def test_is_within_mesh_volume(self):
"""Test :func:`colour.volume.mesh.is_within_mesh_volume` definition."""
self.assertTrue(
is_within_mesh_volume(
np.array([0.0005, 0.0031, 0.0010]), self._mesh
)
)
self.assertFalse(
is_within_mesh_volume(
np.array([0.3205, 0.4131, 0.5100]), self._mesh
)
)
self.assertTrue(
is_within_mesh_volume(
np.array([0.0025, 0.0088, 0.0340]), self._mesh
)
)
self.assertFalse(
is_within_mesh_volume(
np.array([0.4325, 0.3788, 0.1034]), self._mesh
)
)
def test_nan_is_within_mesh_volume(self):
"""
Tests :func:`colour.volume.mesh.is_within_mesh_volume` 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:
is_within_mesh_volume(case, self.__mesh)
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_is_within_mesh_volume(self):
"""
Tests :func:`colour.volume.mesh.is_within_mesh_volume` definition
n-dimensional arrays support.
"""
a = np.array([0.0005, 0.0031, 0.0010])
b = is_within_mesh_volume(a, self._mesh)
a = np.tile(a, (6, 1))
b = np.tile(b, 6)
np.testing.assert_almost_equal(is_within_mesh_volume(a, self._mesh), b)
a = np.reshape(a, (2, 3, 3))
b = np.reshape(b, (2, 3))
np.testing.assert_almost_equal(is_within_mesh_volume(a, self._mesh), b)
def test_n_dimensional_is_within_mesh_volume(self):
"""
Tests :func:`colour.volume.mesh.is_within_mesh_volume` definition
n-dimensional arrays support.
"""
a = np.array([0.0005, 0.0031, 0.0010])
b = is_within_mesh_volume(a, self._mesh)
a = np.tile(a, (6, 1))
b = np.tile(b, 6)
np.testing.assert_almost_equal(is_within_mesh_volume(a, self._mesh), b)
a = np.reshape(a, (2, 3, 3))
b = np.reshape(b, (2, 3))
np.testing.assert_almost_equal(is_within_mesh_volume(a, self._mesh), b)
def is_within_visible_spectrum(
XYZ,
interval=10,
cmfs=STANDARD_OBSERVERS_CMFS['CIE 1931 2 Degree Standard Observer'],
illuminant=sd_ones(
STANDARD_OBSERVERS_CMFS['CIE 1931 2 Degree Standard Observer'].
shape),
tolerance=None):
"""
Returns if given *CIE XYZ* tristimulus values are within visible spectrum
volume / given colour matching functions volume.
Parameters
----------
XYZ : array_like
*CIE XYZ* tristimulus values.
interval : int, optional
Wavelength :math:`\\lambda_{i}` range interval used to compute the
pulse waves for the *CIE XYZ* colourspace outer surface.
cmfs : XYZ_ColourMatchingFunctions, optional
Standard observer colour matching functions.
illuminant : SpectralDistribution, optional
Illuminant spectral distribution.
tolerance : numeric, optional
Tolerance allowed in the inside-triangle check.
Returns
-------
bool
Is within visible spectrum.
Notes
-----
+------------+-----------------------+---------------+
| **Domain** | **Scale - Reference** | **Scale - 1** |
+============+=======================+===============+
| ``XYZ`` | [0, 1] | [0, 1] |
+------------+-----------------------+---------------+
Examples
--------
>>> import numpy as np
>>> is_within_visible_spectrum(np.array([0.3205, 0.4131, 0.51]))
array(True, dtype=bool)
>>> a = np.array([[0.3205, 0.4131, 0.51],
... [-0.0005, 0.0031, 0.001]])
>>> is_within_visible_spectrum(a)
array([ True, False], dtype=bool)
"""
key = (interval, hash(cmfs), hash(illuminant))
vertices = _XYZ_OUTER_SURFACE_POINTS_CACHE.get(key)
if vertices is None:
_XYZ_OUTER_SURFACE_POINTS_CACHE[key] = vertices = (XYZ_outer_surface(
interval,
STANDARD_OBSERVERS_CMFS['CIE 1931 2 Degree Standard Observer'],
illuminant))
return is_within_mesh_volume(XYZ, vertices, tolerance)
def is_within_visible_spectrum(
XYZ,
interval=10,
cmfs=STANDARD_OBSERVERS_CMFS['CIE 1931 2 Degree Standard Observer'],
illuminant=sd_ones(STANDARD_OBSERVERS_CMFS[
'CIE 1931 2 Degree Standard Observer'].shape),
tolerance=None):
"""
Returns if given *CIE XYZ* tristimulus values are within visible spectrum
volume / given colour matching functions volume.
