def single_spd_plot(spd, cmfs='CIE 1931 2 Degree Standard Observer', **kwargs):
"""
Plots given spectral power distribution.
Parameters
----------
spd : SpectralPowerDistribution, optional
Spectral power distribution to plot.
cmfs : unicode
Standard observer colour matching functions used for spectrum creation.
\*\*kwargs : \*\*
Keywords arguments.
Returns
-------
bool
Definition success.
Examples
--------
>>> from colour import SpectralPowerDistribution
>>> data = {400: 0.0641, 420: 0.0645, 440: 0.0562}
>>> spd = SpectralPowerDistribution('Custom', data)
>>> single_spd_plot(spd) # doctest: +SKIP
True
"""
cmfs, name = get_cmfs(cmfs), cmfs
shape = cmfs.shape
spd = spd.clone().interpolate(shape)
wavelengths = shape.range()
colours = []
y1 = []
for wavelength, value in spd:
XYZ = wavelength_to_XYZ(wavelength, cmfs)
colours.append(XYZ_to_sRGB(XYZ))
y1.append(value)
colours = normalise(colours)
settings = {
'title': '"{0}" - {1}'.format(spd.name, cmfs.name),
'x_label': u'Wavelength λ (nm)',
'y_label': 'Spectral Power Distribution',
'x_tighten': True,
'x_ticker': True,
'y_ticker': True
}
settings.update(kwargs)
return colour_parameters_plot([
colour_parameter(x=x[0], y1=x[1], RGB=x[2])
for x in tuple(zip(wavelengths, y1, colours))
], **settings)
def single_spd_plot(spd, cmfs='CIE 1931 2 Degree Standard Observer', **kwargs):
"""
Plots given spectral power distribution.
Parameters
----------
spd : SpectralPowerDistribution
Spectral power distribution to plot.
cmfs : unicode
Standard observer colour matching functions used for spectrum creation.
\*\*kwargs : \*\*
Keywords arguments.
Returns
-------
bool
Definition success.
Examples
--------
>>> from colour import SpectralPowerDistribution
>>> data = {400: 0.0641, 420: 0.0645, 440: 0.0562}
>>> spd = SpectralPowerDistribution('Custom', data)
>>> single_spd_plot(spd) # doctest: +SKIP
True
"""
cmfs = get_cmfs(cmfs)
shape = cmfs.shape
spd = spd.clone().interpolate(shape, 'Linear')
wavelengths = spd.wavelengths
colours = []
y1 = []
for wavelength, value in spd:
XYZ = wavelength_to_XYZ(wavelength, cmfs)
colours.append(XYZ_to_sRGB(XYZ))
y1.append(value)
colours = normalise(colours)
settings = {
'title': '{0} - {1}'.format(spd.title, cmfs.title),
'x_label': 'Wavelength $\\lambda$ (nm)',
'y_label': 'Spectral Power Distribution',
'x_tighten': True,
'x_ticker': True,
'y_ticker': True}
settings.update(kwargs)
return colour_parameters_plot(
[colour_parameter(x=x[0], y1=x[1], RGB=x[2])
for x in tuple(zip(wavelengths, y1, colours))],
**settings)
def blackbody_colours_plot(shape=SpectralShape(150, 12500, 50),
cmfs='CIE 1931 2 Degree Standard Observer',
**kwargs):
"""
Plots blackbody colours.
Parameters
----------
shape : SpectralShape, optional
Spectral shape to use as plot boundaries.
cmfs : unicode, optional
Standard observer colour matching functions.
\*\*kwargs : \*\*
Keywords arguments.
Returns
-------
bool
Definition success.
