Add to_matrix method to DataGraph - #430
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Returns the graph as a real symmetric matrix, the inverse of from_matrix: node weights go on the diagonal (since self-loops are not supported) and edge weights fill the off-diagonal entries, defaulting to 1.0 for edges without an explicit weight. Closes #429
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weight or default treated an explicit 0.0 weight as unset, and indexing the matrix directly by node label assumed labels were exactly 0..N-1, breaking on string labels or non-contiguous integers.
matrix[idx] with a (3, 2) index array fancy-indexes whole rows, not individual (row, col) entries, collapsing the n_nodes=3 case into an all-zero matrix. Index rows/cols separately instead.
alessandro-santini
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Aug 5, 2026
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Seems fine to me! thanks!
alessandro-santini
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fine for me thanks!
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Summary
DataGraph.to_matrix(), the inverse of the existingfrom_matrixclassmethod: returns a real symmetric square matrix with node weights on the diagonal (0.0 if unset, since self-loops aren't supported) and edge weights off-diagonal (defaulting to 1.0 for edges without an explicit weight).0..N-1followingself.nodesinsertion order (not label value), so it also works for non-integer or non-contiguous node labels.Known follow-up
DataGraph._edge_weightsisn't refreshed when edges are added after construction viaadd_edges_from/add_edge(only_reset_dicts()populates it, and that only runs inside the classmethod constructors). This doesn't affectto_matrixitself, but it's a pre-existing gap in the graph, tracked separately in edge_weights does not reflect edges added after construction #431.Tests
Noneweights, and ato_matrix/from_matrixround trip.Closes #429
Alternatives
networkx.adjacency_matrixis a good ready-made alternative but we cannot use it because of bug #431