def test_kron():
n = Matrix.from_lists(list(range(3)), list(range(3)), list(range(3)))
m = Matrix.from_lists(list(range(3)), list(range(3)), list(range(3)))
o = n.kron(m)
assert o == Matrix.from_lists([0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 0, 0, 0, 1, 2, 0, 2, 4])
def test_apply_lambda():
v = Matrix.from_lists([0, 1, 2], [0, 1, 2], [22, 33, 44])
w = v.apply(lambda x: mod(x, 10))
assert w == Matrix.from_lists([0, 1, 2], [0, 1, 2], [2, 3, 4])
w = v.apply(lambda x: mod(x, 7))
assert w == Matrix.from_lists([0, 1, 2], [0, 1, 2], [1, 5, 2])
def test_matrix_multiplication():
a = Matrix.from_lists([0, 0, 1, 1], [0, 1, 0, 1], [4, 1, 1, 2])
b = Matrix.from_lists([0, 0, 1, 1], [0, 1, 0, 1], [7, 1, 3, 1])
c = Matrix.from_lists([0, 0, 1, 1], [0, 1, 0, 1], [31, 5, 13, 3])
result = a @ b
assert result.iseq(c)
def test_mxm():
m = Matrix.from_lists([0, 1, 2], [0, 1, 2], [1, 2, 3])
n = Matrix.from_lists([0, 1, 2], [0, 1, 2], [1, 2, 3])
actual_res = m @ n
expected_res = Matrix.from_lists([0, 1, 2], [0, 1, 2], [1, 4, 9])
assert actual_res.iseq(expected_res), "Matrices are not equal"
def test_apply():
v = Matrix.from_lists(
[0, 1, 2],
[0, 1, 2],
[2, 3, 4])
w = v.apply(unaryop.ainv_int64)
assert w == Matrix.from_lists(
[0, 1, 2],
[0, 1, 2],
[-2, -3, -4])
def test_matrix_eq():
v = Matrix.from_lists(list(range(10)), list(range(10)), list(range(10)))
w = Matrix.from_lists(list(range(10)), list(range(10)), list(range(10)))
x = Matrix.from_lists(list(range(1, 11)),
list(range(1, 11)),
list(range(1, 11)),
ncols=11,
nrows=11)
assert v == w
assert v != x
def test_matrix_transpose():
v = Matrix.from_lists(
list(range(2, -1, -1)),
list(range(3)),
list(range(3)))
w = v.transpose()
assert w == Matrix.from_lists(
[0, 1, 2],
[2, 1, 0],
[0, 1, 2]
)
def test_matrix_ewise_add():
v = Matrix.from_lists(list(range(10)), list(range(10)), list(range(10)))
w = Matrix.from_lists(list(range(10)), list(range(10)), list(range(10)))
x = v.ewise_add(w)
assert x == Matrix.from_lists(list(range(10)), list(range(10)),
list(range(0, 20, 2)))
z = v + w
assert x == z
v += w
assert v == z
def test_vector_ewise_mult():
v = Matrix.from_lists(list(range(10)), list(range(10)), list(range(10)))
w = Matrix.from_lists(list(range(10)), list(range(10)), list(range(10)))
x = v.ewise_mult(w)
assert x == Matrix.from_lists(list(range(10)), list(range(10)),
list(map(lambda x: x * x, list(range(10)))))
z = v * w
assert x == z
v *= w
assert v == z
def test_check_mult():
row_inds = [0, 0, 1, 1]
col_inds = [0, 1, 0, 1]
matrix_1 = Matrix.from_lists(row_inds, col_inds, [1, 2, 0, 3])
matrix_2 = Matrix.from_lists(row_inds, col_inds, [0, 1, 3, 5])
matrix_res = matrix_1 @ matrix_2
expected = Matrix.from_lists(row_inds, col_inds, [6, 11, 9, 15])
assert expected.iseq(matrix_res), "Matrices not equal"
def test_select_ops():
I, J = tuple(map(list, zip(*product(range(3), repeat=2))))