Examples
--------
>>> blackbody_colours_plot() # doctest: +SKIP
True
"""
cmfs, name = get_cmfs(cmfs), cmfs
colours = []
temperatures = []
for temperature in shape:
spd = blackbody_spd(temperature, cmfs.shape)
XYZ = spectral_to_XYZ(spd, cmfs)
RGB = normalise(XYZ_to_sRGB(XYZ / 100))
colours.append(RGB)
temperatures.append(temperature)
settings = {
'title': 'Blackbody Colours',
'x_label': 'Temperature K',
'y_label': '',
'x_tighten': True,
'x_ticker': True,
'y_ticker': False
}
settings.update(kwargs)
return colour_parameters_plot([
colour_parameter(x=x[0], RGB=x[1])
for x in tuple(zip(temperatures, colours))
], **settings)
def blackbody_colours_plot(shape=SpectralShape(150, 12500, 50),
cmfs='CIE 1931 2 Degree Standard Observer',
**kwargs):
"""
Plots blackbody colours.
Parameters
----------
shape : SpectralShape, optional
Spectral shape to use as plot boundaries.
cmfs : unicode, optional
Standard observer colour matching functions.
\*\*kwargs : \*\*
Keywords arguments.
Returns
-------
bool
Definition success.
Examples
--------
>>> blackbody_colours_plot() # doctest: +SKIP
True
"""
cmfs = get_cmfs(cmfs)
colours = []
temperatures = []
for temperature in shape:
spd = blackbody_spd(temperature, cmfs.shape)
XYZ = spectral_to_XYZ(spd, cmfs)
RGB = normalise(XYZ_to_sRGB(XYZ / 100))
colours.append(RGB)
temperatures.append(temperature)
settings = {
'title': 'Blackbody Colours',
'x_label': 'Temperature K',
'y_label': '',
'x_tighten': True,
'x_ticker': True,
'y_ticker': False}
settings.update(kwargs)
return colour_parameters_plot([colour_parameter(x=x[0], RGB=x[1])
for x in tuple(zip(temperatures, colours))],
**settings)
def visible_spectrum_plot(cmfs='CIE 1931 2 Degree Standard Observer',
**kwargs):
"""
Plots the visible colours spectrum using given standard observer *CIE XYZ*
colour matching functions.
Parameters
----------
cmfs : unicode, optional
Standard observer colour matching functions used for spectrum creation.
\*\*kwargs : \*\*
Keywords arguments.
Returns
-------
bool
Definition success.
Examples
--------
>>> visible_spectrum_plot() # doctest: +SKIP
True
"""
cmfs, name = get_cmfs(cmfs), cmfs
cmfs = cmfs.clone().align(DEFAULT_SPECTRAL_SHAPE)
wavelengths = cmfs.shape.range()
colours = []
for i in wavelengths:
XYZ = wavelength_to_XYZ(i, cmfs)
colours.append(XYZ_to_sRGB(XYZ))
colours = np.array([np.ravel(x) for x in colours])
colours *= 1 / np.max(colours)
colours = np.clip(colours, 0, 1)
settings = {
'title': 'The Visible Spectrum - {0}'.format(name),
'x_label': u'Wavelength λ (nm)',
'x_tighten': True
}
settings.update(kwargs)
return colour_parameters_plot([
colour_parameter(x=x[0], RGB=x[1])
for x in tuple(zip(wavelengths, colours))
], **settings)
def visible_spectrum_plot(cmfs='CIE 1931 2 Degree Standard Observer',
**kwargs):
"""
Plots the visible colours spectrum using given standard observer *CIE XYZ*
colour matching functions.
Parameters
----------
cmfs : unicode, optional
Standard observer colour matching functions used for spectrum creation.
\*\*kwargs : \*\*
Keywords arguments.
Returns
-------
bool
Definition success.
