@apunjani Could you clarify if the initial random assignment iterations are always used, even if the initial references are not identical?
In other words, if I am providing known references for 3D classification, should this parameter be set to 0 rather than the default of 5?
Initial random assignment is actually somewhat smart about the references you provided.
In each iteration, the posterior assignment probabilities for each particle against all references are computed. In the first 5 (by default) iterations, assignment is randomized only within sets of particles that have their max probability amongst a set of repeated identical references. So if you provide 3 identical references, all particles will be randomized for the first 5 iters. If you provide 3 distinct references, particles will not be randomized (though for the first 5 iterations, classification will be binary rather than soft). If you provide 2 identical and 1 distinct reference, particles that fall into the first 2 identical classes will be randomized within those 2 classes for the first 5 iters.
Hope that helps!