/
bti.py
1407 lines (1178 loc) · 54.8 KB
/
bti.py
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# Authors: Denis A. Engemann <denis.engemann@gmail.com>
# Martin Luessi <mluessi@nmr.mgh.harvard.edu>
# Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Matti Hamalainen <msh@nmr.mgh.harvard.edu>
# Yuval Harpaz <yuvharpaz@gmail.com>
#
# simplified BSD-3 license
import os.path as op
from itertools import count
import numpy as np
from ...utils import logger, verbose, sum_squared
from ...transforms import (combine_transforms, invert_transform, apply_trans,
Transform)
from ..constants import FIFF
from .. import BaseRaw, _coil_trans_to_loc, _loc_to_coil_trans, _empty_info
from ..utils import _mult_cal_one, read_str
from .constants import BTI
from .read import (read_int32, read_int16, read_float, read_double,
read_transform, read_char, read_int64, read_uint16,
read_uint32, read_double_matrix, read_float_matrix,
read_int16_matrix, read_dev_header)
from ...externals import six
FIFF_INFO_CHS_FIELDS = ('loc',
'ch_name', 'unit_mul', 'coord_frame', 'coil_type',
'range', 'unit', 'cal',
'scanno', 'kind', 'logno')
FIFF_INFO_CHS_DEFAULTS = (np.array([0, 0, 0, 1] * 3, dtype='f4'),
None, 0, 0, 0,
1.0, FIFF.FIFF_UNIT_V, 1.0,
None, FIFF.FIFFV_ECG_CH, None)
FIFF_INFO_DIG_FIELDS = ('kind', 'ident', 'r', 'coord_frame')
FIFF_INFO_DIG_DEFAULTS = (None, None, None, FIFF.FIFFV_COORD_HEAD)
BTI_WH2500_REF_MAG = ('MxA', 'MyA', 'MzA', 'MxaA', 'MyaA', 'MzaA')
BTI_WH2500_REF_GRAD = ('GxxA', 'GyyA', 'GyxA', 'GzaA', 'GzyA')
dtypes = zip(list(range(1, 5)), ('>i2', '>i4', '>f4', '>f8'))
DTYPES = dict((i, np.dtype(t)) for i, t in dtypes)
class _bytes_io_mock_context():
"""Make a context for BytesIO."""
def __init__(self, target): # noqa: D102
self.target = target
def __enter__(self): # noqa: D105
return self.target
def __exit__(self, type, value, tb): # noqa: D105
pass
def _bti_open(fname, *args, **kwargs):
"""Handle BytesIO."""
if isinstance(fname, six.string_types):
return open(fname, *args, **kwargs)
elif isinstance(fname, six.BytesIO):
return _bytes_io_mock_context(fname)
else:
raise RuntimeError('Cannot mock this.')
def _get_bti_dev_t(adjust=0., translation=(0.0, 0.02, 0.11)):
"""Get the general Magnes3600WH to Neuromag coordinate transform.
Parameters
----------
adjust : float | None
Degrees to tilt x-axis for sensor frame misalignment.
If None, no adjustment will be applied.
translation : array-like
The translation to place the origin of coordinate system
to the center of the head.
Returns
-------
m_nm_t : ndarray
4 x 4 rotation, translation, scaling matrix.
"""
flip_t = np.array([[0., -1., 0.],
[1., 0., 0.],
[0., 0., 1.]])
rad = np.deg2rad(adjust)
adjust_t = np.array([[1., 0., 0.],
[0., np.cos(rad), -np.sin(rad)],
[0., np.sin(rad), np.cos(rad)]])
m_nm_t = np.eye(4)
m_nm_t[:3, :3] = np.dot(flip_t, adjust_t)
m_nm_t[:3, 3] = translation
return m_nm_t
def _rename_channels(names, ecg_ch='E31', eog_ch=('E63', 'E64')):
"""Rename appropriately ordered list of channel names.
Parameters
----------
names : list of str
Lists of 4-D channel names in ascending order
Returns
-------
new : list
List of names, channel names in Neuromag style
"""
new = list()
ref_mag, ref_grad, eog, eeg, ext = [count(1) for _ in range(5)]
for i, name in enumerate(names, 1):
if name.startswith('A'):
name = 'MEG %3.3d' % i
elif name == 'RESPONSE':
name = 'STI 013'
elif name == 'TRIGGER':
name = 'STI 014'
elif any(name == k for k in eog_ch):
name = 'EOG %3.3d' % six.advance_iterator(eog)
elif name == ecg_ch:
name = 'ECG 001'
elif name.startswith('E'):
name = 'EEG %3.3d' % six.advance_iterator(eeg)
elif name == 'UACurrent':
name = 'UTL 001'
elif name.startswith('M'):
name = 'RFM %3.3d' % six.advance_iterator(ref_mag)
elif name.startswith('G'):
name = 'RFG %3.3d' % six.advance_iterator(ref_grad)
elif name.startswith('X'):
name = 'EXT %3.3d' % six.advance_iterator(ext)
new += [name]
return new
def _read_head_shape(fname):
"""Read the head shape."""
with _bti_open(fname, 'rb') as fid:
fid.seek(BTI.FILE_HS_N_DIGPOINTS)
_n_dig_points = read_int32(fid)
idx_points = read_double_matrix(fid, BTI.DATA_N_IDX_POINTS, 3)
dig_points = read_double_matrix(fid, _n_dig_points, 3)
return idx_points, dig_points
def _get_ctf_head_to_head_t(idx_points):
"""Get the CTF head transform."""
fp = idx_points.astype('>f8')
dp = np.sum(fp[2] * (fp[0] - fp[1]))
tmp1, tmp2 = sum_squared(fp[2]), sum_squared(fp[0] - fp[1])
dcos = -dp / np.sqrt(tmp1 * tmp2)
dsin = np.sqrt(1. - dcos * dcos)
dt = dp / np.sqrt(tmp2)
# do the transformation
t = np.array([[dcos, -dsin, 0., dt],
[dsin, dcos, 0., 0.],
[0., 0., 1., 0.],
[0., 0., 0., 1.]])
return Transform('ctf_head', 'head', t)
def _flip_fiducials(idx_points_nm):
"""Adjust order of fiducials to Neuromag."""
# XXX presumably swap LPA and RPA
idx_points_nm[[1, 2]] = idx_points_nm[[2, 1]]
return idx_points_nm
def _process_bti_headshape(fname, convert=True, use_hpi=True):
"""Read index points and dig points from BTi head shape file.
Parameters
----------
fname : str
The absolute path to the head shape file
use_hpi : bool
Whether to treat additional hpi coils as digitization points or not.
If False, hpi coils will be discarded.
Returns
-------
dig : list of dicts
The list of dig point info structures needed for the fiff info
structure.
t : dict
The transformation that was used.
"""
idx_points, dig_points = _read_head_shape(fname)
if convert:
ctf_head_t = _get_ctf_head_to_head_t(idx_points)
else:
ctf_head_t = Transform('ctf_head', 'ctf_head')
if dig_points is not None:
# dig_points = apply_trans(ctf_head_t['trans'], dig_points)
all_points = np.r_[idx_points, dig_points]
else:
all_points = idx_points
if convert:
all_points = _convert_hs_points(all_points, ctf_head_t)
dig = _points_to_dig(all_points, len(idx_points), use_hpi)
return dig, ctf_head_t
def _convert_hs_points(points, t):
"""Convert headshape points to Neuromag."""
points = apply_trans(t['trans'], points)
points = _flip_fiducials(points).astype(np.float32)
return points
def _points_to_dig(points, n_idx_points, use_hpi):
"""Put points in info dig structure."""
idx_idents = list(range(1, 4)) + list(range(1, (n_idx_points + 1) - 3))
dig = []
for idx in range(points.shape[0]):
point_info = dict(zip(FIFF_INFO_DIG_FIELDS, FIFF_INFO_DIG_DEFAULTS))
point_info['r'] = points[idx]
if idx < 3:
point_info['kind'] = FIFF.FIFFV_POINT_CARDINAL
point_info['ident'] = idx_idents[idx]
if 2 < idx < n_idx_points and use_hpi:
point_info['kind'] = FIFF.FIFFV_POINT_HPI
point_info['ident'] = idx_idents[idx]
elif idx > 4:
point_info['kind'] = FIFF.FIFFV_POINT_EXTRA
point_info['ident'] = (idx + 1) - len(idx_idents)
if 2 < idx < n_idx_points and not use_hpi:
pass
else:
dig += [point_info]
return dig
def _check_nan_dev_head_t(dev_ctf_t):
"""Make sure we deal with nans."""
has_nan = np.isnan(dev_ctf_t['trans'])
if np.any(has_nan):
logger.info('Missing values BTI dev->head transform. '
'Replacing with identity matrix.')
