plot.boxplot=function(gene, logicalVectors, names.lv=NULL, clean.name=c("Cancer_", ":::::", "DUFVA_", ".*.:"), data=NULL, matrix=NULL, color.v=NULL, order.bl=F, y.range=NULL, spread=F, sample.annotation=NULL, sample.annotation.color="yellow", N=F,sample.color.continuous=NULL,sample.color.continuous.colors=c("#a52a2a", "#d4d3d1", "#fea719"), sample.color.continuous.breaks=c(0, 0.5, 1), sample.color.continuous.limits=c(0,1), sample.color.continuous.title="CIITA methylation\nbeta value", intercept.y=NULL, intercept.y.2=NULL, ylab="Expression (log2)", outlier.size=0.5) {

  library(ggplot2)

  if(is.null(matrix)&is.null(data))stop("No data to plot, check data/matrix")

  if(is.null(names.lv))names.lv=names(logicalVectors)

  if(!all(clean.name=="")|!is.null(clean.name)){

    clean.name=paste(clean.name, collapse="|")

    title=gsub("N:....:|:::::|DUFVA_|.*.:", "", gene)

    names.lv=gsub("Cancer_", " ", names.lv)

    names.lv=gsub(eval(clean.name), "",  names.lv)

    title=gsub(eval(clean.name), "", title)

    names.lv=gsub("_", " ",  names.lv)

    title=gsub("_", " ", title)

  }

  if(is.null(color.v)){

    # http://tools.medialab.sciences-po.fr/iwanthue/

    color.v=c("#d7a85b",

              "#4d56b9",

              "#acb839",

              "#5e2883",

              "#42c87f",

              "#bf4da5",

              "#75b550",

              "#8479e6",

              "#cea632",

              "#5488e3",

              "#d38725",

              "#3e397f",

              "#a4a94e",

              "#be7cde",

              "#4d7122",

              "#8460b5",

              "#62ac6a",

              "#86275d",

              "#43c8ac",

              "#cf483f",

              "#748ed7",

              "#ca6e37",

              "#de91dc",

              "#926a26",

              "#94589d",

              "#822c17",

              "#d76092",

              "#d2745b",

              "#b24258",

              "#d35760")[seq(logicalVectors)]

  }

  if(!is.null(matrix)){

    gene2=ifelse(grepl("GEXP", gene), gene, paste0("'N:GEXP:", gene, ":::::'"))

    D=as.numeric(read.delim(pipe(paste0("grep -Fw ", gene2, " ", matrix)), row.names = 1, header=F))

    names=scan(pipe(paste0("head -n1 ", matrix)), "n")

  }

  if(!is.null(data)){

    if("TP53"%in%colnames(data)){

      D = as.numeric(data[,colnames(data)%in%gene])

      names=colnames(data)

    }else{

      D = as.numeric(data[rownames(data)%in%gene,])

      names=colnames(data)

    }

  }

  bplot_list=lapply(logicalVectors, function(v){

    D[v]

  })

  if(order.bl){

    ord=sapply(bplot_list, median)

    color.v=color.v[order(ord, decreasing = T)]

    bplot_list=bplot_list[order(ord, decreasing = T)]

  }

  if(!is.null(sample.annotation)){

    sample.annotation=lapply(logicalVectors, function(v){

      D[v]%in%D[names%in%sample.annotation&v]

    })

    names(sample.annotation)=gsub("_", " ", names.lv)

    if(order.bl)sample.annotation=sample.annotation[order(ord, decreasing = T)]

  }

  if(!is.null(sample.color.continuous)){

    sample.color.continuous=lapply(logicalVectors, function(v){

      sample.color.continuous[v]

    })

    if(order.bl)sample.color.continuous=sample.color.continuous[order(ord, decreasing = T)]

  }

  if(N){

    names(bplot_list)=paste0(names(bplot_list), " (n=", sapply(logicalVectors, sum, na.rm=T), ")")

  }

  plots=plot.boxplot.list(bplot_list, gene, color.v, order.bl, y.range, spread, sample.annotation, sample.annotation.color, sample.color.continuous,sample.color.continuous.colors,sample.color.continuous.breaks,sample.color.continuous.limits,sample.color.continuous.title, intercept.y, intercept.y.2, ylab, outlier.size)

  return(plots)

}

plot.boxplot.list=function(bplot_list, title="boxplot", color.v, order.bl=F, y.range=NULL, spread=F, sample.annotation=NULL, sample.annotation.color="red", sample.color.continuous=NULL,sample.color.continuous.colors=c("#a52a2a", "#d4d3d1", "#fea719"), sample.color.continuous.breaks=c(0, 0.5, 1), sample.color.continuous.limits=c(0,1), sample.color.continuous.title="methylation\nbeta value", intercept.y=NULL, intercept.y.2=NULL, ylab="Expression (log2)", outlier.size=0.5){

  if(!is.null(sample.color.continuous)){

    df=data.frame(reshape2::melt(bplot_list), "cont.colorv"=unlist(sample.color.continuous))

