def RGB_chromaticity_coordinates_CIE_1931_chromaticity_diagram_plot(
RGB,
colourspace,
**kwargs):
"""
Plots given *RGB* colourspace array in *CIE 1931 Chromaticity Diagram*.
Parameters
----------
RGB : array_like
*RGB* colourspace array.
colourspace : unicode
*RGB* colourspace of the *RGB* array.
\**kwargs : dict, optional
Keywords arguments.
Returns
-------
Figure
Current figure or None.
Examples
--------
>>> RGB = np.random.random((10, 10, 3))
>>> c = 'Rec. 709'
>>> RGB_chromaticity_coordinates_CIE_1931_chromaticity_diagram_plot(
... RGB, c) # doctest: +SKIP
"""
settings = {}
settings.update(kwargs)
settings.update({'standalone': False})
colourspace, name = get_RGB_colourspace(colourspace), colourspace
settings['colourspaces'] = (
[name] + settings.get('colourspaces', []))
RGB_colourspaces_CIE_1931_chromaticity_diagram_plot(**settings)
alpha_p, colour_p = 0.85, 'black'
xy = XYZ_to_xy(RGB_to_XYZ(RGB,
colourspace.whitepoint,
colourspace.whitepoint,
colourspace.RGB_to_XYZ_matrix),
colourspace.whitepoint)
pylab.scatter(xy[..., 0],
xy[..., 1],
alpha=alpha_p / 2,
color=colour_p,
marker='+')
settings.update({'standalone': True})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
def RGB_chromaticity_coordinates_CIE_1976_UCS_chromaticity_diagram_plot(
RGB, colourspace, **kwargs):
"""
Plots given *RGB* colourspace array in *CIE 1976 UCS Chromaticity Diagram*.
Parameters
----------
RGB : array_like
*RGB* colourspace array.
colourspace : unicode
*RGB* colourspace of the *RGB* array.
\**kwargs : dict, optional
Keywords arguments.
Returns
-------
Figure
Current figure or None.
Examples
--------
>>> RGB = np.random.random((10, 10, 3))
>>> c = 'Rec. 709'
>>> RGB_chromaticity_coordinates_CIE_1976_UCS_chromaticity_diagram_plot(
... RGB, c) # doctest: +SKIP
"""
settings = {}
settings.update(kwargs)
settings.update({'standalone': False})
colourspace, name = get_RGB_colourspace(colourspace), colourspace
settings['colourspaces'] = ([name] + settings.get('colourspaces', []))
RGB_colourspaces_CIE_1976_UCS_chromaticity_diagram_plot(**settings)
alpha_p, colour_p = 0.85, 'black'
uv = Luv_to_uv(
XYZ_to_Luv(
RGB_to_XYZ(RGB, colourspace.whitepoint, colourspace.whitepoint,
colourspace.RGB_to_XYZ_matrix), colourspace.whitepoint),
colourspace.whitepoint)
pylab.scatter(uv[..., 0],
uv[..., 1],
alpha=alpha_p / 2,
color=colour_p,
marker='+')
settings.update({'standalone': True})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
def RGB_colourspace_triangle_visual(colourspace='ITU-R BT.709',
diagram='CIE 1931',
uniform_colour=None,
uniform_opacity=1.0,
width=4.0,
parent=None):
"""
Returns a :class:`vispy.scene.visuals.Line` class instance representing
a *RGB* colourspace triangle visual.
Parameters
----------
colourspace : unicode, optional
See :func:`RGB_colourspace_volume_visual` argument for possible values.
:class:`colour.RGB_Colourspace` class instance name defining the *RGB*
colourspace triangle to draw.
diagram : unicode, optional
**{'CIE 1931', 'CIE 1960 UCS', 'CIE 1976 UCS'}**,
Chromaticity diagram to use.
uniform_colour : array_like, optional
Uniform triangle colour.
uniform_opacity : numeric, optional
Uniform mesh opacity.
width : numeric, optional
Triangle edge width.
parent : Node, optional
Parent of the *RGB* colourspace volume visual in the `SceneGraph`.
"""
if uniform_colour is None:
uniform_colour = (0.8, 0.8, 0.8)
colourspace = get_RGB_colourspace(colourspace)
illuminant = DEFAULT_PLOTTING_ILLUMINANT
XYZ_to_ij = CHROMATICITY_DIAGRAM_TRANSFORMATIONS[diagram]['XYZ_to_ij']
ij = XYZ_to_ij(xy_to_XYZ(colourspace.primaries), illuminant)
# TODO: Remove following hack dealing with 'agg' method issues.
ij = np.vstack((ij[-1, ...], ij, ij[0, ...]))
ij[np.isnan(ij)] = 0
RGB = np.hstack((uniform_colour, uniform_opacity)),
line = Line(ij, RGB, width=width, method='agg', parent=parent)
return line
def RGB_colourspace_whitepoint_axis_visual(colourspace='ITU-R BT.709',
reference_colourspace='CIE xyY',
width=2.0,
method='gl',
parent=None):
"""
Returns a :class:`vispy.scene.visuals.Line` class instance representing
a given RGB colourspace whitepoint axis.
Parameters
----------
colourspace : unicode, optional
See :func:`RGB_colourspace_volume_visual` argument for possible values.
:class:`colour.RGB_Colourspace` class instance name defining the *RGB*
colourspace whitepoint axis to draw.
reference_colourspace : unicode, optional
**{'CIE XYZ', 'CIE xyY', 'CIE Lab', 'CIE Luv', 'CIE UCS', 'CIE UVW',
'IPT', 'Hunter Lab', 'Hunter Rdab'}**,
Reference colourspace to use for colour conversions / transformations.
width : numeric, optional
Line width.
method : unicode, optional
**{'gl', 'agg'}**,
Line drawing method.
parent : Node, optional
Parent of the spectral locus visual in the `SceneGraph`.
Returns
-------
Line
RGB colourspace whitepoint axis.
"""
colourspace = get_RGB_colourspace(colourspace)
XYZ_o = xy_to_XYZ(colourspace.whitepoint + (0, ))
XYZ_f = xy_to_XYZ(colourspace.whitepoint + (1.1, ))
XYZ_l = np.vstack((XYZ_o, XYZ_f))
illuminant = DEFAULT_PLOTTING_ILLUMINANT
points = common_colourspace_model_axis_reorder(
XYZ_to_colourspace_model(XYZ_l, illuminant, reference_colourspace),
reference_colourspace)
line = Line(points, (1, 1, 1), width=width, method=method, parent=parent)
return line
def plot_grid(filename, data_points, grid, bbox_xystar, xystar=True):
if not have_matplotlib or not have_colour_package:
return
print("Plotting the grid ...")
plt.figure()
# Draw a nice chromaticity diagram.
clr.CIE_1931_chromaticity_diagram_plot(standalone=False)
clr.canvas(figure_size=(7,7))
# Show the sRGB gamut.
color_space = clr.get_RGB_colourspace('sRGB')
x = color_space.primaries[:,0].tolist()
y = color_space.primaries[:,1].tolist()
plt.fill(x, y, color='black', label='sRGB', fill=False)
# Draw crosses into all internal grid cells.
# for gridcell in grid:
# if len(gridcell.indices) > 0 and gridcell.inside:
# if xystar:
# pointx = sum([data_points[i].xystar[0] for i in gridcell.indices])
# pointy = sum([data_points[i].xystar[1] for i in gridcell.indices])
# pointx /= len(gridcell.indices)
# pointy /= len(gridcell.indices)
# (pointx, pointy) = Transform.xy_from_xystar((pointx, pointy))
# plt.plot(pointx, pointy, "x", color="black")
# else:
# pointx = sum([data_points[i].uv[0] for i in gridcell.indices])
# pointy = sum([data_points[i].uv[1] for i in gridcell.indices])
# pointx /= len(gridcell.indices)
# pointy /= len(gridcell.indices)
# (pointx, pointy) = Transform.xy_from_uv((pointx, pointy))
# plt.plot(pointx, pointy, "x", color="black")
# Draw data points.
for i, data_point in enumerate(data_points):
if xystar:
p = Transform.xy_from_xystar(data_point.xystar)
else:
p = Transform.xy_from_uv(data_point.uv)
if data_point.equal_energy_white:
plt.plot(p[0], p[1], "o", color="white", ms=4)
elif data_point.broken:
plt.plot(p[0], p[1], "o", color="red", ms=4)
else:
plt.plot(p[0], p[1], "o", color="green", ms=4)
# Show grid point indices, for debugging.
# plt.text(p[0]+0.01, p[1]-0.01, '{}'.format(i))
bp0 = Transform.xy_from_xystar([bbox_xystar[0][0], bbox_xystar[0][1]])
bp1 = Transform.xy_from_xystar([bbox_xystar[0][0], bbox_xystar[1][1]])
bp2 = Transform.xy_from_xystar([bbox_xystar[1][0], bbox_xystar[1][1]])
bp3 = Transform.xy_from_xystar([bbox_xystar[1][0], bbox_xystar[0][1]])
plt.plot([bp0[0], bp1[0], bp2[0], bp3[0], bp0[0]],
[bp0[1], bp1[1], bp2[1], bp3[1], bp0[1]],
label="Grid Bounding Box")
plt.xlabel('$x$')
plt.ylabel('$y$')
plt.legend()
plt.savefig(filename)
def RGB_colourspaces_CIE_1976_UCS_chromaticity_diagram_plot(
colourspaces=None,
cmfs='CIE 1931 2 Degree Standard Observer',
**kwargs):
"""
Plots given *RGB* colourspaces in *CIE 1976 UCS Chromaticity Diagram*.
Parameters
----------
colourspaces : array_like, optional
*RGB* colourspaces to plot.
cmfs : unicode, optional
Standard observer colour matching functions used for diagram bounds.
Other Parameters
----------------
\**kwargs : dict, optional
{:func:`boundaries`, :func:`canvas`, :func:`decorate`,
:func:`display`},
Please refer to the documentation of the previously listed definitions.
show_diagram_colours : bool, optional
{:func:`CIE_1976_UCS_chromaticity_diagram_plot`},
Whether to display the chromaticity diagram background colours.
Returns
-------
Figure
Current figure or None.
