code: def test_adjustment():
      imga = zeros([128, 128])
  
      for y in range(128):
          for x in range(128):
              if 10 < y < 115 and 10 < x < 115:
                  imga[x, y] = 100
              if 39 < y < 88 and 39 < x < 88:
                  imga[x, y] = 150
              if 59 < y < 69 and 59 < x < 69:
                  imga[x, y] = 255
  
      high_1 = upper_bound_by_rate(imga)
      high_2 = upper_bound_by_percent(imga)
      vol1 = np.interp(imga, xp=[imga.min(), high_1], fp=[0, 255])
      vol2 = np.interp(imga, xp=[imga.min(), high_2], fp=[0, 255])
      count2 = (88 - 40) * (88 - 40)
      count1 = (114 - 10) * (114 - 10)
  
      count1_test = 0
      count2_test = 0
  
      count2_upper = (88 - 40) * (88 - 40)
      count1_upper = (114 - 10) * (114 - 10)
  
      count1_upper_test = 0
      count2_upper_test = 0
  
      value1 = np.unique(vol1)
      value2 = np.unique(vol2)
  
      for i in range(128):
          for j in range(128):
              if vol1[i][j] > value1[1]:
                  count2_test = count2_test + 1
              if vol1[i][j] > 0:
                  count1_test = count1_test + 1
  
      for i in range(128):
          for j in range(128):
              if vol2[i][j] > value2[1]:
                  count2_upper_test = count2_upper_test + 1
              if vol2[i][j] > 0:
                  count1_upper_test = count1_upper_test + 1
  
      assert_equal(count2, count2_test)
      assert_equal(count1, count1_test)
  
      assert_equal(count2_upper, count2_upper_test)
      assert_equal(count1_upper, count1_upper_test)
  
imports: import numpy
  from numpy import zeros
  from dipy.segment.threshold import upper_bound_by_percent, upper_bound_by_rate
  from numpy.testing import assert_equal
label_desc: Use image node_id 1 for calling a global function with example usage: test_adjustment() without return types