code: def test_find_best_matching_array_hypothesis(model, trials):
      model = np.array(model)
      for row in trials:
          row = np.array(row)
          corrected_row, diffsum = find_best_matching_array(row, model)
  
          assert len(corrected_row) == len(model)
          assert diffsum >= 0
  
file_path: pdftabextract/tests/test_clustering.py
imports: import pytest
  from hypothesis import given
  import hypothesis.strategies
  import numpy
  from scipy.stats import chisquare
  from pdftabextract.clustering import find_clusters_1d_break_dist, zip_clusters_and_values, calc_cluster_centers_1d, array_match_difference_1d, find_best_matching_array, adjust_bad_positions
label_desc: Use image node_id 7 for calling a global function with example usage: test_find_best_matching_array_hypothesis(model, trials) without return types