本文整理匯總了Python中networkx.grid_graph方法的典型用法代碼示例。如果您正苦於以下問題：Python networkx.grid_graph方法的具體用法？Python networkx.grid_graph怎麽用？Python networkx.grid_graph使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類networkx的用法示例。
在下文中一共展示了networkx.grid_graph方法的13個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: test_3d_2x2x2_on_c2
# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import grid_graph [as 別名]
def test_3d_2x2x2_on_c2(self):
embedding = find_grid_embedding([2, 2, 2], 2, 2, t=4)
# should be 4 grids
self.assertEqual(len(embedding), 2*2*2)
target_adj = dwave.embedding.target_to_source(dnx.chimera_graph(2), embedding)
G = nx.grid_graph(dim=[2, 2, 2])
for u in G.adj:
for v in G.adj[u]:
self.assertIn(u, target_adj)
self.assertIn(v, target_adj[u])
for u in target_adj:
for v in target_adj[u]:
self.assertIn(u, G.adj)
self.assertIn(v, G.adj[u]) 示例2: test_2d_6x4_on_c6
# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import grid_graph [as 別名]
def test_2d_6x4_on_c6(self):
dims = [3, 2]
chimera = (3,)
embedding = find_grid_embedding(dims, *chimera)
self.assertEqual(len(embedding), self.prod(dims))
target_adj = dwave.embedding.target_to_source(dnx.chimera_graph(*chimera), embedding)
G = nx.grid_graph(list(reversed(dims)))
for u in G.adj:
for v in G.adj[u]:
self.assertIn(u, target_adj)
self.assertIn(v, target_adj[u], "{} is not adjacent to {}".format(v, u))
for u in target_adj:
for v in target_adj[u]:
self.assertIn(u, G.adj)
self.assertIn(v, G.adj[u], "{} is not adjacent to {}".format(v, u)) 示例3: test_3d_4x4x4_on_c16
# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import grid_graph [as 別名]
def test_3d_4x4x4_on_c16(self):
dims = [4, 4, 4]
chimera = (16,)
embedding = find_grid_embedding(dims, *chimera)
self.assertEqual(len(embedding), self.prod(dims))
target_adj = dwave.embedding.target_to_source(dnx.chimera_graph(*chimera), embedding)
G = nx.grid_graph(dims)
for u in G.adj:
for v in G.adj[u]:
self.assertIn(u, target_adj)
self.assertIn(v, target_adj[u], "{} is not adjacent to {}".format(v, u))
self.assertEqual(set(G.nodes), set(target_adj)) 示例4: test_grid_graph
# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import grid_graph [as 別名]
def test_grid_graph(self):
"""grid_graph([n,m]) is a connected simple graph with the
following properties:
number_of_nodes = n*m
degree_histogram = [0,0,4,2*(n+m)-8,(n-2)*(m-2)]
"""
for n, m in [(3, 5), (5, 3), (4, 5), (5, 4)]:
dim = [n, m]
g = nx.grid_graph(dim)
assert_equal(len(g), n * m)
assert_equal(nx.degree_histogram(g), [0, 0, 4, 2 * (n + m) - 8,
(n - 2) * (m - 2)])
for n, m in [(1, 5), (5, 1)]:
dim = [n, m]
g = nx.grid_graph(dim)
assert_equal(len(g), n * m)
assert_true(nx.is_isomorphic(g, nx.path_graph(5)))
# mg = nx.grid_graph([n,m], create_using=MultiGraph())
# assert_equal(mg.edges(), g.edges()) 示例5: test_grid_graph
# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import grid_graph [as 別名]
def test_grid_graph(self):
"""grid_graph([n,m]) is a connected simple graph with the
following properties:
number_of_nodes = n*m
degree_histogram = [0,0,4,2*(n+m)-8,(n-2)*(m-2)]
"""
for n, m in [(3, 5), (5, 3), (4, 5), (5, 4)]:
dim = [n, m]
g = nx.grid_graph(dim)
assert_equal(len(g), n*m)
assert_equal(nx.degree_histogram(g), [0, 0, 4, 2 * (n + m) - 8,
(n - 2) * (m - 2)])
for n, m in [(1, 5), (5, 1)]:
dim = [n, m]
g = nx.grid_graph(dim)
assert_equal(len(g), n*m)
assert_true(nx.is_isomorphic(g, nx.path_graph(5)))
# mg = nx.grid_graph([n,m], create_using=MultiGraph())
# assert_equal(mg.edges(), g.edges()) 示例6: _gen_grid
# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import grid_graph [as 別名]
def _gen_grid(self, n):
for _ in range(n):
num_v = np.random.randint(self.min_num_v, self.max_num_v)
assert num_v >= 4, 'We require a grid graph to contain at least two ' \
