v3.9

The headline change in 3.9.0 is multi-hazard regional simulation: the regional_sim tool now handles Hazus Hurricane Wind alongside earthquake, and has been restructured around a configuration-driven Intensity Measure model and a conditional loss-assessment framework that generalizes cleanly to additional hazards. Alongside this, a building inventory filter lets users run on any subset of an asset list, and the NNR resampler has been extended to operate on 3D per-realization arrays with a configurable neighbor count.

On the runtime side, pelicun is now fully numpy 2 compatible, and its dependency ranges have been revisited against what the code actually uses — raising the pandas, numpy, and scipy floors, widening the upper bounds, and clearing the ~720 pandas / numpy deprecation warnings previously emitted by the test suite.

Added

• Multi-Hazard Regional Simulation: The regional_sim tool now supports configurable hazards beyond earthquake.
  • Add support for the Hazus Hurricane Wind damage and loss methodology.
  • Introduce a new end-to-end integration test for the hurricane wind scenario, with a dedicated, hazard-specific pytest fixture.
• Building Inventory Filter: Run simulations on a specific subset of assets.
  • Add a filter key to the regional_sim configuration that selects buildings by ID and ID ranges (e.g., "1, 5-10").
  • Add a parametrized test suite covering success and error-handling scenarios for the filter.
• Enhanced Regional Simulation Testing: Add the first comprehensive integration tests for the regional_sim tool, establishing a testing baseline for future changes.
• NNR (Nearest Neighbor Resampling) Enhancements:
  • The "expected value" mode now operates on each realization of a 3D input array independently.
  • The 2D expected value path is now vectorized for improved performance.
  • The number of nearest neighbors is now a configurable parameter.
• numpy 2 Support: Pelicun now runs against numpy 2 (verified on numpy 2.0 through 2.4).
• Module Entry Point: python -m pelicun now dispatches to the CLI, complementing the existing pelicun console script.

Changed

• Regional Simulation Workflow: Major refactoring of the regional_sim script for improved flexibility and robustness.
  • Generalize the Intensity Measure (IM) handling to be dynamically driven by the configuration file, removing all hardcoded "PGA" logic.
  • Rearchitect the loss assessment logic into a conditional framework, with a dedicated path for complex Hazus Earthquake models and an efficient 1-to-1 mapping path for other methods.
  • Reorganize the output stage to save results sequentially, improving robustness against failures in later-stage calculations.
  • Upsample demand realizations when the requested sample size is larger than the available data.
• Runtime Dependency Ranges: Broadened upper bounds and raised lower bounds to reflect what the code actually supports.
  • numpy: <2.0 -> >=1.23, <3.0
  • scipy: <=1.15.3 -> >=1.8.0, <1.16 (scipy 1.16 removed the private stats._mvn module imported by uq.py).
  • pandas: >=1.4.0 -> >=2.2.3, <3.0 (the code uses future.no_silent_downcasting and GroupBy.first(skipna=False), which are only available from pandas 2.2.1+).
  • tqdm, requests, joblib, scikit-learn, packaging: switched from unpinned to explicit compatibility ranges.
• Configuration (breaking): regional_sim now requires a neighbors key under Applications/RegionalMapping/Buildings/ApplicationData in the run configuration. There is no fallback; configs produced by older R2D workflows must be updated.

Fixed

• Pandas / numpy Deprecation Warnings: A full-suite test run previously emitted ~720 deprecation warnings. The following underlying call sites were corrected so that the suite now runs warning-free apart from pelicun's own intentional PelicunWarning emissions:
  • base.convert_dtypes: replace deprecated pd.to_numeric(..., errors='ignore') with an explicit try/except fallback.
  • DemandModel.estimate_RID: replace a DataFrame.stack trick used only for MultiIndex construction with a direct pd.MultiIndex.from_tuples call.
  • Unit-label assignments in assessment.calculate_demand, assessment._add_units, and DemandModel.add_column: build the mixed-dtype "Units" row with an explicit object dtype so string labels no longer trigger a float64 -> object upcast warning.
  • ~27 DataFrame.groupby(..., axis=1) call sites in the damage / loss / regional-sim / DL_calculation paths: rewritten as df.T.groupby(...)...T.
• Damage Model — Fragility Scaling with Unspecified Distribution: ScalingSpecification entries targeting components whose distribution family is missing (stored as NaN, e.g., Hazus collapse-0-1) are now scaled as deterministic capacities instead of being silently ignored with a warning. This aligns damage_model.ds_model._create_dmg_rvs with the existing behavior of uq.rv_class_map.
• Code Quality and Documentation: Continued compliance with ruff, full type hints and docstring added to the NNR function.
• CLI Subprocess Tests: The three pelicun CLI integration tests now invoke the CLI via [sys.executable, '-m', 'pelicun', ...] so they use the same interpreter / virtualenv as the test runner, instead of whichever pelicun script happens to come first on PATH.