Fix IRV results contract for strategy polling

[fsargent]

Summary

• Restore IRV public results to the simulator contract: rank-vector ballots in, high-is-better candidate scores out
• Remove IRV-specific winner/resultsFor behavior so polling and strategic targeting use generic Method semantics
• Add regression coverage for IRV polling/winner selection on the transfer example

Tests

• uv run python -m pytest

Made with Cursor

Summary by Sourcery

Align IRV simulator results with the generic method contract so polling and strategy use high-is-better candidate scores derived from finish order.

New Features:

• Expose helper conversions between IRV rank-vector ballots, preference orderings, and score-style results.

Bug Fixes:

• Ensure IRV resultsFor returns score-style results compatible with strategic polling and winner selection.

Enhancements:

• Refactor IRV result computation to convert finish ordering into high-is-better candidate scores instead of returning winner-first ordering.

Tests:

• Add regression test verifying IRV polling and winner selection preserve the simulator score contract on a transfer example electorate.

[sourcery-ai]

Reviewer's Guide

IRV’s public results contract is restored to return high-is-better candidate scores from rank-vector ballots, IRV-specific resultsFor/winner behavior is removed in favor of generic Method semantics, and regression coverage is added to ensure IRV polling and winner selection behave correctly for strategy use cases.

Sequence diagram for updated IRV.results rank-vector handling

sequenceDiagram
    participant Consumer
    participant Irv
    participant rankVectorToPreference
    participant runIrv
    participant finishOrderToResults

    Consumer->>Irv: results(ballots)
    Irv->>Irv: convert ballots to list
    loop for each ballot
        Irv->>rankVectorToPreference: rankVectorToPreference(ballot)
        rankVectorToPreference-->>Irv: preference_order
    end
    Irv->>runIrv: runIrv(buildPreferenceSchedule(rankings), ncand)
    runIrv-->>Irv: finishOrder
    Irv->>finishOrderToResults: finishOrderToResults(finishOrder)
    finishOrderToResults-->>Irv: results_scores
    Irv-->>Consumer: results_scores

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File-Level Changes

Change	Details	Files
Normalize IRV to use rank-vector ballots internally while exposing high-is-better score-style results and generic winner semantics.	Remove IRV-specific resultsFor wrapper that converted rank vectors to preference orders via a custom chooser. Introduce a reusable helper to convert rank-vector ballots to descending preference candidate ID lists. Change IRV.results to convert rank-vector ballots to preference rankings, run the IRV tabulator, and then convert finish order into high-is-better scores. Update IRV’s winner usage in tests to reflect that winner now operates on score-style results rather than finish-order arrays.	methods.py
Add regression test to enforce IRV’s simulator results contract for strategy/polling scenarios.	Import Irv into regression tests to allow direct method usage. Add a regression test that runs IRV via resultsFor on a mixed electorate, asserting the returned results vector, winner selection, and poll ordering all match the expected high-is-better score semantics.	test/test_regressions.py

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Review details

⚙️ Run configuration

Configuration used: defaults

Review profile: CHILL

Plan: Pro

Run ID: cde876d8-7782-4ec7-9793-9e3ed551a906

📥 Commits

Reviewing files that changed from the base of the PR and between eaed9ab and ac1a532.

📒 Files selected for processing (2)

• src/vse_sim/methods.py
• tests/test_regressions.py

✨ Finishing Touches

🧪 Generate unit tests (beta)

• Create PR with unit tests
• Commit unit tests in branch fix-irv-results-contract

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