jhouck

#!/usr/bin/env python3

import os
from mne.io import read_info
from mne.datasets.brainstorm import bst_phantom_elekta
from mne import get_meg_helmet_surf
from mne.datasets import fetch_phantom
from mne.io.constants import FIFF
from mne.viz import plot_alignment
from mne.transforms import Transform

jhouck

import mne
from mne.io.constants import FIFF
import os.path as op
import numpy as np
from scipy.stats import rankdata

#data_path = mne.datasets.sample.data_path(update_path=False)
data_path = '/export/research/analysis/human/jhouck/shared/tools/MNE-sample-data/MNE-sample-data'
subjects_dir = op.join(data_path, 'subjects')
subject='sample'

jhouck

#!/usr/bin/env python3
# Rationale for using degrees (pitch/roll/yaw) interchangeably with mm  is "borrowed" from afni/3dvolreg. Basically, at a radius of about
# 57 mm (57.2598), circumference=360 mm, and 1 degree of rotation == 1 mm shift on the spherical surface.
# See https://afni.nimh.nih.gov/afni/community/board/read.php?1,82641,82645#msg-82645
import os
import mne
from nibabel.eulerangles import mat2euler
from mne.fixes import einsum
import numpy as np

jhouck

#!/usr/bin/env python3
# So basically what we want to do is:
# - load up dig source, MRISubjectSource, and create a MRIHeadWithFiducialsModel
# - load coreg transformation
# - apply transform
# - Compare distance 

import scipy as sp
import numpy as np
from mne import coreg

jhouck

#!/usr/bin/env python3

import numpy as np
import mne
from mne.datasets import sample
from mne import setup_volume_source_space
from mne.minimum_norm import make_inverse_operator, apply_inverse_raw
import matplotlib.pyplot as plt
import os.path as op
data_path = sample.data_path()

jhouck

#!/usr/bin/env python3

import mne
from mne import setup_volume_source_space
from mne.io import Raw
from mne.datasets import sample
from mne.minimum_norm import make_inverse_operator, apply_inverse_epochs, apply_inverse_raw
import numpy as np

data_path = sample.data_path()

jhouck