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SpikeInterface
ValueError: path while running the extractor
I am loading the file from hard disk (drive E) and running the extractor, is there something wrong with my code in assigning the path for the sorter ?
from pathlib import Path
recording_ecog = spre.bandpass_filter(recording_rhs, freq_min=300,
freq_max = 6000 ) #bandpass filter
recording_notch_ecog = spre.notch_filter(recording_ecog,q = 50)
#notch_filter
rec_ecog_ref = spre.common_reference(recording_notch_ecog,
operator="median", reference="global") #rereferencing the data
output_folder = Path(r"C:\Users\garim\mountainsort5_output789")
sorting_rec = ss.run_sorter("mountainsort5", rec_ecog_ref,
output_folder=output_folder)
print("Sorter found", len(sorting_rec.get_unit_ids()), "units")
sorting_rec = sorting_rec.remove_empty_units()
print("Sorter found", len(sorting_rec.get_unit_ids()), "non empty units")
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
Cell In[27], line 6
4 rec_ecog_ref = spre.common_reference(recording_notch_ecog,
operator="median", reference="global") #rereferencing the data
5 output_folder = Path(r"C:\Users\garim\mountainsort5_output789")
----> 6 sorting_rec = ss.run_sorter("mountainsort5", rec_ecog_ref,
output_folder=output_folder)
7 print("Sorter found", len(sorting_rec.get_unit_ids()), "units")
8 sorting_rec = sorting_rec.remove_empty_units()
File
~\.conda\envs\spike\lib\site-packages\spikeinterface\sorters\runsorter.py:147,
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)
140 container_image = singularity_image
141 return run_sorter_container(
142 container_image=container_image,
143 mode=mode,
144 **common_kwargs,
145 )
--> 147 return run_sorter_local(**common_kwargs)
File
~\.conda\envs\spike\lib\site-packages\spikeinterface\sorters\runsorter.py:170,
in run_sorter_local(sorter_name, recording, output_folder,
remove_existing_folder, delete_output_folder, verbose, raise_error,
with_output, **sorter_params)
167 SorterClass = sorter_dict[sorter_name]
169 # only classmethod call not instance (stateless at instance level
but state is in folder)
--> 170 output_folder = SorterClass.initialize_folder(recording,
output_folder, verbose, remove_existing_folder)
171 SorterClass.set_params_to_folder(recording, output_folder,
sorter_params, verbose)
172 SorterClass.setup_recording(recording, output_folder,
verbose=verbose)
File
~\.conda\envs\spike\lib\site-packages\spikeinterface\sorters\basesorter.py:141,
in BaseSorter.initialize_folder(cls, recording, output_folder, verbose,
remove_existing_folder)
139 rec_file = output_folder / "spikeinterface_recording.json"
140 if recording.check_serializablility("json"):
--> 141 recording.dump(rec_file, relative_to=output_folder)
142 elif recording.check_serializablility("pickle"):
143 recording.dump(output_folder /
"spikeinterface_recording.pickle", relative_to=output_folder)
File
~\.conda\envs\spike\lib\site-packages\spikeinterface\core\base.py:569, in
BaseExtractor.dump(self, file_path, relative_to, folder_metadata)
557 """
558 Dumps extractor to json or pickle
559
(...)
566 This means that file and folder paths in extractor objects
kwargs are changed to be relative rather than absolute.
567 """
568 if str(file_path).endswith(".json"):
--> 569 self.dump_to_json(file_path, relative_to=relative_to,
folder_metadata=folder_metadata)
570 elif str(file_path).endswith(".pkl") or
str(file_path).endswith(".pickle"):
571 self.dump_to_pickle(file_path, folder_metadata=folder_metadata)
File
~\.conda\envs\spike\lib\site-packages\spikeinterface\core\base.py:602, in
BaseExtractor.dump_to_json(self, file_path, relative_to, folder_metadata)
599 relative_to = Path(file_path).parent if relative_to is True
else Path(relative_to)
600 relative_to = relative_to.resolve().absolute()
--> 602 dump_dict = self.to_dict(
603 include_annotations=True,
604 include_properties=False,
605 relative_to=relative_to,
606 folder_metadata=folder_metadata,
607 recursive=True,
608 )
609 file_path = self._get_file_path(file_path, [".json"])
611 file_path.write_text(
612 json.dumps(dump_dict, indent=4, cls=SIJsonEncoder),
613 encoding="utf8",
614 )
File
~\.conda\envs\spike\lib\site-packages\spikeinterface\core\base.py:406, in
BaseExtractor.to_dict(self, include_annotations, include_properties,
relative_to, folder_metadata, recursive)
404 relative_to = Path(relative_to).resolve().absolute()
405 assert relative_to.is_dir(), "'relative_to' must be an
existing directory"
--> 406 dump_dict = _make_paths_relative(dump_dict, relative_to)
408 if folder_metadata is not None:
409 if relative_to is not None:
File
~\.conda\envs\spike\lib\site-packages\spikeinterface\core\base.py:983, in
_make_paths_relative(d, relative)
981 relative = str(Path(relative).resolve().absolute())
982 func = lambda p: os.path.relpath(str(p), start=relative)
--> 983 return recursive_path_modifier(d, func, target="path", copy=True)
File
~\.conda\envs\spike\lib\site-packages\spikeinterface\core\core_tools.py:831,
in recursive_path_modifier(d, func, target, copy)
829 if isinstance(v, dict) and is_dict_extractor(v):
830 nested_extractor_dict = v
--> 831 recursive_path_modifier(nested_extractor_dict, func, copy=False)
832 # deal with list of extractor objects (e.g. concatenate_recordings)
833 elif isinstance(v, list):
File
~\.conda\envs\spike\lib\site-packages\spikeinterface\core\core_tools.py:831,
in recursive_path_modifier(d, func, target, copy)
829 if isinstance(v, dict) and is_dict_extractor(v):
830 nested_extractor_dict = v
--> 831 recursive_path_modifier(nested_extractor_dict, func, copy=False)
832 # deal with list of extractor objects (e.g. concatenate_recordings)
833 elif isinstance(v, list):
[... skipping similar frames: recursive_path_modifier at line 831 (1
times)]
File
~\.conda\envs\spike\lib\site-packages\spikeinterface\core\core_tools.py:831,
in recursive_path_modifier(d, func, target, copy)
829 if isinstance(v, dict) and is_dict_extractor(v):
830 nested_extractor_dict = v
--> 831 recursive_path_modifier(nested_extractor_dict, func, copy=False)
832 # deal with list of extractor objects (e.g. concatenate_recordings)
833 elif isinstance(v, list):
File
~\.conda\envs\spike\lib\site-packages\spikeinterface\core\core_tools.py:824,
in recursive_path_modifier(d, func, target, copy)
821 kwargs = dc["kwargs"]
823 # change in place (copy=False)
--> 824 recursive_path_modifier(kwargs, func, copy=False)
826 # find nested and also change inplace (copy=False)
827 nested_extractor_dict = None
File
~\.conda\envs\spike\lib\site-packages\spikeinterface\core\core_tools.py:847,
in recursive_path_modifier(d, func, target, copy)
845 continue
846 if isinstance(v, (str, Path)):
--> 847 dc[k] = func(v)
848 elif isinstance(v, list):
849 dc[k] = [func(e) for e in v]
File
~\.conda\envs\spike\lib\site-packages\spikeinterface\core\base.py:982, in
_make_paths_relative.<locals>.<lambda>(p)
980 def _make_paths_relative(d, relative) -> dict:
981 relative = str(Path(relative).resolve().absolute())
--> 982 func = lambda p: os.path.relpath(str(p), start=relative)
983 return recursive_path_modifier(d, func, target="path", copy=True)
File ~\.conda\envs\spike\lib\ntpath.py:747, in relpath(path, start)
745 path_drive, path_rest = splitdrive(path_abs)
746 if normcase(start_drive) != normcase(path_drive):
--> 747 raise ValueError("path is on mount %r, start on mount %r" % (
748 path_drive, start_drive))
750 start_list = [x for x in start_rest.split(sep) if x]
751 path_list = [x for x in path_rest.split(sep) if x]
ValueError: path is on mount 'E:', start on mount 'C:'
@kshtjkumar, which version are you using. This was an error for Windows computer that was fixed previously. Could you post the exact paths you're using? (Feel free to put ... if there are parts you want to edit for privacy). E.g.
recording = se.read_xx(r'E:\Users\...\experiment1\...\file.xx')
I would update that to at least 0.100.x I believe the Windows fix was around that time. Otherwise you have to sort on the same drive where the data is. So you could test E: -> E:
file2 ="E:\CEAF_PC_BACKUP\monica_EEG_GSstudy\L37_1_19_1_24_240120_102532\L37_1_19_1_24_240120_102532_merged.rhs"
#reader = se.read_intan(file,stream_name ='RHD2000 amplifier channel',use_names_as_ids=True)
reader2 = se.read_intan(file2,stream_name ='RHD2000 amplifier channel',use_names_as_ids=True)
recording_rhs = reader2 #recording file
print(reader2.channel_ids)
recording_rhs.annotate(is_filtered = False)
channel_ids = recording_rhs.get_channel_ids()
fs = recording_rhs.get_sampling_frequency()
num_chan = recording_rhs.get_num_channels()
num_segments = recording_rhs.get_num_segments()
print("Channel_ids = ", channel_ids)
print("Sampling_frequency = ", fs)
print("Number of Channels = ", num_chan)
print("Number of segments = ", num_segments)
print('Total_rec_duration = ', recording_rhs.get_total_duration())
#ecog = ['D-000','D-002', 'D-004', 'D-006']
ecog = ['B-000', 'B-002', 'B-004', 'B-006']#,'D-000','D-002', 'D-004', 'D-006']
recording_rhs = recording_rhs.channel_slice(ecog) #Using only specific channels for recording
I would update that to at least 0.100.x I believe the Windows fix was around that time. Otherwise you have to sort on the same drive where the data is. So you could test E: -> E:
I dont mind updating but then I will have to change a lot of syntax and waveform extraction also for the newer version.
For version 0.100.x you won't have to change anything. syntax changes with version 0.101.0.
file2 ="E:\CEAF_PC_BACKUP\monica_EEG_GSstudy\L37_1_19_1_24_240120_102532\L37_1_19_1_24_240120_102532_merged.rhs" #reader = se.read_intan(file,stream_name ='RHD2000 amplifier channel',use_names_as_ids=True) reader2 = se.read_intan(file2,stream_name ='RHD2000 amplifier channel',use_names_as_ids=True) recording_rhs = reader2 #recording file print(reader2.channel_ids) recording_rhs.annotate(is_filtered = False) channel_ids = recording_rhs.get_channel_ids() fs = recording_rhs.get_sampling_frequency() num_chan = recording_rhs.get_num_channels() num_segments = recording_rhs.get_num_segments() print("Channel_ids = ", channel_ids) print("Sampling_frequency = ", fs) print("Number of Channels = ", num_chan) print("Number of segments = ", num_segments) print('Total_rec_duration = ', recording_rhs.get_total_duration()) #ecog = ['D-000','D-002', 'D-004', 'D-006'] ecog = ['B-000', 'B-002', 'B-004', 'B-006']#,'D-000','D-002', 'D-004', 'D-006'] recording_rhs = recording_rhs.channel_slice(ecog) #Using only specific channels for recording
Hi here is my reader path, can you help with the changes ?
My only recommendation for the path is that you should use a raw string instead. Windows paths can escape so using a raw string will protect you.
file2 =r"E:\CEAF_PC_BACKUP\monica_EEG_GSstudy\L37_1_19_1_24_240120_102532\L37_1_19_1_24_240120_102532_merged.rhs"
notice the r for raw. This prevents any accidental escaping.
Also as an FYI we've updated intan for neo 13.1 so now there is a difference between RHD and RHS amplifier stream. So that code may break with a future version of neo. Just in case you update.
