pyeeg.solvers.create_laplacian_matrix

pyeeg.solvers.create_laplacian_matrix(n_lags: int, alpha: float = 1.0) → ndarray

Create a Laplacian matrix for smoothness constraints in quadratic regularization.

The Laplacian matrix approximates the second derivative, promoting smoothness in the TRF coefficients across time lags.

Parameters:

n_lagsint

Number of time lags (dimension of the TRF).

alphafloat, optional

Scaling factor for the Laplacian. Default is 1.0.

Returns:

Lndarray (n_lags, n_lags)

Laplacian matrix for smoothness regularization.

Notes:

The Laplacian matrix L has the form:

L[i, i-1] = -1 L[i, i] = 2 L[i, i+1] = -1

for interior points, with appropriate boundary conditions.