e2spt_binarytree 

usage: prog <output> [options]
	Program to build an initial subtomogram average by averaging pairs from the largest subset
	in --input that is a power of 2. For example, if you supply an input stack with 100 subtomograms,
	this program will build an initial reference using 64, since 64 is the largest power of 2 contained in 100.
	In the first iteration, particle 1 will be averaged with 2, 3 with 4, 5 with 6... etc.
	32 new averages (each an average of 2 subtomograms) will be used for the second iteration.
	Again, 1 will be averaged with 2, 3 with 4, etc... yielding 16 new averages.
	The algorithm continues until the entire subset (64) has been merged into 1 average.
	
	This program imports 'preprocfunc' from e2spt_preproc.py and 'alignment' from e2spt_classaverage.py
	
	--mask=mask.sharp:outer_radius=<safe radius>
	--preprocess=filter.lowpass.gauss:cutoff_freq=<1/resolution in A>
Option Type Description
--version None show program's version number and exit
--path str Default=spt. Directory to store results in. The default is a numbered series of directories containing the prefix 'spt'; for example, spt_02 will be the directory by default if 'spt_01' already exists.
--input str Default=None. The name of the input volume stack. MUST be HDF since volume stack support is required.
--npeakstorefine int Default=1. The number of best coarse alignments to refine in search of the best final alignment. Default=1.
--parallel None Parallelism. See http://eman2.org/Parallel
--ppid int Default=-1. Set the PID of the parent process, used for cross platform PPID
--verbose, -v int Default=0. Verbose level [0-9], higher number means higher level of verboseness; 10-11 will trigger many messages that might make little sense since this level of verboseness corresponds to 'debugging mode'
--plots None Default=False. Turn this option on to generatea plot of the ccc scores during each iteration. Running on a cluster or via ssh remotely might not support plotting.
--subset int Default=0 (not used). Refine only this substet of particles from the stack provided through --input
--preavgproc1 str Default=None. A processor (see 'e2help.py processors -v 10' at the command line) to be applied to the raw particle after alignment but before averaging (for example, a threshold to exclude extreme values, or a highphass filter if you have phaseplate data.)
--preavgproc2 str Default=None. A processor (see 'e2help.py processors -v 10' at the command line) to be applied to the raw particle after alignment but before averaging (for example, a threshold to exclude extreme values, or a highphass filter if you have phaseplate data.)
--weighbytiltaxis str Default=None. A,B, where A is an integer number and B a decimal. A represents the location of the tilt axis in the tomogram in pixels (eg.g, for a 4096x4096xZ tomogram, this value should be 2048), and B is the weight of the particles furthest from the tomogram. For example, --weighbytiltaxis=2048,0.5 means that praticles at the tilt axis (with an x coordinate of 2048) will have a weight of 1.0 during averaging, while the distance in the x coordinates of particles not-on the tilt axis will be used to weigh their contribution to the average, with particles at the edge(0+radius or 4096-radius) weighing 0.5, as specified by the value provided for B.
--weighbyscore None Default=False. This option will weigh the contribution of each subtomogram to the average by score/bestscore.
--align str Default is rotate_translate_3d_tree. See e2help.py aligners to see the list of parameters the aligner takes (for example, if there's symmetry, supply --align rotate_translate_3d_tree:sym=icos). This is the aligner used to align particles to the previous class average. Specify 'None' (with capital N) to disable.
--aligncmp str Default=ccc.tomo.thresh. The comparator used for the --align aligner. Do not specify unless you need to use anotherspecific aligner.
--averager str Default=mean.tomo. The type of averager used to produce the class average. Default=mean.tomo.
--shrink int Default=1 (no shrinking). Optionally shrink the input volumes by an integer amount for coarse alignment.
--shrinkfine int Default=1 (no shrinking). Optionally shrink the input volumes by an integer amount for refine alignment.
--threshold str Default=None. A threshold applied to the subvolumes after normalization. For example, --threshold=threshold.belowtozero:minval=0 makes all negative pixels equal 0, so that they do not contribute to the correlation score.
--mask str Default=None. Masking processor applied to particles before alignment. IF using --clip, make sure to express outer mask radii as negative pixels from the edge.
--maskfile str Default=None. Mask file (3D IMAGE) applied to particles before alignment. Must be in HDF format. Default is None.
--normproc str Default=None (see 'e2help.py processors -v 10' at the command line). Normalization processor applied to particles before alignment. If normalize.mask is used, results of the mask option will be passed in automatically. If you want to turn this option off specify 'None'
--clip int Default=0 (which means it's not used). Boxsize to clip particles as part of preprocessing to speed up alignment. For example, the boxsize of the particles might be 100 pixels, but the particles are only 50 pixels in diameter. Aliasing effects are not always as deleterious for all specimens, and sometimes 2x padding isn't necessary; still, there are some benefits from 'oversampling' the data during averaging; so you might still want an average of size 2x, but perhaps particles in a box of 1.5x are sufficiently good for alignment. In this case, you would supply --clip=75
--preprocess str Any processor (see 'e2help.py processors -v 10' at the command line) to be applied to each volume prior to COARSE alignment. Not applied to aligned particles before averaging.
--preprocessfine str Any processor (see 'e2help.py processors -v 10' at the command line) to be applied to each volume prior to FINE alignment. Not applied to aligned particles before averaging.
--lowpass str Default=None. A lowpass filtering processor (see 'e2help.py processors -v 10' at the command line) to be applied to each volume prior to COARSE alignment. Not applied to aligned particles before averaging.
