feat: Implement Monte Carlo plan success probability engine (proposal #36)#30
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82deutschmark wants to merge 5 commits intoPlanExeOrg:mainfrom
Open
feat: Implement Monte Carlo plan success probability engine (proposal #36)#3082deutschmark wants to merge 5 commits intoPlanExeOrg:mainfrom
82deutschmark wants to merge 5 commits intoPlanExeOrg:mainfrom
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added 5 commits
February 10, 2026 22:49
…lanExeOrg#36) - Core simulation engine running 10,000 independent scenarios - Triangular, PERT, and lognormal distribution sampling - Bernoulli risk event sampling with impact distributions - Results aggregation with percentiles (P10/P50/P90) - Risk-adjusted recommendations (GO/CAUTION/NO-GO) - Sensitivity analysis identifying top uncertainty drivers - Comprehensive test suite: 52+ tests, all passing Fulfills proposal PlanExeOrg#36: Monte Carlo Plan Success Probability Engine Enables probabilistic project forecasting with uncertainty quantification
…arlo - Add module-level convenience functions to distributions.py for direct import - Convert bare imports to relative imports in simulation.py and risk_events.py - Ensure all modules can be imported and used together without errors - Verified with local test: simulation runs successfully with realistic output
- distributions.py: Add missing compute_lognormal_params() function for parameter conversion - risk_events.py: Add .flatten() calls to fix numpy array shape mismatch (N,1) -> (N,) - outputs.py: Add safe threshold extraction with decimal-to-percentage conversion All three bugs found during integration testing now fixed and verified.
- Add asdict import for dataclass conversion - Detect MonteCarloResults dataclass objects at method entry - Convert to dict with proper field mapping - Maintains backward compatibility with dict input - Enables seamless integration with MonteCarloSimulation output
- Remove dataclass complexity, accept flat dict directly from simulation - Convert 0-1 probabilities to 0-100 percentages automatically - Compute GO/CAUTION/NO-GO recommendations based on thresholds - Generate clean summary text - All integration tests passing - full pipeline verified end-to-end
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Summary
Implements proposal #36: Monte Carlo Plan Success Probability Engine
Changes
Proposal Details
Enables probabilistic project forecasting with:
Testing
All 52 tests passing:
Ready for Simon's review.