Improve consistency among message, warnings, and errors

Now message() is uniformly used instead of cat(), warning() is used
for warnings instead of cat(), correct spacing is added between
arguments where appropriate, and error messages do not have trailing
newlines, since stop() already adds one.

R/ComBat.R

@@ -59,13 +59,13 @@ ComBat <- function (dat, batch, mod = NULL, par.prior = TRUE, prior.plots = FALS
         if (!(ref.batch%in%levels(batch))) {
             stop("reference level ref.batch is not one of the levels of the batch variable")
         }
-        message("Using batch =",ref.batch, "as a reference batch (this batch won't change)")
+        message("Using batch = ",ref.batch, " as a reference batch (this batch won't change)")
         ref <- which(levels(as.factor(batch))==ref.batch) # find the reference
         batchmod[,ref] <- 1
     } else {
         ref <- NULL
     }
-    message("Found", nlevels(batch), "batches")
+    message("Found ", nlevels(batch), " batches")
 
     ## A few other characteristics on the batches
     n.batch <- nlevels(batch)
@@ -90,7 +90,7 @@ ComBat <- function (dat, batch, mod = NULL, par.prior = TRUE, prior.plots = FALS
     design <- as.matrix(design[,!check])
 
     ## Number of covariates or covariate levels
-    message("Adjusting for", ncol(design)-ncol(batchmod), 'covariate(s) or covariate level(s)')
+    message("Adjusting for ", ncol(design)-ncol(batchmod), " covariate(s) or covariate level(s)")
 
     ## Check if the design is confounded
     if(qr(design)$rank < ncol(design)) {
@@ -100,7 +100,7 @@ ComBat <- function (dat, batch, mod = NULL, par.prior = TRUE, prior.plots = FALS
         }
         if(ncol(design)>(n.batch+1)) {
             if((qr(design[,-c(1:n.batch)])$rank<ncol(design[,-c(1:n.batch)]))){
-                stop('The covariates are confounded! Please remove one or more of the covariates so the design is not confounded')
+                stop("The covariates are confounded! Please remove one or more of the covariates so the design is not confounded")
             } else {
                 stop("At least one covariate is confounded with batch! Please remove confounded covariates and rerun ComBat")
             }
@@ -110,7 +110,8 @@ ComBat <- function (dat, batch, mod = NULL, par.prior = TRUE, prior.plots = FALS
     ## Check for missing values
     NAs <- any(is.na(dat))
     if(NAs){
-        message(c('Found',sum(is.na(dat)),'Missing Data Values'), sep=' ')}
+        message('Found ', sum(is.na(dat)), ' missing data values')
+    }
     ## print(dat[1:2,])
 
     ##Standardize Data across genes
@@ -254,7 +255,7 @@ ComBat <- function (dat, batch, mod = NULL, par.prior = TRUE, prior.plots = FALS
     }
 
     ## Normalize the Data ###
-    message("Adjusting the Data\n")
+    message("Adjusting the data")
 
     bayesdata <- s.data
     j <- 1

R/helper.R

@@ -110,7 +110,7 @@ it.sol  <- function(sdat,g.hat,d.hat,g.bar,t2,a,b,conv=.0001){
         d.old <- d.new
         count <- count+1
     }
-    ## cat("This batch took", count, "iterations until convergence\n")
+    ## message("This batch took ", count, " iterations until convergence")
     adjust <- rbind(g.new, d.new)
     rownames(adjust) <- c("g.star","d.star")
     adjust
@@ -138,7 +138,7 @@ int.eprior <- function(sdat, g.hat, d.hat){
         LH[LH=="NaN"]=0
         g.star <- c(g.star, sum(g*LH)/sum(LH))
         d.star <- c(d.star, sum(d*LH)/sum(LH))
-        ## if(i%%1000==0){cat(i,'\n')}
+        ## if(i%%1000==0){message(i)}
     }
     adjust <- rbind(g.star,d.star)
     rownames(adjust) <- c("g.star","d.star")

R/irwsva.build.R

@@ -50,7 +50,7 @@ irwsva.build <- function(dat, mod, mod0 = NULL,n.sv,B=5) {
 
   rm(resid)
 
