colour.NullInterpolator¶

class colour.NullInterpolator(x, y, absolute_tolerance=1e-06, relative_tolerance=1e-06, default=nan, dtype=<class 'numpy.float64'>)[source]¶

Bases: object

Performs 1-D function null interpolation, i.e. a call within given tolerances will return existing \(y\) variable values and default if outside tolerances.

Parameters

x (ndarray) – Independent \(x\) variable values corresponding with \(y\) variable.
y (ndarray) – Dependent and already known \(y\) variable values to interpolate.
absolute_tolerance (numeric, optional) – Absolute tolerance.
relative_tolerance (numeric, optional) – Relative tolerance.
default (numeric, optional) – Default value for interpolation outside tolerances.
dtype (type) – Data type used for internal conversions.

x¶

y¶

relative_tolerance¶

absolute_tolerance¶

default¶

__call__()[source]¶

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...

property absolute_tolerance

Getter and setter property for the absolute tolerance.

Parameters: value (numeric) – Value to set the absolute tolerance with.
Returns: Absolute tolerance.
Return type: numeric

property default

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

Parameters: value (numeric) – Value to set the default value with.
Returns: Default value.
Return type: numeric

property relative_tolerance

Getter and setter property for the relative tolerance.

Parameters: value (numeric) – Value to set the relative tolerance with.
Returns: Relative tolerance.
Return type: numeric

property x

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

Parameters: value (array_like) – Value to set the independent \(x\) variable with.
Returns: Independent \(x\) variable.
Return type: array_like

property y

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

Parameters: value (array_like) – Value to set the dependent and already known \(y\) variable with.
Returns: Dependent and already known \(y\) variable.
Return type: array_like