def test_wavelet_denoising_args():
 img = astro
 noisy = (img.copy() + (0.1 * np.random.randn(*img.shape)))
 for convert2ycbcr in [True, False]:
  for multichannel in [True, False]:
   for sigma in [0.1, [0.1, 0.1, 0.1], None]:
    if (((not multichannel) and (not convert2ycbcr)) or (isinstance(sigma, list) and (not multichannel))):
     continue
    restoration.denoise_wavelet(noisy, sigma=sigma, convert2ycbcr=convert2ycbcr, multichannel=multichannel)

def test_wavelet_denoising_args ( ) : img = astro noisy = ( img . copy ( ) + ( 0.1 * np . random . randn ( * img . shape ) ) ) for convert2ycbcr in [ True , False ] : for multichannel in [ True , False ] : for sigma in [ 0.1 , [ 0.1 , 0.1 , 0.1 ] , None ] : if ( ( ( not multichannel ) and ( not convert2ycbcr ) ) or ( isinstance ( sigma , list ) and ( not multichannel ) ) ) : continue restoration . denoise_wavelet ( noisy , sigma = sigma , convert2ycbcr = convert2ycbcr , multichannel = multichannel )
some of the functions inside wavelet denoising throw an error the wrong arguments are passed .