colour.MultiSpectralDistributions

class colour.MultiSpectralDistributions(data=None, domain=None, labels=None, **kwargs)[source]

Defines the multi-spectral distributions: the base object for multi spectral computations. It is used to model colour matching functions, display primaries, camera sensitivities, etc…

The multi-spectral distributions will be initialised according to CIE 15:2004 recommendation: the method developed by Sprague (1880) will be used for interpolating functions having a uniformly spaced independent variable and the Cubic Spline method for non-uniformly spaced independent variable. Extrapolation is performed according to CIE 167:2005 recommendation.

Parameters:
  • data (Series or Dataframe or Signal or MultiSignals or MultiSpectralDistributions or array_like or dict_like, optional) – Data to be stored in the multi-spectral distributions.
  • domain (array_like, optional) – Values to initialise the multiple colour.SpectralDistribution class instances colour.continuous.Signal.wavelengths attribute with. If both data and domain arguments are defined, the latter will be used to initialise the colour.continuous.Signal.wavelengths attribute.
  • labels (array_like, optional) – Names to use for the colour.SpectralDistribution class instances.
Other Parameters:
 
  • name (unicode, optional) – Multi-spectral distributions name.
  • interpolator (object, optional) – Interpolator class type to use as interpolating function for the colour.SpectralDistribution class instances.
  • interpolator_args (dict_like, optional) – Arguments to use when instantiating the interpolating function of the colour.SpectralDistribution class instances.
  • extrapolator (object, optional) – Extrapolator class type to use as extrapolating function for the colour.SpectralDistribution class instances.
  • extrapolator_args (dict_like, optional) – Arguments to use when instantiating the extrapolating function of the colour.SpectralDistribution class instances.
  • strict_labels (array_like, optional) – Multi-spectral distributions labels for figures, default to colour.MultiSpectralDistributions.labels attribute value.
strict_name
strict_labels
wavelengths
values
shape
extrapolate()[source]
interpolate()[source]
align()[source]
trim()[source]
normalise()[source]
to_sds()[source]

References

[CIETC1-382005e], [CIETC1-382005g], [CIETC1-482004l]

Examples

Instantiating the multi-spectral distributions with a uniformly spaced independent variable:

>>> from colour.utilities import numpy_print_options
>>> data = {
...     500: (0.004900, 0.323000, 0.272000),
...     510: (0.009300, 0.503000, 0.158200),
...     520: (0.063270, 0.710000, 0.078250),
...     530: (0.165500, 0.862000, 0.042160),
...     540: (0.290400, 0.954000, 0.020300),
...     550: (0.433450, 0.994950, 0.008750),
...     560: (0.594500, 0.995000, 0.003900)
... }
>>> labels = ('x_bar', 'y_bar', 'z_bar')
>>> with numpy_print_options(suppress=True):
...     MultiSpectralDistributions(data, labels=labels)
... # doctest: +ELLIPSIS
MultiSpectral...([[ 500.     ,    0.0049 ,    0.323  ,    0.272  ],
             ...  [ 510.     ,    0.0093 ,    0.503  ,    0.1582 ],
             ...  [ 520.     ,    0.06327,    0.71   ,    0.07825],
             ...  [ 530.     ,    0.1655 ,    0.862  ,    0.04216],
             ...  [ 540.     ,    0.2904 ,    0.954  ,    0.0203 ],
             ...  [ 550.     ,    0.43345,    0.99495,    0.00875],
             ...  [ 560.     ,    0.5945 ,    0.995  ,    0.0039 ]],
             ... labels=[...'x_bar', ...'y_bar', ...'z_bar'],
             ... interpolator=SpragueInterpolator,
             ... interpolator_args={},
             ... extrapolator=Extrapolator,
             ... extrapolator_args={...})

Instantiating a spectral distribution with a non-uniformly spaced independent variable:

