More docstring updates

src/spikeinterface/core/analyzer_extension_core.py

@@ -677,7 +677,8 @@ class ComputeNoiseLevels(AnalyzerExtension):
     ----------
     sorting_analyzer : SortingAnalyzer
         A SortingAnalyzer object
-    **params : dict with additional parameters for the `spikeinterface.get_noise_levels()` function
+    **kwargs : dict
+        Additional parameters for the `spikeinterface.get_noise_levels()` function
 
     Returns
     -------

src/spikeinterface/postprocessing/correlograms.py

@@ -20,8 +20,8 @@ class ComputeCorrelograms(AnalyzerExtension):
 
     Parameters
     ----------
-    sorting_analyzer : SortingAnalyzer
-        A SortingAnalyzer object
+    sorting_analyzer_or_sorting : SortingAnalyzer | Sorting
+        A SortingAnalyzer or Sorting object
     window_ms : float, default: 50.0
         The window around the spike to compute the correlation in ms. For example,
          if 50 ms, the correlations will be computed at lags -25 ms ... 25 ms.

src/spikeinterface/postprocessing/spike_amplitudes.py

@@ -42,8 +42,8 @@ class ComputeSpikeAmplitudes(AnalyzerExtension):
               In case channel_from_template=False, this is the peak sign.
     method : "center_of_mass" | "monopolar_triangulation" | "grid_convolution", default: "center_of_mass"
         The localization method to use
-    method_kwargs : dict, default: dict()
-        Other kwargs depending on the method.
+    **method_kwargs : dict, default: {}
+        Kwargs which are passed to the method function. These can be found in the docstrings of `compute_center_of_mass`, `compute_grid_convolution` and `compute_monopolar_triangulation`.
     outputs : "numpy" | "by_unit", default: "numpy"
         The output format, either concatenated as numpy array or separated on a per unit basis
 

src/spikeinterface/postprocessing/template_metrics.py

@@ -77,9 +77,9 @@ class ComputeTemplateMetrics(AnalyzerExtension):
             * spread_threshold: the threshold to compute the spread, default: 0.2
             * spread_smooth_um: the smoothing in um to compute the spread, default: 20
             * column_range: the range in um in the horizontal direction to consider channels for velocity, default: None
-                        - If None, all channels all channels are considered
-                        - If 0 or 1, only the "column" that includes the max channel is considered
-                        - If > 1, only channels within range (+/-) um from the max channel horizontal position are used
+                - If None, all channels all channels are considered
+                - If 0 or 1, only the "column" that includes the max channel is considered
+                - If > 1, only channels within range (+/-) um from the max channel horizontal position are used
 
     Returns
     -------

src/spikeinterface/postprocessing/unit_locations.py

@@ -28,8 +28,8 @@ class ComputeUnitLocations(AnalyzerExtension):
         A SortingAnalyzer object
     method : "center_of_mass" | "monopolar_triangulation" | "grid_convolution", default: "center_of_mass"
         The method to use for localization
-    method_kwargs : dict, default: {}
-        Other kwargs depending on the method
+    **method_kwargs : dict, default: {}
+        Kwargs which are passed to the method function. These can be found in the docstrings of `compute_center_of_mass`, `compute_grid_convolution` and `compute_monopolar_triangulation`.
 
     Returns
     -------
@@ -94,7 +94,7 @@ def _run(self, verbose=False):
         method_kwargs.pop("method")
 
         if method not in _unit_location_methods:
-            raise ValueError(f"Wrong ethod for unit_locations : it should be in {list(_unit_location_methods.keys())}")
+            raise ValueError(f"Wrong method for unit_locations : it should be in {list(_unit_location_methods.keys())}")
 
         func = _unit_location_methods[method]
         self.data["unit_locations"] = func(self.sorting_analyzer, **method_kwargs)

src/spikeinterface/sortingcomponents/motion/motion_estimation.py

@@ -32,8 +32,6 @@ def estimate_motion(
     **method_kwargs,
 ):
     """
-
-
     Estimate motion with several possible methods.
 
     Most of methods except dredge_lfp needs peaks and after their localization.
@@ -56,7 +54,6 @@ def estimate_motion(
 
     {method_doc}
 
-
     rigid : bool, default: False
         Compute rigid (one motion for the entire probe) or non rigid motion
         Rigid computation is equivalent to non-rigid with only one window with rectangular shape.
@@ -82,6 +79,7 @@ def estimate_motion(
         Display progress bar or not
     verbose : bool, default: False
         If True, output is verbose
+    **method_kwargs :
 
     Returns
     -------

src/spikeinterface/sortingcomponents/motion/motion_interpolation.py

@@ -276,7 +276,7 @@ class InterpolateMotionRecording(BasePreprocessor):
         Interpolation needs to convert to a floating dtype. If dtype is supplied, that will be used.
         If the input recording is already floating and dtype=None, then its dtype is used by default.
         If the input recording is integer, then float32 is used by default.
-    **spatial_interpolation_kwargs: dict
+    **spatial_interpolation_kwargs : dict
         Spatial interpolation kwargs for `interpolate_motion_on_traces`.
 
     Returns