code: def test_digits_approximate_sparse():
      model = MaxCoverageSelection(100, optimizer="approximate-lazy")
      model.fit(X_digits_sparse)
      assert_array_equal(model.ranking, digits_approx_ranking)
      assert_array_almost_equal(model.gains, digits_approx_gains, 4)
      assert_array_almost_equal(
          model.subset, X_digits_sparse[model.ranking].toarray()
      )
  
imports: import scipy
  import numpy
  from apricot import MaxCoverageSelection
  from apricot.optimizers import *
  from sklearn.datasets import load_digits
  from sklearn.metrics import pairwise_distances
  from numpy.testing import assert_almost_equal
  from numpy.testing import assert_array_equal
  from numpy.testing import assert_array_almost_equal
label_desc: Use image node_id 37 for calling a global function with example usage: test_digits_approximate_sparse() without return types