Add precondition to check type and shape of data

Author: alexlyttle

inflammation/models.py

@@ -46,8 +46,12 @@ def daily_min(data):
 
 def patient_normalise(data):
     """Normalise patient data from a 2D inflammation data array."""
+    if not isinstance(data, np.ndarray):
+        raise TypeError('data input should be ndarray')
+    if len(data.shape) != 2:
+        raise ValueError('inflammation array should be 2-dimensional')
     if np.any(data < 0):
-        raise ValueError('Inflammation values should not be negative')
+        raise ValueError('inflammation values should be non-negative')
     max = np.nanmax(data, axis=1)
     with np.errstate(invalid='ignore', divide='ignore'):
         normalised = data / max[:, np.newaxis]