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b/experiments/test_1/moboqm9_results_soap.png differ diff --git a/experiments/test_1/script.py b/experiments/test_1/script.py index e4bb158..197f8c2 100644 --- a/experiments/test_1/script.py +++ b/experiments/test_1/script.py @@ -22,7 +22,7 @@ moboqm9.run_optimization() fig = plot_results(moboqm9.dataframe, [True, True]) fig.tight_layout() -plt.savefig("moboqm9_results.png") +plt.savefig("moboqm9_results_soap.png") plt.show() -moboqm9.dataframe.to_csv("moboqm9_results.csv") +moboqm9.dataframe.to_csv("moboqm9_results_soap.csv") diff --git a/src/data/soap_featurizer.py b/src/data/soap_featurizer.py new file mode 100644 index 0000000..ffcdc51 --- /dev/null +++ b/src/data/soap_featurizer.py @@ -0,0 +1,63 @@ +from dscribe.descriptors import SOAP +from ase import db +from pathlib import Path +import numpy as np + +def get_species(indices): + """ + Get the species for the MOBOQM9 model. + + args: + indices: Indices for the MOBOQM9 model. + + returns: + int: Maximum number of atoms for the MOBOQM9 model. + """ + species = [] + with db.connect(str(Path(__file__).parent / "QM9_data.db")) as qm9: + for i, row in enumerate(qm9.select()): + if i in indices: + atoms = row.toatoms() + species = list(set(atoms.get_chemical_symbols() + species)) + return species + +def get_soap(indices, targets): + """ + Gets the SOAP fingerprints for the MOBOQM9 model. + + args: + indices: Indices for the MOBOQM9 model. + targets: Targets for the MOBOQM9 model. + + returns: + features: Features for the MOBOQM9 model. + targets: Targets for the MOBOQM9 model. + """ + species = get_species(indices) + soap = SOAP( + species=species, + r_cut = 3.0, + n_max = 4, + l_max = 3, + ) + + atoms_list, computed_targets = [], [] + with db.connect(str(Path(__file__).parent / "QM9_data.db")) as qm9: + for i, row in enumerate(qm9.select()): + if i in indices: + is_OK = True + for target in targets: + try: + row[target] + except AttributeError: + is_OK = False + break + if is_OK: + atoms_list.append(row.toatoms()) + target_list = [] + for target in targets: + target_list.append(row[target]) + computed_targets.append(target_list) + features = soap.create(atoms_list, n_jobs=4) + + return features, np.array(computed_targets) \ No newline at end of file