def test_domain_range_scale_LCHab_to_Lab(self):
"""
Tests :func:`colour.models.cie_lab.LCHab_to_Lab` definition domain and
range scale support.
"""
LCHab = np.array([41.52787529, 59.12425901, 27.08848784])
Lab = LCHab_to_Lab(LCHab)
d_r = (('reference', 1, 1), (1, np.array([0.01, 0.01, 1 / 360]), 0.01),
(100, np.array([1, 1, 1 / 3.6]), 1))
for scale, factor_a, factor_b in d_r:
with domain_range_scale(scale):
np.testing.assert_almost_equal(
LCHab_to_Lab(LCHab * factor_a), Lab * factor_b, decimal=7)
def is_within_pointer_gamut(XYZ, tolerance=None):
"""
Returns if given *CIE XYZ* tristimulus values are within Pointer's Gamut
volume.
Parameters
----------
XYZ : array_like
*CIE XYZ* tristimulus values.
tolerance : numeric, optional
Tolerance allowed in the inside-triangle check.
Returns
-------
bool
Is within Pointer's Gamut.
Notes
-----
- Input *CIE XYZ* tristimulus values are in domain [0, 1].
Examples
--------
>>> import numpy as np
>>> is_within_pointer_gamut(np.array([0.3205, 0.4131, 0.5100]))
array(True, dtype=bool)
>>> a = np.array([[0.3205, 0.4131, 0.5100], [0.0005, 0.0031, 0.0010]])
>>> is_within_pointer_gamut(a)
array([ True, False], dtype=bool)
"""
XYZ_p = Lab_to_XYZ(
LCHab_to_Lab(POINTER_GAMUT_DATA), POINTER_GAMUT_ILLUMINANT)
return is_within_mesh_volume(XYZ, XYZ_p, tolerance)
def test_n_dimensional_LCHab_to_Lab(self):
"""
Tests :func:`colour.models.cie_lab.LCHab_to_Lab` definition
n-dimensional arrays support.
"""
LCHab = np.array([41.52787529, 59.12425901, 27.08848784])
Lab = LCHab_to_Lab(LCHab)
LCHab = np.tile(LCHab, (6, 1))
Lab = np.tile(Lab, (6, 1))
np.testing.assert_almost_equal(LCHab_to_Lab(LCHab), Lab, decimal=7)
LCHab = np.reshape(LCHab, (2, 3, 3))
Lab = np.reshape(Lab, (2, 3, 3))
np.testing.assert_almost_equal(LCHab_to_Lab(LCHab), Lab, decimal=7)
def test_n_dimensional_LCHab_to_Lab(self):
"""
Tests :func:`colour.models.cie_lab.LCHab_to_Lab` definition
n-dimensional arrays support.
"""
LCHab = np.array([37.98562910, 24.03190365, 190.58415972])
Lab = np.array([37.98562910, -23.62302887, -4.41417036])
np.testing.assert_almost_equal(LCHab_to_Lab(LCHab), Lab, decimal=7)
LCHab = np.tile(LCHab, (6, 1))
Lab = np.tile(Lab, (6, 1))
np.testing.assert_almost_equal(LCHab_to_Lab(LCHab), Lab, decimal=7)
LCHab = np.reshape(LCHab, (2, 3, 3))
Lab = np.reshape(Lab, (2, 3, 3))
np.testing.assert_almost_equal(LCHab_to_Lab(LCHab), Lab, decimal=7)
def test_n_dimensional_LCHab_to_Lab(self):
"""
Tests :func:`colour.models.cie_lab.LCHab_to_Lab` definition
n-dimensional arrays support.
"""
LCHab = np.array([37.98562910, 24.03845422, 190.58923377])
Lab = np.array([37.98562910, -23.62907688, -4.41746615])
np.testing.assert_almost_equal(LCHab_to_Lab(LCHab), Lab, decimal=7)
LCHab = np.tile(LCHab, (6, 1))
Lab = np.tile(Lab, (6, 1))
np.testing.assert_almost_equal(LCHab_to_Lab(LCHab), Lab, decimal=7)
LCHab = np.reshape(LCHab, (2, 3, 3))
Lab = np.reshape(Lab, (2, 3, 3))
np.testing.assert_almost_equal(LCHab_to_Lab(LCHab), Lab, decimal=7)
def test_LCHab_to_Lab(self):
"""
Tests :func:`colour.models.cie_lab.LCHab_to_Lab` definition.
