A modern, high-performance Python framework designed to provide a cohesive, end-to-end environment for the study of dynamical systems.
A dynamical system is a mathematical concept used to describe any system whose state evolves over time according to a fixed set of rules. This framework is now fundamental across science and engineering, modeling phenomena from planetary orbits to the intricate firing patterns of neurons in the brain. The core components of these models are state variables, which define the system's condition at any instant, and a set of equations (the "dynamics") that dictate how these variables change from one moment to the next. A key feature of many such systems is the presence of feedback loops, where the current state influences its own future rate of change. This can lead to complex, non-intuitive behavior, including deterministic chaos — the discovery that even simple, deterministic rules can generate seemingly random and unpredictable outcomes.
Since many dynamical systems cannot be solved with simple algebraic formulas, numerical simulation has become an indispensable tool. This has led to the development of specialized software to explore these systems. DynamiXplore is a modern, open-source Python library designed to provide a comprehensive and high-performance toolkit for the numerical exploration of continuous and discrete dynamical systems.
-
🚀 High-Performance Rust Core The computational backend is written in Rust to deliver performance comparable to C or Fortran. This allows for the simulation of complex, high-dimensional systems and the analysis of long time-series data on a scale that would be infeasible in pure Python. All heavy computations, from integration to statistical analysis, happen at native speed.
-
🐍 Unified & Pythonic API Interact with the powerful Rust core through a clean, intuitive Python API. The library is designed to feel familiar to users of NumPy, SciPy, and Pandas, allowing for seamless integration into the existing scientific Python ecosystem. Define your system with a simple Python function and let
DynamiXplorehandle the high-performance execution. -
📈 Comprehensive Analysis Suite Go beyond simple simulation.
DynamiXploreprovides a robust suite of tools to quantify the dynamics of your system. Natively calculate Lyapunov exponents to measure chaos, estimate fractal dimensions to characterize attractor geometry, and compute various entropy measures (Permutation, Approximate) to analyze complexity and predictability. -
🌐 Publication-Ready Interactive Visualizations Generate insightful, interactive plots with a single line of code using the Plotly backend. Effortlessly create phase portraits, recurrence plots, and bifurcation diagrams. The ability to zoom, pan, and rotate plots allows for a much deeper exploration of the complex, often fractal, structures of dynamical attractors.
This project is licensed under the MIT License.