"""
Colour Models Plotting
======================
Defines the colour models plotting objects:
- :func:`colour.plotting.\
plot_RGB_colourspaces_in_chromaticity_diagram_CIE1931`
- :func:`colour.plotting.\
plot_RGB_colourspaces_in_chromaticity_diagram_CIE1960UCS`
- :func:`colour.plotting.\
plot_RGB_colourspaces_in_chromaticity_diagram_CIE1976UCS`
- :func:`colour.plotting.\
plot_RGB_chromaticities_in_chromaticity_diagram_CIE1931`
- :func:`colour.plotting.\
plot_RGB_chromaticities_in_chromaticity_diagram_CIE1960UCS`
- :func:`colour.plotting.\
plot_RGB_chromaticities_in_chromaticity_diagram_CIE1976UCS`
- :func:`colour.plotting.\
plot_ellipses_MacAdam1942_in_chromaticity_diagram_CIE1931`
- :func:`colour.plotting.\
plot_ellipses_MacAdam1942_in_chromaticity_diagram_CIE1960UCS`
- :func:`colour.plotting.\
plot_ellipses_MacAdam1942_in_chromaticity_diagram_CIE1976UCS`
- :func:`colour.plotting.plot_single_cctf`
- :func:`colour.plotting.plot_multi_cctfs`
- :func:`colour.plotting.plot_constant_hue_loci`
References
----------
- :cite:`Ebner1998` : Ebner, F., & Fairchild, M. D. (1998). Finding constant
hue surfaces in color space. In G. B. Beretta & R. Eschbach (Eds.), Proc.
SPIE 3300, Color Imaging: Device-Independent Color, Color Hardcopy, and
Graphic Arts III, (2 January 1998) (pp. 107-117). doi:10.1117/12.298269
- :cite:`Hung1995` : Hung, P.-C., & Berns, R. S. (1995). Determination of
constant Hue Loci for a CRT gamut and their predictions using color
appearance spaces. Color Research & Application, 20(5), 285-295.
doi:10.1002/col.5080200506
- :cite:`Mansencal2019` : Mansencal, T. (2019). Colour - Datasets.
doi:10.5281/zenodo.3362520
"""
from __future__ import annotations
import matplotlib.pyplot as plt
import numpy as np
import scipy.optimize
from matplotlib.patches import Ellipse
from matplotlib.path import Path
from colour.colorimetry import MultiSpectralDistributions
from colour.constants import EPSILON
from colour.geometry import (
point_at_angle_on_ellipse,
ellipse_coefficients_canonical_form,
ellipse_fitting,
)
from colour.graph import convert
from colour.hints import (
Any,
ArrayLike,
Callable,
Dict,
List,
Literal,
NDArrayFloat,
Sequence,
Tuple,
cast,
)
from colour.models import (
COLOURSPACE_MODELS_AXIS_LABELS,
COLOURSPACE_MODELS_DOMAIN_RANGE_SCALE_1_TO_REFERENCE,
CCTF_ENCODINGS,
CCTF_DECODINGS,
LCHab_to_Lab,
Lab_to_XYZ,
Luv_to_uv,
DATA_MACADAM_1942_ELLIPSES,
CCS_POINTER_GAMUT_BOUNDARY,
DATA_POINTER_GAMUT_VOLUME,
CCS_ILLUMINANT_POINTER_GAMUT,
RGB_Colourspace,
RGB_to_RGB,
RGB_to_XYZ,
UCS_to_uv,
XYZ_to_Luv,
XYZ_to_RGB,
XYZ_to_UCS,
XYZ_to_xy,
xy_to_Luv_uv,
xy_to_UCS_uv,
)
from colour.plotting import (
CONSTANTS_COLOUR_STYLE,
plot_chromaticity_diagram_CIE1931,
artist,
plot_chromaticity_diagram_CIE1960UCS,
plot_chromaticity_diagram_CIE1976UCS,
colour_cycle,
colour_style,
filter_passthrough,
filter_RGB_colourspaces,
filter_cmfs,
plot_multi_functions,
override_style,
render,
update_settings_collection,
)
from colour.plotting.diagrams import plot_chromaticity_diagram
from colour.utilities import (
CanonicalMapping,
as_array,
as_float_array,
as_int_array,
domain_range_scale,
first_item,
optional,
tsplit,
validate_method,
)
__author__ = "Colour Developers"
__copyright__ = "Copyright 2013 Colour Developers"
__license__ = "New BSD License - https://opensource.org/licenses/BSD-3-Clause"
__maintainer__ = "Colour Developers"
__email__ = "colour-developers@colour-science.org"
__status__ = "Production"
__all__ = [
"COLOURSPACE_MODELS_AXIS_ORDER",
"colourspace_model_axis_reorder",
"plot_pointer_gamut",
"plot_RGB_colourspaces_in_chromaticity_diagram",
"plot_RGB_colourspaces_in_chromaticity_diagram_CIE1931",
"plot_RGB_colourspaces_in_chromaticity_diagram_CIE1960UCS",
"plot_RGB_colourspaces_in_chromaticity_diagram_CIE1976UCS",
"plot_RGB_chromaticities_in_chromaticity_diagram",
"plot_RGB_chromaticities_in_chromaticity_diagram_CIE1931",
"plot_RGB_chromaticities_in_chromaticity_diagram_CIE1960UCS",
"plot_RGB_chromaticities_in_chromaticity_diagram_CIE1976UCS",
"ellipses_MacAdam1942",
"plot_ellipses_MacAdam1942_in_chromaticity_diagram",
"plot_ellipses_MacAdam1942_in_chromaticity_diagram_CIE1931",
"plot_ellipses_MacAdam1942_in_chromaticity_diagram_CIE1960UCS",
"plot_ellipses_MacAdam1942_in_chromaticity_diagram_CIE1976UCS",
"plot_single_cctf",
"plot_multi_cctfs",
"plot_constant_hue_loci",
]
COLOURSPACE_MODELS_AXIS_ORDER: CanonicalMapping = CanonicalMapping(
{
"CAM02LCD": (1, 2, 0),
"CAM02SCD": (1, 2, 0),
"CAM02UCS": (1, 2, 0),
"CAM16LCD": (1, 2, 0),
"CAM16SCD": (1, 2, 0),
"CAM16UCS": (1, 2, 0),
"CIE XYZ": (0, 1, 2),
"CIE xyY": (0, 1, 2),
"CIE Lab": (1, 2, 0),
"CIE LCHab": (1, 2, 0),
"CIE Luv": (1, 2, 0),
"CIE LCHuv": (1, 2, 0),
"CIE UCS": (0, 1, 2),
"CIE UVW": (1, 2, 0),
"DIN99": (1, 2, 0),
"Hunter Lab": (1, 2, 0),
"Hunter Rdab": (1, 2, 0),
"ICaCb": (1, 2, 0),
"ICtCp": (1, 2, 0),
"IPT": (1, 2, 0),
"IPT Ragoo 2021": (1, 2, 0),
"IgPgTg": (1, 2, 0),
"Jzazbz": (1, 2, 0),
"OSA UCS": (1, 2, 0),
"Oklab": (1, 2, 0),
"hdr-CIELAB": (1, 2, 0),
"hdr-IPT": (1, 2, 0),
"Yrg": (1, 2, 0),
}
)
"""Colourspace models axis order."""
[docs]def colourspace_model_axis_reorder(
a: ArrayLike,
model: Literal[
"CAM02LCD",
"CAM02SCD",
"CAM02UCS",
"CAM16LCD",
"CAM16SCD",
"CAM16UCS",
"CIE XYZ",
"CIE xyY",
"CIE Lab",
"CIE LCHab",
"CIE Luv",
"CIE LCHuv",
"CIE UCS",
"CIE UVW",
"DIN99",
"Hunter Lab",
"Hunter Rdab",
"ICaCb",
"ICtCp",
"IPT",
"IPT Ragoo 2021",
"IgPgTg",
"Jzazbz",
"OSA UCS",
"Oklab",
"hdr-CIELAB",
"hdr-IPT",
"Yrg",
]
| str,
direction: Literal["Forward", "Inverse"] | str = "Forward",
) -> NDArrayFloat:
"""
Reorder the axes of given colourspace model :math:`a` array according to
the most common volume plotting axes order.
Parameters
----------
a
Colourspace model :math:`a` array.
model
Colourspace model, see :attr:`colour.COLOURSPACE_MODELS` attribute for
the list of supported colourspace models.
direction
Reordering direction.
