Name

sxpca - Principal Component Analysis of images

Usage

Usage in command lines:

sxpca.py input_stack output_stack --subavg=average_image --rad=mask_radius --nvec=number_of_eigenvectors --incore --shuffle --usebuf --mask=maskfile --MPI

Usage in python programming:

output_stack=pca( input_stacks, subavg, mask_radius=-1, nvec=3, incore=False, shuffle=False, genbuf=True, maskfile="", MPI=False, verbose=False )

Input

input_stack
image stack file (can be bdb or hdf)

Output

output_stack
the result of the PCA. saved as stack files

Options

rad
radius for the mask
mask
stack file for the mask
nvec
number of eigenvectors to be generated
verbose
verbose level(0:no verbose, 1: verbose) default is 0
subavg
the average of the images in the input stack file
incore
computations performed in the memory (no buffer on a disk)

Description

Method

Reference

Author / Maintainer

Chao Yang and Wei Zhang

Keywords

category 1
APPLICATIONS

Files

application.py, sxpca.py

See also

Maturity

stable
works for most people, has been tested; test cases/examples available.

Bugs

None. It is perfect.

sxpca (last edited 2013-07-01 13:12:54 by localhost)