https://github.com/cran/pracma
Revision 26e049d70b4a1c237987e260cba68f6a9413736c authored by Hans W. Borchers on 09 April 2019, 04:10:07 UTC, committed by cran-robot on 09 April 2019, 04:10:07 UTC
1 parent bf07673
Tip revision: 26e049d70b4a1c237987e260cba68f6a9413736c authored by Hans W. Borchers on 09 April 2019, 04:10:07 UTC
version 2.2.5
version 2.2.5
Tip revision: 26e049d
lu.R
##
## l u. R LU Decomposition
##
lu <- function(A, scheme = c("kji", "jki", "ijk")) {
stopifnot(is.numeric(A), is.matrix(A))
n <- nrow(A)
if (ncol(A) != n || n <= 1)
stop("Argument 'A' must be a square, positive definite matrix.")
scheme <- match.arg(scheme)
if (scheme == "kji") {
for (k in 1:(n-1)) {
if (A[k, k] == 0)
stop("All diagonal elements of matrix 'A' must be non-zero.")
for (i in (k+1):n) {
A[i, k] <- A[i, k] / A[k, k]
A[i, (k+1):n] <- A[i, (k+1):n] - A[i, k] * A[k, (k+1):n]
}
}
} else if (scheme == "jki") {
if (A[1, 1] == 0)
stop("All diagonal elements of matrix 'A' must be non-zero.")
i <- 2:n
A[i, 1] <- A[i, 1] / A[1, 1]
for (j in 2:n) {
if (A[j, j] == 0)
stop("All diagonal elements of matrix 'A' must be non-zero.")
for (k in 1:(j-1)) {
i <- (k+1):n
A[i, j] <- A[i, j] - A[i, k] * A[k, j]
}
if (j < n) {
i <- (j+1):n
A[i, j] <- A[i, j] / A[j, j]
}
}
} else if (scheme == "ijk") { # 'compact' Doolittle scheme
for (i in 2:n) { # j in 1:n
for (j in 2:i) {
if (A[j, j] == 0)
stop("All diagonal elements of matrix 'A' must be non-zero.")
A[i, j-1] <- A[i, j-1] / A[j-1, j-1]
k <- 1:(j-1)
A[i, j] <- A[i, j] - A[i, k] %*% A[k, j]
}
if (i < n) {
k <- 1:(i-1)
for (j in (i+1):n) {
A[i, j] <- A[i, j] - A[i, k] %*% A[k, j]
}
}
}
}
L <- eye(n) + tril(A, -1)
U <- triu(A)
return(list(L = L, U = U))
}
lufact <- function(A) {
stopifnot(is.numeric(A), is.matrix(A))
m <- nrow(A); n <- ncol(A)
if (m != n || m == 1)
stop("Matrix 'A' must be a square matrix with 2 rows at least.")
detA <- 1
rows <- 1:n
for (p in 1:(n-1)) {
prow <- which.max(abs(A[p:n, p])) + (p-1)
if (p < prow) {
rows[c(p, prow)] <- rows[c(prow, p)]
detA <- -detA
}
detA <- detA * A[rows[p], p]
if (detA == 0) {
warning("Matrix 'A' is singular, no results computed.")
return(list(LU = A, perm = rows, det = NA, x = NULL))
}
for (k in (p+1):n) {
f <- A[rows[k], p] / A[rows[p], p]
A[rows[k], p] <- f
A[rows[k], (p+1):n] <- A[rows[k],(p+1):n] - f*A[rows[p], (p+1):n]
}
}
detA <- detA * A[rows[n], n]
return(list(LU = A, perm = rows, det = detA))
}
lusys <- function(A, b) {
stopifnot(is.numeric(A), is.matrix(A), is.numeric(b))
b <- as.matrix(b)
m <- nrow(A); n <- ncol(A)
if (m != n || m == 1)
stop("Matrix 'A' must be a square matrix with 2 rows at least.")
x <- zeros(n, 1); y <- zeros(n, 1)
r <- c(1:n)
for (p in 1:(n-1)) {
# find the pivot row for column p
q <- which.max(abs(A[p:n, p])) + (p-1)
# interchange rows p and q
A[c(p, q), ] <- A[c(q, p), ]
r[c(p, q)] <- r[c(q, p)]
if (A[p, p] == 0)
stop("Matrix 'A' singular: no unique solution.")
# calculate multiplier and place
for (k in (p+1):n) {
a = A[k, p] / A[p, p]
A[k, p] <- a
A[k, (p+1):n] <- A[k, (p+1):n] - a*A[p, (p+1):n]
}
}
# solve for y
y[1] = b[r[1]]
for (k in 2:n)
y[k] <- b[r[k]] - A[k,1:(k-1)] %*% y[1:(k-1)]
# solve for x
x[n] <- y[n] / A[n, n]
for (k in (n-1):1)
x[k] <- (y[k] - A[k, (k+1):n] %*% x[(k+1):n]) / A[k, k]
return(x)
}
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