code: def sample_tau(n=10, kappa_3=0.3, ratio=0.5, rel_increase=0.15):
      """
      Return list of control parameters
  
      :param n: number of samples
      :type n: int
      :param kappa_3: inverse bifurcation point
      :type kappa_3: float
      :param ratio: ratio (default 0.5) of samples before and beyond drift-bifurcation
      :type ratio: float
      :param rel_increase: relative increase from bifurcation point
      :type rel_increase: float
      :return: tau. List of sampled bifurcation parameter
      :rtype tau: list
      """
      assert ratio > 0 and ratio <= 1
      assert kappa_3 > 0
      assert rel_increase > 0 and rel_increase <= 1
      tau_c = 1.0 / kappa_3
  
      tau_max = tau_c * (1.0 + rel_increase)
      tau = tau_c + (tau_max - tau_c) * (np.random.rand(n) - ratio)
      return tau.tolist()
  
file_path: tsfresh/tsfresh/examples/driftbif_simulation.py
imports: import logging
  import numpy
  import pandas
label_desc: Use image node_id 1 for calling a global function with example usage: sample_tau(n, kappa_3, ratio, rel_increase) and returns: tau