Remove method Pattern.graph

CHANGELOG.md

@@ -107,6 +107,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   - `.to_<object>_or_none` for transformations that can return `object` or `None`. Equivalently, we use `.from_<object>_or_none` for constructors.
   - accessor methods use nouns instead of verb + noun. Example: `Pattern.max_degree` instead of `Pattern.compute_max_degree`.
 
+- #571: Removed method `Pattern.graph`
+
+
 ## [0.3.5] - 2026-03-26
 
 ### Added

COMPATIBILITY.md

@@ -4,6 +4,8 @@ Graphix does not guarantee backwards compatibility between 0.x version releases.
 
 ## Unreleased
 
+- #571: Method `Pattern.graph` (formely `Pattern.extract_graph`) is removed. Use instead `Pattern.to_opengraph().graph` which standardizes the pattern and fails gracefully if there are non-commutative CLiffords.
+
 - #557: Namespace homogenisation.
 
   The following methods and classes have been renamed to provide a homogeneous, consistent and pythonic naming convention:

docs/source/modifier.rst

@@ -50,8 +50,6 @@ Pattern Manipulation
 
     .. automethod:: is_standard
 
-    .. automethod:: graph
-
     .. automethod:: nodes
 
     .. automethod:: to_causalflow

docs/source/tutorial.rst

@@ -157,7 +157,7 @@ This reveals the graph structure of the resource state which we can inspect:
 .. code-block:: python
 
     import networkx as nx
-    graph = pattern.graph()
+    graph = pattern.to_opengraph().graph
     pos = {0: (0, 0), 1: (0, -0.5), 2: (1, 0), 3: (4, 0), 4: (1, -0.5), 5: (2, -0.5), 6: (3, -0.5), 7: (4, -0.5)}
     graph_params = {'node_size': 240, 'node_color': 'w', 'edgecolors': 'k', 'with_labels': True}
     nx.draw(graph, pos=pos, **graph_params)

examples/fusion_extraction.py

@@ -26,7 +26,7 @@
 
 # %%
 # Here we say we want a graph state with 9 nodes and 12 edges.
-# We can obtain resource graph for a measurement pattern by using :code:`pattern.graph()`.
+# We can obtain resource graph for a measurement pattern by using :code:`pattern.to_opengraph().graph`.
 gs = Graph()
 nodes = [0, 1, 2, 3, 4, 5, 6, 7, 8]
 edges = [(0, 1), (1, 2), (2, 3), (3, 0), (3, 4), (0, 5), (4, 5), (5, 6), (6, 7), (7, 0), (7, 8), (8, 1)]

examples/ghz_with_tn.py

@@ -35,7 +35,7 @@
 pattern = circuit.transpile().pattern
 pattern.standardize()
 
-graph = pattern.graph()
+graph = pattern.to_opengraph().graph
 print(f"Number of nodes: {len(graph.nodes)}")
 print(f"Number of edges: {len(graph.edges)}")
 pos = nx.spring_layout(graph)

examples/qft_with_tn.py

@@ -59,7 +59,7 @@ def qft(circuit: Circuit, n: int) -> None:
 pattern = circuit.transpile().pattern
 pattern.standardize()
 pattern.shift_signals()
-graph = pattern.graph()
+graph = pattern.to_opengraph().graph
 print(f"Number of nodes: {len(graph.nodes)}")
 print(f"Number of edges: {len(graph.edges)}")
 

examples/tn_simulation.py

@@ -78,7 +78,7 @@ def ansatz(
 # %%
 # Print some properties of the graph.
 
-graph = pattern.graph()
+graph = pattern.to_opengraph().graph
 print(f"Number of nodes: {len(graph.nodes)}")
 print(f"Number of edges: {len(graph.edges)}")
 

graphix/pattern.py

@@ -1192,35 +1192,14 @@ def max_degree(self) -> int:
         max_degree : int
             max degree of a pattern
         """
-        graph = self.graph()
+        graph = self.to_opengraph().graph
         degree = graph.degree()
         assert isinstance(degree, nx.classes.reportviews.DiDegreeView)
         degrees = dict(degree).values()
         if len(degrees) == 0:
             return 0
         return int(max(degrees))
 
-    def graph(self) -> nx.Graph[int]:
-        """Return the graph state from the command sequence, extracted from ``N`` and ``E`` commands.
-
-        Returns
-        -------
-        graph_state: nx.Graph[int]
-        """
-        graph: nx.Graph[int] = nx.Graph()
-        graph.add_nodes_from(self.input_nodes)
-        for cmd in self.__seq:
-            match cmd.kind:
-                case CommandKind.N:
-                    graph.add_node(cmd.node)
-                case CommandKind.E:
-                    u, v = cmd.nodes
-                    if graph.has_edge(u, v):
-                        graph.remove_edge(u, v)
-                    else:
-                        graph.add_edge(u, v)
-        return graph
-
     def nodes(self) -> set[int]:
         """Return the set of nodes of the pattern."""
         nodes = set(self.input_nodes)
@@ -1237,8 +1216,15 @@ def isolated_nodes(self) -> set[int]:
         isolated_nodes : set[int]
             set of the isolated nodes
         """
-        graph = self.graph()
-        return {node for node, d in graph.degree if d == 0}
+        nodes = set(self.input_nodes)
+        for cmd in self.__seq:
+            match cmd.kind:
+                case CommandKind.N:
+                    nodes.add(cmd.node)
+                case CommandKind.E:
+                    u, v = cmd.nodes
+                    nodes -= {u, v}
+        return nodes
 
     def to_opengraph(self) -> OpenGraph[Measurement]:
         r"""Extract the underlying resource-state open graph from the pattern.

graphix/sim/tensornet.py

@@ -648,7 +648,7 @@ def __init__(
         if graph_prep == "parallel":
             if not pattern.is_standard():
                 raise ValueError("parallel preparation strategy does not support not-standardized pattern")
-            graph = pattern.graph()
+            graph = pattern.to_opengraph().graph
             state = MBQCTensorNet(
                 graph_nodes=graph.nodes,
                 graph_edges=graph.edges,

tests/test_pattern.py

@@ -1256,7 +1256,7 @@ def test_graph(self) -> None:
             circuit.rx(v, ANGLE_PI / 9)
 
         pattern = circuit.transpile().pattern
-        graph = pattern.graph()
+        graph = pattern.to_opengraph().graph
 
         graph_ref: nx.Graph[int] = nx.Graph()
         graph_ref.add_nodes_from(range(27))

tests/test_space_minimization.py

@@ -77,7 +77,7 @@ def test_minimization_by_degree_edge_ordering() -> None:
         ]
     )
     # Verify Networkx node ordering behaves as expected
-    graph = p.graph()
+    graph = p.to_opengraph().graph
     assert set(graph.edges()) == {(0, 2), (1, 2)}
     assert set(graph.edges(2)) == {(2, 0), (2, 1)}