"""
np.testing.assert_almost_equal(
LCHab_to_Lab(np.array([41.52787529, 59.12425901, 27.08848784])),
np.array([41.52787529, 52.63858304, 26.92317922]),
decimal=7)
np.testing.assert_almost_equal(
LCHab_to_Lab(np.array([55.11636304, 51.42135412, 143.03889556])),
np.array([55.11636304, -41.08791787, 30.91825778]),
decimal=7)
np.testing.assert_almost_equal(
LCHab_to_Lab(np.array([29.80565520, 52.32945383, 292.49133666])),
np.array([29.80565520, 20.01830466, -48.34913874]),
decimal=7)
def test_LCHab_to_Lab(self):
"""
Tests :func:`colour.models.cie_lab.LCHab_to_Lab` definition.
"""
np.testing.assert_almost_equal(
LCHab_to_Lab(np.array([37.98562910, 24.03845422, 190.58923377])),
np.array([37.98562910, -23.62907688, -4.41746615]),
decimal=7)
np.testing.assert_almost_equal(
LCHab_to_Lab(np.array([65.70971880, 56.17077461, 42.27159870])),
np.array([65.70971880, 41.56438554, 37.78303554]),
decimal=7)
np.testing.assert_almost_equal(
LCHab_to_Lab(np.array([50.86223896, 38.51719507, 31.72647736])),
np.array([50.86223896, 32.76150086, 20.25483590]),
decimal=7)
def test_LCHab_to_Lab(self):
"""
Tests :func:`colour.models.cie_lab.LCHab_to_Lab` definition.
"""
np.testing.assert_almost_equal(
LCHab_to_Lab(np.array([100, 21.57210357, 272.2281935])),
np.array([100., 0.83871284, -21.55579303]),
decimal=7)
np.testing.assert_almost_equal(
LCHab_to_Lab(np.array([100, 426.67945353, 72.39590835])),
np.array([100., 129.04406346, 406.69765889]),
decimal=7)
np.testing.assert_almost_equal(
LCHab_to_Lab(np.array([100, 74.05216981, 276.45318193])),
np.array([100., 8.32281957, -73.58297716]),
decimal=7)
def test_LCHab_to_Lab(self):
"""
Tests :func:`colour.models.cie_lab.LCHab_to_Lab` definition.
"""
np.testing.assert_almost_equal(
LCHab_to_Lab(np.array([37.98562910, 24.03190365, 190.58415972])),
np.array([37.98562910, -23.62302887, -4.41417036]),
decimal=7)
np.testing.assert_almost_equal(
LCHab_to_Lab(np.array([65.70971880, 56.18154795, 42.26641468])),
np.array([65.70971880, 41.57577646, 37.78652063]),
decimal=7)
np.testing.assert_almost_equal(
LCHab_to_Lab(np.array([50.86223896, 38.52678179, 31.72327940])),
np.array([50.86223896, 32.77078577, 20.25804815]),
decimal=7)
def test_nan_LCHab_to_Lab(self):
"""
Tests :func:`colour.models.cie_lab.LCHab_to_Lab` definition nan
support.
"""
cases = [-1.0, 0.0, 1.0, -np.inf, np.inf, np.nan]
cases = set(permutations(cases * 3, r=3))
for case in cases:
LCHab = np.array(case)
LCHab_to_Lab(LCHab)
def highlights_recovery_LCHab(RGB,
threshold=None,
RGB_colourspace=sRGB_COLOURSPACE):
"""
Performs highlights recovery in *CIE L\\*C\\*Hab* colourspace.
Parameters
----------
RGB : array_like
*RGB* colourspace array.
threshold : numeric, optional
Threshold for highlights selection, automatically computed
if not given.
