# This code is part of Qiskit.
#
# (C) Copyright IBM 2017, 2019.
#
# obtain a copy of this license in the LICENSE.txt file in the root directory
#
# Any modifications or derivative works of this code must retain this
# copyright notice, and modified files need to carry a notice indicating
# that they have been altered from the originals.

"""Return a circuit with any adjacent barriers merged together."""

from qiskit.transpiler.basepasses import TransformationPass
from qiskit.circuit.barrier import Barrier

"""Return a circuit with any adjacent barriers merged together.

Only barriers which can be merged without affecting the barrier structure
of the DAG will be merged.

Not all redundant barriers will necessarily be merged, only adjacent
barriers are merged.

For example, the circuit::

qr = QuantumRegister(3, 'q')
circuit = QuantumCircuit(qr)
circuit.barrier(qr[0])
circuit.barrier(qr[1])
circuit.barrier(qr)

Will be transformed into a circuit corresponding to::

circuit.barrier(qr[0])
circuit.barrier(qr)

after one iteration of the pass. These two barriers were not merged by the
first pass as they are not adjacent in the initial circuit.

The pass then can be reapplied to merge the newly adjacent barriers.
"""

[documentos]    def run(self, dag):
"""Run the MergeAdjacentBarriers pass on dag."""

# sorted to so that they are in the order they appear in the DAG
# so ancestors/descendants makes sense
barriers = [nd for nd in dag.topological_op_nodes() if nd.name == "barrier"]

# get dict of barrier merges

if not node_to_barrier_qubits:
return dag

# add the merged barriers to a new DAG

# go over current nodes, and add them to the new dag
for node in dag.topological_op_nodes():
if node.name == "barrier":
if node in node_to_barrier_qubits:
qubits = node_to_barrier_qubits[node]
# qubits are stored as a set, need to convert to a list
new_dag.apply_operation_back(Barrier(len(qubits)), qargs=list(qubits))
else:
# copy the condition over too
new_dag.apply_operation_back(node.op, qargs=node.qargs, cargs=node.cargs)
return new_dag

@staticmethod
def _collect_potential_merges(dag, barriers):
"""Return the potential merges.

Returns a dict of DAGNode : Barrier objects, where the barrier needs to be
inserted where the corresponding DAGNode appears in the main DAG.
"""
# if only got 1 or 0 barriers then can't merge
if len(barriers) < 2:
return None

# mapping from the node that will be the main barrier to the
# barrier object that gets built up
node_to_barrier_qubits = {}

# Start from the first barrier
current_barrier = barriers[0]
end_of_barrier = current_barrier
current_barrier_nodes = [current_barrier]

current_qubits = set(current_barrier.qargs)
current_ancestors = dag.ancestors(current_barrier)
current_descendants = dag.descendants(current_barrier)

for next_barrier in barriers[1:]:

# Ensure barriers are adjacent before checking if they are mergeable.
if dag._multi_graph.has_edge(end_of_barrier._node_id, next_barrier._node_id):

# Remove all barriers that have already been included in this new barrier from the
# set of ancestors/descendants as they will be removed from the new DAG when it is
# created.
next_ancestors = {
nd for nd in dag.ancestors(next_barrier) if nd not in current_barrier_nodes
}
next_descendants = {
nd for nd in dag.descendants(next_barrier) if nd not in current_barrier_nodes
}
next_qubits = set(next_barrier.qargs)

if (
not current_qubits.isdisjoint(next_qubits)
and current_ancestors.isdisjoint(next_descendants)
and current_descendants.isdisjoint(next_ancestors)
):

# can be merged
current_ancestors = current_ancestors | next_ancestors
current_descendants = current_descendants | next_descendants
current_qubits = current_qubits | next_qubits

# update the barrier that will be added back to include this barrier

end_of_barrier = next_barrier
current_barrier_nodes.append(end_of_barrier)

continue

# Fallback if barriers are not adjacent or not mergeable.

# store the previously made barrier
node_to_barrier_qubits[end_of_barrier] = current_qubits

# reset the properties
current_qubits = set(next_barrier.qargs)
current_ancestors = dag.ancestors(next_barrier)
current_descendants = dag.descendants(next_barrier)