Bump

Author: bjhardcastle

pyproject.toml

@@ -19,7 +19,7 @@ dependencies = [
     "polars>=0.20.26",
     "pyarrow>=14.0",
 ]
-version = "0.1.33"
+version = "0.1.34"
 classifiers = [
     "Development Status :: 3 - Alpha",
     "Programming Language :: Python :: 3",

src/npc_ephys/spikeinterface.py

@@ -461,11 +461,9 @@ def spike_amplitudes(self, probe: str) -> tuple[npt.NDArray[np.floating], ...]:
         unit_indexes = self.unit_indexes(probe)
         spike_amplitudes_by_unit: list[npt.NDArray[np.floating]] = []
         for index in sorted(np.unique(unit_indexes)):
-            spike_amplitudes_by_unit.append(
-                spike_amplitudes[unit_indexes == index]
-            )
+            spike_amplitudes_by_unit.append(spike_amplitudes[unit_indexes == index])
         return tuple(spike_amplitudes_by_unit)
-    
+
     @functools.cache
     def unit_locations(self, probe: str) -> npt.NDArray[np.floating]:
         return np.load(

src/npc_ephys/units.py

@@ -224,8 +224,13 @@ def _device_helper(
         [len(unit) for unit in units_x_spike_times],
     ), "Mismatch between rows in spike_times and metrics.csv"
     df_device_metrics["spike_times"] = units_x_spike_times
-    df_device_metrics["spike_amplitudes"] = spike_interface_data.spike_amplitudes(electrode_group_name)
-    assert all(len(df_device_metrics["spike_amplitudes"].iloc[i]) == len(spike_times) for i, spike_times in enumerate(units_x_spike_times)), "Mismatch between spike_times and spike_amplitudes"
+    df_device_metrics["spike_amplitudes"] = spike_interface_data.spike_amplitudes(
+        electrode_group_name
+    )
+    assert all(
+        len(df_device_metrics["spike_amplitudes"].iloc[i]) == len(spike_times)
+        for i, spike_times in enumerate(units_x_spike_times)
+    ), "Mismatch between spike_times and spike_amplitudes"
 
     return df_device_metrics