def test_random_seed(self):
        sim_model1 = EconDensity(random_seed=22)
        X1, Y1 = sim_model1.simulate(n_samples=100)

        sim_model2 = EconDensity(random_seed=22)
        X2, Y2 = sim_model2.simulate(n_samples=100)

        diff_x = np.sum(np.abs(X1[:100] - X2[:]))
        diff_y = np.sum(np.abs(Y1[:100] - Y2[:]))
        self.assertAlmostEquals(diff_x, 0, places=2)
        self.assertAlmostEquals(diff_y, 0, places=2)
def generate_report():
  econ_density = EconDensity()

  X, Y = econ_density.simulate(n_samples=1000)
  nke = NeighborKernelDensityEstimation()
  nke.fit_by_cv(X, Y)

  n_samples = 500
  X_test = np.asarray([1 for _ in range(n_samples)])
  Y_test = np.linspace(0, 8, num=n_samples)
  Z = nke.pdf(X_test, Y_test)