def __init__(self, node_id, node_port, config):
self.id = str(node_id)
self.n_start = time.time()
# initialise node's socket
self.s_port = int(node_port)
self._socket = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
self._socket.bind(("127.0.0.1", int(node_port)))
self._socket.settimeout(0.1)
self.lsp = ""
self.net_topology = graph(self.id)
self.neighbours = {} # => {node_id: (cost, port, KA_count)}
self.neighbour_ka = {}
# iterate through config file and insert nieghbours
# Assume the config file is in the same directory
config_file = open(config, "r")
config_file.readline() # Get rid of the first line, it's junk
for line in config_file:
line = line.rstrip('\n')
line = line.split(" ")
self.neighbours[line[0]] = (float(line[1]), int(line[2]))
self.neighbour_ka[line[0]] = 0
self.net_topology.insert_edge(self.id, line[0], line[1])
def run_dash():
"""
runs the dash app
:param: conn [sqlite3.connection] -- connection to the db
:param: curr [sqlite3.cursor] -- cursor in the db
"""
a = graph()
app = dash.Dash()
setup_tall_layout(app)
player_graphs = ['player_a', 'player_b', 'player_c', 'player_d']
@app.callback(
Output(component_id='team_bar', component_property='figure'),
[Input(component_id='team_id_dropdown', component_property='value')]
)
def update_player_output_div(input_value):
return a.usa()
@app.callback(
Output(component_id='player_c', component_property='figure'),
[Input(component_id='team_id_dropdown', component_property='value')]
)
def update_player_graph_a(input_value):
player_position = 1
return a.usa(1)
#return main.my_graph()
app.run_server(port=8066)
def test_graph(self):
g = graph()
airports = ["a","b","c"]
for i in airports:
g.add_vertex(i)
for i in range(len(airports)):
for j in range(len(airports)):
if i != j:
g.add_edge(airports[i], airports[j], i+j)
self.assertTrue(g.weights["a","b"]==1)
self.assertTrue(g.weights["b","c"]==3)
def test_BFS():
g = graph(4)
g.addEdge(0, 1)
g.addEdge(0, 2)
g.addEdge(1, 2)
g.addEdge(2, 0)
g.addEdge(2, 3)
g.addEdge(3, 3)
BFS(g, 2)
def test_shortest_path(self):
g = graph()
airports = ["a","b","c"]
for i in airports:
g.add_vertex(i)
for i in range(len(airports)):
for j in range(len(airports)):
if i != j:
g.add_edge(airports[i], airports[j], i+j)
self.assertTrue(sp(g,"a","b")==['a', 'b'])
self.assertTrue(sp(g,"c","a")==['c', 'a'])
self.assertFalse(sp(g,"c","b")==['c', 'a', 'b'])
def main():
#create common source vertex
g1 = graph()
source = node("s")
g1.add_vertex(source)
SO = node("so")
g1.add_vertex(SO)
SA = node("sa")
g1.add_vertex(SA)
SB = node("sb")
g1.add_vertex(SB)
SAB = node("sab")
g1.add_vertex(SAB)
DO = node("do")
g1.add_vertex(DO)
DA = node("da")
g1.add_vertex(DA)
DB = node("db")
g1.add_vertex(DB)
DAB = node("dab")
g1.add_vertex(DAB)
sink=node("si")
g1.add_vertex(sink)
g1.add_edge(source,SO,50)
g1.add_edge(source,SA,36)
g1.add_edge(source,SB,11)
g1.add_edge(source,SAB,8)
g1.add_edge(DO, sink, 45)
g1.add_edge(DA, sink, 42)
g1.add_edge(DB, sink, 8)
g1.add_edge(DAB, sink, 3)
g1.add_edge(SO,DO,float("inf"))
g1.add_edge(SO, DA, float("inf"))
g1.add_edge(SO, DB, float("inf"))
g1.add_edge(SO, DAB, float("inf"))
g1.add_edge(SA, DA, float("inf"))
g1.add_edge(SA, DAB, float("inf"))
g1.add_edge(SB, DB, float("inf"))
g1.add_edge(SB, DAB, float("inf"))
g1.add_edge(SAB, DAB, float("inf"))
max_flow=g1.find_max_flow(source,sink)
demand = g1.edges[(DO,sink)]+g1.edges[(DA,sink)]+g1.edges[(DB,sink)]+g1.edges[(DAB,sink)]
print("MAX_FLOW = ",max_flow)
print("Demand = ",demand)
if(demand>max_flow):
print("Max flow is lesser than demand. Hence, demand cannot be met.")
else:
print("Max flow is equal to or more than demand. Hence, demand can be met.")
