docstr: Call predict_survival_function on the estimator.
  
  Only available if estimator supports ``predict_survival_function``.
  
  Parameters
  ----------
  X : indexable, length n_samples
      Must fulfill the input assumptions of the
      underlying estimator.
docstr_tok: ["Call","predict_survival_function","on","the","estimator",".","Only","available","if","estimator","supports","``","predict_survival_function","``",".","Parameters","--","--","--","--","--","X",":","indexable",",","length","n_samples","Must","fulfill","the","input","assumptions","of","the","underlying","estimator","."]
code: def predict_survival_function(self, X):
      """Call predict_survival_function on the estimator.
  
      Only available if estimator supports ``predict_survival_function``.
  
      Parameters
      ----------
      X : indexable, length n_samples
          Must fulfill the input assumptions of the
          underlying estimator.
      """
      check_is_fitted(self, "estimator_")
      return self.estimator_.predict_survival_function(X)
  
imports: import numpy
  from sklearn.base import BaseEstimator
  from sklearn.utils import check_array, check_consistent_length
  from sklearn.utils.metaestimators import available_if
  from sklearn.utils.validation import check_is_fitted
  from .exceptions import NoComparablePairException
  from .nonparametric import CensoringDistributionEstimator, SurvivalFunctionEstimator
  from .util import check_y_survival
label_desc: Use image node_id 8 for calling the _ScoreOverrideMixin obj's underlying member method code with example usage: obj.predict_survival_function(X) and returns: self