matchingpennies | ||||||
---|---|---|---|---|---|---|
trial_type | subject | raised-left/match-false | raised-left/match-true | raised-right/match-false | raised-right/match-true | |
05 | 75 | 104 | 55 | 66 | ||
06 | 79 | 62 | 59 | 100 | ||
07 | 50 | 100 | 49 | 101 | ||
08 | 70 | 55 | 66 | 109 | ||
09 | 62 | 91 | 86 | 61 | ||
10 | 65 | 76 | 52 | 107 | ||
11 | 72 | 82 | 60 | 86 |
7 rows × 5 columns
"""Matchingpennies EEG experiment."""
bids_root = "~/mne_data/eeg_matchingpennies"
deriv_root = "~/mne_data/derivatives/mne-bids-pipeline/eeg_matchingpennies"
subjects = ["05"]
task = "matchingpennies"
ch_types = ["eeg"]
interactive = False
reject = {"eeg": 150e-6}
conditions = ["raised-left", "raised-right"]
contrasts = [("raised-left", "raised-right")]
decode = True
interpolate_bads_grand_average = 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