fix cran submission

Author: kalidouBA

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: dicepro
 Title: Semi-Supervised Deconvolution of Bulk RNA-Seq Data with Hyperparameter Optimization
-Version: 1.0.0
+Version: 1.0.1
 Authors@R: c(
     person("Kalidou", "BA",
            role  = c("aut", "cre"),
@@ -10,9 +10,9 @@ Authors@R: c(
            email = "boris.hejblum@u-bordeaux.fr"))
 Description: Performs semi-supervised deconvolution of bulk RNA sequencing
     (RNA-seq) data. Known cell-type proportions are estimated using
-    supervised methods — CIBERSORTx (CSx), CIBERSORT (CS), FARDEEP (Fast
+    supervised methods -- CIBERSORTx (CSx), CIBERSORT (CS), FARDEEP (Fast
     And Robust DEconvolution of Expression Profiles), and DCQ (Digital
-    Cell Quantifier) — while unknown components are inferred using
+    Cell Quantifier) -- while unknown components are inferred using
     non-negative matrix factorization (NMF) with limited-memory
     Broyden-Fletcher-Goldfarb-Shanno with bounds (L-BFGS-B) optimization.
     Hyperparameters are selected automatically using a Pareto-frontier-based

R/hyperopt_selection.R

@@ -248,8 +248,6 @@
 #'   least: \code{lambda_}, \code{gamma}, \code{frobNorm}, \code{constraint}.
 #' @param W                    List of \eqn{W} matrices, one per trial.
 #' @param H                    List of \eqn{H} matrices, one per trial.
-#' @param savePaths            Character scalar. Root directory (kept for
-#'   API compatibility; no file I/O is performed here).
 #' @param constraint_threshold Numeric scalar. Maximum allowed
 #'   \eqn{|1 - \text{constraint}|}; trials above this threshold are discarded
 #'   (default \code{0.1}).
@@ -270,7 +268,6 @@
 best_hyperParams <- function(trials_df,
                              W,
                              H,
-                             savePaths,
                              constraint_threshold = 0.1) {
 
   # ── Guard: empty input ──────────────────────────────────────────────────────

R/nmf_optim.R

@@ -39,8 +39,6 @@
 #' @param gamma_par  Numeric scalar. Penalty coefficient for the sum-to-one
 #'   constraint (default \code{100}). Reduce if the optimizer returns
 #'   infinite values.
-#' @param path2save  Character scalar. Directory where intermediate results
-#'   may be saved (currently unused; reserved for future use).
 #' @param N_unknownCT Positive integer. Number of latent cell types to
 #'   estimate (default \code{1}).
 #' @param con        Named list of control parameters forwarded to
@@ -73,7 +71,6 @@ nmf_lbfgsb <- function(r_dataset,
                        p_prime     = 0,
                        lambda_     = 10,
                        gamma_par   = 100,
-                       path2save   = "",
                        N_unknownCT = 1L,
                        con         = list(maxit = 3000L)) {
 

R/optimization.R

@@ -56,9 +56,9 @@ run_experiment <- function(dataset,
                            refName,
                            hp_max_evals,
                            algo_select,
-                           output_base_dir       = ".",
+                           output_base_dir = tempdir(),
                            hspaceTechniqueChoose,
-                           gamma_ratio_min        = 10,
+                           gamma_ratio_min = 10,
                            seed) {
 
   paths <- .generate_experiment_paths(