dev_ctf_t['trans'] = np.identity(4)
def _convert_coil_trans(coil_trans, dev_ctf_t, bti_dev_t):
"""Convert the coil trans."""
t = combine_transforms(invert_transform(dev_ctf_t), bti_dev_t,
'ctf_head', 'meg')
t = np.dot(t['trans'], coil_trans)
return t
def _correct_offset(fid):
"""Align fid pointer."""
current = fid.tell()
if ((current % BTI.FILE_CURPOS) != 0):
offset = current % BTI.FILE_CURPOS
fid.seek(BTI.FILE_CURPOS - (offset), 1)
def _read_config(fname):
"""Read BTi system config file.
Parameters
----------
fname : str
The absolute path to the config file
Returns
-------
cfg : dict
The config blocks found.
"""
with _bti_open(fname, 'rb') as fid:
cfg = dict()
cfg['hdr'] = {'version': read_int16(fid),
'site_name': read_str(fid, 32),
'dap_hostname': read_str(fid, 16),
'sys_type': read_int16(fid),
'sys_options': read_int32(fid),
'supply_freq': read_int16(fid),
'total_chans': read_int16(fid),
'system_fixed_gain': read_float(fid),
'volts_per_bit': read_float(fid),
'total_sensors': read_int16(fid),
'total_user_blocks': read_int16(fid),
'next_der_chan_no': read_int16(fid)}
fid.seek(2, 1)
cfg['checksum'] = read_uint32(fid)
cfg['reserved'] = read_char(fid, 32)
cfg['transforms'] = [read_transform(fid) for t in
range(cfg['hdr']['total_sensors'])]
cfg['user_blocks'] = dict()
for block in range(cfg['hdr']['total_user_blocks']):
ub = dict()
ub['hdr'] = {'nbytes': read_uint32(fid),
'kind': read_str(fid, 20),
'checksum': read_int32(fid),
'username': read_str(fid, 32),
'timestamp': read_uint32(fid),
'user_space_size': read_uint32(fid),
'reserved': read_char(fid, 32)}
_correct_offset(fid)
start_bytes = fid.tell()
kind = ub['hdr'].pop('kind')
if not kind: # make sure reading goes right. Should never be empty
raise RuntimeError('Could not read user block. Probably you '
'acquired data using a BTi version '
'currently not supported. Please contact '
'the mne-python developers.')
dta, cfg['user_blocks'][kind] = dict(), ub
if kind in [v for k, v in BTI.items() if k[:5] == 'UB_B_']:
if kind == BTI.UB_B_MAG_INFO:
dta['version'] = read_int32(fid)
fid.seek(20, 1)
dta['headers'] = list()
for hdr in range(6):
d = {'name': read_str(fid, 16),
'transform': read_transform(fid),
'units_per_bit': read_float(fid)}
dta['headers'] += [d]
fid.seek(20, 1)
elif kind == BTI.UB_B_COH_POINTS:
dta['n_points'] = read_int32(fid)
dta['status'] = read_int32(fid)
dta['points'] = []
for pnt in range(16):
d = {'pos': read_double_matrix(fid, 1, 3),
'direction': read_double_matrix(fid, 1, 3),
'error': read_double(fid)}
dta['points'] += [d]
elif kind == BTI.UB_B_CCP_XFM_BLOCK:
dta['method'] = read_int32(fid)
# handle difference btw/ linux (0) and solaris (4)
size = 0 if ub['hdr']['user_space_size'] == 132 else 4
fid.seek(size, 1)
dta['transform'] = read_transform(fid)
elif kind == BTI.UB_B_EEG_LOCS:
dta['electrodes'] = []
while True:
d = {'label': read_str(fid, 16),
'location': read_double_matrix(fid, 1, 3)}
if not d['label']:
break
dta['electrodes'] += [d]
elif kind in [BTI.UB_B_WHC_CHAN_MAP_VER,
BTI.UB_B_WHS_SUBSYS_VER]:
dta['version'] = read_int16(fid)
dta['struct_size'] = read_int16(fid)
dta['entries'] = read_int16(fid)
fid.seek(8, 1)
elif kind == BTI.UB_B_WHC_CHAN_MAP:
num_channels = None
for name, data in cfg['user_blocks'].items():
if name == BTI.UB_B_WHC_CHAN_MAP_VER:
num_channels = data['entries']
break
if num_channels is None:
raise ValueError('Cannot find block %s to determine '
'number of channels'
% BTI.UB_B_WHC_CHAN_MAP_VER)
dta['channels'] = list()
for i in range(num_channels):
