code: def test_unsupervised_filter(selector):
      """Check support for unsupervised feature selection for the filter that could
      require only `X`.
      """
      rng = np.random.RandomState(0)
      X = rng.randn(10, 5)
  
      def score_func(X, y=None):
          return np.array([1, 1, 1, 1, 0])
  
      selector.set_params(score_func=score_func)
      selector.fit(X)
      X_trans = selector.transform(X)
      assert_allclose(X_trans, X[:, :4])
      X_trans = selector.fit_transform(X)
      assert_allclose(X_trans, X[:, :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 37 for calling a global function with example usage: test_unsupervised_filter(selector) and returns: np