code: def test_PSNR_vs_IPOL():
      """Tests vs. imdiff result from the following IPOL article and code:
      https://www.ipol.im/pub/art/2011/g_lmii/.
  
      Notes
      -----
      To generate p_IPOL, we need a local copy of cam_noisy:
  
      >>> from skimage import io
      >>> io.imsave('/tmp/cam_noisy.png', cam_noisy)
  
      Then, we use the following command:
      $ ./imdiff -m psnr <path to camera.png>/camera.png /tmp/cam_noisy.png
  
      Values for current data.camera() calculated by Gregory Lee on Sep, 2020.
      Available at:
      https://github.com/scikit-image/scikit-image/pull/4913#issuecomment-700653165
      """
      p_IPOL = 22.409353363576034
      p = peak_signal_noise_ratio(cam, cam_noisy)
      assert_almost_equal(p, p_IPOL, decimal=4)
  
file_path: scikit-image/skimage/metrics/tests/test_simple_metrics.py
imports: import numpy
  import pytest
  from numpy.testing import assert_equal, assert_almost_equal
  from skimage import data
  from skimage._shared._warnings import expected_warnings
  from skimage.metrics import peak_signal_noise_ratio, normalized_root_mse, mean_squared_error, normalized_mutual_information
label_desc: Use image node_id 1 for calling a global function with example usage: test_PSNR_vs_IPOL() without return types