def main():
cdf_graph = graph()
print("*** CDF tool *** usage cdf filename1 cdfname1 filename2 cdfname2 \n")
for arg in sys.argv:
print("args: ",arg)
file_name = sys.argv[1]
file_name1 = sys.argv[3]
handler = file_hander(file_name,0)
handler1 = file_hander(file_name1,0)
data=handler.read_file()
data1 = handler1.read_file()
print("data 1: ",data)
print("name 1: ", sys.argv[2])
print("data 2: ", data1)
print("name 2: ", sys.argv[4])
cdf_graph.cdf(data, data1, sys.argv[2], sys.argv[4])
def basic_operations():
# Create the dictionary with graph elements
graph_elements = {
"a": ["b", "c"],
"b": ["a", "d"],
"c": ["a", "d"],
"d": ["e"],
"e": ["d"]
}
print(graph_elements)
new_graph = graph(graph_elements)
"""Adding a vertex"""
new_graph.add_vertex("f")
print(new_graph.get_vertices())
print(new_graph.edges())
"""Adding an edge"""
new_graph.add_edge({'a', 'e'})
new_graph.add_edge({'a', 'c'})
print(new_graph.edges())
def draw_graph_mith_MinMax_points(self, col, sheetname):
read = readFile(sheetname)
read.readMarks(col)
points = Find_Points()
points.find_min(read.Marks, read.registerations)
points.find_max(read.Marks, read.registerations)
points.find_avg(read.Marks, read.registerations)
graphy = graph(sheetname)
plt = graphy.draw_Simple_graph()
plt.scatter(points.min_cell,
points.min,
color='r',
label='Minimum Marks')
plt.scatter(points.max_cell,
points.max,
color='b',
label='Maximum Marks')
#num=str(points.avg)
#text='Average = ' + num
# plt.figtext(text,0.2,1.3)
plt.title(sheetname + 'Data')
plt.show()
def reverse_graph(g):
new_graph = graph(g.size())
for v in g.nodes():
for c in g.children(v):
new_graph.addEdge(c, v)
return new_graph
stack.append(n)
def strongly_connected_components(g):
stack = []
visited = [False] * g.size()
for i in range(g.size()):
if visited[i] is False:
fill_order(i, g, stack, visited)
rev_g = reverse_graph(g)
visited = [False] * rev_g.size()
print("Strongly Connected Components : ")
while stack:
v = stack.pop()
if visited[v] is False:
scc = []
dfs(v, rev_g, visited, scc)
print(scc)
g = graph(5)
g.addEdge(1, 0)
g.addEdge(0, 2)
g.addEdge(2, 1)
g.addEdge(0, 3)
g.addEdge(3, 4)
strongly_connected_components(g)
n = g.size()
visited = [False]*n
disc = [0]*n
low = [0]*n
parent = [-1]*n
ap = [False]*n
for i in range(n):
if visited[i] is False:
dfs(i, g, visited, disc, low, parent, ap)
print("Articulation Points : ", [i for i in range(n) if ap[i] is True])
g1 = graph(5)
g1.addEdge(1, 0)
g1.addEdge(0, 2)
g1.addEdge(2, 1)
g1.addEdge(0, 3)
g1.addEdge(3, 4)
articulation_points(g1)
g2 = graph(4)
g2.addEdge(0, 1)
g2.addEdge(1, 2)
g2.addEdge(2, 3)
articulation_points(g2)
g3 = graph(7)
g3.addEdge(0, 1)
if edge.getInfo()[1].display() in Stack:
low_link[name] = min(
low_link[name],
index_dict[edge.getInfo()[1].display()])
if index_dict[name] == low_link[name]:
curr_scc = []
while (True):
curr_v = Stack.pop(-1)
curr_scc.append(curr_v)
if (curr_v == name):
break
scc.append(curr_scc)
for vertex in self.getAllVertex():
if vertex not in reached:
visit(vertex)
self._SCC = scc
Graph = graph()
Graph.genRand(4)
Graph.printAdjList()
Reach = reachabilty(Graph)
Reach.displayDFS(0)
Reach.displayBFS(0)
Reach.displaySCC()
def __init__(self, dict=None):
"""Expects a dictionary of lists, each int(key) pointing to a list
containing ["body", "tags[]", "int(parent)"]"""
