code: def test_digits_two_stage_init():
      model = MaxCoverageSelection(
          100, optimizer="two-stage", initial_subset=digits_ranking[:5]
      )
      model.fit(X_digits)
      assert_array_equal(model.ranking[:10], digits_ranking[5:15])
      assert_array_almost_equal(model.gains[:10], digits_gains[5:15], 4)
      assert_array_almost_equal(model.subset, X_digits[model.ranking])
  
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 6 for calling a global function with example usage: test_digits_two_stage_init() without return types