xspline.bspl

xspline.bspl.cache_bspl(function)

Cache implementation for bspline basis functions, to avoid repetitively evaluate functions.

Parameters:

function (Callable[[tuple, ndarray[Any, dtype[_ScalarType_co]]], ndarray[Any, dtype[_ScalarType_co]]] | Callable[[tuple, ndarray[Any, dtype[_ScalarType_co]], int], ndarray[Any, dtype[_ScalarType_co]]]) – Raw value, derivative and definite integral functions.

Returns:

Cached version of the raw functions.

Return type:

describe

xspline.bspl.bspl_val(*args, **kwargs)

Return type:

ndarray[Any, dtype[_ScalarType_co]]

xspline.bspl.bspl_der(*args, **kwargs)

Return type:

ndarray[Any, dtype[_ScalarType_co]]

xspline.bspl.bspl_int(*args, **kwargs)

Return type:

ndarray[Any, dtype[_ScalarType_co]]

xspline.bspl.clear_bspl_cache()

Clear all cache of the value, derivative and definite integral for bspline function.

Return type:

None

class xspline.bspl.Bspl(params)

Bases: BundleXFunction

Basis spline function.

Parameters:

params (tuple[tuple[float, ...], int, int]) – This is a tuple that contains knots, degree and index of the basis function.

Example

>>> bspl = Bspl(((0.0, 1.0), 1, 0)) # knots=(0.0, 1.0), degree=2, index=0
>>> bspl([0.0, 1.0])
array([0., 1.])
>>> bspl([0.0, 1.0], order=1)
array([1., 1.])
>>> bspl([0.0, 1.0], order=2)
array([0., 0.])
>>> bspl([0.0, 1.0], order=-1)
array([0. , 0.5])

xspline.bspl.get_bspl_funs(knots, degree)

Create the bspline basis functions give knots and degree.

Parameters:

• knots (tuple[float, ...]) – Bspline knots.

• degree (int) – Bspline degree.

Returns:

A full set of bspline functions.

Return type:

describe