code: def test_bilinearity(self):
      x = [1, 1, 1, 2, 2, 2, 3, 3, 3]
      y = [1, 2, 3, 1, 2, 3, 1, 2, 3]
      z = [0, 7, 8, 3, 4, 7, 1, 3, 4]
      s = 0.1
      tx = [1 + s, 3 - s]
      ty = [1 + s, 3 - s]
      with suppress_warnings() as sup:
          # This seems to fail (ier=1, see ticket 1642).
          sup.filter(UserWarning, "\nThe coefficients of the spline")
          lut = LSQBivariateSpline(x, y, z, tx, ty, kx=1, ky=1)
  
      tx, ty = lut.get_knots()
      for xa, xb in zip(tx[:-1], tx[1:]):
          for ya, yb in zip(ty[:-1], ty[1:]):
              for t in [0.1, 0.5, 0.9]:
                  for s in [0.3, 0.4, 0.7]:
                      xp = xa * (1 - t) + xb * t
                      yp = ya * (1 - s) + yb * s
                      zp = (
                          +lut(xa, ya) * (1 - t) * (1 - s)
                          + lut(xb, ya) * t * (1 - s)
                          + lut(xa, yb) * (1 - t) * s
                          + lut(xb, yb) * t * s
                      )
                      assert_almost_equal(lut(xp, yp), zp)
  
imports: from __future__ import division, print_function, absolute_import
  import numpy
  from numpy.testing import assert_equal, assert_almost_equal, assert_array_equal, assert_array_almost_equal, assert_allclose
  from scipy._lib._numpy_compat import suppress_warnings
  from pytest import raises
  from numpy import array, diff, linspace, meshgrid, ones, pi, shape
  from scipy.interpolate.fitpack import bisplrep, bisplev
  from scipy.interpolate.fitpack2 import UnivariateSpline, LSQUnivariateSpline, InterpolatedUnivariateSpline, LSQBivariateSpline, SmoothBivariateSpline, RectBivariateSpline, LSQSphereBivariateSpline, SmoothSphereBivariateSpline, RectSphereBivariateSpline
label_desc: Use image node_id 2 for calling the TestLSQBivariateSpline obj's underlying member method code with example usage: obj.test_bilinearity() without return types