//:::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: /** @author John Miller * @version 1.1 * @date Wed May 28 16:06:12 EDT 2014 * @see LICENSE (MIT style license file). */ package scalation.linalgebra //:::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: /** The `SVDDecomp` trait specifies the major methods for Singular Value * Decomposition implementations. */ trait SVDecomp { //:::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: /** Deflate the matrix by iteratively turning elements not in the main * diagonal to zero. Then return the vector of singular values (i.e., the main * diagonal). */ def deflate (): VectorD //:::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: /** Deflate the matrix by iteratively turning elements not in the main * diagonal to zero. Then return the vector of singular values and the * matrices of singular vectors. */ def deflateV (): Product } // SVDecomp trait