error with running KS4 from spikeinterface

Hi, can you please tell me what is going wrong here?
Trying to call KS4 from spikeinterface, I get the error "slice indices must be integers or None or have an index method".
Please see code and full error report below.

Using:
NPX2.0 (two shanks)
spikeinterface 0.100.6
kilosort 4.0.7

Thanks a lot,
Paola

recording_raw = se.read_openephys(folder_path=path, stream_id="{}".format(index), load_sync_channel=False) 
fs = recording_raw.get_sampling_frequency()

# preprocessing steps
recording = st.correct_lsb(recording_raw, verbose=1);
recording = st.bandpass_filter(recording, freq_min=300, freq_max=6000)
recording = st.phase_shift(recording) 
[bad_channel_ids, channel_labels] = st.detect_bad_channels(recording=recording)  
recording = recording.remove_channels(remove_channel_ids=bad_channel_ids)  

grouped_recordings = recording.split_by(property='group')
recgrouplist_hpsf = [st.highpass_spatial_filter(recording=grouped_recordings[k]) for k in grouped_recordings.keys()]  
recording_hpsf = si.aggregate_channels(recgrouplist_hpsf)
print(recording_hpsf)

print("Starting KS4")
t_start = time.perf_counter()
sorting_ks4_prop = ss.run_sorter_by_property("kilosort4", recording=recording_hpsf, grouping_property="group", working_folder=ks_folder, verbose=True)
t_stop = time.perf_counter()
elapsed_prop = np.round(t_stop - t_start, 2)
print(f"Elapsed time by property: {elapsed_prop} s")

Error running kilosort4

SpikeSortingError Traceback (most recent call last)
Cell In[37], line 117
115 print("Starting KS4")
116 t_start = time.perf_counter()
--> 117 sorting_ks4_prop = ss.run_sorter_by_property("kilosort4", recording=recording_hpsf, grouping_property="group", working_folder=ks_folder, verbose=True)
118 t_stop = time.perf_counter()
119 elapsed_prop = np.round(t_stop - t_start, 2)

File ~\miniconda3\envs\ephys-env\lib\site-packages\spikeinterface\sorters\launcher.py:297, in run_sorter_by_property(sorter_name, recording, grouping_property, working_folder, mode_if_folder_exists, engine, engine_kwargs, verbose, docker_image, singularity_image, **sorter_params)
286 job = dict(
287 sorter_name=sorter_name,
288 recording=rec,
(...)
293 **sorter_params,
294 )
295 job_list.append(job)
--> 297 sorting_list = run_sorter_jobs(job_list, engine=engine, engine_kwargs=engine_kwargs, return_output=True)
299 unit_groups = []
300 for sorting, group in zip(sorting_list, recording_dict.keys()):

File ~\miniconda3\envs\ephys-env\lib\site-packages\spikeinterface\sorters\launcher.py:106, in run_sorter_jobs(job_list, engine, engine_kwargs, return_output)
103 if engine == "loop":
104 # simple loop in main process
105 for kwargs in job_list:
--> 106 sorting = run_sorter(**kwargs)
107 if return_output:
108 out.append(sorting)

File ~\miniconda3\envs\ephys-env\lib\site-packages\spikeinterface\sorters\runsorter.py:175, in run_sorter(sorter_name, recording, output_folder, remove_existing_folder, delete_output_folder, verbose, raise_error, docker_image, singularity_image, delete_container_files, with_output, **sorter_params)
168 container_image = singularity_image
169 return run_sorter_container(
170 container_image=container_image,
171 mode=mode,
172 **common_kwargs,
173 )
--> 175 return run_sorter_local(**common_kwargs)

File ~\miniconda3\envs\ephys-env\lib\site-packages\spikeinterface\sorters\runsorter.py:225, in run_sorter_local(sorter_name, recording, output_folder, remove_existing_folder, delete_output_folder, verbose, raise_error, with_output, **sorter_params)
223 SorterClass.set_params_to_folder(recording, output_folder, sorter_params, verbose)
224 SorterClass.setup_recording(recording, output_folder, verbose=verbose)
--> 225 SorterClass.run_from_folder(output_folder, raise_error, verbose)
226 if with_output:
227 sorting = SorterClass.get_result_from_folder(output_folder, register_recording=True, sorting_info=True)

File ~\miniconda3\envs\ephys-env\lib\site-packages\spikeinterface\sorters\basesorter.py:293, in BaseSorter.run_from_folder(cls, output_folder, raise_error, verbose)
290 print(f"{sorter_name} run time {run_time:0.2f}s")
292 if has_error and raise_error:
--> 293 raise SpikeSortingError(
294 f"Spike sorting error trace:\n{log['error_trace']}\n"
295 f"Spike sorting failed. You can inspect the runtime trace in {output_folder}/spikeinterface_log.json."
296 )
298 return run_time

