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Formally read as Python-Natural-Orbital-Functionals, PyNOF is based on the original DoNOF software written in Fortran by Prof. Mario Piris, but it takes advantage of the Python capabilities such as optimizers, vectorization via numpy and gpu compatibility via cupy.
We recommend to perform the installation inside an Anaconda enviroment:
conda create -y -n pynof
conda activate pynof
PyNOF uses Psi4 for integrals, so it is necessary to install it first:
conda install -y psi4 -c conda-forge/label/libint_dev -c conda-forge
then, you can simply install PyNOF using pip
pip install pynof
[Optional] Integrals transformations can benefit from a GPU. If available, just install cupy
conda install -y -c conda-forge cupy
A pynof input has the following parts:
- Import pynof
- A declaration of the molecule geometry
- A parameter object
- The calculation instruction
import pynof
mol = pynof.molecule("""
0 1
O 0.0000 0.000 0.116
H 0.0000 0.749 -0.453
H 0.0000 -0.749 -0.453
""")
p = pynof.param(mol,"cc-pvdz")
p.ipnof=8
p.RI = True
#p.gpu = True
E,C,gamma,fmiug0 = pynof.compute_energy(mol,p)
If everything worked, the job may be executed by
python -u test_energy.py
Note. The first run may be slightly slow due to jit precompilation.
First, clone PyNOF from github and change to the project directory
git clone https://github.com/felipelewyee/PyNOF.git
cd PyNOF
In the PyNOF folder, execute the following code
conda create -y -n pynof
conda activate pynof
conda install -y psi4 -c conda-forge/label/libint_dev -c conda-forge
conda install -y -c conda-forge cupy # Optional
pip install build
python -m build && cd dist && pip install pynof*.whl && cd ..
The PyNOF code has been built by Juan Felipe Huan Lew Yee, Lizeth Franco Nolasco, Iván Alejandro Rivera and Roberto Rojas Hernández under supervision of Jorge Martín del Campo Ramírez and Mario Piris. We also acknowledge contributions from Rodrigo Vargas Hernández and José M. Mercero.