Additional test for Dijkstra search

src/pymatching/bindings.cpp

@@ -48,6 +48,8 @@ PYBIND11_MODULE(_cpp_mwpm, m) {
      .def_readwrite("all_distances", &WeightedStabiliserGraph::all_distances)
      .def_readwrite("all_edges_have_error_probabilities", 
                     &WeightedStabiliserGraph::all_edges_have_error_probabilities)
+     .def_readwrite("_distances", &WeightedStabiliserGraph::_distances)
+     .def_readwrite("_predecessors", &WeightedStabiliserGraph::_predecessors)
      .def("add_edge", &WeightedStabiliserGraph::AddEdge, "node1"_a, "node2"_a, "qubit_ids"_a, 
           "weight"_a, "error_probability"_a=-1.0, "has_error_probability"_a=false)
      .def("add_noise", &WeightedStabiliserGraph::AddNoise)

tests/test_nearest_neighbours.py

@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import sys
+
 import networkx as nx
 import numpy as np
 import pytest
@@ -50,3 +52,13 @@ def test_neighbourhood_matching(defects,num_neighbours,correction):
     assert (np.array_equal(decode_match_neighbourhood(m.stabiliser_graph, 
             np.array(defects), num_neighbours, False).correction, np.array(correction)))
 
+
+def test_distances_and_predecessors_reset():
+    M = Matching([[1,1,0,0],[0,1,1,0],[0,0,1,1],[1,0,0,1]])
+    assert M.stabiliser_graph._distances == []
+    assert M.stabiliser_graph._predecessors == []
+    for z in ([1,0,0,1],[0,1,1,0],[0,0,1,1]):
+        M.decode(z)
+        infty = sys.float_info.max
+        assert [infty]*4 == M.stabiliser_graph._distances
+        assert list(range(4)) == M.stabiliser_graph._predecessors