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)))