text: import random
  import time
  import numpy as np
  
  range_bins = 256
  
  
  def simulateData():
      detObj = dict()
  
      num_points = random.randint(1, 40)
      detObj['x'] = np.random.uniform(low=0.0, high=1.0, size=(num_points,))
      detObj['y'] = np.random.uniform(low=0.0, high=1.0, size=(num_points,))
      detObj['z'] = np.random.uniform(low=0.0, high=1.0, size=(num_points,))
      detObj['doppler'] = np.random.uniform(low=0.0, high=1.0, size=(num_points,))
  
      time.sleep(0.033)
  
      return True, 0, detObj
  
  
  def sim_heatmap(shape: list):
      return np.random.random(shape).astype(np.float16)
  
  
  def sim_detected_points():
      num_points = random.randint(1, 40)
      return np.transpose(np.asarray([np.random.uniform(low=0.0, high=1.0, size=(num_points,)),
                                      np.random.uniform(low=0.0, high=1.0, size=(num_points,)),
                                      np.random.uniform(low=0.0, high=1.0, size=(num_points,)),
                                      np.random.uniform(low=0.0, high=1.0, size=(num_points,))]))
  
  
  def sim_imp():
      return np.random.uniform(low=0.0, high=1.0, size=(range_bins,))
  
  
  def sim_uwb():
      return np.reshape(np.random.uniform(low=0.0, high=10000, size=(65 * 2)), newshape=(65, 2))
  
  
  def sim_leap():
      return '1.0 2.0 3.0 4.0 5.0', sim_heatmap((256, 256))
  
  
  def sim_xe4thru(length=100):
      return np.random.uniform(low=0.0, high=1.0, size=(length,))
  