rapid_tsa_python package

rapid_tsa_python module

rapid_tsa_python.exec_calc_stats(data_path=None, label_path=None, output_path=None)

Calculates statistics.

Note

Either data_path or label_path must be specified.

Parameters:

data_path : str or None, default: None

The time series data file or directory path (absolute path). If use directory path, each file extension must be ‘csv’.

label_path : str or None, default: None

The label data file or directory path (absolute path). If use directory path, each file extension must be ‘lab’.

output_path : str or None, default: None

The output file path (absolute path).

rapid_tsa_python.exec_preprocess(preprocess_def_path, data_path=None, label_path=None, output_dir=None, suffix=None)

Pre-processes the data.

Note

Either data_path or label_path must be specified.

Parameters:

preprocess_def_path: str

The preprocess definition file path (absolute path).

data_path : str or None, default: None

The time series data file or directory path (absolute path). If use directory path, each file extension must be ‘csv’.

label_path : str or None, default: None

The label data file or directory path (absolute path). If use directory path, each file extension must be ‘lab’.

output_dir : str or None, default: None

The output directory path (absolute path).

suffix : str or None, default: None

The suffix for preprocessed file name.

rapid_tsa_python.exec_train(mode, algorithm, label_path, model_dir, preprocess_def_path=None, param_conf_path=None)

Trains with the label data, and generates the model.

Parameters:

mode : {‘reg’, ‘cls’}

Problem type; cls: classification, reg: regression.

algorithm : {‘1DCNN’, ‘1DDCN’, ‘1DOCN’}

The algorithm type; 1DCNN: 1-Dimension Convolutional Neural Network, 1DDCN: 1-Dimension Deep Convolutional Neural Network, 1DOCN: 1-Dimension OneClass Neural Network (only this algorithm is for classification).

label_path : str

The label data file or directory path (absolute path). If use directory path, each file extension must be ‘lab’.

model_dir : str

The model directory path (absolute path).

preprocess_def_path: str or None, default: None

The preprocess definition file path (absolute path).

param_conf_path : str or None, default: None

The hyper-parameter configuration file path (absolute path). Refer to chapter 6.6.2 of RAPID TSA V2.2 User Guide.

rapid_tsa_python.exec_predict(model_dir, data_path=None, label_path=None, preprocess_def_path=None, param_conf_path=None, output_dir=None, suffix=None)

Predicts labels for the time series data by the model.

Note

Either data_path or label_path must be specified.

Parameters:

model_dir : str

The model directory path (absolute path).

data_path : str or None, default: None

The time series data file or directory path (absolute path). If use directory path, each file extension must be ‘csv’.

label_path : str or None, default: None

The label data file or directory path (absolute path). If use directory path, each file extension must be ‘lab’.

preprocess_def_path: str or None, default: None

The preprocess definition file path (absolute path).

param_conf_path : str or None, default: None

The hyper-parameter configuration file path (absolute path). Refer to chapter 6.6.3 of RAPID TSA V2.2 User Guide.

output_dir : str or None, default: None

The output directory path (absolute path).

suffix : str or None, default: None

The suffix for result file name.