How to extract a model from Robust PCA

In general, Robust PCA (rPCA) is an excellent algorithm capable of doing both PCA in the presence of outliers and identifying two classes of outliers, i.e. those that fall within the subset of principal components and those outside (which otherwise would not be detected after dimensionality reduction). Anomaly Detection extension offers rPCA, which implements the algorithm but it hides the PCA model. Is there a way of extracting the PCA model from rPCA? Or should rPCA be moved to the RM core with full features? (of course it is possible to do this in R or a hack in Python)