Add events handling: trace/map + new view for aliggned/rasters + PSTHs (#218)

* Add events handling: trace/map + new view for aliggned/rasters + PSTHs

* EventView in panel

* centralize toolbars in traces

* Add events on Trace/TraceMap for panel

* wip: move event functions to event_tools

* fix multiple event lines in panel and qt

* Fix conflicts2

* Fix conflicts3

* feat: sample events from all segments and subsample based on seg duration

* feat: sample events from all segments and subsample based on seg duration

* fix: filter events based on start/stop and sort them

* cleanup test

* Fix duplicated event source

Author: alejoe91

spikeinterface_gui/basescatterview.py

@@ -211,7 +211,7 @@ def _qt_make_layout(self):
         tb = self.qt_widget.view_toolbar
         self.combo_seg = QT.QComboBox()
         tb.addWidget(self.combo_seg)
-        self.combo_seg.addItems([ f'Segment {segment_index}' for segment_index in range(self.controller.num_segments) ])
+        self.combo_seg.addItems([f'Segment {segment_index}' for segment_index in range(self.controller.num_segments)])
         self.combo_seg.currentIndexChanged.connect(self._qt_change_segment)
         add_stretch_to_qtoolbar(tb)
         self.lasso_but = QT.QPushButton("select", checkable = True)
@@ -313,7 +313,7 @@ def _qt_refresh(self, set_scatter_range=False):
             # make a copy of the color
             color = QT.QColor(self.get_unit_color(unit_id))
             color.setAlpha(int(self.settings['alpha']*255))
-            self.scatter.addPoints(x=spike_times, y=spike_data,  pen=pg.mkPen(None), brush=color)
+            self.scatter.addPoints(x=spike_times, y=spike_data, pen=pg.mkPen(None), brush=color)
 
             color = self.get_unit_color(unit_id)
             curve = pg.PlotCurveItem(hist_count, hist_bins[:-1], fillLevel=None, fillOutline=True, brush=color, pen=color)

spikeinterface_gui/controller.py

@@ -8,13 +8,14 @@
 
 from spikeinterface.widgets.utils import get_unit_colors
 from spikeinterface import compute_sparsity
-from spikeinterface.core import get_template_extremum_channel
+from spikeinterface.core import get_template_extremum_channel, BaseEvent
 from spikeinterface.core.sorting_tools import spike_vector_to_indices
 from spikeinterface.curation import validate_curation_dict
 from spikeinterface.curation.curation_model import Curation
 from spikeinterface.widgets.utils import make_units_table_from_analyzer
 
 from .curation_tools import add_merge, default_label_definitions, empty_curation_data
+from .event_tools import parse_events
 
 spike_dtype =[('sample_index', 'int64'), ('unit_index', 'int64'), 
     ('channel_index', 'int64'), ('segment_index', 'int64'),
@@ -46,6 +47,7 @@ def __init__(
         extra_unit_properties=None,
         skip_extensions=None,
         disable_save_settings_button=False,
+        events=None,
         external_data=None,
         curation_callback=None,
         curation_callback_kwargs=None,
@@ -256,6 +258,16 @@ def __init__(
             self.valid_periods = None
 
         self._potential_merges = None
+        # some direct attribute
+        self.num_segments = self.analyzer.get_num_segments()
+        self.sampling_frequency = self.analyzer.sampling_frequency
+
+        # parse events
+        self.events = None
+        if events is not None:
+            self.events = parse_events(events, self, verbose=verbose)
+            if len(self.events) == 0:
+                self.events = None
 
         t1 = time.perf_counter()
         if verbose:
@@ -266,10 +278,6 @@ def __init__(
         self._extremum_channel = get_template_extremum_channel(self.analyzer,
                                     mode="extremum", peak_sign='both', outputs='index')
 
-        # some direct attribute
-        self.num_segments = self.analyzer.get_num_segments()
-        self.sampling_frequency = self.analyzer.sampling_frequency
-
         # spikeinterface handle colors in matplotlib style tuple values in range (0,1)
         self.refresh_colors()
 
@@ -468,9 +476,12 @@ def update_time_info(self):
         else:
             self.time_info['time_by_seg'] = time_by_seg
 
-    def get_t_start_t_stop(self):
-        segment_index = self.time_info["segment_index"]
-        if self.main_settings["use_times"] and self.has_extension("recording"):
+    def get_t_start_t_stop(self, use_times=None, segment_index=None):
+        if segment_index is None:
+            segment_index = self.time_info["segment_index"]
+        if use_times is None:
+            use_times = self.main_settings["use_times"]
+        if use_times and self.has_extension("recording"):
             t_start = self.analyzer.recording.get_start_time(segment_index=segment_index)
             t_stop = self.analyzer.recording.get_end_time(segment_index=segment_index)
             return t_start, t_stop
@@ -508,14 +519,26 @@ def sample_index_to_time(self, sample_index):
         else:
             return sample_index / self.sampling_frequency
 
