<!--
%\VignetteEngine{knitr::knitr}
%\VignetteIndexEntry{examples}
-->

```{r setup, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

# Polygon methods

```{r}

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")
}

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

```{r}

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")
}
```

# serialize issue

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

```{r}

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))
}
```

# 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.

```{r}

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))
}
```

# LOPART ROC curve

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

```{r}
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
https://www.tutorialspoint.com/dip/grayscale_to_rgb_conversion.htm

```{r}
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()
}
```

## 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.

```{r}
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

```{r}
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
}
```

