colour.SpectralDistribution¶
-
class
colour.
SpectralDistribution
(data=None, domain=None, **kwargs)[source]¶ Defines the spectral distribution: the base object for spectral computations.
The spectral distribution 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 Signal, SpectralDistribution or array_like or dict_like, optional) – Data to be stored in the spectral distribution.
- domain (array_like, optional) – Values to initialise the
colour.SpectralDistribution.wavelength
attribute with. If bothdata
anddomain
arguments are defined, the latter will be used to initialise thecolour.SpectralDistribution.wavelength
attribute.
Other Parameters: - name (unicode, optional) – Spectral distribution name.
- interpolator (object, optional) – Interpolator class type to use as interpolating function.
- interpolator_args (dict_like, optional) – Arguments to use when instantiating the interpolating function.
- extrapolator (object, optional) – Extrapolator class type to use as extrapolating function.
- extrapolator_args (dict_like, optional) – Arguments to use when instantiating the extrapolating function.
- strict_name (unicode, optional) – Spectral distribution name for figures, default to
colour.SpectralDistribution.name
attribute value.
-
strict_name
¶
-
wavelengths
¶
-
values
¶
-
shape
¶
References
[CIET13805a], [CIET13805c], [CIET14804h]
Examples
Instantiating a spectral distribution with a uniformly spaced independent variable:
>>> from colour.utilities import numpy_print_options >>> data = { ... 500: 0.0651, ... 520: 0.0705, ... 540: 0.0772, ... 560: 0.0870, ... 580: 0.1128, ... 600: 0.1360 ... } >>> with numpy_print_options(suppress=True): ... SpectralDistribution(data) # doctest: +ELLIPSIS SpectralDistribution([[ 500. , 0.0651], [ 520. , 0.0705], [ 540. , 0.0772], [ 560. , 0.087 ], [ 580. , 0.1128], [ 600. , 0.136 ]], interpolator=SpragueInterpolator, interpolator_args={}, extrapolator=Extrapolator, extrapolator_args={...})
Instantiating a spectral distribution with a non-uniformly spaced independent variable:
>>> data[510] = 0.31416 >>> with numpy_print_options(suppress=True): ... SpectralDistribution(data) # doctest: +ELLIPSIS SpectralDistribution([[ 500. , 0.0651 ], [ 510. , 0.31416], [ 520. , 0.0705 ], [ 540. , 0.0772 ], [ 560. , 0.087 ], [ 580. , 0.1128 ], [ 600. , 0.136 ]], interpolator=CubicSplineInterpolator, interpolator_args={}, extrapolator=Extrapolator, extrapolator_args={...})
-
__init__
(data=None, domain=None, **kwargs)[source] Initialize self. See help(type(self)) for accurate signature.
Methods
__init__
([data, domain])Initialize self. align
(shape[, interpolator, …])Aligns the spectral 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. domain_distance
(a)Returns the euclidean distance between given array and independent domain \(x\) closest element. extrapolate
(shape[, extrapolator, …])Extrapolates the spectral distribution 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 spectral distribution in-place according to CIE 167:2005 recommendation or given interpolation arguments. is_uniform
()Returns if independent domain \(x\) variable is uniform. normalise
([factor])Normalises the spectral distribution using given normalization factor. signal_unpack_data
([data, domain, dtype])Unpack given data for continuous signal instantiation. to_series
()Converts the continuous signal to a Pandas Series
class instance.trim
(shape)Trims the spectral distribution wavelengths to given spectral shape. trim_wavelengths
(shape)zeros
()Attributes
data
domain
Getter and setter property for the continuous signal independent domain \(x\) variable. dtype
Getter and setter property for the continuous signal dtype. extrapolator
Getter and setter property for the continuous signal extrapolator type. extrapolator_args
Getter and setter property for the continuous signal extrapolator instantiation time arguments. function
Getter and setter property for the continuous signal callable. interpolator
Getter and setter property for the continuous signal interpolator type. interpolator_args
Getter and setter property for the continuous signal interpolator instantiation time arguments. items
name
Getter and setter property for the abstract continuous function name. range
Getter and setter property for the continuous signal corresponding range \(y\) variable. shape
Getter and setter property for the spectral distribution shape. strict_name
Getter and setter property for the spectral distribution strict name. title
values
Getter and setter property for the spectral distribution values. wavelengths
Getter and setter property for the spectral distribution wavelengths \(\lambda_n\).