---
title: "pirateplot"
author: "Nathaniel Phillips"
date: "`r Sys.Date()`"
output: rmarkdown::html_vignette
bibliography: yarrr.bib
vignette: >
  %\VignetteIndexEntry{pirateplot: The plotting choice of R pirates}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

# What is a pirateplot()?

A pirateplot, is the RDI (**Raw** data, **Descriptive** statistics, and **Inferential** statistics) plotting choice of R pirates who are displaying the relationship between 1 to 3 categorical independent variables, and one continuous dependent variable.

```{r, echo = F, message = F, result = 'hide'}
library(yarrr)
```

A pirateplot has 4 main elements

1. points, symbols representing the raw data (jittered horizontally)
2. bar, a vertical bar showing central tendencies
3. bean, a smoothed density (inspired by @kampstra2008beanplot) representing a smoothed density
4. inf, a rectangle representing an inference interval (e.g.; Bayesian Highest Density Interval or frequentist confidence interval)

```{r, fig.width = 6, fig.height = 5, echo = F, fig.align='center'}
pirateplot(
  formula = weight ~ Diet,
  data = ChickWeight,
  theme = 1,
  back.col = "white",
  gl.col = "white",
  bean.f.o = c(0, .1, .7, .1),
  #   bean.b.o = c(0, .1, 1, .1),
  point.o = c(.4, .1, .1, .1),
  avg.line.o = c(.3, 1, .3, .3),
  inf.f.o = c(.1, .1, .1, .9),
  bar.f.o = c(.1, .8, .1, .1),
  inf.f.col = c("white", "white", "white", piratepal("xmen")[4]),
  main = "4 Elements of a pirateplot",
  pal = "xmen"
)


text(.7, 350, labels = "Points")
text(.7, 345, labels = "Raw Data", pos = 1, cex = .8)
arrows(.7, 310, .97, 270, length = .1)

text(1.4, 200, labels = "Bar/Line")
text(1.4, 200, labels = "Center", pos = 1, cex = .8)
arrows(1.4, 170, 1.54, 125, length = .1)

text(2.4, 250, labels = "Bean")
text(2.4, 250, labels = "Density", pos = 1, cex = .8)
arrows(2.4, 220, 2.85, 200, length = .1)

text(3.55, 300, labels = "Band")
text(3.55, 290, labels = "Inference\n95% HDI or CI", pos = 1, cex = .8)

arrows(3.55, 240, 3.8, 150, length = .1)
```

# Main arguments

Here are the main arguments to `pirateplot()`

```{r, echo = FALSE}
pp.elements <- data.frame(
  "Argument" = c("formula", "data", "main", "pal", "theme", "inf"),
  "Description" = c(
    "A formula", "A dataframe",
    "Plot title", "A color palette", "A plotting theme", "Type of inference"
  ),
  "Examples" = c(
    "height ~ sex + eyepatch, weight ~ Time",
    "pirates, ChickWeight",
    "'Pirate heights', 'Chicken Weights",
    "'xmen', 'black'",
    "0, 1, 2",
    "'ci', 'hdi', 'iqr'"
  )
)
knitr::kable(pp.elements, caption = "Main Pirateplot Arguments")
```


# Themes

`pirateplot()` currently supports three themes which change the default look of the plot. To specify a theme, use the `theme` argument:

## Theme 1

`theme = 1` is the default

```{r fig.align='center', fig.width = 6, fig.height = 4}
# Theme 1 (the default)
pirateplot(
  formula = weight ~ Time,
  data = ChickWeight,
  theme = 1,
  main = "theme = 1"
)
```

## Theme 2

Here is `theme = 2`

```{r fig.align='center', fig.width = 6, fig.height = 4}
# Theme 2
pirateplot(
  formula = weight ~ Time,
  data = ChickWeight,
  theme = 2,
  main = "theme = 2"
)
```


## Theme 3

And now...`theme = 3`!

```{r fig.align='center', fig.width = 6, fig.height = 4}
# Theme 3
pirateplot(
  formula = weight ~ Time,
  data = ChickWeight,
  theme = 3,
  main = "theme = 3"
)
```


## Theme 4

`theme = 4` tries to maintain a classic barplot look (but with added raw data).

```{r fig.align='center', fig.width = 6, fig.height = 4}
# Theme 4
pirateplot(
  formula = weight ~ Time,
  data = ChickWeight,
  theme = 4,
  main = "theme = 4"
)
```



## Theme 0

`theme = 0` allows you to start a pirateplot from scratch -- that is, it turns of *all* elements. You can then selectively turn elements on with individual arguments (e.g.; `bean.f.o`, `point.o`)

```{r fig.align='center', fig.width = 6, fig.height = 4}
# Default theme
pirateplot(
  formula = weight ~ Time,
  data = ChickWeight,
  theme = 0,
  main = "theme = 0\nStart from scratch"
)
```

# Color palettes

You can specify a general color palette using the `pal` argument. You can do this in two ways.

