Allow transform graph to get self-edge sequence

src/transformnd/graph.py

@@ -10,6 +10,8 @@
 
 import networkx as nx
 
+from transformnd.transforms.simple import Identity
+
 from .transforms.bijection import Bijection
 from .base import Transform, TransformSequence
 from .util import SpaceRef, ArrayT, same_or_none
@@ -216,13 +218,17 @@ def get_sequence(
         """
         path = nx.shortest_path(self.graph, source_space, target_space, weight)  # type:ignore
         transforms = []
-        wfn = normalise_edge_weight_fn(weight)
+        if len(path) == 1:
+            # source == target
+            transforms.append(Identity[ArrayT](self.space_ndims[source_space]))
+        else:
+            wfn = normalise_edge_weight_fn(weight)
 
-        for src, tgt in pairwise(path):
-            edges = self.graph[src][tgt]
-            transforms.append(
-                min(edges.values(), key=lambda d: wfn(src, tgt, d))[TRANSFORM_KEY]
-            )
+            for src, tgt in pairwise(path):
+                edges = self.graph[src][tgt]
+                transforms.append(
+                    min(edges.values(), key=lambda d: wfn(src, tgt, d))[TRANSFORM_KEY]
+                )
 
         seq = TransformSequence(
             transforms,

tests/test_graph.py

@@ -19,6 +19,14 @@ def test_add_transforms():
     t.add_transform(Translate([10, 20], spaces=Spaces("b", "c")))
 
 
+@pytest.mark.parametrize(("full",), [(True,), (False,)])
+def test_noop_path(coords5x3, full):
+    t: TransformGraph = TransformGraph()
+    t.add_transform(Scale([2, 2], spaces=Spaces("a", "b")))
+    s = t.get_sequence("a", "a", full=full)
+    assert s.apply(coords5x3) == pytest.approx(coords5x3)
+
+
 def test_path():
     t1 = Scale([2, 3], spaces=Spaces("a", "b"))
     t2 = Translate([10, 20], spaces=Spaces("b", "c"))