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# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Denis A. Engemann <denis.engemann@gmail.com>
# Eric Larson <larson.eric.d@gmail.com>
#
# License: BSD-3-Clause
from copy import deepcopy
DEFAULTS = dict(
color=dict(mag='darkblue', grad='b', eeg='k', eog='k', ecg='m', emg='k',
ref_meg='steelblue', misc='k', stim='k', resp='k', chpi='k',
exci='k', ias='k', syst='k', seeg='saddlebrown', dbs='seagreen',
dipole='k', gof='k', bio='k', ecog='k', hbo='#AA3377', hbr='b',
fnirs_cw_amplitude='k', fnirs_fd_ac_amplitude='k',
fnirs_fd_phase='k', fnirs_od='k', csd='k', whitened='k',
gsr='#666633', temperature='#663333'),
si_units=dict(mag='T', grad='T/m', eeg='V', eog='V', ecg='V', emg='V',
misc='AU', seeg='V', dbs='V', dipole='Am', gof='GOF',
bio='V', ecog='V', hbo='M', hbr='M', ref_meg='T',
fnirs_cw_amplitude='V', fnirs_fd_ac_amplitude='V',
fnirs_fd_phase='rad', fnirs_od='V', csd='V/m²',
whitened='Z', gsr='S', temperature='C'),
units=dict(mag='fT', grad='fT/cm', eeg='µV', eog='µV', ecg='µV', emg='µV',
misc='AU', seeg='mV', dbs='µV', dipole='nAm', gof='GOF',
bio='µV', ecog='µV', hbo='µM', hbr='µM', ref_meg='fT',
fnirs_cw_amplitude='V', fnirs_fd_ac_amplitude='V',
fnirs_fd_phase='rad', fnirs_od='V', csd='mV/m²',
whitened='Z', gsr='S', temperature='C'),
# scalings for the units
scalings=dict(mag=1e15, grad=1e13, eeg=1e6, eog=1e6, emg=1e6, ecg=1e6,
misc=1.0, seeg=1e3, dbs=1e6, ecog=1e6, dipole=1e9, gof=1.0,
bio=1e6, hbo=1e6, hbr=1e6, ref_meg=1e15,
fnirs_cw_amplitude=1.0, fnirs_fd_ac_amplitude=1.0,
fnirs_fd_phase=1., fnirs_od=1.0, csd=1e3, whitened=1.,
gsr=1., temperature=1.),
# rough guess for a good plot
scalings_plot_raw=dict(mag=1e-12, grad=4e-11, eeg=20e-6, eog=150e-6,
ecg=5e-4, emg=1e-3, ref_meg=1e-12, misc='auto',
stim=1, resp=1, chpi=1e-4, exci=1, ias=1, syst=1,
seeg=1e-4, dbs=1e-4, bio=1e-6, ecog=1e-4, hbo=10e-6,
hbr=10e-6, whitened=10., fnirs_cw_amplitude=2e-2,
fnirs_fd_ac_amplitude=2e-2, fnirs_fd_phase=2e-1,
fnirs_od=2e-2, csd=200e-4,
dipole=1e-7, gof=1e2,
gsr=1., temperature=0.1),
scalings_cov_rank=dict(mag=1e12, grad=1e11, eeg=1e5, # ~100x scalings
seeg=1e1, dbs=1e4, ecog=1e4, hbo=1e4, hbr=1e4),
ylim=dict(mag=(-600., 600.), grad=(-200., 200.), eeg=(-200., 200.),
misc=(-5., 5.), seeg=(-20., 20.), dbs=(-200., 200.),
dipole=(-100., 100.), gof=(0., 1.), bio=(-500., 500.),
ecog=(-200., 200.), hbo=(0, 20), hbr=(0, 20), csd=(-50., 50.)),
titles=dict(mag='Magnetometers', grad='Gradiometers', eeg='EEG', eog='EOG',
ecg='ECG', emg='EMG', misc='misc', seeg='sEEG', dbs='DBS',
bio='BIO', dipole='Dipole', ecog='ECoG', hbo='Oxyhemoglobin',
ref_meg='Reference Magnetometers',
fnirs_cw_amplitude='fNIRS (CW amplitude)',
fnirs_fd_ac_amplitude='fNIRS (FD AC amplitude)',
fnirs_fd_phase='fNIRS (FD phase)',
fnirs_od='fNIRS (OD)', hbr='Deoxyhemoglobin',
gof='Goodness of fit', csd='Current source density',
stim='Stimulus', gsr='Galvanic skin response',
temperature='Temperature',
),
mask_params=dict(marker='o',
markerfacecolor='w',
markeredgecolor='k',
linewidth=0,
markeredgewidth=1,
markersize=4),
coreg=dict(
mri_fid_opacity=1.0,
dig_fid_opacity=1.0,
mri_fid_scale=5e-3,
dig_fid_scale=8e-3,
extra_scale=4e-3,
eeg_scale=4e-3, eegp_scale=20e-3, eegp_height=0.1,
ecog_scale=5e-3,
seeg_scale=5e-3,
dbs_scale=5e-3,
fnirs_scale=5e-3,
source_scale=5e-3,
detector_scale=5e-3,
hpi_scale=4e-3,
head_color=(0.988, 0.89, 0.74),
hpi_color=(1., 0., 1.),
extra_color=(1., 1., 1.),
meg_color=(0., 0.25, 0.5), ref_meg_color=(0.5, 0.5, 0.5),
helmet_color=(0.0, 0.0, 0.6),
eeg_color=(1., 0.596, 0.588), eegp_color=(0.839, 0.15, 0.16),
ecog_color=(1., 1., 1.),
dbs_color=(0.82, 0.455, 0.659),
seeg_color=(1., 1., .3),
fnirs_color=(1., .647, 0.),
source_color=(1., .05, 0.),
detector_color=(.3, .15, .15),
lpa_color=(1., 0., 0.),
nasion_color=(0., 1., 0.),
rpa_color=(0., 0., 1.),
),
noise_std=dict(grad=5e-13, mag=20e-15, eeg=0.2e-6),
eloreta_options=dict(eps=1e-6, max_iter=20, force_equal=False),
depth_mne=dict(exp=0.8, limit=10., limit_depth_chs=True,
combine_xyz='spectral', allow_fixed_depth=False),
depth_sparse=dict(exp=0.8, limit=None, limit_depth_chs='whiten',
combine_xyz='fro', allow_fixed_depth=True),
interpolation_method=dict(eeg='spline', meg='MNE', fnirs='nearest'),
volume_options=dict(
alpha=None, resolution=1., surface_alpha=None, blending='mip',
silhouette_alpha=None, silhouette_linewidth=2.),
prefixes={'k': 1e-3, 'h': 1e-2, '': 1e0, 'd': 1e1, 'c': 1e2, 'm': 1e3,
'µ': 1e6, 'u': 1e6, 'n': 1e9, 'p': 1e12, 'f': 1e15},
transform_zooms=dict(
translation=None, rigid=None, affine=None, sdr=None),
transform_niter=dict(
translation=(10000, 1000, 100),
rigid=(10000, 1000, 100),
affine=(10000, 1000, 100),
sdr=(10, 10, 5)),
volume_label_indices=(
# Left and middle
4, # Left-Lateral-Ventricle
5, # Left-Inf-Lat-Vent
8, # Left-Cerebellum-Cortex
10, # Left-Thalamus-Proper
11, # Left-Caudate
12, # Left-Putamen
13, # Left-Pallidum
14, # 3rd-Ventricle
15, # 4th-Ventricle
16, # Brain-Stem
17, # Left-Hippocampus
18, # Left-Amygdala
26, # Left-Accumbens-area
28, # Left-VentralDC
# Right
43, # Right-Lateral-Ventricle
44, # Right-Inf-Lat-Vent
47, # Right-Cerebellum-Cortex
49, # Right-Thalamus-Proper
50, # Right-Caudate
51, # Right-Putamen
52, # Right-Pallidum
53, # Right-Hippocampus
54, # Right-Amygdala
58, # Right-Accumbens-area
60, # Right-VentralDC
),
report_stc_plot_kwargs=dict(
views=('lateral', 'medial'),
hemi='split',
backend='pyvistaqt',
time_viewer=False,
show_traces=False,
size=(450, 450),
background='white',
time_label=None,
add_data_kwargs={
'colorbar_kwargs': {
'label_font_size': 12,
'n_labels': 5
}
}
)
)
def _handle_default(k, v=None):
"""Avoid dicts as default keyword arguments.
Use this function instead to resolve default dict values. Example usage::
scalings = _handle_default('scalings', scalings)
"""
this_mapping = deepcopy(DEFAULTS[k])
if v is not None:
if isinstance(v, dict):
this_mapping.update(v)
else:
for key in this_mapping:
this_mapping[key] = v
return this_mapping
HEAD_SIZE_DEFAULT = 0.095 # in [m]
_BORDER_DEFAULT = 'mean'
_INTERPOLATION_DEFAULT = 'cubic'
_EXTRAPOLATE_DEFAULT = 'auto'
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