use std::num::{Zero, Float}; use na::DMat; use traits::operations::Transpose; use traits::structure::{ColSlice, Eye, Indexable}; use traits::geometry::Norm; use std::cmp::min; /// Get the householder matrix corresponding to a reflexion to the hyperplane /// defined by `vec̀ . It can be a reflexion contained in a subspace. /// /// # Arguments /// * `dim` - the dimension of the space the resulting matrix operates in /// * `start` - the starting dimension of the subspace of the reflexion /// * `vec` - the vector defining the reflection. fn householder_matrix, V: Indexable> (dim: uint, start: uint, vec: V) -> Mat { let mut qk : Mat = Eye::new_identity(dim); let stop = start + vec.shape(); assert!(stop <= dim); for j in range(start, stop) { for i in range(start, stop) { unsafe { let vv = vec.unsafe_at(i) * vec.unsafe_at(j); let qkij = qk.unsafe_at((i, j)); qk.unsafe_set((i, j), qkij - vv - vv); } } } qk } /// QR decomposition using Householder reflections /// # Arguments /// * `m` - matrix to decompose pub fn decomp_qr(m: &DMat) -> (DMat, DMat) { let rows = m.nrows(); let cols = m.ncols(); assert!(rows >= cols); let mut q : DMat = Eye::new_identity(rows); let mut r = m.clone(); let iterations = min(rows - 1, cols); for ite in range(0u, iterations) { let mut v = r.col_slice(ite, ite, rows); let alpha = if unsafe { v.unsafe_at(ite) } >= Zero::zero() { -Norm::norm(&v) } else { Norm::norm(&v) }; unsafe { let x = v.unsafe_at(0); v.unsafe_set(0, x - alpha); } let _ = v.normalize(); let qk: DMat = householder_matrix(rows, 0, v); r = qk * r; q = q * Transpose::transpose_cpy(&qk); } (q, r) }