def test_update_settings_collection(self):
"""
Tests :func:`colour.plotting.common.update_settings_collection`
definition.
"""
settings_collection = [{1: 2}, {3: 4}]
keyword_arguments = {5: 6}
update_settings_collection(settings_collection, keyword_arguments, 2)
self.assertListEqual(settings_collection, [{1: 2, 5: 6}, {3: 4, 5: 6}])
settings_collection = [{1: 2}, {3: 4}]
keyword_arguments = [{5: 6}, {7: 8}]
update_settings_collection(settings_collection, keyword_arguments, 2)
self.assertListEqual(settings_collection, [{1: 2, 5: 6}, {3: 4, 7: 8}])
def plot_sds_in_chromaticity_diagram(
sds,
cmfs='CIE 1931 2 Degree Standard Observer',
chromaticity_diagram_callable=plot_chromaticity_diagram,
method='CIE 1931',
annotate_kwargs=None,
plot_kwargs=None,
**kwargs):
"""
Plots given spectral distribution chromaticity coordinates into the
*Chromaticity Diagram* using given method.
Parameters
----------
sds : array_like or MultiSpectralDistributions
Spectral distributions or multi-spectral distributions to
plot. `sds` can be a single
:class:`colour.MultiSpectralDistributions` class instance, a list
of :class:`colour.MultiSpectralDistributions` class instances or a
list of :class:`colour.SpectralDistribution` class instances.
cmfs : unicode or XYZ_ColourMatchingFunctions, optional
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.filter_cmfs` definition.
chromaticity_diagram_callable : callable, optional
Callable responsible for drawing the *Chromaticity Diagram*.
method : unicode, optional
**{'CIE 1931', 'CIE 1960 UCS', 'CIE 1976 UCS'}**,
*Chromaticity Diagram* method.
annotate_kwargs : dict or array_like, optional
Keyword arguments for the :func:`plt.annotate` definition, used to
annotate the resulting chromaticity coordinates with their respective
spectral distribution names. ``annotate_kwargs`` can be either a single
dictionary applied to all the arrows with same settings or a sequence
of dictionaries with different settings for each spectral distribution.
The following special keyword arguments can also be used:
- *annotate* : bool, whether to annotate the spectral distributions.
plot_kwargs : dict or array_like, optional
Keyword arguments for the :func:`plt.plot` definition, used to control
the style of the plotted spectral distributions. ``plot_kwargs`` can be
either a single dictionary applied to all the plotted spectral
distributions with same settings or a sequence of dictionaries with
different settings for each plotted spectral distributions.
The following special keyword arguments can also be used:
- *illuminant* : unicode or :class:`colour.SpectralDistribution`, the
illuminant used to compute the spectral distributions colours. The
default is the illuminant associated with the whitepoint of the
default plotting colourspace. ``illuminant`` can be of any type or
form supported by the :func:`colour.plotting.filter_cmfs`
definition.
- *cmfs* : unicode, the standard observer colour matching functions
used for computing the spectral distributions colours. ``cmfs`` can
be of any type or form supported by the
:func:`colour.plotting.filter_cmfs` definition.
- *normalise_sd_colours* : bool, whether to normalise the computed
spectral distributions colours. The default is *True*.
- *use_sd_colours* : bool, whether to use the computed spectral
distributions colours under the plotting colourspace illuminant.
Alternatively, it is possible to use the :func:`plt.plot`
definition ``color`` argument with pre-computed values. The default
is *True*.
Other Parameters
----------------
\\**kwargs : dict, optional
{:func:`colour.plotting.artist`,
:func:`colour.plotting.diagrams.plot_chromaticity_diagram`,
:func:`colour.plotting.render`},
Please refer to the documentation of the previously listed definitions.
Also handles keywords arguments for deprecation management.
Returns
-------
tuple
Current figure and axes.
Examples
--------
>>> A = SDS_ILLUMINANTS['A']
>>> D65 = SDS_ILLUMINANTS['D65']
>>> annotate_kwargs = [
... {'xytext': (-25, 15), 'arrowprops':{'arrowstyle':'-'}},
... {}
... ]
>>> plot_kwargs = [
... {
... 'illuminant': SDS_ILLUMINANTS['E'],
... 'markersize' : 15,
... 'normalise_sd_colours': True,
... 'use_sd_colours': True
... },
... {'illuminant': SDS_ILLUMINANTS['E']},
... ]
>>> plot_sds_in_chromaticity_diagram(
... [A, D65], annotate_kwargs=annotate_kwargs, plot_kwargs=plot_kwargs)
... # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...AxesSubplot...>)
.. image:: ../_static/Plotting_Plot_SDS_In_Chromaticity_Diagram.png
:align: center
:alt: plot_sds_in_chromaticity_diagram
"""
annotate_kwargs = handle_arguments_deprecation(
{
'ArgumentRenamed': [['annotate_parameters', 'annotate_kwargs']],
}, **kwargs).get('annotate_kwargs', annotate_kwargs)
sds = sds_and_msds_to_sds(sds)
settings = {'uniform': True}
settings.update(kwargs)
_figure, axes = artist(**settings)
method = method.upper()
settings.update({
'axes': axes,
'standalone': False,
'method': method,
'cmfs': cmfs,
})
chromaticity_diagram_callable(**settings)
if method == 'CIE 1931':
def XYZ_to_ij(XYZ):
"""
Converts given *CIE XYZ* tristimulus values to *ij* chromaticity
coordinates.
"""
return XYZ_to_xy(XYZ)
bounding_box = (-0.1, 0.9, -0.1, 0.9)
elif method == 'CIE 1960 UCS':
def XYZ_to_ij(XYZ):
"""
Converts given *CIE XYZ* tristimulus values to *ij* chromaticity
coordinates.
"""
return UCS_to_uv(XYZ_to_UCS(XYZ))
bounding_box = (-0.1, 0.7, -0.2, 0.6)
elif method == 'CIE 1976 UCS':
def XYZ_to_ij(XYZ):
"""
Converts given *CIE XYZ* tristimulus values to *ij* chromaticity
coordinates.
"""
return Luv_to_uv(XYZ_to_Luv(XYZ))
bounding_box = (-0.1, 0.7, -0.1, 0.7)
else:
raise ValueError(
'Invalid method: "{0}", must be one of '
'[\'CIE 1931\', \'CIE 1960 UCS\', \'CIE 1976 UCS\']'.format(
method))
annotate_settings_collection = [{
'annotate': True,
'xytext': (-50, 30),
'textcoords': 'offset points',
'arrowprops': CONSTANTS_ARROW_STYLE,
} for _ in range(len(sds))]
if annotate_kwargs is not None:
update_settings_collection(annotate_settings_collection,
annotate_kwargs, len(sds))
plot_settings_collection = [{
'color':
CONSTANTS_COLOUR_STYLE.colour.brightest,
'label':
'{0}'.format(sd.strict_name),
'marker':
'o',
'markeredgecolor':
CONSTANTS_COLOUR_STYLE.colour.dark,
'markeredgewidth':
CONSTANTS_COLOUR_STYLE.geometry.short * 0.75,
'markersize': (CONSTANTS_COLOUR_STYLE.geometry.short * 6 +
CONSTANTS_COLOUR_STYLE.geometry.short * 0.75),
'cmfs':
cmfs,
'illuminant':
SDS_ILLUMINANTS[
CONSTANTS_COLOUR_STYLE.colour.colourspace.whitepoint_name],
'use_sd_colours':
False,
'normalise_sd_colours':
False,
} for sd in sds]
if plot_kwargs is not None:
update_settings_collection(plot_settings_collection, plot_kwargs,
len(sds))
for i, sd in enumerate(sds):
plot_settings = plot_settings_collection[i]
cmfs = first_item(filter_cmfs(plot_settings.pop('cmfs')).values())
illuminant = first_item(
filter_illuminants(plot_settings.pop('illuminant')).values())
normalise_sd_colours = plot_settings.pop('normalise_sd_colours')
use_sd_colours = plot_settings.pop('use_sd_colours')
with domain_range_scale('1'):
XYZ = sd_to_XYZ(sd, cmfs, illuminant)
if use_sd_colours:
if normalise_sd_colours:
XYZ /= XYZ[..., 1]
plot_settings['color'] = np.clip(XYZ_to_plotting_colourspace(XYZ),
0, 1)
ij = XYZ_to_ij(XYZ)
axes.plot(ij[0], ij[1], **plot_settings)
if (sd.name is not None
and annotate_settings_collection[i]['annotate']):
annotate_settings = annotate_settings_collection[i]
annotate_settings.pop('annotate')
axes.annotate(sd.name, xy=ij, **annotate_settings)
settings.update({'standalone': True, 'bounding_box': bounding_box})
settings.update(kwargs)
return render(**settings)
def plot_planckian_locus_in_chromaticity_diagram(
illuminants: Union[str, Sequence[str]],
chromaticity_diagram_callable: Callable = (
plot_chromaticity_diagram # type: ignore[has-type]
),
method: Union[Literal["CIE 1931", "CIE 1960 UCS"], str] = "CIE 1931",
annotate_kwargs: Optional[Union[Dict, List[Dict]]] = None,
plot_kwargs: Optional[Union[Dict, List[Dict]]] = None,
**kwargs: Any,
) -> Tuple[plt.Figure, plt.Axes]:
"""
Plot the *Planckian Locus* and given illuminants in the
*Chromaticity Diagram* according to given method.
Parameters
----------
illuminants
Illuminants to plot. ``illuminants`` elements can be of any
type or form supported by the
:func:`colour.plotting.filter_passthrough` definition.
chromaticity_diagram_callable
Callable responsible for drawing the *Chromaticity Diagram*.
method
*Chromaticity Diagram* method.
annotate_kwargs
Keyword arguments for the :func:`matplotlib.pyplot.annotate`
definition, used to annotate the resulting chromaticity coordinates
with their respective spectral distribution names. ``annotate_kwargs``
can be either a single dictionary applied to all the arrows with same
settings or a sequence of dictionaries with different settings for each
spectral distribution. The following special keyword arguments can also
be used:
- ``annotate`` : Whether to annotate the spectral distributions.
plot_kwargs
Keyword arguments for the :func:`matplotlib.pyplot.plot` definition,
used to control the style of the plotted illuminants. ``plot_kwargs``
can be either a single dictionary applied to all the plotted
illuminants with the same settings or a sequence of dictionaries with
different settings for eachplotted illuminant.
Other Parameters
----------------
kwargs
{:func:`colour.plotting.artist`,
:func:`colour.plotting.diagrams.plot_chromaticity_diagram`,
:func:`colour.plotting.temperature.plot_planckian_locus`,
:func:`colour.plotting.render`},
See the documentation of the previously listed definitions.
Returns
-------
:class:`tuple`
Current figure and axes.
Examples
--------
>>> annotate_kwargs = [
... {'xytext': (-25, 15), 'arrowprops':{'arrowstyle':'-'}},
... {'arrowprops':{'arrowstyle':'-['}},
... {},
... ]
>>> plot_kwargs = [
... {
... 'markersize' : 15,
... },
... { 'color': 'r'},
... {},
... ]
>>> plot_planckian_locus_in_chromaticity_diagram(
... ['A', 'B', 'C'],
... annotate_kwargs=annotate_kwargs,
... plot_kwargs=plot_kwargs
... ) # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...AxesSubplot...>)
.. image:: ../_static/Plotting_\
Plot_Planckian_Locus_In_Chromaticity_Diagram.png
:align: center
:alt: plot_planckian_locus_in_chromaticity_diagram
"""
cmfs = MSDS_CMFS["CIE 1931 2 Degree Standard Observer"]
illuminants_filtered = filter_passthrough(
CCS_ILLUMINANTS.get(cmfs.name),
illuminants # type: ignore[arg-type]
)
settings: Dict[str, Any] = {"uniform": True}
settings.update(kwargs)
_figure, axes = artist(**settings)
method = method.upper()
settings = {"axes": axes, "method": method}
settings.update(kwargs)
settings["standalone"] = False
chromaticity_diagram_callable(**settings)
plot_planckian_locus(**settings)
if method == "CIE 1931":
def xy_to_ij(xy: NDArray) -> NDArray:
"""
Convert given *CIE xy* chromaticity coordinates to *ij*
chromaticity coordinates.
"""
return xy
bounding_box = (-0.1, 0.9, -0.1, 0.9)
elif method == "CIE 1960 UCS":
def xy_to_ij(xy: NDArray) -> NDArray:
"""
Convert given *CIE xy* chromaticity coordinates to *ij*
chromaticity coordinates.
"""
return UCS_to_uv(XYZ_to_UCS(xy_to_XYZ(xy)))
bounding_box = (-0.1, 0.7, -0.2, 0.6)
else:
raise ValueError(f'Invalid method: "{method}", must be one of '
f'["CIE 1931", "CIE 1960 UCS"]')
annotate_settings_collection = [{
"annotate":
True,
"xytext": (-50, 30),
"textcoords":
"offset points",
"arrowprops":
CONSTANTS_ARROW_STYLE,
"zorder":
CONSTANTS_COLOUR_STYLE.zorder.foreground_annotation,
} for _ in range(len(illuminants_filtered))]
if annotate_kwargs is not None:
update_settings_collection(
annotate_settings_collection,
annotate_kwargs,
len(illuminants_filtered),
)
plot_settings_collection = [{
"color":
CONSTANTS_COLOUR_STYLE.colour.brightest,
"label":
f"{illuminant}",
"marker":
"o",
"markeredgecolor":
CONSTANTS_COLOUR_STYLE.colour.dark,
"markeredgewidth":
CONSTANTS_COLOUR_STYLE.geometry.short * 0.75,
"markersize": (CONSTANTS_COLOUR_STYLE.geometry.short * 6 +
CONSTANTS_COLOUR_STYLE.geometry.short * 0.75),
"zorder":
CONSTANTS_COLOUR_STYLE.zorder.foreground_line,
} for illuminant in illuminants_filtered]
if plot_kwargs is not None:
update_settings_collection(plot_settings_collection, plot_kwargs,
len(illuminants_filtered))
for i, (illuminant, xy) in enumerate(illuminants_filtered.items()):
plot_settings = plot_settings_collection[i]
ij = xy_to_ij(xy)
axes.plot(ij[0], ij[1], **plot_settings)
if annotate_settings_collection[i]["annotate"]:
annotate_settings = annotate_settings_collection[i]
annotate_settings.pop("annotate")
axes.annotate(illuminant, xy=ij, **annotate_settings)
title = ((
f"{', '.join(illuminants_filtered)} Illuminants - Planckian Locus\n"
f"{method.upper()} Chromaticity Diagram - "
"CIE 1931 2 Degree Standard Observer") if illuminants_filtered else
(f"Planckian Locus\n{method.upper()} Chromaticity Diagram - "
f"CIE 1931 2 Degree Standard Observer"))
settings.update({
"axes": axes,
"standalone": True,
"bounding_box": bounding_box,
"title": title,
})
settings.update(kwargs)
return render(**settings)
def plot_multi_sds(
sds: Union[Sequence[Union[SpectralDistribution,
MultiSpectralDistributions]],
MultiSpectralDistributions, ],
plot_kwargs: Optional[Union[Dict, List[Dict]]] = None,
**kwargs: Any,
) -> Tuple[plt.Figure, plt.Axes]:
"""
Plot given spectral distributions.
