PB preprocessed data used in paper "Multi variables time series information bottleneck"

Preprocessed PB data used in paper "Multi variables time series information bottleneck" with the GitHub code This dataset is created from a public available dataset of solar power data collected in Alabama by CalTrans. The npz file is a numpy (np) compressed data and can be loaded using np.load with allow_pickle=True<br> Loaded data is then a python dict described bellow. Each sample 'data' is a np.ndarray with 2 dimensions: time (various length) and wavelength (length=325 representing 325 traffic detectors ordered like in CalTrans). Each sample is given a 'position' which is a list of length 4:<br> position[1] is a string that gives the name of the event<br> position[4] is a boolean vector that gives the time positionsof the corresponding sample in the original sequence of public IRIS level2 data Data file info :<br> Type: .npz<br> Size: 114.23MB<br> *** Key: 'data_TR_PB'<br> ndarray data of length 3<br> containing np.ndarray of shapes [12160, 325] *** Key: 'data_VAL_PB'<br> ndarray data of length 3<br> containing np.ndarray of shapes [868, 325] *** Key: 'data_TE_PB'<br> ndarray data of length 3<br> containing np.ndarray of shapes [4343, 325] *** Key: 'data_TR'<br> ndarray data of length 3<br> containing np.ndarray of shapes [12160, 325] *** Key: 'data_VAL'<br> ndarray data of length 3<br> containing np.ndarray of shapes [868, 325] *** Key: 'data_TE'<br> ndarray data of length 3<br> containing np.ndarray of shapes [4343, 325] *** Key: 'position_TR_PB'<br> ndarray data of length 3<br> containing ndarray data of length 4<br> containing mix of types {'str', 'ndarray', 'int'} *** Key: 'position_VAL_PB'<br> ndarray data of length 3<br> containing ndarray data of length 4<br> containing mix of types {'str', 'ndarray', 'int'} *** Key: 'position_TE_PB'<br> ndarray data of length 3<br> containing ndarray data of length 4<br> containing mix of types {'str', 'ndarray', 'int'} *** Key: 'position_TR'<br> ndarray data of length 3<br> containing ndarray data of length 4<br> containing mix of types {'str', 'ndarray', 'int'} *** Key: 'position_VAL'<br> ndarray data of length 3<br> containing ndarray data of length 4<br> containing mix of types {'str', 'ndarray', 'int'} *** Key: 'position_TE'<br> ndarray data of length 3<br> containing ndarray data of length 4<br> containing mix of types {'str', 'ndarray', 'int'}