  }else{

    df=reshape2::melt(bplot_list)

  }

  df$class <- factor(df[,2], levels = unique(as.character(df[,2])),ordered = TRUE)

  df$Expression=as.numeric(as.vector(df[,1]))

  p <- ggplot(data=df, aes(x=class, y=Expression))+stat_boxplot(geom = "errorbar", width = 0.5)

  if(spread){

    names(color.v)=levels(df$class)

    colScale=scale_colour_manual(name="class", values=color.v)

    df$spreadCol=color.v[match(df$class, names(color.v))]

    if(!is.null(sample.annotation)){

      df$spreadCol2=ifelse(melt(sample.annotation)[,1], sample.annotation.color, "grey20")

      p=p+geom_boxplot(size = 0.0001, outlier.colour = NA, outlier.size = 0, fill=unique(df$spreadCol), fatten = 10000)+

        geom_jitter(width = .3, size=outlier.size, shape=21, color="grey20", fill=df$spreadCol2, stroke = 0)

    }

    if(is.null(sample.annotation)&!is.null(sample.color.continuous)){

      library(ggnewscale)

      p=p+geom_boxplot(size = 0.0001, outlier.size = 0,outlier.colour = NA,outlier.shape = NA, fill=unique(df$spreadCol), fatten = 10000)+

        scale_fill_manual(values = unique(df$spreadCol), na.value = "#d4d3d1") + # scale for box fill (cancer color)

        new_scale_fill() +

        geom_jitter(aes(fill = cont.colorv), width = .3, size=outlier.size, shape=21, stroke = 0) +

        scale_fill_gradientn(colors = sample.color.continuous.colors, breaks = sample.color.continuous.breaks, limits = sample.color.continuous.limits, guide = "colourbar") + # scale for dot fill (methylation beta value)

        guides(fill = guide_colorbar(title = sample.color.continuous.title))

    }

    if(is.null(sample.annotation)&is.null(sample.color.continuous)){

      p=p+geom_boxplot(size = 0.0001, outlier.colour = NA, outlier.size = 0, fill=unique(df$spreadCol), fatten = 10000)+

        geom_jitter(width = .3, size=outlier.size, shape=21, color="grey20", fill=df$spreadCol)

    }

  }else{

    p=p+geom_boxplot(size = 0.0001, outlier.colour = "grey20", outlier.size = 1, fill=color.v, fatten = 10000)

  }

  if(!is.null(intercept.y)) p=p+geom_hline(yintercept=intercept.y, linetype="dashed", color = "red")

  if(!is.null(intercept.y.2)) p=p+geom_hline(yintercept=intercept.y.2, linetype="dashed", color = "blue")

  p2 <- p +

    #theme with white background

    theme_bw() +

    # titles

    theme(plot.title = element_text(color="black", size=10, hjust=0)) +

    theme(axis.title = element_text(color="black", face=NULL, size=8,angle = 90)) +

    theme(axis.title.y = element_text(size = 8, angle = 90, color="black", face=NULL)) +

    ylab(ylab) +

    xlab("") +

    labs(title=title) +

    #eliminates background, gridlines, and chart border

    theme(plot.background = element_blank(),

          panel.grid.major = element_blank(),

          panel.grid.minor = element_blank())+

    theme(panel.border= element_blank())+

    theme(plot.margin = unit(c(0.1,0.1,0.1,5), "cm"))+

    #draws x and y axis line

    theme(axis.line = element_line(),

          axis.line.x = element_line(color="black", size = 0.5),

          axis.line.y = element_line(color="black", size = 0.5)) +

    # X - axis text

    theme(axis.text.x = element_text(angle=45, hjust=1, color="black", size = 8, face=NULL),

          axis.text.y = element_text(hjust=1, color="black", size = 8, face=NULL))+

    # if want to limit to range

    if(!is.null(y.range))scale_y_continuous(breaks=seq(y.range[1], y.range[2], (y.range[2]-y.range[1])/5), limits = y.range)

  return(p2)

}

get.logical=function(annovector, a=NULL, filterv=NULL, PREFIX=NULL){

  if(sum(filterv)<1&!is.null(filterv))stop("Logical filtering vector is empty")

  if(class(annovector)!="list")stop("Annotation vector should be a list")

  binaryfeatures=unlist(lapply(annovector, function(annov, a, filterv, PREFIX){

    if(is.null(filterv))filterv=rep(T, length(annov))

    if(is.null(a)){

      a=unique(annov[filterv])

      a=a[!(is.na(a)|a=="na")]

      annov[!filterv]=NA

    }else{

      b=unique(annov[filterv])

      a=a[a%in%b]

    }

    FUN_BINARYFEAT=function(type, annovector){

      logv=annovector%in%type

    }

    # make binary features

    binaryfeats=lapply(a, FUN_BINARYFEAT, annov)

    if(!is.null(PREFIX))names(binaryfeats)=paste0(a ,"_", PREFIX)

    if(is.null(PREFIX))names(binaryfeats)=a

    return(binaryfeats)

  }, a, filterv, PREFIX), recursive = F)

}

logicalList2vector=function(lv.list){

  classes=names(lv.list)

  vector.classes=rep(NA, length(lv.list[[1]]))

  for(i in seq(classes)){

    vector.classes[lv.list[[i]]]=classes[i]

  }

  return(vector.classes)

}

get.data.type=function(type, feats, fm.f, ord, FDR=F, clean_name=T){

  pl=fm.f[match(feats[grepl(type, feats)], rownames(fm.f)),ord,drop=F]

  if(dim(pl)[1]==0)return(NULL)

  n=do.call(rbind, strsplit(rownames(pl), ":"))[,1:3]

  if(is.null(dim(n)))n=data.frame(t(n))

  rownames(pl)=apply(n, 1, paste, collapse = ":")

  if(clean_name){

    rownames(pl)=make.unique(gsub(".*.:", "", rownames(pl)))

    rownames(pl)=gsub("_", " ", rownames(pl))

  }

  return(pl)

}

make.hm=function(i, dat, param, cluster_rows=F, cluster_columns=F, split=NULL, text_annot=NULL, clean_name=T, WIDTH=50, use_raster=T, show_column_names=F, ...){

  pl=data.matrix(dat[[i]])

  par=param[i,]

  name=par$name

  color=gsub(" ", "", as.character(unlist(strsplit(par$colors, ","))))

  values=as.numeric(unlist(strsplit(par$values, ",")))

  type=ifelse(grepl("^B:", par[1]), "discrete", "numeric")

  labels_legend=values

  if(grepl("^B:", par[1]))labels_legend=c(0,1)

  if(par$scale){

    pl=t(scale(t(pl)))

    pl[pl>2]=2

    pl[pl<(-2)]=-2

    labels_legend=c(-2,-1,0,1,2)

    name=paste(name, "Z-score", sep="\n")

  }

  ha.r=NULL

  if(!is.null(text_annot)&!cluster_rows){

    if(clean_name){

      names(text_annot)=make.unique(gsub(".*.:", "",  names(text_annot)))

      names(text_annot)=gsub("_", " ",  names(text_annot))

    }

    text=text_annot[match(rownames(pl), names(text_annot))]

    if(any(!is.na(text))) ha.r = rowAnnotation(value = anno_text(text, gp = gpar(fontsize = 8)))

  }

  p=Heatmap(pl, cluster_columns = cluster_columns, cluster_rows = cluster_rows, row_names_side = "right", 

            column_names_gp = gpar(fontsize = 8), 

            row_names_gp = gpar(fontsize = 8),

            column_title_gp = gpar(fontsize = 9),

            name=par$type, col = colorRamp2(values, color), 

            show_column_names = show_column_names, width = unit(WIDTH, "mm"),

            # rect_gp = gpar(col = "white", lty = 1, lwd = 0.5),

            height = unit(3*dim(pl)[1], "mm"),

            left_annotation = ha.r,

            use_raster = use_raster,

            heatmap_legend_param = list(legend_direction = "horizontal",title=name,

                                        legend_width = unit(20, "mm"), title_position = "topcenter",color_bar = type, at = labels_legend, title_gp = gpar(fontsize = 8), legend_gp = gpar(fontsize = 8)),

            column_split = split)

  return(p)

}

plot.complexHM.fm=function(feats, fm.f, annotdf=NULL, order_columns=NULL, order_rows=NULL, clean_name=T, feats.barplot=NULL,text_annot=NULL, split.columns=T, plotting.param="plotting_param_fm.txt", NAME=NULL, barplot.height=3, WIDTH=50, show_column_names=F, use_raster=F){

  if(is.null(order_columns)){

    cluster_columns=T

    ord=colnames(fm.f)

  }else{

    cluster_columns=F

    ord=order_columns

  } 

  if(is.null(order_rows)){

    cluster_rows=T

    ord_rows=feats

  }else{

    cluster_rows=F

    ord_rows=order_rows

  }

  if("adj.p"%in%colnames(feats)){

    FDR=feats$adj.p

    feats=unique(feats$featureB)

  }else{

    feats=as.character(feats)