Returns
-------
:class:`numpy.ndarray`
Reordered colourspace model :math:`a` array.
Examples
--------
>>> a = np.array([0, 1, 2])
>>> colourspace_model_axis_reorder(a, "CIE Lab")
array([ 1., 2., 0.])
>>> colourspace_model_axis_reorder(a, "IPT")
array([ 1., 2., 0.])
>>> colourspace_model_axis_reorder(a, "OSA UCS")
array([ 1., 2., 0.])
>>> b = np.array([1, 2, 0])
>>> colourspace_model_axis_reorder(b, "OSA UCS", "Inverse")
array([ 0., 1., 2.])
"""
a = as_float_array(a)
model = validate_method(
model,
tuple(COLOURSPACE_MODELS_AXIS_ORDER),
'"{0}" model is invalid, it must be one of {1}!',
)
direction = validate_method(
direction,
("Forward", "Inverse"),
'"{0}" direction is invalid, it must be one of {1}!',
)
order = COLOURSPACE_MODELS_AXIS_ORDER.get(model, (0, 1, 2))
if direction == "forward":
indexes = (order[0], order[1], order[2])
else:
indexes = (order.index(0), order.index(1), order.index(2))
return a[..., indexes]
[docs]@override_style()
def plot_pointer_gamut(
pointer_gamut_colours: ArrayLike | str | None = None,
pointer_gamut_opacity: float = 1,
method: Literal["CIE 1931", "CIE 1960 UCS", "CIE 1976 UCS"]
| str = "CIE 1931",
**kwargs: Any,
) -> Tuple[plt.Figure, plt.Axes]:
"""
Plot *Pointer's Gamut* according to given method.
Parameters
----------
pointer_gamut_colours
Colours of the *Pointer's Gamut*.
pointer_gamut_opacity
Opacity of the *Pointer's Gamut*.
method
Plotting method.
Other Parameters
----------------
kwargs
{:func:`colour.plotting.artist`, :func:`colour.plotting.render`},
See the documentation of the previously listed definitions.
Returns
-------
:class:`tuple`
Current figure and axes.
Examples
--------
>>> plot_pointer_gamut() # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...Axes...>)
.. image:: ../_static/Plotting_Plot_Pointer_Gamut.png
:align: center
:alt: plot_pointer_gamut
"""
method = validate_method(
method, ("CIE 1931", "CIE 1960 UCS", "CIE 1976 UCS")
)
pointer_gamut_colours = optional(
pointer_gamut_colours, CONSTANTS_COLOUR_STYLE.colour.dark
)
pointer_gamut_opacity = optional(
pointer_gamut_opacity, CONSTANTS_COLOUR_STYLE.opacity.high
)
settings: Dict[str, Any] = {"uniform": True}
settings.update(kwargs)
_figure, axes = artist(**settings)
if method == "cie 1931":
def XYZ_to_ij(
XYZ: NDArrayFloat, *args: Any # noqa: ARG001
) -> NDArrayFloat:
"""
Convert given *CIE XYZ* tristimulus values to *ij* chromaticity
coordinates.
"""
return XYZ_to_xy(XYZ)
def xy_to_ij(xy: NDArrayFloat) -> NDArrayFloat:
"""
Convert given *CIE xy* chromaticity coordinates to *ij*
chromaticity coordinates.
"""
return xy
elif method == "cie 1960 ucs":
def XYZ_to_ij(
XYZ: NDArrayFloat, *args: Any # noqa: ARG001
) -> NDArrayFloat:
"""
Convert given *CIE XYZ* tristimulus values to *ij* chromaticity
coordinates.
"""
return UCS_to_uv(XYZ_to_UCS(XYZ))
def xy_to_ij(xy: NDArrayFloat) -> NDArrayFloat:
"""
Convert given *CIE xy* chromaticity coordinates to *ij*
chromaticity coordinates.
"""
return xy_to_UCS_uv(xy)
elif method == "cie 1976 ucs":
def XYZ_to_ij(XYZ: NDArrayFloat, *args: Any) -> NDArrayFloat:
"""
Convert given *CIE XYZ* tristimulus values to *ij* chromaticity
coordinates.
"""
return Luv_to_uv(XYZ_to_Luv(XYZ, *args), *args)
def xy_to_ij(xy: NDArrayFloat) -> NDArrayFloat:
"""
Convert given *CIE xy* chromaticity coordinates to *ij*
chromaticity coordinates.
"""
return xy_to_Luv_uv(xy)
ij = xy_to_ij(CCS_POINTER_GAMUT_BOUNDARY)
axes.plot(
ij[..., 0],
ij[..., 1],
label="Pointer's Gamut",
color=pointer_gamut_colours,
alpha=pointer_gamut_opacity,
zorder=CONSTANTS_COLOUR_STYLE.zorder.foreground_line,
)
axes.plot(
(ij[-1][0], ij[0][0]),
(ij[-1][1], ij[0][1]),
color=pointer_gamut_colours,
alpha=pointer_gamut_opacity,
zorder=CONSTANTS_COLOUR_STYLE.zorder.foreground_line,
)
XYZ = Lab_to_XYZ(
LCHab_to_Lab(DATA_POINTER_GAMUT_VOLUME), CCS_ILLUMINANT_POINTER_GAMUT
)
ij = XYZ_to_ij(XYZ, CCS_ILLUMINANT_POINTER_GAMUT)
scatter_settings = {
"alpha": pointer_gamut_opacity / 2,
"color": pointer_gamut_colours,
"marker": "+",
"zorder": CONSTANTS_COLOUR_STYLE.zorder.foreground_scatter,
}
axes.scatter(ij[..., 0], ij[..., 1], **scatter_settings)
settings.update({"axes": axes})
settings.update(kwargs)
return render(**settings)
[docs]@override_style()
def plot_RGB_colourspaces_in_chromaticity_diagram(
colourspaces: RGB_Colourspace | str | Sequence[RGB_Colourspace | str],
cmfs: MultiSpectralDistributions
| str
| Sequence[
MultiSpectralDistributions | str
] = "CIE 1931 2 Degree Standard Observer",
chromaticity_diagram_callable: Callable = plot_chromaticity_diagram,
method: Literal["CIE 1931", "CIE 1960 UCS", "CIE 1976 UCS"]
| str = "CIE 1931",
show_whitepoints: bool = True,
show_pointer_gamut: bool = False,
chromatically_adapt: bool = False,
plot_kwargs: dict | List[dict] | None = None,
**kwargs: Any,
) -> Tuple[plt.Figure, plt.Axes]:
"""
Plot given *RGB* colourspaces in the *Chromaticity Diagram* according
to given method.
Parameters
----------
colourspaces
*RGB* colourspaces to plot. ``colourspaces`` elements
can be of any type or form supported by the
:func:`colour.plotting.common.filter_RGB_colourspaces` definition.
cmfs
Standard observer colour matching functions used for computing the
spectral locus boundaries. ``cmfs`` can be of any type or form
supported by the :func:`colour.plotting.common.filter_cmfs` definition.
chromaticity_diagram_callable
Callable responsible for drawing the *Chromaticity Diagram*.
method
*Chromaticity Diagram* method.
show_whitepoints
Whether to display the *RGB* colourspaces whitepoints.
show_pointer_gamut
Whether to display the *Pointer's Gamut*.
chromatically_adapt
Whether to chromatically adapt the *RGB* colourspaces given in
``colourspaces`` to the whitepoint of the default plotting colourspace.
plot_kwargs
Keyword arguments for the :func:`matplotlib.pyplot.plot` definition,
used to control the style of the plotted *RGB* colourspaces.
``plot_kwargs`` can be either a single dictionary applied to all the
plotted *RGB* colourspaces with the same settings or a sequence of
dictionaries with different settings for each plotted *RGB*
colourspace.
Other Parameters
----------------
kwargs
{:func:`colour.plotting.artist`,
:func:`colour.plotting.diagrams.plot_chromaticity_diagram`,
:func:`colour.plotting.models.plot_pointer_gamut`,
:func:`colour.plotting.render`},
See the documentation of the previously listed definitions.
Returns
-------
:class:`tuple`
Current figure and axes.
