code: def pearson4(
      x, amplitude=1.0, center=0.0, sigma=1.0, expon=1.0, skew=0.0
  ):
      """Return a Pearson4 lineshape.
  
      Using the Wikipedia definition:
  
      pearson4(x, amplitude, center, sigma, expon, skew) =
          amplitude*|gamma(expon + I skew/2)/gamma(m)|**2/(w*beta(expon-0.5, 0.5)) * (1+arg**2)**(-expon) * exp(-skew * arctan(arg))
  
      where ``arg = (x-center)/sigma``, `gamma` is the gamma function and `beta` is the beta function.
  
      For more information, see: https://en.wikipedia.org/wiki/Pearson_distribution#The_Pearson_type_IV_distribution
  
      """
      expon = max(tiny, expon)
      sigma = max(tiny, sigma)
      arg = (x - center) / sigma
      logprefactor = 2 * (
          real(loggammafcn(expon + skew * 0.5j)) - loggammafcn(expon)
      ) - betalnfcn(expon - 0.5, 0.5)
      return (amplitude / sigma) * exp(
          logprefactor - expon * log1p(arg * arg) - skew * arctan(arg)
      )
  
imports: from numpy import arctan, copysign, cos, exp, isclose, isnan, log, log1p, maximum, minimum, pi, real, sin, sqrt, where
  from scipy.special import betaln
  from scipy.special import erf, erfc
  from scipy.special import gamma
  from scipy.special import loggamma
  from scipy.special import wofz
label_desc: Use image node_id 9 for calling a global function with example usage: pearson4(x, amplitude, center, sigma, expon, skew) and returns: unknown