code: def test_nan_x_1d(self, method):
      # gh-6624 : if x is nan, result should be nan
      f = RegularGridInterpolator(
          (cp.array([1, 2, 3]),),
          cp.array([10, 20, 30]),
          fill_value=1,
          bounds_error=False,
          method=method,
      )
      assert cp.isnan(f([cp.nan]))
  
      # test arbitrary nan pattern
      rng = cp.random.default_rng(8143215468)
      x = rng.random(size=100) * 4
      i = rng.random(size=100) > 0.5
      x[i] = cp.nan
  
      # out-of-bounds comparisons, `out_of_bounds += x < grid[0]`,
      # generate numpy warnings if `x` contains nans.
      # These warnings should propagate to user
      res = f(x)
  
      assert_array_equal(res[i], cp.nan)
      assert_array_equal(res[~i], f(x[~i]))
  
      # also test the length-one axis f(nan)
      x = [1, 2, 3]
      y = [
          1,
      ]
      data = cp.ones((3, 1))
      f = RegularGridInterpolator(
          (x, y), data, fill_value=1, bounds_error=False, method=method
      )
      assert cp.isnan(f([cp.nan, 1]))
      assert cp.isnan(f([1, cp.nan]))
  
imports: import pytest
  import cupy
  from cupy.testing import assert_allclose, assert_array_equal, assert_array_almost_equal
  from cupy_backends.cuda.api import runtime
  from pytest import raises
  from cupyx.scipy.interpolate import RegularGridInterpolator, interpn
label_desc: Use image node_id 19 for calling the TestRegularGridInterpolator obj's underlying member method code with example usage: obj.test_nan_x_1d(method) without return types