SpikeSortingError: Spike sorting error trace:
Traceback (most recent call last):
File "C:\Users\SNeurobiology\miniconda3\envs\ephys-env\lib\site-packages\spikeinterface\sorters\basesorter.py", line 258, in run_from_folder
SorterClass._run_from_folder(sorter_output_folder, sorter_params, verbose)
File "C:\Users\SNeurobiology\miniconda3\envs\ephys-env\lib\site-packages\spikeinterface\sorters\external\kilosort4.py", line 201, in _run_from_folder
ops = compute_preprocessing(ops, device, tic0=tic0, file_object=file_object)
File "C:\Users\SNeurobiology\miniconda3\envs\ephys-env\lib\site-packages\kilosort\run_kilosort.py", line 295, in compute_preprocessing
whiten_mat = preprocessing.get_whitening_matrix(bfile, xc, yc, nskip=nskip,
File "C:\Users\SNeurobiology\miniconda3\envs\ephys-env\lib\site-packages\kilosort\preprocessing.py", line 103, in get_whitening_matrix
X = f.padded_batch_to_torch(j)
File "C:\Users\SNeurobiology\miniconda3\envs\ephys-env\lib\site-packages\kilosort\io.py", line 716, in padded_batch_to_torch
X = super().padded_batch_to_torch(ibatch)
File "C:\Users\SNeurobiology\miniconda3\envs\ephys-env\lib\site-packages\kilosort\io.py", line 518, in padded_batch_to_torch
data = self.file[bstart : bend]
File "C:\Users\SNeurobiology\miniconda3\envs\ephys-env\lib\site-packages\kilosort\io.py", line 949, in getitem
samples = self.recording.get_traces(start_frame=i, end_frame=j,
File "C:\Users\SNeurobiology\miniconda3\envs\ephys-env\lib\site-packages\spikeinterface\core\baserecording.py", line 288, in get_traces
traces = rs.get_traces(start_frame=start_frame, end_frame=end_frame, channel_indices=channel_indices)
File "C:\Users\SNeurobiology\miniconda3\envs\ephys-env\lib\site-packages\spikeinterface\core\channelslice.py", line 98, in get_traces
traces = self._parent_recording_segment.get_traces(start_frame, end_frame, parent_indices)
File "C:\Users\SNeurobiology\miniconda3\envs\ephys-env\lib\site-packages\spikeinterface\core\channelsaggregationrecording.py", line 144, in get_traces
traces_recording = segment.get_traces(
File "C:\Users\SNeurobiology\miniconda3\envs\ephys-env\lib\site-packages\spikeinterface\preprocessing\highpass_spatial_filter.py", line 189, in get_traces
traces, left_margin, right_margin = get_chunk_with_margin(
File "C:\Users\SNeurobiology\miniconda3\envs\ephys-env\lib\site-packages\spikeinterface\core\recording_tools.py", line 721, in get_chunk_with_margin
traces_chunk = rec_segment.get_traces(
File "C:\Users\SNeurobiology\miniconda3\envs\ephys-env\lib\site-packages\spikeinterface\core\channelslice.py", line 98, in get_traces
traces = self._parent_recording_segment.get_traces(start_frame, end_frame, parent_indices)
File "C:\Users\SNeurobiology\miniconda3\envs\ephys-env\lib\site-packages\spikeinterface\core\channelslice.py", line 98, in get_traces
traces = self._parent_recording_segment.get_traces(start_frame, end_frame, parent_indices)
File "C:\Users\SNeurobiology\miniconda3\envs\ephys-env\lib\site-packages\spikeinterface\preprocessing\phase_shift.py", line 92, in get_traces
traces_chunk, left_margin, right_margin = get_chunk_with_margin(
File "C:\Users\SNeurobiology\miniconda3\envs\ephys-env\lib\site-packages\spikeinterface\core\recording_tools.py", line 751, in get_chunk_with_margin
traces_chunk = rec_segment.get_traces(start_frame2, end_frame2, channel_indices)
File "C:\Users\SNeurobiology\miniconda3\envs\ephys-env\lib\site-packages\spikeinterface\preprocessing\filter.py", line 132, in get_traces
traces_chunk, left_margin, right_margin = get_chunk_with_margin(
File "C:\Users\SNeurobiology\miniconda3\envs\ephys-env\lib\site-packages\spikeinterface\core\recording_tools.py", line 721, in get_chunk_with_margin
traces_chunk = rec_segment.get_traces(
File "C:\Users\SNeurobiology\miniconda3\envs\ephys-env\lib\site-packages\spikeinterface\preprocessing\normalize_scale.py", line 27, in get_traces
scaled_traces = self.parent_recording_segment.get_traces(start_frame, end_frame, channel_indices).astype(
File "C:\Users\SNeurobiology\miniconda3\envs\ephys-env\lib\site-packages\spikeinterface\preprocessing\normalize_scale.py", line 27, in get_traces
scaled_traces = self.parent_recording_segment.get_traces(start_frame, end_frame, channel_indices).astype(
File "C:\Users\SNeurobiology\miniconda3\envs\ephys-env\lib\site-packages\spikeinterface\extractors\neoextractors\neobaseextractor.py", line 326, in get_traces
raw_traces = self.neo_reader.get_analogsignal_chunk(
File "C:\Users\SNeurobiology\miniconda3\envs\ephys-env\lib\site-packages\neo\rawio\baserawio.py", line 805, in get_analogsignal_chunk
raw_chunk = self._get_analogsignal_chunk(block_index, seg_index, i_start, i_stop, stream_index, channel_indexes)
File "C:\Users\SNeurobiology\miniconda3\envs\ephys-env\lib\site-packages\neo\rawio\openephysbinaryrawio.py", line 385, in _get_analogsignal_chunk
sigs = sigs[i_start:i_stop, :]
File "C:\Users\SNeurobiology\miniconda3\envs\ephys-env\lib\site-packages\numpy\core\memmap.py", line 335, in getitem
res = super().getitem(index)
TypeError: slice indices must be integers or None or have an index method

Spike sorting failed. You can inspect the runtime trace in E:\paola_temp\E1_M15\NPXData\2024-04-12_17-49-04\Record Node 101\experiment1\recording1\SpikeData_ProbeA\0/spikeinterface_log.json.

Start by reproducing the reported run_sorter_by_property call with spikeinterface 0.100.6 and kilosort 4.0.7, then trace the failure from kilosort/io.py through spikeinterface/core/channelsaggregationrecording.py to neo/rawio/openephysbinaryrawio.py. Done means the supplied Open Ephys pipeline no longer raises the slice-index TypeError and the failing path has regression coverage.