Get started¶
The quickest way to use MLatom is to run it online on the Aitomistic Hub or Aitomistic Lab@XMU — nothing to install. To run locally, just install MLatom — it pulls in the required dependencies automatically (including the PyTorch/TorchANI and geometry-optimization backends the AIQM2 example below uses). AIQM2 additionally needs the DFT-D4 program (via conda):
pip install -U mlatom
conda install -c conda-forge dftd4
export dftd4bin=$(which dftd4) # point MLatom at the dftd4 executable
From MLatom 3.25.0 on, any dftd4 version gives the same energies for AIQM1,
AIQM2, OMNI-P1 and the ANI -D4 models, because MLatom sets the D4 damping
parameters itself instead of selecting them by functional name. Pick
dftd4 3.5.0 if you need
Hessians, i.e. frequencies and thermochemistry.
See the installation guide for the full dependency list and other methods.
Quick start¶
Optimize the geometry of a water molecule with AIQM2 — an AI-enhanced quantum-mechanical method (native to MLatom, CHNO elements) that reaches beyond-DFT accuracy at semi-empirical cost.
Python API¶
import mlatom as ml
mol = ml.data.molecule.from_xyz_string('''3
O 0.00000 0.00000 0.11779
H 0.00000 0.75545 -0.47116
H 0.00000 -0.75545 -0.47116
''')
aiqm2 = ml.methods(method='AIQM2')
opt = ml.optimize_geometry(model=aiqm2, initial_molecule=mol).optimized_molecule
print(opt.energy) # optimized energy in hartree
To check your setup worked, the printed energy should be approximately:
-76.3838
Command line (input file)¶
The same calculation from the command line. Save the geometry as init.xyz:
3
O 0.00000 0.00000 0.11779
H 0.00000 0.75545 -0.47116
H 0.00000 -0.75545 -0.47116
and the input as geomopt.inp:
AIQM2 # method
geomopt # task: geometry optimization
xyzfile=init.xyz # input geometry
optxyz=opt.xyz # output geometry
then run:
mlatom geomopt.inp
The optimized geometry is written to opt.xyz, and the output reports the
optimized energy (≈ -76.3838 hartree). You can also
download geomopt.inp and
init.xyz.
Note
Prefer zero setup? Run these online on the Aitomistic Hub or Aitomistic Lab@XMU (both powered by Protomia) — no installation needed.