code: def butter_lp(n, Wn):
      """
      Lowpass Butterworth digital filter design.
  
      This computes the same result as scipy.signal.butter(n, Wn, output='zpk'),
      but it uses mpmath, and the results are returned in lists instead of numpy
      arrays.
      """
      zeros = []
      poles = _butter_analog_poles(n)
      k = 1
      fs = 2
      warped = 2 * fs * mpmath.tan(mpmath.pi * Wn / fs)
      z, p, k = _zpklp2lp(zeros, poles, k, wo=warped)
      z, p, k = _zpkbilinear(z, p, k, fs=fs)
      return z, p, k
  
file_path: catboost/contrib/python/scipy/py2/scipy/signal/tests/mpsig.py
imports: from __future__ import division
label_desc: Use image node_id 6 for calling a global function with example usage: butter_lp(n, Wn) and returns: z,  p,  k