def test1():
A = ttensor.ttensor(tensor.tenrands([2,3,4]),
[numpy.random.random([10,2]),
numpy.random.random([30,3]),
numpy.random.random([40,4])]).totensor();
[a,b] = DTA.DTA(A, [1,2,3]);
#print a;
#print b;
Core = numpy.arange(24).reshape([2,3,4]);
#Core = numpy.array([[1,3,5],[2,4,6]] , [[7,9,11],[8,10,12]])
u1 = numpy.array([[1,2],[3,4]]);
u2 = numpy.array([[0,1,0],[1,0,1],[1,1,1]]);
u3 = numpy.array([[1,1,1,1],[1,2,3,4],[1,1,1,1]]);
tt = ttensor.ttensor(tensor.tensor(Core), [u1,u2,u3]);
print tt;
[a,b] = DTA.DTA(tt.totensor(), [1,2,3]);
print a;
print a.totensor();
print b;
def test1():
A = ttensor.ttensor(tensor.tenrands([2, 3, 4]), [
numpy.random.random([10, 2]),
numpy.random.random([30, 3]),
numpy.random.random([40, 4])
]).totensor()
[a, b] = DTA.DTA(A, [1, 2, 3])
#print a;
#print b;
Core = numpy.arange(24).reshape([2, 3, 4])
#Core = numpy.array([[1,3,5],[2,4,6]] , [[7,9,11],[8,10,12]])
u1 = numpy.array([[1, 2], [3, 4]])
u2 = numpy.array([[0, 1, 0], [1, 0, 1], [1, 1, 1]])
u3 = numpy.array([[1, 1, 1, 1], [1, 2, 3, 4], [1, 1, 1, 1]])
tt = ttensor.ttensor(tensor.tensor(Core), [u1, u2, u3])
print tt
[a, b] = DTA.DTA(tt.totensor(), [1, 2, 3])
print a
print a.totensor()
print b
def specialctor(verbose):
print tensor.tenrands([2, 3, 4])
print tensor.tenones([2, 3, 4])
print tensor.tenzeros([2, 3, 4])
print tensor.tendiag([11, 22, 33], [2, 3, 4])
print tensor.tendiag([11, 22], [1, 3, 4])
def specialctor(verbose):
print tensor.tenrands([2,3,4]);
print tensor.tenones([2,3,4]);
print tensor.tenzeros([2,3,4]);
print tensor.tendiag([11,22,33],[2,3,4]);
print tensor.tendiag([11,22],[1,3,4]);
# reverse order for matlab
# tricky double reversal to get first index to vary fastest
ind_tuple = unravel_index(i, d_to_loop[::-1])[::-1]
ind = sls + list(ind_tuple)
mmat(x[ind], format)
print '],[',
for i in x.shape:
print '%d' % i,
print '])'
# bench TTT times
TTT_times = [0.0] * 15
for i in range(1, 16):
A = tensor.tenrands((i, i, i))
B = tensor.tenrands((i, i, i))
start = clock()
C = A.ttt(B)
stop = clock()
TTT_times[i - 1] = stop - start
print ",".join([str(elt) for elt in TTT_times])
# bench CP_ALS times
CP_ALS_times = np.zeros((6, 5))
for i in range(3, 9):
A = tensor.Tensor(np.arange(i**3), (i, i, i))
for j in range(1, 6):
tic = clock()
p = A.cp_als(j, tol=1e-9, maxiters=1000, printitn=1000)
toc = clock()
for i in range(prod(d_to_loop)):
# reverse order for matlab
# tricky double reversal to get first index to vary fastest
ind_tuple = unravel_index(i,d_to_loop[::-1])[::-1]
ind = sls + list(ind_tuple)
mmat(x[ind],format)
print '],[',
for i in x.shape:
print '%d' % i,
print '])'
# bench TTT times
TTT_times = [0.0]*15
for i in range(1, 16):
A = tensor.tenrands((i,i,i))
B = tensor.tenrands((i,i,i))
start = clock()
C = A.ttt(B)
stop = clock()
TTT_times[i-1] = stop-start
print ",".join([str(elt) for elt in TTT_times])
# bench CP_ALS times
CP_ALS_times = np.zeros((6, 5))
for i in range(3,9):
A = tensor.Tensor(np.arange(i ** 3), (i,i,i))
for j in range(1,6):
tic = clock()
p = A.cp_als(j, tol=1e-9, maxiters=1000, printitn=1000)
toc = clock()
