old_contents: import numpy as np
  
  from tslearn.metrics import cdist_gak
  from tslearn.svm import TimeSeriesSVC
  
  __author__ = 'Romain Tavenard romain.tavenard[at]univ-rennes2.fr'
  
  
  def test_svm_gak():
      n, sz, d = 15, 10, 3
      rng = np.random.RandomState(0)
      time_series = rng.randn(n, sz, d)
      labels = rng.randint(low=0, high=2, size=n)
  
      gamma = 10.
      gak_km = TimeSeriesSVC(kernel="gak", gamma=gamma)
      sklearn_X, _ = gak_km._preprocess_sklearn(time_series, labels,
                                                fit_time=True)
  
      cdist_mat = cdist_gak(time_series, sigma=np.sqrt(gamma / 2.))
  
      np.testing.assert_allclose(sklearn_X, cdist_mat)
  
new_contents: import numpy as np
  
  from tslearn.metrics import cdist_gak
  from tslearn.svm import TimeSeriesSVC, TimeSeriesSVR
  
  __author__ = 'Romain Tavenard romain.tavenard[at]univ-rennes2.fr'
  
  
  def test_gamma_value_svm():
      n, sz, d = 5, 10, 3
      rng = np.random.RandomState(0)
      time_series = rng.randn(n, sz, d)
      labels = rng.randint(low=0, high=2, size=n)
  
      gamma = 10.
      for ModelClass in [TimeSeriesSVC, TimeSeriesSVR]:
          gak_model = ModelClass(kernel="gak", gamma=gamma)
          sklearn_X, _ = gak_model._preprocess_sklearn(time_series,
                                                       labels,
                                                       fit_time=True)
  
          cdist_mat = cdist_gak(time_series, sigma=np.sqrt(gamma / 2.))
  
          np.testing.assert_allclose(sklearn_X, cdist_mat)
  
subject: Change test name and test SVR too