My only recommendation for the path is that you should use a raw string instead. Windows paths can escape so using a raw string will protect you.
file2 =r"E:\CEAF_PC_BACKUP\monica_EEG_GSstudy\L37_1_19_1_24_240120_102532\L37_1_19_1_24_240120_102532_merged.rhs"notice the
rfor raw. This prevents any accidental escaping.
tried this it didnt work, same mounting error.
After updating to spikeinterface 0.100.x?
updated to 0.100.1, here is the error:
Exception in thread Thread-5:
Traceback (most recent call last):
File "C:\Users\garim\.conda\envs\spike\lib\threading.py", line 1016, in
_bootstrap_inner
self.run()
File
"C:\Users\garim\.conda\envs\spike\lib\concurrent\futures\process.py",
line 323, in run
self.terminate_broken(cause)
File
"C:\Users\garim\.conda\envs\spike\lib\concurrent\futures\process.py",
line 463, in terminate_broken
work_item.future.set_exception(bpe)
File "C:\Users\garim\.conda\envs\spike\lib\concurrent\futures\_base.py",
line 561, in set_exception
raise InvalidStateError('{}: {!r}'.format(self._state, self))
concurrent.futures._base.InvalidStateError: CANCELLED: <Future at
0x292d9d21f90 state=cancelled>
---------------------------------------------------------------------------
SpikeSortingError Traceback (most recent call last)
Cell In[4], line 6
4 rec_ecog_ref = spre.common_reference(recording_notch_ecog,
operator="median", reference="global") #rereferencing the data
5 output_folder = Path(r"C:\Users\garim\mountainsort5_output78558599")
----> 6 sorting_rec = ss.run_sorter("mountainsort5", rec_ecog_ref,
output_folder=output_folder)
7 print("Sorter found", len(sorting_rec.get_unit_ids()), "units")
8 sorting_rec = sorting_rec.remove_empty_units()
File
~\.conda\envs\spike\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
~\.conda\envs\spike\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
~\.conda\envs\spike\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\garim\.conda\envs\spike\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\garim\.conda\envs\spike\lib\site-packages\spikeinterface\sorters\external\mountainsort5.py",
line 191, in _run_from_folder
recording_cached = create_cached_recording(
File
"C:\Users\garim\.conda\envs\spike\lib\site-packages\mountainsort5\util\create_cached_recording.py",
line 18, in create_cached_recording
si.BinaryRecordingExtractor.write_recording(
File
"C:\Users\garim\.conda\envs\spike\lib\site-packages\spikeinterface\core\binaryrecordingextractor.py",
line 148, in write_recording
write_binary_recording(recording, file_paths=file_paths, dtype=dtype,
**job_kwargs)
File
"C:\Users\garim\.conda\envs\spike\lib\site-packages\spikeinterface\core\recording_tools.py",
line 137, in write_binary_recording
executor.run()
File
"C:\Users\garim\.conda\envs\spike\lib\site-packages\spikeinterface\core\job_tools.py",
line 401, in run
for res in results:
File
"C:\Users\garim\.conda\envs\spike\lib\site-packages\tqdm\notebook.py",
line 250, in __iter__
for obj in it:
File "C:\Users\garim\.conda\envs\spike\lib\site-packages\tqdm\std.py",
line 1181, in __iter__
for obj in iterable:
File
"C:\Users\garim\.conda\envs\spike\lib\concurrent\futures\process.py",
line 575, in _chain_from_iterable_of_lists
for element in iterable:
File "C:\Users\garim\.conda\envs\spike\lib\concurrent\futures\_base.py",
line 621, in result_iterator
yield _result_or_cancel(fs.pop())
File "C:\Users\garim\.conda\envs\spike\lib\concurrent\futures\_base.py",
line 319, in _result_or_cancel
return fut.result(timeout)
File "C:\Users\garim\.conda\envs\spike\lib\concurrent\futures\_base.py",
line 458, in result
return self.__get_result()
File "C:\Users\garim\.conda\envs\spike\lib\concurrent\futures\_base.py",
line 403, in __get_result
raise self._exception
concurrent.futures.process.BrokenProcessPool: A process in the process
pool was terminated abruptly while the future was running or pending.