Examples
--------
>>> c = ['Rec. 709', 'ACEScg', 'S-Gamut']
>>> RGB_colourspaces_CIE_1976_UCS_chromaticity_diagram_plot(
... c) # doctest: +SKIP
"""
settings = {'figure_size': (DEFAULT_FIGURE_WIDTH, DEFAULT_FIGURE_WIDTH)}
settings.update(kwargs)
canvas(**settings)
if colourspaces is None:
colourspaces = ('Rec. 709', 'ACEScg', 'S-Gamut', 'Pointer Gamut')
cmfs, name = get_cmfs(cmfs), cmfs
illuminant = DEFAULT_PLOTTING_ILLUMINANT
settings = {
'title':
'{0} - {1} - CIE 1976 UCS Chromaticity Diagram'.format(
', '.join(colourspaces), name),
'standalone':
False
}
settings.update(kwargs)
CIE_1976_UCS_chromaticity_diagram_plot(**settings)
x_limit_min, x_limit_max = [-0.1], [0.7]
y_limit_min, y_limit_max = [-0.1], [0.7]
settings = {
'colour_cycle_map': 'rainbow',
'colour_cycle_count': len(colourspaces)
}
settings.update(kwargs)
cycle = colour_cycle(**settings)
for colourspace in colourspaces:
if colourspace == 'Pointer Gamut':
uv = Luv_to_uv(
XYZ_to_Luv(xy_to_XYZ(POINTER_GAMUT_BOUNDARIES), illuminant),
illuminant)
alpha_p, colour_p = 0.85, '0.95'
pylab.plot(uv[..., 0],
uv[..., 1],
label='Pointer\'s Gamut',
color=colour_p,
alpha=alpha_p,
linewidth=2)
pylab.plot((uv[-1][0], uv[0][0]), (uv[-1][1], uv[0][1]),
color=colour_p,
alpha=alpha_p,
linewidth=2)
XYZ = Lab_to_XYZ(LCHab_to_Lab(POINTER_GAMUT_DATA),
POINTER_GAMUT_ILLUMINANT)
uv = Luv_to_uv(XYZ_to_Luv(XYZ, illuminant), illuminant)
pylab.scatter(uv[..., 0],
uv[..., 1],
alpha=alpha_p / 2,
color=colour_p,
marker='+')
else:
colourspace, name = get_RGB_colourspace(colourspace), colourspace
r, g, b, _a = next(cycle)
# 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 = Luv_to_uv(XYZ_to_Luv(xy_to_XYZ(P), illuminant), illuminant)
W = Luv_to_uv(
XYZ_to_Luv(xy_to_XYZ(colourspace.whitepoint), illuminant),
illuminant)
pylab.plot((W[0], W[0]), (W[1], W[1]),
color=(r, g, b),
label=colourspace.name,
linewidth=2)
pylab.plot((W[0], W[0]), (W[1], W[1]),
'o',
color=(r, g, b),
linewidth=2)
pylab.plot((P[0, 0], P[1, 0]), (P[0, 1], P[1, 1]),
'o-',
color=(r, g, b),
linewidth=2)
pylab.plot((P[1, 0], P[2, 0]), (P[1, 1], P[2, 1]),
'o-',
color=(r, g, b),
linewidth=2)
pylab.plot((P[2, 0], P[0, 0]), (P[2, 1], P[0, 1]),
'o-',
color=(r, g, b),
linewidth=2)
x_limit_min.append(np.amin(P[..., 0]) - 0.1)
y_limit_min.append(np.amin(P[..., 1]) - 0.1)
x_limit_max.append(np.amax(P[..., 0]) + 0.1)
y_limit_max.append(np.amax(P[..., 1]) + 0.1)
settings.update({
'legend':
True,
'legend_location':
'upper right',
'x_tighten':
True,
'y_tighten':
True,
'limits': (min(x_limit_min), max(x_limit_max), min(y_limit_min),
max(y_limit_max)),
'standalone':
True
})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
def RGB_colourspace_triangle_visual(colourspace='Rec. 709',
diagram='CIE 1931',
uniform_colour=None,
uniform_opacity=1.0,
width=4.0,
parent=None):
"""
Returns a :class:`vispy.scene.visuals.Line` class instance representing
a *RGB* colourspace triangle visual.
Parameters
----------
colourspace : unicode, optional
See :func:`RGB_colourspace_volume_visual` argument for possible values.
:class:`colour.RGB_Colourspace` class instance name defining the *RGB*
colourspace triangle to draw.
diagram : unicode, optional
{'CIE 1931', 'CIE 1960 UCS', 'CIE 1976 UCS'}
Chromaticity diagram to use.
uniform_colour : array_like, optional
Uniform triangle colour.
uniform_opacity : numeric, optional
Uniform mesh opacity.
vertex_colour : array_like, optional
Per vertex varying colour.
wireframe : bool, optional
Use wireframe display.
Uniform mesh opacity.
wireframe_colour : array_like, optional
Wireframe mesh colour.
wireframe_opacity : numeric, optional
Wireframe mesh opacity.
parent : Node, optional
Parent of the *RGB* colourspace volume visual in the `SceneGraph`.
"""
if uniform_colour is None:
uniform_colour = (0.8, 0.8, 0.8)
colourspace = get_RGB_colourspace(colourspace)
illuminant = DEFAULT_PLOTTING_ILLUMINANT
XYZ_to_ij = CHROMATICITY_DIAGRAM_TRANSFORMATIONS[diagram]['XYZ_to_ij']
ij = XYZ_to_ij(xy_to_XYZ(colourspace.primaries), illuminant)
# TODO: Remove following hack dealing with 'agg' method issues.
ij = np.vstack((ij[-1, ...], ij, ij[0, ...]))
ij[np.isnan(ij)] = 0
RGB = np.hstack((uniform_colour, uniform_opacity)),
line = Line(ij,
RGB,
width=width,
method='agg',
parent=parent)
return line
def RGB_colourspaces_gamuts_plot(colourspaces=None,
reference_colourspace='CIE xyY',
segments=8,
display_grid=True,
grid_segments=10,
spectral_locus=False,
spectral_locus_colour=None,
cmfs='CIE 1931 2 Degree Standard Observer',
**kwargs):
"""
Plots given *RGB* colourspaces gamuts in given reference colourspace.
Parameters
----------
colourspaces : array_like, optional
*RGB* colourspaces to plot the gamuts.
reference_colourspace : unicode, optional
**{'CIE XYZ', 'CIE xyY', 'CIE Lab', 'CIE Luv', 'CIE UCS', 'CIE UVW',
'IPT'}**,
Reference colourspace to plot the gamuts into.
segments : int, optional
Edge segments count for each *RGB* colourspace cubes.
display_grid : bool, optional
Display a grid at the bottom of the *RGB* colourspace cubes.
grid_segments : bool, optional
Edge segments count for the grid.
spectral_locus : bool, optional
Is spectral locus line plotted.
spectral_locus_colour : array_like, optional
Spectral locus line colour.
cmfs : unicode, optional
Standard observer colour matching functions used for spectral locus.
\**kwargs : dict, optional
**{'face_colours', 'edge_colours', 'edge_alpha', 'face_alpha'}**,
Arguments for each given colourspace where each key has an array_like
value such as: ``{ 'face_colours': (None, (0.5, 0.5, 1.0)),
'edge_colours': (None, (0.5, 0.5, 1.0)), 'edge_alpha': (0.5, 1.0),
'face_alpha': (0.0, 1.0)}``
**{'grid_face_colours', 'grid_edge_colours', 'grid_face_alpha',
'grid_edge_alpha', 'x_axis_colour', 'y_axis_colour', 'x_ticks_colour',
'y_ticks_colour', 'x_label_colour', 'y_label_colour',
'ticks_and_label_location'}**,
Arguments for the nadir grid such as ``{'grid_face_colours':
(0.25, 0.25, 0.25), 'grid_edge_colours': (0.50, 0.50, 0.50),
'grid_face_alpha': 0.1, 'grid_edge_alpha': 0.5, 'x_axis_colour':
(0.0, 0.0, 0.0, 1.0), 'y_axis_colour': (0.0, 0.0, 0.0, 1.0),
'x_ticks_colour': (0.0, 0.0, 0.0, 0.85), 'y_ticks_colour':
(0.0, 0.0, 0.0, 0.85), 'x_label_colour': (0.0, 0.0, 0.0, 0.85),
'y_label_colour': (0.0, 0.0, 0.0, 0.85), 'ticks_and_label_location':
('-x', '-y')}``
Returns
-------
bool
Definition success.
Examples
--------
>>> c = ['Rec. 709', 'ACEScg', 'S-Gamut']
>>> RGB_colourspaces_gamuts_plot(c) # doctest: +SKIP
True
"""
if colourspaces is None:
colourspaces = ('Rec. 709', 'ACEScg')
count_c = len(colourspaces)
settings = Structure(
**{'face_colours': [None] * count_c,
'edge_colours': [None] * count_c,
'face_alpha': [1] * count_c,
'edge_alpha': [1] * count_c,
'title': '{0} - {1} Reference Colourspace'.format(
', '.join(colourspaces), reference_colourspace)})
settings.update(kwargs)
figure = matplotlib.pyplot.figure()
axes = figure.add_subplot(111, projection='3d')
illuminant = DEFAULT_PLOTTING_ILLUMINANT
points = np.zeros((4, 3))
if spectral_locus:
cmfs = get_cmfs(cmfs)
XYZ = cmfs.values
points = XYZ_to_reference_colourspace(XYZ,
illuminant,
reference_colourspace)
points[np.isnan(points)] = 0
c = ((0.0, 0.0, 0.0, 0.5)
if spectral_locus_colour is None else
spectral_locus_colour)
pylab.plot(points[..., 0],
points[..., 1],
points[..., 2],
color=c,
linewidth=2,
zorder=1)
pylab.plot((points[-1][0], points[0][0]),
(points[-1][1], points[0][1]),
(points[-1][2], points[0][2]),
color=c,
linewidth=2,
zorder=1)
quads, RGB_f, RGB_e = [], [], []
for i, colourspace in enumerate(colourspaces):
colourspace = get_RGB_colourspace(colourspace)
quads_c, RGB = RGB_identity_cube(width_segments=segments,
height_segments=segments,
depth_segments=segments)
XYZ = RGB_to_XYZ(
quads_c,
colourspace.whitepoint,
colourspace.whitepoint,
colourspace.RGB_to_XYZ_matrix)
quads.extend(XYZ_to_reference_colourspace(XYZ,
colourspace.whitepoint,
reference_colourspace))
if settings.face_colours[i] is not None:
RGB = np.ones(RGB.shape) * settings.face_colours[i]
RGB_f.extend(np.hstack(
(RGB, np.full((RGB.shape[0], 1, np.float_),
settings.face_alpha[i]))))
if settings.edge_colours[i] is not None:
RGB = np.ones(RGB.shape) * settings.edge_colours[i]
RGB_e.extend(np.hstack(
(RGB, np.full((RGB.shape[0], 1, np.float_),
settings.edge_alpha[i]))))
quads = np.asarray(quads)
quads[np.isnan(quads)] = 0
if quads.size != 0:
for i, axis in enumerate('xyz'):
min_a = np.min(np.vstack((quads[..., i], points[..., i])))
max_a = np.max(np.vstack((quads[..., i], points[..., i])))
getattr(axes, 'set_{}lim'.format(axis))((min_a, max_a))
labels = REFERENCE_COLOURSPACES_TO_LABELS[reference_colourspace]
for i, axis in enumerate('xyz'):
getattr(axes, 'set_{}label'.format(axis))(labels[i])
if display_grid:
if reference_colourspace == 'CIE Lab':
limits = np.array([[-450, 450], [-450, 450]])
elif reference_colourspace == 'CIE Luv':
limits = np.array([[-650, 650], [-650, 650]])
elif reference_colourspace == 'CIE UVW':
limits = np.array([[-850, 850], [-850, 850]])
else:
limits = np.array([[-1.5, 1.5], [-1.5, 1.5]])
quads_g, RGB_gf, RGB_ge = nadir_grid(
limits, grid_segments, labels, axes, **settings)
quads = np.vstack((quads_g, quads))
RGB_f = np.vstack((RGB_gf, RGB_f))
RGB_e = np.vstack((RGB_ge, RGB_e))
collection = Poly3DCollection(quads)
collection.set_facecolors(RGB_f)
collection.set_edgecolors(RGB_e)
axes.add_collection3d(collection)
settings.update({
'camera_aspect': 'equal',
'no_axes3d': True})
settings.update(kwargs)
camera(**settings)
decorate(**settings)
return display(**settings)
def RGB_scatter_plot(RGB,
colourspace,
reference_colourspace='CIE xyY',
colourspaces=None,
segments=8,
display_grid=True,
grid_segments=10,
spectral_locus=False,
spectral_locus_colour=None,
points_size=12,
cmfs='CIE 1931 2 Degree Standard Observer',
**kwargs):
"""
Plots given *RGB* colourspace array in a scatter plot.
Parameters
----------
RGB : array_like
*RGB* colourspace array.
colourspace : RGB_Colourspace
*RGB* colourspace of the *RGB* array.
reference_colourspace : unicode, optional
**{'CIE XYZ', 'CIE xyY', 'CIE Lab', 'CIE Luv', 'CIE UCS', 'CIE UVW',
'IPT', 'Hunter Lab', 'Hunter Rdab'}**,
Reference colourspace for colour conversion.
colourspaces : array_like, optional
*RGB* colourspaces to plot the gamuts.
segments : int, optional
Edge segments count for each *RGB* colourspace cubes.
display_grid : bool, optional
Display a grid at the bottom of the *RGB* colourspace cubes.
grid_segments : bool, optional
Edge segments count for the grid.
spectral_locus : bool, optional
Is spectral locus line plotted.
spectral_locus_colour : array_like, optional
Spectral locus line colour.
points_size : numeric, optional
Scatter points size.
cmfs : unicode, optional
Standard observer colour matching functions used for spectral locus.
Other Parameters
----------------
\**kwargs : dict, optional
{:func:`RGB_colourspaces_gamuts_plot`},
Please refer to the documentation of the previously listed definitions.
Returns
-------
Figure
Current figure or None.
Examples
--------
>>> c = 'Rec. 709'
>>> RGB_scatter_plot(c) # doctest: +SKIP
"""
colourspace = get_RGB_colourspace(colourspace)
if colourspaces is None:
colourspaces = (colourspace.name, )
count_c = len(colourspaces)
settings = Structure(
**{
'face_colours': [None] * count_c,
'edge_colours': [(0.25, 0.25, 0.25)] * count_c,
'face_alpha': [0.0] * count_c,
'edge_alpha': [0.1] * count_c,
'standalone': False
})
settings.update(kwargs)
RGB_colourspaces_gamuts_plot(colourspaces=colourspaces,
reference_colourspace=reference_colourspace,
segments=segments,
display_grid=display_grid,
grid_segments=grid_segments,
spectral_locus=spectral_locus,
spectral_locus_colour=spectral_locus_colour,
cmfs=cmfs,
**settings)
XYZ = RGB_to_XYZ(RGB, colourspace.whitepoint, colourspace.whitepoint,
colourspace.RGB_to_XYZ_matrix)
points = common_colourspace_model_axis_reorder(
XYZ_to_colourspace_model(XYZ, colourspace.whitepoint,
reference_colourspace), reference_colourspace)
axes = matplotlib.pyplot.gca()
axes.scatter(points[..., 0],
points[..., 1],
points[..., 2],
color=np.reshape(RGB, (-1, 3)),
s=points_size)
settings.update({'standalone': True})
settings.update(kwargs)
camera(**settings)
decorate(**settings)
return display(**settings)
def RGB_scatter_visual(RGB,
colourspace='ITU-R BT.709',
reference_colourspace='CIE xyY',
symbol='disc',
size=4.0,
edge_size=0.5,
uniform_colour=None,
uniform_opacity=1.0,
uniform_edge_colour=None,
uniform_edge_opacity=1.0,
resampling='auto',
parent=None):
"""
Returns a :class:`vispy.scene.visuals.Symbol` class instance representing
*RGB* data using given symbols.
Parameters
----------
RGB : array_like
*RGB* data to draw.
colourspace : unicode, optional
**{'ITU-R BT.709', 'ACES2065-1', 'ACEScc', 'ACEScg', 'ACESproxy',
'ALEXA Wide Gamut', 'Adobe RGB (1998)', 'Adobe Wide Gamut RGB',
'Apple RGB', 'Best RGB', 'Beta RGB', 'CIE RGB', 'Cinema Gamut',
'ColorMatch RGB', 'DCI-P3', 'DCI-P3+', 'DRAGONcolor', 'DRAGONcolor2',
'Don RGB 4', 'ECI RGB v2', 'ERIMM RGB', 'Ekta Space PS 5', 'Max RGB',
'NTSC', 'Pal/Secam', 'ProPhoto RGB', 'REDcolor', 'REDcolor2',
'REDcolor3', 'REDcolor4', 'RIMM RGB', 'ROMM RGB', 'ITU-R BT.2020',
'Russell RGB', 'S-Gamut', 'S-Gamut3', 'S-Gamut3.Cine', 'SMPTE-C RGB',
'V-Gamut', 'Xtreme RGB', 'sRGB'}**,
:class:`colour.RGB_Colourspace` class instance name defining the *RGB*
colourspace of the data to draw.
reference_colourspace : unicode, optional
**{'CIE XYZ', 'CIE xyY', 'CIE Lab', 'CIE Luv', 'CIE UCS', 'CIE UVW',
'IPT', 'Hunter Lab', 'Hunter Rdab'}**,
Reference colourspace to use for colour conversions / transformations.
symbol : unicode, optional
Symbol type to draw.
size : numeric, optional
Symbol size.
edge_size : numeric, optional
Symbol edge size.
uniform_colour : array_like, optional
Uniform symbol colour.
uniform_opacity : numeric, optional
Uniform symbol opacity.
uniform_edge_colour : array_like, optional
Uniform symbol edge colour.
uniform_edge_opacity : numeric, optional
Uniform symbol edge opacity.
resampling : numeric or unicode, optional
Resampling value, if numeric input, one pixel every `resampling`
argument value will be kept.
parent : Node, optional
Parent of the *RGB* scatter visual in the `SceneGraph`.
Returns
-------
Symbol
*RGB* scatter visual.
"""
colourspace = get_RGB_colourspace(colourspace)
RGB = np.asarray(RGB)
if resampling == 'auto':
resampling = max(int((0.0078125 * np.average(RGB.shape[0:1])) // 2), 1)
RGB = RGB[::resampling, ::resampling].reshape((-1, 3))
XYZ = RGB_to_XYZ(RGB, colourspace.whitepoint, colourspace.whitepoint,
colourspace.RGB_to_XYZ_matrix)
points = common_colourspace_model_axis_reorder(
XYZ_to_colourspace_model(XYZ, colourspace.whitepoint,
reference_colourspace), reference_colourspace)
points[np.isnan(points)] = 0
RGB = np.clip(RGB, 0, 1)
if uniform_colour is None:
RGB = np.hstack((RGB,
np.full((RGB.shape[0], 1), uniform_opacity,
DEFAULT_FLOAT_DTYPE)))
else:
RGB = ColorArray(uniform_colour, alpha=uniform_opacity).rgba
if uniform_edge_colour is None:
RGB_e = RGB
else:
RGB_e = ColorArray(uniform_edge_colour,
alpha=uniform_edge_opacity).rgba
markers = Symbol(symbol=symbol,
positions=points,
size=size,
edge_size=edge_size,
face_colour=RGB,
edge_colour=RGB_e,
parent=parent)
return markers
def multi_cctf_plot(colourspaces=None, decoding_cctf=False, **kwargs):
"""
Plots given colourspaces colour component transfer functions.
Parameters
----------
colourspaces : array_like, optional
Colourspaces colour component transfer function to plot.
decoding_cctf : bool
Plot decoding colour component transfer function instead.
Other Parameters
----------------
\**kwargs : dict, optional
{:func:`boundaries`, :func:`canvas`, :func:`decorate`,
:func:`display`},
Please refer to the documentation of the previously listed definitions.
Returns
-------
Figure
Current figure or None.
Examples
--------
>>> multi_cctf_plot(['Rec. 709', 'sRGB']) # doctest: +SKIP
"""
settings = {'figure_size': (DEFAULT_FIGURE_WIDTH, DEFAULT_FIGURE_WIDTH)}
settings.update(kwargs)
canvas(**settings)
if colourspaces is None:
colourspaces = ('Rec. 709', 'sRGB')
samples = np.linspace(0, 1, 1000)
for colourspace in colourspaces:
colourspace = get_RGB_colourspace(colourspace)
RGBs = (colourspace.decoding_cctf(samples)
if decoding_cctf else colourspace.encoding_cctf(samples))
pylab.plot(samples,
RGBs,
label=u'{0}'.format(colourspace.name),
linewidth=2)
settings.update({
'title':
'{0} - {1} CCTFs'.format(', '.join(colourspaces),
'Decoding' if decoding_cctf else 'Encoding'),
'x_tighten':
True,
'x_label':
'Signal Value' if decoding_cctf else 'Tristimulus Value',
'y_label':
'Tristimulus Value' if decoding_cctf else 'Signal Value',
'legend':
True,
'legend_location':
'upper left',
'grid':
True,
'limits': (0, 1, 0, 1),
'aspect':
'equal'
})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
def RGB_colourspaces_CIE_1960_UCS_chromaticity_diagram_plot(
colourspaces=None,
cmfs='CIE 1931 2 Degree Standard Observer',
**kwargs):
"""
Plots given *RGB* colourspaces in *CIE 1960 UCS Chromaticity Diagram*.
Parameters
----------
colourspaces : array_like, optional
*RGB* colourspaces to plot.
cmfs : unicode, optional
Standard observer colour matching functions used for diagram bounds.
\**kwargs : dict, optional
Keywords arguments.
Returns
-------
bool
Definition success.
Examples
--------
>>> c = ['Rec. 709', 'ACEScg', 'S-Gamut']
>>> RGB_colourspaces_CIE_1960_UCS_chromaticity_diagram_plot(
... c) # doctest: +SKIP
True
"""
settings = {'figure_size': (DEFAULT_FIGURE_WIDTH, DEFAULT_FIGURE_WIDTH)}
settings.update(kwargs)
canvas(**settings)
if colourspaces is None:
colourspaces = ('Rec. 709', 'ACEScg', 'S-Gamut', 'Pointer Gamut')
cmfs, name = get_cmfs(cmfs), cmfs
settings = {
'title': '{0} - {1} - CIE 1960 UCS Chromaticity Diagram'.format(
', '.join(colourspaces), name),
'standalone': False}
settings.update(kwargs)
CIE_1960_UCS_chromaticity_diagram_plot(**settings)
x_limit_min, x_limit_max = [-0.1], [0.7]
y_limit_min, y_limit_max = [-0.2], [0.6]
settings = {'colour_cycle_map': 'rainbow',
'colour_cycle_count': len(colourspaces)}
settings.update(kwargs)
cycle = colour_cycle(**settings)
for colourspace in colourspaces:
if colourspace == 'Pointer Gamut':
uv = UCS_to_uv(XYZ_to_UCS(xy_to_XYZ(POINTER_GAMUT_BOUNDARIES)))
alpha_p, colour_p = 0.85, '0.95'
pylab.plot(uv[..., 0],
uv[..., 1],
label='Pointer\'s Gamut',
color=colour_p,
alpha=alpha_p,
linewidth=2)
pylab.plot((uv[-1][0], uv[0][0]),
(uv[-1][1], uv[0][1]),
color=colour_p,
alpha=alpha_p,
linewidth=2)
XYZ = Lab_to_XYZ(LCHab_to_Lab(POINTER_GAMUT_DATA),
POINTER_GAMUT_ILLUMINANT)
uv = UCS_to_uv(XYZ_to_UCS(XYZ))
pylab.scatter(uv[..., 0],
uv[..., 1],
alpha=alpha_p / 2,
color=colour_p,
marker='+')
else:
colourspace, name = get_RGB_colourspace(colourspace), colourspace
r, g, b, _a = next(cycle)
# 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.
primaries = np.where(colourspace.primaries == 0,
EPSILON,
colourspace.primaries)
primaries = UCS_to_uv(XYZ_to_UCS(xy_to_XYZ(primaries)))
whitepoint = UCS_to_uv(XYZ_to_UCS(xy_to_XYZ(
colourspace.whitepoint)))
pylab.plot((whitepoint[0], whitepoint[0]),
(whitepoint[1], whitepoint[1]),
color=(r, g, b),
label=colourspace.name,
linewidth=2)
pylab.plot((whitepoint[0], whitepoint[0]),
(whitepoint[1], whitepoint[1]),
'o',
color=(r, g, b),
linewidth=2)
pylab.plot((primaries[0, 0], primaries[1, 0]),
(primaries[0, 1], primaries[1, 1]),
'o-',
color=(r, g, b),
linewidth=2)
pylab.plot((primaries[1, 0], primaries[2, 0]),
(primaries[1, 1], primaries[2, 1]),
'o-',
color=(r, g, b),
linewidth=2)
pylab.plot((primaries[2, 0], primaries[0, 0]),
(primaries[2, 1], primaries[0, 1]),
'o-',
color=(r, g, b),
linewidth=2)
x_limit_min.append(np.amin(primaries[..., 0]) - 0.1)
y_limit_min.append(np.amin(primaries[..., 1]) - 0.1)
x_limit_max.append(np.amax(primaries[..., 0]) + 0.1)
y_limit_max.append(np.amax(primaries[..., 1]) + 0.1)
settings.update({
'legend': True,
'legend_location': 'upper right',
'x_tighten': True,
'y_tighten': True,
'limits': (min(x_limit_min), max(x_limit_max),
min(y_limit_min), max(y_limit_max)),
'standalone': True})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
def RGB_chromaticity_coordinates_chromaticity_diagram_plot_CIE1976UCS(
RGB,
colourspace='sRGB',
chromaticity_diagram_callable_CIE1976UCS=(
RGB_colourspaces_chromaticity_diagram_plot_CIE1976UCS),
**kwargs):
"""
Plots given *RGB* colourspace array in *CIE 1976 UCS Chromaticity Diagram*.
Parameters
----------
RGB : array_like
*RGB* colourspace array.
colourspace : optional, unicode
*RGB* colourspace of the *RGB* array.
chromaticity_diagram_callable_CIE1976UCS : callable, optional
Callable responsible for drawing the
*CIE 1976 UCS Chromaticity Diagram*.
Other Parameters
----------------
\**kwargs : dict, optional
{:func:`colour.plotting.render`},
Please refer to the documentation of the previously listed definition.
show_diagram_colours : bool, optional
{:func:`colour.plotting.chromaticity_diagram_plot_CIE1976UCS`},
Whether to display the chromaticity diagram background colours.
use_cached_diagram_colours : bool, optional
{:func:`colour.plotting.chromaticity_diagram_plot_CIE1976UCS`},
Whether to used the cached chromaticity diagram background colours
image.
Returns
-------
Figure
Current figure or None.
Examples
--------
>>> RGB = np.random.random((10, 10, 3))
>>> c = 'ITU-R BT.709'
>>> RGB_chromaticity_coordinates_chromaticity_diagram_plot_CIE1976UCS(
... RGB, c) # doctest: +SKIP
"""
settings = {}
settings.update(kwargs)
settings.update({'standalone': False})
colourspace, name = get_RGB_colourspace(colourspace), colourspace
settings['colourspaces'] = ([name] + settings.get('colourspaces', []))
chromaticity_diagram_callable_CIE1976UCS(**settings)
alpha_p, colour_p = 0.85, 'black'
uv = Luv_to_uv(
XYZ_to_Luv(
RGB_to_XYZ(RGB, colourspace.whitepoint, colourspace.whitepoint,
colourspace.RGB_to_XYZ_matrix), colourspace.whitepoint),
colourspace.whitepoint)
pylab.scatter(uv[..., 0],
uv[..., 1],
alpha=alpha_p / 2,
color=colour_p,
marker='+')
settings.update({'standalone': True})
settings.update(kwargs)
return render(**settings)
def RGB_colourspace_volume_visual(colourspace='ITU-R BT.709',
reference_colourspace='CIE xyY',
segments=16,
uniform_colour=None,
uniform_opacity=0.5,
wireframe=True,
wireframe_colour=None,
wireframe_opacity=1.0,
parent=None):
"""
Returns a :class:`vispy.scene.visuals.Node` class instance with one or two
:class:`colour_analysis.visuals.Box` class instance children representing
a *RGB* colourspace volume visual.
Parameters
----------
colourspace : unicode, optional
**{'ITU-R BT.709', 'ACES2065-1', 'ACEScc', 'ACEScg', 'ACESproxy',
'ALEXA Wide Gamut', 'Adobe RGB (1998)', 'Adobe Wide Gamut RGB',
'Apple RGB', 'Best RGB', 'Beta RGB', 'CIE RGB', 'Cinema Gamut',
'ColorMatch RGB', 'DCI-P3', 'DCI-P3+', 'DRAGONcolor', 'DRAGONcolor2',
'Don RGB 4', 'ECI RGB v2', 'ERIMM RGB', 'Ekta Space PS 5', 'Max RGB',
'NTSC', 'Pal/Secam', 'ProPhoto RGB', 'REDcolor', 'REDcolor2',
'REDcolor3', 'REDcolor4', 'RIMM RGB', 'ROMM RGB', 'ITU-R BT.2020',
'Russell RGB', 'S-Gamut', 'S-Gamut3', 'S-Gamut3.Cine', 'SMPTE-C RGB',
'V-Gamut', 'Xtreme RGB', 'sRGB'}**,
:class:`colour.RGB_Colourspace` class instance name defining the *RGB*
colourspace volume to draw.
reference_colourspace : unicode
**{'CIE XYZ', 'CIE xyY', 'CIE Lab', 'CIE Luv', 'CIE UCS', 'CIE UVW',
'IPT', 'Hunter Lab', 'Hunter Rdab'}**,
Reference colourspace to convert the *CIE XYZ* tristimulus values to.
segments : int, optional
Box segments.
uniform_colour : array_like, optional
Uniform mesh colour.
uniform_opacity : numeric, optional
Uniform mesh opacity.
wireframe : bool, optional
Use wireframe display.
Uniform mesh opacity.
wireframe_colour : array_like, optional
Wireframe mesh colour.
wireframe_opacity : numeric, optional
Wireframe mesh opacity.
parent : Node, optional
Parent of the *RGB* colourspace volume visual in the `SceneGraph`.
"""
node = Node(parent)
colourspace = get_RGB_colourspace(colourspace)
RGB_cube_f = RGB_identity_cube(width_segments=segments,
height_segments=segments,
depth_segments=segments,
uniform_colour=uniform_colour,
uniform_opacity=uniform_opacity,
vertex_colours=not uniform_colour,
parent=node)
vertices = RGB_cube_f.mesh_data.get_vertices()
XYZ = RGB_to_XYZ(vertices, colourspace.whitepoint, colourspace.whitepoint,
colourspace.RGB_to_XYZ_matrix)
value = common_colourspace_model_axis_reorder(
XYZ_to_colourspace_model(XYZ, colourspace.whitepoint,
reference_colourspace), reference_colourspace)
value[np.isnan(value)] = 0
RGB_cube_f.mesh_data.set_vertices(value)
if wireframe:
RGB_cube_w = RGB_identity_cube(width_segments=segments,
height_segments=segments,
depth_segments=segments,
uniform_colour=wireframe_colour,
uniform_opacity=wireframe_opacity,
vertex_colours=not wireframe_colour,
wireframe=True,
parent=node)
RGB_cube_w.mesh_data.set_vertices(value)
return node
def plot_grid(filename, data_points, grid, bbox_xystar, xystar=True):
if not have_matplotlib or not have_colour_package:
return
print("Plotting the grid ...")