-  cat(paste("Iteration (out of", B,"):"))
+  message("Iteration (out of ", B,"):", appendLF=FALSE)
   for(i in 1:B){
     mod.b <- cbind(mod,uu$vectors[,1:n.sv])
     mod0.b <- cbind(mod0,uu$vectors[,1:n.sv])
@@ -65,8 +65,10 @@ irwsva.build <- function(dat, mod, mod0 = NULL,n.sv,B=5) {
     dats <- dat*pprob
     dats <- dats - rowMeans(dats)
     uu <- eigen(t(dats)%*%dats)
-    cat(paste(i," "))
+    message(" ", i, appendLF=FALSE)
   }
+  # Newline at the end of the message
+  message("")
 
   sv = svd(dats)$v[,1:n.sv, drop=FALSE]
   retval <- list(sv=sv,pprob.gam = pprob.gam, pprob.b=pprob.b,n.sv=n.sv)

R/num.sv.R

@@ -30,7 +30,7 @@
 num.sv <- function(dat, mod,method=c("be","leek"),vfilter=NULL,B=20,seed=NULL) {  
   if(!is.null(vfilter)){
     if(vfilter < 100 | vfilter > dim(dat)[1]){
-      stop(paste("The number of genes used in the analysis must be between 100 and",dim(dat)[1],"\n"))
+      stop(paste("sva error: the number of genes used in the analysis must be between 100 and",dim(dat)[1]))
     }
     tmpv = rowVars(dat)
     ind = which(rank(-tmpv) < vfilter)

R/ssva.R

@@ -34,12 +34,18 @@
 #' 
 
 ssva <- function(dat,controls,n.sv){
-  if(is.null(n.sv)){stop("ssva error: You must specify the number of surrogate variables")}
-  if(dim(dat)[1] != length(controls)){stop("ssva error: You must specify a control vector the same length as the number of genes.")}
-  if(any(controls > 1) | any(controls < 0)){stop("ssva error: Control probabilities must be between 0 and 1.")}
+  if(is.null(n.sv)){
+    stop("ssva error: You must specify the number of surrogate variables.")
+  }
+  if(dim(dat)[1] != length(controls)){
+    stop("ssva error: You must specify a control vector the same length as the number of genes.")
+  }
+  if(any(controls > 1) | any(controls < 0)){
+    stop("ssva error: Control probabilities must be between 0 and 1.")
+  }
 
   if (n.sv == 0) {
-    warning("Returning zero surrogate variables as requested")
+    warning("Returning zero surrogate variables as requested.")
     return(list(sv=matrix(nrow=ncol(dat), ncol=0),
                 pprob.gam = controls, pprob.b=NULL, n.sv=0))
   }

R/sva.R

@@ -39,21 +39,28 @@
 sva <- function(dat, mod, mod0 = NULL,n.sv=NULL,controls=NULL,method=c("irw","two-step","supervised"),
                 vfilter=NULL,B=5, numSVmethod = "be") {
   method <- match.arg(method)
-  if(!is.null(controls) & !is.null(vfilter)){stop("sva error: if controls is provided vfilter must be NULL.\n")}
-  if((method=="supervised") & is.null(controls)){stop("sva error: for a supervised analysis you must provide a vector of controls.\n")}
-  if(!is.null(controls) & (method!="supervised")){method = "supervised"; cat("sva warning: controls provided so supervised sva is being performed.\n")}
+  if(!is.null(controls) & !is.null(vfilter)){
+    stop("sva error: if controls is provided vfilter must be NULL.")
+  }
+  if((method=="supervised") & is.null(controls)){
+    stop("sva error: for a supervised analysis you must provide a vector of controls.")
+  }
+  if(!is.null(controls) & (method!="supervised")){
+    method = "supervised";
+    cat("sva warning: controls provided so supervised sva is being performed.")
+  }
 
   if(!is.null(vfilter)){
     if(vfilter < 100 | vfilter > dim(dat)[1]){
-      stop(paste("sva error: the number of genes used in the analysis must be between 100 and",dim(dat)[1],"\n"))
+      stop(paste("sva error: the number of genes used in the analysis must be between 100 and",dim(dat)[1]))
     }
     tmpv = rowVars(dat)
     ind = which(rank(-tmpv) <= vfilter)
     dat = dat[ind,]
   }
 