self.dict = {}
self.dict = dict
self.graph = graph()
return path
def longestPath(g, s):
path = topologicalSort(g)
dist = [-9999]*g.size()
dist[s] = 0
while path:
ele = path.pop()
if dist[ele] != -9999:
for c in g.children(ele):
if dist[c] < dist[ele] + g.weight(ele, c):
dist[c] = dist[ele] + g.weight(ele, c)
print(dist)
g = graph()
g.addEdge(0, 1, 5)
g.addEdge(0, 2, 3)
g.addEdge(1, 3, 6)
g.addEdge(1, 2, 2)
g.addEdge(2, 4, 4)
g.addEdge(2, 5, 2)
g.addEdge(2, 3, 7)
g.addEdge(3, 5, 1)
g.addEdge(3, 4, -1)
g.addEdge(4, 5, -2)
longestPath(g, 1)
from Graph import graph
graph = graph({
"a": [("b", 3)],
"b": [("c", 2), ("d", 6), ("e", 3), ("f", 8)],
"c": [("b", 2), ("d", 5)],
"d": [("c", 5), ("b", 6)],
"e": [("b", 3), ("f", 1)],
"f": [("e", 1), ("b", 8)]
})
graph.print_edges()
#start at a
#end at f
graph.dijsktra("a", "f")
stack.append(n)
def strongly_connected_components(g):
stack = []
visited = [False]*g.size()
for i in range(g.size()):
if visited[i] is False:
fill_order(i, g, stack, visited)
rev_g = reverse_graph(g)
visited = [False]*rev_g.size()
print("Strongly Connected Components : ")
while stack:
v = stack.pop()
if visited[v] is False:
scc = []
dfs(v, rev_g, visited, scc)
print(scc)
g = graph(5)
g.addEdge(1, 0)
g.addEdge(0, 2)
g.addEdge(2, 1)
g.addEdge(0, 3)
g.addEdge(3, 4)
strongly_connected_components(g)
low[u] = min(low[u], disc[v])
def bridge(g):
n = g.size()
visited = [False] * n
disc = [0] * n
low = [0] * n
parent = [-1] * n
bridges = []
for i in g.nodes():
if visited[i] is False:
dfs(i, g, visited, disc, low, parent, bridges)
print(bridges)
g1 = graph(5)
g1.addEdge(1, 0)
g1.addEdge(0, 2)
g1.addEdge(2, 1)
g1.addEdge(0, 3)
g1.addEdge(3, 4)
bridge(g1)
g2 = graph(4)
g2.addEdge(0, 1)
g2.addEdge(1, 2)
g2.addEdge(2, 3)
bridge(g2)
disc = [-1]*n
low = [0]*n
global time
time = 0
global scc
scc = []
for i in g.nodes():
if disc[i] == -1:
dfs(i, g, disc, low, stack, stack_mem)
return scc
print("Graph 1")
g1 = graph(5)
g1.addEdge(1, 0)
g1.addEdge(0, 2)
g1.addEdge(2, 1)
g1.addEdge(0, 3)
g1.addEdge(3, 4)
print(strongly_connected_component(g1))
print("Graph 2")
g2 = graph(4)
g2.addEdge(0, 1)
g2.addEdge(1, 2)
g2.addEdge(2, 3)
print(strongly_connected_component(g2))
print("Graph 3")
def bridge(g):
n = g.size()
visited = [False]*n
disc = [0]*n
low = [0]*n
parent = [-1]*n
bridges = []
for i in g.nodes():
if visited[i] is False:
dfs(i, g, visited, disc, low, parent, bridges)
print(bridges)
g1 = graph(5)
g1.addEdge(1, 0)
g1.addEdge(0, 2)
g1.addEdge(2, 1)
g1.addEdge(0, 3)
g1.addEdge(3, 4)
bridge(g1)
g2 = graph(4)
g2.addEdge(0, 1)
g2.addEdge(1, 2)
g2.addEdge(2, 3)
bridge(g2)
time = 0
n = g.size()
visited = [False] * n
disc = [0] * n
low = [0] * n
parent = [-1] * n
ap = [False] * n
for i in range(n):
if visited[i] is False:
dfs(i, g, visited, disc, low, parent, ap)
print("Articulation Points : ", [i for i in range(n) if ap[i] is True])
g1 = graph(5)
g1.addEdge(1, 0)
g1.addEdge(0, 2)
g1.addEdge(2, 1)
g1.addEdge(0, 3)
g1.addEdge(3, 4)
articulation_points(g1)
g2 = graph(4)
g2.addEdge(0, 1)
g2.addEdge(1, 2)
g2.addEdge(2, 3)
articulation_points(g2)
g3 = graph(7)
g3.addEdge(0, 1)
low = [0] * n
global time
time = 0
global scc
scc = []
for i in g.nodes():
if disc[i] == -1:
dfs(i, g, disc, low, stack, stack_mem)
return scc
print("Graph 1")
g1 = graph(5)