Parameters
----------
sds
Spectral distributions or multi-spectral distributions to
plot. `sds` can be a single
:class:`colour.MultiSpectralDistributions` class instance, a list
of :class:`colour.MultiSpectralDistributions` class instances or a
list of :class:`colour.SpectralDistribution` class instances.
plot_kwargs
Keyword arguments for the :func:`matplotlib.pyplot.plot` definition,
used to control the style of the plotted spectral distributions.
`plot_kwargs`` can be either a single dictionary applied to all the
plotted spectral distributions with the same settings or a sequence of
dictionaries with different settings for each plotted spectral
distributions. The following special keyword arguments can also be
used:
- ``illuminant`` : The illuminant used to compute the spectral
distributions colours. The default is the illuminant associated
with the whitepoint of the default plotting colourspace.
``illuminant`` can be of any type or form supported by the
:func:`colour.plotting.filter_cmfs` definition.
- ``cmfs`` : The standard observer colour matching functions used for
computing the spectral distributions colours. ``cmfs`` can be of
any type or form supported by the
:func:`colour.plotting.filter_cmfs` definition.
- ``normalise_sd_colours`` : Whether to normalise the computed
spectral distributions colours. The default is *True*.
- ``use_sd_colours`` : Whether to use the computed spectral
distributions colours under the plotting colourspace illuminant.
Alternatively, it is possible to use the
:func:`matplotlib.pyplot.plot` definition ``color`` argument with
pre-computed values. The default is *True*.
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
--------
>>> from colour import SpectralDistribution
>>> data_1 = {
... 500: 0.004900,
... 510: 0.009300,
... 520: 0.063270,
... 530: 0.165500,
... 540: 0.290400,
... 550: 0.433450,
... 560: 0.594500
... }
>>> data_2 = {
... 500: 0.323000,
... 510: 0.503000,
... 520: 0.710000,
... 530: 0.862000,
... 540: 0.954000,
... 550: 0.994950,
... 560: 0.995000
... }
>>> sd_1 = SpectralDistribution(data_1, name='Custom 1')
>>> sd_2 = SpectralDistribution(data_2, name='Custom 2')
>>> plot_kwargs = [
... {'use_sd_colours': True},
... {'use_sd_colours': True, 'linestyle': 'dashed'},
... ]
>>> plot_multi_sds([sd_1, sd_2], plot_kwargs=plot_kwargs)
... # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...AxesSubplot...>)
.. image:: ../_static/Plotting_Plot_Multi_SDS.png
:align: center
:alt: plot_multi_sds
"""
_figure, axes = artist(**kwargs)
sds_converted = sds_and_msds_to_sds(sds)
plot_settings_collection = [{
"label":
f"{sd.strict_name}",
"zorder":
CONSTANTS_COLOUR_STYLE.zorder.midground_line,
"cmfs":
"CIE 1931 2 Degree Standard Observer",
"illuminant":
SDS_ILLUMINANTS[
CONSTANTS_COLOUR_STYLE.colour.colourspace.whitepoint_name],
"use_sd_colours":
False,
"normalise_sd_colours":
False,
} for sd in sds_converted]
if plot_kwargs is not None:
update_settings_collection(plot_settings_collection, plot_kwargs,
len(sds_converted))
x_limit_min, x_limit_max, y_limit_min, y_limit_max = [], [], [], []
for i, sd in enumerate(sds_converted):
plot_settings = plot_settings_collection[i]
cmfs = cast(
MultiSpectralDistributions,
first_item(filter_cmfs(plot_settings.pop("cmfs")).values()),
)
illuminant = cast(
SpectralDistribution,
first_item(
filter_illuminants(plot_settings.pop("illuminant")).values()),
)
normalise_sd_colours = plot_settings.pop("normalise_sd_colours")
use_sd_colours = plot_settings.pop("use_sd_colours")
wavelengths, values = sd.wavelengths, sd.values
shape = sd.shape
x_limit_min.append(shape.start)
x_limit_max.append(shape.end)
y_limit_min.append(min(values))
y_limit_max.append(max(values))
if use_sd_colours:
with domain_range_scale("1"):
XYZ = sd_to_XYZ(sd, cmfs, illuminant)
if normalise_sd_colours:
XYZ /= XYZ[..., 1]
plot_settings["color"] = np.clip(XYZ_to_plotting_colourspace(XYZ),
0, 1)
axes.plot(wavelengths, values, **plot_settings)
bounding_box = (
min(x_limit_min),
max(x_limit_max),
min(y_limit_min),
max(y_limit_max) + np.max(y_limit_max) * 0.05,
)
settings: Dict[str, Any] = {
"axes": axes,
"bounding_box": bounding_box,
"legend": True,
"x_label": "Wavelength $\\lambda$ (nm)",
"y_label": "Spectral Distribution",
}
settings.update(kwargs)
return render(**settings)
def plot_sds_in_chromaticity_diagram(
sds: Union[Sequence[Union[SpectralDistribution,
MultiSpectralDistributions]],
MultiSpectralDistributions, ],
cmfs: Union[MultiSpectralDistributions, str, Sequence[Union[
MultiSpectralDistributions,
str]], ] = "CIE 1931 2 Degree Standard Observer",
chromaticity_diagram_callable: Callable = plot_chromaticity_diagram,
method: Union[Literal["CIE 1931", "CIE 1960 UCS", "CIE 1976 UCS"],
str] = "CIE 1931",
annotate_kwargs: Optional[Union[Dict, List[Dict]]] = None,
plot_kwargs: Optional[Union[Dict, List[Dict]]] = None,
**kwargs: Any,
) -> Tuple[plt.Figure, plt.Axes]:
"""
Plot given spectral distribution chromaticity coordinates into the
*Chromaticity Diagram* using given method.
Parameters
----------
sds
Spectral distributions or multi-spectral distributions to
plot. `sds` can be a single
:class:`colour.MultiSpectralDistributions` class instance, a list
of :class:`colour.MultiSpectralDistributions` class instances or a
list of :class:`colour.SpectralDistribution` class instances.
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.filter_cmfs` definition.
chromaticity_diagram_callable
Callable responsible for drawing the *Chromaticity Diagram*.
method
*Chromaticity Diagram* method.
annotate_kwargs
Keyword arguments for the :func:`matplotlib.pyplot.annotate`
definition, used to annotate the resulting chromaticity coordinates
with their respective spectral distribution names. ``annotate_kwargs``
can be either a single dictionary applied to all the arrows with same
settings or a sequence of dictionaries with different settings for each
spectral distribution. The following special keyword arguments can also
be used:
- ``annotate`` : Whether to annotate the spectral distributions.
plot_kwargs
Keyword arguments for the :func:`matplotlib.pyplot.plot` definition,
used to control the style of the plotted spectral distributions.
`plot_kwargs`` can be either a single dictionary applied to all the
plotted spectral distributions with the same settings or a sequence of
dictionaries with different settings for each plotted spectral
distributions. The following special keyword arguments can also be
used:
- ``illuminant`` : The illuminant used to compute the spectral
distributions colours. The default is the illuminant associated
with the whitepoint of the default plotting colourspace.
``illuminant`` can be of any type or form supported by the
:func:`colour.plotting.filter_cmfs` definition.
- ``cmfs`` : The standard observer colour matching functions used for
computing the spectral distributions colours. ``cmfs`` can be of
any type or form supported by the
:func:`colour.plotting.filter_cmfs` definition.
- ``normalise_sd_colours`` : Whether to normalise the computed
spectral distributions colours. The default is *True*.
- ``use_sd_colours`` : Whether to use the computed spectral
distributions colours under the plotting colourspace illuminant.
Alternatively, it is possible to use the
:func:`matplotlib.pyplot.plot` definition ``color`` argument with
pre-computed values. The default is *True*.
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
--------
>>> A = SDS_ILLUMINANTS['A']
>>> D65 = SDS_ILLUMINANTS['D65']
>>> annotate_kwargs = [
... {'xytext': (-25, 15), 'arrowprops':{'arrowstyle':'-'}},
... {}
... ]
>>> plot_kwargs = [
... {
... 'illuminant': SDS_ILLUMINANTS['E'],
... 'markersize' : 15,
... 'normalise_sd_colours': True,
... 'use_sd_colours': True
... },
... {'illuminant': SDS_ILLUMINANTS['E']},
... ]
>>> plot_sds_in_chromaticity_diagram(
... [A, D65], annotate_kwargs=annotate_kwargs, plot_kwargs=plot_kwargs)
... # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...AxesSubplot...>)
.. image:: ../_static/Plotting_Plot_SDS_In_Chromaticity_Diagram.png
:align: center
:alt: plot_sds_in_chromaticity_diagram
"""
method = validate_method(method,
["CIE 1931", "CIE 1960 UCS", "CIE 1976 UCS"])
sds_converted = sds_and_msds_to_sds(sds)
settings: Dict[str, Any] = {"uniform": True}
settings.update(kwargs)
_figure, axes = artist(**settings)
settings.update({
"axes": axes,
"standalone": False,
"method": method,
"cmfs": cmfs,
})
chromaticity_diagram_callable(**settings)
if method == "cie 1931":
def XYZ_to_ij(XYZ: NDArray) -> NDArray:
"""
Convert given *CIE XYZ* tristimulus values to *ij* chromaticity
coordinates.
