original_docstring: Segments a LiDAR point cloud based on normal vectors.
  
          Keyword arguments:
  
          i -- Input LiDAR file. 
          output -- Output file. 
          radius -- Search Radius. 
          norm_diff -- Maximum difference in normal vectors, in degrees. 
          maxzdiff -- Maximum difference in elevation (z units) between neighbouring points of the same segment. 
          callback -- Custom functon for handling tool text outputs.
          
docstring: Segments a LiDAR point cloud based on normal vectors.
  Keyword arguments.
  
  - Input LiDAR file.
  output -- Output file.
  radius -- Search Radius.
  norm_diff -- Maximum difference in normal vectors, in degrees.
  maxzdiff -- Maximum difference in elevation (z units) between neighbouring points of the same segment.
  callback -- Custom functon for handling tool text outputs.
docstring_tokens: Segments a LiDAR point cloud based on normal vectors . Keyword arguments . - Input LiDAR file . output -- Output file . radius -- Search Radius . norm_diff -- Maximum difference in normal vectors in degrees . maxzdiff -- Maximum difference in elevation ( z units ) between neighbouring points of the same segment . callback -- Custom functon for handling tool text outputs .
code: def lidar_segmentation(self, i, output, radius=5.0, norm_diff=10.0, maxzdiff=1.0, callback=default_callback):
          """Segments a LiDAR point cloud based on normal vectors.
  
          Keyword arguments:
  
          i -- Input LiDAR file. 
          output -- Output file. 
          radius -- Search Radius. 
          norm_diff -- Maximum difference in normal vectors, in degrees. 
          maxzdiff -- Maximum difference in elevation (z units) between neighbouring points of the same segment. 
          callback -- Custom functon for handling tool text outputs.
          """
          args = []
          args.append("--input='{}'".format(i))
          args.append("--output='{}'".format(output))
          args.append("--radius={}".format(radius))
          args.append("--norm_diff={}".format(norm_diff))
          args.append("--maxzdiff={}".format(maxzdiff))
          return self.run_tool('lidar_segmentation', args, callback)
code_tokens: def lidar_segmentation ( self , i , output , radius = 5.0 , norm_diff = 10.0 , maxzdiff = 1.0 , callback = default_callback ) : args = [ ] args . append ( "--input='{}'" . format ( i ) ) args . append ( "--output='{}'" . format ( output ) ) args . append ( "--radius={}" . format ( radius ) ) args . append ( "--norm_diff={}" . format ( norm_diff ) ) args . append ( "--maxzdiff={}" . format ( maxzdiff ) ) return self . run_tool ( 'lidar_segmentation' , args , callback )
short_docstring: Segments a LiDAR point cloud based on normal vectors.
short_docstring_tokens: Segments a LiDAR point cloud based on normal vectors .
comment: """Segments a LiDAR point cloud based on normal vectors.
  
          Keyword arguments:
  
          i -- Input LiDAR file. 
          output -- Output file. 
          radius -- Search Radius. 
          norm_diff -- Maximum difference in normal vectors, in degrees. 
          maxzdiff -- Maximum difference in elevation (z units) between neighbouring points of the same segment. 
          callback -- Custom functon for handling tool text outputs.
          """