code: def test_ellipse_model_estimate_failers():
      # estimate parameters of real data
      model = EllipseModel()
      warning_message = (
          "Standard deviation of data is too small to estimate "
          "ellipse with meaningful precision."
      )
      with pytest.warns(
          RuntimeWarning, match=warning_message
      ) as _warnings:
          assert not model.estimate(np.ones((6, 2)))
      # Check that stacklevel is correct
      assert len(_warnings) == 1
      assert _warnings[0].filename == __file__
  
      assert not model.estimate(
          np.array([[50, 80], [51, 81], [52, 80]])
      )
  
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 19 for calling a global function with example usage: test_ellipse_model_estimate_failers() without return types