Hi
I used the full_analysis.py script until convergence for the 4 diffusion
models (sphere, prolate, oblate, ellipsoid), each on one different
computer. Those computer, however, are quite similar, all 32-bits x86
Gentoo Linux with same kernel, gcc, python, etc.
For the final run, I switched on a different system, our dual core
pseudo 64-bits NMR console computer running Red Hat Enterprise 4 with
almost everything different from our Gentoo workstations which are
really more up-to-date. Before starting the final run, I wanted to check
if number rounding would be the same... Well, is wasn't and the run with
the ellipsoid diffusion model ended up saying it wasn't converged yet :
#####################
# Convergence tests #
#####################
Chi-squared test:
chi2 (k-1): 7022.7261139599996
chi2 (k): 7022.7261139563052
The chi-squared value has not converged.
Identical model-free models test:
The model-free models have converged.
Identical parameter test:
Spin system: 26 PHE
Parameter: S2f
Value (k-1): 0.84811676720047557
Value (k): 0.84811676720047491
The model-free parameters have not converged.
Convergence:
[ No ]
As is obvious, the differences are really small, but still relax thinks
it's enough to spend many hours more trying to get absolute reproducibility.
My question.
Is it really necessary to get convergence on so small digits ? Probably
yes, as it was designed this way... So, if yes, why ? Isn't it a problem
for multi-computer processing ?
Thanks !
Séb :)
Convergence on different systems