Chaos Theory Python Packages | PyRank

mechanicsdsl-core

Domain-specific language and compiler for physical systems. Write a Lagrangian, get a simulation. Twelve code generation backends, built on SymPy.

497 2 0

chaos-atlas

Interactive explorer for chaotic dynamical systems, strange attractors, bifurcations, Lyapunov exponents, fractals, and coupled-map lattice spatiotemporal patterns

233 0 0

tsa-course

Book and material for the course "Time series analysis with Python" (STA-2003)

224 285 65

hidden-attractors-fo

`hidden-attractors-fo` provides reproducible workflows for seed generation, numerical continuation, simulation, diagnostics, and validation of hidden-attractor candidates in scalar Lur’e systems.

221 0 0

hundun

🦋 hundun is a python library for the exploration of chaos.

219 13 1

pyzeta

Numerical project written (mostly) in Python that is all about (dynamical) zeta functions and their application to the calculation of (quantum and classical) resonances.

207 1 3

chaos-intelligence

A Layer API built on top of `tensorflow.keras` Functional API. Allows application of chaos theory deterministic functions to neural networks.

141 0 0

lorenzpy

A Python package to simulate and measure chaotic dynamical systems.

131 0 1

pattingalloang

JAX-accelerated Python library for simulating and analyzing the Aizawa strange attractor with comprehensive chaos metrics.

93 0 0

frequency-max-power

Feature extraction and prediction of human neural signals, using chaos theory, dynamical systems theory, various physics/maths theories, RNN, CNN, transformers

93 39 10

spectral-edge-density

Feature extraction and prediction of human neural signals, using chaos theory, dynamical systems theory, various physics/maths theories, RNN, CNN, transformers

80 39 10

stftsignal

Feature extraction and prediction of human neural signals, using chaos theory, dynamical systems theory, various physics/maths theories, RNN, CNN, transformers

77 39 10

spectral-centroids

Feature extraction and prediction of human neural signals, using chaos theory, dynamical systems theory, various physics/maths theories, RNN, CNN, transformers

77 39 10

transfer-entropy-all-signals

Feature extraction and prediction of human neural signals, using chaos theory, dynamical systems theory, various physics/maths theories, RNN, CNN, transformers

70 39 10

spectral-entropy-signals

Feature extraction and prediction of human neural signals, using chaos theory, dynamical systems theory, various physics/maths theories, RNN, CNN, transformers

59 39 10

transfer-entropy-hemispheric

Feature extraction and prediction of human neural signals, using chaos theory, dynamical systems theory, various physics/maths theories, RNN, CNN, transformers

55 39 10

phase-space-2d

Feature extraction and prediction of human neural signals, using chaos theory, dynamical systems theory, various physics/maths theories, RNN, CNN, transformers

55 39 10

phase-space-3d

Feature extraction and prediction of human neural signals, using chaos theory, dynamical systems theory, various physics/maths theories, RNN, CNN, transformers

54 39 10

mfdfa1000hz

Feature extraction and prediction of human neural signals, using chaos theory, dynamical systems theory, various physics/maths theories, RNN, CNN, transformers

53 39 10

transfer-entropy-regional

Feature extraction and prediction of human neural signals, using chaos theory, dynamical systems theory, various physics/maths theories, RNN, CNN, transformers

52 39 10

welchspsd

Feature extraction and prediction of human neural signals, using chaos theory, dynamical systems theory, various physics/maths theories, RNN, CNN, transformers

49 39 10

lyapynov

Python package to compute Lyapunov exponents, covariant Lyapunov vectors (CLV) and adjoints of a dynamical systems.

40 34 7