code: def test_ellipse_model_estimate_from_data():
      data = np.array(
          [
              [264, 854],
              [265, 875],
              [268, 863],
              [270, 857],
              [275, 905],
              [285, 915],
              [305, 925],
              [324, 934],
              [335, 764],
              [336, 915],
              [345, 925],
              [345, 945],
              [354, 933],
              [355, 745],
              [364, 936],
              [365, 754],
              [375, 745],
              [375, 735],
              [385, 736],
              [395, 735],
              [394, 935],
              [405, 727],
              [415, 736],
              [415, 727],
              [425, 727],
              [426, 929],
              [435, 735],
              [444, 933],
              [445, 735],
              [455, 724],
              [465, 934],
              [465, 735],
              [475, 908],
              [475, 726],
              [485, 753],
              [485, 728],
              [492, 762],
              [495, 745],
              [491, 910],
              [493, 909],
              [499, 904],
              [505, 905],
              [504, 747],
              [515, 743],
              [516, 752],
              [524, 855],
              [525, 844],
              [525, 885],
              [533, 845],
              [533, 873],
              [535, 883],
              [545, 874],
              [543, 864],
              [553, 865],
              [553, 845],
              [554, 825],
              [554, 835],
              [563, 845],
              [565, 826],
              [563, 855],
              [563, 795],
              [565, 735],
              [573, 778],
              [572, 815],
              [574, 804],
              [575, 665],
              [575, 685],
              [574, 705],
              [574, 745],
              [575, 875],
              [572, 732],
              [582, 795],
              [579, 709],
              [583, 805],
              [583, 854],
              [586, 755],
              [584, 824],
              [585, 655],
              [581, 718],
              [586, 844],
              [585, 915],
              [587, 905],
              [594, 824],
              [593, 855],
              [590, 891],
              [594, 776],
              [596, 767],
              [593, 763],
              [603, 785],
              [604, 775],
              [603, 885],
              [605, 753],
              [605, 655],
              [606, 935],
              [603, 761],
              [613, 802],
              [613, 945],
              [613, 965],
              [615, 693],
              [617, 665],
              [623, 962],
              [624, 972],
              [625, 995],
              [633, 673],
              [633, 965],
              [633, 683],
              [633, 692],
              [633, 954],
              [634, 1016],
              [635, 664],
              [641, 804],
              [637, 999],
              [641, 956],
              [643, 946],
              [643, 926],
              [644, 975],
              [643, 655],
              [646, 705],
              [651, 664],
              [651, 984],
              [647, 665],
              [651, 715],
              [651, 725],
              [651, 734],
              [647, 809],
              [651, 825],
              [651, 873],
              [647, 900],
              [652, 917],
              [651, 944],
              [652, 742],
              [648, 811],
              [651, 994],
              [652, 783],
              [650, 911],
              [654, 879],
          ],
          dtype=np.int32,
      )
  
      # estimate parameters of real data
      model = EllipseModel()
      model.estimate(data)
  
      # test whether estimated parameters are smaller then 1000, so means stable
      assert_array_less(model.params[:4], np.full(4, 1000))
  
      # test whether all parameters are more than 0. Negative values were the
      # result of an integer overflow
      assert_array_less(np.zeros(4), np.abs(model.params[:4]))
  
imports: import numpy
  import pytest
  from skimage._shared import testing
  from skimage._shared._warnings import expected_warnings
  from skimage._shared.testing import arch32, assert_almost_equal, assert_array_less, assert_equal, xfail
  from skimage.measure import CircleModel, EllipseModel, LineModelND, ransac
  from skimage.measure.fit import _dynamic_max_trials
  from skimage.transform import AffineTransform
label_desc: Use image node_id 17 for calling a global function with example usage: test_ellipse_model_estimate_from_data() without return types