IndexError: index 0 is out of bounds for axis 0 with size 0

[cool-RR]

Running this code under Python 3.8 produced the following traceback. Note that it seems that max_n=10**7 is related to this bug, because it didn't happen before I used that.

Traceback (most recent call last):
  File "heapz.py", line 115, in <module>
    best, others = big_o.big_o(heapify, data_generator_heapify, max_n=10**6)
  File "C:\Program Files\Python38\lib\site-packages\big_o\big_o.py", line 157, in big_o
    return infer_big_o_class(ns, time, classes, verbose=verbose)
  File "C:\Program Files\Python38\lib\site-packages\big_o\big_o.py", line 97, in infer_big_o_class
    residuals = inst.fit(ns, time)
  File "C:\Program Files\Python38\lib\site-packages\big_o\complexities.py", line 38, in fit
    return residuals[0]
IndexError: index 0 is out of bounds for axis 0 with size 0

[lucasalavapena]

I did some debugging and testing. Like you mentioned this happens at larger max_n, as in the error message it also happens with max_n=10**7. I tried remove different classes and I think the error seems to occur specifically for the Cubic class, for others not. If you follow the error precisely, you see that coeff, residuals, rank, s = np.linalg.lstsq(x, y, rcond=-1) (here) we get an empty numpy vector for the residual for the Cubic case when max_n is large, the reason being that the rank of x is too small (see the relevant numpy docs) and thus numpy gives one an empty array. I think you should be able to compute the residual doing something like np.linalg.norm(y - x @ coeff) which would still work in this case, however, doing that give different residual from numpy.

Why this specifically happens for the Cubic case, I cannot tell you. I tried this also for another case that I made up and again for large max_n specifically the Cubic case has this problem.

[Tachyon5]

Did this get resolved? Seems like @lucasalavapena got to the bottom of it.