colour.LinearInterpolator#

class colour.LinearInterpolator(x: ArrayLike, y: ArrayLike, dtype: Optional[Type[DTypeNumber]] = None)[source]#

Bases: object

Interpolate linearly a 1-D function.

Parameters
  • x (ArrayLike) – Independent \(x\) variable values corresponding with \(y\) variable.

  • y (ArrayLike) – Dependent and already known \(y\) variable values to interpolate.

  • dtype (Optional[Type[DTypeNumber]]) – Data type used for internal conversions.

Attributes

Methods

Notes

  • This class is a wrapper around numpy.interp definition.

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 = LinearInterpolator(x, y)
>>> f(0.5)  
7.64...

Interpolating an ArrayLike variable:

>>> f([0.25, 0.75])
array([ 6.7825,  8.5075])
__init__(x: ArrayLike, y: ArrayLike, dtype: Optional[Type[DTypeNumber]] = None)[source]#
Parameters
  • x (ArrayLike) –

  • y (ArrayLike) –

  • dtype (Optional[Type[DTypeNumber]]) –

property x: numpy.ndarray#

Getter and setter property for the independent \(x\) variable.

Parameters

value – Value to set the independent \(x\) variable with.

Returns

Independent \(x\) variable.

Return type

numpy.ndarray

property y: numpy.ndarray#

Getter and setter property for the dependent and already known \(y\) variable.

Parameters

value – Value to set the dependent and already known \(y\) variable with.

Returns

Dependent and already known \(y\) variable.

Return type

numpy.ndarray

__call__(x: FloatingOrArrayLike) FloatingOrNDArray[source]#

Evaluate the interpolating polynomial at given point(s).

Parameters

x (FloatingOrArrayLike) – Point(s) to evaluate the interpolant at.

Returns

Interpolated value(s).

Return type

numpy.floating or numpy.ndarray

__weakref__#

list of weak references to the object (if defined)