Unify 'defaults'

src/spikeinterface/comparison/multicomparisons.py

@@ -25,22 +25,22 @@ class MultiSortingComparison(BaseMultiComparison, MixinSpikeTrainComparison):
     ----------
     sorting_list: list
         List of sorting extractor objects to be compared
-    name_list: list
+    name_list: list, default: None
         List of spike sorter names. If not given, sorters are named as 'sorter0', 'sorter1', 'sorter2', etc.
-    delta_time: float
-        Number of ms to consider coincident spikes (default 0.4 ms)
-    match_score: float
-        Minimum agreement score to match units (default 0.5)
-    chance_score: float
-        Minimum agreement score to for a possible match (default 0.1)
-    n_jobs: int
+    delta_time: float, default: 0.4
+        Number of ms to consider coincident spikes
+    match_score: float, default: 0.5
+        Minimum agreement score to match units
+    chance_score: float, default: 0.1
+        Minimum agreement score to for a possible match
+    n_jobs: int, default: -1
        Number of cores to use in parallel. Uses all available if -1
-    spiketrain_mode: str
+    spiketrain_mode: "union" | "intersection", default: "union"
         Mode to extract agreement spike trains:
-            - 'union': spike trains are the union between the spike trains of the best matching two sorters
-            - 'intersection': spike trains are the intersection between the spike trains of the
+            - "union": spike trains are the union between the spike trains of the best matching two sorters
+            - "intersection": spike trains are the intersection between the spike trains of the
                best matching two sorters
-    verbose: bool
+    verbose: bool, default: False
         if True, output is verbose
 
     Returns
@@ -309,13 +309,13 @@ class MultiTemplateComparison(BaseMultiComparison, MixinTemplateComparison):
     ----------
     waveform_list: list
         List of waveform extractor objects to be compared
-    name_list: list
+    name_list: list, default: None
         List of session names. If not given, sorters are named as 'sess0', 'sess1', 'sess2', etc.
-    match_score: float
-        Minimum agreement score to match units (default 0.5)
-    chance_score: float
-        Minimum agreement score to for a possible match (default 0.1)
-    verbose: bool
+    match_score: float, default: 0.8
+        Minimum agreement score to match units
+    chance_score: float, default: 0.3
+        Minimum agreement score to for a possible match
+    verbose: bool, default: False
         if True, output is verbose
 
     Returns

src/spikeinterface/comparison/paircomparisons.py

@@ -111,19 +111,19 @@ class SymmetricSortingComparison(BasePairSorterComparison):
         The first sorting for the comparison
     sorting2: SortingExtractor
         The second sorting for the comparison
-    sorting1_name: str
+    sorting1_name: str, default: None
         The name of sorter 1
-    sorting2_name: : str
+    sorting2_name: : str, default: None
         The name of sorter 2
-    delta_time: float
-        Number of ms to consider coincident spikes (default 0.4 ms)
-    match_score: float
-        Minimum agreement score to match units (default 0.5)
-    chance_score: float
-        Minimum agreement score to for a possible match (default 0.1)
-    n_jobs: int
+    delta_time: float, default: 0.4
+        Number of ms to consider coincident spikes
+    match_score: float, default: 0.5
+        Minimum agreement score to match units
+    chance_score: float, default: 0.1
+        Minimum agreement score to for a possible match
+    n_jobs: int, default: -1
         Number of cores to use in parallel. Uses all available if -1
-    verbose: bool
+    verbose: bool, default: False
         If True, output is verbose
 
