A python implementation of MBAR and TRAM and their respective stochastic aproximators SAMBAR and SATRAM.
- Clone the repository from github
[email protected]:noegroup/SATRAM.git
- Navigate to the cloned repository and run the installation script
cd satram
python setup.py install
- Validate your installation by running all tests in the repository with the command
pytest
Use the 4-state test dataset to generate input for TRAM.
from examples.datasets import toy_problem
ttrajs, dtrajs, bias_matrices = toy_problem.get_tram_input()
Use the ThermodynamicEstimator
class to estimate the free energies from the
dataset. The default solver_type
is "SATRAM"
.
from satram import ThermodynamicEstimator
estimator = ThermodynamicEstimator()
estimator.fit((ttrajs, dtrajs, bias), solver_type="SATRAM")
The estimated free energies can be accessed as
estimator.free_energies
More extensive examples can be found in the jupyter notebooks in the examples folder.
- pytorch
- scipy
- deeptime (v0.4.1)
Copyright (c) 2022, NoeGroup
Project based on the Computational Molecular Science Python Cookiecutter version 1.6.