Archimedes

Archimedes is an open-source Python framework designed to simplify complex modeling and simulation tasks, with the ultimate goal of making it possible to do practical hardware engineering with Python. It builds on the powerful symbolic computation capabilities of CasADi with an interface designed to be familiar to NumPy users.

Key features:

• NumPy-compatible array API with automatic dispatch

• Efficient execution of computational graphs in compiled C++

• Automatic differentiation with forward- and reverse-mode sparse autodiff

• Interface to “plugin” solvers for ODE/DAEs, root-finding, and nonlinear programming

• Automated C code generation for embedded applications

• JAX-style function transformations

• PyTorch-style hierarchical data structures for parameters and dynamics modeling

Quick Example

import numpy as np
import archimedes as arc

def f(x):
    return np.sin(x**2)

# Use automatic differentiation to compute df/dx
df = arc.grad(f)
np.allclose(df(1.0), 2.0 * np.cos(1.0))  # True

# Automatically generate C code
template_args = (0.0,)  # Data type for C function
arc.codegen(df, "grad_f.c", template_args)

Documentation

Getting Started

• Quickstart
• What is Archimedes?
• Getting Started

Core Concepts

• Under the Hood
• Working with PyTrees
• Structured Control Flow
• Hierarchical Design Patterns

Examples

• Multirotor Dynamics
• Deploying to Hardware

Reference

• 🔪 Quirks and Gotchas
• 📚 API Reference

Development

• Development Roadmap
• Community
• Licensing model

Indices and Tables

• Index

• Module Index

• Search Page