pycroscopy.processing.svd_utils

USID utilities for performing randomized singular value decomposition and reconstructing results

Created on Mon Mar 28 09:45:08 2016

@author: Suhas Somnath, Chris Smith

Functions

plot_svd(h5_main[, savefig, num_plots])

Replots the SVD showing the skree, abundance maps, and eigenvectors.

rebuild_svd(h5_main[, components, cores, …])

Rebuild the Image from the SVD results on the windows Optionally, only use components less than n_comp.

simplified_kpca(kpca, source_data)

Performs kernel PCA on the provided dataset and returns the familiar eigenvector, eigenvalue, and scree matrices.

Classes

SVD(h5_main[, num_components])

This class provides a file-wrapper around the sklearn.utils.extmath.randomized_svd() function.