The first way is to specify the name of a color palette in the `piratepal()` function. Here they are:

```{r fig.width = 6, fig.height = 4, fig.align = "center"}
piratepal("all")
```

For example, here is a pirateplot using the `"pony"` palette

```{r fig.width = 6, fig.height = 4, fig.align = "center"}
pirateplot(
  formula = weight ~ Time,
  data = ChickWeight,
  pal = "pony",
  theme = 1,
  main = "pony color palette"
)
```

The second method is to simply enter a vector of one or more colors. Here, I'll create a black and white pirateplot from theme 2 by specifying `pal = 'black'`

```{r fig.width = 6, fig.height = 4, fig.align = "center"}
pirateplot(
  formula = weight ~ Time,
  data = ChickWeight,
  theme = 2,
  pal = "black",
  main = "pal = 'black"
)
```


# Customising elements

Regardless of the theme you use, you can always customize the color and opacity of graphical elements. To do this, specify one of the following arguments. Note: Arguments with `.f.` correspond to the *filling* of an element, while `.b.` correspond to the *border* of an element:

```{r, echo = FALSE}
pp.elements <- data.frame(
  "element" = c("points", "beans", "bar", "inf", "avg.line"),
  "color" = c(
    "point.col, point.bg",
    "bean.f.col, bean.b.col",
    "bar.f.col, bar.b.col",
    "inf.f.col, inf.b.col",
    "avg.line.col"
  ),
  "opacity" = c(
    "point.o",
    "bean.f.o, bean.b.o",
    "bar.f.o, bar.b.o",
    "inf.f.o, inf.b.o", "avg.line.o"
  )
)

knitr::kable(pp.elements, caption = "Customising plotting elements")
```

For example, I could create the following pirateplots using `theme = 0` and specifying elements explicitly:

```{r fig.width = 6, fig.height = 4, fig.align = "center"}
pirateplot(
  formula = weight ~ Time,
  data = ChickWeight,
  theme = 0,
  main = "Fully customized pirateplot",
  pal = "southpark", # southpark color palette
  bean.f.o = .6, # Bean fill
  point.o = .3, # Points
  inf.f.o = .7, # Inference fill
  inf.b.o = .8, # Inference border
  avg.line.o = 1, # Average line
  bar.f.o = .5, # Bar
  inf.f.col = "white", # Inf fill col
  inf.b.col = "black", # Inf border col
  avg.line.col = "black", # avg line col
  bar.f.col = gray(.8), # bar filling color
  point.pch = 21,
  point.bg = "white",
  point.col = "black",
  point.cex = .7
)
```

If you don't want to start from scratch, you can also start with a theme, and then make selective adjustments:

```{r fig.width = 6, fig.height = 4, fig.align = "center"}
pirateplot(
  formula = weight ~ Time,
  data = ChickWeight,
  main = "Adjusting an existing theme",
  theme = 2, # Start with theme 2
  inf.f.o = 0, # Turn off inf fill
  inf.b.o = 0, # Turn off inf border
  point.o = .2, # Turn up points
  bar.f.o = .5, # Turn up bars
  bean.f.o = .4, # Light bean filling
  bean.b.o = .2, # Light bean border
  avg.line.o = 0, # Turn off average line
  point.col = "black" # Black points
)
```

Just to drive the point home, as a barplot is a special case of a pirateplot, you can even reduce a pirateplot into a horrible barplot:

```{r fig.width = 6, fig.height = 4, fig.align = "center"}
pirateplot(
  formula = weight ~ Time,
  data = ChickWeight,
  main = "Reducing a pirateplot to a barplot",
  theme = 0, # Start from scratch
  bar.f.o = .7
) # Just turn on the bars
```

# Additional arguments

There are several more arguments that you can use to customize your plot:

```{r, echo = FALSE}
pp.elements <- data.frame(
  "element" = c("Background color", "Gridlines", "y-axis Locations", "Quantiles", "Average line", "Inference Calculation", "Inference Display"),
  "arguments" = c(
    "back.col",
    "gl.col, gl.lwd, gl.lty", "yaxt.y",
    "quant, quant.lwd, quant.col", "avg.line.fun", "inf.method", "inf.disp"
  ),
  "examples" = c(
    "back.col = 'gray(.9, .9)'",
    "gl.col = 'gray', gl.lwd = c(.75, 0), gl.lty = 1", "yaxt.y = seq(0, 400, 50)",
    "quant = c(.1, .9), quant.lwd = 1, quant.col = 'black'",
    "avg.line.fun = median", "inf.method = 'hdi', inf.method = 'ci'", "inf.disp = 'line', inf.disp = 'bean', inf.disp = 'rect'"
  )
)

knitr::kable(pp.elements, caption = "Additonal pirateplot elements")
```

Here's an example using a background color, and quantile lines.

```{r fig.width = 8, fig.height = 5, fig.align = "center", out.width = "100%"}
pirateplot(
  formula = weight ~ Time,
  data = ChickWeight,
  main = "Adding quantile lines and background colors",
  theme = 2,
  back.col = gray(.98), # Add light gray background
  gl.col = "gray", # Gray gridlines
  gl.lwd = c(.75, 0), # Gridline widths (alternating)
  inf.f.o = .6, # Turn up inf filling
  inf.disp = "bean", # Wrap inference around bean
  bean.b.o = .4, # Turn down bean borders
  quant = c(.1, .9), # 10th and 90th quantiles
  quant.col = "black", # Black quantile lines
  yaxt.y = seq(0, 400, 50) # Locations of y-axis tick marks
)
```

# Multiple IVs

You can use up to 3 categorical IVs in your plot. Here are some examples:

```{r fig.width = 10, fig.height = 5, fig.align = "center", out.width = "100%"}
pirateplot(
  formula = height ~ sex + eyepatch,
  data = pirates,
  theme = 2,
  inf.disp = "bean"
)
```

## beside = FALSE

```{r fig.width = 10, fig.height = 5, fig.align = "center", out.width = "100%"}
# Same as before, but with second IV on different plots by including beside = FALSE
pirateplot(
  formula = height ~ sex + eyepatch,
  data = pirates,
  theme = 2,
  beside = FALSE,
  inf.disp = "bean"
)
```


```{r fig.width = 10, fig.height = 10, fig.align = "center", out.width = "100%"}
# Same as before, but with second IV on different plots by including beside = FALSE
pirateplot(
  formula = weight ~ Time + Diet,
  data = ChickWeight,
  theme = 2,
  beside = FALSE
)
```


If you use 3 ivs, values of the second iv will be beside each other.

```{r fig.width = 10, fig.height = 5, fig.align = "center", out.width = "100%"}
pirateplot(
  formula = height ~ sex + eyepatch + headband,
  data = pirates,
  theme = 2,
  inf.disp = "bean"
)
```


# Output

If you include the `plot = FALSE` argument to a pirateplot, the function will return some values associated with the plot.

```{r fig.width = 10, fig.height = 7, fig.align = "center"}
times.pp <- pirateplot(
  formula = time ~ sequel + genre,
  data = subset(
    movies,
    genre %in% c("Action", "Adventure", "Comedy", "Horror") &
      rating %in% c("G", "PG", "PG-13", "R") &
      time > 0
  ),
  plot = FALSE
)
```

Here's the result. The most interesting element is `$summary` which shows summary statistics for each bean:

```{r}
times.pp
```

# Specifying individual point parameters

If you want to customize the look of individual points in the plot, you can specify them with an additional `pointpars` argument. This should be a dataframe with the same number of rows as `data`, and column names in the set col, bg, pch, labels, jitter.

For example, here is a plot with additional point labels and custom jitter values:

```{r, eval = FALSE}
# Create a smaller version of the ChickWeight data
ChickWeight2 <- ChickWeight[sample(nrow(ChickWeight), size = 100), ]

# Define labels, jitter values, and colors for all individual points
pointpars <- data.frame(
  "labels" = 1:100,
  "jitter" = rep(c(-.1, .1),
    length.out = 100
  ),
  "col" = sample(colors(),
    size = 100,
    replace = TRUE
  )
)

# Createpireatplot with custom point parameters
pirateplot(
  formula = weight ~ Diet,
  data = ChickWeight2,
  pointpars = pointpars,
  point.o = 1
)
```


# References

The pirateplot is really a knock-off of the great beanplot package and visualization from @kampstra2008beanplot. 

