code: def _select_vs(v, p):
      # This one is is about 30 times faster than
      # the generic algorithm it is replacing.
      """returns the points to use for interpolating v"""
  
      if v >= 120.0:
          return 60, 120, inf
      elif v >= 60.0:
          return 40, 60, 120
      elif v >= 40.0:
          return 30, 40, 60
      elif v >= 30.0:
          return 24, 30, 40
      elif v >= 24.0:
          return 20, 24, 30
      elif v >= 19.5:
          return 19, 20, 24
  
      if p >= 0.9:
          if v < 2.5:
              return 1, 2, 3
      else:
          if v < 3.5:
              return 2, 3, 4
  
      vi = int(round(v))
      return vi - 1, vi, vi + 1
  
file_path: statsmodels/statsmodels/stats/libqsturng/qsturng_.py
imports: from statsmodels.compat.python import lrange
  import math
  import scipy.stats
  import numpy
  from scipy.optimize import fminbound
label_desc: Use image node_id 7 for calling a global function with example usage: _select_vs(v, p) and returns: unknown,  vi,  unknown, int,  int,  inf, int,  int,  int, int,  int,  int, int,  int,  int, int,  int,  int, int,  int,  int, int,  int,  int, int,  int,  int