remove to_dict in postprocessing (#1455)

Author: h-mayorquin

spikeinterface/postprocessing/alignsorting.py

@@ -39,7 +39,7 @@ def __init__(self, sorting, unit_peak_shifts):
             self.register_recording(sorting._recording)
 
         self._kwargs = {
-            'sorting': sorting.to_dict(),
+            'sorting': sorting,
             'unit_peak_shifts': unit_peak_shifts
         }
 

spikeinterface/postprocessing/principal_component.py

@@ -333,13 +333,7 @@ def run_for_all_spikes(self, file_path=None, **job_kwargs):
         # and run
         func = _all_pc_extractor_chunk
         init_func = _init_work_all_pc_extractor
-        n_jobs = ensure_n_jobs(recording, job_kwargs.get('n_jobs', None))
-        if n_jobs == 1:
-            init_args = (recording,)
-        else:
-            init_args = (recording.to_dict(),)
-        init_args = init_args + (all_pcs_args, spike_times, spike_labels, we.nbefore, we.nafter, 
-                                 unit_channels, pca_model)
+        init_args = (recording, all_pcs_args, spike_times, spike_labels, we.nbefore, we.nafter, unit_channels, pca_model)
         processor = ChunkRecordingExecutor(recording, func, init_func, init_args, job_name='extract PCs', **job_kwargs)
         processor.run()
 

spikeinterface/postprocessing/spike_amplitudes.py

@@ -68,16 +68,13 @@ def _run(self, **job_kwargs):
         func = _spike_amplitudes_chunk
         init_func = _init_worker_spike_amplitudes
         n_jobs = ensure_n_jobs(recording, job_kwargs.get('n_jobs', None))
-        if n_jobs == 1:
-            init_args = (recording, sorting)
-        else:
+        if n_jobs != 1:
             # TODO: avoid dumping sorting and use spike vector and peak pipeline instead
             assert sorting.check_if_dumpable(), (
                 "The soring object is not dumpable and cannot be processed in parallel. You can use the "
                 "`sorting.save()` function to make it dumpable"
             )
-            init_args = (recording.to_dict(), sorting.to_dict())
-        init_args = init_args + (extremum_channels_index, peak_shifts, return_scaled)
+        init_args = (recording, sorting, extremum_channels_index, peak_shifts, return_scaled)
         processor = ChunkRecordingExecutor(recording, func, init_func, init_args,
                                            handle_returns=True, job_name='extract amplitudes', **job_kwargs)
         out = processor.run()