def test_draw_pegasus_biases(self):
G = dnx.pegasus_graph(2)
h = {v: v % 12 for v in G}
J = {(u, v) if u % 2 else (v, u): (u + v) % 24 for u, v in G.edges()}
for v in G:
J[v, v] = .1
dnx.draw_pegasus(G, linear_biases=h, quadratic_biases=J)
def draw_architecture(target_graph, **kwargs):
""" Draws graph G according to G's family layout.
"""
family = target_graph.graph['family']
if family == 'chimera':
dnx.draw_chimera(target_graph, **kwargs)
elif family == 'pegasus':
dnx.draw_pegasus(target_graph, **kwargs)
else:
nx.draw_spring(target_graph)
warnings.warn(
"Graph family not available. Using NetworkX spring layout")
def yield_double_plot(P, filename):
fig = plt.figure(figsize=(40, 20))
axes = fig.subplots(nrows=1, ncols=2)
dnx.draw_pegasus_yield(P, node_size=80, ax=axes[0])
dnx.draw_pegasus(P,
crosses=True,
node_size=80,
node_color="#f37820",
edge_color="#17bebb",
ax=axes[1])
fig.tight_layout()
plt.savefig(filename)
plt.close()
double_plot(K, P16, clique_embedding, 'clique_doubleplot.png',
[{
'node_size': 100,
'pos': nx.circular_layout(K),
'width': 1,
'edge_color': (0, 0, 0, .1)
}, {
'node_size': 10
}])
from embed_draw_sparse import C, layout_C, emb as sparse_embedding
double_plot(C, P6, sparse_embedding, 'sparse_doubleplot.png',
[{
'node_size': 70,
'pos': layout_C
}, {
'node_size': 30
}])
fig = plt.figure(figsize=(20, 20))
dnx.draw_pegasus(dnx.pegasus_graph(3),
node_color="#f37820",
edge_color="#17bebb",
crosses=True)
plt.savefig("P3.png")
plt.close()
yield_double_plot(P6, "yield_doubleplot.png")
# Copyright 2020 D-Wave Systems Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from pegasus_graph import P6
import dwave_networkx as dnx
import matplotlib
try:
import matplotlib.pyplot as plt
except ImportError:
matplotlib.use("agg")
import matplotlib.pyplot as plt
dnx.draw_pegasus_yield(P6, node_size=80)
dnx.draw_pegasus(P6, node_size=80)
classical_sampler = neal.SimulatedAnnealingSampler() sampler = dimod.StructureComposite(classical_sampler, P6.nodes, P6.edges) # %% # Working With Embeddings # 全結合の40ノードを作りたい num_variables = 40 embedding = dwave.embedding.chimera.find_clique_embedding(num_variables, 16) max(len(chain) for chain in embedding.values()) # チェーン数は11 # %% # 680 node Pegasus num_variables = 40 embedding = dwave.embedding.pegasus.find_clique_embedding(num_variables, 6) max(len(chain) for chain in embedding.values()) # チェーン数は6 # %% # https://qiita.com/YuichiroMinato/items/dbc142ecb1efbebd6adf chimera = dnx.chimera_graph(2, 2, 4) dnx.draw_chimera(chimera) plt.show() # %% P3 = dnx.pegasus_graph(2) dnx.draw_pegasus(P3) plt.show() # %%