V = list(range(9))
m = Matrix.from_lists(I, J, V, 3, 3)
assert m.tril() == Matrix.from_lists(
[0, 1, 1, 2, 2, 2],
[0, 0, 1, 0, 1, 2],
[0, 3, 4, 6, 7, 8])
assert m.triu() == Matrix.from_lists(
[0, 0, 0, 1, 1, 2],
[0, 1, 2, 1, 2, 2],
[0, 1, 2, 4, 5, 8])
assert m.diag() == Matrix.from_lists(
[0, 1, 2],
[0, 1, 2],
[0, 4, 8])
assert m.offdiag() == Matrix.from_lists(
[0, 0, 1, 1, 2, 2],
[1, 2, 0, 2, 0, 1],
[1, 2, 3, 5, 6, 7])
assert m.nonzero() == Matrix.from_lists(
[0, 0, 1, 1, 1, 2, 2, 2],
[1, 2, 0, 1, 2, 0, 1, 2],
[1, 2, 3, 4, 5, 6, 7, 8])
assert -m == Matrix.from_lists(
[0, 0, 0, 1, 1, 1, 2, 2, 2],
[0, 1, 2, 0, 1, 2, 0, 1, 2],
[0, -1, -2, -3, -4, -5, -6, -7, -8])
n = -m
assert abs(m) == Matrix.from_lists(
[0, 0, 0, 1, 1, 1, 2, 2, 2],
[0, 1, 2, 0, 1, 2, 0, 1, 2],
[0, 1, 2, 3, 4, 5, 6, 7, 8])
m = Matrix.from_lists(
[0, 1, 2],
[0, 1, 2],
[0.0, 1.0, 2.0], 3, 3)
n = ~m
assert n == Matrix.from_lists(
[0, 1, 2],
[0, 1, 2],
[float('inf'), 1.0, 0.5])
def test_mxm():
m = Matrix.from_lists([0, 1, 2], [1, 2, 0], [1, 2, 3])
n = Matrix.from_lists([0, 1, 2], [1, 2, 0], [2, 3, 4])
o = m.mxm(n)
assert o.nrows == 3
assert o.ncols == 3
assert o.nvals == 3
r = Matrix.from_lists([0, 1, 2], [2, 0, 1], [3, 8, 6])
assert o == r
assert r == m @ n
m @= n
assert r == m
o = m.mxm(n, semiring=semiring.lor_land_bool)
assert o == Matrix.from_lists([0, 1, 2], [0, 1, 2], [1, 1, 1])
def test_matrix_prod():
A = Matrix.from_lists([0, 0, 0, 1, 1, 1, 2, 2, 2],
[0, 1, 2, 0, 1, 2, 0, 1, 2],
[1, 2, 1, 2, 1, 2, 1, 2, 1])
B = Matrix.from_lists([0, 0, 0, 1, 1, 1, 2, 2, 2],
[0, 1, 2, 0, 1, 2, 0, 1, 2],
[2, 1, 2, 1, 2, 1, 2, 1, 2])
A_times_B = Matrix.from_lists([0, 0, 0, 1, 1, 1, 2, 2, 2],
[0, 1, 2, 0, 1, 2, 0, 1, 2],
[6, 6, 6, 9, 6, 9, 6, 6, 6])
assert A_times_B.iseq(A @ B)
def test_mxv():
m = Matrix.from_lists([0, 1, 2], [1, 2, 0], [1, 2, 3])
v = Vector.from_lists([0, 1, 2], [2, 3, 4])
o = m.mxv(v)
assert o == Vector.from_lists([0, 1, 2], [3, 8, 6])
assert m @ v == o
def test_matrix_reduce_vector():
m = Matrix.from_lists(
list(range(10)),
list(range(10)),
list(range(10)))
v = m.reduce_vector()
v == Vector.from_list(list(range(10)))
def test_select():
v = Matrix.from_lists(
[0, 1, 2],
[0, 1, 2],
[0, 0, 3])
w = v.select(lib.GxB_NONZERO)
assert w.to_lists() == [[2], [2], [3]]
def test_clear():
v = Matrix.from_lists(list(range(10)), list(range(10)), list(range(10)))
assert v.nvals == 10
assert len(v) == 10
v.clear()
assert v.nvals == 0
assert len(v) == 0
def test_matrix_pattern():
v = Matrix.from_lists(list(range(10)), list(range(10)), list(range(10)))
p = v.pattern()
assert p.gb_type == lib.GrB_BOOL
assert p.nrows == 10
assert p.ncols == 10
assert p.nvals == 10
def __init__(self,
edges: List[Edge],
start_states: Optional[Set[int]] = None,
final_states: Optional[Set[int]] = None):
label_to_edges: Dict[Any, Tuple[Indices, Indices]] = {}
label_to_bool_matrix: Dict[Any, Matrix] = {}
self.vertices = set()
for edge in edges:
I, J = label_to_edges.setdefault(edge.label, ([], []))
I.append(edge.node_from)
J.append(edge.node_to)
self.vertices.add(edge.node_from)
self.vertices.add(edge.node_to)
max_size = 0 if not self.vertices else max(self.vertices) + 1
self.matrix_size = max_size
for label, (I, J) in label_to_edges.items():
label_to_bool_matrix[label] = Matrix.from_lists(I=I,
J=J,
V=[True] * len(I),
ncols=max_size,
nrows=max_size,
typ=types.BOOL)
self.label_to_bool_matrix = label_to_bool_matrix
if start_states is None:
start_states = self.vertices
self.start_states = start_states
if final_states is None:
final_states = self.vertices
self.final_states = final_states
def test_matrix_mul():
matrix_1 = Matrix.from_lists([
0, 1, 2], [1, 2, 0], [3, 5, 1]
)
matrix_2 = Matrix.from_lists(
[0, 1, 2], [1, 2, 0], [2, 1, 4]
)
# matrix multiplication
res = matrix_1.mxm(matrix_2)
assert res.nrows == 3
assert res.ncols == 3
assert res.nvals == 3
exp_res = Matrix.from_lists(
[0, 1, 2], [2, 0, 1], [3, 20, 2]
)
assert res.iseq(exp_res)
def test_select_cmp():
I, J = tuple(map(list, zip(*product(range(3), repeat=2))))
V = list(range(9))
m = Matrix.from_lists(I, J, V, 3, 3)
n = m.select('>', 5)
assert n == Matrix.from_lists([2, 2, 2], [0, 1, 2], [6, 7, 8])
n = m.select('>=', 5)
assert n == Matrix.from_lists([1, 2, 2, 2], [2, 0, 1, 2], [5, 6, 7, 8])
n = m.select('<', 5)
assert n == Matrix.from_lists([0, 0, 0, 1, 1], [0, 1, 2, 0, 1],
[0, 1, 2, 3, 4], 3, 3)
n = m.select('<=', 5)
assert n == Matrix.from_lists([0, 0, 0, 1, 1, 1], [0, 1, 2, 0, 1, 2],
[0, 1, 2, 3, 4, 5], 3, 3)
n = m.select('==', 5)
assert n == Matrix.from_lists([1], [2], [5], 3, 3)
n = m.select('!=', 5)
assert n == Matrix.from_lists([0, 0, 0, 1, 1, 2, 2, 2],
[0, 1, 2, 0, 1, 0, 1, 2],
[0, 1, 2, 3, 4, 6, 7, 8], 3, 3)
def test_cmp():
I, J = tuple(map(list, zip(*product(range(3), repeat=2))))
V = list(range(9))
m = Matrix.from_lists(I, J, V, 3, 3)
n = m > 5
assert n == Matrix.from_lists(
[0, 0, 0, 1, 1, 1, 2, 2, 2],
[0, 1, 2, 0, 1, 2, 0, 1, 2],
[False, False, False, False, False, False, True, True, True],
)
n = m >= 5
assert n == Matrix.from_lists(
[0, 0, 0, 1, 1, 1, 2, 2, 2],
[0, 1, 2, 0, 1, 2, 0, 1, 2],
[False, False, False, False, False, True, True, True, True],
)
n = m < 5
assert n == Matrix.from_lists([0, 0, 0, 1, 1], [0, 1, 2, 0, 1],
[True, True, True, True, True], 3, 3)
n = m <= 5
assert n == Matrix.from_lists([0, 0, 0, 1, 1, 1], [0, 1, 2, 0, 1, 2],
[True, True, True, True, True, True], 3, 3)
n = m == 5
assert n == Matrix.from_lists([1], [2], [5], 3, 3)
n = m != 5
assert n == Matrix.from_lists([0, 0, 0, 1, 1, 2, 2, 2],
[0, 1, 2, 0, 1, 0, 1, 2],
[0, 1, 2, 3, 4, 6, 7, 8], 3, 3)
def test_matrix_assign():
m = Matrix.from_lists(list(range(3)), list(range(3)), list(range(3)))
assert m.nvals == 3
m[2] = Vector.from_list(list(repeat(6, 3)))
assert m.nvals == 5
assert m == Matrix.from_lists([0, 1, 2, 2, 2], [0, 1, 0, 1, 2],
[0, 1, 6, 6, 6], 3, 3)
m = Matrix.from_lists(list(range(3)), list(range(3)), list(range(3)))
assert m.nvals == 3
m[2, :] = Vector.from_list(list(repeat(6, 3)))
assert m.nvals == 5
assert m == Matrix.from_lists([0, 1, 2, 2, 2], [0, 1, 0, 1, 2],
[0, 1, 6, 6, 6], 3, 3)
m = Matrix.from_lists(list(range(3)), list(range(3)), list(range(3)))
assert m.nvals == 3
m[:, 2] = Vector.from_list(list(repeat(6, 3)))
assert m.nvals == 5
assert m == Matrix.from_lists([0, 1, 0, 1, 2], [0, 1, 2, 2, 2],
[0, 1, 6, 6, 6], 3, 3)
m = Matrix.from_type(int, 3, 3)
assert m.nvals == 0
n = Matrix.from_lists([0, 1, 2], [0, 1, 2], [0, 1, 2])
m[:, :] = n
assert m == n
def test_resize():
v = Matrix.from_lists(list(range(10)), list(range(10)), list(range(10)))
assert v.nrows == 10
assert v.ncols == 10
assert v.nvals == 10
v.resize(20, 20)
assert v.nrows == 20
assert v.ncols == 20
assert v.nvals == 10
def test_matrix_to_from_lists():
v = Matrix.from_lists(list(range(10)), list(range(10)), list(range(10)))
assert v.nrows == 10
assert v.ncols == 10
assert v.nvals == 10
assert v.to_lists() == [
list(range(10)),
list(range(10)),
list(range(10)),
]
def test_transitive_closure():
g = Graph()
g.from_file("input3.txt")
reachability_matrix = g.transitive_closure()
expected = Matrix.from_lists(
[0, 0, 1, 3, 3, 3, 4, 4],
[1, 2, 2, 1, 2, 4, 1, 2],
[True, True, True, True, True, True, True, True]
)
assert expected.iseq(reachability_matrix)
def test_vxm():
m = Matrix.from_lists([0, 1, 2], [1, 2, 0], [1, 2, 3])
v = Vector.from_lists([0, 1, 2], [2, 3, 4])
o = v.vxm(m)
assert o == Vector.from_lists([0, 1, 2], [12, 2, 6])
w = Vector.dup(v)
assert v @ m == o
v @= m
assert v == o
def test_matrix_multiplication():
matrix_1 = Matrix.from_lists(
[0, 1, 2],
[1, 2, 0],
[1, 2, 3]
)
matrix_2 = Matrix.from_lists(
[0, 1, 2],
[1, 2, 0],
[4, 5, 6]
)
result = matrix_1 @ matrix_2
expected = Matrix.from_lists(
[0, 1, 2],
[2, 0, 1],
[5, 12, 12]
)
assert result.iseq(expected)
def test_matrix_mm_read_write(tmp_path):
mmf = tmp_path / 'mmwrite_test.mm'
mmf.touch()
m = Matrix.from_lists([0, 1, 2], [0, 1, 2], [2, 3, 4])
with mmf.open('w') as f:
m.to_mm(f)
with mmf.open() as f:
assert f.readlines() == [
'%%MatrixMarket matrix coordinate integer symmetric\n',
'%%GraphBLAS GrB_INT64\n', '3 3 3\n', '1 1 2\n', '2 2 3\n',
'3 3 4\n'
]
with mmf.open() as f:
n = Matrix.from_mm(f)
assert n == m
def graph_to_bin_matrix(self):
graph = self.graph
edges = graph.edges
for v_from, key, v_to in edges:
if key in self.M_dict:
self.M_dict[key][0].append(int(v_from))
self.M_dict[key][1].append(int(v_to))
else:
self.M_dict[key] = ([int(v_from)], [int(v_to)])
for key, nodes in self.M_dict.items():
num_edges = len(nodes[0])
self.M_bin[key] = Matrix.from_lists(nodes[0],
nodes[1], [True] * num_edges,
nrows=graph.vertices_num,
ncols=graph.vertices_num)
