changed parallelization backend to fix bug in demo-eq-surr-RF.R

demo/demo-eq-surr-RF.R

@@ -83,6 +83,12 @@ baleq <- list(Calcite=c(C=1, Ca=1), Dolomite=c(C=2, Ca=1, Mg=1))
 
 balance <- CheckBalance(baleq, sam$design, sam$result)
 
+## we import the caret library
+library(caret)
+
+## we register the parallelization backend
+doParallel::registerDoParallel(4)
+
 set.seed(95014)
 fitControl <- trainControl(method = "none",
                            allowParallel = TRUE, 
@@ -92,14 +98,24 @@ fitControl <- trainControl(method = "none",
                            predictionBounds=rep(TRUE,2))
 
 
-## this takes around 8 minutes using 4 cores
+## modk <- parallel::mclapply(colnames(sam$result), function (x) 
+##     return(train(x=sam$design, y=sam$result[,x],trControl = fitControl,  ##tuneGrid = tg, 
+##                  method="parRF")), mc.cores=8)
+
 traintime <- system.time({
-    mods <- parallel::mclapply(colnames(sam$result), function (x) 
-        return(train(x=sam$design, y=sam$result[,x],trControl = fitControl,
-                     method="parRF")), mc.cores=7)
-    names(mods) <- colnames(sam$result)
+    mods <- foreach(i=colnames(sam$result)) %dopar% caret::train(x=sam$design, y=sam$result[,i], trControl = fitControl, method="parRF")
 })
 
+names(mods) <- colnames(sam$result)
+
+## ## this takes around 8 minutes using 4 cores
+## traintime <- system.time({
+##     mods <- parallel::mclapply(colnames(sam$result), function (x) 
+##         return(train(x=sam$design, y=sam$result[,x],trControl = fitControl,
+##                      method="parRF")), mc.cores=7)
+##     names(mods) <- colnames(sam$result)
+## })
+
 PlotModsInSample(mods, sam$result, sam$design)
 saveRDS(mods, "models_equilibrium_RF.rds")