"""
return XYZ_to_xy(XYZ)
bounding_box = (-0.1, 0.9, -0.1, 0.9)
elif method == "cie 1960 ucs":
def XYZ_to_ij(XYZ: NDArray) -> NDArray:
"""
Convert given *CIE XYZ* tristimulus values to *ij* chromaticity
coordinates.
"""
return UCS_to_uv(XYZ_to_UCS(XYZ))
bounding_box = (-0.1, 0.7, -0.2, 0.6)
elif method == "cie 1976 ucs":
def XYZ_to_ij(XYZ: NDArray) -> NDArray:
"""
Convert given *CIE XYZ* tristimulus values to *ij* chromaticity
coordinates.
"""
return Luv_to_uv(XYZ_to_Luv(XYZ))
bounding_box = (-0.1, 0.7, -0.1, 0.7)
annotate_settings_collection = [{
"annotate":
True,
"xytext": (-50, 30),
"textcoords":
"offset points",
"arrowprops":
CONSTANTS_ARROW_STYLE,
"zorder":
CONSTANTS_COLOUR_STYLE.zorder.midground_annotation,
} for _ in range(len(sds_converted))]
if annotate_kwargs is not None:
update_settings_collection(annotate_settings_collection,
annotate_kwargs, len(sds_converted))
plot_settings_collection = [{
"color":
CONSTANTS_COLOUR_STYLE.colour.brightest,
"label":
f"{sd.strict_name}",
"marker":
"o",
"markeredgecolor":
CONSTANTS_COLOUR_STYLE.colour.dark,
"markeredgewidth":
CONSTANTS_COLOUR_STYLE.geometry.short * 0.75,
"markersize": (CONSTANTS_COLOUR_STYLE.geometry.short * 6 +
CONSTANTS_COLOUR_STYLE.geometry.short * 0.75),
"zorder":
CONSTANTS_COLOUR_STYLE.zorder.midground_line,
"cmfs":
cmfs,
"illuminant":
SDS_ILLUMINANTS[
CONSTANTS_COLOUR_STYLE.colour.colourspace.whitepoint_name],
"use_sd_colours":
False,
"normalise_sd_colours":
False,
} for sd in sds_converted]
if plot_kwargs is not None:
update_settings_collection(plot_settings_collection, plot_kwargs,
len(sds_converted))
for i, sd in enumerate(sds_converted):
plot_settings = plot_settings_collection[i]
cmfs = cast(
MultiSpectralDistributions,
first_item(filter_cmfs(plot_settings.pop("cmfs")).values()),
)
illuminant = cast(
SpectralDistribution,
first_item(
filter_illuminants(plot_settings.pop("illuminant")).values()),
)
normalise_sd_colours = plot_settings.pop("normalise_sd_colours")
use_sd_colours = plot_settings.pop("use_sd_colours")
with domain_range_scale("1"):
XYZ = sd_to_XYZ(sd, cmfs, illuminant)
if use_sd_colours:
if normalise_sd_colours:
XYZ /= XYZ[..., 1]
plot_settings["color"] = np.clip(XYZ_to_plotting_colourspace(XYZ),
0, 1)
ij = XYZ_to_ij(XYZ)
axes.plot(ij[0], ij[1], **plot_settings)
if sd.name is not None and annotate_settings_collection[i]["annotate"]:
annotate_settings = annotate_settings_collection[i]
annotate_settings.pop("annotate")
axes.annotate(sd.name, xy=ij, **annotate_settings)
settings.update({"standalone": True, "bounding_box": bounding_box})
settings.update(kwargs)
return render(**settings)
def plot_planckian_locus_in_chromaticity_diagram(
illuminants,
chromaticity_diagram_callable=plot_chromaticity_diagram,
planckian_locus_callable=plot_planckian_locus,
method='CIE 1931',
annotate_kwargs=None,
plot_kwargs=None,
**kwargs):
"""
Plots the *Planckian Locus* and given illuminants in the
*Chromaticity Diagram* according to given method.
Parameters
----------
illuminants : unicode or object or array_like
Illuminants to plot. ``illuminants`` elements can be of any
type or form supported by the
:func:`colour.plotting.filter_passthrough` definition.
chromaticity_diagram_callable : callable, optional
Callable responsible for drawing the *Chromaticity Diagram*.
planckian_locus_callable : callable, optional
Callable responsible for drawing the *Planckian Locus*.
method : unicode, optional
**{'CIE 1931', 'CIE 1960 UCS', 'CIE 1976 UCS'}**,
*Chromaticity Diagram* method.
annotate_kwargs : dict or array_like, optional
Keyword arguments for the :func:`plt.annotate` definition, used to
annotate the resulting chromaticity coordinates with their respective
illuminant names. ``annotate_kwargs`` can be either a single dictionary
applied to all the arrows with same settings or a sequence of
dictionaries with different settings for each illuminant.
