The update v0.3.0 has been released with additional features, API changes and fixes.
MAJOR: Estimators support in AOLS
Now you can use any SysIdentPy estimator in AOLS model structure selection.
API Change:
Refactored base class for model structure selection. A refactored base class for model structure selection has been introduced in SysIdentPy. This update aims to enhance the system identification process by preparing the package for new features that are currently in development, like multiobjective parameter estimation, new basis functions and more.
Several methods within the base class have undergone significant restructuring to improve their functionality and optimize their performance. This reorganization will facilitate the incorporation of advanced model selection techniques in the future, which will enable users to obtain dynamic models with robust dynamic and static performance.
Avoid unnecessary inheritance in every MSS method and improve the readability with better structured classes.
Rewritten methods to avoid code duplication.
Improve overall code readability by rewriting if/elif/else clauses.
Breaking Change: X_train and y_train were replaced respectively by X and y in fit method in MetaMSS model structure selection algorithm. X_test and y_test were replaced by X and y in predict method in MetaMSS.
API Change: Added BaseBasisFunction class, an abstract base class for implementing basis functions.
Enhancement: Added support for python 3.11.
Future Deprecation Warning: The user will have to define the estimator and pass it to every model structure selection algorithm instead of using a string to define the Estimator. Currently the estimator is defined like "estimator='least_squares'". In version 0.4.0 the definition will be like "estimator=LeastSquares()"
FIX: Issue #96. Fix issue with numpy 1.24.* version. Thanks for the contribution @gamcorn.
v0.3.0
CONTRIBUTORS
The update v0.3.0 has been released with additional features, API changes and fixes.
MAJOR: Estimators support in AOLS
API Change:
Several methods within the base class have undergone significant restructuring to improve their functionality and optimize their performance. This reorganization will facilitate the incorporation of advanced model selection techniques in the future, which will enable users to obtain dynamic models with robust dynamic and static performance.
Breaking Change:
X_trainandy_trainwere replaced respectively byXandyinfitmethod in MetaMSS model structure selection algorithm.X_testandy_testwere replaced byXandyinpredictmethod in MetaMSS.API Change: Added BaseBasisFunction class, an abstract base class for implementing basis functions.
Enhancement: Added support for python 3.11.
Future Deprecation Warning: The user will have to define the estimator and pass it to every model structure selection algorithm instead of using a string to define the Estimator. Currently the estimator is defined like "estimator='least_squares'". In version 0.4.0 the definition will be like "estimator=LeastSquares()"
FIX: Issue #96. Fix issue with numpy 1.24.* version. Thanks for the contribution @gamcorn.
FIX: Issue #91. Fix r2_score metric issue with 2 dimensional arrays.
FIX: Issue #90.
FIX: Issue #88 .Fix one step ahead prediction error in SimulateNARMAX class (thanks for pointing out, Lalith).
FIX: Fix error in selecting the correct regressors in AOLS.
Fix: Fix n step ahead prediction method not returning all values of the defined steps-ahead value when passing only the initial condition.
FIX: Fix Visible Deprecation Warning raised in get_max_lag method.
FIX: Fix deprecation warning in Extended Least Squares Example
DATASET: Added air passengers dataset to SysIdentPy repository.
DATASET: Added San Francisco Hospital Load dataset to SysIdentPy repository.
DATASET: Added San Francisco PV GHI dataset to SysIdentPy repository.
DOC: Improved documentation in Setting Specif Lags page. Now we bring an example of how to set specific lags for MISO models.
DOC: Minor additions and grammar fixes.
DOC: Improve image visualization using mkdocs-glightbox.
Update dev packages versions