d = {'subsys_type': read_int16(fid),
'subsys_num': read_int16(fid),
'card_num': read_int16(fid),
'chan_num': read_int16(fid),
'recdspnum': read_int16(fid)}
dta['channels'] += [d]
fid.seek(8, 1)
elif kind == BTI.UB_B_WHS_SUBSYS:
num_subsys = None
for name, data in cfg['user_blocks'].items():
if name == BTI.UB_B_WHS_SUBSYS_VER:
num_subsys = data['entries']
break
if num_subsys is None:
raise ValueError('Cannot find block %s to determine'
' number of subsystems'
% BTI.UB_B_WHS_SUBSYS_VER)
dta['subsys'] = list()
for sub_key in range(num_subsys):
d = {'subsys_type': read_int16(fid),
'subsys_num': read_int16(fid),
'cards_per_sys': read_int16(fid),
'channels_per_card': read_int16(fid),
'card_version': read_int16(fid)}
fid.seek(2, 1)
d.update({'offsetdacgain': read_float(fid),
'squid_type': read_int32(fid),
'timesliceoffset': read_int16(fid),
'padding': read_int16(fid),
'volts_per_bit': read_float(fid)})
dta['subsys'] += [d]
elif kind == BTI.UB_B_CH_LABELS:
dta['version'] = read_int32(fid)
dta['entries'] = read_int32(fid)
fid.seek(16, 1)
dta['labels'] = list()
for label in range(dta['entries']):
dta['labels'] += [read_str(fid, 16)]
elif kind == BTI.UB_B_CALIBRATION:
dta['sensor_no'] = read_int16(fid)
fid.seek(2, 1)
dta['timestamp'] = read_int32(fid)
dta['logdir'] = read_str(fid, 256)
elif kind == BTI.UB_B_SYS_CONFIG_TIME:
# handle difference btw/ linux (256) and solaris (512)
size = 256 if ub['hdr']['user_space_size'] == 260 else 512
dta['sysconfig_name'] = read_str(fid, size)
dta['timestamp'] = read_int32(fid)
elif kind == BTI.UB_B_DELTA_ENABLED:
dta['delta_enabled'] = read_int16(fid)
elif kind in [BTI.UB_B_E_TABLE_USED, BTI.UB_B_E_TABLE]:
dta['hdr'] = {'version': read_int32(fid),
'entry_size': read_int32(fid),
'n_entries': read_int32(fid),
'filtername': read_str(fid, 16),
'n_e_values': read_int32(fid),
'reserved': read_str(fid, 28)}
if dta['hdr']['version'] == 2:
size = 16
dta['ch_names'] = [read_str(fid, size) for ch in
range(dta['hdr']['n_entries'])]
dta['e_ch_names'] = [read_str(fid, size) for ch in
range(dta['hdr']['n_e_values'])]
rows = dta['hdr']['n_entries']
cols = dta['hdr']['n_e_values']
dta['etable'] = read_float_matrix(fid, rows, cols)
else: # handle MAGNES2500 naming scheme
dta['ch_names'] = ['WH2500'] * dta['hdr']['n_e_values']
dta['hdr']['n_e_values'] = 6
dta['e_ch_names'] = BTI_WH2500_REF_MAG
rows = dta['hdr']['n_entries']
cols = dta['hdr']['n_e_values']
dta['etable'] = read_float_matrix(fid, rows, cols)
elif any([kind == BTI.UB_B_WEIGHTS_USED,
kind[:4] == BTI.UB_B_WEIGHT_TABLE]):
dta['hdr'] = dict(
version=read_int32(fid),
n_bytes=read_uint32(fid),
n_entries=read_uint32(fid),
name=read_str(fid, 32))
if dta['hdr']['version'] == 2:
dta['hdr'].update(
description=read_str(fid, 80),
n_anlg=read_uint32(fid),
n_dsp=read_uint32(fid),
reserved=read_str(fid, 72))
dta['ch_names'] = [read_str(fid, 16) for ch in
range(dta['hdr']['n_entries'])]
dta['anlg_ch_names'] = [read_str(fid, 16) for ch in
range(dta['hdr']['n_anlg'])]
dta['dsp_ch_names'] = [read_str(fid, 16) for ch in
range(dta['hdr']['n_dsp'])]
dta['dsp_wts'] = read_float_matrix(
fid, dta['hdr']['n_entries'], dta['hdr']['n_dsp'])
dta['anlg_wts'] = read_int16_matrix(
fid, dta['hdr']['n_entries'], dta['hdr']['n_anlg'])
else: # handle MAGNES2500 naming scheme
fid.seek(start_bytes + ub['hdr']['user_space_size'] -
dta['hdr']['n_bytes'] *
dta['hdr']['n_entries'], 0)
dta['hdr']['n_dsp'] = dta['hdr']['n_bytes'] // 4 - 2
assert (dta['hdr']['n_dsp'] ==
len(BTI_WH2500_REF_MAG) +
len(BTI_WH2500_REF_GRAD))
