code: def test_moa_static_norepeat(self):
      score = moa(
          self.scores,
          3,
          method="static",
          bootstrap_estimators=False,
          random_state=42,
      )
  
      assert_equal(score.shape, (4,))
  
      shuffled_list = shuffle(list(range(0, 6, 1)), random_state=42)
      manual_scores = np.zeros([4, 3])
      manual_scores[:, 0] = np.mean(
          self.scores[:, shuffled_list[0:2]], axis=1
      )
      manual_scores[:, 1] = np.mean(
          self.scores[:, shuffled_list[2:4]], axis=1
      )
      manual_scores[:, 2] = np.mean(
          self.scores[:, shuffled_list[4:6]], axis=1
      )
  
      manual_score = np.max(manual_scores, axis=1)
      assert_array_equal(score, manual_score)
  
imports: from __future__ import division
  from __future__ import print_function
  import os
  import sys
  import unittest
  import numpy
  from numpy.testing import assert_allclose
  from numpy.testing import assert_array_equal
  from numpy.testing import assert_equal
  from numpy.testing import assert_raises
  from sklearn.utils import shuffle
  from pyod.models.combination import aom
  from pyod.models.combination import moa
  from pyod.models.combination import average
  from pyod.models.combination import maximization
  from pyod.models.combination import median
  from pyod.models.combination import majority_vote
label_desc: Use image node_id 2 for calling the TestMOA obj's underlying member method code with example usage: obj.test_moa_static_norepeat() without return types