code: def test_lower_bound_yi_x_y(x, y, float_desired):
      """Test '_lower_bound_yi_x_y' function."""
      x, y = np.asarray(x), np.asarray(y)
      float_actual = _lower_bound_yi_x_y(
          x, min(x), max(x), y, min(y), max(y)
      )
      np.testing.assert_allclose(
          float_actual, float_desired, atol=1e-5, rtol=0
      )
  
imports: import numpy
  import pytest
  import re
  from math import sqrt
  from pyts.metrics.lower_bounds import _lower_bound_yi_x_y, _lower_bound_yi_X_Y, _warping_envelope, _clip
  from pyts.metrics import lower_bound_improved, lower_bound_keogh, lower_bound_kim, lower_bound_yi
  from pyts.metrics import dtw, sakoe_chiba_band
  from pyts.metrics.dtw import _dtw_sakoechiba
  from sklearn.metrics import pairwise_distances
label_desc: Use image node_id 2 for calling a global function with example usage: test_lower_bound_yi_x_y(x, y, float_desired) without return types