TST: Add tests asserting correct calculation of mean rates

hnn_core/network.py

@@ -484,6 +484,13 @@ def mean_rates(self, tstart, tstop, gid_dict, mean_type='all'):
             raise ValueError("Invalid mean_type. Valid arguments include "
                              "'all', 'trial', or 'cell'.")
 
+        # Validate tstart, tstop
+        if not isinstance(tstart, (int, float)) or not isinstance(
+                tstop, (int, float)):
+            raise ValueError('tstart and tstop must be of type int or float')
+        elif tstop <= tstart:
+            raise ValueError('tstop must be greater than tstart')
+
         for cell_type in cell_types:
             cell_type_gids = np.array(gid_dict[cell_type])
             gid_spike_rate = np.zeros((len(self._times), len(cell_type_gids)))

hnn_core/tests/test_network.py

@@ -62,26 +62,14 @@ def test_spikes():
     spiketimes = [[2.3456, 7.89], [4.2812, 93.2]]
     spikegids = [[1, 3], [5, 7]]
     spiketypes = [['L2_pyramidal', 'L2_basket'], ['L5_pyramidal', 'L5_basket']]
+    tstart, tstop = 0.1, 98.4
+    gid_dict = {'L2_pyramidal': range(1, 2), 'L2_basket': range(3, 4),
+                'L5_pyramidal': range(5, 6), 'L5_basket': range(7, 8)}
     spikes = Spikes(times=spiketimes, gids=spikegids, types=spiketypes)
     spikes.plot_hist(show=False)
     spikes.write('/tmp/spk_%d.txt')
     assert spikes == read_spikes('/tmp/spk_*.txt')
     assert ("Spikes | 2 simulation trials" in repr(spikes))
-    # assert spikes.mean_rates() == {
-    #     'L5_pyramidal': 5.08646998982706,
-    #     'L5_basket': 5.08646998982706,
-    #     'L2_pyramidal': 5.08646998982706,
-    #     'L2_basket': 5.08646998982706}
-    # assert spikes.mean_rates(mean_type='trial') == {
-    #     'L5_pyramidal': [0.0, 10.17293997965412],
-    #     'L5_basket': [0.0, 10.17293997965412],
-    #     'L2_pyramidal': [10.17293997965412, 0.0],
-    #     'L2_basket': [10.17293997965412, 0.0]}
-    # assert spikes.mean_rates(mean_type='cell') == {
-    #     'L5_pyramidal': [[0.0], [10.17293997965412]],
-    #     'L5_basket': [[0.0], [10.17293997965412]],
-    #     'L2_pyramidal': [[10.17293997965412], [0.0]],
-    #     'L2_basket': [[10.17293997965412], [0.0]]}
 
     with pytest.raises(TypeError, match="times should be a list of lists"):
         spikes = Spikes(times=([2.3456, 7.89], [4.2812, 93.2]), gids=spikegids,
@@ -95,15 +83,6 @@ def test_spikes():
         spikes = Spikes(times=[[2.3456, 7.89]], gids=spikegids,
                         types=spiketypes)
 
-    with pytest.raises(ValueError, match="tstart and tstop must be of type "
-                       "int or float"):
-        spikes = Spikes()
-        spikes.mean_rates(tstart=0.1, tstop='ABC', gid_dict={})
-
-    with pytest.raises(ValueError, match="tstop must be greater than tstart"):
-        spikes = Spikes()
-        spikes.mean_rates(tstart=0.1, tstop=-1.0, gid_dict={})
-
     spikes = Spikes(times=spiketimes, gids=spikegids, types=spiketypes)
 
     with pytest.raises(TypeError, match="spike_types should be str, "
@@ -122,9 +101,35 @@ def test_spikes():
     with pytest.raises(ValueError, match="No input types found for ABC"):
         spikes.plot_hist(spike_types='ABC', show=False)
 
+    with pytest.raises(ValueError, match="tstart and tstop must be of type "
+                       "int or float"):
+        spikes.mean_rates(tstart=0.1, tstop='ABC', gid_dict=gid_dict)
+
+    with pytest.raises(ValueError, match="tstop must be greater than tstart"):
+        spikes.mean_rates(tstart=0.1, tstop=-1.0, gid_dict=gid_dict)
+
     with pytest.raises(ValueError, match="Invalid mean_type. Valid "
                        "arguments include 'all', 'trial', or 'cell'."):
-        spikes.mean_rates(tstart=0.1, tstop=98.4, gid_dict={}, mean_type='ABC')
+        spikes.mean_rates(tstart=tstart, tstop=tstop, gid_dict=gid_dict,
+                          mean_type='ABC')
+
+    test_rate = (1 / (tstop - tstart)) * 1000
+
+    assert spikes.mean_rates(tstart, tstop, gid_dict) == {
+        'L5_pyramidal': test_rate / 2,
+        'L5_basket': test_rate / 2,
+        'L2_pyramidal': test_rate / 2,
+        'L2_basket': test_rate / 2}
+    assert spikes.mean_rates(tstart, tstop, gid_dict, mean_type='trial') == {
+        'L5_pyramidal': [0.0, test_rate],
+        'L5_basket': [0.0, test_rate],
+        'L2_pyramidal': [test_rate, 0.0],
+        'L2_basket': [test_rate, 0.0]}
+    assert spikes.mean_rates(tstart, tstop, gid_dict, mean_type='cell') == {
+        'L5_pyramidal': [[0.0], [test_rate]],
+        'L5_basket': [[0.0], [test_rate]],
+        'L2_pyramidal': [[test_rate], [0.0]],
+        'L2_basket': [[test_rate], [0.0]]}
 
     # Write spike file with no 'types' column
     # Check for gid_dict errors