def right(self, value):
"""
Setter for the **self.right** property.
"""
if value is not None:
assert is_numeric(value), (
'"{0}" attribute: "{1}" is not a "numeric"!').format(
'right', value)
self._right = value
def right(self, value: Optional[Number]):
"""Setter for the **self.right** property."""
if value is not None:
attest(
is_numeric(value),
f'"right" property: "{value}" is not a "number"!',
)
self._right = value
def right(self, value):
"""
Setter for the **self.right** property.
"""
if value is not None:
assert is_numeric(value), (
'"{0}" attribute: "{1}" is not a "numeric"!').format(
'right', value)
self._right = value
def default(self, value):
"""
Setter for the **self.default** property.
"""
if value is not None:
assert is_numeric(value), (
'"default" variable must be a "numeric"!')
self._default = value
def absolute_tolerance(self, value):
"""
Setter for the **self.absolute_tolerance** property.
"""
if value is not None:
assert is_numeric(value), (
'"absolute_tolerance" variable must be a "numeric"!')
self._absolute_tolerance = value
def bandwidth_FWHM(self, value):
"""
Setter for the **self.bandwidth_FWHM** property.
"""
if value is not None:
assert is_numeric(value), (
'"{0}" attribute: "{1}" is not a "numeric"!'.format(
'bandwidth_FWHM', value))
self._bandwidth_FWHM = value
def bandwidth_FWHM(self, value: Optional[Floating]):
"""Setter for the **self.bandwidth_FWHM** property."""
if value is not None:
attest(
is_numeric(value),
f'"bandwidth_FWHM" property: "{value}" is not a "number"!',
)
value = as_float_scalar(value)
self._bandwidth_FWHM = value
def translate_speed(self, value):
"""
Setter for **self._translate_speed** private attribute.
Parameters
----------
value : numeric
Attribute value.
"""
if value is not None:
assert is_numeric(value), ('"{0}" is not a numeric!'.format(
'translate_speed', value))
self._translate_speed = value
def left(self, value):
"""
Setter for **self.__left** private attribute.
Parameters
----------
value : numeric
Attribute value.
"""
if value is not None:
assert is_numeric(value), (
'"{0}" attribute: "{1}" type is not "numeric"!').format(
'left', value)
self.__left = value
def right(self, value):
"""
Setter for **self.__right** private attribute.
Parameters
----------
value : numeric
Attribute value.
"""
if value is not None:
assert is_numeric(value), (
'"{0}" attribute: "{1}" is not a "numeric"!').format(
'right', value)
self.__right = value
def right(self, value):
"""
Setter for **self._right** private attribute.
Parameters
----------
value : numeric
Attribute value.
"""
if value is not None:
assert is_numeric(value), (
'"{0}" attribute: "{1}" is not a "numeric"!').format(
'right', value)
self._right = value
def bandwidth_FWHM(self, value):
"""
Setter for **self.__bandwidth_FWHM** private attribute.
Parameters
----------
value : numeric
Attribute value.
"""
if value is not None:
assert is_numeric(value), (
'"{0}" attribute: "{1}" is not a "numeric"!'.format(
'bandwidth_FWHM', value))
self.__bandwidth_FWHM = value
def bandwidth_FWHM(self, value):
"""
Setter for **self._bandwidth_FWHM** private attribute.
Parameters
----------
value : numeric
Attribute value.
"""
if value is not None:
assert is_numeric(value), (
'"{0}" attribute: "{1}" is not a "numeric"!'.format(
'bandwidth_FWHM', value))
self._bandwidth_FWHM = value
def test_is_numeric(self):
"""
Tests :func:`colour.utilities.common.is_numeric` definition.
"""
self.assertTrue(is_numeric(1))
self.assertTrue(is_numeric(1))
self.assertTrue(is_numeric(complex(1)))
self.assertFalse(is_numeric((1, )))
self.assertFalse(is_numeric([1]))
self.assertFalse(is_numeric('1'))
def test_is_numeric(self):
"""
Tests :func:`colour.utilities.common.is_numeric` definition.
"""
self.assertTrue(is_numeric(1))
self.assertTrue(is_numeric(1))
self.assertTrue(is_numeric(complex(1)))
self.assertFalse(is_numeric((1, )))
self.assertFalse(is_numeric([1]))
self.assertFalse(is_numeric('1'))
def __round(self, item):
"""
Rounds given item if numeric.
