Chaotic attractors with python (Lorenz, Rossler, Rikitake etc.)
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Updated
Jan 13, 2024 - Python
Chaotic attractors with python (Lorenz, Rossler, Rikitake etc.)
Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"
Development version of phaseR, an R package for phase plane analysis of one- and two-dimensional autonomous ODE systems
A Predator-Prey-Grass multi-agent gridworld environment implemented with Farama's Gymnasium, PettingZoo and MOMAland. Featuring dynamic spawning and deletion and partial observability of agents.
Library to conduct experiments in population dynamics.
Competitive Lotka–Volterra equations, solved using Runge-Kutta methods. Four dimensional system.
Matlab Toolbox for Simulation, Analysis, and Design of Stable Heteroclinic Channel Networks
1-D numerical model, that simulates the vertical coralgal growth patterns observed in a drill core
Introduction to Numerical Methods / Ordinary Differential Equations
Software to set up and solve a Lotka Volterra system for n species. The Prey-Predator case, the 2 Preys-1 Predator and many other simpler models can be easily recovered from this general framework. Allows the use from Python console.
some simulation examples using phoenix live view
A curated collection of mathematical models spanning various disciplines, offering insights and tools for analysis, simulation, and understanding complex phenomena.
Stochastic implementation of a Lotka-Volterra competition model extended to multidimensional niche spaces (published in 10.1103/PhysRevE.91.052107)
An educational tool for understanding ecological models of population dynamics
Dataset for predator-prey interaction
study of nonlinear models describing populations.
Various ODEs
Going through the tutorials for integrating PyMC with ODEs
This Socio-Ecological Model (SEM) is designed to assess the interconnected impacts of economic, social, and environmental factors within a specific system. The model uses real-time data on population, GDP, energy consumption, and climate change to predict future development trends. Simulation results enable policymakers to evaluate.
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