RGB_colourspace : RGB_Colourspace, optional
Working *RGB* colourspace to perform the *CIE L\\*C\\*Hab* to and from.
Returns
-------
ndarray
Highlights recovered *RGB* colourspace array.
"""
L, _C, H = tsplit(
Lab_to_LCHab(
XYZ_to_Lab(
RGB_to_XYZ(RGB, RGB_colourspace.whitepoint,
RGB_colourspace.whitepoint,
RGB_colourspace.RGB_to_XYZ_matrix),
RGB_colourspace.whitepoint)))
_L_c, C_c, _H_c = tsplit(
Lab_to_LCHab(
XYZ_to_Lab(
RGB_to_XYZ(np.clip(RGB, 0,
threshold), RGB_colourspace.whitepoint,
RGB_colourspace.whitepoint,
RGB_colourspace.RGB_to_XYZ_matrix),
RGB_colourspace.whitepoint)))
return XYZ_to_RGB(
Lab_to_XYZ(LCHab_to_Lab(tstack([L, C_c, H])),
RGB_colourspace.whitepoint), RGB_colourspace.whitepoint,
RGB_colourspace.whitepoint, RGB_colourspace.XYZ_to_RGB_matrix)
def is_within_pointer_gamut(XYZ: ArrayLike,
tolerance: Optional[Floating] = None) -> NDArray:
"""
Return whether given *CIE XYZ* tristimulus values are within Pointer's
Gamut volume.
Parameters
----------
XYZ
*CIE XYZ* tristimulus values.
tolerance
Tolerance allowed in the inside-triangle check.
Returns
-------
:class:`numpy.ndarray`
Wether given *CIE XYZ* tristimulus values are within Pointer's Gamut
volume.
Notes
-----
+------------+-----------------------+---------------+
| **Domain** | **Scale - Reference** | **Scale - 1** |
+============+=======================+===============+
| ``XYZ`` | [0, 1] | [0, 1] |
+------------+-----------------------+---------------+
Examples
--------
>>> import numpy as np
>>> is_within_pointer_gamut(np.array([0.3205, 0.4131, 0.5100]))
array(True, dtype=bool)
>>> a = np.array([[0.3205, 0.4131, 0.5100], [0.0005, 0.0031, 0.0010]])
>>> is_within_pointer_gamut(a)
array([ True, False], dtype=bool)
"""
XYZ_p = Lab_to_XYZ(LCHab_to_Lab(DATA_POINTER_GAMUT_VOLUME),
CCS_ILLUMINANT_POINTER_GAMUT)
return is_within_mesh_volume(XYZ, XYZ_p, tolerance)
def RGB_colourspaces_CIE_1931_chromaticity_diagram_plot(
colourspaces=None,
cmfs='CIE 1931 2 Degree Standard Observer',
**kwargs):
"""
Plots given *RGB* colourspaces in *CIE 1931 Chromaticity Diagram*.
Parameters
----------
colourspaces : array_like, optional
*RGB* colourspaces to plot.
cmfs : unicode, optional
Standard observer colour matching functions used for diagram bounds.
Other Parameters
----------------
\**kwargs : dict, optional
{:func:`boundaries`, :func:`canvas`, :func:`decorate`,
:func:`display`},
Please refer to the documentation of the previously listed definitions.
show_diagram_colours : bool, optional
{:func:`CIE_1931_chromaticity_diagram_plot`},
Whether to display the chromaticity diagram background colours.
Returns
-------
Figure
Current figure or None.
Examples
--------
>>> c = ['Rec. 709', 'ACEScg', 'S-Gamut']
>>> RGB_colourspaces_CIE_1931_chromaticity_diagram_plot(
... c) # doctest: +SKIP
"""
settings = {'figure_size': (DEFAULT_FIGURE_WIDTH, DEFAULT_FIGURE_WIDTH)}
settings.update(kwargs)
canvas(**settings)
if colourspaces is None:
colourspaces = ('Rec. 709', 'ACEScg', 'S-Gamut', 'Pointer Gamut')
cmfs, name = get_cmfs(cmfs), cmfs
settings = {
'title':
'{0} - {1} - CIE 1931 Chromaticity Diagram'.format(
', '.join(colourspaces), name),
'standalone':
False
}
settings.update(kwargs)
CIE_1931_chromaticity_diagram_plot(**settings)
x_limit_min, x_limit_max = [-0.1], [0.9]
y_limit_min, y_limit_max = [-0.1], [0.9]
settings = {
'colour_cycle_map': 'rainbow',
'colour_cycle_count': len(colourspaces)
}
settings.update(kwargs)
cycle = colour_cycle(**settings)
for colourspace in colourspaces:
if colourspace == 'Pointer Gamut':
xy = np.asarray(POINTER_GAMUT_BOUNDARIES)
alpha_p, colour_p = 0.85, '0.95'
pylab.plot(xy[..., 0],
xy[..., 1],
label='Pointer\'s Gamut',
color=colour_p,
alpha=alpha_p,
linewidth=2)
pylab.plot((xy[-1][0], xy[0][0]), (xy[-1][1], xy[0][1]),
color=colour_p,
alpha=alpha_p,
linewidth=2)
XYZ = Lab_to_XYZ(LCHab_to_Lab(POINTER_GAMUT_DATA),
POINTER_GAMUT_ILLUMINANT)
xy = XYZ_to_xy(XYZ, POINTER_GAMUT_ILLUMINANT)
pylab.scatter(xy[..., 0],
xy[..., 1],
alpha=alpha_p / 2,
color=colour_p,
marker='+')
else:
colourspace, name = get_RGB_colourspace(colourspace), colourspace
r, g, b, _a = next(cycle)
primaries = colourspace.primaries
whitepoint = colourspace.whitepoint
pylab.plot((whitepoint[0], whitepoint[0]),
(whitepoint[1], whitepoint[1]),
color=(r, g, b),
label=colourspace.name,
linewidth=2)
pylab.plot((whitepoint[0], whitepoint[0]),
(whitepoint[1], whitepoint[1]),
'o',
color=(r, g, b),
linewidth=2)
pylab.plot((primaries[0, 0], primaries[1, 0]),
(primaries[0, 1], primaries[1, 1]),
'o-',
color=(r, g, b),
linewidth=2)
pylab.plot((primaries[1, 0], primaries[2, 0]),
(primaries[1, 1], primaries[2, 1]),
'o-',
color=(r, g, b),
linewidth=2)
pylab.plot((primaries[2, 0], primaries[0, 0]),
(primaries[2, 1], primaries[0, 1]),
'o-',
color=(r, g, b),
linewidth=2)
x_limit_min.append(np.amin(primaries[..., 0]) - 0.1)
y_limit_min.append(np.amin(primaries[..., 1]) - 0.1)
x_limit_max.append(np.amax(primaries[..., 0]) + 0.1)
y_limit_max.append(np.amax(primaries[..., 1]) + 0.1)
settings.update({
'legend':
True,
'legend_location':
'upper right',
'x_tighten':
True,
'y_tighten':
True,
'limits': (min(x_limit_min), max(x_limit_max), min(y_limit_min),
max(y_limit_max)),
'standalone':
True
})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
def RGB_colourspaces_CIE_1976_UCS_chromaticity_diagram_plot(
colourspaces=None,
cmfs='CIE 1931 2 Degree Standard Observer',
**kwargs):
"""
Plots given *RGB* colourspaces in *CIE 1976 UCS Chromaticity Diagram*.
Parameters
----------
colourspaces : array_like, optional
*RGB* colourspaces to plot.
cmfs : unicode, optional
Standard observer colour matching functions used for diagram bounds.
Other Parameters
----------------
\**kwargs : dict, optional
{:func:`boundaries`, :func:`canvas`, :func:`decorate`,
:func:`display`},
Please refer to the documentation of the previously listed definitions.
show_diagram_colours : bool, optional
{:func:`CIE_1976_UCS_chromaticity_diagram_plot`},
Whether to display the chromaticity diagram background colours.
Returns
-------
Figure
Current figure or None.
