ENH: additional sanity checks for the event_number column

pixel_clusterizer/clusterizer.py

@@ -361,6 +361,14 @@ def cluster_hits(self, hits, noisy_pixels=None, disabled_pixels=None):
             if cluster_hits_field_name in self._cluster_hits.dtype.fields:
                 self._cluster_hits[cluster_hits_field_name][:n_hits] = hits[field_name]
 
+        # Check if event number is increasing. Otherwise give a warning message.
+        if self._last_event_number is not None and hits.shape[0] != 0 and self._cluster_hits["event_number"][0] <= self._last_event_number:
+            logging.warning('The event number does not increase with successive chunks.')
+        if hits.shape[0] > 1 and not np.all((self._cluster_hits["event_number"][1:n_hits] - self._cluster_hits["event_number"][:n_hits - 1]) >= 0):
+            raise RuntimeError('Some values in column "%s" decrease.' % (self._hit_fields_mapping["event_number"],))
+        if self._cluster_hits.shape[0] != 0:
+            self._last_event_number = self._cluster_hits[-1]["event_number"]
+
         noisy_pixels_array = np.array([]) if noisy_pixels is None else np.array(noisy_pixels)
         if noisy_pixels_array.shape[0] != 0:
             noisy_pixels_max_range = np.array([max(0, np.max(noisy_pixels_array[:, 0])), max(0, np.max(noisy_pixels_array[:, 1]))])
@@ -386,12 +394,6 @@ def cluster_hits(self, hits, noisy_pixels=None, disabled_pixels=None):
 #         disabled_pixels = np.recarray(disabled_pixels_array.shape[0], dtype=mask_dtype)
 #         disabled_pixels[:] = [(item[0], item[1]) for item in disabled_pixels_array]
 
-        # Check if event number is increasing. Otherwise give a warning message.
-        if self._last_event_number is not None and self._cluster_hits.shape[0] != 0 and self._cluster_hits[0]["event_number"] == self._last_event_number:
-            logging.warning('Event number not increasing.')
-        if self._cluster_hits.shape[0] != 0:
-            self._last_event_number = self._cluster_hits[-1]["event_number"]
-
         n_clusters = self.cluster_functions._cluster_hits(  # Set n_clusters to new size
             hits=self._cluster_hits[:n_hits],
             clusters=self._clusters[:n_hits],
@@ -474,4 +476,4 @@ def _check_struct_compatibility(self, hits):
                 raise TypeError('The dtype for hit data field "%s" does not match. Got/expected: %s/%s.' % (key, hits.dtype[key], self._cluster_hits.dtype[mapped_key]))
         additional_hit_fields = set(hits.dtype.names) - set([key for key, val in self._cluster_hits_descr])
         if additional_hit_fields:
-            logging.warning('Found additional hit fields: %s' % ", ".join(additional_hit_fields))
+            logging.warning('Found additional column: %s' % ", ".join(additional_hit_fields))

pixel_clusterizer/testing/test_clusterizer.py

@@ -63,6 +63,12 @@ def test_exceptions(self):
             'frame': 'frame'}
         clusterizer = HitClusterizer(hit_fields=hit_mapping, hit_dtype=hit_dtype_new, pure_python=self.pure_python)
         _, _ = clusterizer.cluster_hits(np.array([], dtype=hit_dtype_new))
+        # TEST 4 Set custom and correct hit mapping, decrease event_number
+        hits = np.ones(shape=(2, ), dtype=hit_dtype_new)
+        hits[0]['column'], hits[0]['row'], hits[0]['charge'], hits[0]['not_defined'] = 17, 36, 30, 19
+        hits[1]['column'], hits[1]['row'], hits[1]['charge'], hits[1]['not_defined'] = 18, 36, 6, 18
+        with self.assertRaises(RuntimeError):
+            _, _ = clusterizer.cluster_hits(hits)
 
     def test_cluster_algorithm(self):  # Basic functionality checks
         # Initialize Clusterizer with default arguments