def test_scalar(self): data = np.arange(5) # [0, 1, 2, 3, 4] result = pychebfun.even_data(data) expected = np.array( list(range(5)) + list(range(1, 4))[::-1]) # [0, 1, 2, 3, 4, 3, 2, 1] npt.assert_array_almost_equal(result, expected)
def test_even_data(self): """ even_data on vector of length N+1 returns a vector of size 2*N """ N = 32 data = np.random.rand(N + 1).reshape(-1, 1) even = pychebfun.even_data(data) self.assertEqual(len(even), 2 * N)
def test_even_data(self): """ even_data on vector of length N+1 returns a vector of size 2*N """ N = 32 data = np.random.rand(N+1).reshape(-1,1) even = pychebfun.even_data(data) self.assertEqual(len(even), 2*N)
def test_vector(self): data = np.array([[1., 2], [3., 4], [5, 6]]) result = pychebfun.even_data(data) expected = np.array([[1., 2], [3., 4], [5, 6], [3., 4]]) npt.assert_array_almost_equal(result, expected)
def test_vector(self): data = np.array([[1.,2],[3.,4],[5,6]]) result = pychebfun.even_data(data) expected = np.array([[1.,2],[3.,4],[5,6],[3.,4]]) npt.assert_array_almost_equal(result, expected)
def test_scalar(self): data = np.arange(5) # [0, 1, 2, 3, 4] result = pychebfun.even_data(data) expected = np.array(list(range(5)) + list(range(1,4))[::-1]) # [0, 1, 2, 3, 4, 3, 2, 1] npt.assert_array_almost_equal(result, expected)