code: def pval_kstest_approx(D, N):
      pval_two = distributions.kstwobign.sf(D * np.sqrt(N))
      if N > 2666 or pval_two > 0.80 - N * 0.3 / 1000.0:
          return D, distributions.kstwobign.sf(D * np.sqrt(N)), np.nan
      else:
          return D, distributions.ksone.sf(D, N) * 2, np.nan
  
imports: from statsmodels.compat.python import lmap
  import numpy
  from scipy.stats import distributions
  from statsmodels.tools.decorators import cache_readonly
  from scipy.special import kolmogorov
label_desc: Use image node_id 9 for calling a global function with example usage: pval_kstest_approx(D, N) and returns: D,  distributions,  np, D,  unknown,  np