Parameters
----------
XYZ : array_like
*CIE XYZ* tristimulus values.
interval : int, optional
Wavelength :math:`\\lambda_{i}` range interval used to compute the
pulse waves for the *CIE XYZ* colourspace outer surface.
cmfs : XYZ_ColourMatchingFunctions, optional
Standard observer colour matching functions.
illuminant : SpectralDistribution, optional
Illuminant spectral distribution.
tolerance : numeric, optional
Tolerance allowed in the inside-triangle check.
Returns
-------
bool
Is within visible spectrum.
Notes
-----
+------------+-----------------------+---------------+
| **Domain** | **Scale - Reference** | **Scale - 1** |
+============+=======================+===============+
| ``XYZ`` | [0, 1] | [0, 1] |
+------------+-----------------------+---------------+
Examples
--------
>>> import numpy as np
>>> is_within_visible_spectrum(np.array([0.3205, 0.4131, 0.51]))
array(True, dtype=bool)
>>> a = np.array([[0.3205, 0.4131, 0.51],
... [-0.0005, 0.0031, 0.001]])
>>> is_within_visible_spectrum(a)
array([ True, False], dtype=bool)
"""
key = (interval, hash(cmfs), hash(illuminant))
vertices = _XYZ_OUTER_SURFACE_POINTS_CACHE.get(key)
if vertices is None:
_XYZ_OUTER_SURFACE_POINTS_CACHE[key] = vertices = (XYZ_outer_surface(
interval,
STANDARD_OBSERVERS_CMFS['CIE 1931 2 Degree Standard Observer'],
illuminant))
return is_within_mesh_volume(XYZ, vertices, tolerance)
def test_is_within_mesh_volume(self):
"""
Tests :func:`colour.volume.mesh.is_within_mesh_volume` definition.
"""
self.assertTrue(
is_within_mesh_volume(np.array([0.0005, 0.0031, 0.0010]),
self.__mesh))
self.assertFalse(
is_within_mesh_volume(np.array([0.3205, 0.4131, 0.5100]),
self.__mesh))
self.assertTrue(
is_within_mesh_volume(np.array([0.0025, 0.0088, 0.0340]),
self.__mesh))
self.assertFalse(
is_within_mesh_volume(np.array([0.4325, 0.3788, 0.1034]),
self.__mesh))
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 is_within_visible_spectrum(XYZ,
cmfs=STANDARD_OBSERVERS_CMFS.get(
'CIE 1931 2 Degree Standard Observer'),
tolerance=None):
"""
Returns if given *CIE XYZ* tristimulus values are within visible spectrum
volume / given colour matching functions volume.
Parameters
----------
XYZ : array_like
*CIE XYZ* tristimulus values.
cmfs : XYZ_ColourMatchingFunctions
Standard observer colour matching functions.
tolerance : numeric, optional
Tolerance allowed in the inside-triangle check.
Returns
-------
bool
Is within visible spectrum.
Notes
-----
- Input *CIE XYZ* tristimulus values are in domain [0, 1].
- This definition requires *scipy* to be installed.
Examples
--------
>>> import numpy as np
>>> is_within_visible_spectrum(np.array([0.3205, 0.4131, 0.51]))
array(True, dtype=bool)
>>> a = np.array([[0.3205, 0.4131, 0.51],
... [-0.0005, 0.0031, 0.001]])
>>> is_within_visible_spectrum(a)
array([ True, False], dtype=bool)
"""
return is_within_mesh_volume(XYZ, cmfs.values, tolerance)
def is_within_visible_spectrum(XYZ,
cmfs=STANDARD_OBSERVERS_CMFS.get(
'CIE 1931 2 Degree Standard Observer'),
tolerance=None):
"""
Returns if given *CIE XYZ* tristimulus values are within visible spectrum
volume / given colour matching functions volume.
Parameters
----------
XYZ : array_like
*CIE XYZ* tristimulus values.
cmfs : XYZ_ColourMatchingFunctions
Standard observer colour matching functions.
tolerance : numeric, optional
Tolerance allowed in the inside-triangle check.
Returns
-------
bool
Is within visible spectrum.
Notes
-----
- Input *CIE XYZ* tristimulus values are in domain [0, 1].
- This definition requires *scipy* to be installed.
