"""mne-data: Funloc data.

See [mne-data](https://github.com/mne-tools/mne-data/releases/tag/funloc-1) for more.
"""

from pathlib import Path

data_root = Path("~/mne_data").expanduser().resolve()
bids_root = data_root / "MNE-funloc-data"
deriv_root = data_root / "derivatives" / "mne-bids-pipeline" / "MNE-funloc-data"
subjects_dir = bids_root / "derivatives" / "freesurfer" / "subjects"
task = "funloc"
ch_types = ["meg", "eeg"]
data_type = "meg"
n_jobs = 2  # sub-01 and sub-02 (sub-emptyroom is not processed)

# filter
l_freq = None
h_freq = 50.0
# maxfilter
use_maxwell_filter: bool = True
crop_runs = (40, 190)
mf_st_duration = 60.0
# SSP
spatial_filter = "ssp"
process_raw_clean = False
ssp_ecg_channel = {"sub-01": "MEG0111", "sub-02": None}
n_proj_eog = dict(n_mag=1, n_grad=1, n_eeg=2)
n_proj_ecg = dict(n_mag=1, n_grad=1, n_eeg=0)


eog_channels = {"default": None, "sub-02": ["EOG061"]}

# Epochs
epochs_tmin = -0.2
epochs_tmax = 0.5
epochs_decim = 5  # 1000 -> 200 Hz
baseline = (None, 0)
conditions = [
    "auditory/standard",
    # "auditory/deviant",
    "visual/standard",
    # "visual/deviant",
]
decoding_time = False
cov_rank = dict(tol_kind="relative", tol=1e-4)

# contrasts
# contrasts = [("auditory", "visual")]

report_image_format = dict(raster="png")

  Platform             Linux-7.0.0-1004-aws-x86_64-with-glibc2.43 (X11)
Python               3.14.4 (main, May 12 2026, 13:57:53) [GCC 15.2.0]
Executable           /home/circleci/python_env/bin/python3
CPU                  AMD EPYC 9R45 (4 cores)
Memory               15.3 GiB

Core
├☑ mne               1.14.0.dev70+g47797972e (development, latest release is 1.13.2)
├☑ numpy             2.5.3 (OpenBLAS 0.3.34.106.0 with 4 threads via pthreads)
├☑ scipy             1.18.1
└☑ matplotlib        3.11.2 (backend=agg)

Numerical (optional)
├☑ scikit-learn      1.9.1
├☑ threadpoolctl     3.7.0
├☑ numba             0.68.0
├☑ nibabel           5.4.2
├☑ pandas            3.0.6
├☑ h5io              0.2.5
├☑ h5py              3.16.0
└☐ unavailable       nilearn, dipy, openmeeg, python-picard, jamica, cupy

Visualization (optional)
├☑ pyvista           0.49.0 (OpenGL 4.5 (Core Profile) Mesa 26.0.8-1ubuntu0.3 via llvmpipe (LLVM 21.1.8, 256 bits))
├☑ pyvistaqt         0.13.1
├☑ vtk               9.7.1
├☑ qtpy              2.4.3 (PySide6=6.11.2)
└☐ unavailable       ipympl, pyqtgraph, mne-qt-browser, ipywidgets, trame, trame_client, trame_server, trame_pyvista, trame_vtk, trame_vuetify

Ecosystem (optional)
├☑ mne-bids          0.21.0.dev2+g6a86b1513
├☑ mne-icalabel      0.9.0
├☑ mne-bids-pipeline 1.11.0.dev81+ge256fa9be
├☑ autoreject        0.6.0.dev1+g704b0c24
├☑ eeglabio          0.1.4
├☑ edfio             0.4.18
├☑ curryreader       0.1.2
├☑ mffpy             0.11.0
├☑ pybv              0.8.1
├☑ defusedxml        0.7.1
└☐ unavailable       mne-nirs, mne-features, mne-connectivity, neo, pymef, antio