def test_mstump(T, m):
left_P, left_I = naive_mstump(T, m)
# Right
d = T.shape[0]
n = T.shape[1]
k = n - m + 1
excl_zone = int(np.ceil(m / 4)) # See Definition 3 and Figure 3
M_T, Σ_T = _multi_compute_mean_std(T, m)
μ_Q, σ_Q = _multi_compute_mean_std(T, m)
P = np.empty((d, k), dtype='float64')
D = np.zeros((d, k), dtype='float64')
D_prime = np.zeros(k, dtype='float64')
I = np.ones((d, k), dtype='int64') * -1
start = 0
stop = k
P, I = _get_first_mstump_profile(start, T, m, excl_zone, M_T, Σ_T)
QT, QT_first = _get_multi_QT(start, T, m)
right_P, right_I = _mstump(T, m, P, I, D, D_prime, stop, excl_zone, M_T,
Σ_T, QT, QT_first, μ_Q, σ_Q, k, start + 1)
npt.assert_almost_equal(left_P, right_P)
npt.assert_almost_equal(left_I, right_I)
def test_get_multi_QT(T, m):
start = 0
Q = core.rolling_window(T, m)
left_QT = np.empty((Q.shape[0], Q.shape[1]), dtype="float64")
left_QT_first = np.empty((Q.shape[0], Q.shape[1]), dtype="float64")
for dim in range(T.shape[0]):
left_QT[dim] = naive_rolling_window_dot_product(
T[dim, start:start + m], T[dim])
left_QT_first[dim] = naive_rolling_window_dot_product(
T[dim, :m], T[dim])
right_QT, right_QT_first = _get_multi_QT(start, T, m)
npt.assert_almost_equal(left_QT, right_QT)
npt.assert_almost_equal(left_QT_first, right_QT_first)