pflm.fpca.utils.get_eigenvalue_fit#
- get_eigenvalue_fit(raw_cov: ndarray, obs_grid: ndarray, fpca_phi_obs: ndarray, num_pcs: int)[source][source]#
Fit eigenvalues by projecting raw covariance onto the FPCA subspace.
- Parameters:
- raw_covnp.ndarray of shape (M, 5)
Raw covariance entries (sid, t1, t2, w, cov).
- obs_gridnp.ndarray of shape (nt,)
Sorted observation grid.
- fpca_phi_obsnp.ndarray of shape (nt, num_pcs)
Basis on the observation grid (only the first num_pcs columns used).
- num_pcsint
Number of principal components to fit.
- Returns:
- np.ndarray of shape (num_pcs,)
Fitted eigenvalues in the FPCA subspace.
- Raises:
- ValueError
If fpca_phi_obs has incompatible shape.
Notes
The least-squares solve is performed with a low-level LAPACK GELS routine.