Parameters
----------
item : object
Attribute.
Parameters
----------
item : object
Attribute.
Notes
-----
- Reimplements the :meth:`MutableMapping.__setitem__` method.
"""
if is_numeric(item):
return round(item, self.__key_decimals)
else:
return item
def __round(self, item):
"""
Rounds given item if numeric.
Parameters
----------
item : object
Attribute.
Parameters
----------
item : object
Attribute.
Notes
-----
- Reimplements the :meth:`MutableMapping.__setitem__` method.
"""
if is_numeric(item):
return round(item, self.__key_decimals)
else:
return item
def corresponding_chromaticities_prediction_VonKries(experiment=1,
transform='CAT02'):
"""
Returns the corresponding chromaticities prediction for *Von Kries*
chromatic adaptation model using given transform.
Parameters
----------
experiment : integer or CorrespondingColourDataset, optional
{1, 2, 3, 4, 6, 8, 9, 11, 12}
*Breneman (1987)* experiment number or
:class:`colour.CorrespondingColourDataset` class instance.
transform : unicode, optional
**{'CAT02', 'XYZ Scaling', 'Von Kries', 'Bradford', 'Sharp',
'Fairchild', 'CMCCAT97', 'CMCCAT2000', 'CAT02_BRILL_CAT', 'Bianco',
'Bianco PC'}**,
Chromatic adaptation transform.
Returns
-------
tuple
Corresponding chromaticities prediction.
References
----------
:cite:`Breneman1987b`, :cite:`Fairchild2013t`
Examples
--------
>>> from pprint import pprint
>>> pr = corresponding_chromaticities_prediction_VonKries(2, 'Bradford')
>>> pr = [(p.uv_m, p.uv_p) for p in pr]
>>> pprint(pr) # doctest: +ELLIPSIS
[(array([ 0.207, 0.486]), array([ 0.2082014..., 0.4722922...])),
(array([ 0.449, 0.511]), array([ 0.4489102..., 0.5071602...])),
(array([ 0.263, 0.505]), array([ 0.2643545..., 0.4959631...])),
(array([ 0.322, 0.545]), array([ 0.3348730..., 0.5471220...])),
(array([ 0.316, 0.537]), array([ 0.3248758..., 0.5390589...])),
(array([ 0.265, 0.553]), array([ 0.2733105..., 0.5555028...])),
(array([ 0.221, 0.538]), array([ 0.227148 ..., 0.5331318...)),
(array([ 0.135, 0.532]), array([ 0.1442730..., 0.5226804...])),
(array([ 0.145, 0.472]), array([ 0.1498745..., 0.4550785...])),
(array([ 0.163, 0.331]), array([ 0.1564975..., 0.3148796...])),
(array([ 0.176, 0.431]), array([ 0.1760593..., 0.4103772...])),
(array([ 0.244, 0.349]), array([ 0.2259805..., 0.3465291...]))]
"""
experiment_results = (convert_experiment_results_Breneman1987(experiment)
if is_numeric(experiment) else experiment)
with domain_range_scale(1):
XYZ_w, XYZ_wr = experiment_results.XYZ_t, experiment_results.XYZ_r
xy_w, xy_wr = XYZ_to_xy([XYZ_w, XYZ_wr])
uv_t = Luv_to_uv(XYZ_to_Luv(experiment_results.XYZ_ct, xy_w), xy_w)
uv_m = Luv_to_uv(XYZ_to_Luv(experiment_results.XYZ_cr, xy_wr), xy_wr)
XYZ_1 = experiment_results.XYZ_ct
XYZ_2 = chromatic_adaptation_VonKries(XYZ_1, XYZ_w, XYZ_wr, transform)
uv_p = Luv_to_uv(XYZ_to_Luv(XYZ_2, xy_wr), xy_wr)
return tuple([
CorrespondingChromaticitiesPrediction(experiment_results.name,
uv_t[i], uv_m[i], uv_p[i])
for i in range(len(uv_t))
])
def corresponding_chromaticities_prediction_CMCCAT2000(experiment=1):
"""
Returns the corresponding chromaticities prediction for *CMCCAT2000*
chromatic adaptation model.
Parameters
----------
experiment : integer or CorrespondingColourDataset, optional
{1, 2, 3, 4, 6, 8, 9, 11, 12}
*Breneman (1987)* experiment number or
:class:`colour.CorrespondingColourDataset` class instance.
Returns
-------
tuple
Corresponding chromaticities prediction.
References
----------
:cite:`Breneman1987b`, :cite:`Li2002a`, :cite:`Westland2012k`
Examples
--------
>>> from pprint import pprint
>>> pr = corresponding_chromaticities_prediction_CMCCAT2000(2)
>>> pr = [(p.uv_m, p.uv_p) for p in pr]
>>> pprint(pr) # doctest: +ELLIPSIS
[(array([ 0.207, 0.486]), array([ 0.2083210..., 0.4727168...])),
(array([ 0.449, 0.511]), array([ 0.4459270..., 0.5077735...])),
(array([ 0.263, 0.505]), array([ 0.2640262..., 0.4955361...])),
(array([ 0.322, 0.545]), array([ 0.3316884..., 0.5431580...])),
(array([ 0.316, 0.537]), array([ 0.3222624..., 0.5357624...])),
(array([ 0.265, 0.553]), array([ 0.2710705..., 0.5501997...])),
(array([ 0.221, 0.538]), array([ 0.2261826..., 0.5294740...])),
(array([ 0.135, 0.532]), array([ 0.1439693..., 0.5190984...])),
(array([ 0.145, 0.472]), array([ 0.1494835..., 0.4556760...])),
(array([ 0.163, 0.331]), array([ 0.1563172..., 0.3164151...])),
(array([ 0.176, 0.431]), array([ 0.1763199..., 0.4127589...])),
(array([ 0.244, 0.349]), array([ 0.2287638..., 0.3499324...]))]
"""
experiment_results = (convert_experiment_results_Breneman1987(experiment)
if is_numeric(experiment) else experiment)
with domain_range_scale(1):
XYZ_w, XYZ_wr = experiment_results.XYZ_t, experiment_results.XYZ_r
xy_w, xy_wr = XYZ_to_xy([XYZ_w, XYZ_wr])
uv_t = Luv_to_uv(XYZ_to_Luv(experiment_results.XYZ_ct, xy_w), xy_w)
uv_m = Luv_to_uv(XYZ_to_Luv(experiment_results.XYZ_cr, xy_wr), xy_wr)
L_A1 = experiment_results.Y_t
L_A2 = experiment_results.Y_r
XYZ_1 = experiment_results.XYZ_ct
XYZ_2 = chromatic_adaptation_CMCCAT2000(XYZ_1, XYZ_w, XYZ_wr, L_A1,
L_A2)
uv_p = Luv_to_uv(XYZ_to_Luv(XYZ_2, xy_wr), xy_wr)
return tuple([
CorrespondingChromaticitiesPrediction(experiment_results.name,
uv_t[i], uv_m[i], uv_p[i])
for i in range(len(uv_t))
])
def corresponding_chromaticities_prediction_CIE1994(experiment=1):
"""
Returns the corresponding chromaticities prediction for *CIE 1994*
chromatic adaptation model.
Parameters
----------
experiment : integer or CorrespondingColourDataset, optional
{1, 2, 3, 4, 6, 8, 9, 11, 12}
*Breneman (1987)* experiment number or
:class:`colour.CorrespondingColourDataset` class instance. Returns
-------
tuple
Corresponding chromaticities prediction.
