plot density map with msecs on x axis

Author: ecobost

src/spikeinterface/widgets/unit_summary.py

@@ -180,6 +180,7 @@ def plot_matplotlib(self, data_plot, **backend_kwargs):
                 **unitwaveformdensitymapwidget_kwargs,
             )
             col_counter += 1
+            ax_waveform_density.set_xlabel(None)
             ax_waveform_density.set_ylabel(None)
 
         if sorting_analyzer.has_extension("correlograms"):

src/spikeinterface/widgets/unit_waveforms_density_map.py

@@ -121,7 +121,7 @@ def __init__(
                 wfs = wfs_
 
             # make histogram density
-            wfs_flat = wfs.swapaxes(1, 2).reshape(wfs.shape[0], -1)  # num_spikes x times*num_channels
+            wfs_flat = wfs.swapaxes(1, 2).reshape(wfs.shape[0], -1)  # num_spikes x (num_channels * timepoints)
             hists_per_timepoint = [np.histogram(one_timepoint, bins=bins)[0] for one_timepoint in wfs_flat.T]
             hist2d = np.stack(hists_per_timepoint)
 
@@ -157,6 +157,7 @@ def __init__(
             bin_min=bin_min,
             bin_max=bin_max,
             all_hist2d=all_hist2d,
+            sampling_frequency=sorting_analyzer.sampling_frequency,
             templates_flat=templates_flat,
             template_width=wfs.shape[1],
         )
@@ -173,37 +174,36 @@ def plot_matplotlib(self, data_plot, **backend_kwargs):
             backend_kwargs["num_axes"] = 1 if dp.same_axis else len(dp.unit_ids)
         self.figure, self.axes, self.ax = make_mpl_figure(**backend_kwargs)
 
+        freq_khz = dp.sampling_frequency / 1000  # samples / msec
         if dp.same_axis:
-            ax = self.ax
             hist2d = dp.all_hist2d
-            im = ax.imshow(
+            x_max = len(hist2d) / freq_khz  # in milliseconds
+            self.ax.imshow(
                 hist2d.T,
                 interpolation="nearest",
                 origin="lower",
                 aspect="auto",
-                extent=(0, hist2d.shape[0], dp.bin_min, dp.bin_max),
+                extent=(0, x_max, dp.bin_min, dp.bin_max),
                 cmap="hot",
             )
         else:
-            for unit_index, unit_id in enumerate(dp.unit_ids):
+            for ax, unit_id in zip(self.axes.flatten(), dp.unit_ids):
                 hist2d = dp.all_hist2d[unit_id]
-                ax = self.axes.flatten()[unit_index]
-                im = ax.imshow(
+                x_max = len(hist2d) / freq_khz # in milliseconds
+                ax.imshow(
                     hist2d.T,
                     interpolation="nearest",
                     origin="lower",
                     aspect="auto",
-                    extent=(0, hist2d.shape[0], dp.bin_min, dp.bin_max),
+                    extent=(0, x_max, dp.bin_min, dp.bin_max),
                     cmap="hot",
                 )
 
         for unit_index, unit_id in enumerate(dp.unit_ids):
-            if dp.same_axis:
-                ax = self.ax
-            else:
-                ax = self.axes.flatten()[unit_index]
+            ax = self.ax if dp.same_axis else self.axes.flatten()[unit_index]
             color = dp.unit_colors[unit_id]
-            ax.plot(dp.templates_flat[unit_id], color=color, lw=1)
+            x = np.arange(len(dp.templates_flat[unit_id])) / freq_khz
+            ax.plot(x, dp.templates_flat[unit_id], color=color, lw=1)
 
         # final cosmetics
         for unit_index, unit_id in enumerate(dp.unit_ids):
@@ -216,11 +216,11 @@ def plot_matplotlib(self, data_plot, **backend_kwargs):
             chan_inds = dp.channel_inds[unit_id]
             for i, chan_ind in enumerate(chan_inds):
                 if i != 0:
-                    ax.axvline(i * dp.template_width, color="w", lw=3)
+                    ax.axvline(i * dp.template_width / freq_khz, color="w", lw=3)
                 channel_id = dp.channel_ids[chan_ind]
-                x = i * dp.template_width + dp.template_width // 2
+                x = (i + 0.5) * dp.template_width / freq_khz
                 y = (dp.bin_max + dp.bin_min) / 2.0
                 ax.text(x, y, f"chan_id {channel_id}", color="w", ha="center", va="center")
 
-            ax.set_xticks([])
+            ax.set_xlabel('Time [ms]')
             ax.set_ylabel(f"unit_id {unit_id}")