def transform(self, durations, events):
durations = _values_if_series(durations)
durations = durations.astype(self._dtype)
events = _values_if_series(events)
dur_disc, events = self.duc.transform(durations, events)
idx_durations = self.di.transform(dur_disc)
cut_diff = np.diff(self.cuts)
assert (cut_diff > 0).all(), 'Cuts are not unique.'
t_frac = 1. - (dur_disc - durations) / cut_diff[idx_durations - 1]
if idx_durations.min() == 0:
warnings.warn(
"""Got event/censoring at start time. Should be removed! It is set s.t. it has no contribution to loss."""
)
t_frac[idx_durations == 0] = 0
events[idx_durations == 0] = 0
idx_durations = idx_durations - 1
return idx_durations, events.astype('float32'), t_frac.astype(
'float32')
def transform(self, durations, events):
durations = _values_if_series(durations)
durations = durations.astype(self._dtype)
events = _values_if_series(events)
idx_durations, events = self.idu.transform(durations, events)
return idx_durations, events.astype('float32')