| <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 |
| [savealiparm] | This will save alignment parameters for each image to a text file INSTEAD of writing to the 'saveali' file. |
| [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) |