Visualization modifications

src/spikeinterface_pipelines/pipeline.py

@@ -138,6 +138,19 @@ def run_pipeline(
                 )
             else:
                 logger.info("Skipping curation")
+
+            # Visualization
+            visualization_output = None
+            if run_visualization:
+                logger.info("Visualizing results")
+                visualization_output = visualize(
+                    recording=recording_preprocessed,
+                    sorting_curated=sorting_curated,
+                    waveform_extractor=waveform_extractor,
+                    visualization_params=visualization_params,
+                    scratch_folder=scratch_folder,
+                    results_folder=results_folder_visualization,
+                )
         else:
             logger.info("Skipping postprocessing")
             waveform_extractor = None
@@ -148,17 +161,4 @@ def run_pipeline(
         waveform_extractor = None
         sorting_curated = None
 
-    # Visualization
-    visualization_output = None
-    if run_visualization:
-        logger.info("Visualizing results")
-        visualization_output = visualize(
-            recording=recording_preprocessed,
-            sorting_curated=sorting_curated,
-            waveform_extractor=waveform_extractor,
-            visualization_params=visualization_params,
-            scratch_folder=scratch_folder,
-            results_folder=results_folder_visualization,
-        )
-
     return (recording_preprocessed, sorting, waveform_extractor, sorting_curated, visualization_output)

src/spikeinterface_pipelines/postprocessing/postprocessing.py

@@ -47,7 +47,12 @@ def postprocess(
     # first extract some raw waveforms in memory to deduplicate based on peak alignment
     wf_dedup_folder = tmp_folder / "waveforms_dense"
     waveform_extractor_raw = si.extract_waveforms(
-        recording, sorting, folder=wf_dedup_folder, sparse=False, **postprocessing_params.waveforms_raw.model_dump()
+        recording,
+        sorting,
+        folder=wf_dedup_folder,
+        sparse=False,
+        overwrite=True,
+        **postprocessing_params.waveforms_raw.model_dump()
     )
 
     # de-duplication
@@ -66,7 +71,10 @@ def postprocess(
 
     # this is a trick to make the postprocessed folder "self-contained
     sorting_folder = results_folder / "sorting"
-    sorting_deduplicated = sorting_deduplicated.save(folder=sorting_folder)
+    sorting_deduplicated = sorting_deduplicated.save(
+        folder=sorting_folder,
+        overwrite=True,
+    )
 
     # now extract waveforms on de-duplicated units
     logger.info("[Postprocessing] \tSaving sparse de-duplicated waveform extractor folder")

src/spikeinterface_pipelines/visualization/params.py

@@ -1,9 +1,6 @@
-from cProfile import label
 from pydantic import BaseModel, Field
 from typing import Literal, Union
 
-from spikeinterface.widgets import sorting_summary
-
 
 class TracesParams(BaseModel):
     """

src/spikeinterface_pipelines/visualization/visualization.py

@@ -61,7 +61,7 @@ def visualize(
         logger.info(
             "[Visualization] \tKachery client not found. Use `kachery-cloud-init` to initialize kachery client."
         )
-        return
+        # return
     visualization_params_dict = visualization_params.model_dump()
     recording_params = visualization_params_dict["recording"]
 
@@ -80,6 +80,7 @@ def visualize(
             peak_locations = waveform_extractor.load_extension("spike_locations").get_data()
             peak_amps = np.concatenate(waveform_extractor.load_extension("spike_amplitudes").get_data())
             spike_locations_available = True
+
     # otherwise detect peaks
     if not spike_locations_available:
         from spikeinterface.core.node_pipeline import ExtractDenseWaveforms, run_node_pipeline
@@ -207,7 +208,7 @@ def visualize(
         for prop in unit_table_properties:
             if prop not in waveform_extractor.sorting.get_property_keys():
                 logger.info(
-                    f"[Visualization] \tProperty {prop} not found in sorting object. " "Not adding to unit table"
+                    f"[Visualization] \tProperty {prop} not found in sorting object. Not adding to unit table"
                 )
                 unit_table_properties.remove(prop)
         v_sorting = sw.plot_sorting_summary(
@@ -225,7 +226,7 @@ def visualize(
             print(f"\n{url}\n")
             visualization_output["sorting_summary"] = url
         except Exception as e:
-            logger.info("[Visualization] \tSortingview visualization failed with error:\n{e}")
+            logger.info(f"[Visualization] \tSortingview visualization failed with error:\n{e}")
     else:
         logger.info("[Visualization] \tNo units to visualize")