Vehicle-cpp/hkpc/software/scipy/sparse/csgraph/tests/test_reordering.py

import numpy as np
from numpy.testing import assert_equal
from scipy.sparse.csgraph import reverse_cuthill_mckee, structural_rank
from scipy.sparse import csc_matrix, csr_matrix, coo_matrix


def test_graph_reverse_cuthill_mckee():
    A = np.array([[1, 0, 0, 0, 1, 0, 0, 0],
                [0, 1, 1, 0, 0, 1, 0, 1],
                [0, 1, 1, 0, 1, 0, 0, 0],
                [0, 0, 0, 1, 0, 0, 1, 0],
                [1, 0, 1, 0, 1, 0, 0, 0],
                [0, 1, 0, 0, 0, 1, 0, 1],
                [0, 0, 0, 1, 0, 0, 1, 0],
                [0, 1, 0, 0, 0, 1, 0, 1]], dtype=int)
    
    graph = csr_matrix(A)
    perm = reverse_cuthill_mckee(graph)
    correct_perm = np.array([6, 3, 7, 5, 1, 2, 4, 0])
    assert_equal(perm, correct_perm)
    
    # Test int64 indices input
    graph.indices = graph.indices.astype('int64')
    graph.indptr = graph.indptr.astype('int64')
    perm = reverse_cuthill_mckee(graph, True)
    assert_equal(perm, correct_perm)


def test_graph_reverse_cuthill_mckee_ordering():
    data = np.ones(63,dtype=int)
    rows = np.array([0, 0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 
                2, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5,
                6, 6, 6, 7, 7, 7, 7, 8, 8, 8, 8, 9, 9,
                9, 10, 10, 10, 10, 10, 11, 11, 11, 11, 
                12, 12, 12, 13, 13, 13, 13, 14, 14, 14,
                14, 15, 15, 15, 15, 15])
    cols = np.array([0, 2, 5, 8, 10, 1, 3, 9, 11, 0, 2,
                7, 10, 1, 3, 11, 4, 6, 12, 14, 0, 7, 13, 
                15, 4, 6, 14, 2, 5, 7, 15, 0, 8, 10, 13,
                1, 9, 11, 0, 2, 8, 10, 15, 1, 3, 9, 11,
                4, 12, 14, 5, 8, 13, 15, 4, 6, 12, 14,
                5, 7, 10, 13, 15])
    graph = coo_matrix((data, (rows,cols))).tocsr()
    perm = reverse_cuthill_mckee(graph)
    correct_perm = np.array([12, 14, 4, 6, 10, 8, 2, 15,
                0, 13, 7, 5, 9, 11, 1, 3])
    assert_equal(perm, correct_perm)


def test_graph_structural_rank():
    # Test square matrix #1
    A = csc_matrix([[1, 1, 0], 
                    [1, 0, 1],
                    [0, 1, 0]])
    assert_equal(structural_rank(A), 3)
    
    # Test square matrix #2
    rows = np.array([0,0,0,0,0,1,1,2,2,3,3,3,3,3,3,4,4,5,5,6,6,7,7])
    cols = np.array([0,1,2,3,4,2,5,2,6,0,1,3,5,6,7,4,5,5,6,2,6,2,4])
    data = np.ones_like(rows)
    B = coo_matrix((data,(rows,cols)), shape=(8,8))
    assert_equal(structural_rank(B), 6)
    
    #Test non-square matrix
    C = csc_matrix([[1, 0, 2, 0], 
                    [2, 0, 4, 0]])
    assert_equal(structural_rank(C), 2)
    
    #Test tall matrix
    assert_equal(structural_rank(C.T), 2)