Examples
--------
>>> visible_spectrum_plot() # doctest: +SKIP
True
"""
cmfs = get_cmfs(cmfs)
cmfs = cmfs.clone().align(DEFAULT_SPECTRAL_SHAPE)
wavelengths = cmfs.shape.range()
colours = []
for i in wavelengths:
XYZ = wavelength_to_XYZ(i, cmfs)
colours.append(XYZ_to_sRGB(XYZ))
colours = np.array([np.ravel(x) for x in colours])
colours *= 1 / np.max(colours)
colours = np.clip(colours, 0, 1)
settings = {
'title': 'The Visible Spectrum - {0}'.format(cmfs.title),
'x_label': 'Wavelength $\\lambda$ (nm)',
'x_tighten': True}
settings.update(kwargs)
return colour_parameters_plot([colour_parameter(x=x[0], RGB=x[1])
for x in tuple(zip(wavelengths, colours))],
**settings)
def the_blue_sky_plot(
cmfs='CIE 1931 2 Degree Standard Observer',
**kwargs):
"""
Plots the blue sky.
Parameters
----------
cmfs : unicode, optional
Standard observer colour matching functions.
\*\*kwargs : \*\*
Keywords arguments.
Returns
-------
bool
Definition success.
Examples
--------
>>> the_blue_sky_plot() # doctest: +SKIP
True
"""
canvas(**kwargs)
cmfs, name = get_cmfs(cmfs), cmfs
ASTM_G_173_spd = ASTM_G_173_ETR.clone()
rayleigh_spd = rayleigh_scattering_spd()
ASTM_G_173_spd.align(rayleigh_spd.shape)
spd = rayleigh_spd * ASTM_G_173_spd
matplotlib.pyplot.subplots_adjust(hspace=0.4)
matplotlib.pyplot.figure(1)
matplotlib.pyplot.subplot(211)
settings = {
'title': 'The Blue Sky - Synthetic Spectral Power Distribution',
'y_label': u'W / m-2 / nm-1',
'standalone': False}
settings.update(kwargs)
single_spd_plot(spd, name, **settings)
matplotlib.pyplot.subplot(212)
settings = {
'title': 'The Blue Sky - Colour',
'x_label': ('The sky is blue because molecules in the atmosphere '
'scatter shorter wavelengths more than longer ones.\n'
'The synthetic spectral power distribution is computed as '
'follows: '
'(ASTM G-173 ETR * Standard Air Rayleigh Scattering).'),
'y_label': '',
'aspect': None,
'standalone': False}
blue_sky_color = XYZ_to_sRGB(spectral_to_XYZ(spd))
single_colour_plot(colour_parameter('', normalise(blue_sky_color)),
**settings)
settings = {'standalone': True}
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
def blackbody_spectral_radiance_plot(
temperature=3500,
cmfs='CIE 1931 2 Degree Standard Observer',
blackbody='VY Canis Major',
**kwargs):
"""
Plots given blackbody spectral radiance.
Parameters
----------
temperature : numeric, optional
Blackbody temperature.
cmfs : unicode, optional
Standard observer colour matching functions.
blackbody : unicode, optional
Blackbody name.
\*\*kwargs : \*\*
Keywords arguments.
Returns
-------
bool
Definition success.
Examples
--------
>>> blackbody_spectral_radiance_plot() # doctest: +SKIP
True
"""
canvas(**kwargs)
cmfs = get_cmfs(cmfs)
matplotlib.pyplot.subplots_adjust(hspace=0.4)
spd = blackbody_spd(temperature, cmfs.shape)
matplotlib.pyplot.figure(1)
matplotlib.pyplot.subplot(211)
settings = {
'title': '{0} - Spectral Radiance'.format(blackbody),
'y_label': 'W / (sr m$^2$) / m',
'standalone': False}
settings.update(kwargs)
single_spd_plot(spd, cmfs.name, **settings)
XYZ = spectral_to_XYZ(spd, cmfs)
RGB = normalise(XYZ_to_sRGB(XYZ / 100))
matplotlib.pyplot.subplot(212)
settings = {'title': '{0} - Colour'.format(blackbody),
'x_label': '{0}K'.format(temperature),
'y_label': '',
'aspect': None,
'standalone': False}
single_colour_plot(colour_parameter(name='', RGB=RGB), **settings)
settings = {
'standalone': True}
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
def colour_checker_plot(colour_checker='ColorChecker 2005', **kwargs):
"""
Plots given colour checker.