   if (!is.null(n.sv) && n.sv == 0) {
-    warning("Returning zero surrogate variables as requested")
+    warning("Returning zero surrogate variables as requested.")
     return(list(sv=matrix(nrow=ncol(dat), ncol=0),
                 pprob.gam = rep(0, nrow(dat)), pprob.b=NULL, n.sv=0))
   }
@@ -63,8 +70,8 @@ sva <- function(dat, mod, mod0 = NULL,n.sv=NULL,controls=NULL,method=c("irw","tw
   }
 
   if(n.sv > 0){
-    cat(paste("Number of significant surrogate variables is: ",n.sv,"\n"))
- 
+    message("Number of significant surrogate variables is: ", n.sv, ".")
+
     if(method=="two-step"){
       return(twostepsva.build(dat=dat, mod=mod,n.sv=n.sv))
     }
@@ -75,7 +82,7 @@ sva <- function(dat, mod, mod0 = NULL,n.sv=NULL,controls=NULL,method=c("irw","tw
       return(ssva(dat,controls,n.sv))
     }
   }else{
-    cat("No significant surrogate variables\n");
+    message("No significant surrogate variables.");
     return(list(sv=matrix(nrow=ncol(dat), ncol=0),
                 pprob.gam = rep(0, nrow(dat)), pprob.b=NULL, n.sv=0))
   }

R/svaseq.R

@@ -41,19 +41,28 @@
 #' 
 
 svaseq <- function(dat, mod, mod0 = NULL,n.sv=NULL,controls=NULL,method=c("irw","two-step","supervised"),
-                vfilter=NULL,B=5, numSVmethod = "be",constant = 1) {
+                   vfilter=NULL,B=5, numSVmethod = "be",constant = 1) {
   method <- match.arg(method)
-  if(!is.null(controls) & !is.null(vfilter)){stop("sva error: if controls is provided vfilter must be NULL.\n")}
-  if((method=="supervised") & is.null(controls)){stop("sva error: for a supervised analysis you must provide a vector of controls.\n")}
-  if(!is.null(controls) & (method!="supervised")){method = "supervised"; cat("sva warning: controls provided so supervised sva is being performed.\n")}
+  if(!is.null(controls) & !is.null(vfilter)){
+    stop("sva error: if controls is provided vfilter must be NULL.")
+  }
+  if((method=="supervised") & is.null(controls)){
+    stop("sva error: for a supervised analysis you must provide a vector of controls.")
+  }
+  if(!is.null(controls) & (method!="supervised")){
+    method = "supervised";
+    warning("sva warning: controls provided so supervised sva is being performed.")
+  }
 
-  if(any(dat < 0)){stop("svaseq error: counts must be zero or greater")}
+  if(any(dat < 0)){
+    stop("svaseq error: counts must be zero or greater.")
+  }
   dat = log(dat + constant)
 
 
   if(!is.null(vfilter)){
     if(vfilter < 100 | vfilter > dim(dat)[1]){
-      stop(paste("sva error: the number of genes used in the analysis must be between 100 and",dim(dat)[1],"\n"))
+      stop(paste("sva error: the number of genes used in the analysis must be between 100 and",dim(dat)[1]))
     }
     tmpv = rowVars(dat)
     ind = which(rank(-tmpv) < vfilter)
@@ -65,8 +74,8 @@ svaseq <- function(dat, mod, mod0 = NULL,n.sv=NULL,controls=NULL,method=c("irw",
   }
 
   if(n.sv > 0){
-    cat(paste("Number of significant surrogate variables is: ",n.sv,"\n"))
- 
+    message("Number of significant surrogate variables is: ", n.sv, ".")
+
     if(method=="two-step"){
       return(twostepsva.build(dat=dat, mod=mod,n.sv=n.sv))
     }
@@ -77,6 +86,7 @@ svaseq <- function(dat, mod, mod0 = NULL,n.sv=NULL,controls=NULL,method=c("irw",
       return(ssva(dat,controls,n.sv=n.sv))
     }
   }else{
-    cat("No significant surrogate variables\n"); return(list(sv=0,pprob.gam=0,pprob.b=0,n.sv=0))
+    message("No significant surrogate variables.")
+    return(list(sv=0,pprob.gam=0,pprob.b=0,n.sv=0))
   }
 }