pflm.fpca.SmoothedModelResult

class SmoothedModelResult(grid: ndarray, mu: ndarray, cov: ndarray, grid_type: Literal['obs', 'reg'] = 'obs')

Bases: object

Smoothed mean/covariance on a specific grid.

Attributes:

gridnp.ndarray of shape (nt,)

The grid on which the smoothing results are defined.

munp.ndarray of shape (nt,)

Smoothed mean values on grid.

covnp.ndarray of shape (nt, nt)

Smoothed covariance matrix on grid.

grid_type{“obs”, “reg”}

Grid kind: observation grid (“obs”) or regular grid (“reg”).

Notes

This dataclass is a container with no validation logic; shapes and consistency are assumed to be checked upstream.

Examples

>>> import numpy as np
>>> from pflm.fpca import SmoothedModelResult
>>> grid = np.linspace(0, 1, 5)
>>> mu = np.zeros(5)
>>> cov = np.eye(5)
>>> result = SmoothedModelResult(grid=grid, mu=mu, cov=cov, grid_type='reg')
>>> result.grid_type
'reg'

cov: ndarray

grid: ndarray

grid_type: Literal['obs', 'reg'] = 'obs'

mu: ndarray