def __init__(self, graph: DirectedGraph):
self.matrix = []
for i in range(len(graph.get_nodes())):
self.matrix.append([0 for j in range(len(graph.get_nodes()))])
for edge in graph.get_edges():
nodes_ids = edge.get_nodes_ids()
self.matrix[nodes_ids[0].get_id()][nodes_ids[1].get_id()] = 1
def directed_graph_generator_np(n: int, p: float) -> DirectedGraph:
vertices = list([v for v in range(n)])
e = list()
for c in combinations(vertices, 2):
tmp = random()
if tmp < p:
e.append((Node(c[0]), Node(c[1])))
tmp2 = random()
if tmp2 < p:
e.append((Node(c[1]), Node(c[0])))
graph = DirectedGraph()
for v in vertices:
graph.add_node(Node(v))
graph.add_edges_from(e)
return graph
import os
from graphlib.DirectedGraph import DirectedGraph
from graphlib.representations.AdjacencyList import DirectedAdjacencyList
from graphlib.representations.AdjacencyMatrix import DirectedAdjacencyMatrix
directed_adjacency_list_graph = DirectedGraph.create_from_file(
os.path.dirname(__file__) + "/files/directed_adjacency_list.json",
"adjacency_list")
print(directed_adjacency_list_graph)
directed_adjacency_matrix_graph = DirectedGraph.create_from_file(
os.path.dirname(__file__) + "/files/directed_adjacency_matrix.json",
"adjacency_matrix")
print(directed_adjacency_matrix_graph)
directed_incidence_matrix_graph = DirectedGraph.create_from_file(
os.path.dirname(__file__) + "/files/directed_incidence_matrix.json",
"incidence_matrix")
print(directed_incidence_matrix_graph)
DirectedAdjacencyList(directed_incidence_matrix_graph).print()
import os
from graphlib.DirectedGraph import DirectedGraph
from graphlib.algorithms.Algorithms import Algorithms
graph = DirectedGraph.create_from_file(
os.path.dirname(__file__) + "/files/pagerank_list.json", "adjacency_list")
dict = Algorithms().pagerank_randomwalk(graph)
print("========= Błądzenie przypadkowe =========")
for key, value in dict.items():
print(f"({key}) ==> ", value)
dict2 = Algorithms().pagerank_randomwalk(graph)
print("========= Metoda iteracyjna =========")
for key, value in dict2.items():
print(f"({key}) ==> ", value)
def __init__(self, edges: List[Edge] = None, nodes: Set[Node] = None, is_weighted = False):
DirectedGraph.__init__(self, edges, nodes, is_weighted)
self.layers = list()
from graphlib.algorithms.Algorithms import Algorithms
import os
from graphlib.representations.AdjacencyList import DirectedAdjacencyList
np_graph = Generator.directed_graph_generator_np(5, 0.7)
np_graph.draw("graph_2.png")
print("ilość spójnych składowych:", np_graph.SCCs(np_graph))
DirectedAdjacencyList(np_graph).print()
print("------ example ------")
# ex_g = DirectedGraph.create_from_file(os.path.dirname(__file__) + "/files/digraph_ex.json", "adjacency_list")
ex_g = DirectedGraph.create_from_file(
os.path.dirname(__file__) + "/files/example.json", "adjacency_list")
DirectedAdjacencyList(ex_g).print()
comp3 = ex_g.SCCs(ex_g)
print("ilość spójnych składowych:", comp3)
print("------ example ------")
g = DirectedGraph()
g.add_weighted_edge(Node(0), Node(1), weight=-1)
g.add_weighted_edge(Node(1), Node(0), weight=4)
g.add_weighted_edge(Node(0), Node(2), weight=-4)
g.add_weighted_edge(Node(2), Node(1), weight=2)
D = Algorithms().johnson(g)
for i in range(len(D)):
print(D[i])
def __init__(self, graph: DirectedGraph) -> None:
self.list = {key: [] for key in range(len(graph.get_nodes()))}
for edge in graph.get_edges():
nodes = edge.get_nodes_ids()
self.list[nodes[0].get_id()].append(nodes[1].get_id())