Add support for time-varying setpoints in plots #17
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- Modify plot functions in `data_visualization.py` to accept setpoint data of shape (T, n) instead of (n, 1) arrays, where `T` is the number of time steps and `n` is the number of setpoint dimensions. This allows plotting dynamic setpoint lines that vary over time. - Update example scripts (`lti_dd_mpc_example.py`, `nonlinear_dd_mpc_example.py`) to construct setpoint data matrices from controller input-output setpoints and pass them to the updated plot functions. - Update test scripts to align with these changes.
- Centralize plot data validation in `data_visualization.py`:
- Add `validate_data_dimensions` to validate the dimensions of
input-output data arrays, and bound and ylimit lists.
- Update `plot_input_output` and `plot_input_output_animation`
functions to use `validate_data_dimensions` for plot data
validation.
- Add unit tests for `validate_data_dimensions` in
`test_data_visualization.py` and remove redundant test
`test_plot_input_output_mismatched_dim_len`.
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All checks have passed and the new functionality looks good. Merging now. |
pavelacamposp
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Jun 5, 2025
Update the reproduction script to construct setpoint data matrices from controller input-output setpoints and pass them to the reproduction plot function, which uses plot functions updated in PR #17. This prevents the error `ValueError: Shape mismatch.` and ensures compatibility with the updated plot utilities.
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This PR improves the flexibility of plot functions by adding support for dynamic setpoint lines that vary over time. Additionally, it centralizes plot data validation in plot functions.
Key changes:
data_visualization.pyto support time-varying setpoints.data_visualization.py.