Restore sparse transition state-shape validation

src/pyrecest/filters/discrete_state/__init__.py

@@ -341,16 +341,25 @@ def sparse_gaussian_transition_matrix(
     valid_state_mask=None,
 ):
     states = _validated_state_vectors(state_vectors)
+    if states.ndim == 1:
+        states = states[:, None]
+    elif states.ndim != 2:
+        raise ValueError(
+            "state_vectors must have shape (n_states,) or (n_states, state_dim)"
+        )
+    n_states = states.shape[0]
+    if n_states == 0:
+        raise ValueError("state_vectors must contain at least one state")
+    if states.shape[1] == 0:
+        raise ValueError("state_vectors must contain at least one coordinate per state")
+
     sigma = _validated_positive_scalar(sigma, "sigma")
     max_step_sigma = _validated_positive_scalar(
         max_step_sigma,
         "max_step_sigma",
         allow_infinite=True,
     )
 
-    if states.ndim == 1:
-        states = states[:, None]
-    n_states = states.shape[0]
     valid_mask = _module_globals["_coerce_valid_state_mask"](
         valid_state_mask,
         n_states,

tests/filters/test_sparse_gaussian_transition_validation.py

@@ -0,0 +1,23 @@
+import numpy as np
+import pytest
+
+from pyrecest.filters.discrete_state import sparse_gaussian_transition_matrix
+
+
+@pytest.mark.parametrize(
+    ("state_vectors", "message"),
+    [
+        (np.array(1.0), "state_vectors must have shape"),
+        (np.empty((2, 1, 1)), "state_vectors must have shape"),
+        (np.empty((0,)), "state_vectors must contain at least one state"),
+        (
+            np.empty((2, 0)),
+            "state_vectors must contain at least one coordinate per state",
+        ),
+    ],
+)
+def test_sparse_gaussian_transition_matrix_rejects_invalid_state_shapes(
+    state_vectors, message
+):
+    with pytest.raises(ValueError, match=message):
+        sparse_gaussian_transition_matrix(state_vectors, sigma=1.0)