Esempio n. 1
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def test_smoother_ref_traj3_2():
    """ test_smoother_ref_traj3_1 .
  Just check if it can be computed and does not trigger underflow warnings. """
    traj = simple_traj3()
    theta = np.array([-1.0, 1.0])

    smoother_1 = TrajectorySmootherRef(traj, theta)
    smoother_1.computeProbs()
Esempio n. 2
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def test_smoother_ref_traj6_1():
    """ test_smoother_ref_traj6_1 """
    traj = simple_traj6()
    theta = np.array([-1.0, 1.0])
    smoother_ref = TrajectorySmootherRef(traj, theta)
    smoother_ref.computeProbs()
    smoother_1 = TrajectorySmoother1(traj, theta)
    smoother_1.computeProbs()
    check_probs(smoother_1, smoother_ref)
def test_smoother_ref_traj3_2():
  """ test_smoother_ref_traj3_1 .
  Just check if it can be computed and does not trigger underflow warnings. """
  traj = simple_traj3()
  theta = np.array([-1.0, 1.0])
  
  smoother_1 = TrajectorySmootherRef(traj, theta)
  smoother_1.computeProbs()
  
def test_smoother_ref_traj6_1():
  """ test_smoother_ref_traj6_1 """
  traj = simple_traj6()
  theta = np.array([-1.0, 1.0])
  smoother_ref = TrajectorySmootherRef(traj, theta)
  smoother_ref.computeProbs()
  smoother_1 = TrajectorySmoother1(traj, theta)
  smoother_1.computeProbs()
  check_probs(smoother_1, smoother_ref)
def test_filter_ref_2():
  """ test_filter_ref_2
  """
  traj = simple_traj2()
  theta = np.array([1.0, -1.0])
  filter_0 = TrajectoryFilterRef(traj, theta, 0)
  filter_0.computeProbs()
  # The forward probabilities should equal the probabilities
  check_prob_fields(filter_0.forward, filter_0.probabilities)
  # Run the filter in inneficient smooting mode
  filter_L = TrajectoryFilterRef(traj, theta, traj.L)
  filter_L.computeProbs()
  smoother = TrajectorySmootherRef(traj, theta)
  smoother.computeProbs()
  check_prob_fields(filter_L.forward, smoother.forward)
  check_prob_fields(filter_L.backward, smoother.backward)
  check_prob_fields(filter_L.probabilities, smoother.probabilities)
def test_filter_ref_2():
    """ test_filter_ref_2
  """
    traj = simple_traj2()
    theta = np.array([1.0, -1.0])
    filter_0 = TrajectoryFilterRef(traj, theta, 0)
    filter_0.computeProbs()
    # The forward probabilities should equal the probabilities
    check_prob_fields(filter_0.forward, filter_0.probabilities)
    # Run the filter in inneficient smooting mode
    filter_L = TrajectoryFilterRef(traj, theta, traj.L)
    filter_L.computeProbs()
    smoother = TrajectorySmootherRef(traj, theta)
    smoother.computeProbs()
    check_prob_fields(filter_L.forward, smoother.forward)
    check_prob_fields(filter_L.backward, smoother.backward)
    check_prob_fields(filter_L.probabilities, smoother.probabilities)