Metadata-Version: 2.1
Name: dinf
Version: 0.3.0
Summary: discriminator-based inference for population genetics
Home-page: https://github.com/RacimoLab/dinf
Author: Graham Gower
Author-email: graham.gower@gmail.com
License: MIT
Project-URL: Documentation, https://racimolab.github.io/dinf/
Project-URL: Source Code, https://github.com/RacimoLab/dinf
Project-URL: Bug Tracker, https://github.com/RacimoLab/dinf/issues
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: cyvcf2 (>=0.30.14)
Requires-Dist: emcee
Requires-Dist: numpy
Requires-Dist: jax
Requires-Dist: flax (>=0.5.2)
Requires-Dist: optax
Requires-Dist: msprime (>=1.0.4)
Requires-Dist: demes (>=0.2.1)
Requires-Dist: demesdraw
Requires-Dist: multiprocess
Requires-Dist: matplotlib
Requires-Dist: adjustText
Requires-Dist: scipy
Requires-Dist: rich

Dinf is discriminator-based inference for population genetics.
It uses a neural network to discriminate between a target dataset
and a simulated dataset.
Inference is done by finding simulation parameters that produce
data closely matching the target dataset.
Dinf provides a Python API for creating simulation models,
and a CLI for discriminator training and inference.

See the documentation for details.
https://racimolab.github.io/dinf/
