def create_y_signal(cnt):
if has_fixed_trial_len(cnt):
return create_y_signal_fixed_trial_len(cnt, trial_len=int(cnt.fs*4))
else:
return create_cnt_y_start_end_marker(cnt,
start_marker_def=dict((('1',[1]), ('2', [2]), ('3',[3]), ('4', [4]))),
end_marker_def=dict((('1',[5]), ('2', [6]), ('3',[7]), ('4', [8]))),
segment_ival=(0,0), timeaxis=-2)
def create_cnt_y_by_signal_processor(self):
if self.end_marker_def is None:
self.y = create_cnt_y(self.signal_processor.cnt,
self.signal_processor.segment_ival,
self.signal_processor.marker_def, timeaxis=-2)
else:
self.y = create_cnt_y_start_end_marker(self.signal_processor.cnt,
self.signal_processor.marker_def, self.end_marker_def,
self.signal_processor.segment_ival, timeaxis=-2)
def create_y_signal(cnt):
if has_fixed_trial_len(cnt):
return create_y_signal_fixed_trial_len(cnt, trial_len=int(cnt.fs * 4))
else:
return create_cnt_y_start_end_marker(cnt,
start_marker_def=dict(
(('1', [1]), ('2', [2]),
('3', [3]), ('4', [4]))),
end_marker_def=dict(
(('1', [5]), ('2', [6]),
('3', [7]), ('4', [8]))),
segment_ival=(0, 0),
timeaxis=-2)
def create_cnt_y_by_signal_processor(self):
if self.end_marker_def is None:
self.y = create_cnt_y(
self.signal_processor.cnt,
self.signal_processor.segment_ival,
self.signal_processor.marker_def,
timeaxis=-2,
)
else:
self.y = create_cnt_y_start_end_marker(
self.signal_processor.cnt,
self.signal_processor.marker_def,
self.end_marker_def,
self.signal_processor.segment_ival,
timeaxis=-2,
)
def create_y_labels(cnt):
classes = np.unique([m[1] for m in cnt.markers])
if np.array_equal(range(1,5), classes):
return create_y_labels_fixed_trial_len(cnt, trial_len=int(cnt.fs*4))
elif np.array_equal(range(1,9), classes):
y_signal = create_cnt_y_start_end_marker(cnt,
start_marker_def=dict((('1',[1]), ('2', [2]), ('3',[3]), ('4', [4]))),
end_marker_def=dict((('1',[5]), ('2', [6]), ('3',[7]), ('4', [8]))),
segment_ival=(0,0), timeaxis=-2)
y_labels = np.zeros((cnt.data.shape[0]), dtype=np.int32)
y_labels[y_signal[:,0] == 1] = 1
y_labels[y_signal[:,1] == 1] = 2
y_labels[y_signal[:,2] == 1] = 3
y_labels[y_signal[:,3] == 1] = 4
return y_labels
else:
raise ValueError("Expect classes 1,2,3,4, possibly with end markers "
"5,6,7,8, instead got {:s}".format(str(classes)))
def create_y_labels(cnt):
classes = np.unique([m[1] for m in cnt.markers])
if np.array_equal(range(1, 5), classes):
return create_y_labels_fixed_trial_len(cnt, trial_len=int(cnt.fs * 4))
elif np.array_equal(range(1, 9), classes):
y_signal = create_cnt_y_start_end_marker(cnt,
start_marker_def=dict(
(('1', [1]), ('2', [2]),
('3', [3]), ('4', [4]))),
end_marker_def=dict(
(('1', [5]), ('2', [6]),
('3', [7]), ('4', [8]))),
segment_ival=(0, 0),
timeaxis=-2)
y_labels = np.zeros((cnt.data.shape[0]), dtype=np.int32)
y_labels[y_signal[:, 0] == 1] = 1
y_labels[y_signal[:, 1] == 1] = 2
y_labels[y_signal[:, 2] == 1] = 3
y_labels[y_signal[:, 3] == 1] = 4
return y_labels
else:
raise ValueError("Expect classes 1,2,3,4, possibly with end markers "
"5,6,7,8, instead got {:s}".format(str(classes)))
