| --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 |
default=thread:2. Parallelism. See http://blake.bcm.edu/emanwiki/EMAN2/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 |
| --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 |
This is the aligner used to align particles to the previous class average. Default is rotate_translate_3d:search=8:delta=12:dphi=12, 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 for other available normalization processors. 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 |
default=None. 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. |
| --groups |
int |
Default=0 (not used; data not split). This parameter will split the data into a user defined number of groups. For purposes of gold-standard FSC computation later, select --group=2. |
| --clusters |
int |
Number of clusters to group the data in after the 1st iteration, based on correlation. |
| --exclusive_class_min |
int |
Default=0.0 (not used). The minimum multiplicity (number of particles that went into an average) to look for mutually exclusive classes/averages. Two classes are mutually exclusive when non of the members in one are present in the other. In HAC (hierarchical ascendant classification or "all vs all" alignments, classes MERGE, so a class from a later round will be composed of classes from earlier rounds. Some classes remain un-merged for many rounds. If set, this parameter will extract classes with a minimum number of particles (from whatever round/iteration they were generated in) whose members are not present in any other of the extracted classes. The mutually exclusive classes will be put into a separate sub-directory starting with the character 'me_classes'. |
| --minscore |
float |
Default=0.0 (which means this option is off by default and not used). Percent of the maximum score to use as a threshold for the minimum score to allow. For example, if the best pair in the first iteration yielded a score of -15.0, and you supply --minscore=0.9, any pair-wise alignments with a score worse than -15*0.9 = -13.5 will be forbidden. Remember that 'more negative' is 'better' in EMAN2. |
| --maxmergenum |
int |
Default=0 (which means this option is off by default and not used). This is the maximum number of particles ('multiplicity') that any two given averages can have to be allowed to merge. For example, if at some point (some given iteration in the algorithm) a particular average "A" is an average of 10 particles, and --maxmergenum=8, this average "A" will only be allowed to merge with other averages that have 8 particles or less in them. This maintains "big classes" in a mutually exclusive state. For example, if --maxmergenum=1, particles will merge pair-wise in the first round; but after that averages with more than one particle will NOT merge each other, because they will contain 2 or more particles, which exceeds 'maxmergenum'. So in subsequent iterations, the averages formed in the first iteration will continue to take up raw particles or new averages (between single raw particles) might emerge; but "large averages" never inter-merge |