The following special keyword arguments can also be used:
- *annotate* : bool, whether to annotate the illuminants.
plot_kwargs : dict or array_like, optional
Keyword arguments for the :func:`plt.plot` definition, used to control
the style of the plotted illuminants. ``plot_kwargs`` can be either a
single dictionary applied to all the plotted illuminants with same
settings or a sequence of dictionaries with different settings for each
plotted illuminant.
Other Parameters
----------------
\\**kwargs : dict, optional
{:func:`colour.plotting.artist`,
:func:`colour.plotting.diagrams.plot_chromaticity_diagram`,
:func:`colour.plotting.temperature.plot_planckian_locus`,
:func:`colour.plotting.render`},
Please refer to the documentation of the previously listed definitions.
Also handles keywords arguments for deprecation management.
Returns
-------
tuple
Current figure and axes.
Examples
--------
>>> annotate_kwargs = [
... {'xytext': (-25, 15), 'arrowprops':{'arrowstyle':'-'}},
... {'arrowprops':{'arrowstyle':'-['}},
... {},
... ]
>>> plot_kwargs = [
... {
... 'markersize' : 15,
... },
... { 'color': 'r'},
... {},
... ]
>>> plot_planckian_locus_in_chromaticity_diagram(
... ['A', 'B', 'C'],
... annotate_kwargs=annotate_kwargs,
... plot_kwargs=plot_kwargs
... ) # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...AxesSubplot...>)
.. image:: ../_static/Plotting_\
Plot_Planckian_Locus_In_Chromaticity_Diagram.png
:align: center
:alt: plot_planckian_locus_in_chromaticity_diagram
"""
annotate_kwargs = handle_arguments_deprecation(
{
'ArgumentRenamed': [['annotate_parameters', 'annotate_kwargs']],
}, **kwargs).get('annotate_kwargs', annotate_kwargs)
cmfs = MSDS_CMFS['CIE 1931 2 Degree Standard Observer']
illuminants = filter_passthrough(CCS_ILLUMINANTS.get(cmfs.name),
illuminants)
settings = {'uniform': True}
settings.update(kwargs)
_figure, axes = artist(**settings)
method = method.upper()
settings = {'axes': axes, 'method': method}
settings.update(kwargs)
settings['standalone'] = False
chromaticity_diagram_callable(**settings)
planckian_locus_callable(**settings)
if method == 'CIE 1931':
def xy_to_ij(xy):
"""
Converts given *CIE xy* chromaticity coordinates to *ij*
chromaticity coordinates.
"""
return xy
bounding_box = (-0.1, 0.9, -0.1, 0.9)
elif method == 'CIE 1960 UCS':
def xy_to_ij(xy):
"""
Converts given *CIE xy* chromaticity coordinates to *ij*
chromaticity coordinates.
"""
return UCS_to_uv(XYZ_to_UCS(xy_to_XYZ(xy)))
bounding_box = (-0.1, 0.7, -0.2, 0.6)
else:
raise ValueError('Invalid method: "{0}", must be one of '
'[\'CIE 1931\', \'CIE 1960 UCS\']'.format(method))
annotate_settings_collection = [{
'annotate': True,
'xytext': (-50, 30),
'textcoords': 'offset points',
'arrowprops': CONSTANTS_ARROW_STYLE,
} for _ in range(len(illuminants))]
if annotate_kwargs is not None:
update_settings_collection(annotate_settings_collection,
annotate_kwargs, len(illuminants))
plot_settings_collection = [{
'color':
CONSTANTS_COLOUR_STYLE.colour.brightest,
'label':
'{0}'.format(illuminant),
'marker':
'o',
'markeredgecolor':
CONSTANTS_COLOUR_STYLE.colour.dark,
'markeredgewidth':
CONSTANTS_COLOUR_STYLE.geometry.short * 0.75,
'markersize': (CONSTANTS_COLOUR_STYLE.geometry.short * 6 +
CONSTANTS_COLOUR_STYLE.geometry.short * 0.75),
} for illuminant in illuminants]
if plot_kwargs is not None:
update_settings_collection(plot_settings_collection, plot_kwargs,
len(illuminants))
for i, (illuminant, xy) in enumerate(illuminants.items()):
plot_settings = plot_settings_collection[i]
ij = xy_to_ij(xy)
axes.plot(ij[0], ij[1], **plot_settings)
if annotate_settings_collection[i]['annotate']:
annotate_settings = annotate_settings_collection[i]
annotate_settings.pop('annotate')
axes.annotate(illuminant, xy=ij, **annotate_settings)
title = (('{0} Illuminants - Planckian Locus\n'
'{1} Chromaticity Diagram - '
'CIE 1931 2 Degree Standard Observer').format(
', '.join(illuminants), method) if illuminants else
('Planckian Locus\n{0} Chromaticity Diagram - '
'CIE 1931 2 Degree Standard Observer'.format(method)))
settings.update({
'axes': axes,
'standalone': True,
'bounding_box': bounding_box,
'title': title,
})
settings.update(kwargs)
return render(**settings)
def plot_multi_sds(sds, plot_kwargs=None, **kwargs):
"""
Plots given spectral distributions.
