docstr: Checks whether array of scores from (6 4) is correct.
  
  Data is derived from Saltelli et al. 2008,
  in the solution to exercise 3a, Chapter 3, page 134.
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code: def test_scores_from_find_most_distant(self, setup_input):
      """
      Checks whether array of scores from (6 4) is correct.
  
      Data is derived from Saltelli et al. 2008,
      in the solution to exercise 3a, Chapter 3, page 134.
  
      """
      sample_inputs = setup_input
      N = 6
      num_params = 2
      k_choices = 4
      strategy = BruteForce()
      output = strategy.find_most_distant(
          sample_inputs, N, num_params, k_choices
      )
      expected = np.array(
          [
              15.022,
              13.871,
              14.815,
              14.582,
              16.178,
              14.912,
              15.055,
              16.410,
              15.685,
              16.098,
              14.049,
              15.146,
              14.333,
              14.807,
              14.825,
          ],
          dtype=np.float32,
      )
  
      assert_allclose(output, expected, rtol=1e-1, atol=1e-2)
  
imports: from SALib.sample.morris import SampleMorris, LocalOptimisation, BruteForce
  from SALib.sample.morris.morris import _sample_morris
  from SALib.util import read_param_file
  import numpy
  from numpy.testing import assert_equal, assert_allclose
  import numpy.random
  import pytest
  from pytest import fixture, raises
label_desc: Use image node_id 2 for calling the TestBruteForceMethods obj's underlying member method code with example usage: obj.test_scores_from_find_most_distant(setup_input) without return types