def test_mst_prim():
graph = RandomGraph()
mst = mst_prim(graph, graph.nodes()[0])
nx_graph = networkx.Graph()
for node in graph.nodes():
for neighbor in graph.get(node):
if nx_graph.has_edge(node,
neighbor) is False and nx_graph.has_edge(
neighbor, node) is False:
nx_graph.add_edge(node,
neighbor,
weight=graph.get(node, neighbor))
tree = []
for node in mst:
if mst[node] is not None:
tree.append((node, mst[node]))
print(tree)
T = networkx.minimum_spanning_tree(nx_graph)
edges = T.edges(data=False)
# Begin the test
test = True
# I need to check if (x,y) or (y,x) is in networkx generated mst
for node in tree:
x, y = node
print(x, y)
test = test and ((x, y) in edges or (y, x) in edges)
assert test
def test_connected_components():
graph = RandomGraph()
number_cc = len(connected_components(graph))
graph_data = networkx.Graph(graph.graph_dict)
test = networkx.is_connected(graph_data)
test = number_cc == 1 if test else number_cc != 1
assert test
def __init__(self, node_num, p, in_channels, out_channels, graph_mode,
is_train, name):
super(RandWire, self).__init__()
self.node_num = node_num
self.p = p
self.in_channels = in_channels
self.out_channels = out_channels
self.graph_mode = graph_mode
self.is_train = is_train
self.name = name
# get graph nodes and in edges
graph_node = RandomGraph(self.node_num, self.p, graph_mode=graph_mode)
if self.is_train is True:
print("is_train: True")
graph = graph_node.make_graph()
self.nodes, self.in_edges = graph_node.get_graph_info(graph)
graph_node.save_random_graph(graph, name)
else:
graph = graph_node.load_random_graph(name)
self.nodes, self.in_edges = graph_node.get_graph_info(graph)
# define input Node
self.module_list = nn.ModuleList([
Node(self.in_edges[0],
self.in_channels,
self.out_channels,
stride=2)
])
# define the rest Node
self.module_list.extend([
Node(self.in_edges[node], self.out_channels, self.out_channels)
for node in self.nodes if node > 0
])
steps = 200
full_graph = FullGraph(5)
todo = [{
"msg": "Running IL",
"name": "IL",
"partners": 0,
"n_samples": args.n_samples,
"fun": lambda: LJALPart1(graph=Graph(5)).n_steps(steps)
}, {
"msg": "Running LJAL-2",
"name": "LJAL-2",
"partners": 2,
"n_samples": args.n_samples,
"fun": lambda: LJALPart1(graph=RandomGraph(5, 2)).n_steps(steps)
}, {
"msg": "Running LJAL-3",
"name": "LJAL-3",
"partners": 3,
"n_samples": args.n_samples,
"fun": lambda: LJALPart1(graph=RandomGraph(5, 3)).n_steps(steps)
}, {
"msg": "Running JAL",
"name": "JAL",
"partners": 4,
"n_samples": args.n_samples,
"fun": lambda: LJALPart1(graph=full_graph).n_steps(steps)
}]
tasks.run(todo, args.save_name)
def test_cc():
graph = RandomGraph()
number_cc = len(connected_components(graph))
graph_data = networkx.Graph(graph.graph_dict)
assert networkx.number_connected_components(graph_data) == number_cc
def build_graph(filename, p):
for i in range(start, end, offset):
RandomGraph(list(range(i)),
p).save_graph(filename + format_p(p) + str(i))
