by Kevin F. Garrity
This is a python wrapper for the ThreeBodyTB.jl Julia package, which runs two- and three-body tight-binding calculations for materials.
Using the Julia version directly is the primary method for running the code. However, I recognize that many materials science codes are written in python. Therefore, I have created this wrapper to help people with no Julia knowledge run the code using the PyJulia interface.
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Clone this distribution.
git clone https://github.com/kfgarrity/ThreeBodyTB_python.git -
Run the installation
python3 install.py
Note that this can take a while and may use significant disk space. The code will, if necessary, a) download & install Julia b) download & install ThreeBodyTB.jl, and c) create a system image for fast loading.
- Import TB3.py
Example usage :
>>> import TB3
>>> import numpy as np
>>> A = np.eye(3) * 5.0
>>> coords = np.zeros((1,3))
>>> c = TB3.jl.makecrys(A, coords, ["Li"])
>>> energy, tbc, flag = TB3.jl.scf_energy(c)
For main documentation of ThreeBodyTB.jl, see 
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Julia can take advantage multiple threads. Try setting the environment variable below as appropriate for your machine.
JULIA_NUM_THREADS=8 export JULIA_NUM_THREADS -
Note that despite using pre-compilation where possible, some functions will run faster the second time you run them due to the jit.
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Note that you must delete the system image if you want to update the ThreeBodyTB.jl code and re-run the installation.