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