code: def _check_estimate_1d(estimate, test_time):
      estimate = check_array(
          estimate, ensure_2d=False, input_name="estimate"
      )
      if estimate.ndim != 1:
          raise ValueError(
              f"Expected 1D array, got {estimate.ndim}D array instead:\narray={estimate}.\n"
          )
      check_consistent_length(test_time, estimate)
      return estimate
  
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 1 for calling a global function with example usage: _check_estimate_1d(estimate, test_time) and returns: estimate