code: def test_complex_adaptive_false():
      # verify that series with adaptive=False is evaluated with discretized
      # ranges of type complex.
      if not np:
          skip("numpy not installed.")
  
      x, y, u = symbols("x y u")
  
      def do_test(data1, data2):
          assert len(data1) == len(data2)
          for d1, d2 in zip(data1, data2):
              assert np.allclose(d1, d2)
  
      expr1 = sqrt(x) * exp(-(x**2))
      expr2 = sqrt(u * x) * exp(-(x**2))
      s1 = LineOver1DRangeSeries(
          im(expr1), (x, -5, 5), adaptive=False, n=10
      )
      s2 = LineOver1DRangeSeries(
          im(expr2), (x, -5, 5), adaptive=False, n=10, params={u: 1}
      )
      data1 = s1.get_data()
      data2 = s2.get_data()
  
      do_test(data1, data2)
      assert (not np.allclose(data1[1], 0)) and (
          not np.allclose(data2[1], 0)
      )
  
      s1 = Parametric2DLineSeries(
          re(expr1), im(expr1), (x, -pi, pi), adaptive=False, n=10
      )
      s2 = Parametric2DLineSeries(
          re(expr2),
          im(expr2),
          (x, -pi, pi),
          adaptive=False,
          n=10,
          params={u: 1},
      )
      data1 = s1.get_data()
      data2 = s2.get_data()
      do_test(data1, data2)
      assert (not np.allclose(data1[1], 0)) and (
          not np.allclose(data2[1], 0)
      )
  
      s1 = SurfaceOver2DRangeSeries(
          im(expr1),
          (x, -5, 5),
          (y, -10, 10),
          adaptive=False,
          n1=30,
          n2=3,
      )
      s2 = SurfaceOver2DRangeSeries(
          im(expr2),
          (x, -5, 5),
          (y, -10, 10),
          adaptive=False,
          n1=30,
          n2=3,
          params={u: 1},
      )
      data1 = s1.get_data()
      data2 = s2.get_data()
      do_test(data1, data2)
      assert (not np.allclose(data1[1], 0)) and (
          not np.allclose(data2[1], 0)
      )
  
imports: from sympy import latex, exp, symbols, I, pi, sin, cos, tan, log, sqrt, re, im, arg, frac, Sum, S, Abs, lambdify, Function, dsolve, Eq, floor, Tuple
  from sympy.external import import_module
  from sympy.plotting.series import LineOver1DRangeSeries, Parametric2DLineSeries, Parametric3DLineSeries, SurfaceOver2DRangeSeries, ContourSeries, ParametricSurfaceSeries, ImplicitSeries, _set_discretization_points, List2DSeries
  from sympy.testing.pytest import raises, warns, XFAIL, skip, ignore_warnings
label_desc: Use image node_id 28 for calling a global function with example usage: test_complex_adaptive_false() without return types