dynlib 0.37.10

A dynamical systems simulation library.

dynlib

Dynlib is a Python library for modeling, simulating, and analyzing dynamical systems.
Models are described in a TOML-based DSL (Domain-Specific Language) and then executed through a unified runtime—so you can iterate on solvers, parameters, and analyses without rewriting the same Numpy/Matplotlib plumbing for every experiment.

With dynlib, you can define or tweak a model, try different solvers/settings, and visualize behavior quickly. It can be used with notebooks for teaching and demonstration purposes. Created models can be kept in an organized manner and can be shared easily.

Project status

Dynlib is alpha-stage software. APIs may change, and numerical edge cases or bugs can surface. Treat results as exploratory unless you validate them (e.g., alternative steppers, tighter tolerances, smaller step sizes, or analytical checks). If you find suspicious behavior, please open an issue with a minimal reproducer.

Highlights

Modeling (TOML DSL)

• Define ODEs and discrete-time maps using a declarative TOML spec.
• Express equations, parameters, state initialization, and metadata in a consistent format.
• Support for events, auxiliary variables, functions/macros, and lagging where applicable.
• Built-in model registry and URI loading (including builtin://... models).

Simulation runtime

• Multiple stepper families:
  • ODE: Euler, RK4, RK45, Adams–Bashforth (AB2/AB3), and implicit methods (e.g., SDIRK/TR-BDF2).
  • Maps: dedicated discrete runner(s) including integer-safe modes.
• Runner variants and session introspection utilities for iterative workflows.
• JIT acceleration via Numba (optional but highly recommended), plus disk caching for compiled runners.
• Snapshots and resume support for long or staged simulations.
• Selective recording and result APIs designed for downstream analysis.

Analysis

Built-in analysis utilities for common dynamical-systems tasks:

• Bifurcation and post-processing utilities
• Basins of attraction (auto/known variants)
• Lyapunov exponent analysis (including runtime observer support)
• Fixed point / Equilibria detection
• Manifold tracing tools (currently limited to 1D manifolds)
• Homoclinic/Heteroclinic orbit tracing and detection
• Parameter sweep helpers and trajectory/post-analysis utilities

Vector fields & plotting (on top of Matplotlib)

Dynlib includes plotting helpers tailored for dynamical systems rather than raw Matplotlib boilerplate:

• Vector field evaluation utilities and phase-portrait helpers
• Plot modules for basins, bifurcation diagrams, manifolds, and general dynamics
• Higher-level plotting conveniences: themes, facets, decorations, and export helpers
• Vector field animation support

CLI

Dynlib ships a small CLI (Command Line Interface) for convenience tasks such as model validation, listing steppers, and inspecting caches.
The CLI is not required for the Python API.

Prerequisites

• Python 3.10+
• Matplotlib for plots.
• Numpy for numerical calculations.
• Numba is highly recommended for JIT execution:
  • python -m pip install numba

Installation

• python -m pip install dynlib or
• python -m pip install -e . for editable installs from source

Quickstart

Sanity-check the CLI and validate a bundled model:

dynlib --version
dynlib model validate builtin://ode/lorenz.toml

Run a built-in model from Python (Lorenz system):

from dynlib import setup
from dynlib.plot import fig, series, export

sim = setup("builtin://ode/lorenz.toml", stepper="rk4")

sim.run(T=15.0, dt=0.01)
res = sim.results()

print("States:", res.state_names)
print("Final z:", res["z"][-1])

ax = fig.single()
series.plot(x=res.t, y=res["x"], ax=ax, label="x")
series.plot(x=res.t, y=res["z"], ax=ax, label="z", xlabel="time")
export.show()

Next: see the docs for defining your own TOML models, URI tags (proj://...), recording options, and analysis workflows (basins, bifurcation, Lyapunov, fixed points).

Documentation

Check this link for the project documentation:Documentation