019 - Colour Developers'
__license__ = 'New BSD License - https://opensource.org/licenses/BSD-3-Clause'
__maintainer__ = 'Colour Developers'
__email__ = '*****@*****.**'
__status__ = 'Production'
__all__ = ['CHROMATICITY_DIAGRAM_TRANSFORMATIONS', 'Cycle']
CHROMATICITY_DIAGRAM_TRANSFORMATIONS = {
'CIE 1931': {
'XYZ_to_ij': lambda a, i: XYZ_to_xy(a, i),
'ij_to_XYZ': lambda a, i: xy_to_XYZ(a)
},
'CIE 1960 UCS': {
'XYZ_to_ij': lambda a, i: UCS_to_uv(XYZ_to_UCS(a)),
'ij_to_XYZ': lambda a, i: xy_to_XYZ(UCS_uv_to_xy(a))
},
'CIE 1976 UCS': {
'XYZ_to_ij': lambda a, i: Luv_to_uv(XYZ_to_Luv(a, i), i),
'ij_to_XYZ': lambda a, i: xy_to_XYZ(Luv_uv_to_xy(a))
}
}
"""
Chromaticity diagram specific helper conversion objects.
CHROMATICITY_DIAGRAM_TRANSFORMATIONS : dict
**{'CIE 1931', 'CIE 1960 UCS', 'CIE 1976 UCS'}**
message_box('Using "Bradford" CAT.')
print(
colour.adaptation.matrix_chromatic_adaptation_VonKries(
XYZ_w, XYZ_wr, transform='Bradford'))
print('\n')
message_box(('Computing the chromatic adaptation matrix from '
'"CIE Standard Illuminant A" to '
'"CIE Standard Illuminant D Series D65" using "Von Kries" CAT.'))
A = colour.CCS_ILLUMINANTS['CIE 1931 2 Degree Standard Observer']['A']
D65 = colour.CCS_ILLUMINANTS['CIE 1931 2 Degree Standard Observer']['D65']
print(
colour.adaptation.matrix_chromatic_adaptation_VonKries(
colour.xy_to_XYZ(A), colour.xy_to_XYZ(D65), transform='Von Kries'))
print('\n')
XYZ = np.array([1.14176346, 1.00000000, 0.49815206])
message_box(('Adapting given "CIE XYZ" tristimulus values from '
'"CIE Standard Illuminant A" to '
'"CIE Standard Illuminant D Series D65" using "Sharp" CAT.\n'
'\n\t"XYZ":\n\t\t{0}'.format(XYZ)))
print(
colour.chromatic_adaptation(XYZ,
colour.xy_to_XYZ(A),
colour.xy_to_XYZ(D65),
transform='Sharp'))
print(
colour.adaptation.chromatic_adaptation_VonKries(XYZ,
print(colour.convert(sd_dark_skin, 'Spectral Distribution', 'sRGB'))
print(
colour.XYZ_to_sRGB(
colour.sd_to_XYZ(sd_dark_skin,
illuminant=colour.SDS_ILLUMINANTS['D65']) / 100))
print('\n')
RGB = np.array([0.45675795, 0.30986982, 0.24861924])
message_box(('Converting to "CAM16-UCS" colourspace from given '
'"Output-Referred" "sRGB" colourspace values:\n'
'\n\t{0}'.format(RGB)))
print(colour.convert(RGB, 'Output-Referred RGB', 'CAM16UCS'))
specification = colour.XYZ_to_CAM16(
colour.sRGB_to_XYZ(RGB) * 100,
XYZ_w=colour.xy_to_XYZ(
colour.CCS_ILLUMINANTS['CIE 1931 2 Degree Standard Observer']['D65']) *
100,
L_A=64 / np.pi * 0.2,
Y_b=20)
print(
colour.JMh_CAM16_to_CAM16UCS(
colour.utilities.tstack([
specification.J,
specification.M,
specification.h,
])) / 100)
print('\n')
Jpapbp = np.array([0.39994811, 0.09206558, 0.0812752])
message_box(('Converting to "Output-Referred" "sRGB" colourspace from given '
print(('\nNormalised primary matrix to "CIE XYZ" '
'tristimulus values:\n{0}').format(colourspace.RGB_to_XYZ_matrix))
print('\nNormalised primary matrix to "ACES2065-1":\n{0}'.format(
colourspace.XYZ_to_RGB_matrix))
print('\nOpto-electronic transfer function from '
'linear to colourspace:\n{0}'.format(colourspace.encoding_cctf))
print('\nElectro-optical transfer function from '
'colourspace to linear:\n{0}'.format(colourspace.decoding_cctf))
print('\n')
message_box(
('Computing "ACES2065-1" colourspace to "ITU-R BT.709" colourspace '
'matrix.'))
