roychowdhuryresearch / pyHFO

STE/MNI HFO detection, classification and visualization
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Difficulty in working on MNI in SEEG file #3

Open datsu28 opened 2 months ago

datsu28 commented 2 months ago

Hi, when I run MNI with a default setting in windows ver. pyHFO in my SEEG files, I get the following errors. Do you think anyone could fix this?

Thank you very much for your consideration.

Loading recording: C:/Users/ADaida/Box/ADaida@mednet.ucla.edu/atsuro_spindle/data/Th_proj_Pt1_spindle.edf

100%|##########| 79.0/79.0 [00:04<00:00, 18.8it/s]

100%|##########| 79.0/79.0 [00:30<00:00, 2.55it/s]

100%|##########| 79.0/79.0 [00:04<00:00, 19.3it/s]

Filtering COMPLETE! Detecting HFOs...

Traceback (most recent call last):

File "src\utils\utils_gui.py", line 63, in run result = self.fn(*self.args, **self.kwargs)

File "main.py", line 583, in _detect

File "src\hfo_app.py", line 247, in detect_HFO self.channel_names, self.HFOs = self.detector.detect_multi_channels(self.filter_data, self.channel_names, filtered=True)

File "HFODetector\mni.py", line 119, in detect_multi_channels

File "HFODetector\utils.py", line 31, in parallel_process

File "HFODetector\utils.py", line 31, in

File "HFODetector\mni.py", line 157, in detect

File "HFODetector\mni.py", line 248, in _compute_thrd

ValueError: baseline_window contain only 0 and 1

zyp5511 commented 2 months ago

Please check if this is fixed on the main branch

datsu28 commented 1 month ago

Thanks. But unfortunately, I am still encountering the same issue, even after Gitpulling the latest version.

zyp5511 commented 1 month ago

try pip install --upgrade HFODetector==0.0.22

datsu28 commented 1 month ago

Thanks, MNI detection finally worked.

Unfortunately, after saving to npz, I got two errors.

  1. I could not reload the error due to the following error.

  2. I could not annotate

  3. Error to reload npz Loading from npz... Traceback (most recent call last):

    File "c:\Users\ADaida\Documents\GitHub\pyHFO\src\utils\utils_gui.py", line 63, in run result = self.fn(*self.args, **self.kwargs)

    File "c:\Users\ADaida\Documents\GitHub\pyHFO\main.py", line 716, in _load_from_npz self.hfo_app = self.hfo_app.import_app(fname)

    File "c:\Users\ADaida\Documents\GitHub\pyHFO\src\hfo_app.py", line 435, in import_app app.hfo_features.artifact_predictions = checkpoint["artifact_predictions"].item()

ValueError: can only convert an array of size 1 to a Python scalar

Traceback (most recent call last): File "c:\Users\ADaida\Documents\GitHub\pyHFO\main.py", line 363, in scroll_time_waveform_plot

self.waveform_plot.plot(t_start)

File "c:\Users\ADaida\Documents\GitHub\pyHFO\src\ui\plot_waveform.py", line 180, in plot

eeg_data_todisplay,=self.backend.get_eeg_data(int(t_startself.sample_freq),int(t_endself.sample_freq), self.filtered)

File "c:\Users\ADaida\Documents\GitHub\pyHFO\src\hfo_app.py", line 111, in get_eeg_data

return data[:, start:end], self.channel_names

TypeError : 'NoneType' object is not subscriptable

Loading from npz... Traceback (most recent call last):

File "c:\Users\ADaida\Documents\GitHub\pyHFO\src\utils\utils_gui.py", line 63, in run result = self.fn(*self.args, **self.kwargs)

File "c:\Users\ADaida\Documents\GitHub\pyHFO\main.py", line 716, in _load_from_npz self.hfo_app = self.hfo_app.import_app(fname)

File "c:\Users\ADaida\Documents\GitHub\pyHFO\src\hfo_app.py", line 435, in import_app app.hfo_features.artifact_predictions = checkpoint["artifact_predictions"].item()

ValueError: can only convert an array of size 1 to a Python scalar

  1. error to annotation

initializing HFOAnnotation

Traceback (most recent call last): File "c:\Users\ADaida\Documents\GitHub\pyHFO\main.py", line 840, in open_annotation

annotation = HFOAnnotation(self.hfo_app, self, self.close_signal)

File "c:\Users\ADaida\Documents\GitHub\pyHFO\src\ui\annotation.py", line 73, in init

self.waveform_plot.plot(start, end, channel, interval=1.0) # Default interval

File "c:\Users\ADaida\Documents\GitHub\pyHFO\src\ui\annotation_plot.py", line 91, in plot

unfiltered_eeg_data_to_display_one = unfiltered_eeg_data[self.channel_names == channel_name,:][0]

IndexError : boolean index did not match indexed array along dimension 0; dimension is 81 but corresponding boolean dimension is 76

Thank you very much for your help!