def create_k_partite(maxi):
"""
Función para la creación de una gráfica k-partita.
:param maxi: La cota superior al número de vértices que tendrá
la gráfica aleatoria generada.
:return: Una gráfica k-partita de la biblioteca networkx.
:rtype: nx.Graph
"""
n = 1
k = 3
# Quiero repartir uniformemente la misma cantidad de vértices en cada partición.
while n % k != 0:
# Generando la n y la k (números para vértices y particiones, resp.) de forma
# aleatoria en un intervalo permitido.
n = randint(2, maxi)
k = randint(5, 10)
print("Orden de la gráfica (|V|):", n)
print("Número de particiones (k):", k)
# Dependiendo de un segundo volado, se genera una gráfica k-partida de uno u otro tipo.
which_type = randint(1, 2)
if which_type == 1:
return nx.complete_multipartite_graph(*_construct_list_kp(n, k)), k
else:
return nx.turan_graph(n, k), k
def get_graph_list(num_factors):
graph_list = []
# 2, 3 bipartite graph
g = nx.turan_graph(n=5, r=2)
graph_list.append(nx.to_numpy_array(g))
g = nx.house_x_graph()
graph_list.append(nx.to_numpy_array(g))
g = nx.balanced_tree(r=3, h=2)
graph_list.append(nx.to_numpy_array(g))
g = nx.grid_2d_graph(m=3, n=3)
graph_list.append(nx.to_numpy_array(g))
g = nx.hypercube_graph(n=3)
graph_list.append(nx.to_numpy_array(g))
g = nx.octahedral_graph()
graph_list.append(nx.to_numpy_array(g))
return graph_list[:num_factors]
def test_result_turan_graph_50_20(self):
assert (calc_and_compare(NX.turan_graph(50, 5)))
G3S=0
G1T=0
G2T=0
G3T=0
mu=10
sigma=2.5
#Orden logaritmico
for logarithmOrder in range(3,5):
print('Orden: ',logarithmOrder)
log = 2**logarithmOrder
ban=True
# 3 Metodos de generación distintos
G1 = nx.lollipop_graph(log, 2)
for e in G1.edges():
G1[e[0]][e[1]]['capacity'] = np.random.normal(mu, sigma)
G2 = nx.turan_graph(log, 2)
for e in G2.edges():
G2[e[0]][e[1]]['capacity'] = np.random.normal(mu, sigma)
G3 = nx.ladder_graph(log)
for e in G3.edges():
G3[e[0]][e[1]]['capacity'] = np.random.normal(mu, sigma)
for newPair in range(5):
print('Pareja: ',newPair)
#10 Grafos
for graphRepetition in range(10):
if ban:
ban=False
while G1T==G1S:
G1S = choice(list(G1.nodes()))
G1T = choice(list(G1.nodes()))
while G2T==G2S:
def test_turan_graph(self):
assert nx.number_of_edges(nx.turan_graph(13, 4)) == 63
assert is_isomorphic(nx.turan_graph(13, 4),
nx.complete_multipartite_graph(3, 4, 3, 3))
def get_connectivity_graph(qubits, topology='grid', param=None):
attempt = 0
while attempt < 10:
if topology == 'grid':
# assume square grid
side = int(np.sqrt(qubits))
G = nx.grid_2d_graph(side, side)
elif topology == 'erdosrenyi':
if param == None:
print("Erdos Renyi graph needs parameter p.")
G = nx.fast_gnp_random_graph(qubits, param)
elif topology == 'turan':
if param == None:
print("Turan graph needs parameter r.")
G = nx.turan_graph(qubits, param)
elif topology == 'regular':
if param == None:
print("d-regular graph needs parameter d.")
