DOI: 10.5281/zenodo.7524572
title: IRIS preprocessed data used in paper "Multi variables time series information bottleneck"

description: Prprocessed data used in paper "Multi variables time series information bottleneck" with the GitHub code This dataset is created from a public available dataset of observations performed by IRIS, a NASA small explorer mission developed and operated by LMSAL with mission operations executed at NASA Ames Research Center and major contributions to downlink communications funded by ESA and the Norwegian Space Centre. Multiple Time Series of IRIS level 2 data are available here The selected data was labeled using these definitions: QS: Quiet Sun<br> AR: Active Regions of the Sun<br> FL: Flare A time series is labeled QS when every single time step refer to a quiet sun activity.<br> When a given time series is partially composed of flaring events, the global time series is labeled as FL. 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=240 representing a range between 2793.8401Å and 2806.02Å). 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 : Type: .npz<br> Size: 11.89GB *** Key: 'data_TR_QS'<br> ndarray data of length 2467<br> containing np.ndarray of shapes ['various', 240] *** Key: 'data_TR_AR'<br> ndarray data of length 1042<br> containing np.ndarray of shapes ['various', 240] *** Key: 'data_TR_FL'<br> ndarray data of length 1055<br> containing np.ndarray of shapes ['various', 240] *** Key: 'data_VAL_QS'<br> ndarray data of length 325<br> containing np.ndarray of shapes ['various', 240] *** Key: 'data_VAL_AR'<br> ndarray data of length 1042<br> containing np.ndarray of shapes ['various', 240] *** Key: 'data_VAL_FL'<br> ndarray data of length 714<br> containing np.ndarray of shapes ['various', 240] *** Key: 'data_TE_QS'<br> ndarray data of length 1428<br> containing np.ndarray of shapes ['various', 240] *** Key: 'data_TE_AR'<br> ndarray data of length 792<br> containing np.ndarray of shapes ['various', 240] *** Key: 'data_TE_FL'<br> ndarray data of length 356<br> containing np.ndarray of shapes ['various', 240] *** Key: 'data_TR'<br> ndarray data of length 4564<br> containing np.ndarray of shapes ['various', 240] *** Key: 'data_VAL'<br> ndarray data of length 2081<br> containing np.ndarray of shapes ['various', 240] <br> *** Key: 'data_TE'<br> ndarray data of length 2576<br> containing np.ndarray of shapes ['various', 240] *** Key: 'position_TR_QS'<br> ndarray data of length 2467<br> containing ndarray data of length 4<br> containing mix of types {'ndarray', 'int', 'str'} *** Key: 'position_TR_AR'<br> ndarray data of length 1042<br> containing ndarray data of length 4<br> containing mix of types {'ndarray', 'int', 'str'} *** Key: 'position_TR_FL'<br> ndarray data of length 1055<br> containing ndarray data of length 4<br> containing mix of types {'ndarray', 'int', 'str'} *** Key: 'position_VAL_QS'<br> ndarray data of length 325<br> containing ndarray data of length 4<br> containing mix of types {'ndarray', 'int', 'str'} *** Key: 'position_VAL_AR'<br> ndarray data of length 1042<br> containing ndarray data of length 4<br> containing mix of types {'ndarray', 'int', 'str'} *** Key: 'position_VAL_FL'<br> ndarray data of length 714<br> containing ndarray data of length 4<br> containing mix of types {'ndarray', 'int', 'str'} *** Key: 'position_TE_QS'<br> ndarray data of length 1428<br> containing ndarray data of length 4<br> containing mix of types {'ndarray', 'int', 'str'} *** Key: 'position_TE_AR'<br> ndarray data of length 792<br> containing ndarray data of length 4<br> containing mix of types {'ndarray', 'int', 'str'} *** Key: 'position_TE_FL'<br> ndarray data of length 356<br> containing ndarray data of length 4<br> containing mix of types {'ndarray', 'int', 'str'} *** Key: 'position_TR'<br> ndarray data of length 4564<br> containing ndarray data of length 4<br> containing mix of types {'ndarray', 'int', 'str'} *** Key: 'position_VAL'<br> ndarray data of length 2081<br> containing ndarray data of length 4<br> containing mix of types {'ndarray', 'int', 'str'} *** Key: 'position_TE'<br> ndarray data of length 2576<br> containing ndarray data of length 4<br> containing mix of types {'ndarray', 'int', 'str'}