Examples
--------
>>> plot_kwargs = [
... {"color": "r"},
... {"linestyle": "dashed"},
... {"marker": None},
... ]
>>> plot_RGB_colourspaces_in_chromaticity_diagram(
... ["ITU-R BT.709", "ACEScg", "S-Gamut"], plot_kwargs=plot_kwargs
... )
... # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...Axes...>)
.. image:: ../_static/Plotting_\
Plot_RGB_Colourspaces_In_Chromaticity_Diagram.png
:align: center
:alt: plot_RGB_colourspaces_in_chromaticity_diagram
"""
method = validate_method(
method, ("CIE 1931", "CIE 1960 UCS", "CIE 1976 UCS")
)
colourspaces = cast(
List[RGB_Colourspace],
list(filter_RGB_colourspaces(colourspaces).values()),
) # pyright: ignore
settings: Dict[str, Any] = {"uniform": True}
settings.update(kwargs)
_figure, axes = artist(**settings)
cmfs = cast(
MultiSpectralDistributions, first_item(filter_cmfs(cmfs).values())
)
title = (
f"{', '.join([colourspace.name for colourspace in colourspaces])}\n"
f"{cmfs.name} - {method.upper()} Chromaticity Diagram"
)
settings = {"axes": axes, "title": title, "method": method}
settings.update(kwargs)
settings["standalone"] = False
chromaticity_diagram_callable(**settings)
if show_pointer_gamut:
settings = {"axes": axes, "method": method}
settings.update(kwargs)
settings["standalone"] = False
plot_pointer_gamut(**settings)
if method == "cie 1931":
def xy_to_ij(xy: NDArrayFloat) -> NDArrayFloat:
"""
Convert given *CIE xy* chromaticity coordinates to *ij*
chromaticity coordinates.
"""
return xy
x_limit_min, x_limit_max = [-0.1], [0.9]
y_limit_min, y_limit_max = [-0.1], [0.9]
elif method == "cie 1960 ucs":
def xy_to_ij(xy: NDArrayFloat) -> NDArrayFloat:
"""
Convert given *CIE xy* chromaticity coordinates to *ij*
chromaticity coordinates.
"""
return xy_to_UCS_uv(xy)
x_limit_min, x_limit_max = [-0.1], [0.7]
y_limit_min, y_limit_max = [-0.2], [0.6]
elif method == "cie 1976 ucs":
def xy_to_ij(xy: NDArrayFloat) -> NDArrayFloat:
"""
Convert given *CIE xy* chromaticity coordinates to *ij*
chromaticity coordinates.
"""
return xy_to_Luv_uv(xy)
x_limit_min, x_limit_max = [-0.1], [0.7]
y_limit_min, y_limit_max = [-0.1], [0.7]
settings = {"colour_cycle_count": len(colourspaces)}
settings.update(kwargs)
cycle = colour_cycle(**settings)
plotting_colourspace = CONSTANTS_COLOUR_STYLE.colour.colourspace
plot_settings_collection = [
{
"label": f"{colourspace.name}",
"marker": "o",
"color": next(cycle)[:3],
"zorder": CONSTANTS_COLOUR_STYLE.zorder.foreground_line,
}
for colourspace in colourspaces
]
if plot_kwargs is not None:
update_settings_collection(
plot_settings_collection, plot_kwargs, len(colourspaces)
)
for i, colourspace in enumerate(colourspaces):
plot_settings = plot_settings_collection[i]
if chromatically_adapt and not np.array_equal(
colourspace.whitepoint, plotting_colourspace.whitepoint
):
colourspace = colourspace.chromatically_adapt(
plotting_colourspace.whitepoint,
plotting_colourspace.whitepoint_name,
)
# 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 = xy_to_ij(P)
W = xy_to_ij(colourspace.whitepoint)
P_p = np.vstack([P, P[0]])
axes.plot(P_p[..., 0], P_p[..., 1], **plot_settings)
if show_whitepoints:
plot_settings["marker"] = "o"
plot_settings.pop("label")
W_p = np.vstack([W, W])
axes.plot(W_p[..., 0], W_p[..., 1], **plot_settings)
x_limit_min.append(cast(float, np.amin(P[..., 0]) - 0.1))
y_limit_min.append(cast(float, np.amin(P[..., 1]) - 0.1))
x_limit_max.append(cast(float, np.amax(P[..., 0]) + 0.1))
y_limit_max.append(cast(float, np.amax(P[..., 1]) + 0.1))
bounding_box = (
min(x_limit_min),
max(x_limit_max),
min(y_limit_min),
max(y_limit_max),
)
settings.update(
{
"standalone": True,
"legend": True,
"bounding_box": bounding_box,
}
)
settings.update(kwargs)
return render(**settings)
[docs]@override_style()
def plot_RGB_colourspaces_in_chromaticity_diagram_CIE1931(
colourspaces: RGB_Colourspace | str | Sequence[RGB_Colourspace | str],
cmfs: MultiSpectralDistributions
| str
| Sequence[
MultiSpectralDistributions | str
] = "CIE 1931 2 Degree Standard Observer",
chromaticity_diagram_callable_CIE1931: Callable = (
plot_chromaticity_diagram_CIE1931
),
show_whitepoints: bool = True,
show_pointer_gamut: bool = False,
chromatically_adapt: bool = False,
plot_kwargs: dict | List[dict] | None = None,
**kwargs: Any,
) -> Tuple[plt.Figure, plt.Axes]:
"""
Plot given *RGB* colourspaces in the *CIE 1931 Chromaticity Diagram*.
Parameters
----------
colourspaces
*RGB* colourspaces to plot. ``colourspaces`` elements
can be of any type or form supported by the
:func:`colour.plotting.common.filter_RGB_colourspaces` definition.
cmfs
Standard observer colour matching functions used for computing the
spectral locus boundaries. ``cmfs`` can be of any type or form
supported by the :func:`colour.plotting.common.filter_cmfs` definition.
chromaticity_diagram_callable_CIE1931
Callable responsible for drawing the *CIE 1931 Chromaticity Diagram*.
show_whitepoints
Whether to display the *RGB* colourspaces whitepoints.
show_pointer_gamut
Whether to display the *Pointer's Gamut*.
chromatically_adapt
Whether to chromatically adapt the *RGB* colourspaces given in
``colourspaces`` to the whitepoint of the default plotting colourspace.
plot_kwargs
Keyword arguments for the :func:`matplotlib.pyplot.plot` definition,
used to control the style of the plotted *RGB* colourspaces.
``plot_kwargs`` can be either a single dictionary applied to all the
plotted *RGB* colourspaces with the same settings or a sequence of
dictionaries with different settings for each plotted *RGB*
colourspace.
Other Parameters
----------------
kwargs
{:func:`colour.plotting.artist`,
:func:`colour.plotting.diagrams.plot_chromaticity_diagram`,
:func:`colour.plotting.models.plot_pointer_gamut`,
:func:`colour.plotting.models.\
plot_RGB_colourspaces_in_chromaticity_diagram`,
:func:`colour.plotting.render`},
See the documentation of the previously listed definitions.
Returns
-------
:class:`tuple`
Current figure and axes.
Examples
--------
>>> plot_RGB_colourspaces_in_chromaticity_diagram_CIE1931(
... ["ITU-R BT.709", "ACEScg", "S-Gamut"]
... )
... # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...Axes...>)
.. image:: ../_static/Plotting_\
Plot_RGB_Colourspaces_In_Chromaticity_Diagram_CIE1931.png
:align: center
:alt: plot_RGB_colourspaces_in_chromaticity_diagram_CIE1931
"""
settings = dict(kwargs)
settings.update({"method": "CIE 1931"})
return plot_RGB_colourspaces_in_chromaticity_diagram(
colourspaces,
cmfs,
chromaticity_diagram_callable_CIE1931,
show_whitepoints=show_whitepoints,
show_pointer_gamut=show_pointer_gamut,
chromatically_adapt=chromatically_adapt,
plot_kwargs=plot_kwargs,
**settings,
)
[docs]@override_style()
def plot_RGB_colourspaces_in_chromaticity_diagram_CIE1960UCS(
colourspaces: RGB_Colourspace | str | Sequence[RGB_Colourspace | str],
cmfs: MultiSpectralDistributions
| str
| Sequence[
MultiSpectralDistributions | str
] = "CIE 1931 2 Degree Standard Observer",
chromaticity_diagram_callable_CIE1960UCS: Callable = (
plot_chromaticity_diagram_CIE1960UCS
),
show_whitepoints: bool = True,
show_pointer_gamut: bool = False,
chromatically_adapt: bool = False,
plot_kwargs: dict | List[dict] | None = None,
**kwargs: Any,
) -> Tuple[plt.Figure, plt.Axes]:
"""
Plot given *RGB* colourspaces in the *CIE 1960 UCS Chromaticity Diagram*.
