def read(self):
from MatlabIO import read_single_matlab_matrix_as_numpy_structured_array
# extract matlab matrix (called 'events') as numpy structured array
struct_array = read_single_matlab_matrix_as_numpy_structured_array(self.__event_file, 'events')
evs = Events(struct_array)
if self.eliminate_events_with_no_eeg:
# eliminating events that have no eeg file
indicator = np.empty(len(evs), dtype=bool)
for i, ev in enumerate(evs):
indicator[i] = (type(evs[i].eegfile).__name__.startswith('unicode')) & (len(str(evs[i].eegfile)) > 3)
evs = evs[indicator]
self.__events = evs
return self.__events
def read(self):
from MatlabIO import read_single_matlab_matrix_as_numpy_structured_array
# extract matlab matrix (called 'events') as numpy structured array
struct_array = read_single_matlab_matrix_as_numpy_structured_array(
self.__event_file, 'events')
evs = Events(struct_array)
if self.eliminate_events_with_no_eeg:
# eliminating events that have no eeg file
indicator = np.empty(len(evs), dtype=bool)
indicator[:] = False
for i, ev in enumerate(evs):
indicator[i] = (type(
evs[i].eegfile).__name__.startswith('unicode')) & (len(
str(evs[i].eegfile)) > 3)
evs = evs[indicator]
self.__events = evs
return self.__events
def get_sub_events(task, sub, eliminate_events_with_no_eeg=True, rhino_prefix='/', ignore_no_params=False):
"""Returns all events for a given task and subject identifier
Keyword arguments:
task -- string of task name
sub -- string of subject identifier
eliminate_events_with_no_eeg -- (default: True) Do not return events for which no corresponding eeg file exists.
rhino_prefix -- (default: '/') To get data if rhino is mounted as an external volume from a local computer.
ignore_no_params -- (default: False) Automatically handles IOError when no params.txt file is found for a subject.
"""
from MatlabIO import read_single_matlab_matrix_as_numpy_structured_array
e_path = rhino_prefix+'/data/events/'+task+'/'+sub+'_events.mat'
# extract matlab matrix (called 'events') as numpy structured array
struct_array = read_single_matlab_matrix_as_numpy_structured_array(e_path, 'events')
evs = Events(struct_array)
if eliminate_events_with_no_eeg:
# eliminating events that have no eeg file
indicator = np.empty(len(evs), dtype=bool)
indicator[:] = False
for i, ev in enumerate(evs):
indicator[i] = (type(evs[i].eegfile).__name__.startswith('unicode')) & (len(str(evs[i].eegfile)) > 3)
#Due to numpy upgrade
evs = Events(evs[indicator])
evs = evs.add_fields(esrc=np.dtype(RawBinWrapper))
import pathlib
#This may throw and error for a few subjects who have no params file. Should be written to handle this elegantly.
if ignore_no_params:
try:
for ev in evs:
try:
eeg_file_path = join(rhino_prefix, str(pathlib.Path(str(ev.eegfile)).parts[1:]))
ev.esrc = RawBinWrapper(eeg_file_path)
#self.raw_data_root=str(eeg_file_path)
except TypeError:
print 'skipping event with eegfile=',ev.eegfile
pass
except IOError:
print('No params.txt or .params file found for '+sub)
else:
for ev in evs:
try:
eeg_file_path = join(rhino_prefix, str(pathlib.Path(str(ev.eegfile)).parts[1:]))
ev.esrc = RawBinWrapper(eeg_file_path)
#self.raw_data_root=str(eeg_file_path)
except TypeError:
print 'skipping event with eegfile=',ev.eegfile
pass
return(evs)