Spike sorting failed. You can inspect the runtime trace in
C:\Users\garim\mountainsort5_output78558599/spikeinterface_log.json.
We fixed the drive error! So that's one down. So this is a multiprocessing error.
What did you set n_jobs to?
And did you download the most recent 0.100.6 for example?
If you haven't messed with it then it should default to 1 except in run_sorter where it defaults to all cores which could be a problem. Try 0.100.6 and if it doesn't work then we may need to strategize a little bit. Windows are always a bit tricky to get working for these things, but we will do our best to figure this out!
this is after 0.100.6
Exception in thread Thread-7:
Traceback (most recent call last):
File "C:\Users\garim\.conda\envs\spike\lib\threading.py", line 1016, in
_bootstrap_inner
self.run()
File
"C:\Users\garim\.conda\envs\spike\lib\concurrent\futures\process.py",
line 323, in run
self.terminate_broken(cause)
File
"C:\Users\garim\.conda\envs\spike\lib\concurrent\futures\process.py",
line 463, in terminate_broken
work_item.future.set_exception(bpe)
File "C:\Users\garim\.conda\envs\spike\lib\concurrent\futures\_base.py",
line 561, in set_exception
raise InvalidStateError('{}: {!r}'.format(self._state, self))
concurrent.futures._base.InvalidStateError: CANCELLED: <Future at
0x292dc8e4580 state=cancelled>
---------------------------------------------------------------------------
SpikeSortingError Traceback (most recent call last)
Cell In[9], line 6
4 rec_ecog_ref = spre.common_reference(recording_notch_ecog,
operator="median", reference="global") #rereferencing the data
5 output_folder = Path(r"C:\Users\garim\mountainsort5_output785585959")
----> 6 sorting_rec = ss.run_sorter("mountainsort5", rec_ecog_ref,
output_folder=output_folder)
7 print("Sorter found", len(sorting_rec.get_unit_ids()), "units")
8 sorting_rec = sorting_rec.remove_empty_units()
File
~\.conda\envs\spike\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
~\.conda\envs\spike\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
~\.conda\envs\spike\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\garim\.conda\envs\spike\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\garim\.conda\envs\spike\lib\site-packages\spikeinterface\sorters\external\mountainsort5.py",
line 191, in _run_from_folder
recording_cached = recording
File
"C:\Users\garim\.conda\envs\spike\lib\site-packages\mountainsort5\util\create_cached_recording.py",
line 18, in create_cached_recording
si.BinaryRecordingExtractor.write_recording(
File
"C:\Users\garim\.conda\envs\spike\lib\site-packages\spikeinterface\core\binaryrecordingextractor.py",
line 148, in write_recording
write_binary_recording(recording, file_paths=file_paths, dtype=dtype,
**job_kwargs)
File
"C:\Users\garim\.conda\envs\spike\lib\site-packages\spikeinterface\core\recording_tools.py",
line 137, in write_binary_recording
executor.run()
File
"C:\Users\garim\.conda\envs\spike\lib\site-packages\spikeinterface\core\job_tools.py",
line 401, in run
for res in results:
File
"C:\Users\garim\.conda\envs\spike\lib\site-packages\tqdm\notebook.py",
line 250, in __iter__
for obj in it:
File "C:\Users\garim\.conda\envs\spike\lib\site-packages\tqdm\std.py",
line 1181, in __iter__
for obj in iterable:
File
"C:\Users\garim\.conda\envs\spike\lib\concurrent\futures\process.py",
line 575, in _chain_from_iterable_of_lists
for element in iterable:
File "C:\Users\garim\.conda\envs\spike\lib\concurrent\futures\_base.py",
line 621, in result_iterator
yield _result_or_cancel(fs.pop())
File "C:\Users\garim\.conda\envs\spike\lib\concurrent\futures\_base.py",
line 319, in _result_or_cancel
return fut.result(timeout)
File "C:\Users\garim\.conda\envs\spike\lib\concurrent\futures\_base.py",
line 458, in result
return self.__get_result()
File "C:\Users\garim\.conda\envs\spike\lib\concurrent\futures\_base.py",
line 403, in __get_result
raise self._exception
concurrent.futures.process.BrokenProcessPool: A process in the process
pool was terminated abruptly while the future was running or pending.
