Blank rows between the output of `tucker_als()` at each iteration.

[jeremy-myers]

Minimal working example

np.random.seed(0)  # Set seed for reproducibility
X = ttb.sptenrand(
    [5, 4, 3], nonzeros=10
)  # Create a tensor with 10 nonzeros using the 'nonzeros' param.

T = ttb.tucker_als(X, 2)  # best rank(2,2,2) approximation

Tucker Alternating Least-Squares:

 Iter 0: fit = 3.447071e-01 fitdelta = 3.4e-01

 Iter 1: fit = 3.633748e-01 fitdelta = 1.9e-02

 Iter 2: fit = 3.666282e-01 fitdelta = 3.3e-03

 Iter 3: fit = 3.689686e-01 fitdelta = 2.3e-03

 Iter 4: fit = 3.706438e-01 fitdelta = 1.7e-03

 Iter 5: fit = 3.717753e-01 fitdelta = 1.1e-03

 Iter 6: fit = 3.725083e-01 fitdelta = 7.3e-04

 Iter 7: fit = 3.729702e-01 fitdelta = 4.6e-04

 Iter 8: fit = 3.732561e-01 fitdelta = 2.9e-04

 Iter 9: fit = 3.734310e-01 fitdelta = 1.7e-04

 Iter 10: fit = 3.735372e-01 fitdelta = 1.1e-04

 Iter 11: fit = 3.736015e-01 fitdelta = 6.4e-05