Tools for Handling Extraction of Features from Time Series

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Documentation for package ‘theft’ version 0.8.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

calculate_features	Compute features on an input time series dataset
check_vector_quality	Check for presence of NAs and non-numerics in a vector
feature_list	All features available in theft in tidy format
init_theft	Communicate to R the Python virtual environment containing the relevant libraries for calculating features
install_kats	Download and install Kats from Python into a new virtual environment
install_python_pkgs	Download and install tsfresh, TSFEL, and Kats from Python into a new virtual environment
install_tsfel	Download and install TSFEL from Python into a new virtual environment
install_tsfresh	Download and install tsfresh from Python into a new virtual environment
process_hctsa_file	Load in hctsa formatted MATLAB files of time series data into a tidy format ready for feature extraction
simData	Sample of randomly-generated time series to produce function tests and vignettes
theft	Tools for Handling Extraction of Features from Time-series