segment issues

Author: chrishalcrow

src/spikeinterface/postprocessing/spike_amplitudes.py

@@ -31,7 +31,6 @@ class ComputeSpikeAmplitudes(AnalyzerExtension):
     spike_retriver_kwargs : dict
         A dictionary to control the behavior for getting the maximum channel for each spike
         This dictionary contains:
-
           * channel_from_template: bool, default: True
               For each spike is the maximum channel computed from template or re estimated at every spikes
               channel_from_template = True is old behavior but less acurate

src/spikeinterface/widgets/amplitudes.py

@@ -32,7 +32,7 @@ class AmplitudesWidget(BaseRasterWidget):
     y_lim : tuple or None, default: None
         The min and max depth to display, if None (min and max of the amplitudes).
     scatter_decimate : int, default: 1
-        If > 1, the scatter points are decimated.
+        If equal to n, each nth spike is kept for plotting.
     hide_unit_selector : bool, default: False
         If True the unit selector is not displayed
         (sortingview backend)
@@ -73,17 +73,11 @@ def __init__(
         if unit_ids is None:
             unit_ids = sorting.unit_ids
 
-        if sorting.get_num_segments() > 1:
-            if segment_index is None:
-                warn("More than one segment available! Using segment_index 0")
-                segment_index = 0
-        else:
-            segment_index = 0
         amplitudes_segment = amplitudes[segment_index]
         total_duration = sorting_analyzer.get_num_samples(segment_index) / sorting_analyzer.sampling_frequency
 
         all_spiketrains = {
-            unit_id: sorting.get_unit_spike_train(unit_id, segment_index=0, return_times=True)
+            unit_id: sorting.get_unit_spike_train(unit_id, segment_index=segment_index, return_times=True)
             for unit_id in sorting.unit_ids
         }
 

src/spikeinterface/widgets/motion.py

@@ -128,7 +128,7 @@ class DriftRasterMapWidget(BaseRasterWidget):
     depth_lim : tuple or None, default: None
         The min and max depth to display, if None (min and max of the recording).
     scatter_decimate : int, default: None
-        If > 1, the scatter points are decimated.
+        If equal to n, each nth spike is kept for plotting.
     color_amplitude : bool, default: True
         If True, the color of the scatter points is the amplitude of the peaks.
     cmap : str, default: "inferno"
@@ -264,7 +264,7 @@ class MotionInfoWidget(BaseWidget):
     motion_lim : tuple or None, default: None
         The min and max motion to display, if None (min and max of the motion).
     scatter_decimate : int, default: None
-        If > 1, the scatter points are decimated.
+        If equal to n, each nth spike is kept for plotting.
     color_amplitude : bool, default: False
         If True, the color of the scatter points is the amplitude of the peaks.
     amplitude_cmap : str, default: "inferno"

src/spikeinterface/widgets/rasters.py

@@ -28,7 +28,7 @@ class BaseRasterWidget(BaseWidget):
     bins : int | None, default: None
         Number of bins to use in histogram. If None, use 1/30 of spike train sample length.
     scatter_decimate : int | None, default: None
-        If > 1, the scatter points are decimated.
+        If equal to n, each nth spike is kept for plotting.
     unit_colors : dict | None, default: None
         Dict of colors with key : unit, value : color. If None, uses `get_some_colors` to
         generate colors.
@@ -312,16 +312,15 @@ def __init__(
 
         sorting = self.ensure_sorting(sorting)
 
-        if segment_index is None:
-            if sorting.get_num_segments() != 1:
-                raise ValueError("You must provide segment_index=...")
-            segment_index = 0
+        if segment_index is None and sorting.get_num_segments() != 1:
+            raise ValueError("You must provide segment_index=...")
 
         if unit_ids is None:
             unit_ids = sorting.unit_ids
 
         all_spiketrains = {
-            unit_id: sorting.get_unit_spike_train(unit_id, segment_index=0, return_times=True) for unit_id in unit_ids
+            unit_id: sorting.get_unit_spike_train(unit_id, segment_index=segment_index, return_times=True)
+            for unit_id in unit_ids
         }
 
         if time_range is not None: