# Polygon methods

    param.df <- data.frame(
      mean=c(0, 0, 2),
      sd=c(1, 2, 1))
    density.df.list <- list()
    for(param.i in 1:nrow(param.df)){
      one.param <- param.df[param.i,]
      observation <- seq(-4, 4, by=0.1)
      density.df.list[[param.i]] <- data.frame(
        param.i,
        param.fac=factor(param.i),
        one.param,
        observation,
        density=dnorm(observation, one.param$mean, one.param$sd),
        row.names=NULL)
    }
    density.df <- do.call(rbind, density.df.list)

    if(require(ggplot2)){
      gg <- ggplot()+
        geom_line(aes(
          observation, density, color=param.fac),
          data=density.df)
      directlabels::direct.label(gg, "top.polygons")
    }
    #> Loading required package: ggplot2

    if(require(ggplot2)){
      density.df$mean.lab <- paste0("mean=", density.df$mean)
      gg <- ggplot()+
        geom_line(aes(
          observation, density, color=param.fac),
          data=density.df)+
        directlabels::geom_dl(aes(
          observation, density,
          color=param.fac,
          label.group=param.fac,
          label=mean.lab),
          method="top.polygons",
          data=density.df)
      gg
    }

    if(require(ggplot2)){
      gg <- ggplot()+
        geom_line(aes(
          observation, density, color=mean.lab, group=param.fac),
          data=density.df)
      directlabels::direct.label(gg, "top.polygons")
    }

    if(require(ggplot2)){
      data(BodyWeight, package="nlme")
      gg <- ggplot()+
        geom_line(aes(
          Time, weight, color=Rat),
          data=BodyWeight)+
        facet_grid(. ~ Diet)
      gg
    }

    if(require(ggplot2)){
      directlabels::direct.label(gg, "right.polygons")
    }

    if(require(ggplot2)){
      gg.wider <- gg+xlim(-10, 70)
      directlabels::direct.label(gg.wider, "right.polygons")
    }

    if(require(ggplot2)){
      directlabels::direct.label(gg.wider, "left.polygons")
    }

# SO post about stats

https://github.com/tdhock/directlabels/issues/24

    if(require(ggplot2)){
      set.seed(124234345)
      # Generate data
      df.2 <- data.frame(
        "n_gram" = c("word1"),
        "year" = rep(100:199),
        "match_count" = runif(100 ,min = 1000 , max = 2000))
      df.2 <- rbind(df.2, data.frame(
        "n_gram" = c("word2"),
        "year" = rep(100:199),
        "match_count" = runif(100 ,min = 1000 , max = 2000)) )
      # use stat smooth with geom_dl to get matching direct labels.
      span <- 0.3
      ggplot(df.2, aes(year, match_count, group=n_gram, color=n_gram)) +
        geom_line(alpha = I(7/10), color="grey") +
        stat_smooth(linewidth=2, span=span, se=F) +
        directlabels::geom_dl(aes(
          label=n_gram),
          method = "last.qp",
          stat="smooth",
          span=span) +
        xlim(c(100,220))+
        guides(colour="none")
    }
    #> `geom_smooth()` using method = 'loess' and formula = 'y ~ x'
    #> `geom_smooth()` using method = 'loess' and formula = 'y ~ x'

