Q: I have a quetion regarding the reccomended use of "classiter=" in the refine routine. My normal approach to reconstruction involves generating a starting model, then a number of rounds of refine at high angular spacing and starting at classiter=8 to avoid initial model bias, reducing down to classiter=5 then classiter=3. Something like refine 3 ang=10 classiter=8 ..., refine 10 ang=10 classiter=5..., refine 20 ang=10 classiter=3. I would then proceed to reduce ang down until it has reached an appropriate limit based on the target resolution and/or dataset size. My questions are
1) Given that higher values of classiter are expected to yield more blurred models, is it important to refine to psuedo convergence at this stage?
2) When i change to a lower value of ang, should i iterate classiter=8, classiter=5, classiter=3 again again at each new value of ang, or just proceed with classiter=3. I.e. is it important to "reheat" the reconstruction once you have locked into something at high values of ang?