resilience-memory-utac
GenesisAeon Package 97 — real critical-slowing-down statistics and post-perturbation resilience-debt tracking. Deliberately has no UTAC/CREP/AFET bridge — see DISCLAIMER.md.
For a plain-language explanation of the same topic (German, no jargon, written for general audiences), see WHITEPAPER.md.
What's real here
- Dakos et al. (2012, PLOS ONE): the generic early-warning-signal workflow — detrend a time series, compute rolling variance / lag-1 autocorrelation / skewness, test each for a trend with Kendall's tau.
- Scheffer et al. (2009, Nature): the underlying concept — recovery rate from small perturbations declines as a system nears a critical transition ("critical slowing down").
- van Nes & Scheffer (2007, American Naturalist): slow recovery from perturbations, tracked here as an explicit "resilience-debt" — if a system hasn't recovered before the next shock, it carries the deficit forward.
- A live, verified illustration (not calibration input): Rhine at Kaub (24 cm, 2026-08-04, matching the 2018 record), Danube at Paks (-144 cm, below the 2018 record of -98 cm, triggering Hungary's first-ever full reactor shutdown), and Cernavoda NPP (Romania, reactor shutdown + emergency underwater demolition to redirect cooling water) — see DISCLAIMER.md for exactly what this case study is and is not used for.
Quickstart
pip install resilience-memory-utac
from resilience_memory_utac import compute_early_warning_report
# any real time series you supply -- river discharge, coral cover, ...
report = compute_early_warning_report(my_series)
print(f"Variance trend: tau={report.variance_tau:.2f} (p={report.variance_p:.3f})")
print(f"Autocorrelation trend: tau={report.autocorrelation_tau:.2f}")
from resilience_memory_utac import PerturbationEvent, compute_resilience_debt
events = [
PerturbationEvent(label="2018 low-water", time=0, magnitude=8.0, tau=365.0),
PerturbationEvent(label="2026 low-water", time=2800, magnitude=10.0, tau=365.0),
]
states = compute_resilience_debt(events)
print(states[-1].fully_recovered) # False if the 2018 event hadn't fully decayed away
Development
pip install -e ".[dev]"
pre-commit install
ruff check src tests
mypy src
pytest
Citation
See CITATION.cff and .zenodo.json.
Metadata
Release files for resilience-memory-utac 1.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| resilience_memory_utac-1.0.1.tar.gz | 16.5 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| resilience_memory_utac-1.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 27.5 kB
Release files / resilience_memory_utac-1.0.1.tar.gz
| Download URL | resilience_memory_utac-1.0.1.tar.gz |
|---|---|
| Size | 16.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
b680cbc38976f3ccbedf8e1ef925091939967baf29fdce8c49a0c24c3aca678b
|
|
BLAKE2b-256 checksum How to use checksums |
d9e037e8cf38ca0275998b0b531b43b8c00c52e3ad2e3a544294b61fea8220cc
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Release files / resilience_memory_utac-1.0.1-py3-none-any.whl
| Download URL | resilience_memory_utac-1.0.1-py3-none-any.whl |
|---|---|
| Size | 11.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
a731cb0e97d30768b69b83e5c8a991b4bf87d349e7e7fbcf150ecfcd33e9f389
|
|
BLAKE2b-256 checksum How to use checksums |
f48c11e7e24215e389ba12f9cf8f5075e3d75194eb6d765fedc33cf80bd3f77e
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Security for resilience-memory-utac 1.0.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.