Add transfer entropy (KSG + binned) — first bivariate information-flow measure - #1
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Demonstrates entropy of a rolling correlation series as a correlation-regime stability gauge (idea from an r/dataisbeautiful thread). Ships alongside a rolling-std baseline so the example shows that an entropy signal must be checked against a trivial baseline before being trusted — on this synthetic data, std separates the regimes and entropy of the smooth correlation swing does not. - _synthetic.correlated_assets(): two return streams, stable shared-factor regime then a correlation breakdown - examples/correlation_stability.py: rolling corr -> permutation entropy vs rolling-std baseline, prints regime separation for both - tests: smoke test for the new example + a behavioral test asserting the generator's stable half is more correlated than its broken half Uses only the existing public API; no library changes. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Implements embed() in entroscope/_transfer_estimators.py — the single source of (y_future, y_past, x_past) aligned columns consumed by both the binned and KSG estimators. Verified in isolation against hand-computed values (Gate C). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Remove unused imports and split semicolon statements flagged by ruff in the transfer tests; drop a pre-existing unused pandas import in the correlation-stability example. Full suite: 132 passed. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
…g perf Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
CI runs 'ruff format --check'; the new files weren't formatter-clean. Cosmetic only (import wrapping, comment spacing, line reflow), no logic change. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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Adds
entroscope.transfer, the library's first bivariate / information-flowmeasure: directional transfer entropy TE(X→Y) (Schreiber 2000) with two
estimators — Kraskov KSG k-NN (default, no binning) and a binned histogram
cross-check. Mirrors the house
compute / rolling / delta / plotcontract,takes two series, preserves the pandas index.
Born from an r/dataisbeautiful thread asking for transfer entropy + KSG.
Correctness — three independent authorities
The KSG estimator is validated against ground truth that shares no code with it:
The binned-vs-KSG cross-check is treated as a consistency check only (a shared
embedding bug would fool both), so correctness rests on A/B/C.
Notes
blowup flagged in the thread).
Tests
132 passed, ruff clean. New
tests/test_transfer.py(22 tests): the threegates + independence + directionality + cross-check + API/contract + guard.
Also includes the correlation-stability example (this branch is stacked on it).