code: def variance(self) -> float:
      if self._variance is None:
          leaf_node_indices = numpy.nonzero(
              numpy.array(self._tree.feature) < 0
          )[0]
          statistics = self._statistics[leaf_node_indices]
          values = statistics[:, 0]
          weights = statistics[:, 1]
          average_values = numpy.average(values, weights=weights)
          variance = numpy.average(
              (values - average_values) ** 2, weights=weights
          )
  
          self._variance = variance
  
      assert self._variance is not None
      return self._variance
  
imports: from __future__ import annotations
  from functools import lru_cache
  import itertools
  from typing import List
  from typing import Set
  from typing import Tuple
  from typing import TYPE_CHECKING
  from typing import Union
  import numpy
label_desc: Use image node_id 2 for calling the _FanovaTree obj's underlying member method code with example usage: obj.variance() and returns: self