code: def test_digits_cosine_lazy_object():
      model1 = FacilityLocationSelection(100)
      model2 = GraphCutSelection(100)
      model = MixtureSelection(
          100,
          [model1, model2],
          [1.0, 0.3],
          metric="cosine",
          optimizer=LazyGreedy(random_state=0),
      )
      model.fit(X_digits)
      assert_array_equal(model.ranking, digits_cosine_ranking)
      assert_array_almost_equal(model.gains, digits_cosine_gains, 4)
      assert_array_almost_equal(model.subset, X_digits[model.ranking])
  
imports: import scipy
  import numpy
  from apricot import MixtureSelection
  from apricot import FacilityLocationSelection
  from apricot import GraphCutSelection
  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 34 for calling a global function with example usage: test_digits_cosine_lazy_object() without return types