Feature/partial First Pydantic Models for parameter validation

elephant/test/test_spike_train_correlation.py

@@ -913,7 +913,7 @@ def test_timescale_errors(self):
 
         # Tau max with no units
         tau_max = 1
-        self.assertRaises(ValueError,
+        self.assertRaises((ValueError, TypeError),
                           sc.spike_train_timescale, spikes_bin, tau_max)
 
         # Tau max that is not a multiple of the binsize

elephant/test/test_statistics.py

@@ -383,7 +383,7 @@ def test_lv_with_list(self):
     def test_lv_raise_error(self):
         seq = self.test_seq
         self.assertRaises(ValueError, statistics.lv, [])
-        self.assertRaises(ValueError, statistics.lv, 1)
+        self.assertRaises((ValueError, TypeError), statistics.lv, 1)
         self.assertRaises(ValueError, statistics.lv, np.array([seq, seq]))
 
     def test_2short_spike_train(self):
@@ -430,7 +430,7 @@ def test_lvr_with_list(self):
     def test_lvr_raise_error(self):
         seq = self.test_seq
         self.assertRaises(ValueError, statistics.lvr, [])
-        self.assertRaises(ValueError, statistics.lvr, 1)
+        self.assertRaises((ValueError, TypeError), statistics.lvr, 1)
         self.assertRaises(ValueError, statistics.lvr, np.array([seq, seq]))
         self.assertRaises(ValueError, statistics.lvr, seq, -1 * pq.ms)
 
@@ -478,7 +478,7 @@ def test_cv2_with_list(self):
     def test_cv2_raise_error(self):
         seq = self.test_seq
         self.assertRaises(ValueError, statistics.cv2, [])
-        self.assertRaises(ValueError, statistics.cv2, 1)
+        self.assertRaises((ValueError, TypeError), statistics.cv2, 1)
         self.assertRaises(ValueError, statistics.cv2, np.array([seq, seq]))