plt.figure()
# Draw a nice chromaticity diagram.
clr.CIE_1931_chromaticity_diagram_plot(standalone=False)
clr.canvas(figure_size=(7,7))
# Show the sRGB gamut.
color_space = clr.get_RGB_colourspace('sRGB')
x = color_space.primaries[:,0].tolist()
y = color_space.primaries[:,1].tolist()
plt.fill(x, y, color='black', label='sRGB', fill=False)
# Draw crosses into all internal grid cells.
# for gridcell in grid:
# if len(gridcell.indices) > 0 and gridcell.inside:
# if xystar:
# pointx = sum([data_points[i].xystar[0] for i in gridcell.indices])
# pointy = sum([data_points[i].xystar[1] for i in gridcell.indices])
# pointx /= len(gridcell.indices)
# pointy /= len(gridcell.indices)
# (pointx, pointy) = Transform.xy_from_xystar((pointx, pointy))
# plt.plot(pointx, pointy, "x", color="black")
# else:
# pointx = sum([data_points[i].uv[0] for i in gridcell.indices])
# pointy = sum([data_points[i].uv[1] for i in gridcell.indices])
# pointx /= len(gridcell.indices)
# pointy /= len(gridcell.indices)
# (pointx, pointy) = Transform.xy_from_uv((pointx, pointy))
# plt.plot(pointx, pointy, "x", color="black")
# Draw data points.
for i, data_point in enumerate(data_points):
if xystar:
p = Transform.xy_from_xystar(data_point.xystar)
else:
p = Transform.xy_from_uv(data_point.uv)
if data_point.equal_energy_white:
plt.plot(p[0], p[1], "o", color="white", ms=4)
elif data_point.broken:
plt.plot(p[0], p[1], "o", color="red", ms=4)
else:
plt.plot(p[0], p[1], "o", color="green", ms=4)
# Show grid point indices, for debugging.
# plt.text(p[0]+0.01, p[1]-0.01, '{}'.format(i))
bp0 = Transform.xy_from_xystar([bbox_xystar[0][0], bbox_xystar[0][1]])
bp1 = Transform.xy_from_xystar([bbox_xystar[0][0], bbox_xystar[1][1]])
bp2 = Transform.xy_from_xystar([bbox_xystar[1][0], bbox_xystar[1][1]])
bp3 = Transform.xy_from_xystar([bbox_xystar[1][0], bbox_xystar[0][1]])
plt.plot([bp0[0], bp1[0], bp2[0], bp3[0], bp0[0]],
[bp0[1], bp1[1], bp2[1], bp3[1], bp0[1]],
label="Grid Bounding Box")
plt.xlabel('$x$')
plt.ylabel('$y$')
plt.legend()
plt.savefig(filename)
def RGB_colourspaces_CIE_1931_chromaticity_diagram_plot(
colourspaces=None,
cmfs='CIE 1931 2 Degree Standard Observer',
**kwargs):
"""
Plots given *RGB* colourspaces in *CIE 1931 Chromaticity Diagram*.
Parameters
----------
colourspaces : array_like, optional
*RGB* colourspaces to plot.
cmfs : unicode, optional
Standard observer colour matching functions used for diagram bounds.
Other Parameters
----------------
\**kwargs : dict, optional
{:func:`boundaries`, :func:`canvas`, :func:`decorate`,
:func:`display`},
Please refer to the documentation of the previously listed definitions.
show_diagram_colours : bool, optional
{:func:`CIE_1931_chromaticity_diagram_plot`},
Whether to display the chromaticity diagram background colours.
Returns
-------
Figure
Current figure or None.
Examples
--------
>>> c = ['Rec. 709', 'ACEScg', 'S-Gamut']
>>> RGB_colourspaces_CIE_1931_chromaticity_diagram_plot(
... c) # doctest: +SKIP
"""
settings = {'figure_size': (DEFAULT_FIGURE_WIDTH, DEFAULT_FIGURE_WIDTH)}
settings.update(kwargs)
canvas(**settings)
if colourspaces is None:
colourspaces = ('Rec. 709', 'ACEScg', 'S-Gamut', 'Pointer Gamut')
cmfs, name = get_cmfs(cmfs), cmfs
settings = {
'title':
'{0} - {1} - CIE 1931 Chromaticity Diagram'.format(
', '.join(colourspaces), name),
'standalone':
False
}
settings.update(kwargs)
CIE_1931_chromaticity_diagram_plot(**settings)
x_limit_min, x_limit_max = [-0.1], [0.9]
y_limit_min, y_limit_max = [-0.1], [0.9]
settings = {
'colour_cycle_map': 'rainbow',
'colour_cycle_count': len(colourspaces)
}
settings.update(kwargs)
cycle = colour_cycle(**settings)
for colourspace in colourspaces:
if colourspace == 'Pointer Gamut':
xy = np.asarray(POINTER_GAMUT_BOUNDARIES)
alpha_p, colour_p = 0.85, '0.95'
pylab.plot(xy[..., 0],
xy[..., 1],
label='Pointer\'s Gamut',
color=colour_p,
alpha=alpha_p,
linewidth=2)
pylab.plot((xy[-1][0], xy[0][0]), (xy[-1][1], xy[0][1]),
color=colour_p,
alpha=alpha_p,
linewidth=2)
XYZ = Lab_to_XYZ(LCHab_to_Lab(POINTER_GAMUT_DATA),
POINTER_GAMUT_ILLUMINANT)
xy = XYZ_to_xy(XYZ, POINTER_GAMUT_ILLUMINANT)
pylab.scatter(xy[..., 0],
xy[..., 1],
alpha=alpha_p / 2,
color=colour_p,
marker='+')
else:
colourspace, name = get_RGB_colourspace(colourspace), colourspace
r, g, b, _a = next(cycle)
primaries = colourspace.primaries
whitepoint = colourspace.whitepoint
pylab.plot((whitepoint[0], whitepoint[0]),
(whitepoint[1], whitepoint[1]),
color=(r, g, b),
label=colourspace.name,
linewidth=2)
pylab.plot((whitepoint[0], whitepoint[0]),
(whitepoint[1], whitepoint[1]),
'o',
color=(r, g, b),
linewidth=2)
pylab.plot((primaries[0, 0], primaries[1, 0]),
(primaries[0, 1], primaries[1, 1]),
'o-',
color=(r, g, b),
linewidth=2)
pylab.plot((primaries[1, 0], primaries[2, 0]),
(primaries[1, 1], primaries[2, 1]),
'o-',
color=(r, g, b),
linewidth=2)
pylab.plot((primaries[2, 0], primaries[0, 0]),
(primaries[2, 1], primaries[0, 1]),
'o-',
color=(r, g, b),
linewidth=2)
x_limit_min.append(np.amin(primaries[..., 0]) - 0.1)
y_limit_min.append(np.amin(primaries[..., 1]) - 0.1)
x_limit_max.append(np.amax(primaries[..., 0]) + 0.1)
y_limit_max.append(np.amax(primaries[..., 1]) + 0.1)
settings.update({
'legend':
True,
'legend_location':
'upper right',
'x_tighten':
True,
'y_tighten':
True,
'limits': (min(x_limit_min), max(x_limit_max), min(y_limit_min),
max(y_limit_max)),
'standalone':
True
})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
def RGB_chromaticity_coordinates_CIE_1976_UCS_chromaticity_diagram_plot(
RGB, colourspace, **kwargs):
"""
Plots given *RGB* colourspace array in *CIE 1976 UCS Chromaticity Diagram*.
Parameters
----------
RGB : array_like
*RGB* colourspace array.
colourspace : unicode
*RGB* colourspace of the *RGB* array.
Other Parameters
----------------
\**kwargs : dict, optional
{:func:`boundaries`, :func:`canvas`, :func:`decorate`,
:func:`display`},
Please refer to the documentation of the previously listed definitions.
show_diagram_colours : bool, optional
{:func:`CIE_1976_UCS_chromaticity_diagram_plot`},
Whether to display the chromaticity diagram background colours.
Returns
-------
Figure
Current figure or None.
Examples
--------
>>> RGB = np.random.random((10, 10, 3))
>>> c = 'Rec. 709'
>>> RGB_chromaticity_coordinates_CIE_1976_UCS_chromaticity_diagram_plot(
... RGB, c) # doctest: +SKIP
"""
settings = {}
settings.update(kwargs)
settings.update({'standalone': False})
colourspace, name = get_RGB_colourspace(colourspace), colourspace
settings['colourspaces'] = ([name] + settings.get('colourspaces', []))
RGB_colourspaces_CIE_1976_UCS_chromaticity_diagram_plot(**settings)
alpha_p, colour_p = 0.85, 'black'
uv = Luv_to_uv(
XYZ_to_Luv(
RGB_to_XYZ(RGB, colourspace.whitepoint, colourspace.whitepoint,
colourspace.RGB_to_XYZ_matrix), colourspace.whitepoint),
colourspace.whitepoint)
pylab.scatter(uv[..., 0],
uv[..., 1],
alpha=alpha_p / 2,
color=colour_p,
marker='+')
settings.update({'standalone': True})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
def RGB_colourspaces_CIE_1976_UCS_chromaticity_diagram_plot(
colourspaces=None,
cmfs='CIE 1931 2 Degree Standard Observer',
**kwargs):
"""
Plots given *RGB* colourspaces in *CIE 1976 UCS Chromaticity Diagram*.
Parameters
----------
colourspaces : array_like, optional
*RGB* colourspaces to plot.
cmfs : unicode, optional
Standard observer colour matching functions used for diagram bounds.
\**kwargs : dict, optional
Keywords arguments.
Returns
-------
bool
Definition success.
