promptbind.data.data.FABindDataSet

class promptbind.data.data.FABindDataSet(root, data=None, protein_dict=None, compound_dict=None, proteinMode=0, compoundMode=1, add_noise_to_com=None, pocket_radius=20, contactCutoff=8.0, predDis=True, args=None, use_whole_protein=False, compound_coords_init_mode=None, seed=42, pre=None, transform=None, pre_transform=None, pre_filter=None, noise_for_predicted_pocket=5.0, test_random_rotation=False, pocket_idx_no_noise=True, use_esm2_feat=False)

__init__(root, data=None, protein_dict=None, compound_dict=None, proteinMode=0, compoundMode=1, add_noise_to_com=None, pocket_radius=20, contactCutoff=8.0, predDis=True, args=None, use_whole_protein=False, compound_coords_init_mode=None, seed=42, pre=None, transform=None, pre_transform=None, pre_filter=None, noise_for_predicted_pocket=5.0, test_random_rotation=False, pocket_idx_no_noise=True, use_esm2_feat=False)

Methods

__init__(root[, data, protein_dict, ...])
download()	Downloads the dataset to the self.raw_dir folder.
get(idx)	Gets the data object at index idx.
get_summary()	Collects summary statistics for the dataset.
index_select(idx)	Creates a subset of the dataset from specified indices idx.
indices()
len()	Returns the number of data objects stored in the dataset.
print_summary([fmt])	Prints summary statistics of the dataset to the console.
process()	Processes the dataset to the self.processed_dir folder.
shuffle([return_perm])	Randomly shuffles the examples in the dataset.
to_datapipe()	Converts the dataset into a torch.utils.data.DataPipe.

Attributes

has_download	Checks whether the dataset defines a download() method.
has_process	Checks whether the dataset defines a process() method.
num_classes	Returns the number of classes in the dataset.
num_edge_features	Returns the number of features per edge in the dataset.
num_features	Returns the number of features per node in the dataset.
num_node_features	Returns the number of features per node in the dataset.
processed_dir
processed_file_names	The name of the files in the self.processed_dir folder that must be present in order to skip processing.
processed_paths	The absolute filepaths that must be present in order to skip processing.
raw_dir
raw_file_names	The name of the files in the self.raw_dir folder that must be present in order to skip downloading.
raw_paths	The absolute filepaths that must be present in order to skip downloading.