svZeroDTuner Worked Examples

Table of Contents

• Example 1: Minimal Scalar-Target Tuning
• Example 2: Multi-Outlet Pulmonary Tree Tuning
• Optional: Time-Series Target Matching
• Validation Checklist

Example 1: Minimal Scalar-Target Tuning

Recommended starting point:

• applications/svZeroDTuner/examples/closed_loop_Regazzoni

Workflow

1. Baseline run

cd applications/svZeroDTuner/examples/closed_loop_Regazzoni
python -c 'from main import run_baseline; run_baseline("model.json")'

1. Configure scalar targets in one of:

• tuning_differential_evolution.yaml
• tuning_nelder_mead.yaml

1. Run optimization with the CLI

svzerodtuner optimize applications/svZeroDTuner/examples/closed_loop_Regazzoni/tuning_differential_evolution.yaml

Expected artifacts

• optimization_history/history.csv
• optimization_history/objective_history.png
• target_comparison.png and target_comparison.csv
• optimized model JSON in output directory

Example 2: Multi-Outlet Pulmonary Tree Tuning

Pulmonary tree example:

• applications/svZeroDTuner/examples/right_heart_pa

Workflow

1. Run baseline and inspect generated baseline outputs:

cd applications/svZeroDTuner/examples/right_heart_pa
python -c 'from main import run_baseline; run_baseline("model.json")'

1. Tune pulmonary pressures and RPA/LPA flow split using:

• tuning_differential_evolution.yaml, or
• tuning_nelder_mead.yaml

1. Validate branch flow split and PA pressure range in output plots and CSV.

Run with CLI:

svzerodtuner optimize applications/svZeroDTuner/examples/right_heart_pa/tuning_nelder_mead.yaml

Optional: Time-Series Target Matching

Time-series target example:

• applications/svZeroDTuner/examples/closed_loop_Regazzoni/tuning_time_series_target.yaml

This configuration demonstrates:

• type: time_series
• target_file with time,value columns
• range-based matching via relative_bounds

Validation Checklist

For each example:

• Confirm optimization termination reason and success flag.
• Confirm objective trend decreases in objective_history.png.
• Compare target and simulated outputs in target_comparison.csv.
• Check whether best parameters are near bounds (printed warnings).
• Cross-check final waveforms with svZeroDVisualization when needed.