def right_qr_maxvol(nd):
cr = nd.core.copy()
r1, n, r2 = cr.shape
Rv = nd.edges[1].Rv.copy()
cr = np.tensordot(cr, Rv, 1)
r2 = cr.shape[2]
cr = reshape(cr, (r1, -1))
cr = cr.T
q, Rv = np.linalg.qr(cr)
ind, c = maxvol(q)
Rv = np.dot(q[ind, :], Rv)
#q = np.linalg.solve(q[ind, :].T, q.T).T
q = c.copy()
nd.edges[0].Rv = Rv.T.copy()
q = reshape(q.T, (-1, n, r2))
nd.core = q.copy()
nd.maxvol_right = np.unravel_index(ind, (n, r2), order='F')
""" Recomputation of right indices goes here """
""" Finally, update indices """
i_right = nd.edges[1].ind_right
w1 = mkron(np.ones((r2, 1), dtype=np.int32),
reshape(np.arange(n, dtype=np.int32), (-1, 1)))
try:
w2 = mkron(i_right, np.ones((n, 1), dtype=np.int32))
i_next = np.hstack((w1, w2))
except:
i_next = w1
i_next = reshape(i_next, (n * r2, -1))
i_next = i_next[ind, :]
nd.edges[0].ind_right = i_next.copy()
nd.edges[0].ind_right_add = i_next.copy()
def right_qr_maxvol(nd):
cr = nd.core.copy()
r1, n, r2 = cr.shape
Rv = nd.edges[1].Rv.copy()
cr = np.tensordot(cr, Rv, 1)
r2 = cr.shape[2]
cr = reshape(cr, (r1, -1))
cr = cr.T
q, Rv = np.linalg.qr(cr)
ind, c = maxvol(q)
Rv = np.dot(q[ind, :], Rv)
#q = np.linalg.solve(q[ind, :].T, q.T).T
q = c.copy()
nd.edges[0].Rv = Rv.T.copy()
q = reshape(q.T, (-1, n, r2))
nd.core = q.copy()
nd.maxvol_right = np.unravel_index(ind, (n, r2), order='F')
""" Recomputation of right indices goes here """
""" Finally, update indices """
i_right = nd.edges[1].ind_right
w1 = mkron(np.ones((r2, 1), dtype=np.int32), reshape(np.arange(n, dtype=np.int32),(-1, 1)))
try:
w2 = mkron(i_right, np.ones((n, 1), dtype=np.int32))
i_next = np.hstack((w1, w2))
except:
i_next = w1
i_next = reshape(i_next, (n * r2, -1))
i_next = i_next[ind, :]
nd.edges[0].ind_right = i_next.copy()
nd.edges[0].ind_right_add = i_next.copy()
def left_qr_maxvol(nd):
cr = nd.core.copy()
r1, n1, r2 = cr.shape
cr = np.tensordot(nd.edges[0].Ru, cr, 1)
#nd.edges[0].Ru = np.ones((1, 1))
r1 = cr.shape[0]
cr = reshape(cr, (r1 * n1, r2))
q, Ru = qr(cr)
ind, c = maxvol(q)
Ru = np.dot(q[ind, :], Ru)
q = c.copy()
nd.core = reshape(q, (r1, n1, r2)).copy()
nd.edges[1].Ru = Ru.copy()
nd.maxvol_left = np.unravel_index(ind, (r1, n1), order='F')
#The philosophical question if this index should be stored on the edge or in the node
#The typical recomputation:
#Take left index somewhere and update. For the first node it comes from the left edge
#So, we can store ind_left on an edge, whereas ind_left_add in the node
""" This is a logically separate function """
i_left = nd.edges[0].ind_left
#Update index
w1 = mkron(np.ones((n1, 1), dtype=np.int32), i_left)
w2 = mkron(reshape(np.arange(n1, dtype=np.int32), (-1, 1)),
np.ones((r1, 1), dtype=np.int32))
i_next = np.hstack((w1, w2))
i_next = reshape(i_next, (r1 * n1, -1))
i_next = i_next[ind, :]
nd.edges[1].ind_left = i_next.copy()
nd.edges[1].ind_left_add = i_next.copy()
def left_qr_maxvol(nd):
cr = nd.core.copy()
r1, n1, r2 = cr.shape
cr = np.tensordot(nd.edges[0].Ru, cr, 1)
#nd.edges[0].Ru = np.ones((1, 1))
r1 = cr.shape[0]
cr = reshape(cr, (r1 * n1, r2))
q, Ru = qr(cr)
ind, c = maxvol(q)
Ru = np.dot(q[ind, :], Ru)
q = c.copy()
nd.core = reshape(q, (r1, n1, r2)).copy()
nd.edges[1].Ru = Ru.copy()
nd.maxvol_left = np.unravel_index(ind, (r1, n1), order='F')
#The philosophical question if this index should be stored on the edge or in the node
#The typical recomputation:
#Take left index somewhere and update. For the first node it comes from the left edge
#So, we can store ind_left on an edge, whereas ind_left_add in the node
""" This is a logically separate function """
i_left = nd.edges[0].ind_left
#Update index
w1 = mkron(np.ones((n1, 1), dtype=np.int32), i_left)
w2 = mkron(reshape(np.arange(n1, dtype=np.int32),(-1, 1)), np.ones((r1, 1), dtype=np.int32))
i_next = np.hstack((w1, w2))
i_next = reshape(i_next, (r1 * n1, -1))
i_next = i_next[ind, :]
nd.edges[1].ind_left = i_next.copy()
nd.edges[1].ind_left_add = i_next.copy()
