limen.cohort

Inference-time cohort surfaces for aggregating decoder outputs from completed Limen experiments.

Canonical docs

• Cohort
• Trainer

What this package owns

This package owns the cohort-level inference surface:

1. Cohort for direct multi-member aggregation from one experiment and selected permutations
2. single-file cohort (sfc) strategies for choosing those permutations from experiment artefacts

It does not own:

• experiment search execution (owned by limen.experiment)
• raw market data infrastructure
• downstream decisioning/execution logic (outside Limen)

Key entry points

Entry point	Use it when	Notes
Cohort	You want to aggregate selected decoders from one completed experiment at inference time	Supports probability-weighted and majority-vote fallback modes
limen.cohort.sfc.all.select	You want the default "use every round" selector	Preserves existing omitted-permutation_ids behavior
limen.cohort.sfc.top_n.select	You want a simple results-column ranker	Requires results.csv
limen.cohort.sfc.backtest_pareto.select	You want trading-metric Pareto selection	Uses backtest return/risk columns
limen.cohort.sfc.diverse_metrics.select	You want metric-diverse member selection	Uses PCA/KMeans medoids over metric columns

Package map

cohort/
├── cohort.py                # Cohort constructor + aggregation logic
└── sfc/                     # Single-file cohort strategies
    ├── all.py               # select(context) -> ids
    ├── top_n.py             # select(context, *, column, n, ...) -> ids
    ├── backtest_pareto.py   # select(context, *, target_count, ...) -> ids
    └── diverse_metrics.py   # select(context, *, target_count, ...) -> ids

Cohort quick behavior

• Construct from exactly one experiment source (experiment_id or experiment_log_path)
• Validate explicit or selector-produced permutation_ids
• Enforce single-architecture selection
• Infer aggregation mode from architecture capability:
  • probability_weighted when probability output is supported
  • majority_vote fallback otherwise
• predict(...) returns ndarray/tuple contract
• __call__(...) returns decoder-compatible dict contract

See Cohort for full contract and examples.

Selector quick behavior

• Selectors are one-file strategies with one public select(...) function
• Selectors receive a context dict and return permutation IDs only
• Cohort owns all validation after selector execution
• Built-ins cover all-round, single-column rank, backtest Pareto, and metric diversity selection

Adjacent modules

• limen.experiment provides experiment logs, Trainer, and Sensor reconstruction used by Cohort flows
• limen.log provides analysis surfaces commonly used before selector-driven promotion
• limen.sfd and reference architectures define member model output behavior

Read next

• Cohort
• Trainer