  }

  feats=feats[feats%in%rownames(fm.f)]

  param=data.table::fread(plotting.param, data.table = F)

  datatypes=param$type

  dat=lapply(datatypes, get.data.type, feats, fm.f, ord, FDR=F)

  names(dat)=datatypes

  dat=dat[!sapply(dat, is.null)]

  # remove NA columns if they exist, otherwise clustering fails:

  if(cluster_columns){

    rm=lapply(dat, function(d){colSums(is.na(d))==dim(d)[1]})

    filt=Reduce("|", rm)

    dat=lapply(dat, function(d)d[,!filt])

    if(sum(filt)>0)warning(paste("Removed ", sum(filt), "samples, all samples NA for clustering"))

  }

  if(split.columns&!is.null(annotdf)){

    split=as.character(annotdf[ord,1])

    split=factor(split, levels=unique(split))

  }else{

    split=NULL

  }

  param=param[match(names(dat), param[,1]),]

  panels=lapply(seq(dat), make.hm, dat, param, cluster_rows, cluster_columns, split, text_annot, clean_name, WIDTH,use_raster, show_column_names)

  panels=panels[!is.null(panels)]

  if(!is.null(annotdf)){

    annotdf=annotdf[ord,,drop=F]

    h=dim(annotdf)[2]*3

    if(!is.null(feats.barplot)){

      f=annotdf[,feats.barplot,drop=F]

      annotdf=annotdf[,!colnames(annotdf)%in%feats.barplot, drop=F]

      if(dim(annotdf)[2]==0)annotdf=data.frame("dummy"=c(rep(0, dim(f)[1])[-1], 1))

      h=dim(annotdf)[2]*3+barplot.height

      l.barplot=paste("HeatmapAnnotation(", paste(paste0("'", feats.barplot, "' = anno_barplot(as.numeric(f[,",seq(dim(f)[2]),"]), axis = T, gp = gpar(fill = 'grey25'), height=unit(", barplot.height, ", 'mm'))"), collapse=", "),", height = unit(dim(f)[2]*", h,", 'mm'), annotation_name_gp = gpar(fontsize = 8))")

      ha = eval(parse(text = l.barplot))

    }else{

      ha=HeatmapAnnotation(df = annotdf)

    }

    add=Heatmap(t(annotdf), cluster_columns = cluster_columns, top_annotation = ha, cluster_rows = cluster_rows, row_names_side = "right", 

                column_names_gp = gpar(fontsize = 8), 

                row_names_gp = gpar(fontsize = 8), 

                column_title_gp = gpar(fontsize = 9),

                show_column_names = show_column_names, width = unit(WIDTH, "mm"), 

                height = unit(h+10, "mm"),

                use_raster=use_raster,

                heatmap_legend_param = list(legend_direction = "horizontal",title="Annotations",

                                            legend_width = unit(20, "mm"), title_position = "topcenter", title_gp = gpar(fontsize = 8), legend_gp = gpar(fontsize = 8)), column_split = split)

    panels=append(list("Annotations"=add), panels)

    dat=append(list("Annotations"=t(annotdf)), dat)

  }

  heights=colSums(sapply(panels, component_height))+60

  nrows=sum(heights)

  rows_needed=heights

  ind=findInterval(seq(nrows), c(1,cumsum(rows_needed)), rightmost.closed = T, left.open=T)

  figure <-multipanelfigure:: multi_panel_figure(width = 150+WIDTH, height = 40+sum(heights), rows = nrows, columns = 1, panel_label_type = "lower-alpha", unit = "mm", row_spacing = unit(5, "mm"))

  for(i in seq(panels))figure <- multipanelfigure::fill_panel(figure,  panels[[i]], row = which(ind==i), column = 1)

  if(!is.null(NAME))multipanelfigure::save_multi_panel_figure(figure, filename=paste0(NAME, "_fm_complexheatmap.pdf"), limitsize = FALSE)

  return(figure)

}

plot.scatter=function(x, y,namev, lv=NULL, group=NULL, colorv=NULL, main="XY-plot", axis.plot=F, xlab="x", ylab="y", SIZE=3, add.proportions=F,add.density=F, add.legend=T,add.labels=F, rasterize=T, width=77, height=74, text.size=10){

  library(ggplot2)

  library(reshape2)

  library(RColorBrewer)

  library(ggrepel)

  library(ggrastr)

  library(cowplot)

  library(dplyr)

  if(is.null(colorv)){

    # http://tools.medialab.sciences-po.fr/iwanthue/

    colorv=c( "#acb839",

              "#42c87f",

              "#bf4da5",

              "#8479e6",

              "#cea632",

              "#5488e3",

              "#d76092",

              "#d38725",

              "#3e397f",

              "#a4a94e",

              "#be7cde",

              "#4d7122",

              "#8460b5",

              "#62ac6a",

              "#d7a85b",

              "#86275d",

              "#43c8ac",

              "#cf483f",

              "#748ed7",

              "#ca6e37",

              "#de91dc",

              "#926a26",

              "#94589d",

              "#5e2883",

              "#822c17",

              "#4d56b9",

              "#d2745b",

              "#b24258",

              "#75b550",

              "#d35760")