     Returns
@@ -139,7 +139,6 @@ def __init__(
         sorting1_name=None,
         sorting2_name=None,
         delta_time=0.4,
-        sampling_frequency=None,
         match_score=0.5,
         chance_score=0.1,
         n_jobs=-1,
@@ -214,34 +213,35 @@ class GroundTruthComparison(BasePairSorterComparison):
         The first sorting for the comparison
     tested_sorting: SortingExtractor
         The second sorting for the comparison
-    gt_name: str
+    gt_name: str, default: None
         The name of sorter 1
-    tested_name: : str
+    tested_name: : str, default: None
         The name of sorter 2
-    delta_time: float
-        Number of ms to consider coincident spikes (default 0.4 ms)    match_score: float
-        Minimum agreement score to match units (default 0.5)
-    chance_score: float
-        Minimum agreement score to for a possible match (default 0.1)
-    redundant_score: float
-        Agreement score above which units are redundant (default 0.2)
-    overmerged_score: float
-        Agreement score above which units can be overmerged (default 0.2)
-    well_detected_score: float
-        Agreement score above which units are well detected (default 0.8)
-    exhaustive_gt: bool (default True)
+    delta_time: float, default: 0.4
+        Number of ms to consider coincident spikes
+    match_score: float, default: 0.5
+        Minimum agreement score to match units
+    chance_score: float, default: 0.1
+        Minimum agreement score to for a possible match
+    redundant_score: float, default: 0.2
+        Agreement score above which units are redundant
+    overmerged_score: float, default: 0.2
+        Agreement score above which units can be overmerged
+    well_detected_score: float, default: 0.8
+        Agreement score above which units are well detected
+    exhaustive_gt: bool, default: False
         Tell if the ground true is "exhaustive" or not. In other world if the
         GT have all possible units. It allows more performance measurement.
         For instance, MEArec simulated dataset have exhaustive_gt=True
-    match_mode: 'hungarian', or 'best'
-        What is match used for counting : 'hungarian' or 'best match'.
-    n_jobs: int
+    match_mode: "hungarian" | "best", default: 'hungarian
+        The method to match units
+    n_jobs: int, default: -1
         Number of cores to use in parallel. Uses all available if -1
-    compute_labels: bool
-        If True, labels are computed at instantiation (default False)
-    compute_misclassifications: bool
-        If True, misclassifications are computed at instantiation (default False)
-    verbose: bool
+    compute_labels: bool, default: False
+        If True, labels are computed at instantiation
+    compute_misclassifications: bool, default: False
+        If True, misclassifications are computed at instantiation
+    verbose: bool, default: False
         If True, output is verbose
 
     Returns
@@ -471,7 +471,7 @@ def get_well_detected_units(self, well_detected_score=None):
 
         Parameters
         ----------
-        well_detected_score: float (default 0.8)
+        well_detected_score: float, default: None
             The agreement score above which tested units
             are counted as "well detected".
         """
@@ -507,7 +507,7 @@ def get_false_positive_units(self, redundant_score=None):
 
         Parameters
         ----------
-        redundant_score: float (default 0.2)
+        redundant_score: float, default: None
             The agreement score below which tested units
             are counted as "false positive"" (and not "redundant").
         """
@@ -547,7 +547,7 @@ def get_redundant_units(self, redundant_score=None):
 
         Parameters
         ----------
-        redundant_score=None: float (default 0.2)
+        redundant_score=None: float, default: None
             The agreement score above which tested units
             are counted as "redundant" (and not "false positive" ).
         """
@@ -582,7 +582,7 @@ def get_overmerged_units(self, overmerged_score=None):
 
         Parameters
         ----------
-        overmerged_score: float (default 0.4)
+        overmerged_score: float, default: None
             Tested units with 2 or more agreement scores above 'overmerged_score'
             are counted as "overmerged".
         """
@@ -693,16 +693,16 @@ class TemplateComparison(BasePairComparison, MixinTemplateComparison):
         The first waveform extractor to get templates to compare
     we2 : WaveformExtractor
         The second waveform extractor to get templates to compare
-    unit_ids1 : list, optional
-        List of units from we1 to compare, by default None
-    unit_ids2 : list, optional
-        List of units from we2 to compare, by default None
-    similarity_method : str, optional
-        Method for the similaroty matrix, by default "cosine_similarity"
-    sparsity_dict : dict, optional
-        Dictionary for sparsity, by default None
-    verbose : bool, optional
-        If True, output is verbose, by default False
+    unit_ids1 : list, default: None
+        List of units from we1 to compare
+    unit_ids2 : list, default: None
+        List of units from we2 to compare
+    similarity_method : str, default: "cosine_similarity"
+        Method for the similaroty matrix
+    sparsity_dict : dict, default: None
+        Dictionary for sparsity
+    verbose : bool, default: False
+        If True, output is verbose
 