References
----------
:cite:`Breneman1987b`, :cite:`CIETC1-321994b`
Examples
--------
>>> from pprint import pprint
>>> pr = corresponding_chromaticities_prediction_CIE1994(2)
>>> pr = [(p.uv_m, p.uv_p) for p in pr]
>>> pprint(pr) # doctest: +ELLIPSIS
[(array([ 0.207, 0.486]), array([ 0.2273130..., 0.5267609...])),
(array([ 0.449, 0.511]), array([ 0.4612181..., 0.5191849...])),
(array([ 0.263, 0.505]), array([ 0.2872404..., 0.5306938...])),
(array([ 0.322, 0.545]), array([ 0.3489822..., 0.5454398...])),
(array([ 0.316, 0.537]), array([ 0.3371612..., 0.5421567...])),
(array([ 0.265, 0.553]), array([ 0.2889416..., 0.5534074...])),
(array([ 0.221, 0.538]), array([ 0.2412195..., 0.5464301...])),
(array([ 0.135, 0.532]), array([ 0.1530344..., 0.5488239...])),
(array([ 0.145, 0.472]), array([ 0.1568709..., 0.5258835...])),
(array([ 0.163, 0.331]), array([ 0.1499762..., 0.4401747...])),
(array([ 0.176, 0.431]), array([ 0.1876711..., 0.5039627...])),
(array([ 0.244, 0.349]), array([ 0.2560012..., 0.4546263...]))]
"""
experiment_results = (convert_experiment_results_Breneman1987(experiment)
if is_numeric(experiment) else experiment)
with domain_range_scale(1):
XYZ_t, XYZ_r = experiment_results.XYZ_t, experiment_results.XYZ_r
xy_o1, xy_o2 = XYZ_to_xy([XYZ_t, XYZ_r])
uv_t = Luv_to_uv(XYZ_to_Luv(experiment_results.XYZ_ct, xy_o1), xy_o1)
uv_m = Luv_to_uv(XYZ_to_Luv(experiment_results.XYZ_cr, xy_o2), xy_o2)
Y_r = experiment_results.B_r
E_o1, E_o2 = experiment_results.Y_t, experiment_results.Y_r
XYZ_1 = experiment_results.XYZ_ct
XYZ_2 = chromatic_adaptation_CIE1994(XYZ_1, xy_o1, xy_o2, Y_r, E_o1,
E_o2)
uv_p = Luv_to_uv(XYZ_to_Luv(XYZ_2, xy_o2), xy_o2)
return tuple([
CorrespondingChromaticitiesPrediction(experiment_results.name,
uv_t[i], uv_m[i], uv_p[i])
for i in range(len(uv_t))
])
def corresponding_chromaticities_prediction_Fairchild1990(experiment=1):
"""
Returns the corresponding chromaticities prediction for *Fairchild (1990)*
chromatic adaptation model.
Parameters
----------
experiment : integer or CorrespondingColourDataset, optional
{1, 2, 3, 4, 6, 8, 9, 11, 12}
*Breneman (1987)* experiment number or
:class:`colour.CorrespondingColourDataset` class instance.
Returns
-------
tuple
Corresponding chromaticities prediction.
References
----------
:cite:`Breneman1987b`, :cite:`Fairchild1991a`, :cite:`Fairchild2013s`
Examples
--------
>>> from pprint import pprint
>>> pr = corresponding_chromaticities_prediction_Fairchild1990(2)
>>> pr = [(p.uv_m, p.uv_p) for p in pr]
>>> pprint(pr) # doctest: +ELLIPSIS
[(array([ 0.207, 0.486]), array([ 0.2089528..., 0.4724034...])),
(array([ 0.449, 0.511]), array([ 0.4375652..., 0.5121030...])),
(array([ 0.263, 0.505]), array([ 0.2621362..., 0.4972538...])),
(array([ 0.322, 0.545]), array([ 0.3235312..., 0.5475665...])),
(array([ 0.316, 0.537]), array([ 0.3151391..., 0.5398333...])),
(array([ 0.265, 0.553]), array([ 0.2634745..., 0.5544335...])),
(array([ 0.221, 0.538]), array([ 0.2211595..., 0.5324470...])),
(array([ 0.135, 0.532]), array([ 0.1396949..., 0.5207234...])),
(array([ 0.145, 0.472]), array([ 0.1512288..., 0.4533041...])),
(array([ 0.163, 0.331]), array([ 0.1715691..., 0.3026264...])),
(array([ 0.176, 0.431]), array([ 0.1825792..., 0.4077892...])),
(array([ 0.244, 0.349]), array([ 0.2418905..., 0.3413401...]))]
"""
experiment_results = (convert_experiment_results_Breneman1987(experiment)
if is_numeric(experiment) else experiment)
with domain_range_scale(1):
XYZ_t, XYZ_r = experiment_results.XYZ_t, experiment_results.XYZ_r
xy_t, xy_r = XYZ_to_xy([XYZ_t, XYZ_r])
uv_t = Luv_to_uv(XYZ_to_Luv(experiment_results.XYZ_ct, xy_t), xy_t)
uv_m = Luv_to_uv(XYZ_to_Luv(experiment_results.XYZ_cr, xy_r), xy_r)
Y_n = experiment_results.Y_t
XYZ_1 = experiment_results.XYZ_ct
XYZ_2 = chromatic_adaptation_Fairchild1990(XYZ_1, XYZ_t, XYZ_r, Y_n)
uv_p = Luv_to_uv(XYZ_to_Luv(XYZ_2, xy_r), xy_r)
return tuple([
CorrespondingChromaticitiesPrediction(experiment_results.name,
uv_t[i], uv_m[i], uv_p[i])
for i in range(len(uv_t))
])
def plot_corresponding_chromaticities_prediction(
experiment: Union[Literal[1, 2, 3, 4, 6, 8, 9, 11, 12],
CorrespondingColourDataset] = 1,
model: Union[Literal["CIE 1994", "CMCCAT2000", "Fairchild 1990",
"Von Kries", "Zhai 2018", ], str, ] = "Von Kries",
corresponding_chromaticities_prediction_kwargs: Optional[Dict] = None,
**kwargs: Any,
) -> Tuple[plt.Figure, plt.Axes]:
"""
Plot given chromatic adaptation model corresponding chromaticities
prediction.
Parameters
----------
experiment
*Breneman (1987)* experiment number or
:class:`colour.CorrespondingColourDataset` class instance.
model
Corresponding chromaticities prediction model name.
corresponding_chromaticities_prediction_kwargs
Keyword arguments for the :func:`colour.\
corresponding_chromaticities_prediction` definition.
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_corresponding_chromaticities_prediction(1, 'Von Kries')
... # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...AxesSubplot...>)
.. image:: ../_static/Plotting_\
Plot_Corresponding_Chromaticities_Prediction.png
:align: center
:alt: plot_corresponding_chromaticities_prediction
"""
if corresponding_chromaticities_prediction_kwargs is None:
corresponding_chromaticities_prediction_kwargs = {}
settings: Dict[str, Any] = {"uniform": True}
settings.update(kwargs)
_figure, axes = artist(**settings)
name = (
f"Experiment {experiment}" if is_numeric(experiment) else
experiment.name # type: ignore[union-attr]
)
title = (f"Corresponding Chromaticities Prediction - {model} - {name} - "
"CIE 1976 UCS Chromaticity Diagram")
settings = {"axes": axes, "title": title}
settings.update(kwargs)
settings["standalone"] = False
plot_chromaticity_diagram_CIE1976UCS(**settings)
results = corresponding_chromaticities_prediction(
experiment, model, **corresponding_chromaticities_prediction_kwargs)
for result in results:
_name, uv_t, uv_m, uv_p = result
axes.arrow(
uv_t[0],
uv_t[1],
uv_p[0] - uv_t[0] - 0.1 * (uv_p[0] - uv_t[0]),
uv_p[1] - uv_t[1] - 0.1 * (uv_p[1] - uv_t[1]),
color=CONSTANTS_COLOUR_STYLE.colour.dark,
head_width=0.005,
head_length=0.005,
zorder=CONSTANTS_COLOUR_STYLE.zorder.midground_annotation,
)
axes.plot(
uv_t[0],
uv_t[1],
"o",
color=CONSTANTS_COLOUR_STYLE.colour.brightest,
markeredgecolor=CONSTANTS_COLOUR_STYLE.colour.dark,
markersize=(CONSTANTS_COLOUR_STYLE.geometry.short * 6 +
CONSTANTS_COLOUR_STYLE.geometry.short * 0.75),
markeredgewidth=CONSTANTS_COLOUR_STYLE.geometry.short * 0.75,
zorder=CONSTANTS_COLOUR_STYLE.zorder.foreground_line,
)
axes.plot(
uv_m[0],
uv_m[1],
"^",
color=CONSTANTS_COLOUR_STYLE.colour.brightest,
markeredgecolor=CONSTANTS_COLOUR_STYLE.colour.dark,
markersize=(CONSTANTS_COLOUR_STYLE.geometry.short * 6 +
CONSTANTS_COLOUR_STYLE.geometry.short * 0.75),
markeredgewidth=CONSTANTS_COLOUR_STYLE.geometry.short * 0.75,
zorder=CONSTANTS_COLOUR_STYLE.zorder.foreground_line,
)
axes.plot(
uv_p[0],
uv_p[1],
"^",
color=CONSTANTS_COLOUR_STYLE.colour.dark,
zorder=CONSTANTS_COLOUR_STYLE.zorder.foreground_line,
)
settings.update({
"standalone": True,
"bounding_box": (-0.1, 0.7, -0.1, 0.7),
})
settings.update(kwargs)
return render(**settings)
def plot_corresponding_chromaticities_prediction(experiment=1,
model='Von Kries',
transform='CAT02',
**kwargs):
"""
Plots given chromatic adaptation model corresponding chromaticities
prediction.
