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

Maturity

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

Bugs

None. It is perfect.