-    def time_to_sample_index(self, time):
-        segment_index = self.time_info["segment_index"]
-        if self.main_settings["use_times"] and self.has_extension("recording"):
+    def time_to_sample_index(self, time, segment_index=None, use_times=None):
+        if segment_index is None:
+            segment_index = self.time_info["segment_index"]
+        if use_times is None:
+            use_times = self.main_settings["use_times"]
+        if use_times and self.has_extension("recording"):
             time = self.analyzer.recording.time_to_sample_index(time, segment_index=segment_index)
             return time
         else:
             return int(time * self.sampling_frequency)
 
+    def get_events(self, event_name, segment_index=None):
+        if self.events is None:
+            return None
+        if event_name not in self.events:
+            return None
+        if segment_index is None:
+            segment_index = self.time_info['segment_index']
+        return self.events[event_name][segment_index]
+
     def get_information_txt(self):
         nseg = self.analyzer.get_num_segments()
         nchan = self.analyzer.get_num_channels()
@@ -768,6 +791,8 @@ def set_channel_visibility(self, visible_channel_inds):
     def has_extension(self, extension_name):
         if extension_name == 'recording':
             return self.analyzer.has_recording() or self.analyzer.has_temporary_recording()
+        elif extension_name == 'events':
+            return self.events is not None
         else:
             # extension needs to be loaded
             if extension_name in self.skip_extensions:

spikeinterface_gui/event_tools.py

@@ -0,0 +1,89 @@
+import numpy as np
+
+from spikeinterface.core import BaseEvent
+
+def parse_events(events, controller, verbose=False):
+    """Parse events input into a standard format.
+
+    Parameters
+    ----------
+    events : dict | BaseEvent
+        BaseEvent object or a dictionary where keys are event names and values are dictionaries with at least a 
+        'samples' key or 'times' key.
+    controller : Controller
+        Controller object managing the event parsing.
+    verbose : bool, default: False
+        Whether to print verbose messages.
+
+    Returns
+    -------
+    parsed_events : dict
+        Parsed events dictionary. The keys are event names, and the values are lists of numpy arrays of event sample indices.
+        Each element corresponds to a segment in the recording.
+    """
+    parsed_events = {}
+    if isinstance(events, dict):
+        for key, val in events.items():
+            if not isinstance(val, dict):
+                if verbose:
+                    print(f'\tSkipping event {key}: not a dict')
+                continue
+            if 'samples' not in val and 'times' not in val:
+                if verbose:
+                    print(f'\tSkipping event {key}: missing samples or times')
+                continue
+            if 'times' in val:
+                samples_data = val['times']
+                convert_to_samples = True
+            else:
+                samples_data = val['samples']
+                convert_to_samples = False
+            if controller.num_segments > 1:
+                if not len(samples_data) == controller.num_segments:
+                    if verbose:
+                        print(f'\tSkipping event {key}: inconsistent number of samples')
+                    continue
+            else:
+                # here we make sure samples is a list of list
+                if np.array(samples_data).ndim == 1:
+                    samples_data = [samples_data]
+            if convert_to_samples:
+                # filter events based on recording start/stop times
+                filtered_samples_data = []
+                parsed_events[key] = []
+                for segment_index in range(controller.num_segments):
+                    t_start, t_end = controller.get_t_start_t_stop(use_times=True, segment_index=segment_index)
+                    s = samples_data[segment_index]
+                    filtered_samples_data = s[(s >= t_start) & (s <= t_end)]
+                    parsed_events[key].append(
+                        np.sort(
+                            controller.time_to_sample_index(
+                                filtered_samples_data,
+                                segment_index=segment_index,
+                                use_times=True
+                            )
+                        )
+                    )
+                
+            else:
+                parsed_events[key] = [np.sort(s) for s in samples_data]
+    elif isinstance(events, BaseEvent):
+        event_names = events.channel_ids
+        parsed_events = {
+            event_name: [] for event_name in event_names
+        }
+        for event_name in event_names:
+            for segment_index in range(controller.num_segments):
+                event_times_segment = events.get_event_times(
+                    channel_id=event_name,
+                    segment_index=segment_index
+                )
+                event_samples_segment = controller.time_to_sample_index(
+                    event_times_segment, segment_index=segment_index, use_times=True
+                )
+                parsed_events[event_name].append(np.sort(event_samples_segment))
+    else:
+        if verbose:
+            print('\tSkipping events: not a dict or BaseEvent')
+    
+    return parsed_events