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pipeline:utilities:sp_eval_isac
This version (2020/10/21 10:17) was approved by shaikh.The Previously approved version (2020/07/24 23:21) is available.Diff

sp_eval_isac

Separate Into Classes : Separates stacks of particle images into stacks for each class and evaluates results.


Usage

Usage in command line (beta version):

sp_eval_isac.py input_class_avgs output_directory --particles=input_image_stack --align_isac_dir=isac_or_beautifier_dir --filtrad=filter_radius --apix=pixel_size --shrink=shrink_factor --ctf=ctf_mode --nvec=number_of_eigenimages --pca_radius=radius --chains_radius=radius --chains_exe=spchains_executable --applyparams=centering_mode --write_centered --debug --imgformat=image_format --verbosity=verbosity_level


Typical usage

Regular ISAC (top) vs. Evil ISAC (bottom)

The purpose of sp_eval_isac.py is to:

: write particle-membership lists for each class
: write separate stacks for each class, 
: optionally low-pass filter and/or downsample the images, and
: optionally compute eigenimages (basis images) for each class


1. Standard usage: create separate stacks for each class:

sp_eval_isac.py input_class_avgs output_directory 


2. Apply a low-pass filter to the image stacks:

sp_eval_isac.py input_class_avgs output_directory --particles=input_image_stack --filt=filter_radius --apix=pixel_size

Filter radius is in units of Angstroms. If –apix is not specified, program will assume units of pixels^-1.


3. Downsample output image stack:

sp_eval_isac.py input_class_avgs output_directory --particles=input_image_stack --shrink=shrink_factor


4. Apply ISAC alignments to particles:

sp_eval_isac.py input_class_avgs output_directory --particles=input_image_stack --align_isac_dir=isac_or_beautifier_directory

Alignments used by ISAC or beautification will be applied to the particles. In addition, the average and variance for each map will be written.


5. Compute eigenimages (basis images) for each class:

sp_eval_isac.py input_class_avgs output_directory --particles=input_image_stack --align_isac_dir=isac_directory --nvec=number_of_eigenimages --pca_radius=radius

In addition to the average and variance, the requested number of eigenimages will be computed also. If –pca_radius is not provided, the whole image will be used to compute the eigenimages.


6. Apply centering to each class as determined by sp_center_2d3d.py:

sp_eval_isac.py input_class_avgs output_directory --particles=input_image_stack --align_isac_dir=isac_directory --write_centered --applyparams=centering_mode

If you ran sp_center_2d3d.py, you can also apply those centering parameters to the individual particles. The –write_centered flag will write out the particles; omitting the flag will simply write out the alignment parameters without applying them. The options for –applyparams are 'intshifts' for integer shifts and no rotation (i.e., no interpolation) and 'combined' (rotation and shifts).


7. Apply a Gaussian band-pass filter to an image stack (e.g., class averages):

Shape of the band-pass filter
sp_eval_isac.py input_class_avgs output_directory --apix=pixel_size --bandpass_radius=bandpass_radius_angstroms

The default beautifier settings (CTF-correction using a Wiener filter and power-spectrum adjustment) will amplify the low-resolution data, and may make the averages more difficult to interpret. A band-pass filter will dampen the lowest-resolution data, and also the high-resolution noise. This filtration may be helpful for recognizing smaller complexes.

(top) Beautified images and (bottom) band-pass filtered images, centered at 14 Angstroms


Input

Main Parameters

input_class_avgs
Set of 2D class averages, with particle-membership information in header. (default required string)
Filtered, aligned particles of TcdA1 corresponding to class #9 below
output_directory
Directory where outputs will be written. (default required string)
--particles
Particle image stack. (default required string)
--filtrad
Gaussian low-pass filter radius, Angstroms if apix specified below, else pixels^-1. (default None)
--apix
Angstroms per pixel, might be downsampled already by ISAC2. (default None)
--shrink
Downsampling factor, e.g., 6 → 1/6 original size. (default None)
--align_isac_dir
If applying alignments, directory for ISAC output (default None)
--nvec
Number of eigenimages to compute. (default None)
--pca_radius
Radius (pixels) to use for computation of eigenimages. (default None)
--ctf
Applies CTF correction: 'flip' for phase-flipping, 'wiener' for Wiener filter. (default None)
--bandpass_radius
Radius for the center of the band-pass filter, Angstroms.
--bandpass_width
Width of the band-pass filter, units absolute frequency (i.e., px^-1).
--verbosity
Controls how much information to write to screen. (default 1)


Advanced Parameters

--chains_radius
Runs sp_chains.py internally to order input class averages. (default None)
--chains_exe
Path for sp_chains.py if not the default. (default None)
--imgformat
Format of optional output aligned-imaged stacks. (default .mrcs)
--debug
Tests –applyparams=intshifts by applying rotation and integer shifts separately and computing average. (default False)


Output

classmap.txt
Class-to-particle lookup table, one file for all classes
For each class (from left to right): average, variance, and first 5 eigenimages
docclass???.txt
List of particles for each class, one file per class
bdb:stkclass_???
Virtual stacks of particles for each class
bdb:stkflt_???
(Optional) Virtual stacks of filtered particles for each class
params_???.txt
(Optional) Particle alignment parameters, one file per class
stkavgvar.hdf
(Optional) Montage of class averages and variances
stkeigen.hdf
(Optional) Montage of class averages, variances, and eigenimages


Description


Method


Reference


Developer Notes

: Should allow filter types other than Gaussian low-pass


Author / Maintainer

Tapu Shaikh


Keywords

Category 1:: APPLICATIONS


Files

sphire/bin/sp_eval_isac.py


See also


Maturity

Beta:: Under evaluation and testing. Please let us know if there are any bugs.


Bugs

There are no known bugs so far.


pipeline/utilities/sp_eval_isac.txt · Last modified: 2020/10/21 10:17 by shaikh