mathrobo 0.0.4

basic mathematical library for robotics reserach

Mathrobo

Mathrobo is a Python library for robotics-oriented mathematical computation, including Lie group operations, spatial transformations, numerical differentiation/integration, and B-spline utilities.

Installation

Install the latest release from PyPI:

pip install mathrobo

If you use uv, you can add Mathrobo to your project with:

uv add mathrobo

Development install

For local development, clone the repository:

git clone https://github.com/MathRobotics/MathRobo.git
cd MathRobo

Sync the development environment from pyproject.toml and uv.lock:

uv sync --extra dev

Install the package in editable mode:

uv pip install -e .

Examples

Refer to the examples in the examples folder, where you can find Jupyter notebooks and scripts demonstrating various use cases of the library.

Usage

You can also work with spatial transformations using the SE3 class. The following snippet creates a 90 degree rotation around the Z axis with a translation, applies the transformation to a point and then inverts it:

import numpy as np
import mathrobo as mr

# Rotation of 90 deg about Z and translation of 1 m along X
rot = mr.SO3.exp(np.array([0.0, 0.0, 1.0]), np.pi / 2)
T = mr.SE3(rot, np.array([1.0, 0.0, 0.0]))

point = np.array([0.0, 1.0, 0.0])
transformed = T @ point
recovered = T.inv() @ transformed

print(transformed)
print(recovered)

Here is a quick example that computes the numerical gradient of a simple function:

import numpy as np
import mathrobo as mr

f = lambda x: np.sum(x**2)
x = np.array([1.0, 2.0, -3.0])
grad = mr.numerical_grad(x, f)
print(grad)

You can also perform numerical integration using the Gaussian quadrature helper gq_integrate:

import numpy as np
import mathrobo as mr

f = lambda s: np.array([np.sin(s)])
val = mr.gq_integrate(f, 0.0, np.pi, digit=5)
print(val)  # ~ 2.0

For spline trajectories, SciPy's BSpline can be used to create and evaluate a curve:

import numpy as np
from scipy.interpolate import make_interp_spline

t = np.array([0, 1, 2, 3])
points = np.array([0.0, 1.0, 0.0, 1.0])
spl = make_interp_spline(t, points, k=3)

ts = np.linspace(0, 3, 20)
ys = spl(ts)
print(ys)

Running Tests

Run the test suite with uv:

uv run --extra dev pytest

Changelog

• Removed SymPy as a runtime dependency. Mathrobo now supports the NumPy and JAX code paths only, and uv.lock no longer includes SymPy or mpmath.

Contributing

Contributions are welcome! Feel free to report issues, suggest features, or submit pull requests.

License

This project is licensed under the MIT License.