🤖 Autoloop program issue for tsb-perf-evolve. The program definition below is mirrored from .autoloop/programs/tsb-perf-evolve/program.md. Edit the file to update the definition; comment on this issue to steer the agent.

tsb perf evolve — Series.sortValues vs pandas Series.sort_values

Goal

Evolve the implementation of Series.sortValues (src/core/series.ts) so that, on the synthetic benchmark in code/benchmark.ts, tsb runs at least as fast as pandas on the equivalent Series.sort_values call (code/benchmark.py).

Concretely, we minimize the ratio

fitness = mean_ms_tsb / mean_ms_pandas

fitness < 1.0 means tsb is faster than pandas; lower is better. We will keep iterating as long as fitness keeps improving.

This is a performance-evolution program — there is one self-contained artifact (Series.sortValues), one scalar fitness (the ratio), and many plausible algorithmic families to try (comparison sort, typed-array indirect sort, dtype-dispatched non-comparison sort, batched/SoA, etc.). It is the canonical case for the AlphaEvolve strategy.

Validity invariants

1. The existing test suite for sortValues passes.
2. The function signature is unchanged: sortValues(ascending = true, naPosition: "first" | "last" = "last"): Series<T>.
3. No new runtime dependencies.
4. TypeScript strict mode satisfied.
5. Behaviour identical to reference for all dtypes, both ascending/descending, both naPosition values, and empty Series.

Target

Only modify: src/core/series.ts (sortValues method body) and .autoloop/programs/tsb-perf-evolve/code/**.

Evaluation

Metric: fitness = tsb_mean_ms / pandas_mean_ms. Lower is better. < 1.0 means tsb is faster than pandas.

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