Make weight_fn optional in adjacency matrix and fw numpy #158
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This commit makes the weight_fn argument for graph_adjacency_matrix, digraph_adjacency_matrix, graph_floyd_warshall_numpy, and digraph_floyd_warshall_numpy optional. A new kwarg is added default_weight (which defaults to 1.0) which can be used instead of passing a callable. If weight_fn is not set the value of default_weight will be used for all edges. Previously, a function returning a fixed value would have to be used to accomplish this. In practice there was not much overhead to just using something like 'lambda _: 1' as the weight fn, but it was a bit of a clumsy interface.
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This commit migrates Terra's CouplingMap class to us retworkx internally instead of networkx providing >10x speed improvement for CouplingMap operations. Requires: Qiskit/rustworkx#157 Qiskit/rustworkx#156 Qiskit/rustworkx#144 Qiskit/rustworkx#143 Qiskit/rustworkx#147 Qiskit/rustworkx#158 Qiskit/rustworkx#162 Qiskit/rustworkx#161 all be applied to the retworkx version installed.
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* WIP: Use retworkx for CouplingMap This commit migrates Terra's CouplingMap class to us retworkx internally instead of networkx providing >10x speed improvement for CouplingMap operations. Requires: Qiskit/rustworkx#157 Qiskit/rustworkx#156 Qiskit/rustworkx#144 Qiskit/rustworkx#143 Qiskit/rustworkx#147 Qiskit/rustworkx#158 Qiskit/rustworkx#162 Qiskit/rustworkx#161 all be applied to the retworkx version installed. * DNM: Install retworkx from source * DNM: Add retworkx custom branch to travis * Fix draw() copy paste error * Fix typo * DNK: Add source retworkx to docs build * Fix lint * Use graph_distance_matrix instead of floyd warshall * DNM also add retworkx from source for image test job * Use Gnm random function from retworkx in token swapper tests * Remove nx import from token swapper tests * Fix lint * Remove install from git from CI config since retworkx 0.6.0 is released * Fix api call * Use retworkx generators where possible for constructors * Remvoe source install from travis config * Bump version in setup.py too * Use extend_from_edge_list for from_full * Update qiskit/transpiler/coupling.py * Use edge_list() return and has_edge() in sabre In Qiskit/rustworkx#204 the return type of the edge_list() method will be returned as a custom sequence type the defer the type conversion from rust to python. So casting to a list no longer will be a no-op after that point so this commit removes the cast. At the same time in the sabre swap pass one of the bottlenecks at large qubit counts is traversing that edge list looking for edges, this updates that to use the has_edge() method which should be faster than a full list traversal every iteration. * Fix issue in layout_transformation pass In #5281 the layout transformation pass was updated to handle the case where the coupling map was not defined. In those cases for the purposes of the layout transformation it treats the coupling map as being fully connected. So it creates a new full coupling map to use for the token swapper. However, it neglects that the token swapper expects an undirected graph and was passing in a directed graph. This didn't matter too much for the networkx based coupling map object because networkx can handle directed or undirected in the same function. But, for retworkx directed graphs and undirected graphs are different types an can't be used interchangeably. This commit fixes this issue in that pass. * Update qiskit/transpiler/passes/routing/algorithms/token_swapper.py Co-authored-by: Julien Gacon <gaconju@gmail.com> * Fix Lint Co-authored-by: Julien Gacon <gaconju@gmail.com> Co-authored-by: Kevin Krsulich <kevin.krsulich@ibm.com> Co-authored-by: mergify[bot] <37929162+mergify[bot]@users.noreply.github.com>
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This commit makes the weight_fn argument for graph_adjacency_matrix,
digraph_adjacency_matrix, graph_floyd_warshall_numpy, and
digraph_floyd_warshall_numpy optional. A new kwarg is added
default_weight (which defaults to 1.0) which can be used instead of
passing a callable. If weight_fn is not set the value of default_weight
will be used for all edges. Previously, a function returning a fixed
value would have to be used to accomplish this. In practice there was
not much overhead to just using something like 'lambda _: 1' as the
weight fn, but it was a bit of a clumsy interface.
TODO: