def load_datasets_nodelabel(names):
"""
Loads the graph datasets DD, ENZYMES and NCI1, CiteSeer_Eval,CiteSeer_Train,Cora_Eval,Cora_Train and its labels.
:params: list of dataset names to load
:return: list of dataset names, list of loaded graphs for all datasets,
node attributes for loaded graphs for all datasets
"""
# load datasets
datasets = []
if "cs_eval" in names:
datasets.append(Parser('datasets/CiteSeer_Eval'))
if "cs_train" in names:
datasets.append(Parser('datasets/CiteSeer_Train'))
if "co_eval" in names:
datasets.append(Parser('datasets/Cora_Eval'))
if "co_train" in names:
datasets.append(Parser('datasets/Cora_Train'))
# convert datasets into lists graphs, labels
datasets = [dataset.parse_all_graphs() for dataset in datasets]
attr_sets = [[get_node_attributes(graph) for graph in graphs] for graphs in datasets]
labels = [[get_node_labels(graph) for graph in graphs] for graphs in datasets]
# attr_sets is a list of length n, where n is the number of datasets. Then attr[0] contains a list of all node attributes
# for dataset 0. Thus attr[0][0] contains the actual node attribute matrix (X^0) for the graph of fataset 0.
return names, datasets, attr_sets, labels
def load_dataset_nodelabel(name):
"""
Loads one of the graph datasets DD, ENZYMES and NCI1, CiteSeer_Eval,CiteSeer_Train,Cora_Eval,Cora_Train and its labels.
:params: name of dataset to load
:return: list of loaded graphs, list of node features, list of labels
"""
if "cs_train" == name:
dataset = Parser('datasets/CiteSeer_Train')
elif "cs_eval" == name:
dataset = Parser('datasets/CiteSeer_Eval')
elif "co_train" == name:
dataset = Parser('datasets/Cora_Train')
elif "co_eval" == name:
dataset = Parser('datasets/Cora_Eval')
else:
raise ValueError(
f"Given dataset name {name} is not a valid node dataset.")
dataset = dataset.parse_all_graphs()
# convert datasets into lists graphs, labels
features = [get_node_attributes(graph) for graph in dataset]
labels = [get_node_labels(graph) for graph in dataset]
return dataset, features, labels
def load_dataset(name):
"""
Loads and parses one dataset.
:params: name of dataset to load
:return: list of loaded graphs
"""
dataset = Parser(os.path.join('datasets', name))
graphs = dataset.parse_all_graphs()
return graphs
def load_link_graph(name):
"""
Loads the singular graph contained in the datasets Facebook and PPI.
:params: name of dataset to load
:return: singular graph
"""
dataset = Parser(os.path.join('datasets', name))
graphs = dataset.parse_all_graphs()
return graphs[0]
def load_dataset(name):
"""
Loads the graph dataset from file given a dataset name in form of a string.
:param name: string of dataset name
:return: loaded networkX graphs, graph labels
"""
dataset = Parser(os.path.join('datasets', name))
graphs = dataset.parse_all_graphs()
labels = [get_graph_label(graph) for graph in graphs]
return graphs, labels
def load_dataset_graph(name):
"""
Loads the graph dataset from file given a dataset name in form of a string
for graph classification.
:param name: string of dataset name
:return: loaded networkX graphs, graph labels
"""
dataset = Parser(name)
graphs = dataset.parse_all_graphs()
labels = [get_graph_label(graph) for graph in graphs]
return graphs, labels
def load_dataset_nodelabel(name):
"""
Loads one of the graph datasets CiteSeet or Cora and its labels.
:params: name of dataset to load
:return: list of loaded graphs, list of node features, list of labels
"""
dataset = Parser(os.path.join('datasets', name))
graphs = dataset.parse_all_graphs()
# convert datasets into lists graphs, labels
features = [get_node_attributes(graph) for graph in graphs]
labels = [get_node_labels(graph) for graph in graphs]
return graphs, features, labels
def load_dataset_graph(name):
"""
Loads the graph dataset from file given a dataset name in form of a string.
:param name: string of dataset name
:return: loaded networkX graphs, graph labels
"""
if name == "Nci1":
dataset = Parser("datasets/NCI1")
elif name == "Enzymes":
dataset = Parser("datasets/ENZYMES")
else:
raise ValueError(
f"Given dataset name {name} is not a valid graph dataset.")
dataset = dataset.parse_all_graphs()
labels = [get_graph_label(graph) for graph in dataset]
return dataset, labels