docs: def get_contour(mask):
      """Compute the image contour from a mask
  
      The contour is computed in a very inefficient way using scikit-image
      and a conversion of float coordinates to pixel coordinates.
  
      Parameters
      ----------
      mask: binary ndarray of shape (M,N) or (K,M,N)
          The mask outlining the pixel positions of the event.
          If a 3d array is given, then `K` indexes the individual
          contours.
  
      Returns
      -------
      cont: ndarray or list of K ndarrays of shape (J,2)
          A 2D array that holds the contour of an event (in pixels)
          e.g. obtained using `mm.contour` where  `mm` is an instance
          of `RTDCBase`. The first and second columns of `cont`
          correspond to the x- and y-coordinates of the contour.
      """
      if isinstance(mask, np.ndarray) and len(mask.shape) == 2:
          mask = [mask]
          ret_list = False
      else:
          ret_list = True
      contours = []
  
      for mi in mask:
          c0 = find_contours(mi.transpose(),
                             level=.9999,
                             positive_orientation="low",
                             fully_connected="high")[0]
          # round all coordinates to pixel values
          c1 = np.asarray(np.round(c0), int)
          # remove duplicates
          c2 = remove_duplicates(c1)
          contours.append(c2)
      if ret_list:
          return contours
      else:
          return contours[0]