sub-0002, ses-01, task-rest

Raw (original), run 01 data-quality raw run-01

Info raw run-01 data-quality

	General
	Filename(s)	sub-0002_ses-01_task-rest_run-01_meg.meg4
	MNE object type	RawCTF
	Measurement date	1910-10-14 at 12:33:00 UTC
	Participant	sub-0002
	Experimenter	mne_anonymize
	Acquisition
	Duration	00:01:40 (HH:MM:SS)
	Sampling frequency	2400.00 Hz
	Time points	240,001
	Channels
	Magnetometers
	EOG
	ECG
	misc
	Reference Magnetometers
	Head & sensor digitization	6 points
	Filters
	Highpass	0.00 Hz
	Lowpass	1200.00 Hz

Time series raw run-01 data-quality

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PSD raw run-01 data-quality

Raw (filtered), run 01 filtered raw run-01

Info raw run-01 filtered

	General
	Filename(s)	sub-0002_ses-01_task-rest_run-01_meg.meg4
	MNE object type	RawCTF
	Measurement date	1910-10-14 at 12:33:00 UTC
	Participant	sub-0002
	Experimenter	mne_anonymize
	Acquisition
	Duration	00:01:40 (HH:MM:SS)
	Sampling frequency	2400.00 Hz
	Time points	240,001
	Channels
	Magnetometers
	EOG
	ECG
	misc
	Reference Magnetometers
	Head & sensor digitization	6 points
	Filters
	Highpass	1.00 Hz
	Lowpass	40.00 Hz

Time series raw run-01 filtered

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PSD raw run-01 filtered

SSP: ECG ssp ecg

SSP: EOG ssp eog

Epochs: before cleaning epochs

Info epochs

	General
	MNE object type	Epochs
	Measurement date	1910-10-14 at 12:33:00 UTC
	Participant	sub-0002
	Experimenter	mne_anonymize
	Acquisition
	Total number of events	9
	Events counts	rest: 9
	Time range	0.000 – 0.500 s
	Baseline	off
	Sampling frequency	2400.00 Hz
	Time points	1,201
	Metadata	No metadata set
	Channels
	Magnetometers
	EOG
	ECG
	misc
	Reference Magnetometers
	Head & sensor digitization	6 points
	Filters
	Highpass	1.00 Hz
	Lowpass	40.00 Hz

ERF image (Magnetometers) epochs

Drop log epochs

No epochs exceeded the rejection thresholds. Nothing was dropped.

PSD epochs

Raw (clean), run 01 clean raw run-01

Info raw run-01 clean

	General
	Filename(s)	sub-0002_ses-01_task-rest_run-01_proc-filt_raw.fif
	MNE object type	Raw
	Measurement date	1910-10-14 at 12:33:00 UTC
	Participant	sub-0002
	Experimenter	mne_anonymize
	Acquisition
	Duration	00:01:40 (HH:MM:SS)
	Sampling frequency	2400.00 Hz
	Time points	240,001
	Channels
	Magnetometers
	EOG
	ECG
	misc
	Reference Magnetometers
	Head & sensor digitization	6 points
	Filters
	Highpass	1.00 Hz
	Lowpass	40.00 Hz
	Projections	axial-ECG--0.500-0.500)-PCA-01 (off) axial-EOG--0.500-0.500)-PCA-01 (off)

Time series raw run-01 clean

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PSD raw run-01 clean

Epochs: after cleaning clean epochs

Rejection thresholds epochs clean

{}

Info epochs clean

	General
	Filename(s)	sub-0002_ses-01_task-rest_proc-ssp_epo.fif
	MNE object type	EpochsFIF
	Measurement date	1910-10-14 at 12:33:00 UTC
	Participant	sub-0002
	Experimenter	mne_anonymize
	Acquisition
	Total number of events	9
	Events counts	rest: 9
	Time range	0.000 – 0.500 s
	Baseline	off
	Sampling frequency	2400.00 Hz
	Time points	1,201
	Metadata	No metadata set
	Channels
	Magnetometers
	EOG
	ECG
	misc
	Reference Magnetometers
	Head & sensor digitization	6 points
	Filters
	Highpass	1.00 Hz
	Lowpass	40.00 Hz
	Projections	axial-ECG--0.500-0.500)-PCA-01 (on) axial-EOG--0.500-0.500)-PCA-01 (on)

ERF image (Magnetometers) epochs clean

Drop log epochs clean

No epochs exceeded the rejection thresholds. Nothing was dropped.

PSD epochs clean

TFR Power: rest time-frequency rest

TFR ITC: rest time-frequency rest

Noise covariance covariance

Covariance matrix covariance

Singular values covariance

Configuration file configuration

  """OMEGA Resting State Sample Data."""

import numpy as np

bids_root = "~/mne_data/ds000247"
deriv_root = "~/mne_data/derivatives/mne-bids-pipeline/ds000247"

subjects = ["0002"]
sessions = ["01"]
task = "rest"
task_is_rest = True

crop_runs = (0, 100)  # to speed up computations

ch_types = ["meg"]
spatial_filter = "ssp"

l_freq = 1.0
h_freq = 40.0

rest_epochs_duration = 10
rest_epochs_overlap = 0

epochs_tmin = 0
baseline = None

time_frequency_conditions = ["rest"]
time_frequency_freq_min = 1.0
time_frequency_freq_max = 30.0
time_frequency_cycles = np.arange(time_frequency_freq_min, time_frequency_freq_max) / 4
time_frequency_subtract_evoked = True

System information mne-sysinfo

  Platform             Linux-5.15.0-1057-aws-x86_64-with-glibc2.35
Python               3.12.4 (main, Jun  8 2024, 23:40:19) [GCC 11.4.0]
Executable           /home/circleci/.pyenv/versions/3.12.4/bin/python3.12
CPU                  Intel(R) Xeon(R) Platinum 8124M CPU @ 3.00GHz (36 cores)
Memory               68.6 GiB

Core
├☑ mne               1.9.0.dev59+ged933b8d9 (devel, latest release is 1.8.0)
├☑ numpy             2.0.2 (OpenBLAS 0.3.27 with 2 threads)
├☑ scipy             1.14.1
└☑ matplotlib        3.9.2 (backend=agg)

Numerical (optional)
├☑ sklearn           1.5.2
├☑ numba             0.60.0
├☑ nibabel           5.2.1
├☑ pandas            2.2.3
├☑ h5io              0.2.4
├☑ h5py              3.12.1
└☐ unavailable       nilearn, dipy, openmeeg, cupy

Visualization (optional)
├☑ pyvista           0.44.1 (OpenGL 4.5 (Core Profile) Mesa 23.2.1-1ubuntu3.1~22.04.2 via llvmpipe (LLVM 15.0.7, 256 bits))
├☑ pyvistaqt         0.11.1
├☑ vtk               9.3.1
├☑ qtpy              2.4.1 (PyQt6=6.7.1)
└☐ unavailable       ipympl, pyqtgraph, mne-qt-browser, ipywidgets, trame_client, trame_server, trame_vtk, trame_vuetify

Ecosystem (optional)
├☑ mne-bids          0.16.0.dev44+g65da1ae78
├☑ mne-bids-pipeline 1.10.0.dev27+g02cdc20
├☑ edfio             0.4.4
├☑ pybv              0.7.5
└☐ unavailable       mne-nirs, mne-features, mne-connectivity, mne-icalabel, neo, eeglabio, mffpy

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