dta['ch_names'] = ['WH2500'] * dta['hdr']['n_entries']
dta['hdr']['n_anlg'] = 3
# These orders could be wrong, so don't set them
# for now
# dta['anlg_ch_names'] = BTI_WH2500_REF_MAG[:3]
# dta['dsp_ch_names'] = (BTI_WH2500_REF_GRAD +
# BTI_WH2500_REF_MAG)
dta['anlg_wts'] = np.zeros(
(dta['hdr']['n_entries'], dta['hdr']['n_anlg']),
dtype='i2')
dta['dsp_wts'] = np.zeros(
(dta['hdr']['n_entries'], dta['hdr']['n_dsp']),
dtype='f4')
for n in range(dta['hdr']['n_entries']):
dta['anlg_wts'][n] = read_int16_matrix(
fid, 1, dta['hdr']['n_anlg'])
read_int16(fid)
dta['dsp_wts'][n] = read_float_matrix(
fid, 1, dta['hdr']['n_dsp'])
elif kind == BTI.UB_B_TRIG_MASK:
dta['version'] = read_int32(fid)
dta['entries'] = read_int32(fid)
fid.seek(16, 1)
dta['masks'] = []
for entry in range(dta['entries']):
d = {'name': read_str(fid, 20),
'nbits': read_uint16(fid),
'shift': read_uint16(fid),
'mask': read_uint32(fid)}
dta['masks'] += [d]
fid.seek(8, 1)
else:
dta['unknown'] = {'hdr': read_char(fid,
ub['hdr']['user_space_size'])}
n_read = fid.tell() - start_bytes
if n_read != ub['hdr']['user_space_size']:
raise RuntimeError('Internal MNE reading error, read size %d '
'!= %d expected size for kind %s'
% (n_read, ub['hdr']['user_space_size'],
kind))
ub.update(dta) # finally update the userblock data
_correct_offset(fid) # after reading.
cfg['chs'] = list()
# prepare reading channels
for channel in range(cfg['hdr']['total_chans']):
ch = {'name': read_str(fid, 16),
'chan_no': read_int16(fid),
'ch_type': read_uint16(fid),
'sensor_no': read_int16(fid),
'data': dict()}
fid.seek(2, 1)
ch.update({'gain': read_float(fid),
'units_per_bit': read_float(fid),
'yaxis_label': read_str(fid, 16),
'aar_val': read_double(fid),
'checksum': read_int32(fid),
'reserved': read_str(fid, 32)})
cfg['chs'] += [ch]
_correct_offset(fid) # before and after
dta = dict()
if ch['ch_type'] in [BTI.CHTYPE_MEG, BTI.CHTYPE_REFERENCE]:
dev = {'device_info': read_dev_header(fid),
'inductance': read_float(fid),
'padding': read_str(fid, 4),
'transform': _correct_trans(read_transform(fid), False),
'xform_flag': read_int16(fid),
'total_loops': read_int16(fid)}
fid.seek(4, 1)
dev['reserved'] = read_str(fid, 32)
dta.update({'dev': dev, 'loops': []})
for loop in range(dev['total_loops']):
d = {'position': read_double_matrix(fid, 1, 3),
'orientation': read_double_matrix(fid, 1, 3),
'radius': read_double(fid),
'wire_radius': read_double(fid),
'turns': read_int16(fid)}
fid.seek(2, 1)
d['checksum'] = read_int32(fid)
d['reserved'] = read_str(fid, 32)
dta['loops'] += [d]
elif ch['ch_type'] == BTI.CHTYPE_EEG:
dta = {'device_info': read_dev_header(fid),
'impedance': read_float(fid),
'padding': read_str(fid, 4),
'transform': read_transform(fid),
'reserved': read_char(fid, 32)}
elif ch['ch_type'] == BTI.CHTYPE_EXTERNAL:
dta = {'device_info': read_dev_header(fid),
'user_space_size': read_int32(fid),
'reserved': read_str(fid, 32)}
elif ch['ch_type'] == BTI.CHTYPE_TRIGGER:
dta = {'device_info': read_dev_header(fid),
'user_space_size': read_int32(fid)}
fid.seek(2, 1)
dta['reserved'] = read_str(fid, 32)
elif ch['ch_type'] in [BTI.CHTYPE_UTILITY, BTI.CHTYPE_DERIVED]:
dta = {'device_info': read_dev_header(fid),
'user_space_size': read_int32(fid),
'reserved': read_str(fid, 32)}
elif ch['ch_type'] == BTI.CHTYPE_SHORTED:
dta = {'device_info': read_dev_header(fid),
'reserved': read_str(fid, 32)}
ch.update(dta) # add data collected
_correct_offset(fid) # after each reading
return cfg
def _read_epoch(fid):
"""Read BTi PDF epoch."""