Examples
--------
>>> c = ['Rec. 709', 'ACEScg', 'S-Gamut']
>>> RGB_colourspaces_CIE_1976_UCS_chromaticity_diagram_plot(
... c) # doctest: +SKIP
True
"""
settings = {'figure_size': (DEFAULT_FIGURE_WIDTH, DEFAULT_FIGURE_WIDTH)}
settings.update(kwargs)
canvas(**settings)
if colourspaces is None:
colourspaces = ('Rec. 709', 'ACEScg', 'S-Gamut', 'Pointer Gamut')
cmfs, name = get_cmfs(cmfs), cmfs
illuminant = DEFAULT_PLOTTING_ILLUMINANT
settings = {
'title': '{0} - {1} - CIE 1976 UCS Chromaticity Diagram'.format(
', '.join(colourspaces), name),
'standalone': False}
settings.update(kwargs)
CIE_1976_UCS_chromaticity_diagram_plot(**settings)
x_limit_min, x_limit_max = [-0.1], [0.7]
y_limit_min, y_limit_max = [-0.1], [0.7]
settings = {'colour_cycle_map': 'rainbow',
'colour_cycle_count': len(colourspaces)}
settings.update(kwargs)
cycle = colour_cycle(**settings)
for colourspace in colourspaces:
if colourspace == 'Pointer Gamut':
uv = Luv_to_uv(XYZ_to_Luv(xy_to_XYZ(
POINTER_GAMUT_BOUNDARIES), illuminant), illuminant)
alpha_p, colour_p = 0.85, '0.95'
pylab.plot(uv[..., 0],
uv[..., 1],
label='Pointer\'s Gamut',
color=colour_p,
alpha=alpha_p,
linewidth=2)
pylab.plot((uv[-1][0], uv[0][0]),
(uv[-1][1], uv[0][1]),
color=colour_p,
alpha=alpha_p,
linewidth=2)
XYZ = Lab_to_XYZ(LCHab_to_Lab(POINTER_GAMUT_DATA),
POINTER_GAMUT_ILLUMINANT)
uv = Luv_to_uv(XYZ_to_Luv(XYZ, illuminant), illuminant)
pylab.scatter(uv[..., 0],
uv[..., 1],
alpha=alpha_p / 2,
color=colour_p,
marker='+')
else:
colourspace, name = get_RGB_colourspace(colourspace), colourspace
r, g, b, _a = next(cycle)
# 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.
primaries = np.where(colourspace.primaries == 0,
EPSILON,
colourspace.primaries)
primaries = Luv_to_uv(XYZ_to_Luv(xy_to_XYZ(
primaries), illuminant), illuminant)
whitepoint = Luv_to_uv(XYZ_to_Luv(xy_to_XYZ(
colourspace.whitepoint), illuminant), illuminant)
pylab.plot((whitepoint[0], whitepoint[0]),
(whitepoint[1], whitepoint[1]),
color=(r, g, b),
label=colourspace.name,
linewidth=2)
pylab.plot((whitepoint[0], whitepoint[0]),
(whitepoint[1], whitepoint[1]),
'o',
color=(r, g, b),
linewidth=2)
pylab.plot((primaries[0, 0], primaries[1, 0]),
(primaries[0, 1], primaries[1, 1]),
'o-',
color=(r, g, b),
linewidth=2)
pylab.plot((primaries[1, 0], primaries[2, 0]),
(primaries[1, 1], primaries[2, 1]),
'o-',
color=(r, g, b),
linewidth=2)
pylab.plot((primaries[2, 0], primaries[0, 0]),
(primaries[2, 1], primaries[0, 1]),
'o-',
color=(r, g, b),
linewidth=2)
x_limit_min.append(np.amin(primaries[..., 0]) - 0.1)
y_limit_min.append(np.amin(primaries[..., 1]) - 0.1)
x_limit_max.append(np.amax(primaries[..., 0]) + 0.1)
y_limit_max.append(np.amax(primaries[..., 1]) + 0.1)
settings.update({
'legend': True,
'legend_location': 'upper right',
'x_tighten': True,
'y_tighten': True,
'limits': (min(x_limit_min), max(x_limit_max),
min(y_limit_min), max(y_limit_max)),
'standalone': True})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
def RGB_scatter_plot(RGB,
colourspace,
reference_colourspace='CIE xyY',
colourspaces=None,
segments=8,
display_grid=True,
grid_segments=10,
spectral_locus=False,
spectral_locus_colour=None,
points_size=12,
cmfs='CIE 1931 2 Degree Standard Observer',
**kwargs):
"""
Plots given *RGB* colourspace array in a scatter plot.
Parameters
----------
RGB : array_like
*RGB* colourspace array.
colourspace : RGB_Colourspace
*RGB* colourspace of the *RGB* array.
reference_colourspace : unicode, optional
**{'CIE XYZ', 'CIE xyY', 'CIE Lab', 'CIE Luv', 'CIE UCS', 'CIE UVW',
'IPT'}**,
Reference colourspace for colour conversion.
colourspaces : array_like, optional
*RGB* colourspaces to plot the gamuts.
segments : int, optional
Edge segments count for each *RGB* colourspace cubes.
display_grid : bool, optional
Display a grid at the bottom of the *RGB* colourspace cubes.
grid_segments : bool, optional
Edge segments count for the grid.
spectral_locus : bool, optional
Is spectral locus line plotted.
spectral_locus_colour : array_like, optional
Spectral locus line colour.
points_size : numeric, optional
Scatter points size.
cmfs : unicode, optional
Standard observer colour matching functions used for spectral locus.
\**kwargs : dict, optional
**{'face_colours', 'edge_colours', 'edge_alpha', 'face_alpha'}**,
Arguments for each given colourspace where each key has an array_like
value such as: ``{ 'face_colours': (None, (0.5, 0.5, 1.0)),
'edge_colours': (None, (0.5, 0.5, 1.0)), 'edge_alpha': (0.5, 1.0),
'face_alpha': (0.0, 1.0)}``
**{'grid_face_colours', 'grid_edge_colours', 'grid_face_alpha',
'grid_edge_alpha', 'x_axis_colour', 'y_axis_colour', 'x_ticks_colour',
'y_ticks_colour', 'x_label_colour', 'y_label_colour',
'ticks_and_label_location'}**,
Arguments for the nadir grid such as ``{'grid_face_colours':
(0.25, 0.25, 0.25), 'grid_edge_colours': (0.50, 0.50, 0.50),
'grid_face_alpha': 0.1, 'grid_edge_alpha': 0.5, 'x_axis_colour':
(0.0, 0.0, 0.0, 1.0), 'y_axis_colour': (0.0, 0.0, 0.0, 1.0),
'x_ticks_colour': (0.0, 0.0, 0.0, 0.85), 'y_ticks_colour':
(0.0, 0.0, 0.0, 0.85), 'x_label_colour': (0.0, 0.0, 0.0, 0.85),
'y_label_colour': (0.0, 0.0, 0.0, 0.85), 'ticks_and_label_location':
('-x', '-y')}``
Returns
-------
bool
Definition success.
Examples
--------
>>> c = 'Rec. 709'
>>> RGB_scatter_plot(c) # doctest: +SKIP
True
"""
colourspace = get_RGB_colourspace(colourspace)
if colourspaces is None:
colourspaces = (colourspace.name, )
count_c = len(colourspaces)
settings = Structure(
**{
'face_colours': [None] * count_c,
'edge_colours': [(0.25, 0.25, 0.25)] * count_c,
'face_alpha': [0.0] * count_c,
'edge_alpha': [0.1] * count_c,
'standalone': False
})
settings.update(kwargs)
RGB_colourspaces_gamuts_plot(colourspaces=colourspaces,
reference_colourspace=reference_colourspace,
segments=segments,
display_grid=display_grid,
grid_segments=grid_segments,
spectral_locus=spectral_locus,
spectral_locus_colour=spectral_locus_colour,
cmfs=cmfs,
**settings)
XYZ = RGB_to_XYZ(RGB, colourspace.whitepoint, colourspace.whitepoint,
colourspace.RGB_to_XYZ_matrix)
points = XYZ_to_reference_colourspace(XYZ, colourspace.whitepoint,
reference_colourspace)
axes = matplotlib.pyplot.gca()
axes.scatter(points[..., 0],
points[..., 1],
points[..., 2],
color=np.reshape(RGB, (-1, 3)),
s=points_size)
settings.update({'standalone': True})
settings.update(kwargs)
camera(**settings)
decorate(**settings)
return display(**settings)
def multi_conversion_function_plot(colourspaces=None,
EOCF=False,
**kwargs):
"""
Plots given colourspaces opto-electronic conversion functions.
Parameters
----------
colourspaces : array_like, optional
Colourspaces opto-electronic conversion functions to plot.
EOCF : bool
Plot electro-optical conversion functions instead.
\**kwargs : dict, optional
Keywords arguments.
Returns
-------
bool
Definition success.
Examples
--------
>>> multi_conversion_function_plot(['Rec. 709', 'sRGB']) # doctest: +SKIP
True
"""
settings = {'figure_size': (DEFAULT_FIGURE_WIDTH, DEFAULT_FIGURE_WIDTH)}
settings.update(kwargs)
canvas(**settings)
if colourspaces is None:
colourspaces = ('Rec. 709', 'sRGB')
samples = np.linspace(0, 1, 1000)
for colourspace in colourspaces:
colourspace = get_RGB_colourspace(colourspace)
RGBs = colourspace.EOCF(samples) if EOCF else colourspace.OECF(samples)
pylab.plot(samples,
RGBs,
label=u'{0}'.format(colourspace.name),
linewidth=2)
settings.update({
'title': '{0} - {1} Conversion Functions'.format(
', '.join(colourspaces),
'Electro-Optical' if EOCF else 'Opto-Electronic'),
'x_tighten': True,
'legend': True,
'legend_location': 'upper left',
'grid': True,
'limits': (0, 1, 0, 1),
'aspect': 'equal'})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
def RGB_colourspaces_gamuts_plot(colourspaces=None,
reference_colourspace='CIE xyY',
segments=8,
display_grid=True,
grid_segments=10,
spectral_locus=False,
spectral_locus_colour=None,
cmfs='CIE 1931 2 Degree Standard Observer',
**kwargs):
"""
Plots given *RGB* colourspaces gamuts in given reference colourspace.
Parameters
----------
colourspaces : array_like, optional
*RGB* colourspaces to plot the gamuts.
reference_colourspace : unicode, optional
**{'CIE XYZ', 'CIE xyY', 'CIE Lab', 'CIE Luv', 'CIE UCS', 'CIE UVW',
'IPT', 'Hunter Lab', 'Hunter Rdab'}**,
Reference colourspace to plot the gamuts into.
segments : int, optional
Edge segments count for each *RGB* colourspace cubes.
display_grid : bool, optional
Display a grid at the bottom of the *RGB* colourspace cubes.
grid_segments : bool, optional
Edge segments count for the grid.
spectral_locus : bool, optional
Is spectral locus line plotted.
spectral_locus_colour : array_like, optional
Spectral locus line colour.
cmfs : unicode, optional
Standard observer colour matching functions used for spectral locus.
Other Parameters
----------------
\**kwargs : dict, optional
{:func:`nadir_grid`},
Please refer to the documentation of the previously listed definitions.
face_colours : array_like, optional
Face colours array such as `face_colours = (None, (0.5, 0.5, 1.0))`.
edge_colours : array_like, optional
Edge colours array such as `edge_colours = (None, (0.5, 0.5, 1.0))`.
face_alpha : numeric, optional
Face opacity value such as `face_alpha = (0.5, 1.0)`.
edge_alpha : numeric, optional
Edge opacity value such as `edge_alpha = (0.0, 1.0)`.
Returns
-------
Figure
Current figure or None.
