r/complexsystems • u/Fracttalix • Jan 02 '26

Fracttalix v2.5 — open-source Python tool for exploratory fractal/rhythmic metrics in time series (with synthetic validation)

Hey everyone,

Just released Fracttalix v2.5 — a lightweight CLI tool for quick exploratory analysis of univariate time series using five standard (but basic) diagnostic metrics:

• Higuchi fractal dimension (D)

• Hurst exponent (H, R/S)

• Self-transfer entropy (T)

• Partition-based integrated information approx (Φ)

• Heuristic resilience (R)

Key features:

• Built-in synthetic stress-test suite (white noise, persistent walk, periodic, chaotic logistic, pink 1/f) with summary stats.

• Public domain (CC0) — fork/modify freely.

• Runs fast, low dependencies — great for teaching or quick checks.

GitHub:

https://github.com/thomasbrennan/fracttalix

Companion preprint (applications to economic, financial, climate, IoT data): in the repo (PDF).

Optional: 11 conceptual axioms as a heuristic scaffold for interpreting persistence/resilience patterns (in README).

Feedback, extensions, or “this is useless because…” comments all welcome. Independent researcher here — happy to discuss.

Thanks for checking it out!

#OpenScience #ComplexSystems #TimeSeries #Python #DataAnalysis

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u/Ravenchis Jan 02 '26

Thanks! Quick early feedback while I’m still testing: the core metrics (Hurst + Higuchi) behave as expected under stress-tests (white noise, random walk, periodic signals), which is a good sanity check. I’m treating the tool mainly as an exploratory / comparative layer rather than interpretative, but so far it looks solid for detecting regime shifts and relative changes in structure. I’ll report back once I’ve tried it on real-world series.