parameters: (self, token: str, box_vis_level: BoxVisibility = BoxVisibility.IN_FRONT)
docstring: Render all LIDAR and camera sample_data in sample along with annotations.
          :param token: Sample token.
          :param box_vis_level: If sample_data is an image, this sets required visibility for boxes.
docstring_summary: Render all LIDAR and camera sample_data in sample along with annotations.
          :param token: Sample token.
          :param box_vis_level: If sample_data is an image, this sets required visibility for boxes.
docstring_tokens: Render all LIDAR and camera sample_data in sample along with annotations . : param token : Sample token . : param box_vis_level : If sample_data is an image this sets required visibility for boxes .
function: def render_sample(self, token: str, box_vis_level: BoxVisibility = BoxVisibility.IN_FRONT) -> None:
          """
          Render all LIDAR and camera sample_data in sample along with annotations.
          :param token: Sample token.
          :param box_vis_level: If sample_data is an image, this sets required visibility for boxes.
          """
          record = self.nusc.get('sample', token)
  
          # RADAR rendering not implemented yet. So only keep LIDAR and vision.
          selected_data = {}
          for channel, token in record['data'].items():
              sd_record = self.nusc.get('sample_data', token)
              sensor_modality = sd_record['sensor_modality']
              if sensor_modality in ['lidar', 'camera']:
                  selected_data[channel] = token
  
          n = len(selected_data)
          fig, axes = plt.subplots(int(np.ceil(n / 2)), 2, figsize=(18, 27))
  
          for (_, sd_token), ax in zip(selected_data.items(), axes.flatten()):
              self.render_sample_data(sd_token, box_vis_level=box_vis_level, ax=ax)
          axes.flatten()[-1].axis('off')
          plt.tight_layout()
function_tokens: def render_sample ( self , token : str , box_vis_level : BoxVisibility = BoxVisibility . IN_FRONT ) -> None : record = self . nusc . get ( 'sample' , token ) # RADAR rendering not implemented yet. So only keep LIDAR and vision. selected_data = { } for channel , token in record [ 'data' ] . items ( ) : sd_record = self . nusc . get ( 'sample_data' , token ) sensor_modality = sd_record [ 'sensor_modality' ] if sensor_modality in [ 'lidar' , 'camera' ] : selected_data [ channel ] = token n = len ( selected_data ) fig , axes = plt . subplots ( int ( np . ceil ( n / 2 ) ) , 2 , figsize = ( 18 , 27 ) ) for ( _ , sd_token ) , ax in zip ( selected_data . items ( ) , axes . flatten ( ) ) : self . render_sample_data ( sd_token , box_vis_level = box_vis_level , ax = ax ) axes . flatten ( ) [ - 1 ] . axis ( 'off' ) plt . tight_layout ( )