# serialize issue

https://github.com/tdhock/directlabels/issues/6

    if(require(ggplot2) && require(dplyr) && require(ggthemes)){
      ## create data
      aaa <- structure(
        list(x = c(28, 27, 26, 25, 24, 23, 22, 21, 20, 19,
                   18, 17, 28, 27, 26, 25, 24, 23, 22, 21, 20, 19, 18, 17),
             count = c(2344L,
                       4088L, 3247L, 2808L, 2046L, 1669L, 1315L, 951L, 610L, 543L, 469L,
                       370L, 937L, 1116L, 550L, 379L, 282L, 204L, 174L, 160L, 136L,
                       132L, 128L, 122L),
             term = c("aaa", "aaa", "aaa", "aaa", "aaa",
                      "aaa", "aaa", "aaa", "aaa", "aaa", "aaa", "aaa", "bbb", "bbb",
                      "bbb", "bbb", "bbb", "bbb", "bbb", "bbb", "bbb", "bbb", "bbb",
                      "bbb")),
        class = c("tbl_df", "tbl", "data.frame"),
        row.names = c(NA,
                      -24L),
        .Names = c("x", "count", "term"))
      ## have a look
      print(aaa)
      ## initial plot
      p2 <- aaa %>% ggplot(aes(x = x, y = count, group = term, colour = term)) + geom_line()
      ## have a look
      print(p2)
      ## works
      print(directlabels::direct.label(p2))
      ## plot with theme
      p2 <- aaa %>% ggplot(aes(x = x, y = count, group = term, colour = term)) + geom_line() + theme_fivethirtyeight()
      ## have a look
      print(p2)
      ## used to fail but should be OK as of 19 June 2020.
      print(directlabels::direct.label(p2))
    }
    #> Loading required package: dplyr
    #>
    #> Attaching package: 'dplyr'
    #> The following objects are masked from 'package:stats':
    #>
    #>     filter, lag
    #> The following objects are masked from 'package:base':
    #>
    #>     intersect, setdiff, setequal, union
    #> Loading required package: ggthemes
    #> # A tibble: 24 × 3
    #>        x count term
    #>    <dbl> <int> <chr>
    #>  1    28  2344 aaa
    #>  2    27  4088 aaa
    #>  3    26  3247 aaa
    #>  4    25  2808 aaa
    #>  5    24  2046 aaa
    #>  6    23  1669 aaa
    #>  7    22  1315 aaa
    #>  8    21   951 aaa
    #>  9    20   610 aaa
    #> 10    19   543 aaa
    #> # ℹ 14 more rows

# changepoint cost minima

This is a test for `polygon.method` with only one unaligned point per group as input, in particular the new `bottom.polygons` method.

    data(LOPART100, package="directlabels")
    abbrev.vec <- c(
      data="data and models",
      cost="cost of last change")
    yfac <- function(l){
      factor(abbrev.vec[[l]], abbrev.vec)
    }
    COST <- function(dt){
      data.frame(y.var=yfac("cost"), dt)
    }
    DATA <- function(dt){
      data.frame(y.var=yfac("data"), dt)
    }
    sig.color <- "grey50"
    tau <- 99
    up.to.t <- 100
    change.dt <- data.frame(tau, change=tau+0.5)
    t.dt <- data.frame(up.to.t)
    my.hjust <- function(x)ifelse(x < nrow(LOPART100$signal)/2, 0, 1)
    min.dt <- do.call(rbind, by(
      LOPART100$cost,
      LOPART100$cost$Algorithm,
      function(df)df[which.min(df$cost_candidates),]))
    cost.range <- range(LOPART100$cost$cost_candidates)
    cost.h <- cost.range[2]-cost.range[1]
    blank.dt <- data.frame(
      position=1, cost=cost.range[1]-cost.h/4)
    label.colors <- c(
      "1"="#ff7d7d",
      "0"="#f6c48f")
    if(require(ggplot2)){
      gg <- ggplot()+
        geom_blank(aes(
          position, cost),
          data=COST(blank.dt))+
        geom_vline(aes(
          xintercept=up.to.t),
          color=sig.color,
          data=t.dt)+
        geom_text(aes(
          up.to.t, 13,
          hjust=my.hjust(up.to.t),
          label=sprintf(
            "$t=%s$", up.to.t)),
          color=sig.color,
          data=DATA(t.dt))+
        geom_rect(aes(
          xmin=start, xmax=end,
          fill=paste(changes),
          ymin=-Inf, ymax=Inf),
          alpha=0.5,
          data=LOPART100$labels)+
        scale_fill_manual("label", values=label.colors)+
        theme_bw()+
        theme(panel.spacing=grid::unit(0, "lines"))+
        facet_grid(y.var ~ ., scales="free")+
        geom_text(aes(
          change, 1,
          hjust=my.hjust(change),
          label=sprintf(
            "$\\tau = %d$", tau)),
          vjust=0,
          data=DATA(change.dt))+
        geom_vline(aes(
          xintercept=change),
          data=change.dt)+
        geom_segment(aes(
          start-0.5, mean,
          size=Algorithm,
          color=Algorithm,
          xend=end+0.5, yend=mean),
          data=DATA(LOPART100$segments))+
        geom_point(aes(
          position, signal),
          color=sig.color,
          shape=1,
          data=DATA(LOPART100$signal))+
        scale_size_manual(values=c(
          OPART=1.5,
          LOPART=0.5),
          drop=FALSE)+
        scale_shape_manual(values=c(
          OPART=1,
          LOPART=2),
          drop=FALSE)+
        scale_color_manual(values=c(
          OPART="deepskyblue",
          LOPART="black"),
          drop=FALSE)+
        ylab("")+
        scale_x_continuous(
          "position $t,\\tau$",
          breaks=seq(0, 100, by=10))+
        geom_point(aes(
          change, cost_candidates,
          color=Algorithm, shape=Algorithm),
          data=COST(LOPART100$cost))+
        geom_point(aes(
          change, cost_candidates,
          color=Algorithm),
          data=COST(min.dt))
      print(gg)
      label.cost <- function(df){
        gg+
          directlabels::geom_dl(aes(
            change, cost_candidates,
            color=Algorithm,
            label.group=Algorithm,
            label=sprintf("$\\tau^*_{%d} = %d$", up.to.t, tau)),
            method="bottom.polygons",
            data=COST(df))
      }
      print(label.cost(LOPART100$cost))
      ## to make sure it works when there is only one point to label.
      print(label.cost(min.dt))
    }
    #> Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
    #> ℹ Please use `linewidth` instead.
    #> This warning is displayed once per session.
    #> Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
    #> generated.

