classesbybasis

This will classify and align a set of particles based on an orthogonal basis as produced by svdcmp or geodcmp

classesbybasis <input> <ref set> <basis set> [mask=<rad>] [frac=<num>/<denom>] [nbasis=<n>] [saveali=<aligned out>] [logit=<label>] [groups=<ngrp>] [maxshift=<dxy>] [verbose[=<n>]] [lcmptoo] [clsbylcmp[=<filt rad>]] [quiet] [noisecomp] [skip1] [shrink=<n>] [svweight]

Parameters:


<input>Input images to classify
<ref set>Reference data set
<basis set>A set of orthogonal basis images as generated by svdcmp
[mask=<rad>]Mask radius
[frac=<num>/<denom>]Operate only on a fraction of the raw images
[nbasis=<n>]Number of basis images to use from the basis set. Defaults to all.
[saveali=<aligned out>]File to write aligned images to
[logit=<label>]This specifies a label to use in the particle.log file. This records particle number classification throughout a refinement.
[groups=<ngrp>]This will classify into multiple sets. Used by svdmultirefine.py
[maxshift=<dxy>]Maximum radial translation
[verbose[=<n>]]More verbose output
[lcmptoo]This will also generate an lcmp quality factor for each classification
[clsbylcmp[=<filt rad>]]This will classify based on lcmp comparison of the aligned images
[quiet]No logging
[noisecomp]Noise compensation
[skip1]Skips the first basis vector
[shrink=<n>]Scales the images down for initial orientation search, may be risky but gives a big speedup
[svweight]Weight each basis vector by its singular value (rarely a good idea)

Usage:


EMAN Manual page, generated Tue Oct 8 21:38:47 2002