colour.SpragueInterpolator¶
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class
colour.
SpragueInterpolator
(x, y, dtype=<class 'numpy.float64'>)[source]¶ Constructs a fifth-order polynomial that passes through \(y\) dependent variable.
Sprague (1880) method is recommended by the CIE for interpolating functions having a uniformly spaced independent variable.
Parameters: - x (array_like) – Independent \(x\) variable values corresponding with \(y\) variable.
- y (array_like) – Dependent and already known \(y\) variable values to interpolate.
- dtype (type) – Data type used for internal conversions.
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x
¶
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y
¶
Notes
- The minimum number \(k\) of data points required along the interpolation axis is \(k=6\).
References
Examples
Interpolating a single numeric variable:
>>> y = np.array([5.9200, 9.3700, 10.8135, 4.5100, ... 69.5900, 27.8007, 86.0500]) >>> x = np.arange(len(y)) >>> f = SpragueInterpolator(x, y) >>> f(0.5) # doctest: +ELLIPSIS 7.2185025...
Interpolating an array_like variable:
>>> f([0.25, 0.75]) # doctest: +ELLIPSIS array([ 6.7295161..., 7.8140625...])
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__init__
(x, y, dtype=<class 'numpy.float64'>)[source]¶ Initialize self. See help(type(self)) for accurate signature.
Methods
__init__
(x, y[, dtype])Initialize self. Attributes
SPRAGUE_C_COEFFICIENTS
Defines the coefficients used to generate extra points for boundaries interpolation. x
Getter and setter property for the independent \(x\) variable. y
Getter and setter property for the dependent and already known \(y\) variable.