code: def test_isotonic_regression_ties_max():
      # Setup examples with ties on maximum
      x = [1, 2, 3, 4, 5, 5]
      y = [1, 2, 3, 4, 5, 6]
      y_true = [1, 2, 3, 4, 5.5, 5.5]
  
      # Check that we get identical results for fit/transform and fit_transform
      ir = IsotonicRegression()
      ir.fit(x, y)
      assert_array_equal(
          ir.fit(x, y).transform(x), ir.fit_transform(x, y)
      )
      assert_array_equal(y_true, ir.fit_transform(x, y))
  
imports: import copy
  import pickle
  import warnings
  import numpy
  import pytest
  from scipy.special import expit
  import sklearn
  from sklearn.datasets import make_regression
  from sklearn.isotonic import IsotonicRegression, _make_unique, check_increasing, isotonic_regression
  from sklearn.utils import shuffle
  from sklearn.utils._testing import assert_allclose, assert_array_almost_equal, assert_array_equal
  from sklearn.utils.validation import check_array
label_desc: Use image node_id 10 for calling a global function with example usage: test_isotonic_regression_ties_max() without return types