    # image(seq(colorv), 1, as.matrix(1:length(colorv)), col=colorv,

    #       xlab="", ylab = "", xaxt = "n", yaxt = "n", bty = "n")

  }

  dat=data.frame("name"=namev, "x"=x,"y"=y)

  n=paste0("N = ", dim(dat)[1])

  if(is.null(lv))lv=rep(F, length(x))

  dat$Significant=lv

  if(is.null(group)){

    dat$group=""

    colorv=colorv[1]

  }else{

    dat$group=factor(group, levels=unique(group))

    dat=dat[order(dat$group),]

  }

  myColors <- colorv

  names(myColors) <- levels(dat$group)

  colScale <- scale_colour_manual(name = "group",values = myColors)

  if(add.legend){

    legend <- cowplot::get_legend(ggplot(dat, aes(x, y, colour = group)) + theme_bw() +

                                    geom_point(size=0.6) + colScale +theme(legend.position = "bottom", legend.direction = "horizontal", legend.title = element_blank(), 

                                                                           legend.key=element_blank(), legend.box.background=element_blank(),

                                                                           legend.text=element_text(size = text.size, face = "bold", family="Helvetica"))+

                                    theme(plot.margin=unit(c(1,1,1,1), "mm"))+

                                    guides(colour = guide_legend(override.aes = list(size=text.size/3))))

    nrow=4

  }else{

    nrow=3

  }

  if(rasterize){

    p=ggplot(dat, aes(x, y, colour = group)) +

      geom_point_rast(size=SIZE, raster.width = 3, raster.height = 3) + colScale +

      geom_point_rast(data = subset(dat, dat$Significant), size=SIZE*1.5, raster.width = 3, raster.height = 3)

  }else{

    p=ggplot(dat, aes(x, y, colour = group)) +

      geom_point(size=SIZE) + colScale +

      geom_point(data = subset(dat, dat$Significant), size=SIZE*1.5)

  }

  p=p +

    theme_classic(base_size = 12) +

    ggtitle(paste(main, n, sep="\n")) +

    labs(x = xlab, y = ylab, fill = "") +

    scale_y_continuous(breaks = pretty(dat$y, n = 6))+

    theme(legend.position = "none", legend.direction = "horizontal",

          axis.line = element_line(size=1, colour = "black"),

          panel.grid.major = element_blank(),

          panel.grid.minor = element_blank(),

          panel.border = element_rect(colour = "black", fill=NA, size=1),

          # panel.border = element_blank(), panel.background = element_blank(),

          plot.title = element_text(size = text.size, face = "bold", family="Helvetica"),

          text=element_text()

    )+

    theme(

      axis.text.x = element_text(colour="grey20",size=text.size,face="plain", family="Helvetica"),

      axis.text.y = element_text(colour="grey20",size=text.size,face="plain", family="Helvetica"),

      axis.title.x = element_text(colour="grey20",size=text.size,face="plain", family="Helvetica"),

      axis.title.y = element_text(colour="grey20",size=text.size,face="plain", family="Helvetica")

    ) +

    theme(plot.margin=unit(c(1,1,1,1), "mm"))

  if(!axis.plot){

    p=p+theme(axis.title = element_blank(), # remove if needed

    axis.ticks = element_blank(), # remove if needed

    axis.line = element_blank(),

    axis.text = element_blank())

  }

  # add lv labels (useful if plotting genes):

  if(add.labels){

    p=p+geom_text_repel(

      data = subset(dat, dat$Significant),

      aes(label = as.character(dat$name[dat$Significant])),

      size = SIZE*1.25,

      color="black",

      box.padding = unit(0.2, "lines"),

      point.padding = unit(0.2, "lines"),

      family="Helvetica"

    )

  }

  theme0 <- function(...) theme( legend.position = "none",

                                 panel.background = element_blank(),

                                 panel.grid.major = element_blank(),

                                 panel.grid.minor = element_blank(),

                                 panel.spacing = unit(0,"null"),

                                 axis.ticks = element_blank(),

                                 axis.text.x = element_blank(),

                                 axis.text.y = element_blank(),

                                 axis.title.x = element_blank(),

                                 axis.title.y = element_blank(),

                                 axis.ticks.length = unit(0,"null"),

                                 panel.border=element_rect(color=NA),...)

