def delta_E_DIN99(Lab_1, Lab_2, textiles=False):
"""
Returns the difference :math:`\\Delta E_{DIN99}` between two given
*CIE L\\*a\\*b\\** colourspace arrays using *DIN99* formula.
Parameters
----------
Lab_1 : array_like
*CIE L\\*a\\*b\\** colourspace array 1.
Lab_2 : array_like
*CIE L\\*a\\*b\\** colourspace array 2.
Returns
-------
numeric or ndarray
Colour difference :math:`\\Delta E_{DIN99}`.
Notes
-----
+------------+-----------------------+-------------------+
| **Domain** | **Scale - Reference** | **Scale - 1** |
+============+=======================+===================+
| ``Lab_1`` | ``L_1`` : [0, 100] | ``L_1`` : [0, 1] |
| | | |
| | ``a_1`` : [-100, 100] | ``a_1`` : [-1, 1] |
| | | |
| | ``b_1`` : [-100, 100] | ``b_1`` : [-1, 1] |
+------------+-----------------------+-------------------+
| ``Lab_2`` | ``L_2`` : [0, 100] | ``L_2`` : [0, 1] |
| | | |
| | ``a_2`` : [-100, 100] | ``a_2`` : [-1, 1] |
| | | |
| | ``b_2`` : [-100, 100] | ``b_2`` : [-1, 1] |
+------------+-----------------------+-------------------+
References
----------
:cite:`ASTMInternational2007`
Examples
--------
>>> import numpy as np
>>> Lab_1 = np.array([60.2574, -34.0099, 36.2677])
>>> Lab_2 = np.array([60.4626, -34.1751, 39.4387])
>>> delta_E_DIN99(Lab_1, Lab_2) # doctest: +ELLIPSIS
1.1772166...
"""
k_E = 2 if textiles else 1
k_CH = 0.5 if textiles else 1
factor = 100 if get_domain_range_scale() == '1' else 1
d_E = euclidean_distance(
Lab_to_DIN99(Lab_1, k_E, k_CH) * factor,
Lab_to_DIN99(Lab_2, k_E, k_CH) * factor)
return d_E
def test_domain_range_scale_Lab_to_DIN99(self):
"""
Test :func:`colour.models.din99.Lab_to_DIN99` definition domain and
range scale support.
"""
Lab = np.array([41.52787529, 52.63858304, 26.92317922])
Lab_99 = Lab_to_DIN99(Lab)
Lab_99_b = Lab_to_DIN99(Lab, method="DIN99b")
Lab_99_c = Lab_to_DIN99(Lab, method="DIN99c")
Lab_99_d = Lab_to_DIN99(Lab, method="DIN99d")
d_r = (("reference", 1), ("1", 0.01), ("100", 1))
for scale, factor in d_r:
with domain_range_scale(scale):
np.testing.assert_almost_equal(
Lab_to_DIN99(Lab * factor), Lab_99 * factor, decimal=7
)
np.testing.assert_almost_equal(
Lab_to_DIN99((Lab * factor), method="DIN99b"),
Lab_99_b * factor,
decimal=7,
)
np.testing.assert_almost_equal(
Lab_to_DIN99((Lab * factor), method="DIN99c"),
Lab_99_c * factor,
decimal=7,
)
np.testing.assert_almost_equal(
Lab_to_DIN99((Lab * factor), method="DIN99d"),
Lab_99_d * factor,
decimal=7,
)
def test_domain_range_scale_Lab_to_DIN99(self):
"""
Tests :func:`colour.models.din99.Lab_to_DIN99` definition domain and
range scale support.
"""
Lab = np.array([41.52787529, 52.63858304, 26.92317922])
Lab_99 = Lab_to_DIN99(Lab)
d_r = (('reference', 1), (1, 0.01), (100, 1))
for scale, factor in d_r:
with domain_range_scale(scale):
np.testing.assert_almost_equal(Lab_to_DIN99(Lab * factor),
Lab_99 * factor,
decimal=7)
def test_n_dimensional_Lab_to_DIN99(self):
"""
Tests :func:`colour.models.din99.Lab_to_DIN99` definition n-dimensional
support.