Parameters
----------
colour_checker : unicode, optional
Color checker name.
\*\*kwargs : \*\*
Keywords arguments.
Returns
-------
bool
Definition success.
Raises
------
KeyError
If the given colour rendition chart is not found in the factory colour
rendition charts.
Examples
--------
>>> colour_checker_plot() # doctest: +SKIP
True
"""
canvas(**kwargs)
colour_checker, name = COLOURCHECKERS.get(colour_checker), colour_checker
if colour_checker is None:
raise KeyError(
('Colour checker "{0}" not found in '
'factory colour checkers: "{1}".').format(
name, sorted(COLOURCHECKERS.keys())))
_, data, illuminant = colour_checker
colour_parameters = []
for index, label, x, y, Y in data:
XYZ = xyY_to_XYZ((x, y, Y))
RGB = XYZ_to_sRGB(XYZ, illuminant)
colour_parameters.append(
colour_parameter(label.title(),
np.clip(np.ravel(RGB), 0, 1)))
background_colour = '0.1'
matplotlib.pyplot.gca().patch.set_facecolor(background_colour)
width = height = 1.0
spacing = 0.25
across = 6
settings = {
'standalone': False,
'width': width,
'height': height,
'spacing': spacing,
'across': across,
'text_size': 8,
'margins': [-0.125, 0.125, -0.5, 0.125]}
settings.update(kwargs)
multi_colour_plot(colour_parameters, **settings)
text_x = width * (across / 2) + (across * (spacing / 2)) - spacing / 2
text_y = -(len(colour_parameters) / across + spacing / 2)
pylab.text(text_x,
text_y,
'{0} - {1} - Colour Rendition Chart'.format(
name, RGB_COLOURSPACES.get('sRGB').name),
color='0.95',
clip_on=True,
ha='center')
settings.update({
'title': name,
'facecolor': background_colour,
'edgecolor': None,
'standalone': True})
boundaries(**settings)
decorate(**settings)
return display(**settings)
def the_blue_sky_plot(cmfs='CIE 1931 2 Degree Standard Observer', **kwargs):
"""
Plots the blue sky.
Parameters
----------
cmfs : unicode, optional
Standard observer colour matching functions.
\*\*kwargs : \*\*
Keywords arguments.
Returns
-------
bool
Definition success.
Examples
--------
>>> the_blue_sky_plot() # doctest: +SKIP
True
"""
cmfs, name = get_cmfs(cmfs), cmfs
ASTM_G_173_spd = ASTM_G_173_ETR.clone()
rayleigh_spd = rayleigh_scattering_spd()
ASTM_G_173_spd.align(rayleigh_spd.shape)
spd = rayleigh_spd * ASTM_G_173_spd
matplotlib.pyplot.subplots_adjust(hspace=0.4)
matplotlib.pyplot.figure(1)
matplotlib.pyplot.subplot(211)
settings = {
'title': 'The Blue Sky - Synthetic Spectral Power Distribution',
'y_label': u'W / m-2 / nm-1',
'standalone': False
}
settings.update(kwargs)
single_spd_plot(spd, name, **settings)
matplotlib.pyplot.subplot(212)
settings = {
'title':
'The Blue Sky - Colour',
'x_label': ('The sky is blue because molecules in the atmosphere '
'scatter shorter wavelengths more than longer ones.\n'
'The synthetic spectral power distribution is computed as '
'follows: '
'(ASTM G-173 ETR * Standard Air Rayleigh Scattering).'),
'y_label':
'',
'aspect':
None,
'standalone':
False
}
blue_sky_color = XYZ_to_sRGB(spectral_to_XYZ(spd))
single_colour_plot(colour_parameter('', normalise(blue_sky_color)),
**settings)
settings = {'standalone': True}
settings.update(kwargs)
bounding_box(**settings)
aspect(**settings)
return display(**settings)
def blackbody_spectral_radiance_plot(
temperature=3500,
cmfs='CIE 1931 2 Degree Standard Observer',
blackbody='VY Canis Major',
**kwargs):
"""
Plots given blackbody spectral radiance.
