Robust principal component analysis (robust PCA, RPCA) is a modification of principal component analysis (PCA) which works well with respect to grossly corrupted observations. The package implements robust PCA in exact alternating Lagrangian multipliers (EALM) algorithm and inexact alternating Lagrangian multipliers (IALM) algorithm. The implementation refers the paper and its MATLAB implementation.
Use the package manager pip to install.
pip install git+https://github.com/2020leon/rpca.git@v1.1.0import numpy as np
import rpca.ealm
import rpca.ialm
RNG = np.random.default_rng()
D = RNG.random((20, 20))
A0, E0 = rpca.ealm.fit(D)
A1, E1 = rpca.ialm.fit(D)Contributing is welcome!
MIT