def place_line(self, device: 'cirq.google.XmonDevice', length: int) -> GridQubitLineTuple:
"""Runs line sequence search.
Args:
device: Chip description.
length: Required line length.
Returns:
List of linear sequences on the chip found by simulated annealing
method.
"""
seqs = AnnealSequenceSearch(device, self.seed).search(self.trace_func)
return GridQubitLineTuple.best_of(seqs, length)
def place_line(self,
device: 'cirq.google.XmonDevice',
length: int) -> GridQubitLineTuple:
"""Runs line sequence search.
Args:
device: Chip description.
length: Required line length.
Returns:
Linear sequences found on the chip.
Raises:
ValueError: If search algorithm passed on initialization is not
recognized.
"""
if not device.qubits:
return GridQubitLineTuple()
start = min(device.qubits) # type: GridQubit
sequences = [] # type: List[LineSequence]
greedy_search = {
'minimal_connectivity': [
_PickFewestNeighbors(device, start),
],
'largest_area': [
_PickLargestArea(device, start),
],
'best': [
_PickFewestNeighbors(device, start),
_PickLargestArea(device, start),
]
} # type: Dict[str, List[GreedySequenceSearch]]
algos = greedy_search.get(self.algorithm)
if algos is None:
raise ValueError(
"Unknown greedy search algorithm %s" % self.algorithm)
for algorithm in algos:
sequences.append(algorithm.get_or_search())
return GridQubitLineTuple.best_of(sequences, length)
def test_best_of_gets_longest_needs_minimum():
q00 = cirq.GridQubit(0, 0)
q01 = cirq.GridQubit(0, 1)
assert GridQubitLineTuple.best_of([[]], 0) == ()
assert GridQubitLineTuple.best_of([[], [q00]], 0) == ()
assert GridQubitLineTuple.best_of([[q00], []], 0) == ()
assert GridQubitLineTuple.best_of([[], [q00]], 1) == (q00,)
assert GridQubitLineTuple.best_of([[q00], []], 1) == (q00,)
assert GridQubitLineTuple.best_of([[q00, q01], [q00]], 1) == (q00,)
assert GridQubitLineTuple.best_of([[q00, q01], [q00]], 2) == (q00, q01)
assert GridQubitLineTuple.best_of([[q00, q01]], 2) == (q00, q01)
assert GridQubitLineTuple.best_of([], 0) == ()
with pytest.raises(NotFoundError):
_ = GridQubitLineTuple.best_of([[]], 1)
with pytest.raises(NotFoundError):
_ = GridQubitLineTuple.best_of([[q00]], 2)