Examples
--------
>>> c = ['Rec. 709', 'ACEScg', 'S-Gamut']
>>> RGB_colourspaces_gamuts_plot(c) # doctest: +SKIP
"""
if colourspaces is None:
colourspaces = ('Rec. 709', 'ACEScg')
count_c = len(colourspaces)
settings = Structure(
**{
'face_colours': [None] * count_c,
'edge_colours': [None] * count_c,
'face_alpha': [1] * count_c,
'edge_alpha': [1] * count_c,
'title':
'{0} - {1} Reference Colourspace'.format(', '.join(colourspaces),
reference_colourspace)
})
settings.update(kwargs)
figure = matplotlib.pyplot.figure()
axes = figure.add_subplot(111, projection='3d')
illuminant = DEFAULT_PLOTTING_ILLUMINANT
points = np.zeros((4, 3))
if spectral_locus:
cmfs = get_cmfs(cmfs)
XYZ = cmfs.values
points = common_colourspace_model_axis_reorder(
XYZ_to_colourspace_model(XYZ, illuminant, reference_colourspace),
reference_colourspace)
points[np.isnan(points)] = 0
c = ((0.0, 0.0, 0.0,
0.5) if spectral_locus_colour is None else spectral_locus_colour)
pylab.plot(points[..., 0],
points[..., 1],
points[..., 2],
color=c,
linewidth=2,
zorder=1)
pylab.plot((points[-1][0], points[0][0]),
(points[-1][1], points[0][1]),
(points[-1][2], points[0][2]),
color=c,
linewidth=2,
zorder=1)
quads, RGB_f, RGB_e = [], [], []
for i, colourspace in enumerate(colourspaces):
colourspace = get_RGB_colourspace(colourspace)
quads_c, RGB = RGB_identity_cube(width_segments=segments,
height_segments=segments,
depth_segments=segments)
XYZ = RGB_to_XYZ(quads_c, colourspace.whitepoint,
colourspace.whitepoint, colourspace.RGB_to_XYZ_matrix)
quads.extend(
common_colourspace_model_axis_reorder(
XYZ_to_colourspace_model(XYZ, colourspace.whitepoint,
reference_colourspace),
reference_colourspace))
if settings.face_colours[i] is not None:
RGB = np.ones(RGB.shape) * settings.face_colours[i]
RGB_f.extend(
np.hstack((RGB,
np.full((RGB.shape[0], 1), settings.face_alpha[i],
np.float_))))
if settings.edge_colours[i] is not None:
RGB = np.ones(RGB.shape) * settings.edge_colours[i]
RGB_e.extend(
np.hstack((RGB,
np.full((RGB.shape[0], 1), settings.edge_alpha[i],
np.float_))))
quads = np.asarray(quads)
quads[np.isnan(quads)] = 0
if quads.size != 0:
for i, axis in enumerate('xyz'):
min_a = np.min(np.vstack((quads[..., i], points[..., i])))
max_a = np.max(np.vstack((quads[..., i], points[..., i])))
getattr(axes, 'set_{}lim'.format(axis))((min_a, max_a))
labels = COLOURSPACE_MODELS_LABELS[reference_colourspace]
for i, axis in enumerate('xyz'):
getattr(axes, 'set_{}label'.format(axis))(labels[i])
if display_grid:
if reference_colourspace == 'CIE Lab':
limits = np.array([[-450, 450], [-450, 450]])
elif reference_colourspace == 'CIE Luv':
limits = np.array([[-650, 650], [-650, 650]])
elif reference_colourspace == 'CIE UVW':
limits = np.array([[-850, 850], [-850, 850]])
elif reference_colourspace in ('Hunter Lab', 'Hunter Rdab'):
limits = np.array([[-250, 250], [-250, 250]])
else:
limits = np.array([[-1.5, 1.5], [-1.5, 1.5]])
quads_g, RGB_gf, RGB_ge = nadir_grid(limits, grid_segments, labels,
axes, **settings)
quads = np.vstack((quads_g, quads))
RGB_f = np.vstack((RGB_gf, RGB_f))
RGB_e = np.vstack((RGB_ge, RGB_e))
collection = Poly3DCollection(quads)
collection.set_facecolors(RGB_f)
collection.set_edgecolors(RGB_e)
axes.add_collection3d(collection)
settings.update({'camera_aspect': 'equal', 'no_axes': True})
settings.update(kwargs)
camera(**settings)
decorate(**settings)
return display(**settings)
def RGB_colourspaces_CIE_1931_chromaticity_diagram_plot(
colourspaces=None,
cmfs='CIE 1931 2 Degree Standard Observer',
**kwargs):
"""
Plots given *RGB* colourspaces in *CIE 1931 Chromaticity Diagram*.
Parameters
----------
colourspaces : array_like, optional
*RGB* colourspaces to plot.
cmfs : unicode, optional
Standard observer colour matching functions used for diagram bounds.
\**kwargs : dict, optional
Keywords arguments.
Returns
-------
Figure
Current figure or None.
Examples
--------
>>> c = ['Rec. 709', 'ACEScg', 'S-Gamut']
>>> RGB_colourspaces_CIE_1931_chromaticity_diagram_plot(
... c) # doctest: +SKIP
"""
settings = {'figure_size': (DEFAULT_FIGURE_WIDTH, DEFAULT_FIGURE_WIDTH)}
settings.update(kwargs)
canvas(**settings)
if colourspaces is None:
colourspaces = ('Rec. 709', 'ACEScg', 'S-Gamut', 'Pointer Gamut')
cmfs, name = get_cmfs(cmfs), cmfs
settings = {
'title': '{0} - {1} - CIE 1931 Chromaticity Diagram'.format(
', '.join(colourspaces), name),
'standalone': False}
settings.update(kwargs)
CIE_1931_chromaticity_diagram_plot(**settings)
x_limit_min, x_limit_max = [-0.1], [0.9]
y_limit_min, y_limit_max = [-0.1], [0.9]
settings = {'colour_cycle_map': 'rainbow',
'colour_cycle_count': len(colourspaces)}
settings.update(kwargs)
cycle = colour_cycle(**settings)
for colourspace in colourspaces:
if colourspace == 'Pointer Gamut':
xy = np.asarray(POINTER_GAMUT_BOUNDARIES)
alpha_p, colour_p = 0.85, '0.95'
pylab.plot(xy[..., 0],
xy[..., 1],
label='Pointer\'s Gamut',
color=colour_p,
alpha=alpha_p,
linewidth=2)
pylab.plot((xy[-1][0], xy[0][0]),
(xy[-1][1], xy[0][1]),
color=colour_p,
alpha=alpha_p,
linewidth=2)
XYZ = Lab_to_XYZ(LCHab_to_Lab(POINTER_GAMUT_DATA),
POINTER_GAMUT_ILLUMINANT)
xy = XYZ_to_xy(XYZ, POINTER_GAMUT_ILLUMINANT)
pylab.scatter(xy[..., 0],
xy[..., 1],
alpha=alpha_p / 2,
color=colour_p,
marker='+')
else:
colourspace, name = get_RGB_colourspace(colourspace), colourspace
r, g, b, _a = next(cycle)
primaries = colourspace.primaries
whitepoint = colourspace.whitepoint
pylab.plot((whitepoint[0], whitepoint[0]),
(whitepoint[1], whitepoint[1]),
color=(r, g, b),
label=colourspace.name,
linewidth=2)
pylab.plot((whitepoint[0], whitepoint[0]),
(whitepoint[1], whitepoint[1]),
'o',
color=(r, g, b),
linewidth=2)
pylab.plot((primaries[0, 0], primaries[1, 0]),
(primaries[0, 1], primaries[1, 1]),
'o-',
color=(r, g, b),
linewidth=2)
pylab.plot((primaries[1, 0], primaries[2, 0]),
(primaries[1, 1], primaries[2, 1]),
'o-',
color=(r, g, b),
linewidth=2)
pylab.plot((primaries[2, 0], primaries[0, 0]),
(primaries[2, 1], primaries[0, 1]),
'o-',
color=(r, g, b),
linewidth=2)
x_limit_min.append(np.amin(primaries[..., 0]) - 0.1)
y_limit_min.append(np.amin(primaries[..., 1]) - 0.1)
x_limit_max.append(np.amax(primaries[..., 0]) + 0.1)
y_limit_max.append(np.amax(primaries[..., 1]) + 0.1)
settings.update({
'legend': True,
'legend_location': 'upper right',
'x_tighten': True,
'y_tighten': True,
'limits': (min(x_limit_min), max(x_limit_max),
min(y_limit_min), max(y_limit_max)),
'standalone': True})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
def RGB_scatter_visual(RGB,
colourspace='Rec. 709',
reference_colourspace='CIE xyY',
symbol='disc',
size=4.0,
edge_size=0.5,
uniform_colour=None,
uniform_opacity=1.0,
uniform_edge_colour=None,
uniform_edge_opacity=1.0,
resampling='auto',
parent=None):
"""
Returns a :class:`vispy.scene.visuals.Symbol` class instance representing
*RGB* data using given symbols.
Parameters
----------
RGB : array_like
*RGB* data to draw.
colourspace : unicode, optional
{'Rec. 709', 'ACES2065-1', 'ACEScc', 'ACEScg', 'ACESproxy',
'ALEXA Wide Gamut RGB', 'Adobe RGB 1998', 'Adobe Wide Gamut RGB',
'Apple RGB', 'Best RGB', 'Beta RGB', 'CIE RGB', 'Cinema Gamut',
'ColorMatch RGB', 'DCI-P3', 'DCI-P3+', 'DRAGONcolor', 'DRAGONcolor2',
'Don RGB 4', 'ECI RGB v2', 'Ekta Space PS 5', 'Max RGB', 'NTSC RGB',
'Pal/Secam RGB', 'ProPhoto RGB', 'REDcolor', 'REDcolor2', 'REDcolor3',
'REDcolor4', 'Rec. 2020', 'Russell RGB', 'S-Gamut', 'S-Gamut3',
'S-Gamut3.Cine', 'SMPTE-C RGB', 'V-Gamut', 'Xtreme RGB', 'aces',
'adobe1998', 'prophoto', 'sRGB'}
:class:`colour.RGB_Colourspace` class instance name defining the *RGB*
colourspace of the data to draw.
reference_colourspace : unicode, optional
{'CIE XYZ', 'CIE xyY', 'CIE Lab', 'CIE Luv', 'CIE UCS', 'CIE UVW',
'IPT'}
Reference colourspace to use for colour conversions / transformations.
symbol : unicode, optional
Symbol type to draw.
size : numeric, optional
Symbol size.
edge_size : numeric, optional
Symbol edge size.
uniform_colour : array_like, optional
Uniform symbol colour.
uniform_opacity : numeric, optional
Uniform symbol opacity.
uniform_edge_colour : array_like, optional
Uniform symbol edge colour.
uniform_edge_opacity : numeric, optional
Uniform symbol edge opacity.
resampling : numeric or unicode, optional
Resampling value, if numeric input, one pixel every `resampling`
argument value will be kept.
parent : Node, optional
Parent of the *RGB* scatter visual in the `SceneGraph`.
