Bayesian Fast Linear algebra sUbspace eXtraction in JAX
Reason this release was yanked:
this was unncessary
Project description
BayesFlux
BayesFlux is a JAX Python package that provides Fast Linear algebra sUbspace eXtraction for Bayesian inverse problems built off https://github.com/joshuawchen/randLAX.
Features
- Active Subspace for parameter dimension reduction
- Informative Output Subspace for data dimension reduction
Installation
Core Installation (JAX-only functionality)
You can install the core BayesFlux package using pip:
pip install bayesflux
This installs the JAX-based functionality only and does not require Fenics or hippylib.
Installation with hippylib Support (Requires Fenics)
Some BayesFlux functionality depends on hippylib, which requires Fenics 2019.1.
Fenics has system-level dependencies and cannot be reliably installed via pip alone. You must first create a conda environment.
Step 1 — Create a Fenics environment
conda create -n fenics-2019.1_env -c conda-forge fenics==2019.1.0
conda activate fenics-2019.1_env
Step 2 — Install BayesFlux with the hippylib extra
pip install bayesflux[hippylib]
This installs:
- hippylib
- hickle
- bayesflux
Make sure the conda environment is activated before running pip install.
For Developers
If your software depends on BayesFlux with hippylib functionality, declare the dependency in your pyproject.toml as:
dependencies = [
"bayesflux[hippylib]>=<minimum_version>"
]
However, your users must still create the Fenics conda environment before installing your software:
conda create -n fenics-2019.1_env -c conda-forge fenics==2019.1.0
conda activate fenics-2019.1_env
pip install your_package
Important: pip cannot install Fenics. Any software depending on bayesflux[hippylib] must document the required conda environment setup.
Requirements
- Python 3.9
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