code: def test_fortran_get_column(test_data):
      X = test_data["X"]
      fds = test_data["fortran_dataset"]
      ind = np.arange(X.shape[0])
      for j in range(X.shape[1]):
          indices, data, n_nz = fds.get_column(j)
          np.testing.assert_array_equal(indices, ind)
          np.testing.assert_array_equal(data, X[:, j])
          assert n_nz == X.shape[0]
  
file_path: lightning/lightning/impl/tests/test_dataset.py
imports: import pickle
  import numpy
  import pytest
  import scipy.sparse
  from sklearn.datasets import make_classification
  from sklearn.utils import check_random_state
  from lightning.impl.dataset_fast import ContiguousDataset
  from lightning.impl.dataset_fast import FortranDataset
  from lightning.impl.dataset_fast import CSRDataset
  from lightning.impl.dataset_fast import CSCDataset
label_desc: Use image node_id 4 for calling a global function with example usage: test_fortran_get_column(test_data) without return types