API Reference

Welcome to the lmlib API documentation. The reference below is generated directly from the library's docstrings and covers the full public API.

State Space

Autonomous linear state-space models (ALSSMs) and the recursive least-squares machinery to fit them to signals: the models themselves, squared-error cost functions built on them, solvers, window and segment definitions, and higher-level applications.

• lmlib.statespace.model — autonomous linear state-space models (ALSSMs).
• lmlib.statespace.cost — squared-error cost functions built on ALSSMs.
• lmlib.statespace.rls — recursive least-squares solvers.
• lmlib.statespace.window — window definitions.
• lmlib.statespace.segment — segment definitions and direction constants.
• lmlib.statespace.trajectory — trajectories.
• lmlib.statespace.backend — backend selection.
• lmlib.statespace.applications — higher-level applications (e.g. TSLM).

Polynomial

A calculus for univariate and multivariate polynomials in vector-exponent notation, used to build localized polynomial signal models and to combine them inside squared-error cost functions.

• lmlib.polynomial.poly — uni- and multivariate polynomials in vector exponent notation, plus the polynomial operator calculus.

Utils

Supporting utilities used throughout the library: synthetic test-signal generators and signal loaders, input-validation helpers, and the lmlib color palette.

• lmlib.utils.generator — synthetic signal generators and signal loaders.
• lmlib.utils.check — validation helpers.
• lmlib.utils.colors — color palette.