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In function load_from_tsfile (momentfm/utils/data.py) you replace missing vals (replace_missing_vals_with) with NaN by default. However, when padding you use zero, as in ClassificationDataset.__getitem__ (momentfm/data/classification_dataset.py): timeseries = np.pad(timeseries, (self.seq_len - timeseries_len, 0))
Why not both pad and fill missing values with zeros, or with NaN; why use two different filler values?
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In function load_from_tsfile (momentfm/utils/data.py) you replace missing vals (
replace_missing_vals_with
) with NaN by default. However, when padding you use zero, as inClassificationDataset.__getitem__
(momentfm/data/classification_dataset.py):timeseries = np.pad(timeseries, (self.seq_len - timeseries_len, 0))
Why not both pad and fill missing values with zeros, or with NaN; why use two different filler values?
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