audiovisual | |||||||||
---|---|---|---|---|---|---|---|---|---|
trial_type | subject | run | Auditory/Left | Auditory/Right | Button | Smiley | Visual/Left | Visual/Right | |
01 | 01 | 72 | 73 | 16 | 15 | 73 | 71 |
1 rows × 8 columns
"""MNE Sample Data: ICA."""
bids_root = "~/mne_data/ds000248"
deriv_root = "~/mne_data/derivatives/mne-bids-pipeline/ds000248_ica"
ch_types = ["meg"]
data_type = "meg"
subjects = ["01"]
task = "audiovisual"
l_freq = 0.3
h_freq = 40.0
conditions = ["Auditory/Left", "Auditory/Right", "Visual/Left", "Visual/Right"]
epochs_tmin = -0.2
epochs_tmax = 0.5
baseline = (None, 0)
ica_reject = dict(mag=3000e-15, grad=3000e-13)
spatial_filter = "ica"
ica_algorithm = "extended_infomax"
ica_l_freq = 1.0
ica_n_components = 0.8
ica_max_iterations = 500
interactive = False
Platform Linux-5.15.0-1053-aws-x86_64-with-glibc2.35
Python 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0]
Executable /home/circleci/python_env/bin/python3.10
CPU x86_64 (36 cores)
Memory 68.6 GB
Core
├☑ mne 1.7.0.dev156+g415e7f68e (devel, latest release is 1.6.1)
├☑ numpy 1.26.4 (OpenBLAS 0.3.23.dev with 2 threads)
├☑ scipy 1.12.0
└☑ matplotlib 3.8.3 (backend=agg)
Numerical (optional)
├☑ sklearn 1.4.1.post1
├☑ numba 0.59.1
├☑ nibabel 5.2.1
├☑ pandas 2.2.1
└☐ unavailable nilearn, dipy, openmeeg, cupy
Visualization (optional)
├☑ pyvista 0.43.4 (OpenGL 4.5 (Core Profile) Mesa 23.2.1-1ubuntu3.1~22.04.2 via llvmpipe (LLVM 15.0.7, 256 bits))
├☑ pyvistaqt 0.11.0
├☑ vtk 9.3.0
├☑ qtpy 2.4.1 (PyQt6=6.6.0)
└☐ unavailable ipympl, pyqtgraph, mne-qt-browser, ipywidgets, trame_client, trame_server, trame_vtk, trame_vuetify
Ecosystem (optional)
├☑ mne-bids 0.15.0.dev43+g17d20c132
├☑ mne-bids-pipeline 1.8.0
└☐ unavailable mne-nirs, mne-features, mne-connectivity, mne-icalabel, neo