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# Authors: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Matti Hamalainen <msh@nmr.mgh.harvard.edu>
# Martin Luessi <mluessi@nmr.mgh.harvard.edu>
#
# License: BSD (3-clause)
from ..externals.six import string_types
import os
from warnings import warn
import logging
import numpy as np
from scipy import optimize, linalg
from ..io import Raw
from ..io.constants import FIFF
from ..utils import logger, verbose
from ..externals.six.moves import map
from ..externals.six.moves import zip
@verbose
def fit_sphere_to_headshape(info, verbose=None):
""" Fit a sphere to the headshape points to determine head center for
maxfilter.
Parameters
----------
info : dict
Measurement info.
verbose : bool, str, int, or None
If not None, override default verbose level (see mne.verbose).
Returns
-------
radius : float
Sphere radius in mm.
origin_head: ndarray
Head center in head coordinates (mm).
origin_device: ndarray
Head center in device coordinates (mm).
"""
# get head digization points, excluding some frontal points (nose etc.)
hsp = [p['r'] for p in info['dig'] if p['kind'] == FIFF.FIFFV_POINT_EXTRA
and not (p['r'][2] < 0 and p['r'][1] > 0)]
if len(hsp) == 0:
raise ValueError('No head digitization points found')
hsp = 1e3 * np.array(hsp)
# initial guess for center and radius
xradius = (np.max(hsp[:, 0]) - np.min(hsp[:, 0])) / 2
yradius = (np.max(hsp[:, 1]) - np.min(hsp[:, 1])) / 2
radius_init = (xradius + yradius) / 2
center_init = np.array([0.0, 0.0, np.max(hsp[:, 2]) - radius_init])
# optimization
x0 = np.r_[center_init, radius_init]
cost_fun = lambda x, hsp:\
np.sum((np.sqrt(np.sum((hsp - x[:3]) ** 2, axis=1)) - x[3]) ** 2)
disp = True if logger.level <= logging.INFO else False
x_opt = optimize.fmin_powell(cost_fun, x0, args=(hsp,), disp=disp)
origin_head = x_opt[:3]
radius = x_opt[3]
# compute origin in device coordinates
trans = info['dev_head_t']
if trans['from'] != FIFF.FIFFV_COORD_DEVICE\
or trans['to'] != FIFF.FIFFV_COORD_HEAD:
raise RuntimeError('device to head transform not found')
head_to_dev = linalg.inv(trans['trans'])
origin_device = 1e3 * np.dot(head_to_dev,
np.r_[1e-3 * origin_head, 1.0])[:3]
logger.info('Fitted sphere: r = %0.1f mm' % radius)
logger.info('Origin head coordinates: %0.1f %0.1f %0.1f mm' %
(origin_head[0], origin_head[1], origin_head[2]))
logger.info('Origin device coordinates: %0.1f %0.1f %0.1f mm' %
(origin_device[0], origin_device[1], origin_device[2]))
return radius, origin_head, origin_device
def _mxwarn(msg):
warn('Possible MaxFilter bug: %s, more info: '
'http://imaging.mrc-cbu.cam.ac.uk/meg/maxbugs' % msg)
@verbose
def apply_maxfilter(in_fname, out_fname, origin=None, frame='device',
bad=None, autobad='off', skip=None, force=False,
st=False, st_buflen=16.0, st_corr=0.96, mv_trans=None,
mv_comp=False, mv_headpos=False, mv_hp=None,
mv_hpistep=None, mv_hpisubt=None, mv_hpicons=True,
linefreq=None, cal=None, ctc=None, mx_args='',
overwrite=True, verbose=None):
""" Apply NeuroMag MaxFilter to raw data.
Needs Maxfilter license, maxfilter has to be in PATH
Parameters
----------
in_fname : string
Input file name
out_fname : string
Output file name
origin : array-like or string
Head origin in mm. If None it will be estimated from headshape points.