'rows and two columns, thus 4 nodes, got {:d} ' \
'nodes'.format(num_v)
n_rows = np.random.randint(2, num_v // 2)
n_cols = num_v // n_rows
g = nx.grid_graph([n_rows, n_cols])
g = nx.convert_node_labels_to_integers(g)
self.graphs.append(g)
self.labels.append(5) 示例7: grid
# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import grid_graph [as 別名]
def grid(start, dim=2, role_start=0):
""" Builds a 2by2 grid
"""
grid_G = nx.grid_graph([dim, dim])
grid_G = nx.convert_node_labels_to_integers(grid_G, first_label=start)
roles = [role_start for i in grid_G.nodes()]
return grid_G, roles 示例8: test_draw_chimera_embedding
# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import grid_graph [as 別名]
def test_draw_chimera_embedding(self):
C = dnx.chimera_graph(4)
G = nx.grid_graph([2, 3, 2])
emb = {(0, 0, 0): [80, 48], (0, 0, 1): [50, 52], (0, 1, 0): [85, 93],
(0, 1, 1): [84, 82], (0, 2, 0): [89], (0, 2, 1): [92],
(1, 0, 0): [49, 54], (1, 0, 1): [83, 51], (1, 1, 0): [81],
(1, 1, 1): [86, 94], (1, 2, 0): [87, 95], (1, 2, 1): [91]}
dnx.draw_chimera_embedding(C, emb)
dnx.draw_chimera_embedding(C, emb, embedded_graph=G)
dnx.draw_chimera_embedding(C, emb, interaction_edges=C.edges()) 示例9: test_draw_pegasus_embedding
# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import grid_graph [as 別名]
def test_draw_pegasus_embedding(self):
P = dnx.pegasus_graph(2)
G = nx.grid_graph([3, 3, 2])
emb = {(0, 0, 0): [35], (0, 0, 1): [12], (0, 0, 2): [31], (0, 1, 0): [16],
(0, 1, 1): [36], (0, 1, 2): [11], (0, 2, 0): [39], (0, 2, 1): [6],
(0, 2, 2): [41], (1, 0, 0): [34], (1, 0, 1): [13], (1, 0, 2): [30],
(1, 1, 0): [17], (1, 1, 1): [37], (1, 1, 2): [10], (1, 2, 0): [38],
(1, 2, 1): [7], (1, 2, 2): [40]}
dnx.draw_pegasus_embedding(P, emb)
dnx.draw_pegasus_embedding(P, emb, embedded_graph=G)
dnx.draw_pegasus_embedding(P, emb, interaction_edges=P.edges())
dnx.draw_pegasus_embedding(P, emb, crosses=True) 示例10: test_naviable_small_world
# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import grid_graph [as 別名]
def test_naviable_small_world(self):
G = nx.navigable_small_world_graph(5,p=1,q=0)
gg = nx.grid_2d_graph(5,5).to_directed()
assert_true(nx.is_isomorphic(G,gg))
G = nx.navigable_small_world_graph(5,p=1,q=0,dim=3)
gg = nx.grid_graph([5,5,5]).to_directed()
assert_true(nx.is_isomorphic(G,gg))
G = nx.navigable_small_world_graph(5,p=1,q=0,dim=1)
gg = nx.grid_graph([5]).to_directed()
assert_true(nx.is_isomorphic(G,gg)) 示例11: test_navigable_small_world
# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import grid_graph [as 別名]
def test_navigable_small_world(self):
G = nx.navigable_small_world_graph(5, p=1, q=0, seed=42)
gg = nx.grid_2d_graph(5, 5).to_directed()
assert_true(nx.is_isomorphic(G, gg))
G = nx.navigable_small_world_graph(5, p=1, q=0, dim=3)
gg = nx.grid_graph([5, 5, 5]).to_directed()
assert_true(nx.is_isomorphic(G, gg))
G = nx.navigable_small_world_graph(5, p=1, q=0, dim=1)
gg = nx.grid_graph([5]).to_directed()
assert_true(nx.is_isomorphic(G, gg)) 示例12: test_node_input
# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import grid_graph [as 別名]
def test_node_input(self):
G = nx.grid_graph([range(7, 9), range(3, 6)])
assert_equal(len(G), 2 * 3)
assert_true(nx.is_isomorphic(G, nx.grid_graph([2, 3]))) 示例13: test_navigable_small_world
# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import grid_graph [as 別名]
def test_navigable_small_world(self):
G = nx.navigable_small_world_graph(5, p=1, q=0)
gg = nx.grid_2d_graph(5, 5).to_directed()
assert_true(nx.is_isomorphic(G, gg))
G = nx.navigable_small_world_graph(5, p=1, q=0, dim=3)
gg = nx.grid_graph([5, 5, 5]).to_directed()
assert_true(nx.is_isomorphic(G, gg))
G = nx.navigable_small_world_graph(5, p=1, q=0, dim=1)
gg = nx.grid_graph([5]).to_directed()
assert_true(nx.is_isomorphic(G, gg))