class_docstr: Breslow's estimator of the cumulative hazard function.
  
  Attributes
  ----------
  cum_baseline_hazard_ : :class:`sksurv.functions.StepFunction`
      Cumulative baseline hazard function.
  
  baseline_survival_ : :class:`sksurv.functions.StepFunction`
      Baseline survival function.
  
  unique_times_ : ndarray
      Unique event times.
docstr: Predict survival function.
  
  Parameters
  ----------
  linear_predictor : array-like, shape = (n_samples,)
      Linear predictor of risk: `X @ coef`.
  
  Returns
  -------
  survival : ndarray, shape = (n_samples,)
      Predicted survival functions.
docstr_tok: ["Predict","survival","function",".","Parameters","--","--","--","--","--","linear_predictor",":","array-like",",","shape","=","(","n_samples",",",")","Linear","predictor","of","risk",":","`","X","@","coef","`",".","Returns","--","--","--","-","survival",":","ndarray",",","shape","=","(","n_samples",",",")","Predicted","survival","functions","."]
code: def get_survival_function(self, linear_predictor):
      """Predict survival function.
  
      Parameters
      ----------
      linear_predictor : array-like, shape = (n_samples,)
          Linear predictor of risk: `X @ coef`.
  
      Returns
      -------
      survival : ndarray, shape = (n_samples,)
          Predicted survival functions.
      """
      risk_score = np.exp(linear_predictor)
      n_samples = risk_score.shape[0]
      funcs = np.empty(n_samples, dtype=object)
      for i in range(n_samples):
          funcs[i] = StepFunction(
              x=self.baseline_survival_.x,
              y=np.power(self.baseline_survival_.y, risk_score[i]),
          )
      return funcs
  
imports: import numbers
  import warnings
  import numpy
  from scipy.linalg import solve
  from sklearn.base import BaseEstimator
  from sklearn.exceptions import ConvergenceWarning
  from sklearn.utils._param_validation import Interval, StrOptions
  from sklearn.utils.validation import check_array, check_is_fitted
  from ..base import SurvivalAnalysisMixin
  from ..functions import StepFunction
  from ..nonparametric import _compute_counts
  from ..util import check_array_survival
label_desc: Use image node_id 3 for calling the BreslowEstimator obj's underlying member method code with example usage: obj.get_survival_function(linear_predictor) and returns: funcs