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Currently, the DIW dataloader is somewhat hard-coded. The PV dataloader is more flexible, and allows you to specify column names at runtime.
For example, the DIW dataloader currently selects columns to be removed and considered:
target_cols = ['X_Pos_Error', 'Y_Pos_Error', 'Z_Pos_Error'] all_cols = df.columns.tolist() #remove_cols = ['Time', 'node_id', 'delta_X_Pos', 'delta_Y_Pos', 'delta_Z_Pos'] remove_cols = ['Time', 'node_id', 'delta_X_Pos', 'delta_Y_Pos', 'delta_Z_Pos', 'folder.id', 'layer.num', 'shape', 'on.off', 'velocity', 'z_height', 'acceleration'] predictor_cols = [col for col in all_cols if col not in target_cols + remove_cols]
A good improvement would be to specify these columns as an input to the dataloader in the init function
The text was updated successfully, but these errors were encountered:
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Currently, the DIW dataloader is somewhat hard-coded. The PV dataloader is more flexible, and allows you to specify column names at runtime.
For example, the DIW dataloader currently selects columns to be removed and considered:
A good improvement would be to specify these columns as an input to the dataloader in the init function
The text was updated successfully, but these errors were encountered: