colour.characterisation.RGB_DisplayPrimaries

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

Implements support for a RGB display (such as a CRT or LCD) primaries multi-spectral power distributions.

Parameters:
  • data (Series or Dataframe or Signal or MultiSignal or MultiSpectralPowerDistribution or array_like or dict_like, optional) – Data to be stored in the multi-spectral power distribution.
  • domain (array_like, optional) – Values to initialise the multiple colour.SpectralPowerDistribution 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.SpectralPowerDistribution class instances.
Other Parameters:
 
  • name (unicode, optional) – Multi-spectral power distribution name.
  • interpolator (object, optional) – Interpolator class type to use as interpolating function for the colour.SpectralPowerDistribution class instances.
  • interpolator_args (dict_like, optional) – Arguments to use when instantiating the interpolating function of the colour.SpectralPowerDistribution class instances.
  • extrapolator (object, optional) – Extrapolator class type to use as extrapolating function for the colour.SpectralPowerDistribution class instances.
  • extrapolator_args (dict_like, optional) – Arguments to use when instantiating the extrapolating function of the colour.SpectralPowerDistribution class instances.
  • strict_labels (array_like, optional) – Multi-spectral power distribution labels for figures, default to colour.characterisation.RGB_DisplayPrimaries.labels attribute value.
__init__(data=None, domain=None, labels=None, **kwargs)[source]

Methods

__init__([data, domain, labels])
align(shape[, interpolator, …]) Aligns the multi-spectral power distribution 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, must be reimplemented by sub-classes.
domain_distance(a) Returns the euclidean distance between given array and independent domain \(x\) closest element.
extrapolate(shape[, extrapolator, …]) Extrapolates the multi-spectral power distribution in-place accordingly 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 power distribution in-place accordingly to CIE 167:2005 recommendation or given interpolation arguments.
is_uniform() Returns if independent domain \(x\) variable is uniform.
multi_signal_unpack_data([data, domain, …]) Unpack given data for multi-continuous signal instantiation.
normalise([factor]) Normalises the multi-spectral power distribution with given normalization factor.
to_dataframe() Converts the continuous signal to a Pandas DataFrame class instance.
trim(shape) Trims the multi-spectral power distribution wavelengths to given shape.
trim_wavelengths(shape)
zeros()