Returns
-------
Symbol
*RGB* scatter visual.
"""
colourspace = get_RGB_colourspace(colourspace)
RGB = np.asarray(RGB)
if resampling == 'auto':
resampling = int((0.0078125 * np.average(RGB.shape[0:1])) // 2)
RGB = RGB[::resampling, ::resampling].reshape((-1, 3))
XYZ = RGB_to_XYZ(
RGB,
colourspace.whitepoint,
colourspace.whitepoint,
colourspace.RGB_to_XYZ_matrix)
points = XYZ_to_reference_colourspace(XYZ,
colourspace.whitepoint,
reference_colourspace)
points[np.isnan(points)] = 0
RGB = np.clip(RGB, 0, 1)
if uniform_colour is None:
RGB = np.hstack((RGB, np.full((RGB.shape[0], 1), uniform_opacity)))
else:
RGB = ColorArray(uniform_colour, alpha=uniform_opacity).rgba
if uniform_edge_colour is None:
RGB_e = RGB
else:
RGB_e = ColorArray(uniform_edge_colour,
alpha=uniform_edge_opacity).rgba
markers = Symbol(symbol=symbol,
positions=points,
size=size,
edge_size=edge_size,
face_colour=RGB,
edge_colour=RGB_e,
parent=parent)
return markers
def multi_cctf_plot(colourspaces=None, decoding_cctf=False, **kwargs):
"""
Plots given colourspaces colour component transfer functions.
Parameters
----------
colourspaces : array_like, optional
Colourspaces colour component transfer function to plot.
decoding_cctf : bool
Plot decoding colour component transfer function instead.
\**kwargs : dict, optional
Keywords arguments.
Returns
-------
Figure
Current figure or None.
Examples
--------
>>> multi_cctf_plot(['Rec. 709', 'sRGB']) # doctest: +SKIP
"""
settings = {'figure_size': (DEFAULT_FIGURE_WIDTH, DEFAULT_FIGURE_WIDTH)}
settings.update(kwargs)
canvas(**settings)
if colourspaces is None:
colourspaces = ('Rec. 709', 'sRGB')
samples = np.linspace(0, 1, 1000)
for colourspace in colourspaces:
colourspace = get_RGB_colourspace(colourspace)
RGBs = (colourspace.decoding_cctf(samples)
if decoding_cctf else colourspace.encoding_cctf(samples))
pylab.plot(samples,
RGBs,
label=u'{0}'.format(colourspace.name),
linewidth=2)
settings.update({
'title': '{0} - {1} CCTFs'.format(
', '.join(colourspaces),
'Decoding' if decoding_cctf else 'Encoding'),
'x_tighten': True,
'x_label': 'Signal Value' if decoding_cctf else 'Tristimulus Value',
'y_label': 'Tristimulus Value' if decoding_cctf else 'Signal Value',
'legend': True,
'legend_location': 'upper left',
'grid': True,
'limits': (0, 1, 0, 1),
'aspect': 'equal'})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
def RGB_scatter_plot(RGB,
colourspace,
reference_colourspace='CIE xyY',
colourspaces=None,
segments=8,
display_grid=True,
grid_segments=10,
spectral_locus=False,
spectral_locus_colour=None,
points_size=12,
cmfs='CIE 1931 2 Degree Standard Observer',
**kwargs):
"""
Plots given *RGB* colourspace array in a scatter plot.
Parameters
----------
RGB : array_like
*RGB* colourspace array.
colourspace : RGB_Colourspace
*RGB* colourspace of the *RGB* array.
reference_colourspace : unicode, optional
**{'CIE XYZ', 'CIE xyY', 'CIE Lab', 'CIE Luv', 'CIE UCS', 'CIE UVW',
'IPT'}**,
Reference colourspace for colour conversion.
colourspaces : array_like, optional
*RGB* colourspaces to plot the gamuts.
segments : int, optional
Edge segments count for each *RGB* colourspace cubes.
display_grid : bool, optional
Display a grid at the bottom of the *RGB* colourspace cubes.
grid_segments : bool, optional
Edge segments count for the grid.
spectral_locus : bool, optional
Is spectral locus line plotted.
spectral_locus_colour : array_like, optional
Spectral locus line colour.
points_size : numeric, optional
Scatter points size.
cmfs : unicode, optional
Standard observer colour matching functions used for spectral locus.
\**kwargs : dict, optional
**{'face_colours', 'edge_colours', 'edge_alpha', 'face_alpha'}**,
Arguments for each given colourspace where each key has an array_like
value such as: ``{ 'face_colours': (None, (0.5, 0.5, 1.0)),
'edge_colours': (None, (0.5, 0.5, 1.0)), 'edge_alpha': (0.5, 1.0),
'face_alpha': (0.0, 1.0)}``
**{'grid_face_colours', 'grid_edge_colours', 'grid_face_alpha',
'grid_edge_alpha', 'x_axis_colour', 'y_axis_colour', 'x_ticks_colour',
'y_ticks_colour', 'x_label_colour', 'y_label_colour',
'ticks_and_label_location'}**,
Arguments for the nadir grid such as ``{'grid_face_colours':
(0.25, 0.25, 0.25), 'grid_edge_colours': (0.50, 0.50, 0.50),
'grid_face_alpha': 0.1, 'grid_edge_alpha': 0.5, 'x_axis_colour':
(0.0, 0.0, 0.0, 1.0), 'y_axis_colour': (0.0, 0.0, 0.0, 1.0),
'x_ticks_colour': (0.0, 0.0, 0.0, 0.85), 'y_ticks_colour':
(0.0, 0.0, 0.0, 0.85), 'x_label_colour': (0.0, 0.0, 0.0, 0.85),
'y_label_colour': (0.0, 0.0, 0.0, 0.85), 'ticks_and_label_location':
('-x', '-y')}``
Returns
-------
bool
Definition success.
Examples
--------
>>> c = 'Rec. 709'
>>> RGB_scatter_plot(c) # doctest: +SKIP
True
"""
colourspace = get_RGB_colourspace(colourspace)
if colourspaces is None:
colourspaces = (colourspace.name,)
count_c = len(colourspaces)
settings = Structure(
**{'face_colours': [None] * count_c,
'edge_colours': [(0.25, 0.25, 0.25)] * count_c,
'face_alpha': [0.0] * count_c,
'edge_alpha': [0.1] * count_c,
'standalone': False})
settings.update(kwargs)
RGB_colourspaces_gamuts_plot(
colourspaces=colourspaces,
reference_colourspace=reference_colourspace,
segments=segments,
display_grid=display_grid,
grid_segments=grid_segments,
spectral_locus=spectral_locus,
spectral_locus_colour=spectral_locus_colour,
cmfs=cmfs,
**settings)
XYZ = RGB_to_XYZ(
RGB,
colourspace.whitepoint,
colourspace.whitepoint,
colourspace.RGB_to_XYZ_matrix)
points = XYZ_to_reference_colourspace(XYZ,
colourspace.whitepoint,
reference_colourspace)
axes = matplotlib.pyplot.gca()
axes.scatter(points[..., 0],
points[..., 1],
points[..., 2],
color=np.reshape(RGB, (-1, 3)),
s=points_size)
settings.update({'standalone': True})
settings.update(kwargs)
camera(**settings)
decorate(**settings)
return display(**settings)
def RGB_colourspace_volume_visual(colourspace='Rec. 709',
reference_colourspace='CIE xyY',
segments=16,
uniform_colour=None,
uniform_opacity=0.5,
wireframe=True,
wireframe_colour=None,
wireframe_opacity=1.0,
parent=None):
"""
Returns a :class:`vispy.scene.visuals.Node` class instance with one or two
:class:`colour_analysis.visuals.Box` class instance children representing
a *RGB* colourspace volume visual.
Parameters
----------
colourspace : unicode, optional
{'Rec. 709', 'ACES2065-1', 'ACEScc', 'ACEScg', 'ACESproxy',
'ALEXA Wide Gamut RGB', 'Adobe RGB 1998', 'Adobe Wide Gamut RGB',
'Apple RGB', 'Best RGB', 'Beta RGB', 'CIE RGB', 'Cinema Gamut',
'ColorMatch RGB', 'DCI-P3', 'DCI-P3+', 'DRAGONcolor', 'DRAGONcolor2',
'Don RGB 4', 'ECI RGB v2', 'Ekta Space PS 5', 'Max RGB', 'NTSC RGB',
'Pal/Secam RGB', 'ProPhoto RGB', 'REDcolor', 'REDcolor2', 'REDcolor3',
'REDcolor4', 'Rec. 2020', 'Russell RGB', 'S-Gamut', 'S-Gamut3',
'S-Gamut3.Cine', 'SMPTE-C RGB', 'V-Gamut', 'Xtreme RGB', 'aces',
'adobe1998', 'prophoto', 'sRGB'}
:class:`colour.RGB_Colourspace` class instance name defining the *RGB*
colourspace volume to draw.
segments : int, optional
Box segments.
uniform_colour : array_like, optional
Uniform mesh colour.
uniform_opacity : numeric, optional
Uniform mesh opacity.
vertex_colour : array_like, optional
Per vertex varying colour.
wireframe : bool, optional
Use wireframe display.
Uniform mesh opacity.
wireframe_colour : array_like, optional
Wireframe mesh colour.
wireframe_opacity : numeric, optional
Wireframe mesh opacity.
parent : Node, optional
Parent of the *RGB* colourspace volume visual in the `SceneGraph`.
"""
node = Node(parent)
colourspace = get_RGB_colourspace(colourspace)
RGB_cube_f = RGB_identity_cube(
width_segments=segments,
height_segments=segments,
depth_segments=segments,
uniform_colour=uniform_colour,
uniform_opacity=uniform_opacity,
vertex_colours=not uniform_colour,
parent=node)
vertices = RGB_cube_f.mesh_data.get_vertices()
XYZ = RGB_to_XYZ(
vertices,
colourspace.whitepoint,
colourspace.whitepoint,
colourspace.RGB_to_XYZ_matrix)
value = XYZ_to_reference_colourspace(XYZ,
colourspace.whitepoint,
reference_colourspace)
value[np.isnan(value)] = 0
RGB_cube_f.mesh_data.set_vertices(value)
if wireframe:
RGB_cube_w = RGB_identity_cube(
width_segments=segments,
height_segments=segments,
depth_segments=segments,
uniform_colour=wireframe_colour,
uniform_opacity=wireframe_opacity,
vertex_colours=not wireframe_colour,
wireframe=True,
parent=node)
RGB_cube_w.mesh_data.set_vertices(value)
return node
