code: def argus_pdf(x, chi):
      # approach follows Baumgarten/Hoermann: Generating ARGUS random variates
      # for chi > 5, use relationship of the ARGUS distribution to Gamma(1.5)
      if chi <= 5:
          y = 1 - x * x
          return x * math.sqrt(y) * math.exp(-0.5 * chi**2 * y)
      return math.sqrt(x) * math.exp(-x)
  
imports: import math
  import numbers
  import numpy
  from scipy import stats
  from scipy import special
  from ._qmc import check_random_state, Halton, QMCEngine
  from ._unuran.unuran_wrapper import NumericalInversePolynomial
  from scipy._lib._util import check_random_state
label_desc: Use image node_id 1 for calling a global function with example usage: argus_pdf(x, chi) and returns: unknown, unknown