PR #1: Add TDD tests for correct edge_map semantics

src/track_linearization/tests/test_edge_map.py

@@ -0,0 +1,38 @@
+import numpy as np
+import pytest
+
+import track_linearization.core as core
+from track_linearization import make_track_graph
+
+def _mk_line_graph():
+    pos = np.array([[0.0,0.0],[1.0,0.0],[2.0,0.0]], dtype=float)
+    edges = [(0,1),(1,2)]
+    g = make_track_graph(pos, edges)
+    # Explicit, non-index edge IDs to highlight id/index mismatch
+    g.edges[(0,1)]["edge_id"] = 10
+    g.edges[(1,2)]["edge_id"] = 20
+    # Ensure edge distances exist
+    g.edges[(0,1)]["distance"] = 1.0
+    g.edges[(1,2)]["distance"] = 1.0
+    return g
+
+def test_edge_map_label_passthrough_no_change():
+    g = _mk_line_graph()
+    pts = np.array([[0.2,0.0],[1.7,0.0]])
+    df_nomap = core.get_linearized_position(pts, g, use_HMM=False)
+    df_map   = core.get_linearized_position(pts, g, edge_map={10:10, 20:20}, use_HMM=False)
+    # Same geometry -> identical linear positions
+    assert np.allclose(df_nomap["linear_position"], df_map["linear_position"])
+
+def test_edge_map_merge_two_edges_to_one_label():
+    g = _mk_line_graph()
+    pts = np.array([[0.2,0.0],[1.7,0.0]])
+    df = core.get_linearized_position(pts, g, edge_map={10:99, 20:99}, use_HMM=False)
+    assert set(df["track_segment_id"].unique()) == {99}
+
+def test_edge_map_invalid_target_raises():
+    g = _mk_line_graph()
+    pts = np.array([[0.2,0.0]])
+    with pytest.raises(ValueError):
+        # 42 is not a real edge_id in the graph; must raise
+        core.get_linearized_position(pts, g, edge_map={10:42}, use_HMM=False)