Examples
--------
>>> c = ['Rec. 709', 'ACEScg', 'S-Gamut']
>>> RGB_colourspaces_CIE_1976_UCS_chromaticity_diagram_plot(
... c) # doctest: +SKIP
"""
settings = {'figure_size': (DEFAULT_FIGURE_WIDTH, DEFAULT_FIGURE_WIDTH)}
settings.update(kwargs)
canvas(**settings)
if colourspaces is None:
colourspaces = ('Rec. 709', 'ACEScg', 'S-Gamut', 'Pointer Gamut')
cmfs, name = get_cmfs(cmfs), cmfs
illuminant = DEFAULT_PLOTTING_ILLUMINANT
settings = {
'title':
'{0} - {1} - CIE 1976 UCS Chromaticity Diagram'.format(
', '.join(colourspaces), name),
'standalone':
False
}
settings.update(kwargs)
CIE_1976_UCS_chromaticity_diagram_plot(**settings)
x_limit_min, x_limit_max = [-0.1], [0.7]
y_limit_min, y_limit_max = [-0.1], [0.7]
settings = {
'colour_cycle_map': 'rainbow',
'colour_cycle_count': len(colourspaces)
}
settings.update(kwargs)
cycle = colour_cycle(**settings)
for colourspace in colourspaces:
if colourspace == 'Pointer Gamut':
uv = Luv_to_uv(
XYZ_to_Luv(xy_to_XYZ(POINTER_GAMUT_BOUNDARIES), illuminant),
illuminant)
alpha_p, colour_p = 0.85, '0.95'
pylab.plot(uv[..., 0],
uv[..., 1],
label='Pointer\'s Gamut',
color=colour_p,
alpha=alpha_p,
linewidth=2)
pylab.plot((uv[-1][0], uv[0][0]), (uv[-1][1], uv[0][1]),
color=colour_p,
alpha=alpha_p,
linewidth=2)
XYZ = Lab_to_XYZ(LCHab_to_Lab(POINTER_GAMUT_DATA),
POINTER_GAMUT_ILLUMINANT)
uv = Luv_to_uv(XYZ_to_Luv(XYZ, illuminant), illuminant)
pylab.scatter(uv[..., 0],
uv[..., 1],
alpha=alpha_p / 2,
color=colour_p,
marker='+')
else:
colourspace, name = get_RGB_colourspace(colourspace), colourspace
r, g, b, _a = next(cycle)
# RGB colourspaces such as *ACES2065-1* have primaries with
# chromaticity coordinates set to 0 thus we prevent nan from being
# yield by zero division in later colour transformations.
P = np.where(colourspace.primaries == 0, EPSILON,
colourspace.primaries)
P = Luv_to_uv(XYZ_to_Luv(xy_to_XYZ(P), illuminant), illuminant)
W = Luv_to_uv(
XYZ_to_Luv(xy_to_XYZ(colourspace.whitepoint), illuminant),
illuminant)
pylab.plot((W[0], W[0]), (W[1], W[1]),
color=(r, g, b),
label=colourspace.name,
linewidth=2)
pylab.plot((W[0], W[0]), (W[1], W[1]),
'o',
color=(r, g, b),
linewidth=2)
pylab.plot((P[0, 0], P[1, 0]), (P[0, 1], P[1, 1]),
'o-',
color=(r, g, b),
linewidth=2)
pylab.plot((P[1, 0], P[2, 0]), (P[1, 1], P[2, 1]),
'o-',
color=(r, g, b),
linewidth=2)
pylab.plot((P[2, 0], P[0, 0]), (P[2, 1], P[0, 1]),
'o-',
color=(r, g, b),
linewidth=2)
x_limit_min.append(np.amin(P[..., 0]) - 0.1)
y_limit_min.append(np.amin(P[..., 1]) - 0.1)
x_limit_max.append(np.amax(P[..., 0]) + 0.1)
y_limit_max.append(np.amax(P[..., 1]) + 0.1)
settings.update({
'legend':
True,
'legend_location':
'upper right',
'x_tighten':
True,
'y_tighten':
True,
'limits': (min(x_limit_min), max(x_limit_max), min(y_limit_min),
max(y_limit_max)),
'standalone':
True
})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
def plot_pointer_gamut(method='CIE 1931', **kwargs):
"""
Plots *Pointer's Gamut* according to given method.
