svds_real_sym <- function(A, k, nu, nv, opts, mattype, extra_args = list())
{
n = nrow(A)
# Check for matrices that are too small
if (n < 3)
stop("nrow(A) and ncol(A) should be at least 3")
# If all singular values are requested, call svd() instead,
# and give a warning
if (k == n)
{
warning("all singular values are requested, svd() is used instead")
return(c(svd(A, nu = nu, nv = nv),
nconv = n, niter = 0))
}
# Matrix will be passed to C++, so we need to check the type.
# Convert the matrix type if A is stored other than double.
#
# However, for symmetric matrices defined in Matrix package,
# they are always double, so we can omit this check.
if (mattype == "matrix" & typeof(A) != "double")
{
mode(A) = "double"
}
# Check the value of 'k'
if (k <= 0 | k >= n)
stop("'k' must satisfy 0 < k < min(nrow(A), ncol(A)).\nTo calculate all singular values, try svd()")
# Check the values of 'nu' and 'nv'
if (nu < 0 | nv < 0 | nu > k | nv > k)
stop("'nu' and 'nv' must satisfy 0 <= nu <= k and 0 <= nv <= k")
# Arguments to be passed to Spectra
spectra.param = list(ncv = min(n, max(2 * k + 1, 20)),
tol = 1e-10,
maxitr = 1000)
# Update parameters from 'opts' argument
spectra.param[names(opts)] = opts
# Any other arguments passed to C++ code, for example use_lower
spectra.param = c(spectra.param, as.list(extra_args))
# Check the value of 'ncv'
if (spectra.param$ncv <= k | spectra.param$ncv > n)
stop("'opts$ncv' must be > k and <= min(nrow(A), ncol(A))")
# Call the C++ function
res = .Call("svds_sym",
A,
as.integer(n),
as.integer(k), as.integer(nu), as.integer(nv),
as.list(spectra.param),
as.integer(MAT_TYPE[mattype]),
PACKAGE = "RSpectra")
return(res)
}
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