# Quellcode für qiskit.transpiler.coupling

```
# This code is part of Qiskit.
#
# (C) Copyright IBM 2017, 2019.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# 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.
"""
Directed graph object for representing coupling between physical qubits.
The nodes of the graph correspond to physical qubits (represented as integers) and the
directed edges indicate which physical qubits are coupled and the permitted direction of
CNOT gates. The object has a distance function that can be used to map quantum circuits
onto a device with this coupling.
"""
import io
import warnings
import numpy as np
import retworkx as rx
from qiskit.transpiler.exceptions import CouplingError
from qiskit.exceptions import MissingOptionalLibraryError
[Doku]class CouplingMap:
"""
Directed graph specifying fixed coupling.
Nodes correspond to physical qubits (integers) and directed edges correspond
to permitted CNOT gates, with source and destination corresponding to control
and target qubits, respectively.
"""
__slots__ = ("description", "graph", "_dist_matrix", "_qubit_list", "_size", "_is_symmetric")
def __init__(self, couplinglist=None, description=None):
"""
Create coupling graph. By default, the generated coupling has no nodes.
Args:
couplinglist (list or None): An initial coupling graph, specified as
an adjacency list containing couplings, e.g. [[0,1], [0,2], [1,2]].
It is required that nodes are contiguously indexed starting at 0.
Missed nodes will be added as isolated nodes in the coupling map.
description (str): A string to describe the coupling map.
"""
self.description = description
# the coupling map graph
self.graph = rx.PyDiGraph()
# a dict of dicts from node pairs to distances
self._dist_matrix = None
# a sorted list of physical qubits (integers) in this coupling map
self._qubit_list = None
# number of qubits in the graph
self._size = None
self._is_symmetric = None
if couplinglist is not None:
self.graph.extend_from_edge_list([tuple(x) for x in couplinglist])
[Doku] def size(self):
"""Return the number of physical qubits in this graph."""
if self._size is None:
self._size = len(self.graph)
return self._size
[Doku] def get_edges(self):
"""
Gets the list of edges in the coupling graph.
Returns:
Tuple(int,int): Each edge is a pair of physical qubits.
"""
return self.graph.edge_list()
[Doku] def add_physical_qubit(self, physical_qubit):
"""Add a physical qubit to the coupling graph as a node.
physical_qubit (int): An integer representing a physical qubit.
Raises:
CouplingError: if trying to add duplicate qubit
"""
if not isinstance(physical_qubit, int):
raise CouplingError("Physical qubits should be integers.")
if physical_qubit in self.physical_qubits:
raise CouplingError(
"The physical qubit %s is already in the coupling graph" % physical_qubit
)
self.graph.add_node(physical_qubit)
self._dist_matrix = None # invalidate
self._qubit_list = None # invalidate
self._size = None # invalidate
[Doku] def add_edge(self, src, dst):
"""
Add directed edge to coupling graph.
src (int): source physical qubit
dst (int): destination physical qubit
"""
if src not in self.physical_qubits:
self.add_physical_qubit(src)
if dst not in self.physical_qubits:
self.add_physical_qubit(dst)
self.graph.add_edge(src, dst, None)
self._dist_matrix = None # invalidate
self._is_symmetric = None # invalidate
[Doku] def subgraph(self, nodelist):
"""Return a CouplingMap object for a subgraph of self.
nodelist (list): list of integer node labels
"""
warnings.warn(
"The .subgraph() method is deprecated and will be removed in a "
"future release. Instead the .reduce() method should be used "
"instead which does the same thing but preserves nodelist order.",
DeprecationWarning,
stacklevel=2,
)
subcoupling = CouplingMap()
subcoupling.graph = self.graph.subgraph(nodelist)
return subcoupling
@property
def physical_qubits(self):
"""Returns a sorted list of physical_qubits"""
if self._qubit_list is None:
self._qubit_list = self.graph.node_indexes()
return self._qubit_list
[Doku] def is_connected(self):
"""
Test if the graph is connected.
Return True if connected, False otherwise
"""
try:
return rx.is_weakly_connected(self.graph)
except rx.NullGraph:
return False
[Doku] def neighbors(self, physical_qubit):
"""Return the nearest neighbors of a physical qubit.
Directionality matters, i.e. a neighbor must be reachable
by going one hop in the direction of an edge.
"""
return self.graph.neighbors(physical_qubit)
@property
def distance_matrix(self):
"""Return the distance matrix for the coupling map."""
self.compute_distance_matrix()
return self._dist_matrix
[Doku] def compute_distance_matrix(self):
"""Compute the full distance matrix on pairs of nodes.
