Merge pull request #2149 from zm711/plot_traces

Add assert error in the case of unichannel data for sortingview backend + minor clarifications

src/spikeinterface/widgets/traces.py

@@ -26,7 +26,6 @@ class TracesWidget(BaseWidget):
         List with start time and end time
     mode: "line" | "map" | "auto", default: "auto"
         Three possible modes
-
         * "line": classical for low channel count
         * "map": for high channel count use color heat map
         * "auto": auto switch depending on the channel count ("line" if less than 64 channels, "map" otherwise)
@@ -50,7 +49,7 @@ class TracesWidget(BaseWidget):
     seconds_per_row: float, default: 0.2
         For "map" mode and sortingview backend, seconds to render in each row
     add_legend : bool, default: True
-        If True adds legend to figures, default: True
+        If True adds legend to figures
     """
 
     def __init__(
@@ -85,7 +84,10 @@ def __init__(
             recordings = {f"rec{i}": rec for i, rec in enumerate(recording)}
             rec0 = recordings[0]
         else:
-            raise ValueError("plot_traces recording must be recording or dict or list")
+            raise ValueError(
+                "plot_traces 'recording' must be recording or dict or list, recording "
+                f"is currently of type {type(recording)}"
+            )
 
         if rec0.has_channel_location():
             channel_locations = rec0.get_channel_locations()
@@ -111,15 +113,15 @@ def __init__(
 
         if segment_index is None:
             if rec0.get_num_segments() != 1:
-                raise ValueError("You must provide segment_index=...")
+                raise ValueError('You must provide "segment_index" for multisegment recordings.')
             segment_index = 0
 
         fs = rec0.get_sampling_frequency()
         if time_range is None:
             time_range = (0, 1.0)
         time_range = np.array(time_range)
 
-        assert mode in ("auto", "line", "map"), "Mode must be in auto/line/map"
+        assert mode in ("auto", "line", "map"), 'Mode must be one of "auto","line", "map"'
         if mode == "auto":
             if len(channel_ids) <= 64:
                 mode = "line"
@@ -181,7 +183,9 @@ def __init__(
             if isinstance(clim, tuple):
                 clims = {layer_key: clim for layer_key in layer_keys}
             elif isinstance(clim, dict):
-                assert all(layer_key in clim for layer_key in layer_keys), ""
+                assert all(
+                    layer_key in clim for layer_key in layer_keys
+                ), f"all recordings must be a key in `clim` if `clim` is a dict. Provide keys {layer_keys} in clim"
                 clims = clim
             else:
                 raise TypeError(f"'clim' can be None, tuple, or dict! Unsupported type {type(clim)}")
@@ -257,7 +261,7 @@ def plot_matplotlib(self, data_plot, **backend_kwargs):
                 ax.legend(loc="upper right")
 
         elif dp.mode == "map":
-            assert len(dp.list_traces) == 1, 'plot_traces with mode="map" do not support multi recording'
+            assert len(dp.list_traces) == 1, 'plot_traces with mode="map" does not support multi-recording'
             assert len(dp.clims) == 1
             clim = list(dp.clims.values())[0]
             extent = (dp.time_range[0], dp.time_range[1], min_y, max_y)
@@ -473,11 +477,11 @@ def plot_sortingview(self, data_plot, **backend_kwargs):
         try:
             import pyvips
         except ImportError:
-            raise ImportError("To use the timeseries in sorting view you need the pyvips package.")
+            raise ImportError("To use `plot_traces()` in sortingview you need the pyvips package.")
 
         dp = to_attr(data_plot)
 
-        assert dp.mode == "map", 'sortingview plot_traces is only mode="map"'
+        assert dp.mode == "map", 'sortingview `plot_traces` can only have mode="map"'
 
         if not dp.order_channel_by_depth:
             warnings.warn(
@@ -486,6 +490,7 @@ def plot_sortingview(self, data_plot, **backend_kwargs):
 
         tiled_layers = []
         for layer_key, traces in zip(dp.layer_keys, dp.list_traces):
+            assert traces.shape[1] != 1, 'mode="map" only works with multichannel data'
             img = array_to_image(
                 traces,
                 clim=dp.clims[layer_key],
@@ -499,7 +504,7 @@ def plot_sortingview(self, data_plot, **backend_kwargs):
 
         self.view = vv.TiledImage(tile_size=dp.tile_size, layers=tiled_layers)
 
-        # timeseries currently doesn't display on the jupyter backend
+        # traces currently doesn't display on the jupyter backend
         backend_kwargs["display"] = False
 
         self.url = handle_display_and_url(self, self.view, **backend_kwargs)