code: def fdrcorrection_bak(pvals, alpha=0.05, method="indep"):
      """Reject False discovery rate correction for pvalues
  
      Old version, to be deleted
  
  
      missing: methods that estimate fraction of true hypotheses
  
      """
      pvals = np.asarray(pvals)
  
      pvals_sortind = np.argsort(pvals)
      pvals_sorted = pvals[pvals_sortind]
      pecdf = ecdf(pvals_sorted)
      if method in ["i", "indep", "p", "poscorr"]:
          rline = pvals_sorted / alpha
      elif method in ["n", "negcorr"]:
          cm = np.sum(1.0 / np.arange(1, len(pvals)))
          rline = pvals_sorted / alpha * cm
      elif method in ["g", "onegcorr"]:  # what's this ? german diss
          rline = pvals_sorted / (pvals_sorted * (1 - alpha) + alpha)
      elif method in ["oth", "o2negcorr"]:  # other invalid, cut-paste
          cm = np.sum(np.arange(len(pvals)))
          rline = pvals_sorted / alpha / cm
      else:
          raise ValueError("method not available")
  
      reject = pecdf >= rline
      if reject.any():
          rejectmax = max(np.nonzero(reject)[0])
      else:
          rejectmax = 0
      reject[:rejectmax] = True
      return reject[pvals_sortind.argsort()]
  
imports: from collections import namedtuple
  from statsmodels.compat.python import lzip, lrange
  import copy
  import math
  import numpy
  from numpy.testing import assert_almost_equal, assert_equal
  from scipy import stats, interpolate
  from statsmodels.iolib.table import SimpleTable
  from statsmodels.stats.multitest import multipletests, _ecdf, fdrcorrection, fdrcorrection_twostage
  from statsmodels.graphics import utils
  from statsmodels.tools.sm_exceptions import ValueWarning
label_desc: Use image node_id 10 for calling a global function with example usage: fdrcorrection_bak(pvals, alpha, method) and returns: reject