>>> data[511] = (0.00314, 0.31416, 0.03142)
>>> with numpy_print_options(suppress=True):
...     MultiSpectralDistributions(data, labels=labels)
... # doctest: +ELLIPSIS
MultiSpectral...([[ 500.     ,    0.0049 ,    0.323  ,    0.272  ],
             ...  [ 510.     ,    0.0093 ,    0.503  ,    0.1582 ],
             ...  [ 511.     ,    0.00314,    0.31416,    0.03142],
             ...  [ 520.     ,    0.06327,    0.71   ,    0.07825],
             ...  [ 530.     ,    0.1655 ,    0.862  ,    0.04216],
             ...  [ 540.     ,    0.2904 ,    0.954  ,    0.0203 ],
             ...  [ 550.     ,    0.43345,    0.99495,    0.00875],
             ...  [ 560.     ,    0.5945 ,    0.995  ,    0.0039 ]],
             ... labels=[...'x_bar', ...'y_bar', ...'z_bar'],
             ... interpolator=CubicSplineInterpolator,
             ... interpolator_args={},
             ... extrapolator=Extrapolator,
             ... extrapolator_args={...})
__init__(data=None, domain=None, labels=None, **kwargs)[source]

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__([data, domain, labels]) Initialize self.
align(shape[, interpolator, …]) Aligns the multi-spectral distributions in-place to given spectral shape: Interpolates first then extrapolates to fit the given range.
arithmetical_operation(a, operation[, in_place]) Performs given arithmetical operation with \(a\) operand, the operation can be either performed on a copy or in-place.
clone()
copy() Returns a copy of the sub-class instance.
domain_distance(a) Returns the euclidean distance between given array and independent domain \(x\) closest element.
extrapolate(shape[, extrapolator, …]) Extrapolates the multi-spectral distributions in-place according to CIE 15:2004 and CIE 167:2005 recommendations or given extrapolation arguments.
fill_nan([method, default]) Fill NaNs in independent domain \(x\) variable and corresponding range \(y\) variable using given method.
get()
interpolate(shape[, interpolator, …]) Interpolates the multi-spectral distributions in-place according to CIE 167:2005 recommendation or given interpolation arguments.
is_uniform() Returns if independent domain \(x\) variable is uniform.
multi_signals_unpack_data([data, domain, …]) Unpack given data for multi-continuous signals instantiation.
normalise([factor]) Normalises the multi-spectral distributions with given normalization factor.
to_dataframe() Converts the continuous signal to a Pandas DataFrame class instance.
to_sds() Converts the multi-spectral distributions to a list of spectral distributions and update their name and strict name using the labels and strict labels.
trim(shape) Trims the multi-spectral distributions wavelengths to given shape.
trim_wavelengths(shape)
zeros()

Attributes

data
domain Getter and setter property for the colour.continuous.Signal sub-class instances independent domain \(x\) variable.
dtype Getter and setter property for the continuous signal dtype.
extrapolator Getter and setter property for the colour.continuous.Signal sub-class instances extrapolator type.
extrapolator_args Getter and setter property for the colour.continuous.Signal sub-class instances extrapolator instantiation time arguments.
function Getter and setter property for the colour.continuous.Signal sub-class instances callable.
interpolator Getter and setter property for the colour.continuous.Signal sub-class instances interpolator type.
interpolator_args Getter and setter property for the colour.continuous.Signal sub-class instances interpolator instantiation time arguments.
items
labels Getter and setter property for the colour.continuous.Signal sub-class instances name.
mapping
name Getter and setter property for the abstract continuous function name.
range Getter and setter property for the colour.continuous.Signal sub-class instances corresponding range \(y\) variable.
shape Getter and setter property for the multi-spectral distributions shape.
signal_type Getter and setter property for the colour.continuous.Signal sub-class instances type.
signals Getter and setter property for the colour.continuous.Signal sub-class instances.
strict_labels Getter and setter property for the multi-spectral distributions strict labels.
strict_name Getter and setter property for the multi-spectral distributions strict name.
title
values Getter and setter property for the multi-spectral distributions values.
wavelengths Getter and setter property for the multi-spectral distributions wavelengths \(\lambda_n\).
x
y
z