basischan

hypercoil.functional.tsconv.basischan(X: Tensor, basis_functions: List[Callable], include_const: bool = False) → Tensor

Create a channel basis for the data.

Given K basis functions, single-channel data are mapped across K channels, and the ith channel is constituted by evaluating the ith basis function over the input data.

Dimension:

Input : \((N, *, C, obs)\)

N denotes batch size, * denotes any number of intervening dimensions, C denotes number of data channels or variables, obs denotes number of observations per channel.

Output : \((N, K, *, C, obs)\)

K denotes the number of basis functions.

Parameters:

XTensor

Dataset to expand with basis functions. A new channel will be created containing the same dataset transformed using each basis function.

basis_functionslist(callable)

Functions to use to constitute the basis. Each function’s signature must map a single input to a single output of the same dimension. Use partial functions as appropriate to conform function signatures to this requirement.

include_constbool (default False)

Indicates that a constant or intercept term should be included.