add test file to git instead of annex

code/reachgraspio/test_reachgraspio.py

@@ -0,0 +1,137 @@
+import sys
+from os.path import join, realpath, dirname
+
+sys.path.insert(0, realpath(join(dirname(__file__), '..')))
+import numpy as np
+
+import unittest
+import reachgraspio.reachgraspio as rg
+
+rio = rg.ReachGraspIO("../../datasets_blackrock/i140703-001",
+                      odml_directory="../../datasets_blackrock",
+                      nsx_to_load='all')
+block1 = rio.read_block(lazy=True)
+
+rio = rg.ReachGraspIO("../../datasets_blackrock/l101210-001",
+                      odml_directory="../../datasets_blackrock",
+                      nsx_to_load='all')
+block2 = rio.read_block(lazy=True)
+
+class RGIOTestCase(unittest.TestCase):
+    def setUp(self):
+        self.blocks = [block1, block2]
+
+    def test_group_units_present(self):
+        for block in self.blocks:
+            unit_groups = [g for g in block.groups if 'Unit' in g.name]
+            self.assertGreater(len(unit_groups), 0)
+            self.assertGreaterEqual(len(unit_groups), len(block.segments[0].spiketrains))
+
+    def test_channel_infos_present(self):
+        for block in self.blocks:
+            for seg in block.segments:
+                for anasig in seg.analogsignals:
+                    if anasig.annotations['neural_signal']:
+                        self.assertIn('connector_aligned_ids', anasig.array_annotations)
+                        self.assertIn('coordinates_x', anasig.array_annotations)
+                        self.assertIn('coordinates_y', anasig.array_annotations)
+
+    def test_group_unit_annotations(self):
+        for block in self.blocks:
+            for group in block.groups:
+                if 'Unit' in group.name:
+                    self.assertIn('unit_id', group.annotations)
+                    self.assertIn('connector_aligned_id', group.annotations)
+                    self.assertIn('sua', group.annotations)
+                    self.assertIn('mua', group.annotations)
+                    self.assertIn('noise', group.annotations)
+
+                    # To be investigated
+                    # if group.annotations['unit_id'] > 0:
+                    #     print(group.annotations)
+                    #     self.assertIn('spike_duration', group.annotations)
+                    #     self.assertIn('spike_amplitude', group.annotations)
+                    #     self.assertIn('spike_count', group.annotations)
+
+    def test_group_unit_linking(self):
+        for block in self.blocks:
+            # run this test only if neuronal signals are present
+            if not [a for seg in block.segments for a in seg.analogsignals if
+                    a.annotations['neural_signal']]:
+                return
+            for group in block.groups:
+                if 'Unit' in group.name:
+                    asig_annotations = group.channelviews[0].obj.array_annotations
+                    idx = group.channelviews[0].index
+                    self.assertEqual(group.annotations['channel_id'],
+                                     asig_annotations['channel_ids'][idx])
+
+    def test_consecutive_trial_ids(self):
+        for block in self.blocks:
+            for seg in block.segments:
+                for ev in seg.events:
+                    if 'trial_id' in ev.array_annotations:
+                        # exclude invalid trial_ids:
+                        trial_ids = ev.array_annotations['trial_id']
+                        valid_ids = trial_ids[trial_ids != -1]
+                        self.assertTrue(all(np.diff(valid_ids) >= 0))
+
+    def test_rejection_annotations_present(self):
+        for block in self.blocks:
+            for seg in block.segments:
+                for anasig in seg.analogsignals:
+                    if anasig.annotations['neural_signal']:
+                        for key in ['file_origin', 'connector_ID', 'connector_pinID',
+                                    'nsx_hi_freq_order', 'nsx_lo_freq_order', 'nsx_hi_freq_type',
+                                    'nsx_lo_freq_type', 'description', 'nsx',
+                                    'electrode_reject_IFC', 'electrode_reject_LFC',
+                                    'electrode_reject_HFC']:
+                            self.assertIn(key, anasig.array_annotations)
+
+                for st in seg.spiketrains:
+                    for key in ['electrode_reject_IFC', 'electrode_reject_LFC',
+                                'electrode_reject_HFC','nev_dig_factor', 'nb_sorted_units',
+                                'nev_hi_freq_order', 'nev_hi_freq_type', 'nev_lo_freq_order',
+                                'nev_lo_freq_type']:
+                        self.assertIn(key, st.annotations)
+
+    def test_event_annotations(self):
+        for block in self.blocks:
+            for seg in block.segments:
+                for ev in seg.events:
+                    if ev.name in ['DigitalTrialEvents', 'AnalogTrialEvents', 'TrialEvents']:
+                        for key in ['trial_event_labels', 'trial_timestamp_id', 'trial_id',
+                                    'belongs_to_trialtype', 'performance_in_trial',
+                                    'performance_in_trial_str', 'trial_reject_HFC', 'trial_reject_LFC',
+                                    'trial_reject_IFC']:
+                            self.assertIn(key, ev.array_annotations)
+
+                ev_names = [ev.name for ev in seg.events]
+                for key in ['AnalogTrialEvents', 'DigitalTrialEvents', 'TrialEvents']:
+                    self.assertIn(key, ev_names)
+
+    def test_block_annotation(self):
+        for block in self.blocks:
+            self.assertIn('conditions', block.annotations)
+            self.assertGreater(len(block.annotations['conditions']), 0)
+
+    def test_connector_aligned_ids_coordinates(self):
+        for block in self.blocks:
+            for seg in block.segments:
+                for anasig in seg.analogsignals:
+                    if not anasig.annotations['neural_signal']:
+                        continue  # only check annotations of neural signals
+                    for coords in ['coordinates_x', 'coordinates_y']:
+                        if coords in anasig.array_annotations:
+                            self.assertEqual(len(np.unique(anasig.array_annotations[coords])), 10)
+                        self.assertIn('connector_aligned_ids', anasig.array_annotations)
+
+
+def suite():
+    suite = unittest.makeSuite(RGIOTestCase, 'test')
+    return suite
+
+if __name__ == "__main__":
+    runner = unittest.TextTestRunner(verbosity=2)
+    runner.run(suite())
+