parameters: (self, normalize=True)
return_statement: return showImage(self.transposeToVigraOrder(), normalize)
docstring: Display this image in a vigra.pyqt.ImageWindow.
  
          The channels are intepreted as follows: 1 channel = gray image,
          2 channels = gray + alpha, 3 channels = RGB, 4 channels = RGB + alpha.
  
          The parameter `normalize` can be used to normalize an image's
          value range to 0..255:
  
          `normalize` = (nmin, nmax):
            scale & clip image values from nmin..nmax to 0..255
  
          `normalize` = nmax:
            lets nmin default to zero, i.e. scale & clip the range 0..nmax
            to 0..255
  
          `normalize` = True: (default)
            scale the image's actual range min()..max() to 0..255
  
          `normalize` = False:
            don't scale the image's values
docstring_summary: Display this image in a vigra.pyqt.ImageWindow.
docstring_tokens: Display this image in a vigra . pyqt . ImageWindow .
function: def show(self, normalize=True):
          '''
          Display this image in a vigra.pyqt.ImageWindow.
  
          The channels are intepreted as follows: 1 channel = gray image,
          2 channels = gray + alpha, 3 channels = RGB, 4 channels = RGB + alpha.
  
          The parameter `normalize` can be used to normalize an image's
          value range to 0..255:
  
          `normalize` = (nmin, nmax):
            scale & clip image values from nmin..nmax to 0..255
  
          `normalize` = nmax:
            lets nmin default to zero, i.e. scale & clip the range 0..nmax
            to 0..255
  
          `normalize` = True: (default)
            scale the image's actual range min()..max() to 0..255
  
          `normalize` = False:
            don't scale the image's values
  
          '''
          from pyqt.imagewindow import showImage
  
          ndim = self.ndim
          channelIndex = self.channelIndex
          if channelIndex < ndim:
              if self.channels > 4:
                  raise RuntimeError("VigraArray.show(): array can have at most 4 channels.")
              ndim -= 1
          if ndim != 2:
              raise RuntimeError("VigraArray.show(): array must have 2 non-channel axes.")
  
          return showImage(self.transposeToVigraOrder(), normalize)
function_tokens: def show ( self , normalize = True ) : from pyqt . imagewindow import showImage ndim = self . ndim channelIndex = self . channelIndex if channelIndex < ndim : if self . channels > 4 : raise RuntimeError ( "VigraArray.show(): array can have at most 4 channels." ) ndim -= 1 if ndim != 2 : raise RuntimeError ( "VigraArray.show(): array must have 2 non-channel axes." ) return showImage ( self . transposeToVigraOrder ( ) , normalize )