code: def lp2hp(b, a, wo=1.0):
      r"""
      Transform a lowpass filter prototype to a highpass filter.
  
      Return an analog high-pass filter with cutoff frequency `wo`
      from an analog low-pass filter prototype with unity cutoff frequency, in
      transfer function ('ba') representation.
  
      Parameters
      ----------
      b : array_like
          Numerator polynomial coefficients.
      a : array_like
          Denominator polynomial coefficients.
      wo : float
          Desired cutoff, as angular frequency (e.g., rad/s).
          Defaults to no change.
  
      Returns
      -------
      b : array_like
          Numerator polynomial coefficients of the transformed high-pass filter.
      a : array_like
          Denominator polynomial coefficients of the transformed high-pass
          filter.
  
      See Also
      --------
      lp2lp, lp2bp, lp2bs, bilinear
      lp2hp_zpk
      scipy.signal.lp2hp
  
      Notes
      -----
      This is derived from the s-plane substitution
  
      .. math:: s \rightarrow \frac{\omega_0}{s}
  
      This maintains symmetry of the lowpass and highpass responses on a
      logarithmic scale.
      """
      a, b = map(cupy.atleast_1d, (a, b))
      try:
          wo = float(wo)
      except TypeError:
          wo = float(wo[0])
      d = len(a)
      n = len(b)
      if wo != 1:
          pwo = wo ** cupy.arange(max(d, n))
      else:
          pwo = cupy.ones(max(d, n), b.dtype)
      if d >= n:
          outa = a[::-1] * pwo
          outb = cupy.resize(b, (d,))
          outb[n:] = 0.0
          outb[:n] = b[::-1] * pwo[:n]
      else:
          outb = b[::-1] * pwo
          outa = cupy.resize(a, (n,))
          outa[d:] = 0.0
          outa[:d] = a[::-1] * pwo[:d]
  
      return normalize(outb, outa)
  
imports: import warnings
  import math
  from math import pi, prod
  import cupy
  from cupyx.scipy.special import binom
  import cupyx.scipy.special
  from cupyx.scipy.signal import _optimize
  from cupyx.scipy.signal._polyutils import roots, poly
  from cupyx.scipy.signal._lti_conversion import abcd_normalize
label_desc: Use image node_id 17 for calling a global function with example usage: lp2hp(b, a, wo) and returns: normalize