The distance map self._dist_matrix is computed from the graph using
all_pairs_shortest_path_length. This is normally handled internally
by the :attr:`~qiskit.transpiler.CouplingMap.distance_matrix`
attribute or the :meth:`~qiskit.transpiler.CouplingMap.distance` method
but can be called if you're accessing the distance matrix outside of
those or want to pre-generate it.
"""
if self._dist_matrix is None:
if not self.is_connected():
raise CouplingError("coupling graph not connected")
self._dist_matrix = rx.digraph_distance_matrix(self.graph, as_undirected=True)
[Doku] def distance(self, physical_qubit1, physical_qubit2):
"""Returns the undirected distance between physical_qubit1 and physical_qubit2.
Args:
physical_qubit1 (int): A physical qubit
physical_qubit2 (int): Another physical qubit
Returns:
int: The undirected distance
Raises:
CouplingError: if the qubits do not exist in the CouplingMap
"""
if physical_qubit1 >= self.size():
raise CouplingError("%s not in coupling graph" % physical_qubit1)
if physical_qubit2 >= self.size():
raise CouplingError("%s not in coupling graph" % physical_qubit2)
self.compute_distance_matrix()
return int(self._dist_matrix[physical_qubit1, physical_qubit2])
[Doku] def shortest_undirected_path(self, physical_qubit1, physical_qubit2):
"""Returns the shortest undirected path between physical_qubit1 and physical_qubit2.
Args:
physical_qubit1 (int): A physical qubit
physical_qubit2 (int): Another physical qubit
Returns:
List: The shortest undirected path
Raises:
CouplingError: When there is no path between physical_qubit1, physical_qubit2.
"""
paths = rx.digraph_dijkstra_shortest_paths(
self.graph, source=physical_qubit1, target=physical_qubit2, as_undirected=True
)
if not paths:
raise CouplingError(
f"Nodes {str(physical_qubit1)} and {str(physical_qubit2)} are not connected"
)
return paths[physical_qubit2]
@property
def is_symmetric(self):
"""
Test if the graph is symmetric.
Return True if symmetric, False otherwise
"""
if self._is_symmetric is None:
self._is_symmetric = self._check_symmetry()
return self._is_symmetric
[Doku] def make_symmetric(self):
"""
Convert uni-directional edges into bi-directional.
"""
edges = self.get_edges()
for src, dest in edges:
if (dest, src) not in edges:
self.add_edge(dest, src)
self._dist_matrix = None # invalidate
self._is_symmetric = None # invalidate
def _check_symmetry(self):
"""
Calculates symmetry
Returns:
Bool: True if symmetric, False otherwise
"""
return self.graph.is_symmetric()
[Doku] def reduce(self, mapping):
"""Returns a reduced coupling map that
corresponds to the subgraph of qubits
selected in the mapping.
Args:
mapping (list): A mapping of reduced qubits to device
qubits.
Returns:
CouplingMap: A reduced coupling_map for the selected qubits.
Raises:
CouplingError: Reduced coupling map must be connected.
"""
from scipy.sparse import coo_matrix, csgraph
reduced_qubits = len(mapping)
inv_map = [None] * (max(mapping) + 1)
for idx, val in enumerate(mapping):
inv_map[val] = idx
reduced_cmap = []
for edge in self.get_edges():
if edge[0] in mapping and edge[1] in mapping:
reduced_cmap.append([inv_map[edge[0]], inv_map[edge[1]]])
# Verify coupling_map is connected
rows = np.array([edge[0] for edge in reduced_cmap], dtype=int)
cols = np.array([edge[1] for edge in reduced_cmap], dtype=int)
data = np.ones_like(rows)
mat = coo_matrix((data, (rows, cols)), shape=(reduced_qubits, reduced_qubits)).tocsr()
if csgraph.connected_components(mat)[0] != 1:
raise CouplingError("coupling_map must be connected.")
return CouplingMap(reduced_cmap)
[Doku] @classmethod
def from_full(cls, num_qubits, bidirectional=True) -> "CouplingMap":
"""Return a fully connected coupling map on n qubits."""
cmap = cls(description="full")
if bidirectional:
cmap.graph = rx.generators.directed_mesh_graph(num_qubits)
else:
edge_list = []
for i in range(num_qubits):
for j in range(i):
edge_list.append((j, i))
cmap.graph.extend_from_edge_list(edge_list)
return cmap
[Doku] @classmethod
def from_line(cls, num_qubits, bidirectional=True) -> "CouplingMap":
"""Return a coupling map of n qubits connected in a line."""
