code: def _assert_least_squares(tf, src, dst):
      baseline = np.sum((tf(src) - dst) ** 2)
      for i in range(tf.params.size):
          for update in [0.001, -0.001]:
              params = np.copy(tf.params)
              params.flat[i] += update
              new_tf = tf.__class__(matrix=params)
              new_ssq = np.sum((new_tf(src) - dst) ** 2)
              assert new_ssq > baseline
  
imports: import re
  import textwrap
  import numpy
  import pytest
  from numpy.testing import assert_almost_equal, assert_array_almost_equal, assert_equal
  from skimage.transform import AffineTransform, EssentialMatrixTransform, EuclideanTransform, FundamentalMatrixTransform, PiecewiseAffineTransform, PolynomialTransform, ProjectiveTransform, SimilarityTransform, estimate_transform, matrix_transform
  from skimage.transform._geometric import _GeometricTransform, _affine_matrix_from_vector, _center_and_normalize_points, _euler_rotation_matrix
label_desc: Use image node_id 41 for calling a global function with example usage: _assert_least_squares(tf, src, dst) without return types