Running into errors while trying to sort tetrode data by group

[nightshade2303]

Hello, we are a new lab and are just starting our first few recordings. I wanted to get used to the spikeinterface environment, and so have been using it to load our data and attempt to sort it. However, I have been facing this issue which I could not really trace back:

recording = se.read_openephys(data_path, stream_name = 'Record Node 101#OE_FPGA_Acquisition_Board-100.Rhythm Data')
events = se.read_openephys_event(data_path)
print(recording)
# select ephys channels only
selection = ['CH'+str(i) for i in np.arange(1,65)]
ephys_recording = recording.select_channels(selection)

# make a channel map 
channelmapoe = [40, 38, 36, 34,
                48, 46, 44, 42,
                56, 54, 52, 50,
                58, 64, 62, 60,
                63, 61, 59, 57,
                55, 53, 51, 49,
                47, 45, 43, 41,
                39, 37, 35, 33,
                25, 27, 29, 31,
                17, 19, 21, 23,
                9, 11, 13, 15,
                1, 3, 5, 7,
                4, 6, 8, 2,
                10, 12, 14, 16,
                18, 20, 22, 24,
                26, 28, 30, 32]

# subtract 1 to fit python indexing
channelmappythonic = np.array(channelmapoe) - 1

# create probegroup and set channel locations for sorting purposes
probegroup = ProbeGroup()
for i in range(16): # we have 16 tetrodes
    tetrode = generate_tetrode()
    tetrode.move([i * 300, 0]) # make lots of space between tetrodes
    probegroup.add_probe(tetrode)

probegroup.set_global_device_channel_indices(channelmappythonic) # tetrodes arranged based on channelmap
ephys_recording = ephys_recording.set_probegroup(probegroup, group_mode='by_probe')

# remove all bad channels
bad_channel_ids = [48, 39, 33, 21, 12, 13, 15, 3, 5, 7]
bad_channel_ids = ['CH'+str(i) for i in bad_channel_ids]
ephys_recording = ephys_recording.remove_channels(remove_channel_ids=bad_channel_ids)
# group-wise preprocessinga

from spikeinterface import aggregate_channels
# bad_channel_ids, info = spre.detect_bad_channels(ephys_recording)
# print(bad_channel_ids, info)
# ephys_recording = ephys_recording.remove_channels(bad_channel_ids)

split_recording_dict = ephys_recording.split_by("group")

preprocessed_recordings = []

# loop over the recordings contained in the dictionary
for chan_group_rec in split_recording_dict.values():

    # Apply the preprocessing steps to the channel group in isolation
    filtered_recording = spre.bandpass_filter(chan_group_rec, freq_min=300, freq_max=6000)

    referenced_recording = spre.common_reference(filtered_recording, operator='median')

    preprocessed_recordings.append(referenced_recording)

 # Combine our preprocessed channel groups back together
combined_preprocessed_recording = aggregate_channels(preprocessed_recordings)

aggregate_sorting = ss.run_sorter_by_property(
    sorter_name = 'tridesclous2',
    recording = combined_preprocessed_recording,
    grouping_property = "group",
    folder = fr'L:\4portProb_ephys\Box1_ephys\Bayleef\sorted\{folder_name}_sorted_by_group_1',
    engine = "joblib",
    verbose = True, 
    engine_kwargs = {"n_jobs": 1}
)

But I keep getting the following error:

---------------------------------------------------------------------------
SpikeSortingError                         Traceback (most recent call last)
Cell In[11], line 26
     23 combined_preprocessed_recording = aggregate_channels(preprocessed_recordings)
     25 # only for si.__version__ == 0.102.0
---> 26 aggregate_sorting = ss.run_sorter_by_property(
     27     sorter_name = 'tridesclous2',
     28     recording = combined_preprocessed_recording,
     29     grouping_property = "group",
     30     folder = fr'L:\4portProb_ephys\Box1_ephys\Bayleef\sorted\{folder_name}_sorted_by_group_1',
     31     engine = "joblib",
     32     verbose = True, 
     33     engine_kwargs = {"n_jobs": 1}
     34 )
     35 # sorting = ss.run_sorter(
     36 #     sorter_name = 'mountainsort5',
     37 #     filter = True,
   (...)     41 #     folder = f'{folder_name}_sorted6'
     42 # )

