bloyl

import numpy as np
import pylab as pl
import mne
from mne.datasets import sample
from mne.fiff import Raw, pick_types
from mne.minimum_norm import apply_inverse_epochs, read_inverse_operator

import time
from guppy import hpy

bloyl

import numpy as np


def computeIntegrationPoints(h, acc, base=None, shape='circle'):
    # These coil definitions make use of integration points according to the
    # last formula in section 25.4.62 in the "Handbook of Mathematical
    # Functions: With Formulas, Graphs, and Mathematical Tables"
    # edited by Abramowitz and Stegun.
    # http://people.math.sfu.ca/~cbm/aands/abramowitz_and_stegun.pdf

bloyl

import os.path as op
import matplotlib.pyplot as plt

import mne

data_path = mne.datasets.sample.data_path()
fname = op.join(data_path, 'MEG', 'sample', 'sample_audvis-ave.fif')
evoked = mne.read_evokeds(fname, baseline=(None, 0), proj=True)

evoked_l_aud = evoked[0]

bloyl

from mne import read_trans
from mne import io
import os.path as op

from mne.io.constants import FIFF
from mne.transforms import apply_trans, combine_transforms

ds_fname = 'test.ds'
meas_fname = '%s-info.fif' % op.splitext(ds_fname)[0]

bloyl

import os.path as op
import numpy as np
import matplotlib.pyplot as plt

import mne

data_path = mne.datasets.sample.data_path()
fname = op.join(data_path, 'MEG', 'sample', 'sample_audvis-ave.fif')
evoked = mne.read_evokeds(fname, baseline=(None, 0), proj=True)

bloyl

"""
================================
Brainstorm resting state dataset
================================

Here we compute the resting state from raw for the
Brainstorm tutorial dataset. For comparison, see [1]_ and:

    http://neuroimage.usc.edu/brainstorm/Tutorials/MedianNerveCtf

bloyl

name: hnn
channels:
- defaults
dependencies:
- python>=3.6
- pip
- numpy
- scipy
- matplotlib
- cython

bloyl

def plot_tfr(tfr, vmin, vmax, axes=None, colorbar=False, title=None,
             set_chan_title=True, show=True):
    from mne.viz.utils import center_cmap
    from matplotlib import pyplot as plt
    cmap = center_cmap(plt.cm.RdBu_r, vmin, vmax)  # zero maps to white
    n_chans = len(tfr.ch_names)
    if axes is None:
        if colorbar:
            w_ratios = list(np.repeat(10, n_chans)) + [1]
            fig, axes = plt.subplots(1, n_chans + 1, figsize=(12, 4),

bloyl

import numpy as np

tbl_data = np.zeros((2, 100))
tbl_data[0] = 1000 + np.arange(100)
tbl_data[1] = 3 * np.arange(100)

tableNode = slicer.mrmlScene.AddNewNodeByClass('vtkMRMLTableNode')
updateTableFromArray(tableNode, tbl_data.transpose())
tableNode.GetTable().GetColumn(0).SetName('X')
tableNode.GetTable().GetColumn(1).SetName('Y')