Parameters
----------
method : unicode, optional
**{'CIE 1931', 'CIE 1960 UCS', 'CIE 1976 UCS'}**,
Plotting method.
Other Parameters
----------------
\\**kwargs : dict, optional
{:func:`colour.plotting.artist`, :func:`colour.plotting.render`},
Please refer to the documentation of the previously listed definitions.
Returns
-------
tuple
Current figure and axes.
Examples
--------
>>> plot_pointer_gamut() # doctest: +SKIP
.. image:: ../_static/Plotting_Plot_Pointer_Gamut.png
:align: center
:alt: plot_pointer_gamut
"""
settings = {'uniform': True}
settings.update(kwargs)
figure, axes = artist(**settings)
method = method.upper()
if method == 'CIE 1931':
def XYZ_to_ij(XYZ, *args):
"""
Converts given *CIE XYZ* tristimulus values to *ij* chromaticity
coordinates.
"""
return XYZ_to_xy(XYZ, *args)
def xy_to_ij(xy):
"""
Converts given *xy* chromaticity coordinates to *ij* chromaticity
coordinates.
"""
return xy
elif method == 'CIE 1960 UCS':
def XYZ_to_ij(XYZ, *args):
"""
Converts given *CIE XYZ* tristimulus values to *ij* chromaticity
coordinates.
"""
return UCS_to_uv(XYZ_to_UCS(XYZ))
def xy_to_ij(xy):
"""
Converts given *xy* chromaticity coordinates to *ij* chromaticity
coordinates.
"""
return xy_to_UCS_uv(xy)
elif method == 'CIE 1976 UCS':
def XYZ_to_ij(XYZ, *args):
"""
Converts given *CIE XYZ* tristimulus values to *ij* chromaticity
coordinates.
"""
return Luv_to_uv(XYZ_to_Luv(XYZ, *args), *args)
def xy_to_ij(xy):
"""
Converts given *xy* chromaticity coordinates to *ij* chromaticity
coordinates.
"""
return xy_to_Luv_uv(xy)
else:
raise ValueError(
'Invalid method: "{0}", must be one of '
'{\'CIE 1931\', \'CIE 1960 UCS\', \'CIE 1976 UCS\'}'.format(
method))
ij = xy_to_ij(as_float_array(POINTER_GAMUT_BOUNDARIES))
alpha_p = COLOUR_STYLE_CONSTANTS.opacity.high
colour_p = COLOUR_STYLE_CONSTANTS.colour.darkest
axes.plot(ij[..., 0],
ij[..., 1],
label='Pointer\'s Gamut',
color=colour_p,
alpha=alpha_p)
axes.plot((ij[-1][0], ij[0][0]), (ij[-1][1], ij[0][1]),
color=colour_p,
alpha=alpha_p)
XYZ = Lab_to_XYZ(LCHab_to_Lab(POINTER_GAMUT_DATA),
POINTER_GAMUT_ILLUMINANT)
ij = XYZ_to_ij(XYZ, POINTER_GAMUT_ILLUMINANT)
axes.scatter(ij[..., 0],
ij[..., 1],
alpha=alpha_p / 2,
color=colour_p,
marker='+')
settings.update({'axes': axes})
settings.update(kwargs)
return render(**settings)
def RGB_colourspaces_CIE_1960_UCS_chromaticity_diagram_plot(
colourspaces=None,
cmfs='CIE 1931 2 Degree Standard Observer',
**kwargs):
"""
Plots given *RGB* colourspaces in *CIE 1960 UCS Chromaticity Diagram*.
Parameters
----------
colourspaces : array_like, optional
*RGB* colourspaces to plot.
cmfs : unicode, optional
Standard observer colour matching functions used for diagram bounds.
\**kwargs : dict, optional
Keywords arguments.
Returns
-------
bool
Definition success.
