Fix raster and trace (#60)

BlueBrain · May 27, 2020 · 018426e · 018426e
1 parent d3b4b53
commit 018426e
Showing 1 changed file with 5 additions and 5 deletions.
diff --git a/bluepysnap/_plotting.py b/bluepysnap/_plotting.py
@@ -91,7 +91,7 @@ def spikes_firing_rate_histogram(filtered_report, time_binsize=None, ax=None):
     return ax
 
 
-def spike_raster(filtered_report, y_axis="node_id", ax=None):  # pragma: no cover
+def spike_raster(filtered_report, y_axis=None, ax=None):  # pragma: no cover
     """Spike raster plot.
 
     Shows a global overview of the circuit's firing nodes. The y axis can project either the
@@ -122,7 +122,7 @@ def spike_raster(filtered_report, y_axis="node_id", ax=None):  # pragma: no cove
              }
 
     def _update_raster_properties():
-        if y_axis == "node_id":
+        if y_axis is None:
             props["node_id_offset"] += spikes.nodes.size
             props["pop_separators"].append(props["node_id_offset"])
         elif pd.api.types.is_categorical_dtype(spikes.nodes.property_dtypes[y_axis]):
@@ -141,7 +141,7 @@ def _update_raster_properties():
     for population in population_names:
         spikes = spike_report[population]
         mask = report["population"] == population
-        if y_axis == "node_id":
+        if y_axis is None:
             data.loc[mask] = report.loc[mask, "ids"] + props["node_id_offset"]
         else:
             ids = report.loc[mask, "ids"].to_numpy()
@@ -160,7 +160,7 @@ def _update_raster_properties():
         ax.set_xlabel("Time [ms]")
         ax.tick_params(axis='y', which='both', length=0)
         ax.set_xlim(spike_report.time_start, spike_report.time_stop)
-        if y_axis == "node_id":
+        if y_axis is None:
             ax.set_ylim(0, props["node_id_offset"])
             ax.set_ylabel("nodes")
         else:
@@ -352,7 +352,7 @@ def frame_trace(filtered_report, plot_type='mean', ax=None):  # pragma: no cover
         elif plot_type == "all":
             ax.set_ylabel('Voltage [{}]'.format(data_units))
         ax.set_xlabel("Time [{}]".format(filtered_report.frame_report.time_units))
-        ax.set_xlim([filtered_report.t_start, filtered_report.t_stop])
+        ax.set_xlim([filtered_report.report.index.min(), filtered_report.report.index.max()])
 
     if plot_type == "mean":
         ax.plot(filtered_report.report.T.mean())