code: def test_omp_cv():
      y_ = y[:, 0]
      gamma_ = gamma[:, 0]
      ompcv = OrthogonalMatchingPursuitCV(
          fit_intercept=False, max_iter=10
      )
      ompcv.fit(X, y_)
      assert ompcv.n_nonzero_coefs_ == n_nonzero_coefs
      assert_array_almost_equal(ompcv.coef_, gamma_)
      omp = OrthogonalMatchingPursuit(
          fit_intercept=False, n_nonzero_coefs=ompcv.n_nonzero_coefs_
      )
      omp.fit(X, y_)
      assert_array_almost_equal(ompcv.coef_, omp.coef_)
  
imports: import numpy
  import pytest
  from sklearn.datasets import make_sparse_coded_signal
  from sklearn.linear_model import LinearRegression, OrthogonalMatchingPursuit, OrthogonalMatchingPursuitCV, orthogonal_mp, orthogonal_mp_gram
  from sklearn.utils import check_random_state
  from sklearn.utils._testing import assert_allclose, assert_array_almost_equal, assert_array_equal, ignore_warnings
label_desc: Use image node_id 17 for calling a global function with example usage: test_omp_cv() without return types