Utility functions

sktime has a number of modules dedicated to utilities:

sktime.datatypes, which contains utilities for data format checks and conversion.
sktime.pipeline, which contains generics for pipeline construction.
sktime.registry, which contains utilities for estimator and tag search, as well as serialization of estimator blueprints as strings.
sktime.utils, which contains generic utility functions.

Data Format Checking and Conversion

Module exports: data type definitions, checks, validation, fixtures, converters.

`convert_to`(obj, to_type[, as_scitype, ...])	Convert object to a different machine representation, subject to scitype.
`convert`(obj, from_type, to_type[, ...])	Convert objects between different machine representations, subject to scitype.
`check_raise`(obj, mtype[, scitype, var_name])	Check object for compliance with mtype specification, raise errors.
`check_is_mtype`(obj, mtype[, scitype, ...])	Check object for compliance with mtype specification, return metadata.
`check_is_scitype`(obj, scitype[, ...])	Check object for compliance with scitype specification, return metadata.
`mtype`(obj[, as_scitype, exclude_mtypes])	Infer the mtype of an object considered as a specific scitype.
`scitype`(obj[, candidate_scitypes, ...])	Infer the scitype of an object.
`mtype_to_scitype`(mtype[, return_unique, ...])	Infer scitype belonging to mtype.
`scitype_to_mtype`(scitype[, softdeps])	Return list of all mtypes belonging to scitype.

Pipeline maker utility.

`make_pipeline`(*steps)	Create a pipeline from estimators of any type.
`sklearn_to_sktime`(estimator)	Coerces an sklearn estimator to the sktime pipeline interface.

Registry for sktime estimator base classes, tags, global aliases.

`all_estimators`([estimator_types, ...])	List all estimators or objects in sktime, by scitype or tag.
`all_tags`([estimator_types, as_dataframe])	List all tags in sktime, for objects of a certain type.
`check_tag_is_valid`(tag_name, tag_value)	Check validity of a tag value.

Registry for sktime estimator base classes, tags, global aliases.

`craft`(spec)	Instantiate an object from the specification string.
`deps`(spec[, include_test_deps])	Get PEP 440 dependency requirements for a craft spec.
`imports`(spec)	Get import code block for a craft spec.

Common timeseries plotting functionality.

`plot_series`(*series[, labels, markers, ...])	Plot one or more time series.
`plot_lags`(series[, lags, suptitle])	Plot one or more lagged versions of a time series.
`plot_correlations`(series[, lags, alpha, ...])	Plot series and its ACF and PACF values.
`plot_windows`(cv, y[, title, ax])	Plot training and test windows.
`plot_interval`(ax, interval_df)	Plot prediction intervals on an existing matplotlib axes.
`plot_calibration`(y_true, y_pred[, ax])	Plot the calibration curve for a sample of quantile predictions.

Estimator checker for extension.

check_estimator(estimator[, ...])

Run all tests on one single estimator.