OpenEphysBinaryRawIO: Fixing ttl multichan

neo/rawio/openephysbinaryrawio.py

@@ -217,7 +217,6 @@ def _parse_header(self):
                         if name + "_npy" in info:
                             data = np.load(info[name + "_npy"], mmap_mode="r")
                             info[name] = data
-
                     # check that events have timestamps
                     assert "timestamps" in info, "Event stream does not have timestamps!"
                     # Updates for OpenEphys v0.6:
@@ -253,30 +252,50 @@ def _parse_header(self):
                     # 'states' was introduced in OpenEphys v0.6. For previous versions, events used 'channel_states'
                     if "states" in info or "channel_states" in info:
                         states = info["channel_states"] if "channel_states" in info else info["states"]
+
                         if states.size > 0:
                             timestamps = info["timestamps"]
                             labels = info["labels"]
-                            rising = np.where(states > 0)[0]
-                            falling = np.where(states < 0)[0]
 
-                            # infer durations
+                            # Identify unique channels based on state values
+                            channels = np.unique(np.abs(states))
+
+                            rising_indices = []
+                            falling_indices = []
+
+                            for channel in channels:
+                                # Find rising and falling edges for each channel
+                                rising = np.where(states == channel)[0]
+                                falling = np.where(states == -channel)[0]
+
+                                # Ensure each rising has a corresponding falling
+                                if rising.size > 0 and falling.size > 0:
+                                    if rising[0] > falling[0]:
+                                        falling = falling[1:]
+                                    if rising.size > falling.size:
+                                        rising = rising[:-1]
+
+                                    rising_indices.extend(rising)
+                                    falling_indices.extend(falling)
+
+                            rising_indices = np.array(rising_indices)
+                            falling_indices = np.array(falling_indices)
+
+                            # Sort the indices to maintain chronological order
+                            sorted_order = np.argsort(rising_indices)
+                            rising_indices = rising_indices[sorted_order]
+                            falling_indices = falling_indices[sorted_order]
+
                             durations = None
-                            if len(states) > 0:
-                                # make sure first event is rising and last is falling
-                                if states[0] < 0:
-                                    falling = falling[1:]
-                                if states[-1] > 0:
-                                    rising = rising[:-1]
-
-                                if len(rising) == len(falling):
-                                    durations = timestamps[falling] - timestamps[rising]
-                                    if not self._use_direct_evt_timestamps:
-                                        timestamps = timestamps / info["sample_rate"]
-                                        durations = durations / info["sample_rate"]
-
-                            info["rising"] = rising
-                            info["timestamps"] = timestamps[rising]
-                            info["labels"] = labels[rising]
+                            if len(rising_indices) == len(falling_indices):
+                                durations = timestamps[falling_indices] - timestamps[rising_indices]
+                                if not self._use_direct_evt_timestamps:
+                                    timestamps = timestamps / info["sample_rate"]
+                                    durations = durations / info["sample_rate"]
+
+                            info["rising"] = rising_indices
+                            info["timestamps"] = timestamps[rising_indices]
+                            info["labels"] = labels[rising_indices]
                             info["durations"] = durations
 
         # no spike read yet

neo/test/rawiotest/test_openephysbinaryrawio.py

@@ -3,6 +3,8 @@
 from neo.rawio.openephysbinaryrawio import OpenEphysBinaryRawIO
 from neo.test.rawiotest.common_rawio_test import BaseTestRawIO
 
+import numpy as np
+
 
 class TestOpenEphysBinaryRawIO(BaseTestRawIO, unittest.TestCase):
     rawioclass = OpenEphysBinaryRawIO
@@ -57,6 +59,25 @@ def test_missing_folders(self):
             )
             rawio.parse_header()
 
+    def test_multiple_ttl_events_parsing(self):
+        rawio = OpenEphysBinaryRawIO(
+            self.get_local_path("openephysbinary/v0.6.x_neuropixels_with_sync"), load_sync_channel=False
+        )
+        rawio.parse_header()
+        rawio.header = rawio.header
+        # Testing co
+        # This is the TTL events from the NI Board channel
+        ttl_events = rawio._evt_streams[0][0][1]
+        assert "rising" in ttl_events.keys()
+        assert "labels" in ttl_events.keys()
+        assert "durations" in ttl_events.keys()
+        assert "timestamps" in ttl_events.keys()
+
+        # Check that durations of different event streams are correctly parsed:
+        assert np.allclose(ttl_events["durations"][ttl_events["labels"] == "1"], 0.5, atol=0.001)
+        assert np.allclose(ttl_events["durations"][ttl_events["labels"] == "6"], 0.025, atol=0.001)
+        assert np.allclose(ttl_events["durations"][ttl_events["labels"] == "7"], 0.016666, atol=0.001)
+
 
 if __name__ == "__main__":
     unittest.main()