out = {'pts_in_epoch': read_int32(fid),
'epoch_duration': read_float(fid),
'expected_iti': read_float(fid),
'actual_iti': read_float(fid),
'total_var_events': read_int32(fid),
'checksum': read_int32(fid),
'epoch_timestamp': read_int32(fid)}
fid.seek(28, 1)
return out
def _read_channel(fid):
"""Read BTi PDF channel."""
out = {'chan_label': read_str(fid, 16),
'chan_no': read_int16(fid),
'attributes': read_int16(fid),
'scale': read_float(fid),
'yaxis_label': read_str(fid, 16),
'valid_min_max': read_int16(fid)}
fid.seek(6, 1)
out.update({'ymin': read_double(fid),
'ymax': read_double(fid),
'index': read_int32(fid),
'checksum': read_int32(fid),
'off_flag': read_str(fid, 16),
'offset': read_float(fid)})
fid.seek(12, 1)
return out
def _read_event(fid):
"""Read BTi PDF event."""
out = {'event_name': read_str(fid, 16),
'start_lat': read_float(fid),
'end_lat': read_float(fid),
'step_size': read_float(fid),
'fixed_event': read_int16(fid),
'checksum': read_int32(fid)}
fid.seek(32, 1)
_correct_offset(fid)
return out
def _read_process(fid):
"""Read BTi PDF process."""
out = {'nbytes': read_int32(fid),
'process_type': read_str(fid, 20),
'checksum': read_int32(fid),
'user': read_str(fid, 32),
'timestamp': read_int32(fid),
'filename': read_str(fid, 256),
'total_steps': read_int32(fid)}
fid.seek(32, 1)
_correct_offset(fid)
out['processing_steps'] = list()
for step in range(out['total_steps']):
this_step = {'nbytes': read_int32(fid),
'process_type': read_str(fid, 20),
'checksum': read_int32(fid)}
ptype = this_step['process_type']
if ptype == BTI.PROC_DEFAULTS:
this_step['scale_option'] = read_int32(fid)
fid.seek(4, 1)
this_step['scale'] = read_double(fid)
this_step['dtype'] = read_int32(fid)
this_step['selected'] = read_int16(fid)
this_step['color_display'] = read_int16(fid)
fid.seek(32, 1)
elif ptype in BTI.PROC_FILTER:
this_step['freq'] = read_float(fid)
fid.seek(32, 1)
elif ptype in BTI.PROC_BPFILTER:
this_step['high_freq'] = read_float(fid)
this_step['low_frew'] = read_float(fid)
else:
jump = this_step['user_space_size'] = read_int32(fid)
fid.seek(32, 1)
fid.seek(jump, 1)
out['processing_steps'] += [this_step]
_correct_offset(fid)
return out
def _read_assoc_file(fid):
"""Read BTi PDF assocfile."""
out = {'file_id': read_int16(fid),
'length': read_int16(fid)}
fid.seek(32, 1)
out['checksum'] = read_int32(fid)
return out
def _read_pfid_ed(fid):
"""Read PDF ed file."""