Parameters
----------
experiment : integer or CorrespondingColourDataset, optional
{1, 2, 3, 4, 6, 8, 9, 11, 12}
*Breneman (1987)* experiment number or
:class:`colour.CorrespondingColourDataset` class instance.
model : unicode, optional
Corresponding chromaticities prediction model name.
transform : unicode, optional
Transformation to use with *Von Kries* chromatic adaptation model.
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.
Returns
-------
tuple
Current figure and axes.
Examples
--------
>>> plot_corresponding_chromaticities_prediction(1, 'Von Kries', 'CAT02')
... # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, <...AxesSubplot...>)
.. image:: ../_static/Plotting_\
Plot_Corresponding_Chromaticities_Prediction.png
:align: center
:alt: plot_corresponding_chromaticities_prediction
"""
settings = {'uniform': True}
settings.update(kwargs)
_figure, axes = artist(**settings)
name = ('Experiment {0}'.format(experiment)
if is_numeric(experiment) else experiment.name)
title = (('Corresponding Chromaticities Prediction - {0} ({1}) - {2} - '
'CIE 1976 UCS Chromaticity Diagram').format(
model, transform, name) if model.lower() in ('von kries',
'vonkries') else
('Corresponding Chromaticities Prediction - {0} - {1} - '
'CIE 1976 UCS Chromaticity Diagram').format(model, name))
settings = {'axes': axes, 'title': title}
settings.update(kwargs)
settings['standalone'] = False
plot_chromaticity_diagram_CIE1976UCS(**settings)
results = corresponding_chromaticities_prediction(experiment,
transform=transform)
for result in results:
_name, uv_t, uv_m, uv_p = result
axes.arrow(uv_t[0],
uv_t[1],
uv_p[0] - uv_t[0] - 0.1 * (uv_p[0] - uv_t[0]),
uv_p[1] - uv_t[1] - 0.1 * (uv_p[1] - uv_t[1]),
color=CONSTANTS_COLOUR_STYLE.colour.dark,
head_width=0.005,
head_length=0.005)
axes.plot(uv_t[0],
uv_t[1],
'o',
color=CONSTANTS_COLOUR_STYLE.colour.brightest,
markeredgecolor=CONSTANTS_COLOUR_STYLE.colour.dark,
markersize=(CONSTANTS_COLOUR_STYLE.geometry.short * 6 +
CONSTANTS_COLOUR_STYLE.geometry.short * 0.75),
markeredgewidth=CONSTANTS_COLOUR_STYLE.geometry.short * 0.75)
axes.plot(uv_m[0],
uv_m[1],
'^',
color=CONSTANTS_COLOUR_STYLE.colour.brightest,
markeredgecolor=CONSTANTS_COLOUR_STYLE.colour.dark,
markersize=(CONSTANTS_COLOUR_STYLE.geometry.short * 6 +
CONSTANTS_COLOUR_STYLE.geometry.short * 0.75),
markeredgewidth=CONSTANTS_COLOUR_STYLE.geometry.short * 0.75)
axes.plot(uv_p[0],
uv_p[1],
'^',
color=CONSTANTS_COLOUR_STYLE.colour.dark)
settings.update({
'standalone': True,
'bounding_box': (-0.1, 0.7, -0.1, 0.7),
})
settings.update(kwargs)
return render(**settings)
