code: def test_highlighted_kspace_pixel(self, im_shape, im_type):
      data = self.get_data(im_shape, im_type)
      loc = [0] + [int(im_shape[i] / 2) for i in range(len(im_shape))]
      k_intensity = 10
  
      t = KSpaceSpikeNoised(KEYS, loc, k_intensity)
      out = t(data)
  
      for k in KEYS:
          if isinstance(out[k], torch.Tensor):
              out[k] = out[k].cpu()
  
          n_dims = len(im_shape)
          out_k = fftshift(
              fftn(out[k], axes=tuple(range(-n_dims, 0))),
              axes=tuple(range(-n_dims, 0)),
          )
          log_mag = np.log(np.absolute(out_k))
          np.testing.assert_allclose(
              k_intensity, log_mag[tuple(loc)], 1e-1
          )
  
file_path: MONAI/tests/test_k_space_spike_noised.py
imports: from __future__ import annotations
  import unittest
  from copy import deepcopy
  import numpy
  import torch
  from numpy.fft import fftn, fftshift
  from parameterized import parameterized
  from monai.data.synthetic import create_test_image_2d, create_test_image_3d
  from monai.transforms import KSpaceSpikeNoised
  from monai.utils.misc import set_determinism
  from tests.utils import TEST_NDARRAYS, assert_allclose
label_desc: Use image node_id 5 for calling the TestKSpaceSpikeNoised obj's underlying member method code with example usage: obj.test_highlighted_kspace_pixel(im_shape, im_type) without return types