"""
Lab = np.array([41.52787529, 52.63858304, 26.92317922])
Lab_99 = Lab_to_DIN99(Lab)
Lab = np.tile(Lab, (6, 1))
Lab_99 = np.tile(Lab_99, (6, 1))
np.testing.assert_almost_equal(Lab_to_DIN99(Lab), Lab_99, decimal=7)
Lab = np.reshape(Lab, (2, 3, 3))
Lab_99 = np.reshape(Lab_99, (2, 3, 3))
np.testing.assert_almost_equal(Lab_to_DIN99(Lab), Lab_99, decimal=7)
def test_Lab_to_DIN99(self):
"""
Tests :func:`colour.models.din99.Lab_to_DIN99` definition.
"""
np.testing.assert_almost_equal(
Lab_to_DIN99(np.array([41.52787529, 52.63858304, 26.92317922])),
np.array([53.22821988, 28.41634656, 3.89839552]),
decimal=7)
np.testing.assert_almost_equal(
Lab_to_DIN99(np.array([55.11636304, -41.08791787, 30.91825778])),
np.array([66.08943912, -17.35290106, 16.09690691]),
decimal=7)
np.testing.assert_almost_equal(
Lab_to_DIN99(np.array([29.80565520, 20.01830466, -48.34913874])),
np.array([40.71533366, 3.48714163, -21.45321411]),
decimal=7)
def test_Lab_to_DIN99(self):
"""Test :func:`colour.models.din99.Lab_to_DIN99` definition."""
np.testing.assert_almost_equal(
Lab_to_DIN99(np.array([41.52787529, 52.63858304, 26.92317922])),
np.array([53.22821988, 28.41634656, 3.89839552]),
decimal=7,
)
np.testing.assert_almost_equal(
Lab_to_DIN99(np.array([55.11636304, -41.08791787, 30.91825778])),
np.array([66.08943912, -17.35290106, 16.09690691]),
decimal=7,
)
np.testing.assert_almost_equal(
Lab_to_DIN99(np.array([29.80565520, 20.01830466, -48.34913874])),
np.array([40.71533366, 3.48714163, -21.45321411]),
decimal=7,
)
np.testing.assert_almost_equal(
Lab_to_DIN99(
np.array([41.52787529, 52.63858304, 26.92317922]),
method="DIN99b",
),
np.array([45.58303137, 34.71824493, 17.61622149]),
decimal=7,
)
np.testing.assert_almost_equal(
Lab_to_DIN99(
np.array([41.52787529, 52.63858304, 26.92317922]),
method="DIN99c",
),
np.array([45.40284208, 32.75074741, 15.74603532]),
decimal=7,
)
np.testing.assert_almost_equal(
Lab_to_DIN99(
np.array([41.52787529, 52.63858304, 26.92317922]),
method="DIN99d",
),
np.array([45.31204747, 31.42106716, 14.17004652]),
decimal=7,
)
def XYZ_to_colourspace_model(XYZ, illuminant, model, **kwargs):
"""
Converts from *CIE XYZ* tristimulus values to given colourspace model.
Parameters
----------
XYZ : array_like
*CIE XYZ* tristimulus values.
illuminant : array_like
*CIE XYZ* tristimulus values *illuminant* *xy* chromaticity
coordinates.
model : unicode
**{'CIE XYZ', 'CIE xyY', 'CIE xy', 'CIE Lab', 'CIE LCHab', 'CIE Luv',
'CIE Luv uv', 'CIE LCHuv', 'CIE UCS', 'CIE UCS uv', 'CIE UVW',
'DIN 99', 'Hunter Lab', 'Hunter Rdab', 'IPT', 'JzAzBz, 'OSA UCS',
'hdr-CIELAB', 'hdr-IPT'}**,
Colourspace model to convert the *CIE XYZ* tristimulus values to.
Other Parameters
----------------
\\**kwargs : dict, optional
Keywords arguments.
Returns
-------
ndarray
Colourspace model values.
