"""tDCS EEG."""

import numpy as np
import pandas as pd

bids_root = "~/mne_data/ds001810"
deriv_root = "~/mne_data/derivatives/mne-bids-pipeline/ds001810"

task = "attentionalblink"
interactive = False
ch_types = ["eeg"]
eeg_template_montage = "biosemi64"
reject = dict(eeg=100e-6)
baseline = (None, 0)
conditions = ["61450", "61511"]
contrasts = [("61450", "61511")]
decode = True
decoding_n_splits = 3  # only for testing, use 5 otherwise

l_freq = 0.3

subjects = ["01"]
sessions = "all"

interpolate_bads_grand_average = False
n_jobs = 4

epochs_custom_metadata = {
    "ses-anodalpost": pd.DataFrame({"ones": np.ones(253)}),
    "ses-anodalpre": pd.DataFrame({"ones": np.ones(268)}),
    "ses-anodaltDCS": pd.DataFrame({"ones": np.ones(269)}),
    "ses-cathodalpost": pd.DataFrame({"ones": np.ones(290)}),
    "ses-cathodalpre": pd.DataFrame({"ones": np.ones(267)}),
    "ses-cathodaltDCS": pd.DataFrame({"ones": np.ones(297)}),
}  # number of rows are hand-set

  Platform             Linux-6.8.0-1029-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               8.0 GiB

Core
├☑ mne               1.10.0.dev126+ged69487d6 (devel, latest release is 1.9.0)
├☑ numpy             2.2.6 (OpenBLAS 0.3.29 with 1 thread)
├☑ scipy             1.15.3
└☑ matplotlib        3.10.3 (backend=agg)

Numerical (optional)
├☑ sklearn           1.7.0
├☑ numba             0.61.2
├☑ nibabel           5.3.2
├☑ pandas            2.3.0
├☑ h5io              0.2.5
├☑ h5py              3.14.0
└☐ unavailable       nilearn, dipy, openmeeg, cupy

Visualization (optional)
├☑ pyvista           0.45.2 (OpenGL 4.5 (Core Profile) Mesa 23.2.1-1ubuntu3.1~22.04.3 via llvmpipe (LLVM 15.0.7, 256 bits))
├☑ pyvistaqt         0.11.2
├☑ vtk               9.4.2
├☑ qtpy              2.4.3 (PyQt6=6.9.0)
└☐ unavailable       ipympl, pyqtgraph, mne-qt-browser, ipywidgets, trame_client, trame_server, trame_vtk, trame_vuetify

Ecosystem (optional)
├☑ mne-bids          0.17.0.dev53+ga619cb7
├☑ mne-bids-pipeline 1.10.0.dev86+gd81dc4b
├☑ eeglabio          0.1.0
├☑ edfio             0.4.9
├☑ pybv              0.7.6
└☐ unavailable       mne-nirs, mne-features, mne-connectivity, mne-icalabel, neo, mffpy