Hello,

I would like to test nSBM on bipartite graphs but before going on I need to be sure I'm able to build a bipartite graph in graph-tool starting from a matrix:

A_nodes = np.arange(data.shape[0]) #nodes for rows start from 0

B_nodes = np.arange(data.shape[1]) + data.shape[0] # nodes from columns start from the last A_node

g = gt.Graph(directed=True) # directed or not directed... maybe not important at all

g.add_vertex(len(A_nodes) + len(B_nodes)) #add all needed nodes

partition = g.new_vertex_property('bool') # create a property indicating the node type

for x in A_nodes:

partition[g.vertex(x)] = 0 # set all A nodes to 0

for x in B_nodes:

partition[g.vertex(x)] = 1 # set all B to 1

idx = np.nonzero(data) # take the edge values

weights = adata.X[idx]

idx = (idx[0], idx[1] + len(A_nodes)) # node number of columns need to be augmented by the offset

g.add_edge_list(np.transpose(idx)) #add weights

ew = g.new_edge_property("double")

ew.a = weights

g.ep['weight'] = ew

Is there a more straightforward way to go?

d