original_docstring: 
      Multi-dimensional spline filter.
  
      For more details, see `spline_filter1d`.
  
      See Also
      --------
      spline_filter1d
  
      Notes
      -----
      The multi-dimensional filter is implemented as a sequence of
      one-dimensional spline filters. The intermediate arrays are stored
      in the same data type as the output. Therefore, for output types
      with a limited precision, the results may be imprecise because
      intermediate results may be stored with insufficient precision.
  
      
docstring: Multi-dimensional spline filter.
  For more details, see `spline_filter1d`.
  
  See Also
  
  
  
  Notes
  
  The multi-dimensional filter is implemented as a sequence of
  one-dimensional spline filters. The intermediate arrays are stored
  in the same data type as the output. Therefore, for output types
  with a limited precision, the results may be imprecise because
  intermediate results may be stored with insufficient precision.
docstring_tokens: Multi - dimensional spline filter . For more details see ` spline_filter1d ` . See Also Notes The multi - dimensional filter is implemented as a sequence of one - dimensional spline filters . The intermediate arrays are stored in the same data type as the output . Therefore for output types with a limited precision the results may be imprecise because intermediate results may be stored with insufficient precision .
code: def spline_filter(input, order=3, output=numpy.float64):
      """
      Multi-dimensional spline filter.
  
      For more details, see `spline_filter1d`.
  
      See Also
      --------
      spline_filter1d
  
      Notes
      -----
      The multi-dimensional filter is implemented as a sequence of
      one-dimensional spline filters. The intermediate arrays are stored
      in the same data type as the output. Therefore, for output types
      with a limited precision, the results may be imprecise because
      intermediate results may be stored with insufficient precision.
  
      """
      if order < 2 or order > 5:
          raise RuntimeError('spline order not supported')
      input = numpy.asarray(input)
      if numpy.iscomplexobj(input):
          raise TypeError('Complex type not supported')
      output, return_value = _ni_support._get_output(output, input)
      if order not in [0, 1] and input.ndim > 0:
          for axis in range(input.ndim):
              spline_filter1d(input, order, axis, output=output)
              input = output
      else:
          output[...] = input[...]
      return return_value
code_tokens: def spline_filter ( input , order = 3 , output = numpy . float64 ) : if order < 2 or order > 5 : raise RuntimeError ( 'spline order not supported' ) input = numpy . asarray ( input ) if numpy . iscomplexobj ( input ) : raise TypeError ( 'Complex type not supported' ) output , return_value = _ni_support . _get_output ( output , input ) if order not in [ 0 , 1 ] and input . ndim > 0 : for axis in range ( input . ndim ) : spline_filter1d ( input , order , axis , output = output ) input = output else : output [ ... ] = input [ ... ] return return_value
short_docstring: Multi-dimensional spline filter.
short_docstring_tokens: Multi - dimensional spline filter .
comment: """
      Multi-dimensional spline filter.
  
      For more details, see `spline_filter1d`.
  
      See Also
      --------
      spline_filter1d
  
      Notes
      -----
      The multi-dimensional filter is implemented as a sequence of
      one-dimensional spline filters. The intermediate arrays are stored
      in the same data type as the output. Therefore, for output types
      with a limited precision, the results may be imprecise because
      intermediate results may be stored with insufficient precision.
  
      """