code: def test_unequal_bs():
      def mean_diff(*args):
          return args[0].mean() - args[1].mean()
  
      rs = RandomState(0)
      x = rs.standard_normal(800)
      y = rs.standard_normal(200)
  
      bs = IndependentSamplesBootstrap(x, y, seed=rs)
      variance = bs.var(mean_diff)
      assert variance > 0
      ci = bs.conf_int(mean_diff)
      assert ci[0] < ci[1]
      applied = bs.apply(mean_diff, 1000)
      assert len(applied) == 1000
  
      x = pd.Series(x)
      y = pd.Series(y)
      bs = IndependentSamplesBootstrap(x, y)
      variance = bs.var(mean_diff)
      assert variance > 0
  
      with pytest.raises(ValueError, match="BCa cannot be applied"):
          bs.conf_int(mean_diff, method="bca")
  
imports: from __future__ import annotations
  import copy
  from typing import Callable, NamedTuple
  import warnings
  import numpy
  from numpy.random import RandomState
  from numpy.testing import assert_allclose, assert_equal
  import pandas
  from pandas.testing import assert_frame_equal, assert_series_equal
  import pytest
  import scipy.stats
  from arch.bootstrap import CircularBlockBootstrap, IIDBootstrap, IndependentSamplesBootstrap, MovingBlockBootstrap, StationaryBootstrap
  from arch.bootstrap._samplers_python import stationary_bootstrap_sample
  from arch.bootstrap._samplers_python import stationary_bootstrap_sample_python
  from arch.bootstrap.base import _loo_jackknife
  from arch.utility.exceptions import StudentizationError
label_desc: Use image node_id 30 for calling a global function with example usage: test_unequal_bs() and returns: unknown