docstr: Return survival functions.
  
  Parameters
  ----------
  baseline_model : sksurv.linear_model.coxph.BreslowEstimator
      Estimator of baseline survival function.
  
  prediction : array-like, shape=(n_samples,)
      Predicted risk scores.
  
  return_array : bool
      If True, return a float array of the survival function
      evaluated at the unique event times, otherwise return
      an array of :class:`sksurv.functions.StepFunction` instances.
  
  Returns
  -------
  survival : ndarray
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code: def _predict_survival_function(
      self, baseline_model, prediction, return_array
  ):
      """Return survival functions.
  
      Parameters
      ----------
      baseline_model : sksurv.linear_model.coxph.BreslowEstimator
          Estimator of baseline survival function.
  
      prediction : array-like, shape=(n_samples,)
          Predicted risk scores.
  
      return_array : bool
          If True, return a float array of the survival function
          evaluated at the unique event times, otherwise return
          an array of :class:`sksurv.functions.StepFunction` instances.
  
      Returns
      -------
      survival : ndarray
      """
      return self._predict_function(
          "get_survival_function",
          baseline_model,
          prediction,
          return_array,
      )
  
imports: import numpy
label_desc: Use image node_id 2 for calling the SurvivalAnalysisMixin obj's underlying member method code with example usage: obj._predict_survival_function(baseline_model, prediction, return_array) and returns: self