Solve a planned SVD problem. — solve.eigencore_svd

S3 method that runs the planned solver for an SVD problem built by svd_problem(). Most users call svd_partial(), which constructs the problem and dispatches here; call solve() directly when you want to build a problem once and reuse or inspect it. Returns a certified partial singular-value decomposition.

Usage

# S3 method for class 'eigencore_svd_problem'
solve(
  a,
  b,
  rank,
  method = auto(),
  tol = 1e-08,
  vectors = c("both", "left", "right", "none"),
  certify = TRUE,
  allow_dense_fallback = c("auto", "never", "always"),
  ...
)

Arguments

a: Eigencore SVD problem object.
b: Unused second argument reserved by the base solve() generic.
rank: Number of singular values to compute.
method: Solver method descriptor.
tol: Convergence and certification tolerance.
vectors: Which singular-vector sides to compute.
certify: Whether to compute certification diagnostics.
allow_dense_fallback: Dense fallback policy.
...: Reserved for future solver options.

Value

An eigencore_svd_result.