cat = colour.adaptation.chromatic_adaptation_matrix_VonKries(
colour.xy_to_XYZ(colourspace.whitepoint),
colour.xy_to_XYZ(colour.RGB_COLOURSPACES['ITU-R BT.709'].whitepoint))
print(
np.dot(colour.RGB_COLOURSPACES['ITU-R BT.709'].XYZ_to_RGB_matrix,
np.dot(cat, colourspace.RGB_to_XYZ_matrix)))
print('\n')
RGB = np.array([0.45620519, 0.03081071, 0.04091952])
message_box(
('Converting from "ITU-R BT.709" colourspace to "ACEScg" colourspace '
'given "RGB" values:\n'
'\n\t{0}'.format(RGB)))
print(
colour.RGB_to_RGB(
RGB,
print(colour.xyY_to_XYZ(xyY))
print('\n')
message_box(('Converting to "xy" chromaticity coordinates from given '
'"CIE XYZ" tristimulus values:\n'
'\n\t{0}'.format(XYZ)))
print(colour.XYZ_to_xy(XYZ))
print('\n')
xy = (0.43250000, 0.37880000)
message_box(('Converting to "CIE XYZ" tristimulus values from given "xy" '
'chromaticity coordinates:\n'
'\n\t{0}'.format(xy)))
print(colour.xy_to_XYZ(xy))
print('\n')
message_box(('Converting to "RGB" colourspace from given "CIE XYZ" '
'tristimulus values:\n'
'\n\t{0}'.format(XYZ)))
D50 = colour.ILLUMINANTS['CIE 1931 2 Degree Standard Observer']['D50']
print(
colour.XYZ_to_RGB(XYZ, D50, colour.sRGB_COLOURSPACE.whitepoint,
colour.sRGB_COLOURSPACE.XYZ_to_RGB_matrix, 'Bradford',
colour.sRGB_COLOURSPACE.encoding_cctf))
print('\n')
RGB = (1.26651054, 0.91394181, 0.76936593)
def load(self):
"""
Syncs, parses, converts and returns the *Hung and Berns (1995)*
*Constant Hue Loci Data* dataset content.
Returns
-------
OrderedDict
*Hung and Berns (1995)* *Constant Hue Loci Data* dataset content.
Examples
--------
>>> from colour_datasets.utilities import suppress_stdout
>>> dataset = DatasetLoader_Hung1995()
>>> with suppress_stdout():
... dataset.load()
>>> len(dataset.content.keys())
6
"""
super(DatasetLoader_Hung1995, self).sync()
self._content = OrderedDict()
filenames = OrderedDict([
('Table I.csv', 'Reference colors.'),
('Table II.csv', 'Intra- and interobserver variances for each '
'reference hue expressed in circumferential '
'hue-angle difference.'),
('Table III.csv', 'Weight-averaged constant hue loci for the CL '
'experiment.'),
('Table IV.csv', 'Weight-averaged constant hue loci for the VL '
'experiment.'),
])
for filename in filenames:
datafile_path = os.path.join(self.record.repository, 'dataset',
filename)
self._content[filename.split('.')[0]] = np.genfromtxt(
datafile_path,
delimiter=',',
names=True,
dtype=None,
encoding='utf-8')
hues = [
'Red', 'Red-yellow', 'Yellow', 'Yellow-green', 'Green',
'Green-cyan', 'Cyan', 'Cyan-blue', 'Blue', 'Blue-magenta',
'Magenta', 'Magenta-red'
]
XYZ_r = xy_to_XYZ(
CCS_ILLUMINANTS['CIE 1931 2 Degree Standard Observer']['C'])
for table, experiment in [('Table III', 'CL'), ('Table IV', 'VL')]:
key = 'Constant Hue Loci Data - {0}'.format(experiment)
self._content[key] = OrderedDict()
for hue in hues:
for sample_r in self._content['Table I']:
sample_r = sample_r.tolist()
if sample_r[0] == hue:
XYZ_cr = xyY_to_XYZ(sample_r[1:4]) / 100
break
XYZ_ct = []
metadata = {
'Color name': [],
'C*uv': [],
}
for sample_t in self._content[table]:
sample_t = sample_t.tolist()
if not sample_t[0] == hue:
continue
XYZ_ct.append(sample_t[2:])
metadata['Color name'].append(sample_t[0])
metadata['C*uv'].append(sample_t[1])
self._content[key][hue] = (
ConstantPerceivedHueColourMatches_Hung1995(
hue, XYZ_r, XYZ_cr,
np.vstack(XYZ_ct) / 100, metadata))
return self._content
f"\nOpto-electronic transfer function from linear to colourspace:\n"
f"{colourspace.cctf_encoding}"
)
print(
f"\nElectro-optical transfer function from colourspace to linear:\n"
f"{colourspace.cctf_decoding}"
)
print("\n")
message_box(
'Computing the "ACES2065-1" colourspace to "ITU-R BT.709" colourspace '
"matrix."
