Metadata-Version: 2.4
Name: complexsphere
Version: 1.0.0
Summary: Atmospheric Disorder Index (ADI) — multi-node entropy, relativistic kinetics, PMFG topology, and ER=EPR temporal analogue analysis.
License: Apache-2.0
Project-URL: Repository, https://github.com/inc-research/complexsphere
Keywords: atmospheric science,entropy,information geometry,climate analysis,PMFG,Shannon entropy,Riemannian distance,Granger causality,temporal analogue
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Atmospheric Science
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.21
Requires-Dist: pandas>=1.3
Requires-Dist: scipy>=1.7
Requires-Dist: requests>=2.25
Requires-Dist: networkx>=2.6
Requires-Dist: statsmodels>=0.13
Provides-Extra: dev
Requires-Dist: pytest>=7.0; extra == "dev"
Requires-Dist: pytest-cov; extra == "dev"
Requires-Dist: jupyter; extra == "dev"
Requires-Dist: matplotlib>=3.4; extra == "dev"
Requires-Dist: black; extra == "dev"
Requires-Dist: ruff; extra == "dev"
Dynamic: license-file

ComplexSphere
Information-Theoretic & Relativistic Climate Dynamics for Python

ComplexSphere is a quantitative physics framework designed to detect non-stationary structural phase shifts in meteorological and climatological data.

Standard Bayesian models and rolling historical averages frequently fail to anticipate complex thermodynamic breakouts (e.g., localized heat traps and grid demand spikes). ComplexSphere solves this by applying principles of Information Geometry, Relativistic Kinetics, and Quantum Information Theory (ER=EPR) to standard weather time-series, allowing researchers to measure the velocity and memory of a regional climate system.
