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

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
AR: Active Regions of the Sun
FL: Flare

A time series is labeled QS when every single time step refer to a quiet sun activity.
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
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:
position[1] is a string that gives the name of the event
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
Size: 11.89GB

*** Key: 'data_TR_QS'
ndarray data of length 2467
containing np.ndarray of shapes ['various', 240]

*** Key: 'data_TR_AR'
ndarray data of length 1042
containing np.ndarray of shapes ['various', 240]

*** Key: 'data_TR_FL'
ndarray data of length 1055
containing np.ndarray of shapes ['various', 240]

*** Key: 'data_VAL_QS'
ndarray data of length 325
containing np.ndarray of shapes ['various', 240]

*** Key: 'data_VAL_AR'
ndarray data of length 1042
containing np.ndarray of shapes ['various', 240]

*** Key: 'data_VAL_FL'
ndarray data of length 714
containing np.ndarray of shapes ['various', 240]

*** Key: 'data_TE_QS'
ndarray data of length 1428
containing np.ndarray of shapes ['various', 240]

*** Key: 'data_TE_AR'
ndarray data of length 792
containing np.ndarray of shapes ['various', 240]

*** Key: 'data_TE_FL'
ndarray data of length 356
containing np.ndarray of shapes ['various', 240]

*** Key: 'data_TR'
ndarray data of length 4564
containing np.ndarray of shapes ['various', 240]

*** Key: 'data_VAL'
ndarray data of length 2081
containing np.ndarray of shapes ['various', 240]

*** Key: 'data_TE'
ndarray data of length 2576
containing np.ndarray of shapes ['various', 240]

*** Key: 'position_TR_QS'
ndarray data of length 2467
containing ndarray data of length 4
containing mix of types {'ndarray', 'int', 'str'}

*** Key: 'position_TR_AR'
ndarray data of length 1042
containing ndarray data of length 4
containing mix of types {'ndarray', 'int', 'str'}

*** Key: 'position_TR_FL'
ndarray data of length 1055
containing ndarray data of length 4
containing mix of types {'ndarray', 'int', 'str'}

*** Key: 'position_VAL_QS'
ndarray data of length 325
containing ndarray data of length 4
containing mix of types {'ndarray', 'int', 'str'}

*** Key: 'position_VAL_AR'
ndarray data of length 1042
containing ndarray data of length 4
containing mix of types {'ndarray', 'int', 'str'}

*** Key: 'position_VAL_FL'
ndarray data of length 714
containing ndarray data of length 4
containing mix of types {'ndarray', 'int', 'str'}

*** Key: 'position_TE_QS'
ndarray data of length 1428
containing ndarray data of length 4
containing mix of types {'ndarray', 'int', 'str'}

*** Key: 'position_TE_AR'
ndarray data of length 792
containing ndarray data of length 4
containing mix of types {'ndarray', 'int', 'str'}

*** Key: 'position_TE_FL'
ndarray data of length 356
containing ndarray data of length 4
containing mix of types {'ndarray', 'int', 'str'}

*** Key: 'position_TR'
ndarray data of length 4564
containing ndarray data of length 4
containing mix of types {'ndarray', 'int', 'str'}

*** Key: 'position_VAL'
ndarray data of length 2081
containing ndarray data of length 4
containing mix of types {'ndarray', 'int', 'str'}

*** Key: 'position_TE'
ndarray data of length 2576
containing ndarray data of length 4
containing mix of types {'ndarray', 'int', 'str'}