• Create a specific conda environment (for testing purposes):

  1. Navigate to the scripts folder, where the bash script install.sh is present.
  2. Type the command chmod +x install.sh and execute source ./install.sh.
  3. Make sure you are in the correct env.: conda activate test_moda every time you use it.ç

• Install in your usual conda environment (via pip):

  1. Navigate to the scripts folder.
  2. Find the requirements.txt file.
  3. Make sure you are in the right conda env.: conda activate myenv
  4. Execute pip install -r requirements.txt.
  5. Compile the Fortran95 files cd ./MLcool/descriptors and type python -m numpy.f2py -c optimized_kernels.f95 -m optimized_kernels

This repository contains a comprehensive dataset documenting the structures and magnetic exchange couplings, denoted as J_AB, across all datasets considered in this project. The data is neatly organized according to the respective datasets in a hierarchical folder structure for easy navigation and access.

The ./OTHER/ directory consolidates both the THIL and PHYL datasets. For individual structural data, browse through the ./OTHER/XYZ/XXX/ directory where you'll find conformers stored in .xyz format. Each conformer is named as stepN.xyz, where 'N' represents the angle θ associated with each conformer in the rigid body rotational scan.

Magnetic exchange coupling data (J_AB) for this dataset can be located within the ./OTHER/couplings/ directory. The respective .dat files are labeled as PHYL.dat and THIL.dat.

The ./TTTA/ directory is reserved for the TTTA dataset and follows a structure similar to the ./OTHER/ directory.

In the ./TTTA/XYZ/ directory, you will find subfolders named HT-XXX-DACB. Here, 'XXX' corresponds to the temperature value (either 300 or 250), while 'A' and 'B' indicate specific indices denoting the column (C) and dimer (D) positions. Each of these folders contains .xyz files named STEPN.xyz, where 'N' acts as a placeholder identifying each sample during the AIMD simulation.

For magnetic exchange coupling data (J_AB) related to this dataset, navigate to the ./TTTA/couplings/ directory. This directory houses HT-XXX-DACB.dat files, each corresponding to a file in the ./TTTA/XYZ/ directory.

Find the files in jupyter notebook (MODA_tutorial.ipynb) or in pdf format (MODA_tutorial.pdf) with a tutorial to an end-to-end case study showing how to use MODA.