code: def idz_estrank(eps, A):
      """
      Estimate rank of a complex matrix to a specified relative precision using
      random sampling.
  
      The output rank is typically about 8 higher than the actual rank.
  
      :param eps:
          Relative precision.
      :type eps: float
      :param A:
          Matrix.
      :type A: :class:`numpy.ndarray`
  
      :return:
          Rank estimate.
      :rtype: int
      """
      A = np.asfortranarray(A)
      m, n = A.shape
      n2, w = idz_frmi(m)
      ra = np.empty(
          n * n2 + (n + 1) * (n2 + 1), dtype="complex128", order="F"
      )
      k, ra = _id.idz_estrank(eps, A, w, ra)
      return k
  
imports: import scipy.linalg._interpolative
  import numpy
label_desc: Use image node_id 44 for calling a global function with example usage: idz_estrank(eps, A) and returns: k