R/155_reductions_dcp2cone_canonicalizers_lambda_max_canon.R

In CVXR: Disciplined Convex Optimization

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## DO NOT EDIT THIS FILE!! EDIT THE SOURCE INSTEAD: rsrc_tree/reductions/dcp2cone/canonicalizers/lambda_max_canon.R
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## CVXPY SOURCE: reductions/dcp2cone/canonicalizers/lambda_max_canon.py
## lambda_max(A) -> t  subject to  PSD(t*I - A), symmetry check


lambda_max_canon <- function(expr, args, solver_context = NULL) {
  A <- args[[1L]]
  n <- A@shape[1L]
  t <- Variable()
  ## promote scalar t to (n,1) vector, then create diagonal matrix
  prom_t <- cvxr_promote(t, c(n, 1L))
  ## t*I_n - A must be PSD
  tmp_expr <- DiagVec(prom_t) - A
  constr <- list(PSD(tmp_expr))
  ## Enforce symmetry if A is not known to be symmetric
  if (!is_symmetric(A)) {
    ut <- upper_tri(A)
    lt <- upper_tri(t(A))
    constr <- c(constr, list(ut == lt))
  }
  list(t, constr)
}

method(dcp_canonicalize, LambdaMax) <- lambda_max_canon
method(has_dcp_canon, LambdaMax) <- function(expr) TRUE