bundles / scipy 1.17.1 / scipy / sparse / csgraph / _reordering / structural_rank
cython_function_or_method
scipy.sparse.csgraph._reordering:structural_rank
Signature
def structural_rank ( graph ) Summary
Compute the structural rank of a graph (matrix) with a given sparsity pattern.
Extended Summary
The structural rank of a matrix is the number of entries in the maximum transversal of the corresponding bipartite graph, and is an upper bound on the numerical rank of the matrix. A graph has full structural rank if it is possible to permute the elements to make the diagonal zero-free.
Parameters
graph: sparse array or matrixInput sparse array.
Returns
rank: intThe structural rank of the sparse graph.
Examples
from scipy.sparse import csr_array from scipy.sparse.csgraph import structural_rank✓
graph = [ [0, 1, 2, 0], [1, 0, 0, 1], [2, 0, 0, 3], [0, 1, 3, 0] ] graph = csr_array(graph)✓
print(graph)
✗structural_rank(graph)
✗Aliases
-
scipy.sparse.csgraph.structural_rank