  # 74mm * 99mm per final panel

  figure <-multipanelfigure:: multi_panel_figure(width = width, height = height, rows = nrow, columns = 5, panel_label_type = "none", unit = "mm", row_spacing = unit(2, "mm"), column_spacing = unit(0, "mm"))

  figure <- multipanelfigure::fill_panel(figure,  p, row = 1:3, column = 2:5)

  if(add.density){

    library(ggplot2)

    library(gridExtra)

    DF=dat

    p2 <- ggplot(DF,aes(x=x,colour=factor(group))) + colScale +

      geom_density(alpha=0.5) + 

      scale_x_continuous(breaks=NULL,expand=c(0.02,0)) +

      scale_y_continuous(breaks=NULL,expand=c(0.02,0)) +

      theme_bw() +

      theme0(plot.margin = unit(c(1,0,0,2.2),"lines")) 

    p3 <- ggplot(DF,aes(x=y,colour=factor(group))) + colScale +

      geom_density(alpha=0.5) + 

      coord_flip()  + 

      scale_x_continuous(labels = NULL,breaks=NULL,expand=c(0.02,0)) +

      scale_y_continuous(labels = NULL,breaks=NULL,expand=c(0.02,0)) +

      theme_bw() +

      theme0(plot.margin = unit(c(0,1,1.2,0),"lines"))

    p=grid.arrange(arrangeGrob(p2,ncol=2,widths=c(3,1)),

                   arrangeGrob(p,p3,ncol=2,widths=c(3,1)),

                   heights=c(1,3))

  }

  if(add.proportions){

    prop.dat=data.frame(main,as.data.frame(table(group)/length(group), stringsAsFactors=F), stringsAsFactors = F)

    ord=order(prop.dat$Freq, decreasing = F)

    prop.dat=prop.dat[ord,]

    prop.dat$group=factor(prop.dat$group, levels=prop.dat$group)

    myColors=colorv

    names(myColors) <- levels(dat$group)

    colScale2 <- scale_fill_manual(values = myColors)

    p2=ggplot(data=prop.dat,

              aes(x=main, y=Freq, fill=group)) + colScale2 +

      geom_bar(position="fill", stat = "identity", inherit.aes = T) +

      ggtitle(paste(" ", " ", sep="\n")) +

      theme(legend.position = "none", legend.direction = "horizontal",

            axis.line.y = element_line(size=1, colour = "black"),

            axis.line.x = element_blank(),

            panel.grid.major = element_blank(),

            panel.grid.minor = element_blank(),

            axis.text.x = element_blank(),

            axis.title.x = element_blank(),

            axis.title.y = element_blank(),

            axis.ticks.x = element_blank(),

            axis.text.y = element_text(colour="grey20",size=text.size,face="plain", family="Helvetica"),  

            axis.ticks.length = unit(2,"mm"),

            panel.border = element_blank(), panel.background = element_blank(),

            plot.title = element_text(size = text.size, face = "bold", family="Helvetica"),

            text=element_text())+

      theme(plot.margin=unit(c(0,0,0,0), "mm"))

    # 74mm * 99mm per panel

    figure <- multipanelfigure::fill_panel(figure,  p2, row = 1:3, column = 1)

  }  

  if(add.legend)figure <- multipanelfigure::fill_panel(figure,  legend, row = 4, column = 2:4)

  return(figure)

}

get.only.legend=function(colorv, group, position="right", direction="vertical", text.size=10){

  dat=data.frame(group, colorv)

  levels(dat$group)=group

  myColors <- colorv

  names(myColors) <- levels(group)

  colScale <- scale_colour_manual(name = "group",values = myColors)

  dat$x=dim(dat)[1]

  dat$y=dim(dat)[1]

  legend <- cowplot::get_legend(ggplot(dat, aes(x, y, colour = group)) + theme_bw() +

                                  geom_point(size=0.6) + colScale +theme(legend.position = position, legend.direction = direction, legend.title = element_blank(), 

                                                                         legend.key=element_blank(), legend.box.background=element_blank(),

                                                                         legend.text=element_text(size = text.size, face = "bold", family="Helvetica"))+

                                  theme(plot.margin=unit(c(1,1,1,1), "mm"))+

                                  guides(colour = guide_legend(override.aes = list(size=text.size/3))))

  return(legend)

}

plot.DotPlot=function (object, assay = NULL, features, cols = c("lightgrey", "blue"), col.min = -2.5, col.max = 2.5, dot.min = 0, dot.scale = 6, group.by = NULL, split.by = NULL, scale.by = "radius", scale.min = NA, scale.max = NA){

  library(cowplot)

  # if seurat input:

  library(Seurat)

  assay <- DefaultAssay(object = object)

  DefaultAssay(object = object) <- assay

  scale.func <- switch(EXPR = scale.by, size = scale_size, 

                       radius = scale_radius, stop("'scale.by' must be either 'size' or 'radius'"))

  data.features <- FetchData(object = object, vars = features)

  data.features$id <- if (is.null(x = group.by)) {

    Idents(object = object)