Examples
--------
>>> import numpy as np
>>> XYZ = np.array([0.20654008, 0.12197225, 0.05136952])
>>> W = np.array([0.31270, 0.32900])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'CIE XYZ')
array([ 0.2065400..., 0.1219722..., 0.0513695...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'CIE xyY')
array([ 0.5436955..., 0.3210794..., 0.1219722...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'CIE xy')
array([ 0.5436955..., 0.3210794...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'CIE Lab')
array([ 0.4152787..., 0.5263858..., 0.2692317...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'CIE LCHab')
array([ 0.4152787..., 0.5912425..., 0.0752458...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'CIE Luv')
array([ 0.4152787..., 0.9683626..., 0.1775210...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'CIE Luv uv')
array([ 0.3772021..., 0.5012026...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'CIE LCHuv')
array([ 0.4152787..., 0.9844997..., 0.0288560...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'CIE UCS uv')
array([ 0.3772021..., 0.3341350...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'CIE UVW')
array([ 0.9455035..., 0.1155536..., 0.4054757...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'DIN 99')
array([ 0.5322822..., 0.2841634..., 0.0389839...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'Hunter Lab')
array([ 0.3492452..., 0.4703302..., 0.1439330...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'Hunter Rdab')
array([ 0.1219722..., 0.5709032..., 0.1747109...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'IPT')
array([ 0.3842619..., 0.3848730..., 0.1888683...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'JzAzBz')
array([ 0.0053504..., 0.0092430..., 0.0052600...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'OSA UCS')
array([-0.0300499..., 0.0299713..., -0.0966784...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'hdr-CIELAB')
array([ 0.5187002..., 0.6047633..., 0.3214551...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'hdr-IPT')
array([ 0.4839376..., 0.4244990..., 0.2201954...])
"""
with domain_range_scale(1):
values = None
if model == 'CIE XYZ':
values = XYZ
elif model == 'CIE xyY':
values = XYZ_to_xyY(XYZ, illuminant)
elif model == 'CIE xy':
values = XYZ_to_xy(XYZ, illuminant)
elif model == 'CIE Lab':
values = XYZ_to_Lab(XYZ, illuminant)
elif model == 'CIE LCHab':
values = Lab_to_LCHab(XYZ_to_Lab(XYZ, illuminant))
elif model == 'CIE Luv':
values = XYZ_to_Luv(XYZ, illuminant)
elif model == 'CIE Luv uv':
values = Luv_to_uv(XYZ_to_Luv(XYZ, illuminant), illuminant)
elif model == 'CIE LCHuv':
values = Luv_to_LCHuv(XYZ_to_Luv(XYZ, illuminant))
elif model == 'CIE UCS':
values = XYZ_to_UCS(XYZ)
elif model == 'CIE UCS uv':
values = UCS_to_uv(XYZ_to_UCS(XYZ))
elif model == 'CIE UVW':
values = XYZ_to_UVW(XYZ, illuminant)
elif model == 'DIN 99':
values = Lab_to_DIN99(XYZ_to_Lab(XYZ, illuminant))
elif model == 'Hunter Lab':
values = XYZ_to_Hunter_Lab(XYZ, xy_to_XYZ(illuminant))
elif model == 'Hunter Rdab':
values = XYZ_to_Hunter_Rdab(XYZ, xy_to_XYZ(illuminant))
elif model == 'IPT':
values = XYZ_to_IPT(XYZ)
elif model == 'JzAzBz':
values = XYZ_to_JzAzBz(XYZ)
elif model == 'OSA UCS':
values = XYZ_to_OSA_UCS(XYZ)
elif model == 'hdr-CIELAB':
values = XYZ_to_hdr_CIELab(XYZ, illuminant, **kwargs)
elif model == 'hdr-IPT':
values = XYZ_to_hdr_IPT(XYZ, **kwargs)
if values is None:
raise ValueError(
'"{0}" not found in colourspace models: "{1}".'.format(
model, ', '.join(COLOURSPACE_MODELS)))
return values
def XYZ_to_colourspace_model(XYZ, illuminant, model, **kwargs):
"""
Converts from *CIE XYZ* tristimulus values to given colourspace model.
