code: def test_nystroem_callable():
      # Test Nystroem on a callable.
      rnd = np.random.RandomState(42)
      n_samples = 10
      X = rnd.uniform(size=(n_samples, 4))
  
      def logging_histogram_kernel(x, y, log):
          """Histogram kernel that writes to a log."""
          log.append(1)
          return np.minimum(x, y).sum()
  
      kernel_log = []
      X = list(X)  # test input validation
      Nystroem(
          kernel=logging_histogram_kernel,
          n_components=(n_samples - 1),
          kernel_params={"log": kernel_log},
      ).fit(X)
      assert len(kernel_log) == n_samples * (n_samples - 1) / 2
  
      # if degree, gamma or coef0 is passed, we raise a ValueError
      msg = "Don't pass gamma, coef0 or degree to Nystroem"
      params = ({"gamma": 1}, {"coef0": 1}, {"degree": 2})
      for param in params:
          ny = Nystroem(
              kernel=_linear_kernel,
              n_components=(n_samples - 1),
              **param,
          )
          with pytest.raises(ValueError, match=msg):
              ny.fit(X)
  
imports: import re
  import numpy
  import pytest
  from sklearn.datasets import make_classification
  from sklearn.kernel_approximation import AdditiveChi2Sampler, Nystroem, PolynomialCountSketch, RBFSampler, SkewedChi2Sampler
  from sklearn.metrics.pairwise import chi2_kernel, kernel_metrics, polynomial_kernel, rbf_kernel
  from sklearn.utils._testing import assert_allclose, assert_array_almost_equal, assert_array_equal
  from sklearn.utils.fixes import CSR_CONTAINERS
label_desc: Use image node_id 21 for calling a global function with example usage: test_nystroem_callable() and returns: np