cmap = cls(description="line")
cmap.graph = rx.generators.directed_path_graph(num_qubits, bidirectional=bidirectional)
return cmap
[Doku] @classmethod
def from_ring(cls, num_qubits, bidirectional=True) -> "CouplingMap":
"""Return a coupling map of n qubits connected to each of their neighbors in a ring."""
cmap = cls(description="ring")
cmap.graph = rx.generators.directed_cycle_graph(num_qubits, bidirectional=bidirectional)
return cmap
[Doku] @classmethod
def from_grid(cls, num_rows, num_columns, bidirectional=True) -> "CouplingMap":
"""Return a coupling map of qubits connected on a grid of num_rows x num_columns."""
cmap = cls(description="grid")
cmap.graph = rx.generators.directed_grid_graph(
num_rows, num_columns, bidirectional=bidirectional
)
return cmap
[Doku] @classmethod
def from_heavy_hex(cls, distance, bidirectional=True) -> "CouplingMap":
"""Return a heavy hexagon graph coupling map.
A heavy hexagon graph is described in:
https://journals.aps.org/prx/abstract/10.1103/PhysRevX.10.011022
Args:
distance (int): The code distance for the generated heavy hex
graph. The value for distance can be any odd positive integer.
The distance relates to the number of qubits by:
:math:`n = \\frac{5d^2 - 2d - 1}{2}` where :math:`n` is the
number of qubits and :math:`d` is the ``distance`` parameter.
bidirectional (bool): Whether the edges in the output coupling
graph are bidirectional or not. By default this is set to
``True``
Returns:
CouplingMap: A heavy hex coupling graph
"""
cmap = cls(description="heavy-hex")
cmap.graph = rx.generators.directed_heavy_hex_graph(distance, bidirectional=bidirectional)
return cmap
[Doku] @classmethod
def from_heavy_square(cls, distance, bidirectional=True) -> "CouplingMap":
"""Return a heavy square graph coupling map.
A heavy square graph is described in:
https://journals.aps.org/prx/abstract/10.1103/PhysRevX.10.011022
Args:
distance (int): The code distance for the generated heavy square
graph. The value for distance can be any odd positive integer.
The distance relates to the number of qubits by:
:math:`n = 3d^2 - 2d` where :math:`n` is the
number of qubits and :math:`d` is the ``distance`` parameter.
bidirectional (bool): Whether the edges in the output coupling
graph are bidirectional or not. By default this is set to
``True``
Returns:
CouplingMap: A heavy square coupling graph
"""
cmap = cls(description="heavy-square")
cmap.graph = rx.generators.directed_heavy_square_graph(
distance, bidirectional=bidirectional
)
return cmap
[Doku] @classmethod
def from_hexagonal_lattice(cls, rows, cols, bidirectional=True) -> "CouplingMap":
"""Return a hexagonal lattice graph coupling map.
Args:
rows (int): The number of rows to generate the graph with.
cols (int): The number of columns to generate the graph with.
bidirectional (bool): Whether the edges in the output coupling
graph are bidirectional or not. By default this is set to
``True``
Returns:
CouplingMap: A hexagonal lattice coupling graph
"""
cmap = cls(description="hexagonal-lattice")
cmap.graph = rx.generators.directed_hexagonal_lattice_graph(
rows, cols, bidirectional=bidirectional
)
return cmap
[Doku] def largest_connected_component(self):
"""Return a set of qubits in the largest connected component."""
return max(rx.weakly_connected_components(self.graph), key=len)
def __str__(self):
"""Return a string representation of the coupling graph."""
string = ""
if self.get_edges():
string += "["
string += ", ".join([f"[{src}, {dst}]" for (src, dst) in self.get_edges()])
string += "]"
return string
[Doku] def draw(self):
"""Draws the coupling map.
This function needs `pydot <https://github.com/erocarrera/pydot>`_,
which in turn needs `Graphviz <https://www.graphviz.org/>`_ to be
installed. Additionally, `pillow <https://python-pillow.org/>`_ will
need to be installed.
Returns:
PIL.Image: Drawn coupling map.
Raises:
MissingOptionalLibraryError: when pydot or pillow are not installed.
"""
try:
import pydot
except ImportError as ex:
raise MissingOptionalLibraryError(
libname="pydot",
name="coupling map drawer",
pip_install="pip install pydot",
) from ex
try:
from PIL import Image
except ImportError as ex:
raise MissingOptionalLibraryError(
libname="pillow",
name="coupling map drawer",
pip_install="pip install pillow",
) from ex
dot_str = self.graph.to_dot()
dot = pydot.graph_from_dot_data(dot_str)[0]
png = dot.create_png(prog="neato")
return Image.open(io.BytesIO(png))
```