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import numpy as np
import os.path as op
from ...utils import logger
from ...transforms import (rotation3d_align_z_axis, get_ras_to_neuromag_trans,
apply_trans)
from ..meas_info import _make_dig_points
def _load_mne_locs(fname=None):
"""Load MNE locs structure from file (if exists) or recreate it."""
if (not fname):
# find input file
resource_dir = op.join(op.dirname(op.abspath(__file__)), 'resources')
fname = op.join(resource_dir, 'Artemis123_mneLoc.csv')
if not op.exists(fname):
raise IOError('MNE locs file "%s" does not exist' % (fname))
logger.info('Loading mne loc file {}'.format(fname))
locs = dict()
with open(fname, 'r') as fid:
for line in fid:
vals = line.strip().split(',')
locs[vals[0]] = np.array(vals[1::], np.float)
return locs
def _generate_mne_locs_file(output_fname):
"""Generate mne coil locs and save to supplied file."""
logger.info('Converting Tristan coil file to mne loc file...')
resource_dir = op.join(op.dirname(op.abspath(__file__)), 'resources')
chan_fname = op.join(resource_dir, 'Artemis123_ChannelMap.csv')
chans = _load_tristan_coil_locs(chan_fname)
# compute a dict of loc structs
locs = {n: _compute_mne_loc(cinfo) for n, cinfo in chans.items()}
# write it out to output_fname
with open(output_fname, 'w') as fid:
for n in sorted(locs.keys()):
fid.write('%s,' % n)
fid.write(','.join(locs[n].astype(str)))
fid.write('\n')
def _load_tristan_coil_locs(coil_loc_path):
"""Load the Coil locations from Tristan CAD drawings."""
channel_info = dict()
with open(coil_loc_path, 'r') as fid:
# skip 2 Header lines
fid.readline()
fid.readline()
for line in fid:
line = line.strip()
vals = line.split(',')
channel_info[vals[0]] = dict()
if vals[6]:
channel_info[vals[0]]['inner_coil'] = \
np.array(vals[2:5], np.float)
channel_info[vals[0]]['outer_coil'] = \
np.array(vals[5:8], np.float)
else: # nothing supplied
channel_info[vals[0]]['inner_coil'] = np.zeros(3)
channel_info[vals[0]]['outer_coil'] = np.zeros(3)
return channel_info
def _compute_mne_loc(coil_loc):
"""Convert a set of coils to an mne Struct.
Note input coil locations are in inches.
"""
loc = np.zeros((12))
if (np.linalg.norm(coil_loc['inner_coil']) == 0) and \
(np.linalg.norm(coil_loc['outer_coil']) == 0):
return loc
# channel location is inner coil location converted to meters From inches
loc[0:3] = coil_loc['inner_coil'] / 39.370078
# figure out rotation
z_axis = coil_loc['outer_coil'] - coil_loc['inner_coil']
R = rotation3d_align_z_axis(z_axis)
loc[3:13] = R.T.reshape(9)
return loc
def _read_pos(fname):
"""Read the .pos file and return positions as dig points."""
nas = None
lpa = None
rpa = None
hpi = None
extra = None
with open(fname, 'r') as fid:
for line in fid:
line = line.strip()
if len(line) > 0:
parts = line.split()
# The lines can have 4 or 5 parts. First part is for the id,
# which can be an int or a string. The last three are for xyz
# coordinates. The extra part is for additional info
# (e.g. 'Pz', 'Cz') which is ignored.
if len(parts) not in [4, 5]:
continue
if parts[0].lower() == 'nasion':
nas = np.array([float(p) for p in parts[-3:]]) / 100.
elif parts[0].lower() == 'left':
lpa = np.array([float(p) for p in parts[-3:]]) / 100.
elif parts[0].lower() == 'right':
rpa = np.array([float(p) for p in parts[-3:]]) / 100.
elif 'hpi' in parts[0].lower():
if hpi is None:
hpi = list()
hpi.append(np.array([float(p) for p in parts[-3:]]) / 100.)
else:
if extra is None:
extra = list()
extra.append(np.array([float(p)
for p in parts[-3:]]) / 100.)
# move into MNE head coords
if ((nas is not None) and (lpa is not None) and (rpa is not None)):
neuromag_trans = get_ras_to_neuromag_trans(nas, lpa, rpa)
nas = apply_trans(neuromag_trans, nas)
lpa = apply_trans(neuromag_trans, lpa)
rpa = apply_trans(neuromag_trans, rpa)
if hpi is not None:
hpi = apply_trans(neuromag_trans, hpi)
if extra is not None:
extra = apply_trans(neuromag_trans, extra)
digs = _make_dig_points(nasion=nas, lpa=lpa, rpa=rpa, hpi=hpi,
extra_points=extra)
return digs
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