  }else {

    object[[group.by, drop = TRUE]]

  }

  if (!is.factor(x = data.features$id)) {

    data.features$id <- factor(x = data.features$id)

  }

  id.levels <- levels(x = data.features$id)

  data.features$id <- as.vector(x = data.features$id)

  if (!is.null(x = split.by)) {

    splits <- object[[split.by, drop = TRUE]]

    if (length(x = unique(x = splits)) > length(x = cols)) {

      stop("Not enought colors for the number of groups")

    }

    cols <- cols[1:length(x = unique(x = splits))]

    names(x = cols) <- unique(x = splits)

    data.features$id <- paste(data.features$id, splits, sep = "_")

    unique.splits <- unique(x = splits)

    id.levels <- paste0(rep(x = id.levels, each = length(x = unique.splits)), 

                        "_", rep(x = unique(x = splits), times = length(x = id.levels)))

  }

  data.plot <- lapply(X = unique(x = data.features$id), FUN = function(ident) {

    data.use <- data.features[data.features$id == ident, 

                              1:(ncol(x = data.features) - 1), drop = FALSE]

    avg.exp <- apply(X = data.use, MARGIN = 2, FUN = function(x) {

      return(mean(x = expm1(x = x)))

    })

    pct.exp <- apply(X = data.use, MARGIN = 2, FUN = PercentAbove, 

                     threshold = 0)

    return(list(avg.exp = avg.exp, pct.exp = pct.exp))

  })

  names(x = data.plot) <- unique(x = data.features$id)

  data.plot <- lapply(X = names(x = data.plot), FUN = function(x) {

    data.use <- as.data.frame(x = data.plot[[x]])

    data.use$features.plot <- rownames(x = data.use)

    data.use$id <- x

    return(data.use)

  })

  data.plot <- do.call(what = "rbind", args = data.plot)

  if (!is.null(x = id.levels)) {

    data.plot$id <- factor(x = data.plot$id, levels = id.levels)

  }

  # could continue here with other kinds of data too

  avg.exp.scaled <- sapply(X = unique(x = data.plot$features.plot), 

                           FUN = function(x) {

                             data.use <- data.plot[data.plot$features.plot == 

                                                     x, "avg.exp"]

                             data.use <- scale(x = data.use)

                             data.use <- MinMax(data = data.use, min = col.min, 

                                                max = col.max)

                             return(data.use)

                           })

  avg.exp.scaled <- as.vector(x = t(x = avg.exp.scaled))

  if (!is.null(x = split.by)) {

    avg.exp.scaled <- as.numeric(x = cut(x = avg.exp.scaled, 

                                         breaks = 20))

  }

  data.plot$avg.exp.scaled <- avg.exp.scaled

  data.plot$features.plot <- factor(x = data.plot$features.plot, 

                                    levels = rev(x = features))

  data.plot$pct.exp[data.plot$pct.exp < dot.min] <- NA

  data.plot$pct.exp <- data.plot$pct.exp * 100

  if (!is.null(x = split.by)) {

    splits.use <- vapply(X = strsplit(x = as.character(x = data.plot$id), 

                                      split = "_"), FUN = "[[", FUN.VALUE = character(length = 1L), 

                         2)

    data.plot$colors <- mapply(FUN = function(color, value) {

      return(colorRampPalette(colors = c("grey", color))(20)[value])

    }, color = cols[splits.use], value = avg.exp.scaled)

  }

  color.by <- ifelse(test = is.null(x = split.by), yes = "avg.exp.scaled", 

                     no = "colors")

  if (!is.na(x = scale.min)) {

    data.plot[data.plot$pct.exp < scale.min, "pct.exp"] <- scale.min

  }

  if (!is.na(x = scale.max)) {

    data.plot[data.plot$pct.exp > scale.max, "pct.exp"] <- scale.max

  }

  plot <- ggplot(data = data.plot, mapping = aes_string(x = "id", y = "features.plot")) + 

    geom_point(mapping = aes_string(size = "pct.exp", color = color.by)) + 

    scale.func(range = c(0, dot.scale), limits = c(scale.min, scale.max)) + 

    theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + 

    guides(size = guide_legend(title = "Percent Expressed")) + 

    labs(x = "", y = ifelse(test = is.null(x = split.by), yes = "", no = "Split Identity")) + 

    theme_cowplot() +

    theme(axis.text.x=element_text(angle=45, hjust=1)) + 

    theme(axis.text.y = element_text(colour="grey20",size=10,face="plain", family="Helvetica"), axis.text.x = element_text(colour="grey20",size=10,face="plain", family="Helvetica")) +

    theme(legend.key=element_blank(), legend.box.background=element_blank(),

           legend.text=element_text(size = 10, family="Helvetica"))+

    theme(plot.margin=unit(c(1,1,1,1), "mm"))

  if (!is.null(x = split.by)) {

    plot <- plot + scale_color_identity()

