def ctrl_transpose(self):
grapht = transpose(self._G)
if not self._G.is_graphb():
fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(25,15))
ax = axes.flatten()
graph = self._G
# print(graph.is_valued())
PRINT_GRAPH(graph, ax[0], 'Original')
grapht = transpose(graph)
PRINT_GRAPH(grapht, ax[1], 'Transposto')
# print(graph.vertexes['b'])
plt.show() # display
else:
print('A entrada deve ser um dígrafo.')
input()
def STRONGLY_CONNECTED_COMPONENTS(G: Graph):
order = TOPOLOGICAL_SORT(G)
Gt = transpose(G)
order.reverse()
# print(order)
fig, axes = plt.subplots(nrows=1, ncols=1, figsize=(25, 15))
# ax = axes.flatten()
# print(sorted(G.vertexes))
res = DFS(Gt, all=True, order=order)
random.seed()
roots = set()
for v in res.r:
roots.add(res.r[v])
hex_colors = {}
r = lambda: random.randint(0, 255)
for i in roots:
hex_colors[i] = '#%02X%02X%02X' % (r(), r(), r())
# print(hex_colors)
# print(res.r)
colors = {'roots': roots, 'hex': hex_colors, 'elements': res.r}
PRINT_GRAPH(G,
axes,
'Componentes Fortemente Conexas',
colors=colors,
colors_fun=get_colors_components)
# PRINT_GRAPH(Gt, ax[1], 'Transposto')
plt.show() # display
return roots, res.r
def ctrl_BFS(self, s):
graph = self._G
fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(25, 15))
PRINT_GRAPH(graph, axes[0], "Grafo", colors=None, colors_fun=get_colors_tree)
result = BFS(graph, s)
edges= []
order = list(result.q_path.queue)
# print(order)
# input(graph.get_type())
if(graph.get_type() == Type.DIGRAPH):
graph_caminho = AdjMatrix(graph.get_len(), Type.DIGRAPH, False)
else:
graph_caminho = AdjMatrix(graph.get_len(), Type.GRAPH, False)
ant = order.pop(0)
for v in order:
edges.append((ant, v))
graph_caminho.make_relation(ant, v)
ant = v
PRINT_GRAPH(graph_caminho, axes[1], "BFS", colors=edges, colors_fun=get_colors_bfs)
plt.show() # display
def ctrl_topological_sort(self):
graph = self._G
if not self._G.is_graphb():
fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(25, 15))
PRINT_GRAPH(graph, axes[0], "Grafo", colors=None, colors_fun=get_colors_tree)
order = TOPOLOGICAL_SORT(graph)
edges= []
order.reverse()
# print(order)
graph_caminho = AdjMatrix(graph.get_len(), Type.DIGRAPH, False)
ant = order.pop(0)
for v in order:
edges.append((ant, v))
graph_caminho.make_relation(ant, v)
ant = v
PRINT_GRAPH(graph_caminho, axes[1], "Ordem Topológica", colors=edges, colors_fun=get_colors_bfs)
plt.show() # display
else:
print('A entrada deve ser um dígrafo.')
input()
def ctrl_mst(self):
graph = self._G
if self._G.is_graphb():
result = KRUSKAL(graph)
graph = self._G
fig, axes = plt.subplots(nrows=1, ncols=1, figsize=(25, 15))
# print(result)
soma = 0
for val in result:
soma+=val[2]
PRINT_GRAPH(graph, axes, "AGM - Kruskal - Custo Total: {}".format(soma), colors=result, colors_fun=get_colors_tree)
plt.show() # display
else:
print('A entrada deve ser um grafo.')
input()
def ctrl_shortest_path(self, s):
graph = self._G
graph.set_num_edges(self.get_len_edges(self._contents))
result = DIJKSTRA(graph, s)
edges = []
textstr = 'Distâncias Mínimas:'
for v in graph.vertexes:
if v != s:
soma = 0
path = result.get_path(v)
for u, w in path:
soma += graph.get_value(u, w)
textstr += "\n{}: {}".format(v, soma)
edges += path
# print(soma)
fig, axes = plt.subplots(nrows=1, ncols=1, figsize=(25, 15))
props = dict(boxstyle='round', facecolor='wheat', alpha=0.5)
axes.text(0.05, 0.95, textstr, transform=axes.transAxes, fontsize=14, verticalalignment='top', bbox=props)
PRINT_GRAPH(graph, axes, "Caminho Mínimo - Dijkstra - Início({})".format(s), colors=edges, colors_fun=get_colors_dij)
plt.show() # display
def connected_components(G: Graph):
res = DFS(G)
random.seed()
r = lambda: random.randint(0, 255)
fig, axes = plt.subplots(nrows=1, ncols=1, figsize=(25, 15))
roots = set()
for v in res.r:
roots.add(res.r[v])
hex_colors = {}
for i in roots:
hex_colors[i] = '#%02X%02X%02X' % (r(), r(), r())
colors = {'roots': roots, 'hex': hex_colors, 'elements': res.r}
PRINT_GRAPH(G,
axes,
'Componentes Conexas',
colors=colors,
colors_fun=get_colors_components)
plt.show()
return roots, res.r
# elif(len(x) == 2):
# graph.make_relation(x[0], x[1])
# else:
# graph.make_relation(x[0], x[1], int(x[2]))
# # graph.print_all()
# return graph
def main():
tests()
if __name__ == "__main__":
