Save extension class info.

src/spikeinterface/core/base.py

@@ -23,6 +23,7 @@
     make_paths_relative,
     make_paths_absolute,
     check_paths_relative,
+    retrieve_importing_provenance,
 )
 from .job_tools import _shared_job_kwargs_doc
 
@@ -427,22 +428,8 @@ def to_dict(
 
             kwargs = new_kwargs
 
-        module_import_path = self.__class__.__module__
-        class_name_no_path = self.__class__.__name__
-        class_name = f"{module_import_path}.{class_name_no_path}"  # e.g. 'spikeinterface.core.generate.AClass'
-        module = class_name.split(".")[0]
-
-        imported_module = importlib.import_module(module)
-        module_version = getattr(imported_module, "__version__", "unknown")
-
-        dump_dict = {
-            "class": class_name,
-            "module": module,
-            "kwargs": kwargs,
-            "version": module_version,
-        }
-
-        dump_dict["version"] = module_version  # Can be spikeinterface, spikeforest, etc.
+        dump_dict = retrieve_importing_provenance(self.__class__)
+        dump_dict["kwargs"] = kwargs
 
         if include_annotations:
             dump_dict["annotations"] = self._annotations

src/spikeinterface/core/core_tools.py

@@ -6,6 +6,7 @@
 import datetime
 import json
 from copy import deepcopy
+import importlib
 
 
 import numpy as np
@@ -476,3 +477,38 @@ def normal_pdf(x, mu: float = 0.0, sigma: float = 1.0):
     """
 
     return 1 / (sigma * np.sqrt(2 * np.pi)) * np.exp(-((x - mu) ** 2) / (2 * sigma**2))
+
+
+def retrieve_importing_provenance(a_class):
+    """
+    Retrieve the import provenance of a class, including its an import name that consists of the class name and the module, the top-level module, and the module version.
+
+    Parameters
+    ----------
+    a_class : type
+        The class object for which to retrieve the import provenance.
+
+    Returns
+    -------
+    dict
+        A dictionary containing:
+        - 'class':  The module path and the name of the class concatenated (e.g., 'package.subpackage.ClassName').
+        - 'module': The top-level module name where the class is defined.
+        - 'version': The version of the module if available, otherwise 'unknown'.
+    Get class info as a dict.
+    """
+    module_import_path = a_class.__module__
+    class_name_no_path = a_class.__name__
+    class_name = f"{module_import_path}.{class_name_no_path}"  # e.g. 'spikeinterface.core.generate.AClass'
+    module = class_name.split(".")[0]
+
+    imported_module = importlib.import_module(module)
+    module_version = getattr(imported_module, "__version__", "unknown")
+
+    info = {
+        "class": class_name,
+        "module": module,
+        "version": module_version,
+    }
+
+    return info

src/spikeinterface/core/sortinganalyzer.py

@@ -20,7 +20,7 @@
 
 from .base import load_extractor
 from .recording_tools import check_probe_do_not_overlap, get_rec_attributes
-from .core_tools import check_json
+from .core_tools import check_json, retrieve_importing_provenance
 from .job_tools import split_job_kwargs
 from .numpyextractors import SharedMemorySorting
 from .sparsity import ChannelSparsity, estimate_sparsity
@@ -1317,6 +1317,7 @@ def run(self, save=True, **kwargs):
         if save and not self.sorting_analyzer.is_read_only():
             # this also reset the folder or zarr group
             self._save_params()
+            self._save_info()
 
         self._run(**kwargs)
 
@@ -1325,6 +1326,7 @@ def run(self, save=True, **kwargs):
 
     def save(self, **kwargs):
         self._save_params()
+        self._save_info()
         self._save_data(**kwargs)
 
     def _save_data(self, **kwargs):
@@ -1443,6 +1445,7 @@ def set_params(self, save=True, **params):
 
         if save:
             self._save_params()
+            self._save_info()
 
     def _save_params(self):
         params_to_save = self.params.copy()
@@ -1465,6 +1468,21 @@ def _save_params(self):
             extension_group = self._get_zarr_extension_group(mode="r+")
             extension_group.attrs["params"] = check_json(params_to_save)
 
+    def _save_info(self):
+        # this save class info, this is not uselfull at the moment but this could be usefull in futur
+        # if some class change the data model and if we need to make backwards compatibility
+        # we have the same machanism in base.py for recording and sorting
+
+        info = retrieve_importing_provenance(self.__class__)
+        if self.format == "binary_folder":
+            extension_folder = self._get_binary_extension_folder()
+            extension_folder.mkdir(exist_ok=True, parents=True)
+            info_file = extension_folder / "info.json"
+            info_file.write_text(json.dumps(info, indent=4), encoding="utf8")
+        elif self.format == "zarr":
+            extension_group = self._get_zarr_extension_group(mode="r+")
+            extension_group.attrs["info"] = info
+
     def get_pipeline_nodes(self):
         assert (
             self.use_nodepipeline

src/spikeinterface/sortingcomponents/clustering/split.py

@@ -231,6 +231,17 @@ def split(
             possible_labels = clust.labels_
             is_split = np.setdiff1d(possible_labels, [-1]).size > 1
         elif clusterer == "isocut5":
+            print(final_features[:, 0].shape)
+            unique_feat, counts_feat = np.unique(final_features[:, 0], return_counts=True)
+            import matplotlib.pyplot as plt
+
+            fig, ax = plt.subplots()
+            ax.hist(final_features[:, 0])
+            fig, ax = plt.subplots()
+            ax.plot(unique_feat, counts_feat)
+            plt.show()
+
+            print(np.sum(counts_feat > 1))
             dipscore, cutpoint = isocut5(final_features[:, 0])
             possible_labels = np.zeros(final_features.shape[0])
             if dipscore > 1.5: