Name

sxpca - Principal Component Analysis of images

Usage

Usage in command lines:

sxpca.py input_stack output_stack [start end step] --nfile=number_of_input --rad=mask_radius --mask=maskfile --nvec=number_of_eigenvectors

Usage in python programming:

pca(input_stack, output_stack, rad=mask_radius, nvec=number_of_eigenvectors)

start: the starting image for pca
end: the ending image for pca
step: step of images selected for pca.
nfile: number of input files: sxpca can be applied on a series of stack files (usually the result of the bootstrap calculation). If this is the case, nfile should be the number of bootstrap volume stack file
rad: radius for the mask
mask: stack file for the mask
nvec: number of components will be generated
verbose: verbose level(0:no verbose, 1: verbose) default is 0

Chao Yang and Wei Zhang

application.py, sxpca.py

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

None. It is perfect.