code: def _ess_z_scale(ary, relative=False):
      """Calculate ess for z-scaLe."""
      ary = np.asarray(ary)
      if _not_valid(ary, shape_kwargs=dict(min_draws=4, min_chains=1)):
          return np.nan
      return _ess(_z_scale(_split_chains(ary)), relative=relative)
  
imports: import warnings
  from collections.abc import Sequence
  import numpy
  import packaging
  import pandas
  import scipy
  from scipy import stats
  from ..data import convert_to_dataset
  from ..utils import Numba, _numba_var, _stack, _var_names
  from .density_utils import histogram
  from .stats_utils import _circular_standard_deviation, _sqrt
  from .stats_utils import autocov
  from .stats_utils import not_valid
  from .stats_utils import quantile
  from .stats_utils import stats_variance_2d
  from .stats_utils import wrap_xarray_ufunc
label_desc: Use image node_id 24 for calling a global function with example usage: _ess_z_scale(ary, relative) and returns: _ess, np