contents = read_file("test/test_files/15_kruskal.txt")
graph = generate_graph(contents, True, False, True)
result = KRUSKAL(graph)
fig, axes = plt.subplots(nrows=1, ncols=1, figsize=(25, 15))
print(result)
soma = 0
for val in result:
soma += val[2]
PRINT_GRAPH(graph,
axes,
"AGM - Kruskal - Custo Total: {}".format(soma),
colors=result,
colors_fun=get_colors_tree)
plt.show() # display
# main()
graph.set_num_edges(get_len_edges(contents))
start = 't'
result = DIJKSTRA(graph, start)
edges = []
textstr = 'Distâncias Mínimas:'
for v in graph.vertexes:
if v != start:
soma = 0
path = result.get_path(v)
for u, w in path:
soma += graph.get_value(u, w)
textstr += "\n{}: {}".format(v, soma)
edges += path
print(soma)
fig, axes = plt.subplots(nrows=1, ncols=1, figsize=(25, 15))
props = dict(boxstyle='round', facecolor='wheat', alpha=0.5)
axes.text(0.05,
0.95,
textstr,
transform=axes.transAxes,
fontsize=14,
verticalalignment='top',
bbox=props)
PRINT_GRAPH(graph,
axes,
"Caminho Mínimo - Dijkstra - Início({})".format(start),
colors=edges,
colors_fun=get_colors_dij)
plt.show() # display
# return graph
def main():
# tests()
pass
if __name__ == "__main__":
# main()
contents = read_file("test/test_files/16_BFS.txt")
graph = generate_graph(contents, False, False, False)
fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(25, 15))
PRINT_GRAPH(graph,
axes[0],
"Grafo",
colors=None,
colors_fun=get_colors_tree)
result = BFS(graph, 'F')
edges = []
order = list(result.q_path.queue)
# print(order)
graph_caminho = AdjMatrix(graph.get_len(), Type.DIGRAPH, False)
ant = order.pop(0)
for v in order:
edges.append((ant, v))
graph_caminho.make_relation(ant, v)
ant = v
PRINT_GRAPH(graph_caminho,
def coloring(G: Graph):
if G.get_len() == 0:
return None
aux = ColoringAux(G)
if G.get_len() == 1:
for i in G.vertexes:
aux.colored[i] = aux.cc
else:
aux = ColoringAux(G)
u = bigger_degree(G)
coloring_vertex(G, u, aux)
# input(G.vertexes)
for v in G.vertexes:
if v not in aux.colored.keys():
coloring_vertex(G, v, aux)
hex_colors = {}
# print(aux.colored.keys())
# input()
cor = get_spaced_colors(aux.cc + 1) #cria as cores na quantidade cromática
# print(cor)
# input(len(cor))
# print(aux.colored)
# exit()
# flipped = {}
# for key, value in aux.colored.items():
# if value not in flipped:
# flipped[value] = [key]
# else:
# flipped[value].append(key)
# print(flipped)
# print(len(flipped))
# i = 0
# j = 1
# print(cor)
# print(len(cor))
# input()
# cor = [(0, 255, 0), (255, 0, 0), (0, 0, 255)]
# while i < len(flipped):
# for x in flipped[i]:
# hex_colors[x] = '#%02X%02X%02X' % cor[i]
# # print(cor[i])
# i+=1
for i in aux.colored:
hex_colors[i] = '#%02X%02X%02X' % cor[aux.colored[i]]
# print(hex_colors)
# hex_colors[i] = '#%02X%02X%02X' % (aux.colored[i]*89, aux.colored[i]*12, aux.colored[i]*100)
# print(cor)
colors = {'hex': hex_colors}
# print(colors)
# input()
plt.figure(figsize=(25, 15))
plt.axis('off')
PRINT_GRAPH(G, colors=colors, colors_fun=get_colors_coloring)
plt.title('Valor cromático: {0}'.format(aux.cc + 1))
plt.show()
return aux
from test.helper_leitura import *
from algorithms.PRINT_GRAPH import *
from algorithms.MINIMUM_PATH_AOG import *
from structs.graph import Type
if __name__ == "__main__":
# main()
contents = read_file("test/test_files/17_topological.txt")
graph = generate_graph(contents, False, False, False)
fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(25, 15))
PRINT_GRAPH(graph,
axes[0],
"Grafo",
colors=None,
colors_fun=get_colors_tree)
order = TOPOLOGICAL_SORT(graph)
edges = []
order.reverse()
# print(order)
graph_caminho = AdjMatrix(graph.get_len(), Type.DIGRAPH, False)
ant = order.pop(0)
for v in order:
edges.append((ant, v))
graph_caminho.make_relation(ant, v)
ant = v
PRINT_GRAPH(graph_caminho,
axes[1],
"Ordem Topológica",
colors=edges,
from algorithms.TRANSPOSE import *
from algorithms.PRINT_GRAPH import *
from test.helper_leitura import *
contents = read_file("test/test_files/11_prim_slide.txt")
fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(25, 15))
ax = axes.flatten()
graph = generate_graph(contents, True, False, False)
print(graph.is_valued())
PRINT_GRAPH(graph, ax[0], 'Original')
grapht = transpose(graph)
PRINT_GRAPH(grapht, ax[1], 'Transposto')
print(graph.vertexes['b'])
plt.show() # display