def test_eeg_read_incomplete_data(self):
e_path_incomplete = '/Volumes/rhino_root/data/events/RAM_PS/R1104D_events.mat'
if sys.platform.startswith('win'):
e_path_incomplete = 'D:/data/events/RAM_PS/R1104D_events.mat'
base_event_reader = BaseEventReader(filename=e_path_incomplete)
base_events = base_event_reader.read()
sess_1 = base_events[base_events.session == 1]
sess_3 = base_events[base_events.session == 3]
sess_5 = base_events[base_events.session == 5]
sess_7 = base_events[base_events.session == 7]
sess_1[440].eegoffset = 2000000000000
sess_1[444].eegoffset = 2000000000000
sess_1[434].eegoffset = 2000000000000
shuffled_sess_events = np.hstack((sess_3, sess_7, sess_1, sess_5)).view(np.recarray)
eeg_reader = EEGReader(events=shuffled_sess_events, channels=np.array(['002', '003']),
start_time=self.start_time, end_time=self.end_time, buffer_time=self.buffer_time)
base_eegs = eeg_reader.read()
if eeg_reader.removed_bad_data():
print('REMOVED BAD DATA !!!!!!!!!!!!!')
events = base_eegs['events'].data.view(np.recarray)
if not isinstance(events, Events):
events = Events(events)
from ptsa.data.rawbinwrapper import RawBinWrapper
events = events.add_fields(esrc=np.dtype(RawBinWrapper))
# ------------- using PTSAevent reader functions to prepare events for reading old-ptsa-style
ptsa_event_reader = PTSAEventReader()
ptsa_event_reader.attach_rawbinwrapper_groupped(events)
eegs = events.get_data(channels=['002', '003'], start_time=self.start_time, end_time=self.end_time,
buffer_time=self.buffer_time, eoffset='eegoffset', keep_buffer=True,
eoffset_in_time=False, verbose=True)
npt.assert_array_equal(eegs[:, :, :-1], base_eegs.data)
def read(self):
"""
Reads Matlab event file , converts it to np.recarray and attaches rawbinwrappers (if appropriate flags indicate so)
:return: Events object. depending on flagg settings the rawbinwrappers may be attached as well
"""
# calling base class read fcn
evs = BaseEventReader.read(self)
# in case evs is simply recarray
if not isinstance(evs, Events):
evs = Events(evs)
if self.attach_rawbinwrapper:
evs = evs.add_fields(esrc=np.dtype(RawBinWrapper))
if self.use_groupped_rawbinwrapper: # this should be default choice - much faster execution
self.attach_rawbinwrapper_groupped(evs)
else: # used for debugging purposes
self.attach_rawbinwrapper_individual(evs)
return evs
def read(self):
'''
Reads Matlab event file , converts it to np.recarray and attaches rawbinwrappers (if appropriate flags indicate so)
:return: Events object. depending on flagg settings the rawbinwrappers may be attached as well
'''
# calling base class read fcn
evs = BaseEventReader.read(self)
# in case evs is simply recarray
if not isinstance(evs, Events):
evs = Events(evs)
if self.attach_rawbinwrapper:
evs = evs.add_fields(esrc=np.dtype(RawBinWrapper))
if self.use_groupped_rawbinwrapper: # this should be default choice - much faster execution
self.attach_rawbinwrapper_groupped(evs)
else: # used for debugging purposes
self.attach_rawbinwrapper_individual(evs)
return evs
# sys.exit()
for field in matevs.dtype.names:
try:
newevs[field] = matevs[field]
except ValueError:
if ((field == 'stimAmp') and
(np.all(np.array(matevs[field],np.str)=='X'))):
matevs[field].fill(np.nan)
newevs[field] = matevs[field]
else: # not sure what's going on, so raise the same error as above
newevs[field] = matevs[field]
events = Events(newevs)
events = events.add_fields(esrc=np.dtype(RawBinWrapper))
good_indices = np.ones(len(events),np.bool)
for e,event in enumerate(events):
try:
event['esrc'] = RawBinWrapper(event['eegfile'])
except IOError:
print('No EEG files for',event['subject'],event['session'],event['eegfile'])
good_indices[e] = False
events = events[good_indices]
start_time = -0.6
end_time = 1.6
buf = 1
# sys.exit()
for field in matevs.dtype.names:
try:
newevs[field] = matevs[field]
except ValueError:
if ((field == 'stimAmp')
and (np.all(np.array(matevs[field], np.str) == 'X'))):
matevs[field].fill(np.nan)
newevs[field] = matevs[field]
else: # not sure what's going on, so raise the same error as above
newevs[field] = matevs[field]
events = Events(newevs)
events = events.add_fields(esrc=np.dtype(RawBinWrapper))
good_indices = np.ones(len(events), np.bool)
for e, event in enumerate(events):
try:
event['esrc'] = RawBinWrapper(event['eegfile'])
except IOError:
print('No EEG files for', event['subject'], event['session'],
event['eegfile'])
good_indices[e] = False
events = events[good_indices]
start_time = -0.6
end_time = 1.6
buf = 1
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)
'catFR2':{
'output_path': rhino_mount+'/data10/scratch/cweidema/RAM/RAM_catFR/RAM_catFR2_power/hdf5_files_sess',
'ev_file': rhino_mount+'/home1/cweidema/Christoph/Analyses/RAM/RAM_catFR/data/RAM_catFR2_events20151106.npy'
},
'FR1':{
'output_path': rhino_mount+'/data10/scratch/cweidema/RAM/RAM_FR/RAM_FR1_power/hdf5_files_sess',
'ev_file': rhino_mount+'/home1/cweidema/Christoph/Analyses/RAM/RAM_FR/data/RAM_FR1_events20151106.npy'
},
'FR2':{
'output_path': rhino_mount+'/data10/scratch/cweidema/RAM/RAM_FR/RAM_FR2_power/hdf5_files_sess',
'ev_file': rhino_mount+'/home1/cweidema/Christoph/Analyses/RAM/RAM_FR/data/RAM_FR2_events20151106.npy'
}
}
ev = Events(np.load(pow_params[exp]['ev_file']))
ev = ev.add_fields(esrc=np.dtype(RawBinWrapper))
ev = ev[ev['type']=='WORD']
good_indices = np.ones(len(ev),np.bool)
for e,event in enumerate(ev):
try:
event['esrc'] = RawBinWrapper(rhino_mount+event['eegfile'])
except IOError:
print('No EEG files for',event['subject'],event['session'],event['eegfile'])
good_indices[e] = False
ev = ev[good_indices]
start_time = -0.6
end_time = 1.6
buf = 1
baseline = (-.6,-.4)
