diff --git a/R/methodsplot.R b/R/methodsplot.R
index b97abdd..5884f6a 100644
--- a/R/methodsplot.R
+++ b/R/methodsplot.R
@@ -1,246 +1,102 @@
 methodsplot <- function(x,...) UseMethod("methodsplot")
 methodsplot.default <- function(x, ...) stop("not implemented for this class")
 
-methodsplot.challenge=function(x, 
+methodsplot.challenge=function(x,
                                na.treat=NULL,
                                methods=list(testBased=.%>%test() %>% rank(ties.method = "min"),
                                             meanThenRank=  .%>%  aggregate(  FUN="mean") %>% rank(ties.method = "min"),
                                             medianThenRank=.%>% aggregate(  FUN="median") %>% rank(ties.method = "min"),
                                             rankThenMean= .%>%rank(ties.method = "min") %>%  aggregate(  FUN="mean") %>%rank(ties.method = "min"),
                                             rankThenMedian=.%>%rank(ties.method = "min") %>%  aggregate(  FUN="median") %>%rank(ties.method = "min")
                                             ),
-                               ordering, ...){
-  
-   if (!inherits(x,"list")){
-    if (any(is.na(x[,attr(x, "value")]))) { # only if missings present, else do nothing
-      if (is.null(na.treat)){
-        warning("Please specify na.treat in as.challenge()")
-        return(NULL)
-      } else {
-        x=as.challenge(x,
-                      value=attr(x,"value"), 
-                      algorithm=attr(x,"algorithm") ,
-                      case=attr(x,"case"),
-                      annotator = attr(x,"annotator"),
-                      smallBetter = !attr(x,"largeBetter"),
-                      na.treat=na.treat)
-       } 
-    }
-  } else {
-    if (any(sapply(x, 
-                    function(task) any(is.na(task[,attr(x, "value")])))))  { # only if missings present, else do nothing
-      if (is.null(na.treat)){
-        warning("Please specify na.treat in as.challenge()")
-        return(NULL)
-      } else {
-        xx = melt(x,
-                  id.vars=c(attr(x,"value"), 
-                            attr(x,"algorithm") ,
-                            attr(x,"case"),
-                            attr(x,"annotator"),
-                            attr(x,"by")
-        ))
-        
-        x=as.challenge(xx,
-                       value=attr(x,"value"), 
-                       algorithm=attr(x,"algorithm") ,
-                       case=attr(x,"case"),
-                       by=attr(x,"by"),
-                       annotator = attr(x,"annotator"),
-                       smallBetter = !attr(x,"largeBetter"),
-                       na.treat=na.treat)
-      } 
-    }
-  }
+                               ordering, ...) {
 
-  if (inherits(x,"list"))  {
-    a=lapply(methods,function(fun) fun(x))  
-    dat=melt(a,measure.vars="rank")
-    colnames(dat)[4:5]=c("task","rankingMethod")  
-    
-    if (missing(ordering)){
-      lev=sort(unique(dat$algorithm))
-      lab=lev
-    } else {
-      lev=ordering
-      #   lab=paste(1:length(ordering),ordering)
-      lab=lev
-    }
-    
-    dat=dat%>% 
-      dplyr::rename(rank=.data$value)%>%
-      mutate(rank=factor(.data$rank))%>%
-      mutate(task=factor(.data$task))%>%
-      mutate(algorithm=factor(.data$algorithm, levels=lev,labels = lab))
-    
-    ggplot(data = dat) +
-      aes(x = rankingMethod, y = rank, color=algorithm, group=algorithm ) +
-      geom_line(size=1)+
-      facet_wrap( ~ task)+
-      xlab("Ranking method")  +
-      ylab("Rank")+ 
-      theme(
-        # legend.position = "none",
-        #panel.spacing = unit(0, "lines"),
-        #strip.background = element_blank(),
-        #     strip.text.x = element_text(angle = 90),
-        #    strip.text.y = element_text(angle = 0),
-        strip.placement = "outside",
-        #   axis.text.y = element_text(color=levels(dat$algorithm)) ,
-        axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1) 
-      )#+legend_none()
-    
-  } else {
-    
-    a=lapply(methods,function(fun) fun(x))  
-    if (is.null(x$fulldata)) a=lapply(methods,function(fun) fun(x$data)) else {
-      a=lapply(methods,function(fun) fun(x$fulldata))
-      a=lapply(a, function(aa) {
-        res=aa
-        res$mat=aa$mat[rownames(a$testBased$mat)%in%rownames(x$mat),]
-        res
-      })
-      
-    } 
-    dat=melt(a)
-    colnames(dat)[ncol(dat)]=c("rankingMethod")  
-    
-    if (missing(ordering)){
-      lev=sort(unique(dat$algorithm))
-      lab=lev
+  if (any(sapply(x,
+                  function(task) any(is.na(task[,attr(x, "value")]))))) { # only if missings present, else do nothing
+    if (is.null(na.treat)) {
+      warning("Please specify na.treat in as.challenge()")
+      return(NULL)
     } else {
-      lev=ordering
-      #  lab=paste(1:length(ordering),ordering)
-      lab=lev
+      xx = melt(x,
+                id.vars=c(attr(x,"value"),
+                          attr(x,"algorithm") ,
+                          attr(x,"case"),
+                          attr(x,"annotator"),
+                          attr(x,"by")
+      ))
+
+      x=as.challenge(xx,
+                     value=attr(x,"value"),
+                     algorithm=attr(x,"algorithm") ,
+                     case=attr(x,"case"),
+                     by=attr(x,"by"),
+                     annotator = attr(x,"annotator"),
+                     smallBetter = !attr(x,"largeBetter"),
+                     na.treat=na.treat)
     }
-    
-    dat=dat%>% 
-      mutate(rank=factor(.data$rank))%>%
-      mutate(algorithm=factor(.data$algorithm, levels=lev,labels = lab))
-    
-    ggplot(data = dat) +
-      aes(x = rankingMethod, y = rank, color=algorithm, group=algorithm ) +
-      geom_line(size=1)+
-      xlab("Ranking method")+
-      ylab("Rank")+
-      theme(
-        strip.placement = "outside",
-        axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1) )
-    
   }
-  
-  
-}
-
-
 
+  a=lapply(methods,function(fun) fun(x))
+  dat=melt(a,measure.vars="rank")
+  colnames(dat)[4:5]=c("task","rankingMethod")
 
-methodsplot.ranked=function(x, 
-                            methods=list(testBased=.%>%test() %>% rank(ties.method = "min"),
-                                         meanThenRank=  .%>%  aggregate(  FUN="mean") %>% rank(ties.method = "min"),
-                                         medianThenRank=.%>% aggregate(  FUN="median") %>% rank(ties.method = "min"),
-                                         rankThenMean= .%>%rank(ties.method = "min") %>%  aggregate(  FUN="mean") %>%rank(ties.method = "min"),
-                                         rankThenMedian=.%>%rank(ties.method = "min") %>%  aggregate(  FUN="median") %>%rank(ties.method = "min")
-                                         ), 
-                            ...){
-  
-  na.treat=x$call[[1]][[1]]$na.treat
-  if (any(is.na(x$data[,attr(x, "value")]))) { #missings present
-    if (is.null(na.treat)){
-      warning("Please specify na.treat in as.challenge()")
-      return(NULL)
-    } else {
-      if (is.null(x$fulldata)) {
-        xx=x$data
-        x$data=as.challenge(xx,
-                        value=attr(xx,"value"), 
-                        algorithm=attr(xx,"algorithm") ,
-                        case=attr(xx,"case"),
-                        annotator = attr(xx,"annotator"),
-                        smallBetter = !attr(xx,"largeBetter"),
-                        na.treat=na.treat)
-      } else {
-        xx=x$fulldata
-        x$fulldata=as.challenge(xx,
-                            value=attr(xx,"value"), 
-                            algorithm=attr(xx,"algorithm") ,
-                            case=attr(xx,"case"),
-                            annotator = attr(xx,"annotator"),
-                            smallBetter = !attr(xx,"largeBetter"),
-                            na.treat=na.treat)
-      }
-    } 
+  if (missing(ordering)){
+    lev=sort(unique(dat$algorithm))
+    lab=lev
+  } else {
+    lev=ordering
+    lab=lev
   }
-  
-  
-    if (is.null(x$fulldata)) {
-      a=lapply(methods,function(fun) fun(x$data)) 
-    } else {
-      a=lapply(methods,function(fun) fun(x$fulldata))
-      a=lapply(a, function(aa) {
-        res=aa
-        res$mat=aa$mat[rownames(a$testBased$mat)%in%rownames(x$mat),]
-        res
-      })
-               
-    } 
-    dat=melt(a)
-    colnames(dat)[ncol(dat)]=c("rankingMethod")  
-    
-    ordering=  names(sort(t(x$mat[,"rank",drop=F])["rank",]))
-    lab=lev=ordering
 
-    dat=dat%>% 
-      mutate(rank=factor(.data$rank))%>%
-      mutate(algorithm=factor(.data$algorithm, levels=lev,labels = lab))
-    
-    ggplot(data = dat) +
-      aes(x = rankingMethod, y = rank, color=algorithm, group=algorithm ) +
-      geom_line(size=1)+
-      xlab("Ranking method")+
-      ylab("Rank")+
-      theme(
-        strip.placement = "outside",
-        axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1) )
-    
+  dat=dat%>%
+    dplyr::rename(rank=.data$value)%>%
+    mutate(rank=factor(.data$rank))%>%
+    mutate(task=factor(.data$task))%>%
+    mutate(algorithm=factor(.data$algorithm, levels=lev,labels = lab))
+
+  ggplot(data = dat) +
+    aes(x = rankingMethod, y = rank, color=algorithm, group=algorithm ) +
+    geom_line(size=1)+
+    facet_wrap( ~ task)+
+    xlab("Ranking method")  +
+    ylab("Rank")+
+    theme(
+      strip.placement = "outside",
+      axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
+    )
 }
 
 # methodsplot.ranked.list does not exist, use methodpsplot.challenge instead since consonsus ranking needed for ordering (or alphabetical ordering instead)
 
-
-
-
-
 #similar plot to methods plot, instead of across ranking methods across tasks
 lineplot <- function(x,...) UseMethod("lineplot")
 lineplot.default <- function(x, ...) stop("not implemented for this class")
 
-lineplot.challenge=function(x, 
+lineplot.challenge=function(x,
                             ordering,...){
   if (inherits(x,"list"))  {
     dat=melt(x,measure.vars="rank")
-    colnames(dat)[4]=c("task")  
-    
+    colnames(dat)[4]=c("task")
+
     if (missing(ordering)){
       lev=sort(unique(dat$algorithm))
       lab=lev
     } else {
       lev=ordering
       lab=paste(1:length(ordering),ordering)
     }
-    
-    dat=dat%>% 
+
+    dat=dat%>%
       dplyr::rename(rank=.data$value)%>%
       mutate(rank=factor(.data$rank))%>%
       mutate(task=factor(.data$task))%>%
       mutate(algorithm=factor(.data$algorithm, levels=lev,labels = lab))
-    
+
     ggplot(data = dat) +
       aes(x = task, y = rank, color=algorithm, group=algorithm ) +
       geom_line(size=1)+
       theme(
         axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1) )
-    
+
   } else stop("Only applicable to multiple tasks")
 }
-