original_docstring: 
          Perform offline diffusion search for multiple sequences of data points.
          Each sequence is aggregated to find the combined neighbors for each sequence.
  
          Args:
              X: List of of list of data points.
  
          Returns:
              A list of diffusion scores and a list of ids
  
          
docstring: Perform offline diffusion search for multiple sequences of data points.
  Each sequence is aggregated to find the combined neighbors for each sequence.
docstring_tokens: Perform offline diffusion search for multiple sequences of data points . Each sequence is aggregated to find the combined neighbors for each sequence .
code: def online_search_multiple(self, X):
          """
          Perform offline diffusion search for multiple sequences of data points.
          Each sequence is aggregated to find the combined neighbors for each sequence.
  
          Args:
              X: List of of list of data points.
  
          Returns:
              A list of diffusion scores and a list of ids
  
          """
          X = [_conform_x(x_i) for x_i in X]
          ys_ids = [self._initialize_online(x_i, agg=True) for x_i in X]
          f_opts = np.concatenate([self._diffuse_online(y, id_) for y, id_ in ys_ids])
          f_opt, ranks = _sort2d(f_opts)
          return f_opt, ranks
code_tokens: def online_search_multiple ( self , X ) : X = [ _conform_x ( x_i ) for x_i in X ] ys_ids = [ self . _initialize_online ( x_i , agg = True ) for x_i in X ] f_opts = np . concatenate ( [ self . _diffuse_online ( y , id_ ) for y , id_ in ys_ids ] ) f_opt , ranks = _sort2d ( f_opts ) return f_opt , ranks
short_docstring: Perform offline diffusion search for multiple sequences of data points.
short_docstring_tokens: Perform offline diffusion search for multiple sequences of data points .
comment: """
          Perform offline diffusion search for multiple sequences of data points.
          Each sequence is aggregated to find the combined neighbors for each sequence.
  
          Args:
              X: List of of list of data points.
  
          Returns:
              A list of diffusion scores and a list of ids
  
          """