# LOPART ROC curve

This is a test for `polygon.method` with only one unaligned point per group as input, in particular with `right.polygons`.

    data(LOPART.ROC, package="directlabels")
    algo.colors <- c(
      OPART="#0077CC",
      LOPART="black",
      SegAnnot="#22CC22")
    if(require(ggplot2)){
      ggplot()+
        theme_bw()+
        scale_color_manual(values=algo.colors)+
        scale_size_manual(values=c(
          LOPART=1.5,
          OPART=1))+
        directlabels::geom_dl(aes(
          FPR, TPR,
          color=model.name,
          label=paste0(model.name, ifelse(is.na(auc), "", sprintf(
            " AUC=%.3f", auc
          )))),
          method=list(
            cex=0.8,
            directlabels::polygon.method(
              "right",
              offset.cm=0.5,
              padding.cm=0.05)),
          data=LOPART.ROC$points)+
        geom_path(aes(
          FPR, TPR,
          color=model.name,
          size=model.name,
          group=paste(model.name, test.fold)),
          data=LOPART.ROC$roc)+
        geom_point(aes(
          FPR, TPR,
          color=model.name),
          size=3,
          shape=21,
          fill="white",
          data=LOPART.ROC$points)+
        theme(
          panel.spacing=grid::unit(0, "lines"),
          legend.position="none"
        )+
        facet_grid(test.fold ~ Penalty + Parameters, labeller=label_both)+
        coord_equal()+
        scale_x_continuous(
          "False Positive Rate (test set labels)",
          breaks=c(0, 0.5, 1),
          labels=c("0", "0.5", "1"))+
        scale_y_continuous(
          "True Positive Rate (test set labels)",
          breaks=c(0, 0.5, 1),
          labels=c("0", "0.5", "1"))
    }

## white or black text on colored background

The weighted method for rgb to grayscale conversion is used for the default `text.color` in `polygon.method`, and explained here.

