parameters: (self, sameGaussianParameters)
return_statement: return (means, variances)
docstring: Return a tuple of (means, variances) for the initial segmentation-fitting stage.
docstring_summary: Return a tuple of (means, variances) for the initial segmentation-fitting stage.
docstring_tokens: Return a tuple of ( means variances ) for the initial segmentation - fitting stage .
function: def get_cheating_gaussians(self, sameGaussianParameters):
          """
          Return a tuple of (means, variances) for the initial segmentation-fitting stage.
          """
          means = np.zeros(len(sameGaussianParameters))
          variances = 0.01 * np.ones(len(sameGaussianParameters))
          for l in range(len(sameGaussianParameters)):
              labels = np.array(sameGaussianParameters[l])
  
              if any((labels >= 200) & (labels <= 226) & (labels != 215)):
                  means[l] = 3  # Hippo SF > Hippo
              elif any((labels >= 7000)):
                  means[l] = 3  # Amygdala Subnuclei -> Amygdala
              elif any(labels == 0):
                  means[l] = 1  # Background is 1 instead of 0
              elif any(labels == 999):
                  means[l] = 55
                  variances[l] = 55 ** 2  # This is the generic `suspicious` label we use for cysts
              else:
                  means[l] = labels[0]
          return (means, variances)
function_tokens: def get_cheating_gaussians ( self , sameGaussianParameters ) : means = np . zeros ( len ( sameGaussianParameters ) ) variances = 0.01 * np . ones ( len ( sameGaussianParameters ) ) for l in range ( len ( sameGaussianParameters ) ) : labels = np . array ( sameGaussianParameters [ l ] ) if any ( ( labels >= 200 ) & ( labels <= 226 ) & ( labels != 215 ) ) : means [ l ] = 3 # Hippo SF > Hippo elif any ( ( labels >= 7000 ) ) : means [ l ] = 3 # Amygdala Subnuclei -> Amygdala elif any ( labels == 0 ) : means [ l ] = 1 # Background is 1 instead of 0 elif any ( labels == 999 ) : means [ l ] = 55 variances [ l ] = 55 ** 2 # This is the generic `suspicious` label we use for cysts else : means [ l ] = labels [ 0 ] return ( means , variances )