File c:\Users\dlab\miniforge3\envs\si_env_rolling_new\Lib\site-packages\spikeinterface\sorters\launcher.py:308, in run_sorter_by_property(sorter_name, recording, grouping_property, folder, mode_if_folder_exists, engine, engine_kwargs, verbose, docker_image, singularity_image, working_folder, **sorter_params)
    297     job = dict(
    298         sorter_name=sorter_name,
    299         recording=rec,
   (...)    304         **sorter_params,
    305     )
    306     job_list.append(job)
--> 308 sorting_list = run_sorter_jobs(job_list, engine=engine, engine_kwargs=engine_kwargs, return_output=True)
    310 unit_groups = []
    311 for sorting, group in zip(sorting_list, recording_dict.keys()):

File c:\Users\dlab\miniforge3\envs\si_env_rolling_new\Lib\site-packages\spikeinterface\sorters\launcher.py:115, in run_sorter_jobs(job_list, engine, engine_kwargs, return_output)
    113 n_jobs = engine_kwargs["n_jobs"]
    114 backend = engine_kwargs["backend"]
--> 115 sortings = Parallel(n_jobs=n_jobs, backend=backend)(delayed(run_sorter)(**kwargs) for kwargs in job_list)
    116 if return_output:
    117     out.extend(sortings)

File c:\Users\dlab\miniforge3\envs\si_env_rolling_new\Lib\site-packages\joblib\parallel.py:1918, in Parallel.__call__(self, iterable)
   1916     output = self._get_sequential_output(iterable)
   1917     next(output)
-> 1918     return output if self.return_generator else list(output)
   1920 # Let's create an ID that uniquely identifies the current call. If the
   1921 # call is interrupted early and that the same instance is immediately
   1922 # re-used, this id will be used to prevent workers that were
   1923 # concurrently finalizing a task from the previous call to run the
   1924 # callback.
   1925 with self._lock:

File c:\Users\dlab\miniforge3\envs\si_env_rolling_new\Lib\site-packages\joblib\parallel.py:1847, in Parallel._get_sequential_output(self, iterable)
   1845 self.n_dispatched_batches += 1
   1846 self.n_dispatched_tasks += 1
-> 1847 res = func(*args, **kwargs)
   1848 self.n_completed_tasks += 1
   1849 self.print_progress()

File c:\Users\dlab\miniforge3\envs\si_env_rolling_new\Lib\site-packages\spikeinterface\sorters\runsorter.py:199, in run_sorter(sorter_name, recording, folder, remove_existing_folder, delete_output_folder, verbose, raise_error, docker_image, singularity_image, delete_container_files, with_output, output_folder, **sorter_params)
    188             raise RuntimeError(
    189                 "The python `spython` package must be installed to "
    190                 "run singularity. Install with `pip install spython`"
    191             )
    193     return run_sorter_container(
    194         container_image=container_image,
    195         mode=mode,
    196         **common_kwargs,
    197     )
--> 199 return run_sorter_local(**common_kwargs)

File c:\Users\dlab\miniforge3\envs\si_env_rolling_new\Lib\site-packages\spikeinterface\sorters\runsorter.py:261, in run_sorter_local(sorter_name, recording, folder, remove_existing_folder, delete_output_folder, verbose, raise_error, with_output, output_folder, **sorter_params)
    259 SorterClass.setup_recording(recording, folder, verbose=verbose)
    260 # This NEEDS to happen in the docker because of dependencies
--> 261 SorterClass.run_from_folder(folder, raise_error, verbose)
    262 if with_output:
    263     sorting = SorterClass.get_result_from_folder(folder, register_recording=True, sorting_info=True)

File c:\Users\dlab\miniforge3\envs\si_env_rolling_new\Lib\site-packages\spikeinterface\sorters\basesorter.py:310, in BaseSorter.run_from_folder(cls, output_folder, raise_error, verbose)
    307         print(f"{sorter_name} run time {run_time:0.2f}s")
    309 if has_error and raise_error:
--> 310     raise SpikeSortingError(
    311         f"Spike sorting error trace:\n{error_log_to_display}\n"
    312         f"Spike sorting failed. You can inspect the runtime trace in {output_folder}/spikeinterface_log.json."
    313     )
    315 return run_time

