stopro — Elementary Stochastic Processes

stopro is a small Python library for generating and simulating common (multivariate) stochastic processes.

Currently included processes:

1. Wiener process
2. Ornstein–Uhlenbeck process
3. Integrated Ornstein–Uhlenbeck process
4. Exponential Ornstein–Uhlenbeck process
5. Geometric Brownian Motion
6. Colored Geometric Brownian Motion
7. Gillespie Replicator
8. Kimura Replicator
9. White Replicator
10. Colored Replicator
11. Multispecies Moran process
    (discrete particle kinetics & diffusion approximation)
12. Competitive Lotka–Volterra process
    (discrete particle kinetics & diffusion approximation)

Examples and documentation are provided as Jupyter notebooks.

Quick start (recommended)

This project uses uv, a fast Python package manager and virtual environment tool. You need to install uv on your system first. When that's done:

git clone https://github.com/dirkbrockmann/stopro.git
cd stopro
make notebook

Using stopro in your own code

import stopro

Installation via pip

You can now install stopro directly from PyPI:

pip install stopro

To install the latest development version from source:

pip install git+https://github.com/dirkbrockmann/stopro.git

Or clone and work with the code locally:

git clone https://github.com/dirkbrockmann/stopro.git
cd stopro
pip install -e .

Running the examples

To run the Jupyter notebook examples, install stopro with the extra dependencies:

pip install "stopro[examples]"

This will install all required packages for the example notebooks.

Running the benchmarks

To run the Jupyter notebook examples, install stopro with the extra dependencies:

pip install "stopro[bench]"

This will install all required packages for the example notebooks.

License

MIT