def chromaticity_diagram_visual(samples=256,
cmfs='CIE 1931 2 Degree Standard Observer',
transformation='CIE 1931',
parent=None):
"""
Creates a chromaticity diagram visual based on
:class:`colour_analysis.visuals.Primitive` class.
Parameters
----------
samples : int, optional
Inner samples count used to construct the chromaticity diagram
triangulation.
cmfs : unicode, optional
Standard observer colour matching functions used for the chromaticity
diagram boundaries.
transformation : unicode, optional
**{'CIE 1931', 'CIE 1960 UCS', 'CIE 1976 UCS'}**,
Chromaticity diagram transformation.
parent : Node, optional
Parent of the chromaticity diagram in the `SceneGraph`.
Returns
-------
Primitive
Chromaticity diagram visual.
"""
cmfs = first_item(filter_cmfs(cmfs).values())
illuminant = DEFAULT_PLOTTING_ILLUMINANT
XYZ_to_ij = (
CHROMATICITY_DIAGRAM_TRANSFORMATIONS[transformation]['XYZ_to_ij'])
ij_to_XYZ = (
CHROMATICITY_DIAGRAM_TRANSFORMATIONS[transformation]['ij_to_XYZ'])
ij_c = XYZ_to_ij(cmfs.values, illuminant)
triangulation = Delaunay(ij_c, qhull_options='QJ')
samples = np.linspace(0, 1, samples)
ii, jj = np.meshgrid(samples, samples)
ij = tstack([ii, jj])
ij = np.vstack([ij_c, ij[triangulation.find_simplex(ij) > 0]])
ij_p = np.hstack([ij, np.full((ij.shape[0], 1), 0, DEFAULT_FLOAT_DTYPE)])
triangulation = Delaunay(ij, qhull_options='QJ')
RGB = normalise_maximum(
XYZ_to_sRGB(ij_to_XYZ(ij, illuminant), illuminant), axis=-1)
diagram = Primitive(
vertices=ij_p,
faces=triangulation.simplices,
vertex_colours=RGB,
parent=parent)
return diagram
def spectrum_to_rgb(
wavelength,
spectrum,
# cmfs=None,
illuminant='LED-B3',
Y=None,
):
"""
Calculate the rgb color given a wavelength and spectrum. Note spectrum should have spacing of 1, 5, 10 or 10 nm.
Parameters
----------
wavelength
spectrum
cmfs
illuminant
Returns
-------
"""
# if is_uniform(wavelength) and interval(wavelength)
XYZ = spectrum_to_XYZ(
wavelength=wavelength,
spectrum=spectrum,
# cmfs=cmfs,
illuminant=illuminant)
XYZ = XYZ / 100
if Y is not None:
xyY = XYZ_to_xyY(XYZ)
xyY[2] = Y
XYZ = xyY_to_XYZ(xyY)
# Convert to rgb. Note the illuminant doesn't matter here except for points
# where XYZ=0.
rgb = XYZ_to_sRGB(XYZ)
return rgb
def spectral_locus_visual(reference_colourspace='CIE xyY',
cmfs='CIE 1931 2 Degree Standard Observer',
width=2.0,
uniform_colour=None,
uniform_opacity=1.0,
method='gl',
parent=None):
"""
Returns a :class:`vispy.scene.visuals.Line` class instance representing
the spectral locus.
Parameters
----------
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.
cmfs : unicode, optional
Standard observer colour matching functions used to draw the spectral
locus.
width : numeric, optional
Line width.
uniform_colour : array_like, optional
Uniform symbol colour.
uniform_opacity : numeric, optional
Uniform symbol opacity.
method : unicode, optional
**{'gl', 'agg'}**,
Line drawing method.
parent : Node, optional
Parent of the spectral locus visual in the `SceneGraph`.
Returns
-------
Line
Spectral locus visual.
"""
cmfs = first_item(filter_cmfs(cmfs).values())
XYZ = cmfs.values
XYZ = np.vstack([XYZ, XYZ[0, ...]])
illuminant = DEFAULT_PLOTTING_ILLUMINANT
points = common_colourspace_model_axis_reorder(
XYZ_to_colourspace_model(XYZ, illuminant, reference_colourspace),
reference_colourspace)
points[np.isnan(points)] = 0
if uniform_colour is None:
RGB = normalise_maximum(XYZ_to_sRGB(XYZ, illuminant), axis=-1)
RGB = np.hstack([
RGB,
np.full((RGB.shape[0], 1), uniform_opacity, DEFAULT_FLOAT_DTYPE)
])
else:
RGB = ColorArray(uniform_colour, alpha=uniform_opacity).rgba
line = Line(points,
np.clip(RGB, 0, 1),
width=width,
method=method,
parent=parent)
return line