def rotate(T, embedding, theta=90):
""" Rotate the embedding on the same graph to re-distribute qubit
assignments. If a perfect fit isn't found, due to disabled qubits,
the invalid embedding is still returned.
Optional arguments:
theta: ({0,90,180,270,360,-90,-180,-270})
Rotation angle.
Example:
>>> import embera
>>> import networkx as nx
>>> import dwave_networkx as dnx
>>> S = nx.complete_graph(11)
>>> T = dnx.chimera_graph(7)
>>> embedding = minorminer.find_embedding(S,T)
>>> dnx.draw_chimera_embedding(T,embedding,node_size=10)
>>> theta = 270
>>> new_embedding = embera.transform.embedding.rotate(T,embedding,theta)
>>> dnx.draw_chimera_embedding(T,new_embedding,node_size=10)
"""
tiling = DWaveNetworkXTiling(T)
shape = np.array(tiling.shape)
# Define rotations
m, n = tiling.shape
t = tiling.graph['tile']
if theta in [90, -270]:
new_tile = lambda i, j: (j, m - i - 1)
new_shore = lambda shore: 0 if shore else 1
new_k = lambda k, shore: t - k - 1 if shore else k
elif theta in [180, -180]:
new_tile = lambda i, j: (m - i - 1, n - j - 1)
new_shore = lambda shore: shore
new_k = lambda k, shore: t - k - 1
elif theta in [-90, 270]:
new_tile = lambda i, j: (n - j - 1, i)
new_shore = lambda shore: 0 if shore else 1
new_k = lambda k, shore: k if shore else t - k - 1
elif theta in [0, 360]:
return embedding
else:
raise ValueError("Value of theta not supported")
# Rotate all qubits by chain
new_embedding = {}
for v, chain in embedding.items():
new_chain = []
for q in chain:
k = tiling.get_k(q)
tile = tiling.get_tile(q)
shore = tiling.get_shore(q)
new_coordinates = (new_tile(*tile), new_shore(shore),
new_k(k, shore))
new_chain.append(next(tiling.get_qubits(*new_coordinates)))
new_embedding[v] = new_chain
return new_embedding
def translate(T, embedding, origin=(0, 0)):
""" Transport the embedding on the same graph to re-distribute qubit
assignments.
Optional arguments:
origin: (tuple)
A tuple of tile coordinates pointing to where the left-uppermost
occupied tile in the embedding should move to. All other tiles
are moved relative to the origin.
Example:
>>> import embera
>>> import networkx as nx
>>> import dwave_networkx as dnx
>>> S = nx.complete_graph(11)
>>> T = dnx.chimera_graph(7)
>>> embedding = minorminer.find_embedding(S,T)
>>> dnx.draw_chimera_embedding(T,embedding,node_size=10)
>>> origin = (2,3)
>>> new_embedding = embera.transform.embedding.translate(T,embedding,origin)
>>> dnx.draw_chimera_embedding(T,new_embedding,node_size=10)
"""
tiling = DWaveNetworkXTiling(T)
shape = tiling.shape
# Initialize offset
offset = shape
# Find margins
for v, chain in embedding.items():
for q in chain:
tile = np.array(tiling.get_tile(q))
offset = [min(t, o) for t, o in zip(tile, offset)]
# Define flips
m, n = tiling.shape
t = tiling.graph['tile']
new_embedding = {}
for v, chain in embedding.items():
new_chain = []
for q in chain:
k = tiling.get_k(q)
tile = tiling.get_tile(q)
shore = tiling.get_shore(q)
new_tile = tuple(
np.array(tile) - np.array(offset) + np.array(origin))
new_q = tiling.set_tile(q, new_tile)
new_chain.append(new_q)
new_embedding[v] = new_chain
return new_embedding
def mirror(T, embedding, axis=0):
""" Flip the embedding on the same graph to re-distribute qubit
assignments.
Optional arguments:
axis: {0,1}
0 toflip on horizontal and 1 to flip on vertical
Example:
>>> import embera
>>> import networkx as nx
>>> import dwave_networkx as dnx
>>> S = nx.complete_graph(11)
>>> T = dnx.chimera_graph(7)
>>> embedding = minorminer.find_embedding(S,T)
>>> dnx.draw_chimera_embedding(T,embedding,node_size=10)
>>> axis = 1
>>> new_embedding = embera.transform.embedding.mirror(T,embedding,axis)
>>> dnx.draw_chimera_embedding(T,new_embedding,node_size=10)
"""
tiling = DWaveNetworkXTiling(T)
shape = np.array(tiling.shape)
# Define flips
m, n = tiling.shape
t = tiling.graph['tile']
if axis is 0:
new_tile = lambda i, j: (i, n - j - 1)
new_k = lambda k, shore: k if shore else t - k - 1
elif axis is 1:
new_tile = lambda i, j: (m - i - 1, j)
new_k = lambda k, shore: t - k - 1 if shore else k
else:
raise ValueError("Value of axis not supported")
# Mirror all qubits by chain
new_embedding = {}
for v, chain in embedding.items():
new_chain = []
for q in chain:
k = tiling.get_k(q)
tile = tiling.get_tile(q)
shore = tiling.get_shore(q)
new_coordinates = (new_tile(*tile), shore, new_k(k, shore))
new_chain.append(next(tiling.get_qubits(*new_coordinates)))
new_embedding[v] = new_chain
return new_embedding