Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

The DIW dataloader should be more general #10

Open
bgpierc opened this issue Jun 14, 2024 · 0 comments
Open

The DIW dataloader should be more general #10

bgpierc opened this issue Jun 14, 2024 · 0 comments
Labels
enhancement New feature or request good first issue Good for newcomers

Comments

@bgpierc
Copy link
Contributor

bgpierc commented Jun 14, 2024

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

@bgpierc bgpierc added enhancement New feature or request good first issue Good for newcomers labels Jun 14, 2024
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
enhancement New feature or request good first issue Good for newcomers
Projects
None yet
Development

No branches or pull requests

1 participant