Parameters
----------
colourspaces
*RGB* colourspaces to plot. ``colourspaces`` elements
can be of any type or form supported by the
:func:`colour.plotting.common.filter_RGB_colourspaces` definition.
cmfs
Standard observer colour matching functions used for computing the
spectral locus boundaries. ``cmfs`` can be of any type or form
supported by the :func:`colour.plotting.common.filter_cmfs` definition.
chromaticity_diagram_callable_CIE1960UCS
Callable responsible for drawing the
*CIE 1960 UCS Chromaticity Diagram*.
show_whitepoints
Whether to display the *RGB* colourspaces whitepoints.
show_pointer_gamut
Whether to display the *Pointer's Gamut*.
chromatically_adapt
Whether to chromatically adapt the *RGB* colourspaces given in
``colourspaces`` to the whitepoint of the default plotting colourspace.
plot_kwargs
Keyword arguments for the :func:`matplotlib.pyplot.plot` definition,
used to control the style of the plotted *RGB* colourspaces.
``plot_kwargs`` can be either a single dictionary applied to all the
plotted *RGB* colourspaces with the same settings or a sequence of
dictionaries with different settings for each plotted *RGB*
colourspace.
Other Parameters
----------------
kwargs
{:func:`colour.plotting.artist`,
:func:`colour.plotting.diagrams.plot_chromaticity_diagram`,
:func:`colour.plotting.models.plot_pointer_gamut`,
:func:`colour.plotting.models.\
plot_RGB_colourspaces_in_chromaticity_diagram`,
:func:`colour.plotting.render`},
See the documentation of the previously listed definitions.
Returns
-------
:class:`tuple`
Current figure and axes.
Examples
--------
>>> plot_RGB_colourspaces_in_chromaticity_diagram_CIE1960UCS(
... ["ITU-R BT.709", "ACEScg", "S-Gamut"]
... )
... # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...Axes...>)
.. image:: ../_static/Plotting_\
Plot_RGB_Colourspaces_In_Chromaticity_Diagram_CIE1960UCS.png
:align: center
:alt: plot_RGB_colourspaces_in_chromaticity_diagram_CIE1960UCS
"""
settings = dict(kwargs)
settings.update({"method": "CIE 1960 UCS"})
return plot_RGB_colourspaces_in_chromaticity_diagram(
colourspaces,
cmfs,
chromaticity_diagram_callable_CIE1960UCS,
show_whitepoints=show_whitepoints,
show_pointer_gamut=show_pointer_gamut,
chromatically_adapt=chromatically_adapt,
plot_kwargs=plot_kwargs,
**settings,
)
[docs]@override_style()
def plot_RGB_colourspaces_in_chromaticity_diagram_CIE1976UCS(
colourspaces: RGB_Colourspace | str | Sequence[RGB_Colourspace | str],
cmfs: MultiSpectralDistributions
| str
| Sequence[
MultiSpectralDistributions | str
] = "CIE 1931 2 Degree Standard Observer",
chromaticity_diagram_callable_CIE1976UCS: Callable = (
plot_chromaticity_diagram_CIE1976UCS
),
show_whitepoints: bool = True,
show_pointer_gamut: bool = False,
chromatically_adapt: bool = False,
plot_kwargs: dict | List[dict] | None = None,
**kwargs: Any,
) -> Tuple[plt.Figure, plt.Axes]:
"""
Plot given *RGB* colourspaces in the *CIE 1976 UCS Chromaticity Diagram*.
Parameters
----------
colourspaces
*RGB* colourspaces to plot. ``colourspaces`` elements
can be of any type or form supported by the
:func:`colour.plotting.common.filter_RGB_colourspaces` definition.
cmfs
Standard observer colour matching functions used for computing the
spectral locus boundaries. ``cmfs`` can be of any type or form
supported by the :func:`colour.plotting.common.filter_cmfs` definition.
chromaticity_diagram_callable_CIE1976UCS
Callable responsible for drawing the
*CIE 1976 UCS Chromaticity Diagram*.
show_whitepoints
Whether to display the *RGB* colourspaces whitepoints.
show_pointer_gamut
Whether to display the *Pointer's Gamut*.
chromatically_adapt
Whether to chromatically adapt the *RGB* colourspaces given in
``colourspaces`` to the whitepoint of the default plotting colourspace.
plot_kwargs
Keyword arguments for the :func:`matplotlib.pyplot.plot` definition,
used to control the style of the plotted *RGB* colourspaces.
``plot_kwargs`` can be either a single dictionary applied to all the
plotted *RGB* colourspaces with the same settings or a sequence of
dictionaries with different settings for each plotted *RGB*
colourspace.
Other Parameters
----------------
kwargs
{:func:`colour.plotting.artist`,
:func:`colour.plotting.diagrams.plot_chromaticity_diagram`,
:func:`colour.plotting.models.plot_pointer_gamut`,
:func:`colour.plotting.models.\
plot_RGB_colourspaces_in_chromaticity_diagram`,
:func:`colour.plotting.render`},
See the documentation of the previously listed definitions.
Returns
-------
:class:`tuple`
Current figure and axes.
Examples
--------
>>> plot_RGB_colourspaces_in_chromaticity_diagram_CIE1976UCS(
... ["ITU-R BT.709", "ACEScg", "S-Gamut"]
... )
... # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...Axes...>)
.. image:: ../_static/Plotting_\
Plot_RGB_Colourspaces_In_Chromaticity_Diagram_CIE1976UCS.png
:align: center
:alt: plot_RGB_colourspaces_in_chromaticity_diagram_CIE1976UCS
"""
settings = dict(kwargs)
settings.update({"method": "CIE 1976 UCS"})
return plot_RGB_colourspaces_in_chromaticity_diagram(
colourspaces,
cmfs,
chromaticity_diagram_callable_CIE1976UCS,
show_whitepoints=show_whitepoints,
show_pointer_gamut=show_pointer_gamut,
chromatically_adapt=chromatically_adapt,
plot_kwargs=plot_kwargs,
**settings,
)
[docs]@override_style()
def plot_RGB_chromaticities_in_chromaticity_diagram(
RGB: ArrayLike,
colourspace: RGB_Colourspace
| str
| Sequence[RGB_Colourspace | str] = "sRGB",
chromaticity_diagram_callable: Callable = (
plot_RGB_colourspaces_in_chromaticity_diagram
),
method: Literal["CIE 1931", "CIE 1960 UCS", "CIE 1976 UCS"]
| str = "CIE 1931",
scatter_kwargs: dict | None = None,
**kwargs: Any,
) -> Tuple[plt.Figure, plt.Axes]:
"""
Plot given *RGB* colourspace array in the *Chromaticity Diagram* according
to given method.
Parameters
----------
RGB
*RGB* colourspace array.
colourspace
*RGB* colourspace of the *RGB* array. ``colourspace`` can be of any
type or form supported by the
:func:`colour.plotting.common.filter_RGB_colourspaces` definition.
chromaticity_diagram_callable
Callable responsible for drawing the *Chromaticity Diagram*.
method
*Chromaticity Diagram* method.
scatter_kwargs
Keyword arguments for the :func:`matplotlib.pyplot.scatter` definition.
The following special keyword arguments can also be used:
- ``c`` : If ``c`` is set to *RGB*, the scatter will use the colours
as given by the ``RGB`` argument.
- ``apply_cctf_encoding`` : If ``apply_cctf_encoding`` is set to
*False*, the encoding colour component transfer function /
opto-electronic transfer function is not applied when encoding the
samples to the plotting space.
Other Parameters
----------------
kwargs
{:func:`colour.plotting.artist`,
:func:`colour.plotting.diagrams.plot_chromaticity_diagram`,
:func:`colour.plotting.models.\
plot_RGB_colourspaces_in_chromaticity_diagram`,
:func:`colour.plotting.render`},
See the documentation of the previously listed definitions.
Returns
-------
:class:`tuple`
Current figure and axes.
Examples
--------
>>> RGB = np.random.random((128, 128, 3))
>>> plot_RGB_chromaticities_in_chromaticity_diagram(RGB, "ITU-R BT.709")
... # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...Axes...>)
.. image:: ../_static/Plotting_\
Plot_RGB_Chromaticities_In_Chromaticity_Diagram.png
:align: center
:alt: plot_RGB_chromaticities_in_chromaticity_diagram
"""
RGB = np.reshape(as_float_array(RGB), (-1, 3))
method = validate_method(
method, ("CIE 1931", "CIE 1960 UCS", "CIE 1976 UCS")
)
settings: Dict[str, Any] = {"uniform": True}
settings.update(kwargs)
_figure, axes = artist(**settings)
scatter_settings = {
"s": 40,
"c": "RGB",
"marker": "o",
"alpha": 0.85,
"zorder": CONSTANTS_COLOUR_STYLE.zorder.midground_scatter,
"apply_cctf_encoding": True,
}
if scatter_kwargs is not None:
scatter_settings.update(scatter_kwargs)
settings = dict(kwargs)
settings.update({"axes": axes, "standalone": False})
colourspace = cast(
RGB_Colourspace,
first_item(filter_RGB_colourspaces(colourspace).values()),
)
settings["colourspaces"] = [colourspace, *settings.get("colourspaces", [])]
chromaticity_diagram_callable(**settings)
use_RGB_colours = str(scatter_settings["c"]).upper() == "RGB"
apply_cctf_encoding = scatter_settings.pop("apply_cctf_encoding")
if use_RGB_colours:
RGB = RGB[RGB[:, 1].argsort()]
scatter_settings["c"] = np.clip(
np.reshape(
RGB_to_RGB(
RGB,
colourspace,
CONSTANTS_COLOUR_STYLE.colour.colourspace,
apply_cctf_encoding=apply_cctf_encoding,
),
(-1, 3),
),
0,
1,
)
XYZ = RGB_to_XYZ(RGB, colourspace)
if method == "cie 1931":
ij = XYZ_to_xy(XYZ)
elif method == "cie 1960 ucs":
ij = UCS_to_uv(XYZ_to_UCS(XYZ))
elif method == "cie 1976 ucs":
ij = Luv_to_uv(
XYZ_to_Luv(XYZ, colourspace.whitepoint), colourspace.whitepoint
)
axes.scatter(ij[..., 0], ij[..., 1], **scatter_settings)
settings.update({"standalone": True})
settings.update(kwargs)
return render(**settings)
[docs]@override_style()
def plot_RGB_chromaticities_in_chromaticity_diagram_CIE1931(
RGB: ArrayLike,
colourspace: RGB_Colourspace
| str
| Sequence[RGB_Colourspace | str] = "sRGB",
chromaticity_diagram_callable_CIE1931: Callable = (
plot_RGB_colourspaces_in_chromaticity_diagram_CIE1931
),
scatter_kwargs: dict | None = None,
**kwargs: Any,
) -> Tuple[plt.Figure, plt.Axes]:
"""
Plot given *RGB* colourspace array in the *CIE 1931 Chromaticity Diagram*.
Parameters
----------
RGB
*RGB* colourspace array.
colourspace
*RGB* colourspace of the *RGB* array. ``colourspace`` can be of any
type or form supported by the
:func:`colour.plotting.common.filter_RGB_colourspaces` definition.
chromaticity_diagram_callable_CIE1931
Callable responsible for drawing the *CIE 1931 Chromaticity Diagram*.
scatter_kwargs
Keyword arguments for the :func:`matplotlib.pyplot.scatter` definition.
The following special keyword arguments can also be used:
- ``c`` : If ``c`` is set to *RGB*, the scatter will use the colours
as given by the ``RGB`` argument.
- ``apply_cctf_encoding`` : If ``apply_cctf_encoding`` is set to
*False*, the encoding colour component transfer function /
opto-electronic transfer function is not applied when encoding the
samples to the plotting space.
Other Parameters
----------------
kwargs
{:func:`colour.plotting.artist`,
:func:`colour.plotting.diagrams.plot_chromaticity_diagram`,
:func:`colour.plotting.models.\
plot_RGB_colourspaces_in_chromaticity_diagram`,
:func:`colour.plotting.render`},
See the documentation of the previously listed definitions.
Returns
-------
:class:`tuple`
Current figure and axes.
Examples
--------
>>> RGB = np.random.random((128, 128, 3))
>>> plot_RGB_chromaticities_in_chromaticity_diagram_CIE1931(
... RGB, "ITU-R BT.709"
... )
... # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...Axes...>)
.. image:: ../_static/Plotting_\
Plot_RGB_Chromaticities_In_Chromaticity_Diagram_CIE1931.png
:align: center
:alt: plot_RGB_chromaticities_in_chromaticity_diagram_CIE1931
"""
settings = dict(kwargs)
settings.update({"method": "CIE 1931"})
return plot_RGB_chromaticities_in_chromaticity_diagram(
RGB,
colourspace,
chromaticity_diagram_callable_CIE1931,
scatter_kwargs=scatter_kwargs,
**settings,
)
[docs]@override_style()
def plot_RGB_chromaticities_in_chromaticity_diagram_CIE1960UCS(
RGB: ArrayLike,
colourspace: RGB_Colourspace
| str
| Sequence[RGB_Colourspace | str] = "sRGB",
chromaticity_diagram_callable_CIE1960UCS: Callable = (
plot_RGB_colourspaces_in_chromaticity_diagram_CIE1960UCS
),
scatter_kwargs: dict | None = None,
**kwargs: Any,
) -> Tuple[plt.Figure, plt.Axes]:
"""
Plot given *RGB* colourspace array in the
*CIE 1960 UCS Chromaticity Diagram*.
Parameters
----------
RGB
*RGB* colourspace array.
colourspace
*RGB* colourspace of the *RGB* array. ``colourspace`` can be of any
type or form supported by the
:func:`colour.plotting.common.filter_RGB_colourspaces` definition.
chromaticity_diagram_callable_CIE1960UCS
Callable responsible for drawing the
*CIE 1960 UCS Chromaticity Diagram*.
scatter_kwargs
Keyword arguments for the :func:`matplotlib.pyplot.scatter` definition.
The following special keyword arguments can also be used:
- ``c`` : If ``c`` is set to *RGB*, the scatter will use the colours
as given by the ``RGB`` argument.
- ``apply_cctf_encoding`` : If ``apply_cctf_encoding`` is set to
*False*, the encoding colour component transfer function /
opto-electronic transfer function is not applied when encoding the
samples to the plotting space.
Other Parameters
----------------
kwargs
{:func:`colour.plotting.artist`,
:func:`colour.plotting.diagrams.plot_chromaticity_diagram`,
:func:`colour.plotting.models.\
plot_RGB_colourspaces_in_chromaticity_diagram`,
:func:`colour.plotting.render`},
See the documentation of the previously listed definitions.
Returns
-------
:class:`tuple`
Current figure and axes.
Examples
--------
>>> RGB = np.random.random((128, 128, 3))
>>> plot_RGB_chromaticities_in_chromaticity_diagram_CIE1960UCS(
... RGB, "ITU-R BT.709"
... )
... # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...Axes...>)
.. image:: ../_static/Plotting_\
Plot_RGB_Chromaticities_In_Chromaticity_Diagram_CIE1960UCS.png
:align: center
:alt: plot_RGB_chromaticities_in_chromaticity_diagram_CIE1960UCS
"""
settings = dict(kwargs)
settings.update({"method": "CIE 1960 UCS"})
return plot_RGB_chromaticities_in_chromaticity_diagram(
RGB,
colourspace,
chromaticity_diagram_callable_CIE1960UCS,
scatter_kwargs=scatter_kwargs,
**settings,
)
[docs]@override_style()
def plot_RGB_chromaticities_in_chromaticity_diagram_CIE1976UCS(
RGB: ArrayLike,
colourspace: RGB_Colourspace
| str
| Sequence[RGB_Colourspace | str] = "sRGB",
chromaticity_diagram_callable_CIE1976UCS: Callable = (
plot_RGB_colourspaces_in_chromaticity_diagram_CIE1976UCS
),
scatter_kwargs: dict | None = None,
**kwargs: Any,
) -> Tuple[plt.Figure, plt.Axes]:
"""
Plot given *RGB* colourspace array in the
*CIE 1976 UCS Chromaticity Diagram*.
Parameters
----------
RGB
*RGB* colourspace array.
colourspace
*RGB* colourspace of the *RGB* array. ``colourspace`` can be of any
type or form supported by the
:func:`colour.plotting.common.filter_RGB_colourspaces` definition.
chromaticity_diagram_callable_CIE1976UCS
Callable responsible for drawing the
*CIE 1976 UCS Chromaticity Diagram*.
scatter_kwargs
Keyword arguments for the :func:`matplotlib.pyplot.scatter` definition.
The following special keyword arguments can also be used:
- ``c`` : If ``c`` is set to *RGB*, the scatter will use the colours
as given by the ``RGB`` argument.
- ``apply_cctf_encoding`` : If ``apply_cctf_encoding`` is set to
*False*, the encoding colour component transfer function /
opto-electronic transfer function is not applied when encoding the
samples to the plotting space.
