pySPFM._solvers.debiasing.innovation_to_block#
- innovation_to_block(hrf, y, estimates_matrix, is_ls)[source]#
Perform debiasing with the block model.
- Parameters:
hrf ((E x T) ndarray) – Matrix containing shifted HRFs in its columns. E stands for the number of volumes times the number of echo-times.
y ((T x S) ndarray) – Matrix with fMRI data provided to pySPFM.
estimates_matrix ((T x S) ndarray) – Matrix containing the non-zero coefficients selected as neuronal-related.
is_ls (bool) – Whether least squares is solved in favor of ridge regression.
- Returns:
beta ((T x S) ndarray) – Debiased activity-inducing signal obtained from estimated innovation signal.
s ((T x L) ndarray) – Transformation matrix used to integrate the innovation signal into activity-inducing signal. L stands for the number of steps to integrate.