Perform (multi-reference) 2D-alignment using a maximum-likelihood ( ML ) target function.
Initial references can be generated from random subsets of the experimental images or can be provided by the user (this can introduce bias). The output of the protocol consists of the refined 2D classes (weighted averages over all experimental images). The experimental images are not altered at all.
Although the calculations can be rather time-consuming (especially for many, large experimental images and a large number of references we strongly recommend to let the calculations converge.
Write the input images as a Xmipp metadata file.