Other Parameters
----------------
kwargs
{:func:`colour.plotting.artist`,
:func:`colour.plotting.diagrams.plot_chromaticity_diagram`,
:func:`colour.plotting.models.\
plot_RGB_colourspaces_in_chromaticity_diagram`,
:func:`colour.plotting.render`},
See the documentation of the previously listed definitions.
Returns
-------
:class:`tuple`
Current figure and axes.
Examples
--------
>>> RGB = np.random.random((128, 128, 3))
>>> plot_RGB_chromaticities_in_chromaticity_diagram_CIE1976UCS(
... RGB, "ITU-R BT.709"
... )
... # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...Axes...>)
.. image:: ../_static/Plotting_\
Plot_RGB_Chromaticities_In_Chromaticity_Diagram_CIE1976UCS.png
:align: center
:alt: plot_RGB_chromaticities_in_chromaticity_diagram_CIE1976UCS
"""
settings = dict(kwargs)
settings.update({"method": "CIE 1976 UCS"})
return plot_RGB_chromaticities_in_chromaticity_diagram(
RGB,
colourspace,
chromaticity_diagram_callable_CIE1976UCS,
scatter_kwargs=scatter_kwargs,
**settings,
)
def ellipses_MacAdam1942(
method: Literal["CIE 1931", "CIE 1960 UCS", "CIE 1976 UCS"]
| str = "CIE 1931"
) -> List[NDArrayFloat]:
"""
Return *MacAdam (1942) Ellipses (Observer PGN)* coefficients according to
given method.
Parameters
----------
method
Computation method.
Returns
-------
:class:`list`
*MacAdam (1942) Ellipses (Observer PGN)* coefficients.
Examples
--------
>>> ellipses_MacAdam1942()[0] # doctest: +SKIP
array([ 1.60000000e-01, 5.70000000e-02, 5.00000023e-03,
1.56666660e-02, -2.77000015e+01])
"""
method = validate_method(
method, ("CIE 1931", "CIE 1960 UCS", "CIE 1976 UCS")
)
if method == "cie 1931":
def xy_to_ij(xy: NDArrayFloat) -> NDArrayFloat:
"""
Convert given *CIE xy* chromaticity coordinates to *ij*
chromaticity coordinates.
"""
return xy
elif method == "cie 1960 ucs":
def xy_to_ij(xy: NDArrayFloat) -> NDArrayFloat:
"""
Convert given *CIE xy* chromaticity coordinates to *ij*
chromaticity coordinates.
"""
return xy_to_UCS_uv(xy)
elif method == "cie 1976 ucs":
def xy_to_ij(xy: NDArrayFloat) -> NDArrayFloat:
"""
Convert given *CIE xy* chromaticity coordinates to *ij*
chromaticity coordinates.
"""
return xy_to_Luv_uv(xy)
x, y, _a, _b, _theta, a, b, theta = tsplit(DATA_MACADAM_1942_ELLIPSES)
ellipses_coefficients = []
# pylint: disable=C0200
for i in range(len(theta)):
xy = point_at_angle_on_ellipse(
np.linspace(0, 360, 36),
[x[i], y[i], a[i] / 60, b[i] / 60, theta[i]],
)
ij = xy_to_ij(xy)
ellipses_coefficients.append(
ellipse_coefficients_canonical_form(ellipse_fitting(ij))
)
return ellipses_coefficients
[docs]@override_style()
def plot_ellipses_MacAdam1942_in_chromaticity_diagram(
chromaticity_diagram_callable: Callable = plot_chromaticity_diagram,
method: Literal["CIE 1931", "CIE 1960 UCS", "CIE 1976 UCS"]
| str = "CIE 1931",
chromaticity_diagram_clipping: bool = False,
ellipse_kwargs: dict | List[dict] | None = None,
**kwargs: Any,
) -> Tuple[plt.Figure, plt.Axes]:
"""
Plot *MacAdam (1942) Ellipses (Observer PGN)* in the
*Chromaticity Diagram* according to given method.
Parameters
----------
chromaticity_diagram_callable
Callable responsible for drawing the *Chromaticity Diagram*.
method
*Chromaticity Diagram* method.
chromaticity_diagram_clipping
Whether to clip the *Chromaticity Diagram* colours with the ellipses.
ellipse_kwargs
Parameters for the :class:`Ellipse` class, ``ellipse_kwargs`` can
be either a single dictionary applied to all the ellipses with same
settings or a sequence of dictionaries with different settings for each
ellipse.
Other Parameters
----------------
kwargs
{:func:`colour.plotting.artist`,
:func:`colour.plotting.diagrams.plot_chromaticity_diagram`,
:func:`colour.plotting.render`},
See the documentation of the previously listed definitions.
Returns
-------
:class:`tuple`
Current figure and axes.
Examples
--------
>>> plot_ellipses_MacAdam1942_in_chromaticity_diagram()
... # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...Axes...>)
.. image:: ../_static/\
Plotting_Plot_Ellipses_MacAdam1942_In_Chromaticity_Diagram.png
:align: center
:alt: plot_ellipses_MacAdam1942_in_chromaticity_diagram
"""
settings: Dict[str, Any] = {"uniform": True}
settings.update(kwargs)
_figure, axes = artist(**settings)
settings = dict(kwargs)
settings.update({"axes": axes, "standalone": False})
ellipses_coefficients = ellipses_MacAdam1942(method=method)
if chromaticity_diagram_clipping:
diagram_clipping_path_x = []
diagram_clipping_path_y = []
for coefficients in ellipses_coefficients:
coefficients = np.copy(coefficients)
coefficients[2:4] /= 2
x, y = tsplit(
point_at_angle_on_ellipse(
np.linspace(0, 360, 36),
coefficients,
)
)
diagram_clipping_path_x.append(x)
diagram_clipping_path_y.append(y)
diagram_clipping_path = np.rollaxis(
np.array([diagram_clipping_path_x, diagram_clipping_path_y]), 0, 3
)
diagram_clipping_path = Path.make_compound_path_from_polys(
diagram_clipping_path
).vertices
settings.update({"diagram_clipping_path": diagram_clipping_path})
chromaticity_diagram_callable(**settings)
ellipse_settings_collection = [
{
"color": CONSTANTS_COLOUR_STYLE.colour.cycle[4],
"alpha": 0.4,
"linewidth": colour_style()["lines.linewidth"],
"zorder": CONSTANTS_COLOUR_STYLE.zorder.midground_polygon,
}
for _ellipses_coefficient in ellipses_coefficients
]
if ellipse_kwargs is not None:
update_settings_collection(
ellipse_settings_collection,
ellipse_kwargs,
len(ellipses_coefficients),
)
for i, coefficients in enumerate(ellipses_coefficients):
x_c, y_c, a_a, a_b, theta_e = coefficients
ellipse = Ellipse(
(x_c, y_c),
a_a,
a_b,
angle=theta_e,
**ellipse_settings_collection[i],
)
axes.add_artist(ellipse)
settings.update({"standalone": True})
settings.update(kwargs)
return render(**settings)
[docs]@override_style()
def plot_ellipses_MacAdam1942_in_chromaticity_diagram_CIE1931(
chromaticity_diagram_callable_CIE1931: Callable = (
plot_chromaticity_diagram_CIE1931
),
chromaticity_diagram_clipping: bool = False,
ellipse_kwargs: dict | List[dict] | None = None,
**kwargs: Any,
) -> Tuple[plt.Figure, plt.Axes]:
"""
Plot *MacAdam (1942) Ellipses (Observer PGN)* in the
*CIE 1931 Chromaticity Diagram*.
Parameters
----------
chromaticity_diagram_callable_CIE1931
Callable responsible for drawing the *CIE 1931 Chromaticity Diagram*.
chromaticity_diagram_clipping
Whether to clip the *CIE 1931 Chromaticity Diagram* colours with the
ellipses.
ellipse_kwargs
Parameters for the :class:`Ellipse` class, ``ellipse_kwargs`` can
be either a single dictionary applied to all the ellipses with same
settings or a sequence of dictionaries with different settings for each
ellipse.
Other Parameters
----------------
kwargs
{:func:`colour.plotting.artist`,
:func:`colour.plotting.diagrams.plot_chromaticity_diagram`,
:func:`colour.plotting.models.\
plot_ellipses_MacAdam1942_in_chromaticity_diagram`},
:func:`colour.plotting.render`},
See the documentation of the previously listed definitions.
Returns
-------
:class:`tuple`
Current figure and axes.
