Closed mtehrani-code closed 4 months ago
The create_sorting_analyzer takes a sorting object first and then a recording, not the other way around!
Okay. When I swap those, this is what I get:
SortingAnalyzer: 49 channels - 120 units - 1 segments - memory - has recording Loaded 0 extensions:
No processing happens...Shouldn't there be an output file like a 'waveforms' folder somewhere?
No, this only creates a sorting analyzer, that can be used to compute extensions. Note that the waveform extraction step has been deprecated
Still working with the Cambridge NeuroTech, November 2023 tutorial.
In the waveform extraction step, I type:
we = si.create_sorting_analyzer(recording_saved, sorting, folder=base_folder / "waveforms_dense", sparse=False, overwrite=True, **job_kwargs) print(we)
And I get this error:
AttributeError Traceback (most recent call last) Cell In[109], line 1 ----> 1 we = si.create_sorting_analyzer(recording_saved, sorting, folder=base_folder / "waveforms_dense", 2 sparse=False, overwrite=True, **job_kwargs) 3 print(we)
File ~\Documents\GitHub\spikeinterface\src\spikeinterface\core\sortinganalyzer.py:121, in create_sorting_analyzer(sorting, recording, format, folder, sparse, sparsity, overwrite, **sparsity_kwargs) 118 else: 119 sparsity = None --> 121 sorting_analyzer = SortingAnalyzer.create(sorting, recording, format=format, folder=folder, sparsity=sparsity) 123 return sorting_analyzer
File ~\Documents\GitHub\spikeinterface\src\spikeinterface\core\sortinganalyzer.py:221, in SortingAnalyzer.create(cls, sorting, recording, format, folder, sparsity) 219 assert sorting.sampling_frequency == recording.sampling_frequency 220 # check that multiple probes are non-overlapping --> 221 all_probes = recording.get_probegroup().probes 222 check_probe_do_not_overlap(all_probes) 224 if format == "memory":
AttributeError: 'KiloSortSortingExtractor' object has no attribute 'get_probegroup'
I'm replacing "extract_waveforms" with "create_sorting_analyzer" as was suggested in the update.
Please help!