Test mixing array and scalar operations

tests/test_frame.py

@@ -138,8 +138,34 @@ def test_transform_with_other_labels(self):
                 data[i, j] = (i+1)*(j+1)
 
         transform_map = {
-            0: lambda x, f, i: x + f.get("owl-ratio", i), # Increase owl capacity
-            8: lambda x, f, i: np.mean(f.get("owl-ratio", None)) - x  # Normalise the splines
+            0: lambda x, f, i: x + f.get(TEST_PARAMETERS[0], i), # Increase owl capacity
+            8: lambda x, f, i: np.mean(f.get(TEST_PARAMETERS[8], None)) - x  # Normalise the splines
+        }
+        test_transformations = {}
+        for label_index in transform_map:
+            test_transformations[TEST_PARAMETERS[label_index]] = transform_map[label_index]
+
+        transformed_frame = frame.transform(test_transformations)
+        for transform in test_transformations:
+            for i, row in enumerate(frame):
+                for j, col in enumerate(frame[i]):
+                    if j in transform_map:
+                        self.assertEquals(transform_map[j](frame[i, j], frame, i),
+                                          transformed_frame[i, j])
+                    else:
+                        # Check nothing was transformed if it shouldn't have been
+                        self.assertEquals(frame[i, j], transformed_frame[i, j])
+
+    def test_transform_mix_array_and_scalar_functionality(self):
+        # Initialise data frame with trivial data
+        data = np.zeros([ARBITRARY_ROWS, len(TEST_PARAMETERS)])
+        frame = DataFrame(data, TEST_PARAMETERS)
+        for i in range(0, ARBITRARY_ROWS):
+            for j in range(0, len(TEST_PARAMETERS)):
+                data[i, j] = (i+1)*(j+1)
+
+        transform_map = {
+            0: lambda x, f, i: f.get(TEST_PARAMETERS[0], i) + math.factorial(math.ceil(x/2)), # Factorialising owl capacity
         }
         test_transformations = {}
         for label_index in transform_map: