adding some typing (#2031)

src/spikeinterface/core/sparsity.py

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 import numpy as np
 
 from .recording_tools import get_channel_distances, get_noise_levels
@@ -125,7 +127,7 @@ def unit_id_to_channel_indices(self):
                 self._unit_id_to_channel_indices[unit_id] = channel_inds
         return self._unit_id_to_channel_indices
 
-    def sparsify_waveforms(self, waveforms: np.ndarray, unit_id: str) -> np.ndarray:
+    def sparsify_waveforms(self, waveforms: np.ndarray, unit_id: str | int) -> np.ndarray:
         """
         Sparsify the waveforms according to a unit_id corresponding sparsity.
 
@@ -159,7 +161,7 @@ def sparsify_waveforms(self, waveforms: np.ndarray, unit_id: str) -> np.ndarray:
 
         return sparsified_waveforms
 
-    def densify_waveforms(self, waveforms: np.ndarray, unit_id: str) -> np.ndarray:
+    def densify_waveforms(self, waveforms: np.ndarray, unit_id: str | int) -> np.ndarray:
         """
         Densify sparse waveforms that were sparisified according to a unit's channel sparsity.
 
@@ -199,7 +201,7 @@ def densify_waveforms(self, waveforms: np.ndarray, unit_id: str) -> np.ndarray:
     def are_waveforms_dense(self, waveforms: np.ndarray) -> bool:
         return waveforms.shape[-1] == self.num_channels
 
-    def are_waveforms_sparse(self, waveforms: np.ndarray, unit_id: str) -> bool:
+    def are_waveforms_sparse(self, waveforms: np.ndarray, unit_id: str | int) -> bool:
         non_zero_indices = self.unit_id_to_channel_indices[unit_id]
         num_active_channels = len(non_zero_indices)
         return waveforms.shape[-1] == num_active_channels