class_docstr: based on https://github.com/cgtuebingen/learning-blind-motion-deblurring/blob/master/synthblur/src/flow.cpp#L44
code: def _construct_wheel(self):
      k = 0
  
      RY, YG, GC = 15, 6, 4
      YG, GC, CB = 6, 4, 11
      BM, MR = 13, 6
  
      self.wheel = np.zeros((55, 3), dtype=np.float32)
  
      for i in range(RY):
          self.wheel[k] = np.array([255.0, 255.0 * i / float(RY), 0])
          k += 1
  
      for i in range(YG):
          self.wheel[k] = np.array(
              [255.0 - 255.0 * i / float(YG), 255.0, 0]
          )
          k += 1
  
      for i in range(GC):
          self.wheel[k] = np.array([0, 255.0, 255.0 * i / float(GC)])
          k += 1
  
      for i in range(CB):
          self.wheel[k] = np.array(
              [0, 255.0 - 255.0 * i / float(CB), 255.0]
          )
          k += 1
  
      for i in range(BM):
          self.wheel[k] = np.array([255.0 * i / float(BM), 0, 255.0])
          k += 1
  
      for i in range(MR):
          self.wheel[k] = np.array(
              [255.0, 0, 255.0 - 255.0 * i / float(MR)]
          )
          k += 1
  
      self.wheel = self.wheel / 255.0
  
imports: import numpy
label_desc: Use image node_id 3 for calling the Flow obj's underlying member method code with example usage: obj._construct_wheel() without return types