old_contents: import numpy as np
  
  def Y_from_censored(T,E=None):
      if T is None:
          return None
      if E is None:
      	E = np.ones_like(T)
      Y = np.empty(dtype=[('Event', np.bool), ('Time', np.float64)],
                   shape=T.shape[0])
      Y['Event'] = E.astype(bool)
      Y['Time'] = T.astype(float)
      return Y
new_contents: import numpy as np
  
  def Y_from_censored(T,E=None):
      if T is None:
          return None
      if E is None:
      	E = np.ones_like(T)
      Y = np.empty(dtype=[('Event', bool), ('Time', np.float64)],
                   shape=T.shape[0])
      Y['Event'] = E.astype(bool)
      Y['Time'] = T.astype(float)
      return Y
subject: Update helpers.py