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)
