diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index cf6a27dc..3441ff90 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -34,7 +34,7 @@ jobs: CIBW_BUILD: "${{ matrix.os_dist.dist }}" CIBW_ARCHS_MACOS: "x86_64 universal2 arm64" CIBW_BEFORE_BUILD: pip install --upgrade ninja - CIBW_TEST_REQUIRES: pytest stim~=1.10.dev1666411378 + CIBW_TEST_REQUIRES: pytest stim CIBW_TEST_COMMAND: pytest {project}/tests strategy: fail-fast: false @@ -116,6 +116,8 @@ jobs: - uses: actions/checkout@v3 with: submodules: true + + - uses: actions/setup-python@v4 - name: Install g++ if: runner.os == 'Linux' @@ -123,7 +125,7 @@ jobs: sudo apt update sudo apt install gcc-10 g++-10 - - uses: pypa/cibuildwheel@v2.16.4 + - uses: pypa/cibuildwheel@v2.16.5 - name: Verify clean directory run: git diff --exit-code @@ -179,7 +181,7 @@ jobs: fail-fast: false matrix: platform: [windows-latest, macos-latest, ubuntu-latest] - python-version: ["3.10"] + python-version: ["3.11"] runs-on: ${{ matrix.platform }} @@ -193,16 +195,16 @@ jobs: python-version: ${{ matrix.python-version }} - name: Add requirements - run: python -m pip install --upgrade cmake>=3.12 ninja==1.10.2.4 pytest flake8 pytest-cov + run: python -m pip install --upgrade cmake>=3.12 ninja pytest flake8 pytest-cov setuptools - name: Build and install - run: pip install --verbose -e . + run: python -m pip install --verbose -e . - name: Test without stim run: python -m pytest tests - name: Add stim - run: python -m pip install stim~=1.10.dev1666411378 + run: python -m pip install stim - name: Test with stim using coverage run: python -m pytest tests --cov=./src/pymatching --cov-report term @@ -218,8 +220,6 @@ jobs: submodules: true - uses: actions/setup-python@v4 - with: - python-version: ${{ matrix.python-version }} - name: Install pandoc run: | @@ -244,7 +244,7 @@ jobs: with: python-version: '3.10' - name: Add requirements - run: python -m pip install --upgrade cmake>=3.12 ninja==1.10.2.4 pytest flake8 pytest-cov stim~=1.10.dev1666411378 + run: python -m pip install --upgrade cmake>=3.12 ninja pytest flake8 pytest-cov stim - name: Build and install run: pip install --verbose -e . - name: Run tests and collect coverage diff --git a/src/pymatching/sparse_blossom/driver/user_graph.cc b/src/pymatching/sparse_blossom/driver/user_graph.cc index 564b3d4b..47ba74eb 100644 --- a/src/pymatching/sparse_blossom/driver/user_graph.cc +++ b/src/pymatching/sparse_blossom/driver/user_graph.cc @@ -245,18 +245,17 @@ double pm::UserGraph::max_abs_weight() { pm::MatchingGraph pm::UserGraph::to_matching_graph(pm::weight_int num_distinct_weights) { pm::MatchingGraph matching_graph(nodes.size(), _num_observables); - double normalising_constant = iter_discretized_edges( + + double normalising_constant = to_matching_or_search_graph_helper( num_distinct_weights, [&](size_t u, size_t v, pm::signed_weight_int weight, const std::vector& observables) { matching_graph.add_edge(u, v, weight, observables); }, [&](size_t u, pm::signed_weight_int weight, const std::vector& observables) { - // Only add the boundary edge if it already isn't present. Ideally parallel edges should already have been - // merged, however we are implicitly merging all boundary nodes in this step, which could give rise to new - // parallel edges. - if (matching_graph.nodes[u].neighbors.empty() || matching_graph.nodes[u].neighbors[0]) - matching_graph.add_boundary_edge(u, weight, observables); - }); + matching_graph.add_boundary_edge(u, weight, observables); + } + ); + matching_graph.normalising_constant = normalising_constant; if (boundary_nodes.size() > 0) { matching_graph.is_user_graph_boundary_node.clear(); @@ -270,18 +269,16 @@ pm::MatchingGraph pm::UserGraph::to_matching_graph(pm::weight_int num_distinct_w pm::SearchGraph pm::UserGraph::to_search_graph(pm::weight_int num_distinct_weights) { /// Identical to to_matching_graph but for constructing a pm::SearchGraph pm::SearchGraph search_graph(nodes.size()); - iter_discretized_edges( + + to_matching_or_search_graph_helper( num_distinct_weights, [&](size_t u, size_t v, pm::signed_weight_int weight, const std::vector& observables) { search_graph.add_edge(u, v, weight, observables); }, [&](size_t u, pm::signed_weight_int weight, const std::vector& observables) { - // Only add the boundary edge if it already isn't present. Ideally parallel edges should already