code: def test_f_oneway_ints():
      # Smoke test f_oneway on integers: that it does raise casting errors
      # with recent numpys
      rng = np.random.RandomState(0)
      X = rng.randint(10, size=(10, 10))
      y = np.arange(10)
      fint, pint = f_oneway(X, y)
  
      # test that is gives the same result as with float
      f, p = f_oneway(X.astype(float), y)
      assert_array_almost_equal(f, fint, decimal=4)
      assert_array_almost_equal(p, pint, decimal=4)
  
imports: import itertools
  import warnings
  import numpy
  import pytest
  from numpy.testing import assert_allclose
  from scipy import sparse, stats
  from sklearn.datasets import load_iris, make_classification, make_regression
  from sklearn.feature_selection import GenericUnivariateSelect, SelectFdr, SelectFpr, SelectFwe, SelectKBest, SelectPercentile, chi2, f_classif, f_oneway, f_regression, mutual_info_classif, mutual_info_regression, r_regression
  from sklearn.utils import safe_mask
  from sklearn.utils._testing import _convert_container, assert_almost_equal, assert_array_almost_equal, assert_array_equal, ignore_warnings
  from sklearn.utils.fixes import CSR_CONTAINERS
label_desc: Use image node_id 2 for calling a global function with example usage: test_f_oneway_ints() without return types