code: def test_bootstrap_batch(method, axis):
      # for one-sample statistics, batch size shouldn't affect the result
      np.random.seed(0)
  
      x = np.random.rand(10, 11, 12)
      res1 = bootstrap(
          (x,),
          np.mean,
          batch=None,
          method=method,
          random_state=0,
          axis=axis,
          n_resamples=100,
      )
      res2 = bootstrap(
          (x,),
          np.mean,
          batch=10,
          method=method,
          random_state=0,
          axis=axis,
          n_resamples=100,
      )
  
      assert_equal(
          res2.confidence_interval.low, res1.confidence_interval.low
      )
      assert_equal(
          res2.confidence_interval.high, res1.confidence_interval.high
      )
      assert_equal(res2.standard_error, res1.standard_error)
  
imports: import numpy
  import pytest
  from scipy.stats import bootstrap
  from numpy.testing import assert_allclose, assert_equal
  from scipy import stats
  from scipy.stats import _bootstrap
  from scipy._lib._util import rng_integers
label_desc: Use image node_id 2 for calling a global function with example usage: test_bootstrap_batch(method, axis) without return types