frame : string ('device' or 'head')
Coordinate frame for head center
bad : string, list (or None)
List of static bad channels. Can be a list with channel names, or a
string with channels (names or logical channel numbers)
autobad : string ('on', 'off', 'n')
Sets automated bad channel detection on or off
skip : string or a list of float-tuples (or None)
Skips raw data sequences, time intervals pairs in sec,
e.g.: 0 30 120 150
force : bool
Ignore program warnings
st : bool
Apply the time-domain MaxST extension
st_buflen : float
MaxSt buffer length in sec (disabled if st is False)
st_corr : float
MaxSt subspace correlation limit (disabled if st is False)
mv_trans : string (filename or 'default') (or None)
Transforms the data into the coil definitions of in_fname, or into the
default frame (None: don't use option)
mv_comp : bool (or 'inter')
Estimates and compensates head movements in continuous raw data
mv_headpos : bool
Estimates and stores head position parameters, but does not compensate
movements (disabled if mv_comp is False)
mv_hp : string (or None)
Stores head position data in an ascii file
(disabled if mv_comp is False)
mv_hpistep : float (or None)
Sets head position update interval in ms (disabled if mv_comp is False)
mv_hpisubt : string ('amp', 'base', 'off') (or None)
Subtracts hpi signals: sine amplitudes, amp + baseline, or switch off
(disabled if mv_comp is False)
mv_hpicons : bool
Check initial consistency isotrak vs hpifit
(disabled if mv_comp is False)
linefreq : int (50, 60) (or None)
Sets the basic line interference frequency (50 or 60 Hz)
(None: do not use line filter)
cal : string
Path to calibration file
ctc : string
Path to Cross-talk compensation file
mx_args : string
Additional command line arguments to pass to MaxFilter
overwrite : bool
Overwrite output file if it already exists
verbose : bool, str, int, or None
If not None, override default verbose level (see mne.verbose).
Returns
-------
origin: string
Head origin in selected coordinate frame
"""
# check for possible maxfilter bugs
if mv_trans is not None and mv_comp:
_mxwarn("Don't use '-trans' with head-movement compensation "
"'-movecomp'")
if autobad != 'off' and (mv_headpos or mv_comp):
_mxwarn("Don't use '-autobad' with head-position estimation "
"'-headpos' or movement compensation '-movecomp'")
if st and autobad != 'off':
_mxwarn("Don't use '-autobad' with '-st' option")
# determine the head origin if necessary
if origin is None:
logger.info('Estimating head origin from headshape points..')
raw = Raw(in_fname)
r, o_head, o_dev = fit_sphere_to_headshape(raw.info)
raw.close()
logger.info('[done]')
if frame == 'head':
origin = o_head
elif frame == 'device':
origin = o_dev
else:
RuntimeError('invalid frame for origin')
if not isinstance(origin, string_types):
origin = '%0.1f %0.1f %0.1f' % (origin[0], origin[1], origin[2])
# format command
cmd = ('maxfilter -f %s -o %s -frame %s -origin %s '
% (in_fname, out_fname, frame, origin))
if bad is not None:
# format the channels
if not isinstance(bad, list):
bad = bad.split()
bad = map(str, bad)
bad_logic = [ch[3:] if ch.startswith('MEG') else ch for ch in bad]
bad_str = ' '.join(bad_logic)
cmd += '-bad %s ' % bad_str
cmd += '-autobad %s ' % autobad
if skip is not None:
if isinstance(skip, list):
skip = ' '.join(['%0.3f %0.3f' % (s[0], s[1]) for s in skip])
cmd += '-skip %s ' % skip
if force:
cmd += '-force '
if st:
cmd += '-st '
cmd += ' %d ' % st_buflen
cmd += '-corr %0.4f ' % st_corr
if mv_trans is not None:
cmd += '-trans %s ' % mv_trans
if mv_comp:
cmd += '-movecomp '
if mv_comp == 'inter':
cmd += ' inter '
if mv_headpos:
cmd += '-headpos '
if mv_hp is not None:
cmd += '-hp %s ' % mv_hp
if mv_hpisubt is not None:
cmd += 'hpisubt %s ' % mv_hpisubt
if mv_hpicons:
cmd += '-hpicons '
if linefreq is not None:
cmd += '-linefreq %d ' % linefreq
if cal is not None:
cmd += '-cal %s ' % cal
if ctc is not None:
cmd += '-ctc %s ' % ctc
cmd += mx_args
if overwrite and os.path.exists(out_fname):
os.remove(out_fname)
logger.info('Running MaxFilter: %s ' % cmd)
st = os.system(cmd)
if st != 0:
raise RuntimeError('MaxFilter returned non-zero exit status %d' % st)
logger.info('[done]')
return origin
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