e2classesbyref

usage: prog <references> <particles> <classmx> [options]
	
	** EXPERIMENTAL **
	
	This program classifies a set of particles based on a set of references (usually projections). This program makes use of
	rotational/translational invariants which, aside from computing the invariants, makes the process extremely fast.
	
	

Option Type Description
--version None show program's version number and exit
--sep int The number of classes a particle can contribute towards (default is 1)
--align str specify an aligner to use after classification. Default rotate_translate_tree
--aligncmp str Similarity metric for the aligner
--ralign str specify a refine aligner to use after the coarse alignment
--raligncmp str Similarity metric for the refine aligner
--cmp str Default=auto. The name of a 'cmp' to be used in assessing the aligned images
--classmx str Store results in a classmx_xx.hdf style file
--classinfo str Store results in a classinfo_xx.json style file
--classes str Generate class-averages directly. No bad particle exclusion or iteration. Specify filename.
--averager str Averager to use for class-averages
--invartype None Which type of invariants to generate: (bispec,harmonic)
--msamode str Enable MSA based classification, default=disabled, typically 'pca', see e2msa.py --mode option for full list
--nbasisfp int Only used in MSA mode. Number of MSA basis vectors to use when classifying particles, default=12
--compressbits int Bits to keep when writing class-averages with compression. 0->lossless floating point. Default 10 (3 significant figures)
--threads int Number of threads to run in parallel on the local computer
--verbose, -v int verbose level [0-9], higher number means higher level of verboseness
--ppid int Set the PID of the parent process, used for cross platform PPID