SpikeSortingError: Spike sorting error trace:
Traceback (most recent call last):
  File "c:\Users\dlab\miniforge3\envs\si_env_rolling_new\Lib\site-packages\spikeinterface\sorters\basesorter.py", line 270, in run_from_folder
    SorterClass._run_from_folder(sorter_output_folder, sorter_params, verbose)
  File "c:\Users\dlab\miniforge3\envs\si_env_rolling_new\Lib\site-packages\spikeinterface\sorters\internal\tridesclous2.py", line 107, in _run_from_folder
    recording_raw = cls.load_recording_from_folder(sorter_output_folder.parent, with_warnings=False)
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "c:\Users\dlab\miniforge3\envs\si_env_rolling_new\Lib\site-packages\spikeinterface\sorters\basesorter.py", line 221, in load_recording_from_folder
    recording = load(json_file, base_folder=output_folder)
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "c:\Users\dlab\miniforge3\envs\si_env_rolling_new\Lib\site-packages\spikeinterface\core\loading.py", line 100, in load
    return _load_object_from_dict(d, object_type, base_folder=base_folder)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "c:\Users\dlab\miniforge3\envs\si_env_rolling_new\Lib\site-packages\spikeinterface\core\loading.py", line 175, in _load_object_from_dict
    return BaseExtractor.from_dict(d, base_folder=base_folder)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "c:\Users\dlab\miniforge3\envs\si_env_rolling_new\Lib\site-packages\spikeinterface\core\base.py", line 571, in from_dict
    extractor = _load_extractor_from_dict(dictionary)
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "c:\Users\dlab\miniforge3\envs\si_env_rolling_new\Lib\site-packages\spikeinterface\core\base.py", line 1108, in _load_extractor_from_dict
    new_kwargs[name] = _load_extractor_from_dict(value)
                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "c:\Users\dlab\miniforge3\envs\si_env_rolling_new\Lib\site-packages\spikeinterface\core\base.py", line 1127, in _load_extractor_from_dict
    extractor = extractor_class(**new_kwargs)
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: ChannelsAggregationRecording.__init__() got an unexpected keyword argument 'recording_list'

Spike sorting failed. You can inspect the runtime trace in L:\4portProb_ephys\Box1_ephys\Bayleef\sorted\Bayleef_2025-01-30_11-53-57_010_sorted_by_group_1\0/spikeinterface_log.json.

If anyone can help me out on this I'll be really grateful. Thanks!!

[nightshade2303]

I think (please correct me if I am wrong) that because I am trying to preprocess the recordings by group and then combine them into one, run_sorter_by_property isn't too happy about it

[alejoe91]

Hi @nightshade2303

The error suggests that you're just missing the spython package.
Try to pip install spython and to run it again!

[chrishalcrow]

@alejoe91 I don't think so, the error is a few lines down from that.

This must be related to #3767, where we changed the argument name in ChannelsAggregationRecording from recording_list to recording_list_or_dict. My bad! I'll try and get a fix now.

@nightshade2303 you can either wait for me to get a bug fix, or if you run the release version of spikeinterface, that version should work (that is, use pip install spikeinterface instead of cloning the github repo and installing locally) since this is a very new bug

[nightshade2303]

Hi @alejoe91 and @chrishalcrow, thank you for your quick replies!
About the package installation, I had used full_spikeinterface_environment_rolling_updates.yml for creating my conda environment, so if the package is required and missing, you could add it there.

