manifold-mcmc-for-diffusions/pyproject.toml at main · thiery-lab/manifold-mcmc-for-diffusions · GitHub

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[build-system]
build-backend = "setuptools.build_meta"
requires = ["setuptools >= 77.0.3"]

[project]
name = "sde"
version = "0.1.1"
description = "Utilities for inference in SDE models using Mici"
readme = "README.md"
requires-python = ">=3.11"
keywords = [
    "stochastic differential equation",
    "diffusion",
    "Bayesian inference",
    "Monte Carlo",
    "Markov chain Monte Carlo",
    "MCMC"
]
license = "MIT"
license-files = ["LICENSE"]
authors = [{name = "Matt Graham"}]
classifiers = [
  "Operating System :: OS Independent",
  "Development Status :: 4 - Beta",
  "Programming Language :: Python",
  "Intended Audience :: Science/Research",
  "Topic :: Scientific/Engineering",
  "Programming Language :: Python :: 3",
  "Programming Language :: Python :: 3 :: Only",
  "Programming Language :: Python :: 3.11",
  "Programming Language :: Python :: 3.12",
  "Programming Language :: Python :: 3.13",
]
dependencies = [
  "mici~=0.3",
  "symnum~=0.2",
  "numpy~=2.2",
  "sympy~=1.8",
  "jax~=0.6"
]

[project.optional-dependencies]
notebook = [
  "matplotlib~=3.9",
  "arviz~=0.21",
  "corner~=2.2",
  "jupyter~=1.1"
]
scripts = [
  "matplotlib~=3.9",
  "arviz~=0.21",
  "pandas~=2.2",
]

[project.urls]
repository = "https://github.com/thiery-lab/manifold-mcmc-for-diffusions.git"