Add missing is_scaled

src/spikeinterface/core/generate.py

@@ -1448,7 +1448,7 @@ def generate_templates(
     mode="ellipsoid",
 ):
     """
-    Generate some templates from the given channel positions and neuron position.s
+    Generate some templates from the given channel positions and neuron positions.
 
     The implementation is very naive : it generates a mono channel waveform using generate_single_fake_waveform()
     and duplicates this same waveform on all channel given a simple decay law per unit.

src/spikeinterface/core/tests/test_template_tools.py

@@ -47,6 +47,7 @@ def _get_templates_object_from_sorting_analyzer(sorting_analyzer):
         sparsity_mask=None,
         channel_ids=sorting_analyzer.channel_ids,
         unit_ids=sorting_analyzer.unit_ids,
+        is_scaled=sorting_analyzer.return_scaled,
     )
     return templates
 

src/spikeinterface/generation/drifting_generator.py

@@ -404,6 +404,7 @@ def generate_drifting_recording(
         sampling_frequency=sampling_frequency,
         nbefore=nbefore,
         probe=probe,
+        is_scaled=True,
     )
 
     drifting_templates = DriftingTemplates.from_static(templates)

src/spikeinterface/generation/tests/test_drift_tools.py

@@ -73,6 +73,7 @@ def make_some_templates():
         sampling_frequency=sampling_frequency,
         nbefore=nbefore,
         probe=probe,
+        is_scaled=True,
     )
 
     return templates

src/spikeinterface/sorters/internal/spyking_circus2.py

@@ -1,4 +1,5 @@
 from __future__ import annotations
+from operator import is_
 
 from .si_based import ComponentsBasedSorter
 
@@ -250,13 +251,14 @@ def _run_from_folder(cls, sorter_output_folder, params, verbose):
             )
 
             templates = Templates(
-                templates_array,
-                sampling_frequency,
-                nbefore,
-                None,
-                recording_w.channel_ids,
-                unit_ids,
-                recording_w.get_probe(),
+                templates_array=templates_array,
+                sampling_frequency=sampling_frequency,
+                nbefore=nbefore,
+                sparsity_mask=None,
+                channel_ids=recording_w.channel_ids,
+                unit_ids=unit_ids,
+                probe=recording_w.get_probe(),
+                is_scaled=False,
             )
 
             sparsity = compute_sparsity(templates, noise_levels, **params["sparsity"])

src/spikeinterface/sorters/internal/tridesclous2.py

@@ -191,7 +191,9 @@ def _run_from_folder(cls, sorter_output_folder, params, verbose):
             templates_array=templates_array,
             sampling_frequency=sampling_frequency,
             nbefore=nbefore,
+            sparsity_mask=None,
             probe=recording_w.get_probe(),
+            is_scaled=False,
         )
         # TODO : try other methods for sparsity
         # sparsity = compute_sparsity(templates_dense, method="radius", radius_um=120.)

src/spikeinterface/sortingcomponents/benchmark/tests/common_benchmark_testing.py

@@ -77,6 +77,7 @@ def compute_gt_templates(recording, gt_sorting, ms_before=2.0, ms_after=3.0, ret
         channel_ids=recording.channel_ids,
         unit_ids=gt_sorting.unit_ids,
         probe=recording.get_probe(),
+        is_scaled=return_scaled,
     )
     return gt_templates
 

src/spikeinterface/sortingcomponents/clustering/position_and_features.py

@@ -184,7 +184,12 @@ def main_function(cls, recording, peaks, params):
                 **params["job_kwargs"],
             )
             templates = Templates(
-                templates_array=templates_array, sampling_frequency=fs, nbefore=nbefore, probe=recording.get_probe()
+                templates_array=templates_array,
+                sampling_frequency=fs,
+                nbefore=nbefore,
+                sparsity_mask=None,
+                probe=recording.get_probe(),
+                is_scaled=False,
             )
 
             labels, peak_labels = remove_duplicates_via_matching(

src/spikeinterface/sortingcomponents/tools.py

@@ -137,4 +137,5 @@ def remove_empty_templates(templates):
         channel_ids=templates.channel_ids,
         unit_ids=templates.unit_ids[not_empty],
         probe=templates.probe,
+        is_scaled=templates.is_scaled,
     )