code: def _power_equivalence_het_v0(
      es_low,
      es_upp,
      nobs,
      alpha=0.05,
      std_null_low=None,
      std_null_upp=None,
      std_alternative=None,
  ):
      """power for equivalence test"""
  
      s0_low = std_null_low
      s0_upp = std_null_upp
      s1 = std_alternative
  
      crit = norm.isf(alpha)
      pow_ = (
          norm.cdf((np.sqrt(nobs) * es_low - crit * s0_low) / s1)
          + norm.cdf((np.sqrt(nobs) * es_upp - crit * s0_upp) / s1)
          - 1
      )
      return pow_
  
imports: import numpy
  import warnings
  from scipy import stats, optimize
  from statsmodels.stats.base import HolderTuple
  from statsmodels.stats.weightstats import _zstat_generic2
  from statsmodels.stats._inference_tools import _mover_confint
label_desc: Use image node_id 15 for calling a global function with example usage: _power_equivalence_het_v0(es_low, es_upp, nobs, alpha, std_null_low, std_null_upp, std_alternative) and returns: pow_