Parameters
----------
temperature : numeric, optional
Blackbody temperature.
cmfs : unicode, optional
Standard observer colour matching functions.
blackbody : unicode, optional
Blackbody name.
\*\*kwargs : \*\*
Keywords arguments.
Returns
-------
bool
Definition success.
Examples
--------
>>> blackbody_spectral_radiance_plot() # doctest: +SKIP
True
"""
cmfs, name = get_cmfs(cmfs), cmfs
matplotlib.pyplot.subplots_adjust(hspace=0.4)
spd = blackbody_spd(temperature, cmfs.shape)
matplotlib.pyplot.figure(1)
matplotlib.pyplot.subplot(211)
settings = {
'title': '{0} - Spectral Radiance'.format(blackbody),
'y_label': u'W / (sr m²) / m',
'standalone': False
}
settings.update(kwargs)
single_spd_plot(spd, name, **settings)
XYZ = spectral_to_XYZ(spd, cmfs)
RGB = normalise(XYZ_to_sRGB(XYZ / 100))
matplotlib.pyplot.subplot(212)
settings = {
'title': '{0} - Colour'.format(blackbody),
'x_label': '{0}K'.format(temperature),
'y_label': '',
'aspect': None,
'standalone': False
}
single_colour_plot(colour_parameter(name='', RGB=RGB), **settings)
settings = {'standalone': True}
settings.update(kwargs)
bounding_box(**settings)
aspect(**settings)
return display(**settings)
def colour_checker_plot(colour_checker='ColorChecker 2005', **kwargs):
"""
Plots given colour checker.
Parameters
----------
colour_checker : unicode, optional
Color checker name.
\*\*kwargs : \*\*
Keywords arguments.
Returns
-------
bool
Definition success.
Raises
------
KeyError
If the given colour rendition chart is not found in the factory colour
rendition charts.
Examples
--------
>>> colour_checker_plot() # doctest: +SKIP
True
"""
colour_checker, name = COLOURCHECKERS.get(colour_checker), colour_checker
if colour_checker is None:
raise KeyError(('Colour checker "{0}" not found in '
'factory colour checkers: "{1}".').format(
name, sorted(COLOURCHECKERS.keys())))
_, data, illuminant = colour_checker
colour_parameters = []
for index, label, x, y, Y in data:
XYZ = xyY_to_XYZ((x, y, Y))
RGB = XYZ_to_sRGB(XYZ, illuminant)
colour_parameters.append(
colour_parameter(label.title(), np.clip(np.ravel(RGB), 0, 1)))
background_colour = '0.1'
matplotlib.pyplot.gca().patch.set_facecolor(background_colour)
width = height = 1.0
spacing = 0.25
across = 6
settings = {
'standalone': False,
'width': width,
'height': height,
'spacing': spacing,
'across': across,
'text_size': 8,
'margins': [-0.125, 0.125, -0.5, 0.125]
}
settings.update(kwargs)
multi_colour_plot(colour_parameters, **settings)
text_x = width * (across / 2) + (across * (spacing / 2)) - spacing / 2
text_y = -(len(colour_parameters) / across + spacing / 2)
pylab.text(text_x,
text_y,
'{0} - {1} - Colour Rendition Chart'.format(
name,
RGB_COLOURSPACES.get('sRGB').name),
color='0.95',
clip_on=True,
ha='center')
settings.update({
'title': name,
'facecolor': background_colour,
'edgecolor': None,
'standalone': True
})
bounding_box(**settings)
aspect(**settings)
return display(**settings)