Parameters
----------
sds : array_like or MultiSpectralDistributions
Spectral distributions or multi-spectral distributions to
plot. `sds` can be a single
:class:`colour.MultiSpectralDistributions` class instance, a list
of :class:`colour.MultiSpectralDistributions` class instances or a
list of :class:`colour.SpectralDistribution` class instances.
plot_kwargs : dict or array_like, optional
Keyword arguments for the :func:`plt.plot` definition, used to control
the style of the plotted spectral distributions. ``plot_kwargs`` can be
either a single dictionary applied to all the plotted spectral
distributions with same settings or a sequence of dictionaries with
different settings for each plotted spectral distributions.
The following special keyword arguments can also be used:
- *illuminant* : unicode or :class:`colour.SpectralDistribution`, the
illuminant used to compute the spectral distributions colours. The
default is the illuminant associated with the whitepoint of the
default plotting colourspace. ``illuminant`` can be of any type or
form supported by the :func:`colour.plotting.filter_cmfs`
definition.
- *cmfs* : unicode, the standard observer colour matching functions
used for computing the spectral distributions colours. ``cmfs`` can
be of any type or form supported by the
:func:`colour.plotting.filter_cmfs` definition.
- *normalise_sd_colours* : bool, whether to normalise the computed
spectral distributions colours. The default is *True*.
- *use_sd_colours* : bool, whether to use the computed spectral
distributions colours under the plotting colourspace illuminant.
Alternatively, it is possible to use the :func:`plt.plot`
definition ``color`` argument with pre-computed values. The default
is *True*.
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
--------
>>> from colour import SpectralDistribution
>>> data_1 = {
... 500: 0.004900,
... 510: 0.009300,
... 520: 0.063270,
... 530: 0.165500,
... 540: 0.290400,
... 550: 0.433450,
... 560: 0.594500
... }
>>> data_2 = {
... 500: 0.323000,
... 510: 0.503000,
... 520: 0.710000,
... 530: 0.862000,
... 540: 0.954000,
... 550: 0.994950,
... 560: 0.995000
... }
>>> sd_1 = SpectralDistribution(data_1, name='Custom 1')
>>> sd_2 = SpectralDistribution(data_2, name='Custom 2')
>>> plot_kwargs = [
... {'use_sd_colours': True},
... {'use_sd_colours': True, 'linestyle': 'dashed'},
... ]
>>> plot_multi_sds([sd_1, sd_2], plot_kwargs=plot_kwargs)
... # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...AxesSubplot...>)
.. image:: ../_static/Plotting_Plot_Multi_SDS.png
:align: center
:alt: plot_multi_sds
"""
handle_arguments_deprecation(
{'ArgumentRemoved': ['normalise_sd_colours', 'use_sds_colours']},
**kwargs)
_figure, axes = artist(**kwargs)
sds = sds_and_msds_to_sds(sds)
plot_settings_collection = [{
'label':
'{0}'.format(sd.strict_name),
'cmfs':
'CIE 1931 2 Degree Standard Observer',
'illuminant':
SDS_ILLUMINANTS[
CONSTANTS_COLOUR_STYLE.colour.colourspace.whitepoint_name],
'use_sd_colours':
False,
'normalise_sd_colours':
False,
} for sd in sds]
if plot_kwargs is not None:
update_settings_collection(plot_settings_collection, plot_kwargs,
len(sds))
x_limit_min, x_limit_max, y_limit_min, y_limit_max = [], [], [], []
for i, sd in enumerate(sds):
plot_settings = plot_settings_collection[i]
cmfs = first_item(filter_cmfs(plot_settings.pop('cmfs')).values())
illuminant = first_item(
filter_illuminants(plot_settings.pop('illuminant')).values())
normalise_sd_colours = plot_settings.pop('normalise_sd_colours')
use_sd_colours = plot_settings.pop('use_sd_colours')
wavelengths, values = sd.wavelengths, sd.values
shape = sd.shape
x_limit_min.append(shape.start)
x_limit_max.append(shape.end)
y_limit_min.append(min(values))
y_limit_max.append(max(values))
if use_sd_colours:
with domain_range_scale('1'):
XYZ = sd_to_XYZ(sd, cmfs, illuminant)
if normalise_sd_colours:
XYZ /= XYZ[..., 1]
plot_settings['color'] = np.clip(XYZ_to_plotting_colourspace(XYZ),
0, 1)
axes.plot(wavelengths, values, **plot_settings)
bounding_box = (min(x_limit_min), max(x_limit_max), min(y_limit_min),
max(y_limit_max) + max(y_limit_max) * 0.05)
settings = {
'axes': axes,
'bounding_box': bounding_box,
'legend': True,
'x_label': 'Wavelength $\\lambda$ (nm)',
'y_label': 'Spectral Distribution',
}
settings.update(kwargs)
return render(**settings)