---
license: gpl-3.0
task_categories:
- video-classification
language:
- en
tags:
- solar
- flare
- forecasting
configs:
- config_name: default
  data_files:
  - split: train_72min
    path: "data/train/metadata_hmivideo_Mthr_fstep72min_train.json"
  - split: train_72min_downsampled
    path: "data/train/metadata_hmivideo_Mthr_fstep72min_downsampled_train.json"
  - split: train_72min_downsampled_bal
    path: "data/train/metadata_hmivideo_Mthr_fstep72min_downsampled_bal_train.json"   
  - split: test_72min
    path: "data/test/metadata_hmivideo_Mthr_fstep72min_test.json"
  - split: val_72min
    path: "data/cv/metadata_hmivideo_Mthr_fstep72min_cv.json"
  - split: val_72min_downsampled_bal
    path: "data/cv/metadata_hmivideo_Mthr_fstep72min_cv.json"  
  - split: train_36min
    path: "data/train/metadata_hmivideo_Mthr_fstep36min_train.json"
  - split: train_36min_downsampled
    path: "data/train/metadata_hmivideo_Mthr_fstep36min_downsampled_train.json"
  - split: train_36min_downsampled_bal
    path: "data/train/metadata_hmivideo_Mthr_fstep36min_downsampled_bal_train.json"   
  - split: test_36min
    path: "data/test/metadata_hmivideo_Mthr_fstep36min_test.json"
  - split: val_36min
    path: "data/cv/metadata_hmivideo_Mthr_fstep36min_cv.json"
  - split: val_36min_downsampled_bal
    path: "data/cv/metadata_hmivideo_Mthr_fstep36min_cv.json"    
---

This dataset is intended to be used for training/testing solar flare forecasting models. 
It contains various data splits (in json format) of SDO/HMI magnetogram images compiled by `Boucheron, L.E., et al., 2023, Sci Data 10, 825, https://doi.org/10.1038/s41597-023-02628-8` and arranged in 16 video frames with different frame cadence (32 min, 76 min).

Splits "train_72min" ("train_36min"), "val_72min" ("val_36min"), "test_72min" ("val_36min") corresponds to the original data splits provided by Boucheron et al. using different frame cadences (32 min, 72 min), while the other splits (labelled as "downsampled") are created by downsampling the No-Flare and C flare class to obtain more balanced splits and mitigate class imbalance.