Corrected improper use of .base on quantities objects (NeuralEnsemble…

…#211)

* Corrected impropoer use of .base on quantities objects

* Fixed situation where magnitude would have been called on a numpy array

* Added test to check for too high threshold, and fixed unit tests alltogether

elephant/spike_train_generation.py

@@ -152,19 +152,19 @@ def threshold_detection(signal, threshold=0.0 * mV, sign='above'):
         cutout = np.where(signal < threshold)[0]
 
     if len(cutout) <= 0:
-        events = np.zeros(0)
+        events_base = np.zeros(0)
     else:
         take = np.where(np.diff(cutout) > 1)[0] + 1
         take = np.append(0, take)
 
         time = signal.times
         events = time[cutout][take]
 
-    events_base = events.base
-    if events_base is None:
-        # This occurs in some Python 3 builds due to some
-        # bug in quantities.
-        events_base = np.array([event.base for event in events])  # Workaround
+        events_base = events.magnitude
+        if events_base is None:
+            # This occurs in some Python 3 builds due to some
+            # bug in quantities.
+            events_base = np.array([event.magnitude for event in events])  # Workaround
 
     result_st = SpikeTrain(events_base, units=signal.times.units,
                            t_start=signal.t_start, t_stop=signal.t_stop)
@@ -236,12 +236,12 @@ def peak_detection(signal, threshold=0.0 * mV, sign='above', format=None):
         max_idc = maxima_idc_split + true_borders[0::2]
 
         events = signal.times[max_idc]
-        events_base = events.base
+        events_base = events.magnitude
 
-    if events_base is None:
-        # This occurs in some Python 3 builds due to some
-        # bug in quantities.
-        events_base = np.array([event.base for event in events])  # Workaround
+        if events_base is None:
+            # This occurs in some Python 3 builds due to some
+            # bug in quantities.
+            events_base = np.array([event.magnitude for event in events])  # Workaround
     if format is None:
         result_st = SpikeTrain(events_base, units=signal.times.units,
                                t_start=signal.t_start, t_stop=signal.t_stop)

elephant/test/test_spike_train_generation.py

@@ -31,22 +31,23 @@ def pdiff(a, b):
 class AnalogSignalThresholdDetectionTestCase(unittest.TestCase):
 
     def setUp(self):
-        pass
-
-    def test_threshold_detection(self):
-        # Test whether spikes are extracted at the correct times from
-        # an analog signal.
-
         # Load membrane potential simulated using Brian2
         # according to make_spike_extraction_test_data.py.
         curr_dir = os.path.dirname(os.path.realpath(__file__))
-        raw_data_file_loc = os.path.join(curr_dir,'spike_extraction_test_data.txt')
+        raw_data_file_loc = os.path.join(curr_dir, 'spike_extraction_test_data.txt')
         raw_data = []
         with open(raw_data_file_loc, 'r') as f:
             for x in (f.readlines()):
                 raw_data.append(float(x))
-        vm = neo.AnalogSignal(raw_data, units=V, sampling_period=0.1*ms)
-        spike_train = stgen.threshold_detection(vm)
+        self.vm = neo.AnalogSignal(raw_data, units=V, sampling_period=0.1*ms)
+        self.true_time_stamps = [0.0123,  0.0354,  0.0712,  0.1191,  0.1694,
+                                 0.2200,  0.2711] * second
+
+    def test_threshold_detection(self):
+        # Test whether spikes are extracted at the correct times from
+        # an analog signal.
+
+        spike_train = stgen.threshold_detection(self.vm)
         try:
             len(spike_train)
         except TypeError: # Handles an error in Neo related to some zero length
@@ -58,17 +59,18 @@ def test_threshold_detection(self):
                                                  t_stop=spike_train.t_stop,
                                                  units=spike_train.units)
 
-        # Correct values determined previously.
-        true_spike_train = [0.0123, 0.0354, 0.0712, 0.1191,
-                            0.1694, 0.22, 0.2711]
-
         # Does threshold_detection gives the correct number of spikes?
-        self.assertEqual(len(spike_train),len(true_spike_train))
+        self.assertEqual(len(spike_train),len(self.true_time_stamps))
         # Does threshold_detection gives the correct times for the spikes?
         try:
-            assert_array_almost_equal(spike_train,spike_train)
+            assert_array_almost_equal(spike_train, self.true_time_stamps)
         except AttributeError: # If numpy version too old to have allclose
-            self.assertTrue(np.array_equal(spike_train,spike_train))
+            self.assertTrue(np.array_equal(spike_train, self.true_time_stamps))
+
+    def test_peak_detection_threshold(self):
+        # Test for empty SpikeTrain when threshold is too high
+        result = stgen.threshold_detection(self.vm, threshold=30 * mV)
+        self.assertEqual(len(result), 0)
 
 
 class AnalogSignalPeakDetectionTestCase(unittest.TestCase):
@@ -100,6 +102,7 @@ def test_peak_detection_threshold(self):
         result = stgen.peak_detection(self.vm, threshold=30 * mV)
         self.assertEqual(len(result), 0)
 
+
 class AnalogSignalSpikeExtractionTestCase(unittest.TestCase):
 
     def setUp(self):