xspline.indi

xspline.indi.indi_val(params, x)

Indicator value function,

Parameters:

• params (tuple[tuple[float, bool], tuple[float, bool]]) – Indicator parameters as a tuple consists of lower and upper bound of the interval corresponding to the indicator function.

• x (ndarray[Any, dtype[_ScalarType_co]]) – Data points.

Returns:

Indicator function value.

Return type:

describe

xspline.indi.indi_der(params, x, order)

Indicator derivative function. Since indicator function is a piecewise constant function, its derivative will always be zero.

Parameters:

• params (tuple[tuple[float, bool], tuple[float, bool]]) – Indicator parameters as a tuple consists of lower and upper bound of the interval corresponding to the indicator function.

• x (ndarray[Any, dtype[_ScalarType_co]]) – Data points.

• order (int) –

Returns:

Indicator deviative value.

Return type:

describe

xspline.indi.indi_int(params, x, order)

Indicator definite integral function. It is a piecewise polynomial function.

Parameters:

• params (tuple[tuple[float, bool], tuple[float, bool]]) – Indicator parameters as a tuple consists of lower and upper bound of the interval corresponding to the indicator function.

• x (ndarray[Any, dtype[_ScalarType_co]]) – Data points.

• order (int) –

Returns:

Indicator definite integral value.

Return type:

describe

class xspline.indi.Indi(params)

Bases: BundleXFunction

Indicator function.

Parameters:

params (tuple[tuple[float, bool], tuple[float, bool]]) – This is a tuple contains the lower and upper bounds of the indicator function. For each bound it consists of a number for the location of the bound and a boolean for the inclusion of the bound. For example, if we pass in ((0.0, True), (1.0, False)), this represents interval [0, 1).

Example

>>> indi = Indi(((0.0, True), (1.0, False)))
>>> indi([-1.0, 0.0, 1.0])
array([0., 1., 0.])
>>> indi([-1.0, 0.0, 1.0], order=1)
array([0., 0., 0.])
>>> indi([-1.0, 0.0, 1.0], order=-1)
array([0., 0., 1.])