)
cat = colour.adaptation.matrix_chromatic_adaptation_VonKries(
colour.xy_to_XYZ(colourspace.whitepoint),
colour.xy_to_XYZ(colour.RGB_COLOURSPACES["ITU-R BT.709"].whitepoint),
)
print(
np.dot(
colour.RGB_COLOURSPACES["ITU-R BT.709"].matrix_XYZ_to_RGB,
np.dot(cat, colourspace.matrix_RGB_to_XYZ),
)
)
print("\n")
RGB = np.array([0.45620519, 0.03081071, 0.04091952])
message_box(
f'Converting from the "ITU-R BT.709" colourspace to the "ACEScg" '
f'colourspace given "RGB" values:\n\n\t{RGB}'
[0.45079660, 0.52288689],
[0.19124902, 0.55444488],
[0.13128455, 0.51210591],
[0.14889223, 0.37091478],
[0.28992574, 0.30964533],
]
swatches_XYZ = []
for patch in swatches:
in_XYZ = colour.Luv_to_XYZ(colour.uv_to_Luv(patch))
swatches_XYZ.append(in_XYZ * (average_luminance / in_XYZ[1]))
# Adapting Luminance, 250 cd/m^2 represents a typical modern computer
# display peak luminance.
L_a = 250 * average_luminance
bg_grey = colour.xy_to_XYZ(colour.Luv_uv_to_xy(wp)) * average_luminance
swatches_normal = []
swatches_VCC = []
swatches_VAC = []
for i in range(len(swatches)):
VCC = colour.HelmholtzKohlrausch_effect_luminous_Nayatani1997(swatches[i],
wp,
L_a,
method="VCC")
VAC = colour.HelmholtzKohlrausch_effect_luminous_Nayatani1997(swatches[i],
wp,
L_a,
method="VAC")
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Showcases correlated colour temperature computations.
"""
import colour
from colour.utilities.verbose import message_box
message_box('Correlated Colour Temperature Computations')
cmfs = colour.CMFS['CIE 1931 2 Degree Standard Observer']
illuminant = colour.ILLUMINANTS_RELATIVE_SPDS['D65']
xy = colour.XYZ_to_xy(colour.spectral_to_XYZ(illuminant, cmfs))
uv = colour.UCS_to_uv(colour.XYZ_to_UCS(colour.xy_to_XYZ(xy)))
message_box(('Converting to "CCT" and "Duv" from given "CIE UCS" colourspace '
'"uv" chromaticity coordinates using "Yoshi Ohno (2013)" '
'method:\n'
'\n\t{0}'.format(uv)))
print(colour.uv_to_CCT_ohno2013(uv, cmfs=cmfs))
print(colour.uv_to_CCT(uv, cmfs=cmfs))
print('\n')
message_box('Faster computation with 3 iterations but a lot less precise.')
print(colour.uv_to_CCT_ohno2013(uv, cmfs=cmfs, iterations=3))
print('\n')
message_box(('Converting to "CCT" and "Duv" from given "CIE UCS" colourspace '
print(colour.xyY_to_XYZ(xyY))
print('\n')
message_box(('Converting to "xy" chromaticity coordinates from given '
'"CIE XYZ" colourspace values:\n'
'\n\t{0}'.format(XYZ)))
print(colour.XYZ_to_xy(XYZ))
print('\n')
xy = (0.43249999995420696, 0.378800000065942)
message_box(('Converting to "CIE XYZ" colourspace from given "xy" '
'chromaticity coordinates:\n'
'\n\t{0}'.format(xy)))
print(colour.xy_to_XYZ(xy))
print('\n')
message_box(('Converting to "RGB" colourspace from given "CIE XYZ" '
'colourspace values:\n'
'\n\t{0}'.format(XYZ)))
print(colour.XYZ_to_RGB(
XYZ,
colour.ILLUMINANTS['CIE 1931 2 Degree Standard Observer']['D50'],
colour.sRGB_COLOURSPACE.whitepoint,
colour.sRGB_COLOURSPACE.XYZ_to_RGB_matrix,
'Bradford',
colour.sRGB_COLOURSPACE.transfer_function))
print('\n')
__status__ = 'Production'
__all__ = [
'POINTER_GAMUT_DATA', 'POINTER_GAMUT_BOUNDARIES', 'pointer_gamut_visual',
'pointer_gamut_boundaries_visual', 'pointer_gamut_hull_visual'
]
POINTER_GAMUT_DATA = Lab_to_XYZ(LCHab_to_Lab(POINTER_GAMUT_DATA),
POINTER_GAMUT_ILLUMINANT)
"""
Pointer's Gamut data converted to *CIE XYZ* tristimulus values.
POINTER_GAMUT_DATA : ndarray
"""
POINTER_GAMUT_BOUNDARIES = xy_to_XYZ(POINTER_GAMUT_BOUNDARIES)
"""
Pointer's Gamut boundaries data converted to *CIE XYZ* tristimulus values.
POINTER_GAMUT_BOUNDARIES : ndarray
"""
def pointer_gamut_visual(reference_colourspace='CIE xyY',
size=4.0,
edge_size=0.5,
uniform_colour=(0.9, 0.9, 0.9),
uniform_opacity=0.8,
uniform_edge_colour=(0.9, 0.9, 0.9),
uniform_edge_opacity=0.8,
parent=None):
message_box('Using "Bradford" CAT.')
print(
colour.adaptation.matrix_chromatic_adaptation_VonKries(
XYZ_w, XYZ_wr, transform="Bradford"))
print("\n")
message_box(
"Computing the chromatic adaptation matrix from "
'the "CIE Standard Illuminant A" to '
'the "CIE Standard Illuminant D Series D65" using the "Von Kries" CAT.')
A = colour.CCS_ILLUMINANTS["CIE 1931 2 Degree Standard Observer"]["A"]
D65 = colour.CCS_ILLUMINANTS["CIE 1931 2 Degree Standard Observer"]["D65"]
print(
colour.adaptation.matrix_chromatic_adaptation_VonKries(
colour.xy_to_XYZ(A), colour.xy_to_XYZ(D65), transform="Von Kries"))
print("\n")
XYZ = np.array([1.14176346, 1.00000000, 0.49815206])
message_box(
f'Adapting given "CIE XYZ" tristimulus values from '
f'the "CIE Standard Illuminant A" to the '
f'"CIE Standard Illuminant D Series D65" using the "Sharp" CAT.\n\n'
f'\t"XYZ": {XYZ}')
print(
colour.chromatic_adaptation(XYZ,
colour.xy_to_XYZ(A),
colour.xy_to_XYZ(D65),
transform="Sharp"))
print(
import colour
from colour.utilities import message_box
message_box('"CIE 1994" Chromatic Adaptation Model Computations')
XYZ_1 = np.array([0.2800, 0.2126, 0.0527])
xy_o1 = np.array([0.4476, 0.4074])
xy_o2 = np.array([0.3127, 0.3290])
Y_o = 20
E_o1 = 1000
E_o2 = 1000
message_box(('Computing chromatic adaptation using "CIE 1994" chromatic '
'adaptation model.\n'
'\n\t"XYZ_1":\n\t\t{0}\n\t"xy_o1":\n\t\t{1}\n\t"xy_o2":\n\t\t{2}'
'\n\t"Y_o":\n\t\t{3}\n\t"E_o1":\n\t\t{4}'
'\n\t"E_o2":\n\t\t{5}\n\n'
'Warning: The input domain and output range of that definition '
'are non standard!'.format(XYZ_1, xy_o1, xy_o2, Y_o, E_o1, E_o2)))
print(
colour.chromatic_adaptation(
XYZ_1,
colour.xy_to_XYZ(xy_o1),
colour.xy_to_XYZ(xy_o2),
method='CIE 1994',
Y_o=Y_o,
E_o1=E_o1,
E_o2=E_o2))
print(
colour.adaptation.chromatic_adaptation_CIE1994(XYZ_1 * 100.0, xy_o1, xy_o2,
Y_o, E_o1, E_o2) / 100.0)
import colour
from colour.utilities.verbose import message_box
message_box('Chromatic Adaptation Computations')
XYZ1 = (1.09923822, 1.000, 0.35445412)
XYZ2 = (0.96907232, 1.000, 1.121792157)
message_box(('Computing the chromatic adaptation matrix from two source '
'"CIE XYZ" matrices, default CAT is "CAT02".\n'
'\n\t"XYZ1":\n\t\t{0}\n\t"XYZ2":\n\t\t{1}'.format(XYZ1, XYZ2)))
print(colour.chromatic_adaptation_matrix(XYZ1, XYZ2))
print('\n')
message_box('Using "Bradford" CAT.')
print(colour.chromatic_adaptation_matrix(XYZ1, XYZ2, method='Bradford'))
print('\n')
message_box(('Computing the chromatic adaptation matrix from '
'"CIE Standard Illuminant A" to '
'"CIE Standard Illuminant D Series D60" using "Von Kries" CAT.'))
A = colour.ILLUMINANTS['CIE 1931 2 Degree Standard Observer']['A']
D60 = colour.ILLUMINANTS['CIE 1931 2 Degree Standard Observer']['D60']
print(colour.chromatic_adaptation_matrix(
colour.xy_to_XYZ(A),
colour.xy_to_XYZ(D60),
method='Von Kries'))