  }

  else if (length(x = cols) == 1) {

    plot <- plot + scale_color_distiller(palette = cols)

  }

  else {

    plot <- plot + scale_color_gradient(low = cols[1], high = cols[2])

  }

  if (is.null(x = split.by)) {

    plot <- plot + guides(color = guide_colorbar(title = "Average Expression"))

  }

  return(plot)

}

PercentAbove <- function(x, threshold) {

  return(length(x = x[x > threshold]) / length(x = x))

}

RandomName <- function(length = 5L, ...) {

  CheckDots(..., fxns = 'sample')

  return(paste(sample(x = letters, size = length, ...), collapse = ''))

}

MinMax=function (data, min, max) {

  data2 <- data

  data2[data2 > max] <- max

  data2[data2 < min] <- min

  return(data2)

}

scale.func <- function (name = waiver(), breaks = waiver(), labels = waiver(), 

                        limits = NULL, range = c(1, 6), trans = "identity", guide = "legend") 

{

  continuous_scale("size", "radius", scales::rescale_pal(range), name = name, 

                   breaks = breaks, labels = labels, limits = limits, trans = trans, 

                   guide = guide)

}

#' Contains columns: variable.1, variable.2, features (y name), id (x name)

#' @examples

#' #'\dontrun{

#'df=data.frame("variable.1"=c(-2, 4), "variable.2"=c(10,40), "features"=c("feature1", "feature2"), "id"=c("group1", "group2"))

#'plot.DotPlot.df(df)

#'# example, modified:

#'plot.DotPlot.df(df, name.variable.1 = "Fold-Change", name.variable.2 = "FDR (-log10)", cols = c("blue","white", "red"), col.min = -2, col.max = 2, scale.min = 0, scale.max = 20, dot.scale = 4)

#'}

plot.DotPlot.df=function(data.plot, scale.min=NULL, scale.max=NULL, col.min=NULL,col.max=NULL, dot.scale = 6, fontsize=8, cols = c("lightgrey", "red"), name.variable.1="variable.1", name.variable.2="variable.2", number.legend.points=NULL){

  library(cowplot)

  # set scales for data:

  if(is.null(col.min))col.min=min(data.plot$variable.1)

  if(is.null(col.max))col.max=max(data.plot$variable.1)

  if(is.null(scale.min))scale.min=min(data.plot$variable.2)

  if(is.null(scale.max))scale.max=max(data.plot$variable.2)

  if(!is.null(number.legend.points)){

    breaks=seq(scale.min, scale.max, length.out=number.legend.points)

  }else{

    breaks=waiver()

  }

  # set scales:

  data.plot$variable.1 <- MinMax(data = data.plot$variable.1, min = col.min, max = col.max)

  data.plot$variable.2 <- MinMax(data = data.plot$variable.2, min = scale.min, max = scale.max)

  # rearrenge, feature1 on top:

  data.plot$features=factor(data.plot$features, levels=rev(unique(data.plot$features)))

  plot <- ggplot(data = data.plot, mapping = aes_string(x = "id", y = "features")) + 

    geom_point(mapping = aes_string(size = "variable.2", color = "variable.1")) + 

    scale.func(range = c(0, dot.scale), limits = c(scale.min, scale.max), breaks = breaks) + 

    theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + 

    guides(size = guide_legend(title = name.variable.2)) + 

    guides(colour=guide_legend(title = name.variable.1)) + 

    labs(x = "", y = "") + 

    theme_cowplot() +

    theme(axis.text.x=element_text(angle=45, hjust=1)) + 

    theme(axis.text.y = element_text(colour="grey20",size=fontsize,face="plain", family="Helvetica"), axis.text.x = element_text(colour="grey20",size=fontsize,face="plain", family="Helvetica")) +

    theme(legend.key=element_blank(), legend.box.background=element_blank(),

          legend.text=element_text(size=fontsize, family="Helvetica"))+

    theme(plot.margin=unit(c(1,1,1,1), "mm"))

  # 2 color gradient

  if(length(cols)==2)plot <- plot + scale_colour_gradient(low = cols[1], high = cols[2])

  # 3 color gradient

  # if(length(cols)==3)plot <- plot + scale_colour_gradient2(low = cols[1],mid = cols[2], high = cols[3], midpoint = 0)

  # forces to range (no midpoint, but middle color will be midpoint):

  if(length(cols)>2)plot <- plot + scale_colour_gradientn(colours = cols, limits = c(col.min, col.max))

  return(plot)

}