     Returns
     -------

src/spikeinterface/core/base.py

@@ -171,11 +171,11 @@ def set_property(self, key, values: Sequence, ids: Optional[Sequence] = None, mi
             The property name
         values : np.array
             Array of values for the property
-        ids : list/np.array, optional
-            List of subset of ids to set the values, by default None
-        missing_value : object, optional
+        ids : list/np.array, default: None
+            List of subset of ids to set the values, default: None
+        missing_value : object, default: None
             In case the property is set on a subset of values ('ids' not None),
-            it specifies the how the missing values should be filled, by default None.
+            it specifies the how the missing values should be filled.
             The missing_value has to be specified for types int and unsigned int.
         """
 
@@ -320,18 +320,18 @@ def to_dict(
 
         Parameters
         ----------
-        include_annotations: bool
-            If True, all annotations are added to the dict, by default False
-        include_properties: bool
-            If True, all properties are added to the dict, by default False
-        relative_to: str, Path, or None
-            If not None, files and folders are serialized relative to this path, by default None
+        include_annotations: bool, default: False
+            If True, all annotations are added to the dict
+        include_properties: bool, default: False
+            If True, all properties are added to the dict
+        relative_to: str, Path, or None, default: None
+            If not None, files and folders are serialized relative to this path
             Used in waveform extractor to maintain relative paths to binary files even if the
             containing folder / diretory is moved
         folder_metadata: str, Path, or None
             Folder with numpy `npy` files containing additional information (e.g. probe in BaseRecording) and properties.
-        recursive: bool
-            If True, all dicitionaries in the kwargs are expanded with `to_dict` as well, by default False.
+        recursive: bool, default: False
+            If True, all dicitionaries in the kwargs are expanded with `to_dict` as well
 
         Returns
         -------
@@ -866,21 +866,22 @@ def save_to_zarr(
 
         Parameters
         ----------
-        name: str or None
+        name: str or None, default: None
             Name of the subfolder in get_global_tmp_folder()
             If 'name' is given, 'folder' must be None.
-        folder: str, Path, or None
+        folder: str, Path, or None, default: None
             The folder used to save the zarr output. If the folder does not have a '.zarr' suffix,
             it will be automatically appended.
-        storage_options: dict or None
+        storage_options: dict or None, default: None
             Storage options for zarr `store`. E.g., if "s3://" or "gcs://" they can provide authentication methods, etc.
             For cloud storage locations, this should not be None (in case of default values, use an empty dict)
-        channel_chunk_size: int or None
-            Channels per chunk. Default None (chunking in time only)
-        verbose: bool
-            If True (default), the output is verbose.
-        zarr_path: str, Path, or None
-            (Deprecated) Name of the zarr folder (.zarr).
+        channel_chunk_size: int or None, default: None
+            Channels per chunk
+        verbose: bool, default: True
+            If True, the output is verbose
+        zarr_path: str, Path, or None, default: None
+            (Deprecated) Name of the zarr folder (.zarr)
+        **save_kwargs: Keyword arguments for saving.
 
         Returns
         -------

src/spikeinterface/core/baseevent.py

@@ -80,14 +80,14 @@ def get_events(
 
         Parameters
         ----------
-        channel_id : int or str, optional
-            The event channel id, by default None
-        segment_index : int, optional
-            The segment index, required for multi-segment objects, by default None
-        start_time : float, optional
-            The start time in seconds, by default None
-        end_time : float, optional
-            The end time in seconds, by default None
+        channel_id : int or str, default: None
+            The event channel id
+        segment_index : int or None, default: None
+            The segment index, required for multi-segment objects
+        start_time : float, default: None
+            The start time in seconds
+        end_time : float, default: None
+            The end time in seconds
 
         Returns
         -------
@@ -110,14 +110,14 @@ def get_event_times(
 
         Parameters
         ----------
-        channel_id : int or str, optional
-            The event channel id, by default None
-        segment_index : int, optional
-            The segment index, required for multi-segment objects, by default None
-        start_time : float, optional
-            The start time in seconds, by default None
-        end_time : float, optional
-            The end time in seconds, by default None
+        channel_id : int or str, default: None
+            The event channel id
+        segment_index : int or None, default: None
+            The segment index, required for multi-segment objects
+        start_time : float, default: None
+            The start time in seconds
+        end_time : float, default: None
+            The end time in seconds
 
         Returns
         -------