## tests of R functions based on the lapack module ## ------- examples from ?svd using La.svd --------- hilbert <- function(n) { i <- 1:n; 1 / outer(i - 1, i, "+") } Eps <- 100 * .Machine$double.eps X <- hilbert(9)[,1:6] str(s <- La.svd(X)); D <- diag(s$d) stopifnot(abs(X - s$u %*% D %*% s$vt) < Eps)# X = U D V' stopifnot(abs(D - t(s$u) %*% X %*% t(s$vt)) < Eps)# D = U' X V str(s <- La.svd(X, method = "dgesvd")); D <- diag(s$d) stopifnot(abs(X - s$u %*% D %*% s$vt) < Eps)# X = U D V' stopifnot(abs(D - t(s$u) %*% X %*% t(s$vt)) < Eps)# D = U' X V X <- cbind(1, 1:7) str(s <- La.svd(X)); D <- diag(s$d) stopifnot(abs(X - s$u %*% D %*% s$vt) < Eps)# X = U D V' stopifnot(abs(D - t(s$u) %*% X %*% t(s$vt)) < Eps)# D = U' X V X <- cbind(1, 1:7) str(s <- La.svd(X, method = "dgesvd")); D <- diag(s$d) stopifnot(abs(X - s$u %*% D %*% s$vt) < Eps)# X = U D V' stopifnot(abs(D - t(s$u) %*% X %*% t(s$vt)) < Eps)# D = U' X V # test nu and nv La.svd(X, nu = 0) (s <- La.svd(X, nu = 7)) stopifnot(dim(s$u) == c(7,7)) La.svd(X, nv = 0) La.svd(X, nu = 0, method = "dgesvd") (s <- La.svd(X, nu = 7, method = "dgesvd")) stopifnot(dim(s$u) == c(7,7)) La.svd(X, nv = 0, method = "dgesvd") # test of complex case X <- cbind(1, 1:7+(-3:3)*1i) str(s <- La.svd(X)); D <- diag(s$d) stopifnot(abs(X - s$u %*% D %*% s$vt) < Eps) stopifnot(abs(D - Conj(t(s$u)) %*% X %*% Conj(t(s$vt))) < Eps) # in this case svd calls La.svd str(s <- svd(X)); D <- diag(s$d) stopifnot(abs(X - s$u %*% D %*% Conj(t(s$v))) < Eps) stopifnot(abs(D - Conj(t(s$u)) %*% X %*% s$v) < Eps) ## ------- examples from ?eigen using La.eigen --------- La.eigen(cbind(c(1,-1),c(-1,1))) La.eigen(cbind(c(1,-1),c(-1,1)), symmetric = FALSE) La.eigen(cbind(1,c(1,-1)), only.values = TRUE) La.eigen(cbind(-1,2:1)) # complex values La.eigen(print(cbind(c(0,1i), c(-1i,0))))# Hermite ==> real eigenvalues ## 3 x 3: La.eigen(cbind( 1,3:1,1:3)) La.eigen(cbind(-1,c(1:2,0),0:2)) # complex values La.eigen(cbind(c(1,-1),c(-1,1)), method = "dsyev") set.seed(1234) Meps <- .Machine$double.eps m <- matrix(round(rnorm(25),3), 5,5) sm <- m + t(m) #- symmetric matrix em <- La.eigen(sm); V <- em$vect print(lam <- em$values) # ordered DEcreasingly stopifnot( abs(sm %*% V - V %*% diag(lam)) < 60*Meps, abs(sm - V %*% diag(lam) %*% t(V)) < 60*Meps) em <- La.eigen(sm, method = "dsyev"); V <- em$vect print(lam <- em$values) # ordered DEcreasingly stopifnot( abs(sm %*% V - V %*% diag(lam)) < 60*Meps, abs(sm - V %*% diag(lam) %*% t(V)) < 60*Meps) # check only.values = TRUE too La.eigen(sm, only.values = TRUE) La.eigen(sm, only.values = TRUE, method = "dsyev") ## symmetric = FALSE em <- La.eigen(sm, symmetric = FALSE); V2 <- em$vect print(lam2 <- em$values) # ordered decreasingly in ABSolute value ! print(i <- rev(order(lam2))) stopifnot(abs(lam - lam2[i]) < 60 * Meps) zapsmall(Diag <- t(V2) %*% V2) # orthonormal print(norm2V <- apply(V2 * V2, 2, sum)) stopifnot( abs(1- norm2V / diag(Diag)) < 60*Meps) stopifnot(abs(sm %*% V2 - V2 %*% diag(lam2)) < 60*Meps, abs(sm - V2 %*% diag(lam2) %*% t(V2)) < 60*Meps) ## ------- tests of random real and complex matrices ------ # 100 may cause failures here. eigenok <- function(A, E, Eps=1000*.Machine$double.eps) { V <- E$vect; lam <- E$values stopifnot(abs(A %*% V - V %*% diag(lam)) < Eps, abs(A - V %*% diag(lam) %*% t(V)) < Eps) } Ceigenok <- function(A, E, Eps=1000*.Machine$double.eps) { V <- E$vect; lam <- E$values stopifnot(Mod(A %*% V - V %*% diag(lam)) < Eps, Mod(A - V %*% diag(lam) %*% Conj(t(V))) < Eps) } set.seed(123) sm <- matrix(rnorm(25), 5, 5) sm <- 0.5 * (sm + t(sm)) eigenok(sm, eigen(sm)) eigenok(sm, La.eigen(sm)) eigenok(sm, La.eigen(sm, method="dsyev")) eigenok(sm, La.eigen(sm, sym=FALSE)) sm[] <- as.complex(sm) Ceigenok(sm, eigen(sm)) Ceigenok(sm, La.eigen(sm)) Ceigenok(sm, La.eigen(sm, sym=FALSE)) sm[] <- sm + rnorm(25) * 1i sm <- 0.5 * (sm + Conj(t(sm))) Ceigenok(sm, eigen(sm)) Ceigenok(sm, La.eigen(sm)) Ceigenok(sm, La.eigen(sm, sym=FALSE))