    if(require(RColorBrewer) && require(ggplot2)){
      m <- RColorBrewer::brewer.pal.info
      brewer.dt.list <- list()
      for(brewer.row in 1:nrow(m)){
        brewer.name <- rownames(m)[[brewer.row]]
        brewer.info <- m[brewer.name, ]
        col.vec <- RColorBrewer::brewer.pal(brewer.info[, "maxcolors"], brewer.name)
        rgb.mat <- col2rgb(col.vec)
        hsv.mat <- rgb2hsv(rgb.mat)
        brewer.dt.list[[brewer.name]] <- data.frame(
          brewer.name,
          brewer.fac=factor(brewer.name, rownames(m)),
          brewer.row,
          category=factor(brewer.info[, "category"], c("seq", "qual", "div")),
          column=seq_along(col.vec),
          color=col.vec,
          t(rgb.mat),
          t(hsv.mat))
      }
      brewer.dt <- do.call(rbind, brewer.dt.list)
      ggplot()+
        theme_bw()+
        theme(panel.spacing=grid::unit(0, "lines"))+
        facet_grid(category ~ ., scales="free", space="free")+
        geom_tile(aes(
          factor(column), brewer.fac, fill=color),
          data=brewer.dt)+
        geom_text(aes(
          factor(column), brewer.fac, label=brewer.fac, color=ifelse(
          ((0.3 * red) + (0.59 * green) + (0.11 * blue))/255 < 0.5, "white", "black")),
          data=brewer.dt)+
        scale_fill_identity()+
        scale_color_identity()
    }
    #> Loading required package: RColorBrewer

## odd qp labels for timings figure

In the image below the strange thing in the labels is that the end of the pointer of `nc::capture_melt_single` is inside of the pointer for `cdata::unpivot_to_blocks` – this is ok, but we could probably avoid this by switching the order. we should be able to detect/avoid this using a linear inequality constraint: bottom of label box must be greater than next target down, etc. But if targets are too close together this could lead to no feasible solution.

    data(odd_timings, package="directlabels")
    odd4 <- subset(odd_timings, captures==4)
    if(require(ggplot2)){
      gg <- ggplot()+
        geom_line(aes(
          N.col, median.seconds, color=fun),
          data=odd4)+
        scale_x_log10(limits=c(10, 1e6))+
        scale_y_log10()
      directlabels::direct.label(gg, "right.polygons")
    }

TODO edit `polygon.method` so that the right panel labels do not cross – can this be added as a constraint in the qp, or do we just need to re-order?

## two dlgrobs

This example has two `geom_dl` with the same method, but the grobs need different names to render correctly https://github.com/tdhock/directlabels/issues/30

    data(odd_timings, package="directlabels")
    zero <- subset(odd_timings, captures==0)
    on.right <- with(zero, N.col==max(N.col))
    funs.right <- unique(zero[on.right, "fun"])
    is.right <- zero$fun %in% funs.right
    timings.right <- zero[is.right,]
    timings.left <- zero[!is.right,]
    if(require(ggplot2)){
      gg <- ggplot()+
        geom_line(aes(
          N.col, median.seconds, color=fun),
          data=zero)+
        directlabels::geom_dl(aes(
          N.col, median.seconds, color=fun, label=fun),
          method="right.polygons",
          data=timings.left)+
        directlabels::geom_dl(aes(
          N.col, median.seconds, color=fun, label=fun),
          method="right.polygons",
          data=timings.right)+
        scale_x_log10(limits=c(10, 1e6))+
        scale_y_log10()
      gg
    }

## dl.add

    set.seed(1)
    count.df <- data.frame(people=1:20, Role=rep(c("aut","ctb"),each=10), release=runif(10))
    space.cm <- 0.2 # space between polygon point and data point.
    geom_dl_poly <- function(position, direction)directlabels::geom_dl(aes(
      label=people, label.group=release),
      method=list(
        paste0(position,".points"),
        cex=0.7, # text size of direct labels.
        directlabels::dl.add(y=direction*space.cm),
        directlabels::polygon.method(position, offset.cm=0.5)))
    if(require("ggplot2")){
      ggplot(count.df, aes(
        release, people, color=Role))+
        geom_line(linewidth=1)+
        geom_point(shape=21, fill="white")+
        scale_y_continuous(limits=c(-5, 25))+
        geom_dl_poly("bottom", -1)+
        geom_dl_poly("top", 1)
    }