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# Author: Joan Massich <mailsik@gmail.com>
#
# License: BSD-3-Clause
import numpy as np
import os.path as op
from io import BytesIO
from ...annotations import Annotations
from .res4 import _read_res4
from .info import _convert_time
def _get_markers(fname):
def consume(fid, predicate): # just a consumer to move around conveniently
while predicate(fid.readline()):
pass
def parse_marker(string): # XXX: there should be a nicer way to do that
data = np.genfromtxt(
BytesIO(string.encode()), dtype=[('trial', int), ('sync', float)])
return int(data['trial']), float(data['sync'])
markers = dict()
with open(fname) as fid:
consume(fid, lambda line: not line.startswith('NUMBER OF MARKERS:'))
num_of_markers = int(fid.readline())
for _ in range(num_of_markers):
consume(fid, lambda line: not line.startswith('NAME:'))
label = fid.readline().strip('\n')
consume(
fid, lambda line: not line.startswith('NUMBER OF SAMPLES:'))
n_markers = int(fid.readline())
consume(fid, lambda line: not line.startswith('LIST OF SAMPLES:'))
next(fid) # skip the samples header
markers[label] = [
parse_marker(next(fid)) for _ in range(n_markers)
]
return markers
def _get_res4_info_needed_by_markers(directory):
"""Get required information from CTF res4 information file."""
# we only need a few values from res4. Maybe we can read them directly
# instead of parsing the entire res4 file.
res4 = _read_res4(directory)
total_offset_duration = res4['pre_trig_pts'] / res4['sfreq']
trial_duration = res4['nsamp'] / res4['sfreq']
meas_date = (_convert_time(res4['data_date'],
res4['data_time']), 0)
return total_offset_duration, trial_duration, meas_date
def _read_annotations_ctf(directory):
total_offset, trial_duration, meas_date \
= _get_res4_info_needed_by_markers(directory)
return _read_annotations_ctf_call(directory, total_offset, trial_duration,
meas_date)
def _read_annotations_ctf_call(directory, total_offset, trial_duration,
meas_date):
fname = op.join(directory, 'MarkerFile.mrk')
if not op.exists(fname):
return Annotations(list(), list(), list(), orig_time=meas_date)
else:
markers = _get_markers(fname)
onset = [synctime + (trialnum * trial_duration) + total_offset
for _, m in markers.items() for (trialnum, synctime) in m]
description = np.concatenate([
np.repeat(label, len(m)) for label, m in markers.items()
])
return Annotations(onset=onset, duration=np.zeros_like(onset),
description=description, orig_time=meas_date)
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