colour.SpragueInterpolator¶
-
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.
-
x
¶
-
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) 7.2185025...
Interpolating an array_like variable:
>>> f([0.25, 0.75]) array([ 6.7295161..., 7.8140625...])
-
__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.
Getter and setter property for the independent \(x\) variable.
Getter and setter property for the dependent and already known \(y\) variable.