class_docstr: Callable step function.
  
  .. math::
  
      f(z) = a * y_i + b,
      x_i \leq z < x_{i + 1}
  
  Parameters
  ----------
  x : ndarray, shape = (n_points,)
      Values on the x axis in ascending order.
  
  y : ndarray, shape = (n_points,)
      Corresponding values on the y axis.
  
  a : float, optional, default: 1.0
      Constant to multiply by.
  
  b : float, optional, default: 0.0
      Constant offset term.
  
  domain : tuple, optional
      A tuple with two entries that sets the limits of the
      domain of the step function.
      If entry is `None`, use the first/last value of `x` as limit.
docstr: Returns the domain of the function, that means
  the range of values that the function accepts.
  
  Returns
  -------
  lower_limit : float
      Lower limit of domain.
  
  upper_limit : float
      Upper limit of domain.
docstr_tok: ["Returns","the","domain","of","the","function",",","that","means","the","range","of","values","that","the","function","accepts",".","Returns","--","--","--","-","lower_limit",":","float","Lower","limit","of","domain",".","upper_limit",":","float","Upper","limit","of","domain","."]
code: def domain(self):
      """Returns the domain of the function, that means
      the range of values that the function accepts.
  
      Returns
      -------
      lower_limit : float
          Lower limit of domain.
  
      upper_limit : float
          Upper limit of domain.
      """
      return self._domain
  
file_path: scikit-survival/sksurv/functions.py
imports: import numpy
  from sklearn.utils import check_consistent_length
label_desc: Use image node_id 2 for calling the StepFunction obj's underlying member method code with example usage: obj.domain() and returns: self