Update default parameters to healthy baseline & add optimization examples/docs #44
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…ples Resolves ComputationalPhysiology#42. **Default Parameter Overhaul:** Addressed the unstable default parameters noted in the issue. While the original suggestion was to use values from the Regazzoni paper, those were also found to be suboptimal. Instead, we optimized the model to match a specific healthy physiological baseline (BP ~120/80, SV ~70mL) and set these as the new defaults. **Documentation & Examples:** - Added `optimize_healthy_baseline.py`: Demonstrates the derivation of the new default parameters. - Added `optimize_pulmonary_hypertension.py`: Illustrates parameter tuning for pathological cases. - Added `regazzoni_vco_experiment.py`: Analyzes effects of virtual vena cava occlusion. **Technical Fixes:** - `base.py`: Fixed a bug where `initial_state` retained units even when `add_units=False` (previously only applied to parameters). - `_config.yml`: Added `.venv` to exclude patterns.
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Thanks @dtsteene. This looks really great! 🤩 |
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Resolves #42.
Default Parameter Overhaul:
Addressed the unstable default parameters noted in the issue. While the original suggestion was to use values from the Regazzoni paper, those were also found to be suboptimal. Instead, we optimized the model to match a specific healthy physiological baseline (BP ~120/80, SV ~70mL) and set these as the new defaults.
Documentation & Examples:
optimize_healthy_baseline.py: Demonstrates the derivation of the new default parameters.optimize_pulmonary_hypertension.py: Illustrates parameter tuning for pathological cases.regazzoni_vco_experiment.py: Analyzes effects of virtual vena cava occlusion.Technical Fixes:
base.py: Fixed a bug whereinitial_stateretained units even whenadd_units=False(previously only applied to parameters)._config.yml: Added.venvto exclude patterns.