def _test_breadth_first_search_parallel(ds):
import pydatastructs.utils.misc_util as utils
GraphNode = getattr(utils, "Adjacency" + ds + "GraphNode")
V1 = GraphNode(0)
V2 = GraphNode(1)
V3 = GraphNode(2)
V4 = GraphNode(3)
V5 = GraphNode(4)
V6 = GraphNode(5)
V7 = GraphNode(6)
V8 = GraphNode(7)
G1 = Graph(V1, V2, V3, V4, V5, V6, V7, V8)
edges = [(V1.name, V2.name), (V1.name, V3.name), (V1.name, V4.name),
(V2.name, V5.name), (V2.name, V6.name), (V3.name, V6.name),
(V3.name, V7.name), (V4.name, V7.name), (V4.name, V8.name)]
for edge in edges:
G1.add_edge(*edge)
parent = {}
def bfs_tree(curr_node, next_node, parent):
if next_node != "":
parent[next_node] = curr_node
return True
breadth_first_search_parallel(G1, V1.name, 5, bfs_tree, parent)
assert (parent[V2.name] == V1.name and parent[V3.name] == V1.name
and parent[V4.name] == V1.name and parent[V5.name] == V2.name
and (parent[V6.name] in (V2.name, V3.name))
and (parent[V7.name] in (V3.name, V4.name))
and (parent[V8.name] == V4.name))
def _test_breadth_first_search(ds):
import pydatastructs.utils.misc_util as utils
GraphNode = getattr(utils, "Adjacency" + ds + "GraphNode")
V1 = GraphNode(0)
V2 = GraphNode(1)
V3 = GraphNode(2)
G1 = Graph(V1, V2, V3)
edges = [(V1.name, V2.name), (V2.name, V3.name), (V1.name, V3.name)]
for edge in edges:
G1.add_edge(*edge)
parent = dict()
def bfs_tree(curr_node, next_node, parent):
if next_node != "":
parent[next_node] = curr_node
return True
breadth_first_search(G1, V1.name, bfs_tree, parent)
assert (parent[V3.name] == V1.name and parent[V2.name] == V1.name) or \
(parent[V3.name] == V2.name and parent[V2.name] == V1.name)
V4 = GraphNode(0)
V5 = GraphNode(1)
V6 = GraphNode(2)
V7 = GraphNode(3)
V8 = GraphNode(4)
edges = [(V4.name, V5.name), (V5.name, V6.name), (V6.name, V7.name),
(V6.name, V4.name), (V7.name, V8.name)]
G2 = Graph(V4, V5, V6, V7, V8)
for edge in edges:
G2.add_edge(*edge)
path = []
def path_finder(curr_node, next_node, dest_node, parent, path):
if next_node != "":
parent[next_node] = curr_node
if curr_node == dest_node:
node = curr_node
path.append(node)
while node is not None:
if parent.get(node, None) is not None:
path.append(parent[node])
node = parent.get(node, None)
path.reverse()
return False
return True
parent.clear()
breadth_first_search(G2, V4.name, path_finder, V7.name, parent, path)
assert path == [V4.name, V5.name, V6.name, V7.name]
def _test_random_walk(ds):
import pydatastructs.utils.misc_util as utils
GraphNode = getattr(utils, "Adjacency" + ds + "GraphNode")
V1 = GraphNode(0)
V2 = GraphNode(1)
V3 = GraphNode(2)
V4 = GraphNode(3)
V5 = GraphNode(4)
V6 = GraphNode(5)
V7 = GraphNode(6)
V8 = GraphNode(7)
G = Graph(V1, V2, V3, V4, V5, V6, V7, V8)
edges = [
(V1.name, V2.name),
(V1.name, V3.name),
(V1.name, V4.name),
(V2.name, V5.name),
(V2.name, V6.name),
(V3.name, V6.name),
(V3.name, V7.name),
(V4.name, V7.name),
(V4.name, V8.name)
]
for edge in edges:
G1.add_edge(*edge)
random_walk = random_walk(G, V1, 3)
assert random_walk == [3]
def _test_shortest_paths_negative_edges(ds, algorithm):
import pydatastructs.utils.misc_util as utils
GraphNode = getattr(utils, "Adjacency" + ds + "GraphNode")
vertices = [
GraphNode('s'),
GraphNode('a'),
GraphNode('b'),
GraphNode('c'),
GraphNode('d')
]
graph = Graph(*vertices)
graph.add_edge('s', 'a', 3)
graph.add_edge('s', 'b', 2)
graph.add_edge('a', 'c', 1)
graph.add_edge('b', 'd', 1)
graph.add_edge('b', 'a', -2)
graph.add_edge('c', 'd', 1)
dist, pred = shortest_paths(graph, algorithm, 's')
assert dist == {'s': 0, 'a': 0, 'b': 2, 'c': 1, 'd': 2}
assert pred == {'s': None, 'a': 'b', 'b': 's', 'c': 'a', 'd': 'c'}
dist, pred = shortest_paths(graph, algorithm, 's', 'd')
assert dist == 2
assert pred == {'s': None, 'a': 'b', 'b': 's', 'c': 'a', 'd': 'c'}
def _test_minimum_spanning_tree(func, ds, algorithm, *args):
import pydatastructs.utils.misc_util as utils
GraphNode = getattr(utils, "Adjacency" + ds + "GraphNode")
a, b, c, d, e = [GraphNode(x) for x in [0, 1, 2, 3, 4]]
graph = Graph(a, b, c, d, e)
graph.add_edge(a.name, c.name, 10)
graph.add_edge(c.name, a.name, 10)
