simulation-validator

Pre-flight validation checks your simulation configuration, resources, and parameter ranges before execution starts. Run preflight_checker.py on your config file to catch mismatches, resource constraints, and invalid settings early, preventing failed runs and wasted compute time.

Runtime monitoring tracks convergence metrics and timestep stability while your simulation executes. The runtime_monitor.py script processes your log files to detect divergence, dt instability, and other runtime anomalies in real time, producing JSON-formatted alerts.

Post-run validation assesses mass conservation, energy balance, NaN/Inf detection, and result bounds. The result_validator.py script inspects metrics and log outputs to confirm physical correctness and data integrity, returning a confidence_score for result reliability.

The failure_diagnoser.py module interprets simulation logs to identify root causes—configuration errors, numerical instability, resource exhaustion, or convergence breakdown. It produces structured JSON output mapping failure symptoms to likely causes for rapid troubleshooting.

Yes. The validation suite runs on Linux, macOS, and Windows with Python 3.8+ and no external dependencies, making it portable across development and HPC environments without additional setup or compatibility layers.

Yes. All validation outputs produce JSON-ready reports with status, blockers, warnings, and confidence scores designed for RAG pipelines and downstream analysis automation, enabling seamless integration into CI/CD and data processing workflows.