= e2classaverage3d =

This program is the 3-D analog of [[EMAN2/Programs/e2classaverage|e2classaverage]]. It will iteratively align and average stacks
of 3D particles.

For a more extensive description of ''e2classaverage3d'' and its usage including running single particle tomography (SPT) from the Workflow, as well as background on Single Particle Tomography and proposed 'exercises' to learn how to do SPT in EMAN2, download the ''__'''e2SPT USERS' GUIDE'''__'' from the '''EMAN2 TUTORIALS page''':
 http://blake.bcm.edu/emanwiki/EMAN2/Tutorials

To see the entire list of command line options for '''e2classaverage3D''', and an explanation of what they're for, type ''e2classaverage3D.py -h'' at the command line.

==== OPTIONS ====
|| ||--input||string||The name of the input volume stack. MUST be HDF or BDB, since volume stack support is required.||
|| ||--output||string||The name of the output class-average stack. MUST be HDF or BDB, since volume stack support is required.||
|| ||--oneclass||int||Create only a single class-average. Specify the class number.||
|| ||--classmx||string||The name of the classification matrix specifying how particles in 'input' should be grouped. If omitted, all particles will be averaged.||
|| ||--ref||string||Reference image(s). Used as an initial alignment reference and for final orientation adjustment if present. This is typically the projections that were used for classification.||
|| ||--resultmx||string||Specify an output image to store the result matrix. This is in the same format as the classification matrix. http://blake.bcm.edu/emanwiki/EMAN2/ClassmxFiles||
|| ||--iter||int||The number of iterations to perform. Default is 1.||
|| ||--savesteps||bool||If set, will save the average after each iteration to class_#.hdf. Each class in a separate file. Appends to existing files.||
|| ||--saveali||bool||If set, will save the aligned particle volumes in class_ptcl.hdf. Overwrites existing file.||
|| ||--sym||string||Symmetry to impose - choices are: c<n>, d<n>, h<n>, tet, oct, icos||
|| ||--mask||string||Mask processor applied to particles before alignment. Default is mask.sharp:outer_radius=-2||
|| ||--normproc||string||Normalization processor applied to particles before alignment. Default is to use normalize.mask. 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'||
|| ||--preprocess||string||A processor (as in e2proc3d.py) to be applied to each volume prior to alignment. Not applied to aligned particles before averaging.||
|| ||--npeakstorefine||int||The number of best coarse alignments to refine in search of the best final alignment. Default=4.||
|| ||--align||string||This is the aligner used to align particles to the previous class average. Default is rotate_translate_3d:search=10:delta=15:dphi=15||
|| ||--aligncmp||string||The comparator used for the --align aligner. Default is the internal tomographic ccc. Do not specify unless you need to use another specific aligner.||
|| ||--ralign||string||This is the second stage aligner used to refine the first alignment. Default is refine.3d, specify 'None' to disable||
|| ||--raligncmp||string||The comparator used by the second stage aligner. Default is the internal tomographic ccc||
|| ||--averager||string||The type of averager used to produce the class average. Default=mean||
|| ||--keep||float||The fraction of particles to keep in each class.||
|| ||--keepsig||bool||Causes the keep argument to be interpreted in standard deviations.||
|| ||--postprocess||string||A processor to be applied to the volume after averaging the raw volumes, before subsequent iterations begin.||
|| ||--shrink||int||Optionally shrink the input volumes by an integer amount for coarse alignment.||
|| ||--shrinkrefine||int||Optionally shrink the input volumes by an integer amount for refine alignment.||
|| ||--parallel||string||Parallelism. See http://blake.bcm.edu/emanwiki/EMAN2/Parallel||
||-h||--help||bool||show this help message and exit||
||-v||--verbose||int||verbose level [0-9], higner number means higher level of verboseness||

==== USAGE ====

Example:
{{{
e2classaverage3d.py --input=whatever_stack.hdf --output=out_name.hdf --ref=reference.hdf --npeakstorefine=4 -v 3 --mask=mask.sharp:outer_radius=48 --preprocess=filter.lowpass.gauss:cutoff_freq=.025 --align=rotate_translate_3d:search=12:delta=8:dphi=8:verbose=1:sym=icos --parallel=thread:2 --ralign=refine_3d_grid:delta=3:range=9 --averager=mean.tomo
}}}