Examples
--------
>>> import numpy as np
>>> is_within_visible_spectrum(np.array([0.3205, 0.4131, 0.51]))
array(True, dtype=bool)
>>> a = np.array([[0.3205, 0.4131, 0.51],
... [-0.0005, 0.0031, 0.001]])
>>> is_within_visible_spectrum(a)
array([ True, False], dtype=bool)
"""
return is_within_mesh_volume(XYZ, cmfs.values, tolerance)
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 is_within_visible_spectrum(
XYZ,
cmfs=MSDS_CMFS['CIE 1931 2 Degree Standard Observer'].copy().align(
SPECTRAL_SHAPE_OUTER_SURFACE_XYZ),
illuminant=sd_ones(SPECTRAL_SHAPE_OUTER_SURFACE_XYZ),
tolerance=None,
**kwargs):
"""
Returns if given *CIE XYZ* tristimulus values are within visible spectrum
volume / given colour matching functions volume.
Parameters
----------
XYZ : array_like
*CIE XYZ* tristimulus values.
cmfs : XYZ_ColourMatchingFunctions, optional
Standard observer colour matching functions.
illuminant : SpectralDistribution, optional
Illuminant spectral distribution.
tolerance : numeric, optional
Tolerance allowed in the inside-triangle check.
Other Parameters
----------------
\\**kwargs : dict, optional
{:func:`colour.msds_to_XYZ`},
Please refer to the documentation of the previously listed definition.
Returns
-------
bool
Is within visible spectrum.
Notes
-----
+------------+-----------------------+---------------+
| **Domain** | **Scale - Reference** | **Scale - 1** |
+============+=======================+===============+
| ``XYZ`` | [0, 1] | [0, 1] |
+------------+-----------------------+---------------+
Examples
--------
>>> import numpy as np
>>> is_within_visible_spectrum(np.array([0.3205, 0.4131, 0.51]))
array(True, dtype=bool)
>>> a = np.array([[0.3205, 0.4131, 0.51],
... [-0.0005, 0.0031, 0.001]])
>>> is_within_visible_spectrum(a)
array([ True, False], dtype=bool)
"""
key = (hash(cmfs), hash(illuminant), six.text_type(kwargs))
vertices = _CACHE_OUTER_SURFACE_XYZ_POINTS.get(key)
if vertices is None:
_CACHE_OUTER_SURFACE_XYZ_POINTS[key] = vertices = (XYZ_outer_surface(
cmfs, illuminant, **kwargs))
return is_within_mesh_volume(XYZ, vertices, tolerance)
def is_within_visible_spectrum(
XYZ: ArrayLike,
cmfs: Optional[MultiSpectralDistributions] = None,
illuminant: Optional[SpectralDistribution] = None,
tolerance: Optional[Floating] = None,
**kwargs: Any,
) -> NDArray:
"""
Return whether given *CIE XYZ* tristimulus values are within the visible
spectrum volume, i.e. *Rösch-MacAdam* colour solid, for given colour
matching functions and illuminant.
Parameters
----------
XYZ
*CIE XYZ* tristimulus values.
cmfs
Standard observer colour matching functions, default to the
*CIE 1931 2 Degree Standard Observer*.
illuminant
Illuminant spectral distribution, default to *CIE Illuminant E*.
tolerance
Tolerance allowed in the inside-triangle check.
Other Parameters
----------------
kwargs
{:func:`colour.msds_to_XYZ`},
See the documentation of the previously listed definition.
Returns
-------
:class:`numpy.ndarray`
Are *CIE XYZ* tristimulus values within the visible spectrum volume,
i.e. *Rösch-MacAdam* colour solid.
Notes
-----
+------------+-----------------------+---------------+
| **Domain** | **Scale - Reference** | **Scale - 1** |
+============+=======================+===============+
| ``XYZ`` | [0, 1] | [0, 1] |
+------------+-----------------------+---------------+
Examples
--------
>>> import numpy as np
>>> is_within_visible_spectrum(np.array([0.3205, 0.4131, 0.51]))
array(True, dtype=bool)
>>> a = np.array([[0.3205, 0.4131, 0.51],
... [-0.0005, 0.0031, 0.001]])
>>> is_within_visible_spectrum(a)
array([ True, False], dtype=bool)
"""
cmfs, illuminant = handle_spectral_arguments(
cmfs,
illuminant,
"CIE 1931 2 Degree Standard Observer",
"E",
SPECTRAL_SHAPE_OUTER_SURFACE_XYZ,
)
key = (hash(cmfs), hash(illuminant), str(kwargs))
vertices = _CACHE_OUTER_SURFACE_XYZ_POINTS.get(key)
if vertices is None:
_CACHE_OUTER_SURFACE_XYZ_POINTS[key] = vertices = solid_RoschMacAdam(
cmfs, illuminant, **kwargs)
return is_within_mesh_volume(XYZ, vertices, tolerance)
