code: def test_isotonic_regression_reversed():
      y = np.array([10, 9, 10, 7, 6, 6.1, 5])
      y_ = IsotonicRegression(increasing=False).fit_transform(
          np.arange(len(y)), y
      )
      assert_array_equal(
          np.ones(y_[:-1].shape), ((y_[:-1] - y_[1:]) >= 0)
      )
  
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 13 for calling a global function with example usage: test_isotonic_regression_reversed() without return types