Index

A

Autoencoder (class in ml.nn)

C

CGCNN (class in ml.gnn) chem.base module chem.crystal module chem.formula module

chem.molecule module core.env module core.sys module

D

data.base module data.crystal module data.formula module data.graph module

data.molecule module data.vector module Dataset (class in data.base) dec() (Autoencoder method) denormalize() (VectorDataset method)

E

enc() (Autoencoder method)

even_samples() (in module chem.crystal)

F

FCNN (class in ml.nn) fit() (Autoencoder method) (FCNN method) (GNN method) (SKLearnModel method) form_to_vec() (in module chem.formula)

FormDataset (class in data.formula) forward() (Autoencoder method) (CGCNN method) (FCNN method) (GAT method) (GCN method) (GIN method)

G

GAT (class in ml.gnn) GCN (class in ml.gnn) get_atom_info() (in module chem.crystal) get_batch_sizes() (in module ml.util) get_bond_info() (in module chem.crystal) get_crystal_graph() (in module chem.crystal) get_data_loader() (in module ml.util) get_error_dist() (in module util.analysis) get_init_lrs() (in module ml.util) get_loss_func() (in module ml.util)

get_model() (in module ml.util) get_mol_graph() (in module chem.molecule) get_one_hot_feat() (in module util.preprocessing) get_optimizer() (in module ml.util) get_split_idx() (in module util.preprocessing) get_target_dist() (in module util.analysis) GIN (class in ml.gnn) GNN (class in ml.gnn) gpu() (PyTorchModel method) GraphDataset (class in data.graph)

I

impute() (in module util.preprocessing)

L

load() (PyTorchModel method) (SKLearnModel method) load_dataset() (in module data.crystal) (in module data.formula) (in module data.molecule) (in module data.vector)

load_elem_feats() (in module chem.base) load_mendeleev_feats() (in module chem.base)

M

ml.base module ml.gnn module ml.nn module ml.transfer_learning module ml.util module Model (class in ml.base) module chem.base chem.crystal chem.formula chem.molecule core.env core.sys data.base data.crystal data.formula data.graph data.molecule data.vector ml.base ml.gnn ml.nn ml.transfer_learning ml.util util.analysis util.optimization util.preprocessing util.visualization

N

n_data() (GraphDataset method) n_edge_feats() (GraphDataset method)

n_graphs() (GraphDataset method) n_node_feats() (GraphDataset method) normalize() (VectorDataset method)

O

optimize() (in module util.optimization)

P

parse_form() (in module chem.formula) plot_embeddings() (in module util.visualization) plot_error_dist() (in module util.visualization) plot_pred_result() (in module util.visualization) plot_target_dist() (in module util.visualization)

predict() (Autoencoder method) (FCNN method) (GNN method) (SKLearnModel method) PyTorchModel (class in ml.base)

R

rbf() (in module chem.crystal) read_data_file() (in module data.base)

remove_outliers() (VectorDataset method) run_ml_model() (in module util.optimization)

S

save() (PyTorchModel method) (SKLearnModel method) save_eval_results() (in module ml.util) save_interpretation() (in module ml.util)

set_gpu_runnable() (in module core.sys) SKLearnModel (class in ml.base) split() (FormDataset method) (GraphDataset method) (VectorDataset method)

T

tl_fine_tuning() (in module ml.transfer_learning) tl_retrain_head() (in module ml.transfer_learning) to_tensor() (VectorDataset method) training (Autoencoder attribute) (CGCNN attribute) (FCNN attribute) (GAT attribute) (GCN attribute) (GIN attribute) (GNN attribute) (PyTorchModel attribute)

U

util.analysis module util.optimization module

util.preprocessing module util.visualization module

V

VectorDataset (class in data.vector)