Examples
--------
>>> plot_ellipses_MacAdam1942_in_chromaticity_diagram_CIE1931()
... # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...Axes...>)
.. image:: ../_static/\
Plotting_Plot_Ellipses_MacAdam1942_In_Chromaticity_Diagram_CIE1931.png
:align: center
:alt: plot_ellipses_MacAdam1942_in_chromaticity_diagram_CIE1931
"""
settings = dict(kwargs)
settings.update({"method": "CIE 1931"})
return plot_ellipses_MacAdam1942_in_chromaticity_diagram(
chromaticity_diagram_callable_CIE1931,
chromaticity_diagram_clipping=chromaticity_diagram_clipping,
ellipse_kwargs=ellipse_kwargs,
**settings,
)
[docs]@override_style()
def plot_ellipses_MacAdam1942_in_chromaticity_diagram_CIE1960UCS(
chromaticity_diagram_callable_CIE1960UCS: Callable = (
plot_chromaticity_diagram_CIE1960UCS
),
chromaticity_diagram_clipping: bool = False,
ellipse_kwargs: dict | List[dict] | None = None,
**kwargs: Any,
) -> Tuple[plt.Figure, plt.Axes]:
"""
Plot *MacAdam (1942) Ellipses (Observer PGN)* in the
*CIE 1960 UCS Chromaticity Diagram*.
Parameters
----------
chromaticity_diagram_callable_CIE1960UCS
Callable responsible for drawing the
*CIE 1960 UCS Chromaticity Diagram*.
chromaticity_diagram_clipping
Whether to clip the *CIE 1960 UCS Chromaticity Diagram* colours with
the ellipses.
ellipse_kwargs
Parameters for the :class:`Ellipse` class, ``ellipse_kwargs`` can
be either a single dictionary applied to all the ellipses with same
settings or a sequence of dictionaries with different settings for each
ellipse.
Other Parameters
----------------
kwargs
{:func:`colour.plotting.artist`,
:func:`colour.plotting.diagrams.plot_chromaticity_diagram`,
:func:`colour.plotting.models.\
plot_ellipses_MacAdam1942_in_chromaticity_diagram`},
:func:`colour.plotting.render`},
See the documentation of the previously listed definitions.
Returns
-------
:class:`tuple`
Current figure and axes.
Examples
--------
>>> plot_ellipses_MacAdam1942_in_chromaticity_diagram_CIE1960UCS()
... # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...Axes...>)
.. image:: ../_static/\
Plotting_Plot_Ellipses_MacAdam1942_In_Chromaticity_Diagram_CIE1960UCS.png
:align: center
:alt: plot_ellipses_MacAdam1942_in_chromaticity_diagram_CIE1960UCS
"""
settings = dict(kwargs)
settings.update({"method": "CIE 1960 UCS"})
return plot_ellipses_MacAdam1942_in_chromaticity_diagram(
chromaticity_diagram_callable_CIE1960UCS,
chromaticity_diagram_clipping=chromaticity_diagram_clipping,
ellipse_kwargs=ellipse_kwargs,
**settings,
)
[docs]@override_style()
def plot_ellipses_MacAdam1942_in_chromaticity_diagram_CIE1976UCS(
chromaticity_diagram_callable_CIE1976UCS: Callable = (
plot_chromaticity_diagram_CIE1976UCS
),
chromaticity_diagram_clipping: bool = False,
ellipse_kwargs: dict | List[dict] | None = None,
**kwargs: Any,
) -> Tuple[plt.Figure, plt.Axes]:
"""
Plot *MacAdam (1942) Ellipses (Observer PGN)* in the
*CIE 1976 UCS Chromaticity Diagram*.
Parameters
----------
chromaticity_diagram_callable_CIE1976UCS
Callable responsible for drawing the
*CIE 1976 UCS Chromaticity Diagram*.
chromaticity_diagram_clipping
Whether to clip the *CIE 1976 UCS Chromaticity Diagram* colours with
the ellipses.
ellipse_kwargs
Parameters for the :class:`Ellipse` class, ``ellipse_kwargs`` can
be either a single dictionary applied to all the ellipses with same
settings or a sequence of dictionaries with different settings for each
ellipse.
Other Parameters
----------------
kwargs
{:func:`colour.plotting.artist`,
:func:`colour.plotting.diagrams.plot_chromaticity_diagram`,
:func:`colour.plotting.models.\
plot_ellipses_MacAdam1942_in_chromaticity_diagram`},
:func:`colour.plotting.render`},
See the documentation of the previously listed definitions.
Returns
-------
:class:`tuple`
Current figure and axes.
Examples
--------
>>> plot_ellipses_MacAdam1942_in_chromaticity_diagram_CIE1976UCS()
... # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...Axes...>)
.. image:: ../_static/\
Plotting_Plot_Ellipses_MacAdam1942_In_Chromaticity_Diagram_CIE1976UCS.png
:align: center
:alt: plot_ellipses_MacAdam1942_in_chromaticity_diagram_CIE1976UCS
"""
settings = dict(kwargs)
settings.update({"method": "CIE 1976 UCS"})
return plot_ellipses_MacAdam1942_in_chromaticity_diagram(
chromaticity_diagram_callable_CIE1976UCS,
chromaticity_diagram_clipping=chromaticity_diagram_clipping,
ellipse_kwargs=ellipse_kwargs,
**settings,
)
[docs]@override_style()
def plot_single_cctf(
cctf: Callable | str, cctf_decoding: bool = False, **kwargs: Any
) -> Tuple[plt.Figure, plt.Axes]:
"""
Plot given colourspace colour component transfer function.
Parameters
----------
cctf
Colour component transfer function to plot. ``function`` can be of any
type or form supported by the
:func:`colour.plotting.common.filter_passthrough` definition.
cctf_decoding
Plot the decoding colour component transfer function instead.
Other Parameters
----------------
kwargs
{:func:`colour.plotting.artist`,
:func:`colour.plotting.plot_multi_functions`,
:func:`colour.plotting.render`},
See the documentation of the previously listed definitions.
Returns
-------
:class:`tuple`
Current figure and axes.
Examples
--------
>>> plot_single_cctf("ITU-R BT.709") # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...Axes...>)
.. image:: ../_static/Plotting_Plot_Single_CCTF.png
:align: center
:alt: plot_single_cctf
"""
settings: Dict[str, Any] = {
"title": f"{cctf} - {'Decoding' if cctf_decoding else 'Encoding'} CCTF"
}
settings.update(kwargs)
return plot_multi_cctfs([cctf], cctf_decoding, **settings)
[docs]@override_style()
def plot_multi_cctfs(
cctfs: Callable | str | Sequence[Callable | str],
cctf_decoding: bool = False,
**kwargs: Any,
) -> Tuple[plt.Figure, plt.Axes]:
"""
Plot given colour component transfer functions.
Parameters
----------
cctfs
Colour component transfer function to plot. ``cctfs`` elements can be
of any type or form supported by the
:func:`colour.plotting.common.filter_passthrough` definition.
cctf_decoding
Plot the decoding colour component transfer function instead.
Other Parameters
----------------
kwargs
{:func:`colour.plotting.artist`,
:func:`colour.plotting.plot_multi_functions`,
:func:`colour.plotting.render`},
See the documentation of the previously listed definitions.
Returns
-------
:class:`tuple`
Current figure and axes.
Examples
--------
>>> plot_multi_cctfs(["ITU-R BT.709", "sRGB"]) # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...Axes...>)
.. image:: ../_static/Plotting_Plot_Multi_CCTFs.png
:align: center
:alt: plot_multi_cctfs
"""
cctfs_filtered = filter_passthrough(
CCTF_DECODINGS if cctf_decoding else CCTF_ENCODINGS, cctfs
)
mode = "Decoding" if cctf_decoding else "Encoding"
title = f"{', '.join(list(cctfs_filtered))} - {mode} CCTFs"
settings: Dict[str, Any] = {
"bounding_box": (0, 1, 0, 1),
"legend": True,
"title": title,
"x_label": "Signal Value" if cctf_decoding else "Tristimulus Value",
"y_label": "Tristimulus Value" if cctf_decoding else "Signal Value",
}
settings.update(kwargs)
with domain_range_scale("1"):
return plot_multi_functions(cctfs_filtered, **settings)
[docs]@override_style()
def plot_constant_hue_loci(
data: ArrayLike,
model: Literal[
"CAM02LCD",
"CAM02SCD",
"CAM02UCS",
"CAM16LCD",
"CAM16SCD",
"CAM16UCS",
"CIE XYZ",
"CIE xyY",
"CIE Lab",
"CIE Luv",
"CIE UCS",
"CIE UVW",
"DIN99",
"Hunter Lab",
"Hunter Rdab",
"ICaCb",
"ICtCp",
"IPT",
"IPT Ragoo 2021",
"IgPgTg",
"Jzazbz",
"OSA UCS",
"Oklab",
"hdr-CIELAB",
"hdr-IPT",
]
| str = "CIE Lab",
scatter_kwargs: dict | None = None,
convert_kwargs: dict | None = None,
**kwargs: Any,
) -> Tuple[plt.Figure, plt.Axes]:
"""
Plot given constant hue loci colour matches data such as that from
:cite:`Hung1995` or :cite:`Ebner1998` that are easily loaded with
`Colour - Datasets <https://github.com/colour-science/colour-datasets>`__.