Spike sorting failed. You can inspect the runtime trace in
C:\Users\garim\mountainsort5_output785585959/spikeinterface_log.json.
Does anything appear in your terminal? When mountsort5 runs it usually starts printing stuff. Do you get to that point or does it break earlier?
Does anything appear in your terminal? When mountsort5 runs it usually starts printing stuff. Do you get to that point or does it break earlier?
Okay cool, it is failing at the write_binary. Could you try:
ss.run_sorter("mountainsort5", rec_ecog_ref, output_folder=output_folder, n_jobs=1)
And see what it does?
This might be pretty slow but it will help us diagnose things!
Cool. Okay so the problem is in the multiprocessing. Could you try setting n_jobs=2 or n_jobs=3. We need to check if the problem is that you were defaulting to too many jobs or if all multiprocessing is broken in your setup.
so basically last time also when i tried the n_jobs argument it gave this error, previous run was executed without mentioning the n_jobs, so by default it took that as 1. here is the error:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
Cell In[22], line 7
4 rec_ecog_ref = spre.common_reference(recording_notch_ecog,
operator="median", reference="global") #rereferencing the data
6 output_folder =
Path(r"C:\Users\garim\mountainsort5_output78558588877559")
----> 7 sorting_rec = ss.run_sorter("mountainsort5", rec_ecog_ref,
output_folder=output_folder, n_jobs = 2)
8 print("Sorter found", len(sorting_rec.get_unit_ids()), "units")
9 sorting_rec = sorting_rec.remove_empty_units()
File
~\.conda\envs\spike\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
~\.conda\envs\spike\lib\site-packages\spikeinterface\sorters\runsorter.py:223,
in run_sorter_local(sorter_name, recording, output_folder,
remove_existing_folder, delete_output_folder, verbose, raise_error,
with_output, **sorter_params)
221 # only classmethod call not instance (stateless at instance level
but state is in folder)
222 output_folder = SorterClass.initialize_folder(recording,
output_folder, verbose, remove_existing_folder)
--> 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)
File
~\.conda\envs\spike\lib\site-packages\spikeinterface\sorters\basesorter.py:180,
in BaseSorter.set_params_to_folder(cls, recording, output_folder,
new_params, verbose)
178 bad_params.append(p)
179 if len(bad_params) > 0:
--> 180 raise AttributeError("Bad parameters: " + str(bad_params))
182 params.update(new_params)
184 # custom check params
AttributeError: Bad parameters: ['n_jobs']
I mean from when it failed due to the broken process and it actually working. It just randomly worked or you made a specific change?
no after updating to 0.100.6 , i ran this command :
ss.run_sorter("mountainsort5", rec_ecog_ref, output_folder=output_folder, n_jobs=1)
but it gave the error :
AttributeError: Bad parameters: ['n_jobs']
So i ran this command:
ss.run_sorter("mountainsort5", rec_ecog_ref, output_folder=output_folder)
this is the one which is very slow.
If you type
si.get_global_job_kwargs
What does it say? Because it was saying that it wasn't letting you change the n_jobs in the run_sorter function. Could you try
ss.run_sorter("mountainsort5", rec_ecog_ref, output_folder=output_folder, verbose=True)
If you type
si.get_global_job_kwargsWhat does it say? Because it was saying that it wasn't letting you change the
n_jobsin therun_sorterfunction. Could you tryss.run_sorter("mountainsort5", rec_ecog_ref, output_folder=output_folder, verbose=True)
si.get_global_job_kwargs()
{'n_jobs': 1,
'chunk_duration': '1s',
'progress_bar': True,
'mp_context': None,
'max_threads_per_process': 1}
si.get_global_job_kwargs
<function spikeinterface.core.globals.get_global_job_kwargs()>
Sorry that was my typo you were right to type: si.get_global_job_kwargs()
I'm still trying to figure out what if causing the multiprocessing to fail sometimes.