colour.NullInterpolator#

class colour.NullInterpolator(x: ArrayLike, y: ArrayLike, absolute_tolerance: float = TOLERANCE_ABSOLUTE_DEFAULT, relative_tolerance: float = TOLERANCE_RELATIVE_DEFAULT, default: float = np.nan, dtype: Type[DTypeReal] | None = None, *args: Any, **kwargs: Any)[source]#

Bases: object

Implement 1-D function null interpolation.

This interpolator returns existing \(y\) values when called with \(x\) values within specified tolerances, and returns a default value when outside tolerances. Unlike traditional interpolators that estimate intermediate values, this null interpolator only returns exact matches within tolerance bounds.

Parameters:

x (ArrayLike) – Independent \(x\) variable values corresponding with \(y\) variable.
y (ArrayLike) – Dependent and already known \(y\) variable values to interpolate.
absolute_tolerance (float) – Absolute tolerance.
relative_tolerance (float) – Relative tolerance.
default (float) – Default value for interpolation outside tolerances.
dtype (Type[DTypeReal] | None) – Data type used for internal conversions.
args (Any)
kwargs (Any)

Attributes

x
y
relative_tolerance
absolute_tolerance
default

Methods

__init__()
__call__()

Examples

>>> y = np.array([5.9200, 9.3700, 10.8135, 4.5100, 69.5900, 27.8007, 86.0500])
>>> x = np.arange(len(y))
>>> f = NullInterpolator(x, y)
>>> f(0.5)
nan
>>> f(1.0)
9.3699999...
>>> f = NullInterpolator(x, y, absolute_tolerance=0.01)
>>> f(1.01)
9.3699999...

__weakref__#: list of weak references to the object

__init__(x: ArrayLike, y: ArrayLike, absolute_tolerance: float = TOLERANCE_ABSOLUTE_DEFAULT, relative_tolerance: float = TOLERANCE_RELATIVE_DEFAULT, default: float = np.nan, dtype: Type[DTypeReal] | None = None, *args: Any, **kwargs: Any) → None[source]#

Parameters:

x (ArrayLike)
y (ArrayLike)
absolute_tolerance (float)
relative_tolerance (float)
default (float)
dtype (Type[DTypeReal] | None)
args (Any)
kwargs (Any)

Return type:

None

property x: NDArrayFloat#

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

Parameters:: value – Value to set the independent \(x\) variable with.
Returns:: Independent \(x\) variable.
Return type:: numpy.ndarray
Raises:: AssertionError – If the provided value has not exactly one dimension.

property y: NDArrayFloat#

Getter and setter 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
Raises:: AssertionError – If the provided value has not exactly one dimension.

property relative_tolerance: float#

Getter and setter property for the relative tolerance for numerical comparisons.

Parameters:: value – Value to set the relative tolerance for numerical comparisons with.
Returns:: Relative tolerance for numerical comparisons.
Return type:: float
Raises:: AssertionError – If the value is not numeric.

property absolute_tolerance: float#

Getter and setter property for the absolute tolerance for numerical comparisons.

Parameters:: value – Value to set the absolute tolerance for numerical comparisons with.
Returns:: Absolute tolerance for numerical comparisons.
Return type:: float
Raises:: AssertionError – If the value is not numeric.

property default: float#

Getter and setter property for the default value for call outside tolerances.

Parameters:: value – Value to set the default value with for call outside tolerances.
Returns:: Default value for call outside tolerances.
Return type:: float
Raises:: AssertionError – If the value is not numeric.

__call__(x: ArrayLike) → NDArrayFloat[source]#

Evaluate the interpolator at specified point(s).

Parameters:: x (ArrayLike) – Point(s) to evaluate the interpolant at.
Returns:: Interpolated value(s).
Return type:: numpy.ndarray

colour.NullInterpolator#

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