def test_Mult_CTD_3D(quad):
SD = ShenDirichlet(N, quad=quad)
SD.plan((N, 4, 4), 0, np.complex, {})
C = inner_product((SD.CT, 0), (SD, 1))
B = inner_product((SD.CT, 0), (SD.CT, 0))
vk = np.random.random((N, 4, 4)) + np.random.random((N, 4, 4)) * 1j
wk = np.random.random((N, 4, 4)) + np.random.random((N, 4, 4)) * 1j
bv = np.zeros((N, 4, 4), dtype=np.complex)
bw = np.zeros((N, 4, 4), dtype=np.complex)
vk0 = np.zeros((N, 4, 4), dtype=np.complex)
wk0 = np.zeros((N, 4, 4), dtype=np.complex)
cv = np.zeros((N, 4, 4), dtype=np.complex)
cw = np.zeros((N, 4, 4), dtype=np.complex)
vk0 = SD.forward(vk, vk0)
vk = SD.backward(vk0, vk)
vk0 = SD.forward(vk, vk0)
wk0 = SD.forward(wk, wk0)
wk = SD.backward(wk0, wk)
wk0 = SD.forward(wk, wk0)
LUsolve.Mult_CTD_3D_ptr(N, vk0, wk0, bv, bw, 0)
cv = np.zeros_like(vk0)
cw = np.zeros_like(wk0)
cv = C.matvec(vk0, cv)
cw = C.matvec(wk0, cw)
cv /= B[0].repeat(np.array(bv.shape[1:]).prod()).reshape(bv.shape)
cw /= B[0].repeat(np.array(bv.shape[1:]).prod()).reshape(bv.shape)
assert np.allclose(cv, bv)
assert np.allclose(cw, bw)
def test_Mult_CTD_3D(quad):
SD = FunctionSpace(N, 'C', bc=(0, 0))
F0 = FunctionSpace(4, 'F', dtype='D')
F1 = FunctionSpace(4, 'F', dtype='d')
T = TensorProductSpace(comm, (SD, F0, F1))
TO = T.get_orthogonal()
CT = TO.bases[0]
C = inner_product((CT, 0), (SD, 1))
B = inner_product((CT, 0), (CT, 0))
vk = Array(T)
wk = Array(T)
vk[:] = np.random.random(vk.shape)
wk[:] = np.random.random(vk.shape)
bv = Function(T)
bw = Function(T)
vk0 = vk.forward()
vk = vk0.backward()
wk0 = wk.forward()
wk = wk0.backward()
LUsolve.Mult_CTD_3D_ptr(N, vk0, wk0, bv, bw, 0)
cv = np.zeros_like(vk0)
cw = np.zeros_like(wk0)
cv = C.matvec(vk0, cv)
cw = C.matvec(wk0, cw)
cv /= B[0].repeat(np.array(bv.shape[1:]).prod()).reshape(bv.shape)
cw /= B[0].repeat(np.array(bv.shape[1:]).prod()).reshape(bv.shape)
assert np.allclose(cv, bv)
assert np.allclose(cw, bw)