Removed cv argument (#5)

Co-authored-by: Theophilus Quachie Asenso <85598983+Theo-qua@users.noreply.github.com>
Co-authored-by: Waldir Leoncio <w.l.netto@medisin.uio.no>

R/MADMMplasso.R

@@ -50,7 +50,7 @@
 
 #' @example inst/examples/MADMMplasso_example.R
 #' @export
-MADMMplasso <- function(X, Z, y, alpha, my_lambda = NULL, lambda_min = .001, max_it = 50000, e.abs = 1E-3, e.rel = 1E-3, maxgrid, nlambda, rho = 5, my_print = F, alph = 1.8, tree, cv = F, parallel = T, pal = 0, gg = NULL, tol = 1E-4, cl = 4, legacy = FALSE) {
+MADMMplasso <- function(X, Z, y, alpha, my_lambda = NULL, lambda_min = .001, max_it = 50000, e.abs = 1E-3, e.rel = 1E-3, maxgrid, nlambda, rho = 5, my_print = F, alph = 1.8, tree, parallel = T, pal = 0, gg = NULL, tol = 1E-4, cl = 4, legacy = FALSE) {
   N <- nrow(X)
 
   p <- ncol(X)
@@ -211,7 +211,7 @@ MADMMplasso <- function(X, Z, y, alpha, my_lambda = NULL, lambda_min = .001, max
       admm_MADMMplasso(
         beta0, theta0, beta, beta_hat, theta, rho1, X, Z, max_it, my_W_hat, XtY,
         y, N, e.abs, e.rel, alpha, lam[i, ], alph, svd.w, tree, my_print,
-        invmat, cv, gg[i, ],legacy
+        invmat, gg[i, ],legacy
       )
     }
     parallel::stopCluster(cl)
@@ -222,7 +222,7 @@ MADMMplasso <- function(X, Z, y, alpha, my_lambda = NULL, lambda_min = .001, max
         admm_MADMMplasso(
           beta0, theta0, beta, beta_hat, theta, rho1, X, Z, max_it, my_W_hat,
           XtY, y, N, e.abs, e.rel, alpha, lam[g, ], alph, svd.w, tree, my_print,
-          invmat, cv, gg[g, ],legacy
+          invmat, gg[g, ],legacy
         )
       }
     )
@@ -241,7 +241,7 @@ MADMMplasso <- function(X, Z, y, alpha, my_lambda = NULL, lambda_min = .001, max
       my_values <- admm_MADMMplasso(
         beta0, theta0, beta, beta_hat, theta, rho1, X, Z, max_it, my_W_hat, XtY,
         y, N, e.abs, e.rel, alpha, lambda, alph, svd.w, tree, my_print, invmat,
-        cv, gg[hh, ],legacy
+        gg[hh, ],legacy
       )
 
       beta <- my_values$beta
@@ -297,18 +297,10 @@ MADMMplasso <- function(X, Z, y, alpha, my_lambda = NULL, lambda_min = .001, max
     Y_HAT[[hh]] <- y_hat
     THETA[[hh]] <- as.sparse3Darray(theta1)
 
-    if (cv == F) {
-      if (hh == 1) {
-        print(c(hh, (n_main_terms[hh]), non_zero_theta[hh], obj1))
-      } else {
-        print(c(hh, (n_main_terms[hh]), non_zero_theta[hh], obj[hh - 1], obj1))
-      }
+    if (hh == 1) {
+      print(c(hh, (n_main_terms[hh]), non_zero_theta[hh], obj1))
     } else {
-      if (hh == 1) {
-        print(c(hh, (n_main_terms[hh]), non_zero_theta[hh], obj1))
-      } else {
-        print(c(hh, (n_main_terms[hh]), non_zero_theta[hh], obj[hh - 1], obj1))
-      }
+      print(c(hh, (n_main_terms[hh]), non_zero_theta[hh], obj[hh - 1], obj1))
     }
 
     hh <- hh + 1

R/admm_MADMMplasso.R

@@ -27,7 +27,6 @@
 #' However, user decide on a specific structure and then input a tree that follows such structure. 
 #' @param my_print Should information form each ADMM iteration be printed along the way? Default TRUE. This prints  the dual and primal residuals
 #' @param invmat A list of length ncol(y), each containing the C_d part of equation 32 in the paper
-#' @param cv TODO: fill paramater description
 #' @param gg penalty terms for the tree structure for lambda_1 and  lambda_2 for the admm call.
 #' @param legacy If \code{TRUE}, use the R version of the algorithm. Defaults to
 #' C++.
@@ -49,7 +48,7 @@
 
 
 #' @export
-admm_MADMMplasso <- function(beta0, theta0, beta, beta_hat, theta, rho1, X, Z, max_it, W_hat, XtY, y, N, e.abs, e.rel, alpha, lambda, alph, svd.w, tree, my_print = T, invmat, cv = cv, gg = 0.2, legacy = FALSE) {
+admm_MADMMplasso <- function(beta0, theta0, beta, beta_hat, theta, rho1, X, Z, max_it, W_hat, XtY, y, N, e.abs, e.rel, alpha, lambda, alph, svd.w, tree, my_print = T, invmat, gg = 0.2, legacy = FALSE) {
   if (!legacy) {
     out <- admm_MADMMplasso_cpp(
       beta0, theta0, beta, beta_hat, theta, rho1, X, Z, max_it, W_hat, XtY, y,

R/cv_MADMMplasso.R

@@ -52,7 +52,7 @@ cv_MADMMplasso <- function(fit, nfolds, X, Z, y, alpha = 0.5, lambda = fit$Lambd
     print(c("fold,", ii))
     oo <- foldid == ii
 
-    ggg[[ii]] <- MADMMplasso(X = X[!oo, , drop = F], Z = Z[!oo, , drop = F], y = y[!oo, , drop = F], alpha = alpha, my_lambda = lambda, lambda_min = .01, max_it = max_it, e.abs = e.abs, e.rel = e.rel, nlambda = length(lambda[, 1]), rho = rho, tree = TT, my_print = my_print, alph = alph, cv = T, parallel = parallel, pal = pal, gg = gg, tol = tol, cl = cl)
+    ggg[[ii]] <- MADMMplasso(X = X[!oo, , drop = F], Z = Z[!oo, , drop = F], y = y[!oo, , drop = F], alpha = alpha, my_lambda = lambda, lambda_min = .01, max_it = max_it, e.abs = e.abs, e.rel = e.rel, nlambda = length(lambda[, 1]), rho = rho, tree = TT, my_print = my_print, alph = alph, parallel = parallel, pal = pal, gg = gg, tol = tol, cl = cl)
 
     cv_p <- predict.MADMMplasso(ggg[[ii]], X = X[oo, , drop = F], Z = Z[oo, ], y = y[oo, ])
     ggg[[ii]] <- 0

tests/testthat/test-admm_MADMMplasso_cpp.R

@@ -164,7 +164,7 @@ my_values <- suppressWarnings(suppressMessages(admm_MADMMplasso(
   beta0 = beta0, theta0 = theta0, beta = beta, beta_hat = beta_hat,
   theta = theta, rho, X, Z, max_it, W_hat = my_W_hat, XtY, y, N, e.abs,
   e.rel, alpha, lambda = lambda, alph, svd.w = svd.w, tree = TT,
-  my_print = mprt, invmat = invmat, cv = FALSE, gg = gg, legacy = TRUE
+  my_print = mprt, invmat = invmat, gg = gg, legacy = TRUE
 )))
 beta <- my_values$beta
 theta <- my_values$theta