Parameters
----------
XYZ : array_like
*CIE XYZ* tristimulus values.
illuminant : array_like
Reference *illuminant* *CIE xy* chromaticity coordinates or *CIE xyY*
colourspace array.
model : unicode
**{'CIE XYZ', 'CIE xyY', 'CIE xy', 'CIE Lab', 'CIE LCHab', 'CIE Luv',
'CIE Luv uv', 'CIE LCHuv', 'CIE UCS', 'CIE UCS uv', 'CIE UVW',
'DIN 99', 'Hunter Lab', 'Hunter Rdab', 'IPT', 'JzAzBz, 'OSA UCS',
'hdr-CIELAB', 'hdr-IPT'}**,
Colourspace model to convert the *CIE XYZ* tristimulus values to.
Other Parameters
----------------
\\**kwargs : dict, optional
Keywords arguments.
Returns
-------
ndarray
Colourspace model values.
Warnings
--------
This definition is is deprecated and will be removed in a future release.
:func:`colour.convert` definition should be used instead.
Examples
--------
>>> import numpy as np
>>> XYZ = np.array([0.20654008, 0.12197225, 0.05136952])
>>> W = np.array([0.31270, 0.32900])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'CIE XYZ')
array([ 0.2065400..., 0.1219722..., 0.0513695...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'CIE xyY')
array([ 0.5436955..., 0.3210794..., 0.1219722...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'CIE xy')
array([ 0.5436955..., 0.3210794...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'CIE Lab')
array([ 0.4152787..., 0.5263858..., 0.2692317...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'CIE LCHab')
array([ 0.4152787..., 0.5912425..., 0.0752458...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'CIE Luv')
array([ 0.4152787..., 0.9683626..., 0.1775210...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'CIE Luv uv')
array([ 0.3772021..., 0.5012026...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'CIE LCHuv')
array([ 0.4152787..., 0.9844997..., 0.0288560...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'CIE UCS')
array([ 0.1376933..., 0.1219722..., 0.1053731...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'CIE UCS uv')
array([ 0.3772021..., 0.3341350...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'CIE UVW')
array([ 0.9455035..., 0.1155536..., 0.4054757...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'DIN 99')
array([ 0.5322822..., 0.2841634..., 0.0389839...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'Hunter Lab')
array([ 0.3492452..., 0.4703302..., 0.1439330...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'Hunter Rdab')
array([ 0.1219722..., 0.5709032..., 0.1747109...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'IPT')
array([ 0.3842619..., 0.3848730..., 0.1888683...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'JzAzBz')
array([ 0.0053504..., 0.0092430..., 0.0052600...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'OSA UCS')
array([-0.0300499..., 0.0299713..., -0.0966784...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'hdr-CIELAB')
array([ 0.5187002..., 0.6047633..., 0.3214551...])
>>> XYZ_to_colourspace_model( # doctest: +ELLIPSIS
... XYZ, W, 'hdr-IPT')
array([ 0.4839376..., 0.4244990..., 0.2201954...])
>>> try:
... XYZ_to_colourspace_model(XYZ, W, 'Undefined')
... except ValueError as error:
... print(error)
"Undefined" not found in colourspace models: "CIE XYZ, CIE xyY, CIE Lab, \
CIE LCHab, CIE Luv, CIE Luv uv, CIE LCHuv, CIE UCS, CIE UCS uv, CIE UVW, \
DIN 99, Hunter Lab, Hunter Rdab, IPT, JzAzBz, OSA UCS, hdr-CIELAB, hdr-IPT".