g1.addEdge(1, 0)
g1.addEdge(0, 2)
g1.addEdge(2, 1)
g1.addEdge(0, 3)
g1.addEdge(3, 4)
print(strongly_connected_component(g1))
print("Graph 2")
g2 = graph(4)
g2.addEdge(0, 1)
g2.addEdge(1, 2)
g2.addEdge(2, 3)
print(strongly_connected_component(g2))
print("Graph 3")
def union(parent, x, y):
x_parent = find(parent, x)
y_parent = find(parent, y)
if x_parent == y_parent:
return False
else:
parent[x_parent] = y_parent
return True
def isCycle(g):
parent = [-1] * g.size()
for e in g.edges():
if union(parent, e[0], e[1]) is False:
return True
return False
g = graph(3)
g.addEdge(0, 1)
g.addEdge(1, 2)
g.addEdge(0, 2)
if isCycle(g) is True:
print("Graph Contains Cycle")
else:
print("Graph does not contains cycle")
le = le_time(graph, toposeq, ee[graph.get_num() - 1])
return crt_path(graph, ee, le)
if __name__ == '__main__':
#先把图7.15用临接矩阵的形式表现出来
inf = float('inf')
G715 = [[inf, 7, 13, 8, inf, inf, inf, inf, inf],
[inf, inf, 4, inf, inf, 14, inf, inf, inf],
[inf, inf, inf, inf, 5, inf, 8, 12, inf],
[inf, inf, inf, inf, 13, inf, inf, 10, inf],
[inf, inf, inf, inf, inf, 7, 3, inf, inf],
[inf, inf, inf, inf, inf, inf, inf, inf, 5],
[inf, inf, inf, inf, inf, inf, inf, inf, 7],
[inf, inf, inf, inf, inf, inf, inf, inf, 8],
[inf, inf, inf, inf, inf, inf, inf, inf, inf]]
g715 = graph(G715, inf)
tps = toposort(g715)
print(tps) #正确，注意此时加入邻接矩阵的时候对角线元素不能再用0表示，即本身不是本身的临接边
print(' ')
#验证AOV网络的关键路径是什么，以及关键路径上面的关键活动
aoe_path, ee, le = critical_paths(g715)
print(ee)
print(' ')
print(le)
print(' ')
print(aoe_path)
print(' ')
if parent[i] == -1:
return i
return find(parent, parent[i])
def union(parent, x, y):
x_parent = find(parent, x)
y_parent = find(parent, y)
if x_parent == y_parent:
return False
else:
parent[x_parent] = y_parent
return True
def isCycle(g):
parent = [-1]*g.size()
for e in g.edges():
if union(parent, e[0], e[1]) is False:
return True
return False
g = graph(3)
g.addEdge(0, 1)
g.addEdge(1, 2)
g.addEdge(0, 2)
if isCycle(g) is True:
print("Graph Contains Cycle")
else:
print("Graph does not contains cycle")
if a[i][j] > a[i][k] + a[k][j]:
a[i][j] = a[i][k] + a[k][j]
path[i][j] = path[i][k] #运用了性质vi到v的最短路径的v的前一个点v·,
# 那么vi到v`也是最短路径，那么下一个顶点都是相同的
return (a, path)
if __name__ == '__main__':
#定义一个无穷数
inf = float('inf')
#定义有向图G7
G7 = [[0, inf, 6, 3, inf, inf, inf], [11, 0, 4, inf, inf, 7, inf],
[inf, 3, 0, inf, 5, inf, inf], [inf, inf, inf, 0, 5, inf, inf],
[inf, inf, inf, inf, 0, inf, 9], [inf, inf, inf, inf, inf, 0, 10],
[inf, inf, inf, inf, inf, inf, 0]]
g7 = graph(G7, inf)
#测试导入
# print(g7._mat)
# for x in range(g7._vnum):
# print(g7.out_edge(x),end=' ')
# print(' ')
#利用递归实现深度优先遍历DFS，得到生成树，正确
print(span_forest(g7))
print(' ')
print(K_MST(g7))
print(' ')
print(P_MST(g7)) #正确
print(' ')
#检验单源点到其他所有顶点的最短路径的算法
def reverse_graph(g):
new_graph = graph(g.size())
for v in g.nodes():
for c in g.children(v):
new_graph.addEdge(c, v)
return new_graph
visited[n] = True
stack = list()
stack.append(n)
while stack:
ele = stack.pop()
childs = g.children(ele)
for c in childs:
if visited[c] is False:
stack.append(c)
elif c != ele:
return True
return False
g = graph()
g.addEdge(1, 0)
g.addEdge(0, 2)
g.addEdge(2, 0)
g.addEdge(0, 3)
g.addEdge(3, 4)
if iscycle(g) is True:
print("Graph contains cycle")
else:
print("Graph does not contain cycle")
g = graph()
g.addEdge(0, 1)
g.addEdge(1, 2)