--lowpassfine str Default=None. A lowpass filtering processor (see 'e2help.py processors -v 10' at the command line) to be applied to each volume prior to FINE alignment. Not applied to aligned particles before averaging.
--highpass str Default=None. A highpass filtering processor (see 'e2help.py processors -v 10' at the command line) to be applied to each volume prior to COARSE alignment. Not applied to aligned particles before averaging.
--highpassfine str Default=None. A highpass filtering processor (see 'e2help.py processors -v 10' at the command line) to be applied to each volume prior to FINE alignment. Not applied to aligned particles before averaging.
--matchimgs None Default=False. Applies filter.matchto to one image so that it matches the other's spectral profile during preprocessing for pair-wise alignment purposes.
--filterbyfsc None Default=False. If on, this parameter will use dynamic FSC filtering. --lowpass will be used to build initial references if no --ref supplied, then, the FSC between the even and odd initial references will be used to filter the data during preprocessing. If --ref is supplied, --lowpass will be used during the first iteration to align the particles against the reference. Thereafter, the FSC between the most current particle average and the original reference (--ref) will be used in the next iteration.
--radius float Default=0 (which means it's not used by default). Hydrodynamic radius of the particle in Angstroms. This will be used to automatically calculate the angular steps to use in search of the best alignment. Make sure the apix is correct on the particles' headers, sine the radius will be converted from Angstroms to pixels. Then, the fine angular step is equal to 360/(2*pi*radius), and the coarse angular step 4 times that.
--precision float Default=1.0. Precision in pixels to use when figuring out alignment parameters automatically using --radius. Precision would be the number of pixels that the the edge of the specimen is moved (rotationally) during the finest sampling, --falign. If precision is 1, then the precision of alignment will be that of the sampling (apix of your images) times the --shrinkfine factor specified.
--search int "Default=8. During COARSE alignment translational search in X, Y and Z, in pixels. Default=8. This WILL overwrite any search: provided through --align, EXCEPT if you provide --search=8, which is the default. In general, just avoid providing search twice (through here and through the aligner, --align). If you do, just be careful to make them consistent to minimize misinterpretation and error.
--searchfine int "Default=2. During FINE alignment translational search in X, Y and Z, in pixels. Default=2. This WILL overwrite any search: provided through --falign, EXCEPT if you provide --searchfine=2, which is the default. In general, just avoid providing search twice (through here and through the fine aligner --falign). If you do, just be careful to make them consistent to minimize misinterpretation and error.
--iterstop int Default=0. (Not used). The program is called to convergence by default (all particles merge into one final average). To stop at an intermediate iteration, provide this parameter. For example, --iterstop=1, will only allow the algorithm to complete 1 iteration; --iterstop=2 will allow it to go through 2, etc.
--savesteps None Default=False. If set, will save the average after each iteration to class_#.hdf. Each class in a separate file. Appends to existing files.
--saveali None Default=False. If set, will save the aligned particle volumes in class_ptcl.hdf. Overwrites existing file.
--saveallalign None Default=False. If set, will save the alignment parameters after each iteration
--sym None Default=None (equivalent to c1). Symmetry to impose -choices are: c<n>, d<n>, h<n>, tet, oct, icos
--postprocess str A processor to be applied to the FINAL volume after averaging the raw volumes in their FINAL orientations, after all iterations are done.
--procfinelikecoarse None If you supply this parameters, particles for fine alignment will be preprocessed identically to particles for coarse alignment by default. If you supply this, but want specific parameters for preprocessing particles for also supply: fine alignment, nd supply fine alignment parameters, such as --lowpassfine, --highpassfine, etc; to preprocess the particles for FINE alignment differently than for COARSE alignment.
--falign str Default=None. This is the second stage aligner used to fine-tune the first alignment.
--faligncmp str Default=ccc.tomo.thresh. The comparator used by the second stage aligner.
--breaksym None Default=False. Break symmetry. Do not apply symmetrization after averaging, even if searching the asymmetric unit provided through --sym only for alignment. Default=False
--randomizewedge None Default=False. This parameter is EXPERIMENTAL. It randomizes the position of the particles BEFORE alignment, to minimize missing wedge bias and artifacts during symmetric alignment where only a fraction of space is scanned
--autocenter str Default=None. Autocenters each averaged pair during initial average generation with --btref and --hacref. Will also autocenter the average of all particles after each iteration of iterative refinement. Options are --autocenter=xform.centerofmass (self descriptive), or --autocenter=xform.centeracf, which applies auto-convolution on the average.
--autocentermask str Default=None. Masking processor to apply before autocentering. See 'e2help.py processors -v 10' at the command line.
--autocenterpreprocess None Default=False. This will apply a highpass filter at a frequency of half the box size times the apix, shrink by 2, and apply a low pass filter at half nyquist frequency to any computed average for autocentering purposes if --autocenter is provided. Default=False.
--tweak None WARNING: BUGGY. This will perform a final alignment with no downsampling [without using --shrink or --shrinkfine] if --shrinkfine > 1.
--nseedlimit int Maximum number of particles\n\t\tto use. For example, if you supply a stack with 150 subtomograms, the program will\n\t\tautomatically select 128 as the limit to use because it's the largest power of 2 that is\n\t\tsmaller than 150. But if you provide, say --nseedlimit=100, then the number of particles\n\t\tused will be 64, because it's the largest power of 2 that is still smaller than 100.