graph.add_edge(a.name, d.name, 7)
graph.add_edge(d.name, a.name, 7)
graph.add_edge(c.name, d.name, 9)
graph.add_edge(d.name, c.name, 9)
graph.add_edge(d.name, b.name, 32)
graph.add_edge(b.name, d.name, 32)
graph.add_edge(d.name, e.name, 23)
graph.add_edge(e.name, d.name, 23)
mst = func(graph, algorithm, *args)
expected_mst = [('0_3', 7), ('2_3', 9), ('3_4', 23), ('3_1', 32),
('3_0', 7), ('3_2', 9), ('4_3', 23), ('1_3', 32)]
assert len(expected_mst) == len(mst.edge_weights.items())
for k, v in mst.edge_weights.items():
assert (k, v.value) in expected_mst
def _test_topological_sort(func, ds, algorithm, threads=None):
import pydatastructs.utils.misc_util as utils
GraphNode = getattr(utils, "Adjacency" + ds + "GraphNode")
vertices = [
GraphNode('2'),
GraphNode('3'),
GraphNode('5'),
GraphNode('7'),
GraphNode('8'),
GraphNode('10'),
GraphNode('11'),
GraphNode('9')
]
graph = Graph(*vertices)
graph.add_edge('5', '11')
graph.add_edge('7', '11')
graph.add_edge('7', '8')
graph.add_edge('3', '8')
graph.add_edge('3', '10')
graph.add_edge('11', '2')
graph.add_edge('11', '9')
graph.add_edge('11', '10')
graph.add_edge('8', '9')
if threads is not None:
l = func(graph, algorithm, threads)
else:
l = func(graph, algorithm)
assert all([(l1 in l[0:3]) for l1 in ('3', '5', '7')] +
[(l2 in l[3:5])
for l2 in ('8', '11')] + [(l3 in l[5:])
for l3 in ('10', '9', '2')])
def _test_shortest_paths(ds, algorithm):
import pydatastructs.utils.misc_util as utils
GraphNode = getattr(utils, "Adjacency" + ds + "GraphNode")
vertices = [
GraphNode('S'),
GraphNode('C'),
GraphNode('SLC'),
GraphNode('SF'),
GraphNode('D')
]
graph = Graph(*vertices)
graph.add_edge('S', 'SLC', 2)
graph.add_edge('C', 'S', 4)
graph.add_edge('C', 'D', 2)
graph.add_edge('SLC', 'C', 2)
graph.add_edge('SLC', 'D', 3)
graph.add_edge('SF', 'SLC', 2)
graph.add_edge('SF', 'S', 2)
graph.add_edge('D', 'SF', 3)
dist, pred = shortest_paths(graph, algorithm, 'SLC')
assert dist == {'S': 6, 'C': 2, 'SLC': 0, 'SF': 6, 'D': 3}
assert pred == {
'S': 'C',
'C': 'SLC',
'SLC': None,
'SF': 'D',
'D': 'SLC'
}
dist, pred = shortest_paths(graph, algorithm, 'SLC', 'SF')
assert dist == 6
assert pred == {
'S': 'C',
'C': 'SLC',
'SLC': None,
'SF': 'D',
'D': 'SLC'
}
graph.remove_edge('SLC', 'D')
graph.add_edge('D', 'SLC', -10)
assert raises(ValueError,
lambda: shortest_paths(graph, 'bellman_ford', 'SLC'))
def _test_strongly_connected_components(func, ds, algorithm, *args):
import pydatastructs.utils.misc_util as utils
GraphNode = getattr(utils, "Adjacency" + ds + "GraphNode")
a, b, c, d, e, f, g, h = \
[GraphNode(chr(x)) for x in range(ord('a'), ord('h') + 1)]
graph = Graph(a, b, c, d, e, f, g, h)
graph.add_edge(a.name, b.name)
graph.add_edge(b.name, c.name)
graph.add_edge(b.name, f.name)
graph.add_edge(b.name, e.name)
graph.add_edge(c.name, d.name)
graph.add_edge(c.name, g.name)
graph.add_edge(d.name, h.name)
graph.add_edge(d.name, c.name)
graph.add_edge(e.name, f.name)
graph.add_edge(e.name, a.name)
graph.add_edge(f.name, g.name)
graph.add_edge(g.name, f.name)
graph.add_edge(h.name, d.name)
graph.add_edge(h.name, g.name)
comps = func(graph, algorithm)
expected_comps = [{'e', 'a', 'b'}, {'d', 'c', 'h'}, {'g', 'f'}]
assert comps == expected_comps
def _test_shortest_paths_negative_edges(ds, algorithm):
import pydatastructs.utils.misc_util as utils
GraphNode = getattr(utils, "Adjacency" + ds + "GraphNode")
vertices = [
GraphNode('1'),
GraphNode('2'),
GraphNode('3'),
GraphNode('4')
]
graph = Graph(*vertices)
graph.add_edge('1', '3', -2)
graph.add_edge('2', '1', 4)
graph.add_edge('2', '3', 3)
graph.add_edge('3', '4', 2)
graph.add_edge('4', '2', -1)
dist, next_v = shortest_paths(graph, algorithm, 's')
assert dist == {
'1': {
'3': -2,
'1': 0,
'4': 0,
'2': -1
},
'2': {
'1': 4,
'3': 2,
'2': 0,
'4': 4
},
'3': {
'4': 2,
'3': 0,
'1': 5,
'2': 1
},
'4': {
'2': -1,
'4': 0,
'1': 3,
'3': 1
}
}
assert next_v == {
'1': {
'3': '1',
'1': '1',
'4': None,
'2': None
},
'2': {
'1': '2',
'3': None,
'2': '2',
'4': None
},
'3': {
'4': '3',
'3': '3',
'1': None,
'2': None
},
'4': {
'2': '4',
'4': '4',
'1': None,
'3': None
}
}