G = nx.random_regular_graph(param, qubits)
elif topology == 'cycle':
G = nx.cycle_graph(qubits)
elif topology == 'wheel':
G = nx.wheel_graph(qubits)
elif topology == 'complete':
G = nx.complete_graph(qubits)
elif topology == 'hexagonal':
# assume square hexagonal grid, node = 2(m+1)**2-2
side = int(np.sqrt((qubits + 2) / 2)) - 1
G = nx.hexagonal_lattice_graph(side, side)
elif topology == 'path':
G = nx.path_graph(qubits)
elif topology == 'ibm_falcon':
# https://www.ibm.com/blogs/research/2020/07/qv32-performance/
# 27 qubits
G = nx.empty_graph(27)
G.name = "ibm_falcon"
G.add_edges_from([(0, 1), (1, 2), (2, 3), (3, 4), (3, 5), (5, 6),
(6, 7), (7, 8), (8, 9), (8, 10), (10, 11),
(1, 12), (6, 13), (11, 14), (12, 15), (15, 16),
(16, 17), (17, 18), (17, 19), (19, 20), (13, 20),
(20, 21), (21, 22), (22, 23), (22, 24), (24, 25),
(14, 25), (25, 26)])
elif topology == 'ibm_penguin':
# 20 qubits
G = nx.empty_graph(20)
G.name = "ibm_penguin"
G.add_edges_from([(0, 1), (1, 2), (2, 3), (3, 4), (0, 5), (5, 6),
(6, 7), (7, 8), (8, 9), (4, 9), (5, 10),
(10, 11), (11, 12), (7, 12), (12, 13), (13, 14),
(9, 14), (10, 15), (15, 16), (16, 17), (17, 18),
(18, 19), (14, 19)])
elif topology == '1express': # path with express channels
G = nx.convert_node_labels_to_integers(nx.path_graph(qubits))
G.add_edges_from([(s, s + param)
for s in range(0, qubits - param, param // 2)])
elif topology == '2express': # grid with express channels
side = int(np.sqrt(qubits))
G = nx.convert_node_labels_to_integers(nx.grid_2d_graph(
side, side))
G.add_edges_from([
(s, s + param) for x in range(side)
for s in range(x * side, x * side + side - param, param // 2)
]) # rows
G.add_edges_from([
(s, s + param * side) for y in range(side)
for s in range(y, y + side * (side - param), param // 2 * side)
]) # cols
else:
print("Topology %s not recognized; use empty graph instead." %
topology)
G = nx.empty_graph(qubits)
if nx.is_connected(G) or nx.is_empty(G):
break
else:
attempt += 1
return nx.convert_node_labels_to_integers(G)
G = nx.random_lobster(6, 0.9, 0.9)
G = nx.barabasi_albert_graph(8, 5)
G = nx.watts_strogatz_graph(8, 3, 0.1)
G = nx.erdos_renyi_graph(10, 0.15)
G = nx.complete_bipartite_graph(3, 5)
G = nx.dorogovtsev_goltsev_mendes_graph(2)
G = nx.petersen_graph()
G = nx.tutte_graph()
G = nx.sedgewick_maze_graph() # cool
# G = nx.tetrahedral_graph() # not cool
G = nx.ladder_graph(8)
G = nx.barbell_graph(5, 2)
G = nx.turan_graph(10, 3)
def g2d(g):
return {k: {k1 for k1 in v} for k, v in g.adj.items()}
#pprint(g2d(G))
#nx.draw_shell(G)
#plt.show()
# sorting nodes (with optional tails - additional strings for each node):
# for each node - create "projection"
# slice graph into levels by distance
# append levels with subgraphs not connected to selected node
# canonicalize each subgraph and sort them
'gen':
nx.trivial_graph(),
'description_fn':
'trivial_graph()',
'description':
'Return the Trivial graph with one node (with label 0) and no edges.',
},
'turan_graph': {
'name': 'Turan Graph',
'args': ('n', 'r'),
'argtypes': (
int,
int,
),
'argvals': (3, 3),
'gen': lambda n, r: nx.turan_graph(n, r),
'description_fn': 'turan_graph(n, r)',
'description': 'Return the Turan Graph.',
},
'wheel_graph': {
'name': 'Wheel Graph',
'args': ('n', ),
'argtypes': (int, ),
'argvals': (3, ),
'gen': lambda n: nx.wheel_graph(n),
'description_fn': 'wheel_graph(n)',
'description': 'Return the wheel graph.',
},
'random_geometric': {
'name':
'Random Geometric',
fig = plt.figure() nx.draw(G, with_labels=True) fig.text(0.02, 0.95, "path graph", fontweight='bold') fig.text(0.02, 0.90, "n(node count) = " + str(n)) plt.show() #star graph G = nx.star_graph(n) fig = plt.figure() nx.draw(G, with_labels=True) fig.text(0.02, 0.95, "star graph", fontweight='bold') fig.text(0.02, 0.90, "n(node count) = " + str(n)) plt.show() #turan graph G = nx.turan_graph(n, 2) fig = plt.figure() nx.draw(G, with_labels=True) fig.text(0.02, 0.95, "turan graph", fontweight='bold') fig.text(0.02, 0.90, "n(node count) = " + str(n)) fig.text(0.02, 0.85, "with 2 disjoint subset") plt.show() #wheel graph G = nx.wheel_graph(n) fig = plt.figure() nx.draw(G, with_labels=True) fig.text(0.02, 0.95, "wheel graph", fontweight='bold') fig.text(0.02, 0.90, "n(node count) = " + str(n)) plt.show()
def create_k_partitte_graph(n: int, k: int) -> nx.classes.graph.Graph:
return nx.turan_graph(n, k)
