Checking out our data with pytorch-geometric

PROTEINS_embedding.py

# Let's take a look at our data. We'll look at dataset (all data) and data (our first graph):

data = dataset[0]  # Get the first graph object.

print()
print(f'Dataset: {dataset}:')
print('====================')
# How many graphs?
print(f'Number of graphs: {len(dataset)}')
# How many features?
print(f'Number of features: {dataset.num_features}')
# Now, in our first graph, how many edges?
print(f'Number of edges: {data.num_edges}')
# Average node degree?
print(f'Average node degree: {data.num_edges / data.num_nodes:.2f}')
# Do we have isolated nodes?
print(f'Contains isolated nodes: {data.contains_isolated_nodes()}')
# Do we contain self-loops?
print(f'Contains self-loops: {data.contains_self_loops()}')
# Is this an undirected graph?
print(f'Is undirected: {data.is_undirected()}')