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license: mit |
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# Data Format |
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The dataset has been split into `train`, `val`, and `test` jsonl files. |
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Each line of each jsonl file has the following fields: |
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* `object_id`: unique identifier for the object |
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* `times_wv`: an array of shape _(T, 2)_, where the i-th element contains (t_i, w_i), the time and wavelength of the i-th measured flux value. If t_i = 0, then this is a padded value and the associated flux f_i will also be 0. |
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* `lightcurve`: an array of shape _(T, 2)_, where the i-th element contains (f_i, f_err_i), the i-th flux and uncertainty on that flux measurement (flux error). |
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* `label`: an integer label corresponding to an astronomical object type. This is the value to be predicted. |
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# Usage |
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The directory includes a custom dataset loading script (`raw_train_with_labels.py`), which will be used when calling |
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``` |
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load_dataset("/path/to/current/dir") |
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``` |
