code: def test_isotonic_sample_weight():
      ir = IsotonicRegression()
      x = [1, 2, 3, 4, 5, 6, 7]
      y = [1, 41, 51, 1, 2, 5, 24]
      sample_weight = [1, 2, 3, 4, 5, 6, 7]
      expected_y = [1, 13.95, 13.95, 13.95, 13.95, 13.95, 24]
      received_y = ir.fit_transform(x, y, sample_weight=sample_weight)
  
      assert_array_equal(expected_y, received_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 19 for calling a global function with example usage: test_isotonic_sample_weight() without return types