Parameters
----------
data
Constant hue loci colour matches data expected to be an `ArrayLike` as
follows::
[
('name', XYZ_r, XYZ_cr, (XYZ_ct, XYZ_ct, XYZ_ct, ...), \
{metadata}),
('name', XYZ_r, XYZ_cr, (XYZ_ct, XYZ_ct, XYZ_ct, ...), \
{metadata}),
('name', XYZ_r, XYZ_cr, (XYZ_ct, XYZ_ct, XYZ_ct, ...), \
{metadata}),
...
]
where ``name`` is the hue angle or name, ``XYZ_r`` the *CIE XYZ*
tristimulus values of the reference illuminant, ``XYZ_cr`` the
*CIE XYZ* tristimulus values of the reference colour under the
reference illuminant, ``XYZ_ct`` the *CIE XYZ* tristimulus values of
the colour matches under the reference illuminant and ``metadata`` the
dataset metadata.
model
Colourspace model, see :attr:`colour.COLOURSPACE_MODELS` attribute for
the list of supported colourspace models.
scatter_kwargs
Keyword arguments for the :func:`matplotlib.pyplot.scatter` definition.
The following special keyword arguments can also be used:
- ``c`` : If ``c`` is set to *RGB*, the scatter will use the colours
as given by the ``RGB`` argument.
convert_kwargs
Keyword arguments for the :func:`colour.convert` definition.
Other Parameters
----------------
kwargs
{:func:`colour.plotting.artist`,
:func:`colour.plotting.plot_multi_functions`,
:func:`colour.plotting.render`},
See the documentation of the previously listed definitions.
Returns
-------
:class:`tuple`
Current figure and axes.
References
----------
:cite:`Ebner1998`, :cite:`Hung1995`, :cite:`Mansencal2019`
Examples
--------
>>> data = [
... [
... None,
... np.array([0.95010000, 1.00000000, 1.08810000]),
... np.array([0.40920000, 0.28120000, 0.30600000]),
... np.array(
... [
... [0.02495100, 0.01908600, 0.02032900],
... [0.10944300, 0.06235900, 0.06788100],
... [0.27186500, 0.18418700, 0.19565300],
... [0.48898900, 0.40749400, 0.44854600],
... ]
... ),
... None,
... ],
... [
... None,
... np.array([0.95010000, 1.00000000, 1.08810000]),
... np.array([0.30760000, 0.48280000, 0.42770000]),
... np.array(
... [
... [0.02108000, 0.02989100, 0.02790400],
... [0.06194700, 0.11251000, 0.09334400],
... [0.15255800, 0.28123300, 0.23234900],
... [0.34157700, 0.56681300, 0.47035300],
... ]
... ),
... None,
... ],
... [
... None,
... np.array([0.95010000, 1.00000000, 1.08810000]),
... np.array([0.39530000, 0.28120000, 0.18450000]),
... np.array(
... [
... [0.02436400, 0.01908600, 0.01468800],
... [0.10331200, 0.06235900, 0.02854600],
... [0.26311900, 0.18418700, 0.12109700],
... [0.43158700, 0.40749400, 0.39008600],
... ]
... ),
... None,
... ],
... [
... None,
... np.array([0.95010000, 1.00000000, 1.08810000]),
... np.array([0.20510000, 0.18420000, 0.57130000]),
... np.array(
... [
... [0.03039800, 0.02989100, 0.06123300],
... [0.08870000, 0.08498400, 0.21843500],
... [0.18405800, 0.18418700, 0.40111400],
... [0.32550100, 0.34047200, 0.50296900],
... [0.53826100, 0.56681300, 0.80010400],
... ]
... ),
... None,
... ],
... [
... None,
... np.array([0.95010000, 1.00000000, 1.08810000]),
... np.array([0.35770000, 0.28120000, 0.11250000]),
... np.array(
... [
... [0.03678100, 0.02989100, 0.01481100],
... [0.17127700, 0.11251000, 0.01229900],
... [0.30080900, 0.28123300, 0.21229800],
... [0.52976000, 0.40749400, 0.11720000],
... ]
... ),
... None,
... ],
... ]
>>> plot_constant_hue_loci(data, "CIE Lab") # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...Axes...>)
.. image:: ../_static/Plotting_Plot_Constant_Hue_Loci.png
:align: center
:alt: plot_constant_hue_loci
"""
# TODO: Filter appropriate colour models.
# NOTE: "dtype=object" is required for ragged array support
# in "Numpy" 1.24.0.
data = as_array(data, dtype=object) # pyright: ignore
settings: Dict[str, Any] = {"uniform": True}
settings.update(kwargs)
_figure, axes = artist(**settings)
scatter_settings = {
"s": 40,
"c": "RGB",
"marker": "o",
"alpha": 0.85,
"zorder": CONSTANTS_COLOUR_STYLE.zorder.foreground_scatter,
}
if scatter_kwargs is not None:
scatter_settings.update(scatter_kwargs)
convert_kwargs = optional(convert_kwargs, {})
use_RGB_colours = str(scatter_settings["c"]).upper() == "RGB"
colourspace = CONSTANTS_COLOUR_STYLE.colour.colourspace
for hue_data in data:
_name, XYZ_r, XYZ_cr, XYZ_ct, _metadata = hue_data
xy_r = XYZ_to_xy(XYZ_r)
convert_settings = {"illuminant": xy_r}
convert_settings.update(convert_kwargs)
ijk_ct = colourspace_model_axis_reorder(
convert(XYZ_ct, "CIE XYZ", model, **convert_settings), model
)
ijk_cr = colourspace_model_axis_reorder(
convert(XYZ_cr, "CIE XYZ", model, **convert_settings), model
)
ijk_ct *= COLOURSPACE_MODELS_DOMAIN_RANGE_SCALE_1_TO_REFERENCE[model]
ijk_cr *= COLOURSPACE_MODELS_DOMAIN_RANGE_SCALE_1_TO_REFERENCE[model]
def _linear_equation(
x: NDArrayFloat, a: NDArrayFloat, b: NDArrayFloat
) -> NDArrayFloat:
"""Define the canonical linear equation for a line."""
return a * x + b
popt, _pcov = scipy.optimize.curve_fit(
_linear_equation, ijk_ct[..., 0], ijk_ct[..., 1]
)
axes.plot(
ijk_ct[..., 0],
_linear_equation(ijk_ct[..., 0], *popt),
c=CONSTANTS_COLOUR_STYLE.colour.average,
zorder=CONSTANTS_COLOUR_STYLE.zorder.midground_line,
)
if use_RGB_colours:
RGB_ct = XYZ_to_RGB(
XYZ_ct, colourspace, xy_r, apply_cctf_encoding=True
)
RGB_cr = XYZ_to_RGB(
XYZ_cr, colourspace, xy_r, apply_cctf_encoding=True
)
scatter_settings["c"] = np.clip(RGB_ct, 0, 1)
axes.scatter(ijk_ct[..., 0], ijk_ct[..., 1], **scatter_settings)
axes.plot(
ijk_cr[..., 0],
ijk_cr[..., 1],
"s",
c=np.clip(np.ravel(RGB_cr), 0, 1),
markersize=CONSTANTS_COLOUR_STYLE.geometry.short * 8,
zorder=CONSTANTS_COLOUR_STYLE.zorder.midground_line,
)
labels = np.array(COLOURSPACE_MODELS_AXIS_LABELS[model])[
as_int_array(colourspace_model_axis_reorder([0, 1, 2], model))
]
settings = {
"axes": axes,
"title": f"Constant Hue Loci - {model}",
"x_label": labels[0],
"y_label": labels[1],
}
settings.update(kwargs)
return render(**settings)