Compute log second marginal and transported feature means (sparse CSR) — uot_kl_logpi2_meanF_sparse

Same as `uot_kl_logpi2_meanF_dense_cpp` but for a sparse cost graph.

Usage

uot_kl_logpi2_meanF_sparse_cpp(
  row_ptr,
  col_idx,
  cost,
  n_rows,
  n_cols,
  alpha,
  beta,
  fbar,
  gbar,
  epsilon,
  F = NULL
)

row_ptr: Integer vector of length n+1 with CSR row offsets (0-based or 1-based accepted; if 1-based, it must start at 0 or 1 and be nondecreasing).
col_idx: Integer vector of length nnz giving 1-based column indices.
cost: Numeric vector of length nnz aligned with `col_idx`.
n_rows: Number of source nodes.
n_cols: Number of target nodes.
alpha: Source masses (length n_rows).
beta: Target masses (length n_cols).
fbar: Translation-invariant source potential (length n_rows).
gbar: Translation-invariant target potential (length n_cols).
epsilon: Entropic regularization parameter (> 0).
F: Optional source features (n_rows x D).

A list with `log_pi2` and optionally `mean_F`.