"""
from colour.models import (
Lab_to_DIN99, Lab_to_LCHab, Luv_to_LCHuv, Luv_to_uv, UCS_to_uv,
XYZ_to_IPT, XYZ_to_Hunter_Lab, XYZ_to_Hunter_Rdab, XYZ_to_Lab,
XYZ_to_Luv, XYZ_to_OSA_UCS, XYZ_to_UCS, XYZ_to_UVW, XYZ_to_hdr_CIELab,
XYZ_to_hdr_IPT, XYZ_to_JzAzBz, XYZ_to_xy, XYZ_to_xyY, xy_to_XYZ)
with domain_range_scale(1):
values = None
if model == 'CIE XYZ':
values = XYZ
elif model == 'CIE xyY':
values = XYZ_to_xyY(XYZ, illuminant)
elif model == 'CIE xy':
values = XYZ_to_xy(XYZ, illuminant)
elif model == 'CIE Lab':
values = XYZ_to_Lab(XYZ, illuminant)
elif model == 'CIE LCHab':
values = Lab_to_LCHab(XYZ_to_Lab(XYZ, illuminant))
elif model == 'CIE Luv':
values = XYZ_to_Luv(XYZ, illuminant)
elif model == 'CIE Luv uv':
values = Luv_to_uv(XYZ_to_Luv(XYZ, illuminant), illuminant)
elif model == 'CIE LCHuv':
values = Luv_to_LCHuv(XYZ_to_Luv(XYZ, illuminant))
elif model == 'CIE UCS':
values = XYZ_to_UCS(XYZ)
elif model == 'CIE UCS uv':
values = UCS_to_uv(XYZ_to_UCS(XYZ))
elif model == 'CIE UVW':
values = XYZ_to_UVW(XYZ, illuminant)
elif model == 'DIN 99':
values = Lab_to_DIN99(XYZ_to_Lab(XYZ, illuminant))
elif model == 'Hunter Lab':
values = XYZ_to_Hunter_Lab(XYZ, xy_to_XYZ(illuminant))
elif model == 'Hunter Rdab':
values = XYZ_to_Hunter_Rdab(XYZ, xy_to_XYZ(illuminant))
elif model == 'IPT':
values = XYZ_to_IPT(XYZ)
elif model == 'JzAzBz':
values = XYZ_to_JzAzBz(XYZ)
elif model == 'OSA UCS':
values = XYZ_to_OSA_UCS(XYZ)
elif model == 'hdr-CIELAB':
values = XYZ_to_hdr_CIELab(XYZ, illuminant, **kwargs)
elif model == 'hdr-IPT':
values = XYZ_to_hdr_IPT(XYZ, **kwargs)
if values is None:
raise ValueError(
'"{0}" not found in colourspace models: "{1}".'.format(
model, ', '.join(COLOURSPACE_MODELS)))
return values
def delta_E_DIN99(Lab_1: ArrayLike,
Lab_2: ArrayLike,
textiles: Boolean = False) -> FloatingOrNDArray:
"""
Return the difference :math:`\\Delta E_{DIN99}` between two given
*CIE L\\*a\\*b\\** colourspace arrays using *DIN99* formula.
Parameters
----------
Lab_1
*CIE L\\*a\\*b\\** colourspace array 1.
Lab_2
*CIE L\\*a\\*b\\** colourspace array 2.
textiles
Textiles application specific parametric factors,
:math:`k_E=2,\\ k_{CH}=0.5` weights are used instead of
:math:`k_E=1,\\ k_{CH}=1`.
Returns
-------
:class:`numpy.floating` or :class:`numpy.ndarray`
Colour difference :math:`\\Delta E_{DIN99}`.
Notes
-----
+------------+-----------------------+-------------------+
| **Domain** | **Scale - Reference** | **Scale - 1** |
+============+=======================+===================+
| ``Lab_1`` | ``L_1`` : [0, 100] | ``L_1`` : [0, 1] |
| | | |
| | ``a_1`` : [-100, 100] | ``a_1`` : [-1, 1] |
| | | |
| | ``b_1`` : [-100, 100] | ``b_1`` : [-1, 1] |
+------------+-----------------------+-------------------+
| ``Lab_2`` | ``L_2`` : [0, 100] | ``L_2`` : [0, 1] |
| | | |
| | ``a_2`` : [-100, 100] | ``a_2`` : [-1, 1] |
| | | |
| | ``b_2`` : [-100, 100] | ``b_2`` : [-1, 1] |
+------------+-----------------------+-------------------+
References
----------
:cite:`ASTMInternational2007`
Examples
--------
>>> import numpy as np
>>> Lab_1 = np.array([60.2574, -34.0099, 36.2677])
>>> Lab_2 = np.array([60.4626, -34.1751, 39.4387])
>>> delta_E_DIN99(Lab_1, Lab_2) # doctest: +ELLIPSIS
1.1772166...
"""
k_E = 2 if textiles else 1
k_CH = 0.5 if textiles else 1
factor = 100 if get_domain_range_scale() == "1" else 1
d_E = euclidean_distance(
Lab_to_DIN99(Lab_1, k_E, k_CH) * factor,
Lab_to_DIN99(Lab_2, k_E, k_CH) * factor,
)
return d_E