Test patient_normalise checks type and shape of data

Author: alexlyttle

tests/test_models.py

@@ -73,9 +73,19 @@ def test_daily_min_string():
         ),
         (
             [[-1, 2, 3], [4, 5, 6], [7, 8, 9]],
-            [[0, 0.67, 1], [0.67, 0.83, 1], [0.78, 0.89, 1]],
+            None,
             ValueError,
         ),
+        (
+            'hello',
+            None,
+            TypeError,
+        ),
+        (
+            3,
+            None,
+            TypeError,
+        ),
         (
             [[1, 2, 3], [4, 5, 6], [7, 8, 9]],
             [[0.33, 0.67, 1], [0.67, 0.83, 1], [0.78, 0.89, 1]],
@@ -84,11 +94,13 @@ def test_daily_min_string():
     ])
 def test_patient_normalise(test, expected, expect_raises):
     """Test normalisation works for arrays of one and positive integers."""
-        
+    if isinstance(test, list):
+        test = np.array(test)
+
     if expect_raises is not None:
         with pytest.raises(expect_raises):
-            result = patient_normalise(np.array(test))
+            result = patient_normalise(test)
             npt.assert_allclose(result, np.array(expected), rtol=1e-2, atol=1e-2)
     else:
-        result = patient_normalise(np.array(test))
+        result = patient_normalise(test)
         npt.assert_allclose(result, np.array(expected), rtol=1e-2, atol=1e-2)