Examples
--------
>>> c = ['Rec. 709', 'ACEScg', 'S-Gamut']
>>> RGB_colourspaces_CIE_1960_UCS_chromaticity_diagram_plot(
... c) # doctest: +SKIP
True
"""
settings = {'figure_size': (DEFAULT_FIGURE_WIDTH, DEFAULT_FIGURE_WIDTH)}
settings.update(kwargs)
canvas(**settings)
if colourspaces is None:
colourspaces = ('Rec. 709', 'ACEScg', 'S-Gamut', 'Pointer Gamut')
cmfs, name = get_cmfs(cmfs), cmfs
settings = {
'title': '{0} - {1} - CIE 1960 UCS Chromaticity Diagram'.format(
', '.join(colourspaces), name),
'standalone': False}
settings.update(kwargs)
CIE_1960_UCS_chromaticity_diagram_plot(**settings)
x_limit_min, x_limit_max = [-0.1], [0.7]
y_limit_min, y_limit_max = [-0.2], [0.6]
settings = {'colour_cycle_map': 'rainbow',
'colour_cycle_count': len(colourspaces)}
settings.update(kwargs)
cycle = colour_cycle(**settings)
for colourspace in colourspaces:
if colourspace == 'Pointer Gamut':
uv = UCS_to_uv(XYZ_to_UCS(xy_to_XYZ(POINTER_GAMUT_BOUNDARIES)))
alpha_p, colour_p = 0.85, '0.95'
pylab.plot(uv[..., 0],
uv[..., 1],
label='Pointer\'s Gamut',
color=colour_p,
alpha=alpha_p,
linewidth=2)
pylab.plot((uv[-1][0], uv[0][0]),
(uv[-1][1], uv[0][1]),
color=colour_p,
alpha=alpha_p,
linewidth=2)
XYZ = Lab_to_XYZ(LCHab_to_Lab(POINTER_GAMUT_DATA),
POINTER_GAMUT_ILLUMINANT)
uv = UCS_to_uv(XYZ_to_UCS(XYZ))
pylab.scatter(uv[..., 0],
uv[..., 1],
alpha=alpha_p / 2,
color=colour_p,
marker='+')
else:
colourspace, name = get_RGB_colourspace(colourspace), colourspace
r, g, b, _a = next(cycle)
# RGB colourspaces such as *ACES2065-1* have primaries with
# chromaticity coordinates set to 0 thus we prevent nan from being
# yield by zero division in later colour transformations.
primaries = np.where(colourspace.primaries == 0,
EPSILON,
colourspace.primaries)
primaries = UCS_to_uv(XYZ_to_UCS(xy_to_XYZ(primaries)))
whitepoint = UCS_to_uv(XYZ_to_UCS(xy_to_XYZ(
colourspace.whitepoint)))
pylab.plot((whitepoint[0], whitepoint[0]),
(whitepoint[1], whitepoint[1]),
color=(r, g, b),
label=colourspace.name,
linewidth=2)
pylab.plot((whitepoint[0], whitepoint[0]),
(whitepoint[1], whitepoint[1]),
'o',
color=(r, g, b),
linewidth=2)
pylab.plot((primaries[0, 0], primaries[1, 0]),
(primaries[0, 1], primaries[1, 1]),
'o-',
color=(r, g, b),
linewidth=2)
pylab.plot((primaries[1, 0], primaries[2, 0]),
(primaries[1, 1], primaries[2, 1]),
'o-',
color=(r, g, b),
linewidth=2)
pylab.plot((primaries[2, 0], primaries[0, 0]),
(primaries[2, 1], primaries[0, 1]),
'o-',
color=(r, g, b),
linewidth=2)
x_limit_min.append(np.amin(primaries[..., 0]) - 0.1)
y_limit_min.append(np.amin(primaries[..., 1]) - 0.1)
x_limit_max.append(np.amax(primaries[..., 0]) + 0.1)
y_limit_max.append(np.amax(primaries[..., 1]) + 0.1)
settings.update({
'legend': True,
'legend_location': 'upper right',
'x_tighten': True,
'y_tighten': True,
'limits': (min(x_limit_min), max(x_limit_max),
min(y_limit_min), max(y_limit_max)),
'standalone': True})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