out = {'comment_size': read_int32(fid),
'name': read_str(fid, 17)}
fid.seek(9, 1)
out.update({'pdf_number': read_int16(fid),
'total_events': read_int32(fid),
'timestamp': read_int32(fid),
'flags': read_int32(fid),
'de_process': read_int32(fid),
'checksum': read_int32(fid),
'ed_id': read_int32(fid),
'win_width': read_float(fid),
'win_offset': read_float(fid)})
fid.seek(8, 1)
return out
def _read_coil_def(fid):
"""Read coil definition."""
coildef = {'position': read_double_matrix(fid, 1, 3),
'orientation': read_double_matrix(fid, 1, 3),
'radius': read_double(fid),
'wire_radius': read_double(fid),
'turns': read_int16(fid)}
fid.seek(fid, 2, 1)
coildef['checksum'] = read_int32(fid)
coildef['reserved'] = read_str(fid, 32)
def _read_ch_config(fid):
"""Read BTi channel config."""
cfg = {'name': read_str(fid, BTI.FILE_CONF_CH_NAME),
'chan_no': read_int16(fid),
'ch_type': read_uint16(fid),
'sensor_no': read_int16(fid)}
fid.seek(fid, BTI.FILE_CONF_CH_NEXT, 1)
cfg.update({'gain': read_float(fid),
'units_per_bit': read_float(fid),
'yaxis_label': read_str(fid, BTI.FILE_CONF_CH_YLABEL),
'aar_val': read_double(fid),
'checksum': read_int32(fid),
'reserved': read_str(fid, BTI.FILE_CONF_CH_RESERVED)})
_correct_offset(fid)
# Then the channel info
ch_type, chan = cfg['ch_type'], dict()
chan['dev'] = {'size': read_int32(fid),
'checksum': read_int32(fid),
'reserved': read_str(fid, 32)}
if ch_type in [BTI.CHTYPE_MEG, BTI.CHTYPE_REF]:
chan['loops'] = [_read_coil_def(fid) for d in
range(chan['dev']['total_loops'])]
elif ch_type == BTI.CHTYPE_EEG:
chan['impedance'] = read_float(fid)
chan['padding'] = read_str(fid, BTI.FILE_CONF_CH_PADDING)
chan['transform'] = read_transform(fid)
chan['reserved'] = read_char(fid, BTI.FILE_CONF_CH_RESERVED)
elif ch_type in [BTI.CHTYPE_TRIGGER, BTI.CHTYPE_EXTERNAL,
BTI.CHTYPE_UTILITY, BTI.CHTYPE_DERIVED]:
chan['user_space_size'] = read_int32(fid)
if ch_type == BTI.CHTYPE_TRIGGER:
fid.seek(2, 1)
chan['reserved'] = read_str(fid, BTI.FILE_CONF_CH_RESERVED)
elif ch_type == BTI.CHTYPE_SHORTED:
chan['reserved'] = read_str(fid, BTI.FILE_CONF_CH_RESERVED)
cfg['chan'] = chan
_correct_offset(fid)
return cfg
def _read_bti_header_pdf(pdf_fname):
"""Read header from pdf file."""
with _bti_open(pdf_fname, 'rb') as fid:
fid.seek(-8, 2)
start = fid.tell()
header_position = read_int64(fid)
check_value = header_position & BTI.FILE_MASK
if ((start + BTI.FILE_CURPOS - check_value) <= BTI.FILE_MASK):
header_position = check_value
# Check header position for alignment issues
if ((header_position % 8) != 0):
header_position += (8 - (header_position % 8))
fid.seek(header_position, 0)
# actual header starts here
info = {'version': read_int16(fid),
'file_type': read_str(fid, 5),
'hdr_size': start - header_position, # add for convenience
'start': start}
fid.seek(1, 1)
info.update({'data_format': read_int16(fid),
'acq_mode': read_int16(fid),
'total_epochs': read_int32(fid),
'input_epochs': read_int32(fid),
'total_events': read_int32(fid),
'total_fixed_events': read_int32(fid),
'sample_period': read_float(fid),
'xaxis_label': read_str(fid, 16),
'total_processes': read_int32(fid),
'total_chans': read_int16(fid)})
fid.seek(2, 1)
info.update({'checksum': read_int32(fid),
'total_ed_classes': read_int32(fid),
'total_associated_files': read_int16(fid),
'last_file_index': read_int16(fid),
'timestamp': read_int32(fid)})
fid.seek(20, 1)
_correct_offset(fid)
