text: from keanu import BayesNet, KeanuRandom, Model
  from keanu.vertex import Gamma, Exponential, Cauchy, Gaussian, Uniform
  from keanu.algorithm import GradientOptimizer
  
  
  def test_thermometers_example():
      # %%SNIPPET_START%% PythonTwoThermometers
      with Model() as m:
          m.temperature = Uniform(20., 30.)
          m.first_thermometer = Gaussian(m.temperature, 2.5)
          m.second_thermometer = Gaussian(m.temperature, 5.)
  
      m.first_thermometer.observe(25.)
      m.second_thermometer.observe(30.)
  
      bayes_net = m.to_bayes_net()
      optimizer = GradientOptimizer(bayes_net)
      optimizer.max_a_posteriori()
  
      calculated_temperature = m.temperature.get_value()
      # %%SNIPPET_END%% PythonTwoThermometers
  