Chaospy Uncertainty Propagation Starter

Use this skill to run a deterministic uncertainty-propagation toy workflow with Chaospy and inspect a machine-readable summary of the propagated response distribution.

What This Skill Does

• defines a small two-parameter input distribution with one Gaussian and one uniform variable
• builds a polynomial-chaos surrogate with quadrature
• reports the propagated mean, standard deviation, percentiles, and representative quadrature evaluations

When To Use It

• when you need a runnable uncertainty-aware-simulation starter
• when you want a local Chaospy example before wiring in an expensive scientific simulator
• when you need deterministic uncertainty summaries for repository tests

Run

./slurm/envs/numerics/bin/python skills/scientific-computing-and-numerical-methods/chaospy-uncertainty-propagation-starter/scripts/run_chaospy_uncertainty_propagation.py \
  --config skills/scientific-computing-and-numerical-methods/chaospy-uncertainty-propagation-starter/examples/toy_parameters.json \
  --out scratch/numerics/chaospy_uncertainty_summary.json

Notes

• The response model is intentionally synthetic; it exists to verify the UQ loop, not to stand in for a real simulator.
• The script uses deterministic quadrature rather than random sampling so the summary is stable across reruns.