# actual header ends here, so dar seems ok.
info['epochs'] = [_read_epoch(fid) for epoch in
range(info['total_epochs'])]
info['chs'] = [_read_channel(fid) for ch in
range(info['total_chans'])]
info['events'] = [_read_event(fid) for event in
range(info['total_events'])]
info['processes'] = [_read_process(fid) for process in
range(info['total_processes'])]
info['assocfiles'] = [_read_assoc_file(fid) for af in
range(info['total_associated_files'])]
info['edclasses'] = [_read_pfid_ed(fid) for ed_class in
range(info['total_ed_classes'])]
info['extra_data'] = fid.read(start - fid.tell())
info['pdf_fname'] = pdf_fname
info['total_slices'] = sum(e['pts_in_epoch'] for e in
info['epochs'])
info['dtype'] = DTYPES[info['data_format']]
bps = info['dtype'].itemsize * info['total_chans']
info['bytes_per_slice'] = bps
return info
def _read_bti_header(pdf_fname, config_fname, sort_by_ch_name=True):
"""Read bti PDF header."""
info = _read_bti_header_pdf(pdf_fname) if pdf_fname is not None else dict()
cfg = _read_config(config_fname)
info['bti_transform'] = cfg['transforms']
# augment channel list by according info from config.
# get channels from config present in PDF
chans = info.get('chs', None)
if chans is not None:
chans_cfg = [c for c in cfg['chs'] if c['chan_no']
in [c_['chan_no'] for c_ in chans]]
# check all pdf channels are present in config
match = [c['chan_no'] for c in chans_cfg] == \
[c['chan_no'] for c in chans]
if not match:
raise RuntimeError('Could not match raw data channels with'
' config channels. Some of the channels'
' found are not described in config.')
else:
chans_cfg = cfg['chs']
chans = [dict() for d in chans_cfg]
# transfer channel info from config to channel info
for ch, ch_cfg in zip(chans, chans_cfg):
ch['upb'] = ch_cfg['units_per_bit']
ch['gain'] = ch_cfg['gain']
ch['name'] = ch_cfg['name']
if ch_cfg.get('dev', dict()).get('transform', None) is not None:
ch['loc'] = _coil_trans_to_loc(ch_cfg['dev']['transform'])
else:
ch['loc'] = None
if pdf_fname is not None:
if info['data_format'] <= 2: # see DTYPES, implies integer
ch['cal'] = ch['scale'] * ch['upb'] / float(ch['gain'])
else: # float
ch['cal'] = ch['scale'] * ch['gain']
else: # if we are in this mode we don't read data, only channel info.
ch['cal'] = ch['scale'] = 1.0 # so we put a trivial default value
if sort_by_ch_name:
by_index = [(i, d['index']) for i, d in enumerate(chans)]
by_index.sort(key=lambda c: c[1])
by_index = [idx[0] for idx in by_index]
chs = [chans[pos] for pos in by_index]
sort_by_name_idx = [(i, d['name']) for i, d in enumerate(chs)]
a_chs = [c for c in sort_by_name_idx if c[1].startswith('A')]
other_chs = [c for c in sort_by_name_idx if not c[1].startswith('A')]
sort_by_name_idx = sorted(
a_chs, key=lambda c: int(c[1][1:])) + sorted(other_chs)
sort_by_name_idx = [idx[0] for idx in sort_by_name_idx]
info['chs'] = [chans[pos] for pos in sort_by_name_idx]
info['order'] = sort_by_name_idx
else:
info['chs'] = chans
info['order'] = np.arange(len(chans))
# finally add some important fields from the config
info['e_table'] = cfg['user_blocks'][BTI.UB_B_E_TABLE_USED]
info['weights'] = cfg['user_blocks'][BTI.UB_B_WEIGHTS_USED]
return info
def _correct_trans(t, check=True):
"""Convert to a transformation matrix."""
t = np.array(t, np.float64)
t[:3, :3] *= t[3, :3][:, np.newaxis] # apply scalings
t[3, :3] = 0. # remove them
if check:
assert t[3, 3] == 1.
else:
t[3, 3] = 1.
return t
class RawBTi(BaseRaw):
"""Raw object from 4D Neuroimaging MagnesWH3600 data.
Parameters
----------
pdf_fname : str
Path to the processed data file (PDF).
config_fname : str
Path to system config file.
head_shape_fname : str | None
Path to the head shape file.
rotation_x : float
Degrees to tilt x-axis for sensor frame misalignment. Ignored
if convert is True.
translation : array-like, shape (3,)
The translation to place the origin of coordinate system
to the center of the head. Ignored if convert is True.