Get started

To get started, we provide show how to use different capabilities of MLatom on an example of geometry optimization.

Preparation

For starting, you need the initial geometry guess, which you can download as the file init.xyz or copy-paste from:

8

C             0.0000000000000           0.0000000000000           0.7608350816719
H            -0.0000000000000           1.0182031026887           1.1438748775511
H             0.8817897531403          -0.5091015513443           1.1438748775511
H            -0.8817897531403          -0.5091015513443           1.1438748775511
C            -0.0000000000000          -0.0000000000000          -0.7608350816719
H            -0.8817897531403           0.5091015513443          -1.1438748775511
H             0.8817897531403           0.5091015513443          -1.1438748775511
H            -0.0000000000000          -1.0182031026887          -1.1438748775511

Using input file

You can watch a short video demonstrating how to use the command-line options or input file to run some calculations on the XACS cloud.

MLatom can be run in the command line format using the command-line options or input file. To optimize geometry using the ANI-1ccx method, you can use the input file geomopt.inp which you can download or copy-paste from:

ANI-1ccx                # pre-trained model
geomopt                 # requests geometry optimization
xyzfile=init.xyz        # initial geometry guess
optxyz=opt.xyz          # file with optimized geometry

Then run MLatom simulations using this input file as:

mlatom geomopt.inp &> geomopt.out

The program will print out the relevant calculation information to the output file geomopt.out.

Using PyAPI

You can watch a short video demonstrating how to use PyAPI on the XACS cloud.

Below is an example of Python script using MLatom to optimize geometry at ANI-1ccx – the simulation task the same as in the above example with command-line execution:

import mlatom as ml                                                                         # import MLatom module.
ani = ml.models.methods(method='ANI-1ccx')                                                  # denfine an ANI-1cxx model.
init_mol = ml.data.molecule.from_xyz_file('init.xyz')                                       # load the molecular structure.
final_mol = ml.optimize_geometry(model=ani, initial_molecule=init_mol).optimized_molecule   # the optimized structure can be obtained by command.
final_mol.xyz_coordinates                                                                   # we can see the coordinates of the last molecule.
print(final_mol.get_xyz_string())                                                           # print the coordinates in ".xyz" format.
final_mol.write_file_with_xyz_coordnates(filename='final.xyz')                              # save it in "final.xyz".