have been - // merged, however we are implicitly merging all boundary nodes in this step, which could give rise to new - // parallel edges. - if (search_graph.nodes[u].neighbors.empty() || search_graph.nodes[u].neighbors[0]) - search_graph.add_boundary_edge(u, weight, observables); - }); + search_graph.add_boundary_edge(u, weight, observables); + } + ); return search_graph; } diff --git a/src/pymatching/sparse_blossom/driver/user_graph.h b/src/pymatching/sparse_blossom/driver/user_graph.h index 78ac0177..fef68276 100644 --- a/src/pymatching/sparse_blossom/driver/user_graph.h +++ b/src/pymatching/sparse_blossom/driver/user_graph.h @@ -99,6 +99,11 @@ class UserGraph { pm::weight_int num_distinct_weights, const EdgeCallable& edge_func, const BoundaryEdgeCallable& boundary_edge_func); + template + double to_matching_or_search_graph_helper( + pm::weight_int num_distinct_weights, + const EdgeCallable& edge_func, + const BoundaryEdgeCallable& boundary_edge_func); pm::MatchingGraph to_matching_graph(pm::weight_int num_distinct_weights); pm::SearchGraph to_search_graph(pm::weight_int num_distinct_weights); pm::Mwpm to_mwpm(pm::weight_int num_distinct_weights, bool ensure_search_graph_included); @@ -120,7 +125,6 @@ inline double UserGraph::iter_discretized_edges( pm::weight_int num_distinct_weights, const EdgeCallable& edge_func, const BoundaryEdgeCallable& boundary_edge_func) { - pm::MatchingGraph matching_graph(nodes.size(), _num_observables); double normalising_constant = get_edge_weight_normalising_constant(num_distinct_weights); for (auto& e : edges) { @@ -141,6 +145,38 @@ inline double UserGraph::iter_discretized_edges( return normalising_constant * 2; } +template +inline double UserGraph::to_matching_or_search_graph_helper( + pm::weight_int num_distinct_weights, + const EdgeCallable& edge_func, + const BoundaryEdgeCallable& boundary_edge_func) { + + // Use vectors to store boundary edges initially before adding them to the graph, so + // that parallel boundary edges with negative edge weights can be handled correctly + std::vector has_boundary_edge(nodes.size(), false); + std::vector boundary_edge_weights(nodes.size()); + std::vector> boundary_edge_observables(nodes.size()); + + double normalising_constant = iter_discretized_edges( + num_distinct_weights, + edge_func, + [&](size_t u, pm::signed_weight_int weight, const std::vector& observables) { + // For parallel boundary edges, keep the boundary edge with the smaller weight + if (!has_boundary_edge[u] || boundary_edge_weights[u] > weight){ + boundary_edge_weights[u] = weight; + boundary_edge_observables[u] = observables; + has_boundary_edge[u] = true; + } + }); + + // Now add boundary edges to the graph + for (size_t i = 0; i < has_boundary_edge.size(); i++) { + if (has_boundary_edge[i]) + boundary_edge_func(i, boundary_edge_weights[i], boundary_edge_observables[i]); + } + return normalising_constant; +} + UserGraph detector_error_model_to_user_graph(const stim::DetectorErrorModel& detector_error_model); } // namespace pm diff --git a/tests/matching/decode_test.py b/tests/matching/decode_test.py index 9aaee166..4f713bbd 100644 --- a/tests/matching/decode_test.py +++ b/tests/matching/decode_test.py @@ -276,3 +276,24 @@ def test_decode_to_edges(): m.add_edge(i, i + 1) edges = m.decode_to_edges_array([0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0]) assert np.array_equal(edges, np.array([[9, 8], [5, 6], [4, 3], [5, 4], [0, 1], [0, -1]], dtype=np.int64)) + + +def test_parallel_boundary_edges_decoding(): + m = Matching() + m.set_boundary_nodes({0, 2}) + m.add_edge(0, 1, fault_ids=0, weight=3.5) + m.add_edge(1, 2, fault_ids=1, weight=2.5) + assert np.array_equal(m.decode([0, 1]), np.array([0, 1], dtype=np.uint8)) + m.add_boundary_edge(1, fault_ids=100, weight=100) + # Test pm::SearchGraph + assert np.array_equal(np.nonzero(m.decode([0, 1]))[0], np.array([1], dtype=int)) + + m = Matching() + m.add_edge(0, 1, fault_ids=0, weight=-1) + m.add_edge(0, 2, fault_ids=1, weight=3) + m.add_boundary_edge(0, fault_ids=2, weight=-0.5) + m.add_edge(0, 3, fault_ids=3, weight=-3) + m.add_edge(0, 4, fault_ids=4, weight=-2) + assert np.array_equal(m.decode([1, 0, 0, 0, 0]), np.array([0, 0, 1, 0, 0], dtype=np.uint8)) + m.set_boundary_nodes({1, 2, 3, 4}) + assert np.array_equal(m.decode([1, 0, 0, 0, 0]), np.array([0, 0, 0, 1, 0], dtype=np.uint8))