usage: prog [options] 
	This program will compute a variance map, using the results from an iteration of e2refine_easy.py as a basis
	for the computation. It uses a bootstrap resampling technique, where random particles are excluded from
	the model with replacement. This is repeated N times, producing a new 3-D model each time. The variance of
	the 3-D models is then computed. Note that this program requires a fair bit of memory. If running the entire program
	on a single machine, you will need enough memory to hold ~5 copies of a 3-D map + whatever is required
	by e2classaverage.py. It may be best-used on downsampled data (also for speed).

Option Type Description
--version None show program's version number and exit
--verbose, -v int verbose level [0-9], higher number means higher level of verboseness
--shrink3d int Shrink the class-averages and make a downsampled variance map
--reslimit float Low-pass filter the individual maps to target the variance to the specified resolution in A. Variance maps cannot be filtered as a post-processing operation. Default = 10
--input str The name of the image containing the particle data
--usefilt str Specify a particle data file that has been low pass or Wiener filtered. Has a one to one correspondence with your particle data. If specified will be used in projection matching routines, and elsewhere.
--path str The name of an existing refine_XX folder to use for input and output
--output str The name of a directory where the variance calculated should be placed. If unspecified will generate one automatically of type refinevar_??.
--mass float The mass of the particle in kilodaltons, used to run normalize.bymass. If unspecified nothing happens. Requires the --apix argument.
--apix float The angstrom per pixel of the input particles. This argument is required if you specify the --mass argument. If unspecified, the convergence plot is generated using either the project apix, or if not an apix of 1.
--nmodels int The number of different bootstrap models to generate for the variance computation. Default=10
--iteration int The refinement iteration to use as a basis for the variance map
--volfiles None This will bypass the construction of the individual resampled models, and use files previously generated with the --keep3d options
--threads int Number of threads to run in parallel on a single computer when multi-computer parallelism isn't useful
--sym None Specify symmetry - choices are: c<n>, d<n>, h<n>, tet, oct, icos
--classkeep float The fraction of particles to keep in each class, based on the similarity score generated by the --cmp argument.
--classkeepsig None Change the keep ('--keep') criterion from fraction-based to sigma-based.
--classiter int The number of iterations to perform. Default is 1.
--classalign str If doing more than one iteration, this is the name and parameters of the 'aligner' used to align particles to the previous class average.
--classaligncmp str This is the name and parameters of the comparitor used by the fist stage aligner Default is dot.
--classralign str The second stage aligner which refines the results of the first alignment in class averaging. Default is None.
--classraligncmp str The comparitor used by the second stage aligner in class averageing. Default is dot:normalize=1.
--classaverager str The averager used to generate the class averages. Default is 'mean'.
--classcmp str The name and parameters of the comparitor used to generate similarity scores, when class averaging. Default is 'dot:normalize=1'
--classnormproc str Normalization applied during class averaging
--classrefsf None Use the setsfref option in class averaging to produce better filtered averages.
--prefilt None Filter each reference (c) to match the power spectrum of each particle (r) before alignment and comparison
--pad int To reduce Fourier artifacts, the model is typically padded by ~25 percent - only applies to Fourier reconstruction
--recon None Reconstructor to use see e2help.py reconstructors -v
--m3dkeep float The percentage of slices to keep in e2make3d.py
--m3dkeepsig None The standard deviation alternative to the --m3dkeep argument
--m3dsetsf None The standard deviation alternative to the --m3dkeep argument
--m3diter int The number of times the 3D reconstruction should be iterated
--m3dpreprocess str Normalization processor applied before 3D reconstruction
--m3dpostprocess str Post processor to be applied to the 3D volume once the reconstruction is completed
--keep3d None Keep all of the individual 3-D models used to make the variance map. This make take substantial disk space.
--lowmem None Make limited use of memory when possible - useful on lower end machines
--parallel, -P str Run in parallel, specify type:<option>=<value>:<option>:<value>
--ppid int Set the PID of the parent process, used for cross platform PPID