Until the bug is fixed, here's what I did to temporarily not use aggregate_channels:

... (continued from previous)

split_recording_dict = ephys_recording.split_by("group")

preprocessed_recordings = []

sortings = {}
# loop over the recordings contained in the dictionary
for grouper, chan_group_rec in split_recording_dict.items():

    # Apply the preprocessing steps to the channel group in isolation
    filtered_recording = spre.bandpass_filter(chan_group_rec, freq_min=300, freq_max=6000)

    referenced_recording = spre.common_reference(filtered_recording, operator='median')

    preprocessed_recordings.append(referenced_recording)

    sorting = ss.run_sorter(
        sorter_name='mountainsort5',
        recording=referenced_recording,
        folder=fr'L:\4portProb_ephys\Box1_ephys\Bayleef\sorted\{folder_name}_sorted_by_group\{grouper}',
        filter = False,
        verbose = True,
        detect_threshold = 4
        )

    sortings[grouper] = sorting
    print('Sorting done for group', grouper)

I'll keep this issue open until the fix is up. Thanks!

[chrishalcrow]

Glad you've got something working :) Soon we're going to have a really nice new way to deal with grouped recordings, I'll ping you when it's ready!

I can't reproduce the bug, could you please share which verison of spikeinterface is installed by running pip list in your conda enviroment, or running

import spikeinterface
spikeinterface.__version__

Thanks!

Just to note: tridesclous2 is still in activate development (by the wonderful @samuelgarcia) and hasn't been published yet. So you should consider it "experimental" for now! Mountainsort is a great tried and tested sorter, especially for tetrode data.

[nightshade2303]

Sounds awesome, thanks!

SI version is 0.102.2. (I set up this environment today using conda env create --file full_spikeinterface_environment_rolling_updates.yml)

Yes, I was trying mountainsort5 initially, but then wanted to see if it was a sorter dependent issue so switched to the internal one.

[paolahydra]

Hi @alejoe91 and @chrishalcrow ,
I am having the same issue described here. I am also running spikeinterface 0.102.2.
Should I go around it as @nightshade2303 did?
Sorry if I am a bit lost here, and thank you for any clarification.
Paola

[chrishalcrow]

Hi @paolahydra , this bug should be fixed in the "dev" version of spikeinterface, which you can access by installing spikeinterface from source https://spikeinterface.readthedocs.io/en/stable/get_started/installation.html#from-source
And when 0.102.3 gets released (hopefully soon!), it will be fixed in the "release" version too.
Sorry for the inconvenience!

[unaialduntzin]

Hi @chrishalcrow,

I am having a similar issue described here, but I have updated my spikeinterface version to 0.102.3 and I am still getting a similar error. Is there something I have not done properly? Thanks!

spikeinterface.sorters.utils.misc.SpikeSortingError: Spike sorting in docker failed with the following error:
Traceback (most recent call last):
  File "/Users/abrah/Data/Ephys/Chronic_recordings/sorted/2025-04-04_09-36-47_sorted_by_group/in_container_sorter_script.py", line 13, in <module>
    recording = load(json_rec)
  File "/root/.local/lib/python3.9/site-packages/spikeinterface/core/loading.py", line 100, in load
    return _load_object_from_dict(d, object_type, base_folder=base_folder)
  File "/root/.local/lib/python3.9/site-packages/spikeinterface/core/loading.py", line 175, in _load_object_from_dict
    return BaseExtractor.from_dict(d, base_folder=base_folder)
  File "/root/.local/lib/python3.9/site-packages/spikeinterface/core/base.py", line 571, in from_dict
    extractor = _load_extractor_from_dict(dictionary)
  File "/root/.local/lib/python3.9/site-packages/spikeinterface/core/base.py", line 1108, in _load_extractor_from_dict
    new_kwargs[name] = _load_extractor_from_dict(value)
  File "/root/.local/lib/python3.9/site-packages/spikeinterface/core/base.py", line 1127, in _load_extractor_from_dict
    extractor = extractor_class(**new_kwargs)
TypeError: __init__() got an unexpected keyword argument 'recording_list'`

[chrishalcrow]

Oh no, that doesn't sound good. Could you please post your script from reading in your recording to sorting please? Thanks!

[unaialduntzin]

Oh no, that doesn't sound good. Could you please post your script from reading in your recording to sorting please? Thanks!

Sorry @chrishalcrow, I had installed the latest version of spikeinterface but I forgot to restart the program. No errors now, sorry for the confusion. It's working fine now.

[chrishalcrow]

That's great!!