---
title: "Attribute Plots"
author: "Jake Conway and Nils Gehlenborg"
vignette: >
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteIndexEntry{Attribute Plots}
  \usepackage[utf8]{inputenc}
---

<br>

For all examples the movies data set contained in the package will be used.
```{r, tidy=TRUE}
library(UpSetR); library(ggplot2); library(grid); library(plyr)
movies <- read.csv( system.file("extdata", "movies.csv", package = "UpSetR"), header=T, sep=";" )
```

<br>

*attribute.plots* Parameter Breakdown
----------------------------------
The `attribute.plots` parameter is broken down into 3 fields: `gridrows`, `plots`, and `ncols`

- `gridrows`: specifies how much to expand the plot window to add room for attribute plots. The _UpSetR_ plot is plotted on a 100 by 100 grid. So for example, if we set `gridrows` to 50, the new grid layout would be 150 by 100, setting aside 1/3 of the plot for the attribute plots.

- `plots`: takes a list of paramters. These paramters include `plot`, `x`, `y` (if applicable), and `queries`.

- `plot`: is a function that returns a ggplot

- `x`: is the x aesthetic to be used in the ggplot (entered as string)

- `y`: is the y aesthetic to be used in the ggplot (entered as string)

- `queries`: indicates whether or not to overlay the plot with the queries present. If `queries` is `TRUE`, the attribute plot will be overlayed with data from the queries. If `queries` is `FALSE`, no query results will be plotted on the attribute plot.

- `ncols`: specifies how the plots should be arranged in the `gridrows` space. If two attribute plots are entered and `ncols` is 1,then the plots will display one above the other. Alternatively, if two attribute plots are entered and `ncols` is 2, the attribute plots will be displayed side by side.

**Additional:** to add a legend of the queries, use `query.legend = "bottom"` (see Example 2).

<br>

Example 1: Built-In Attribute Histogram
-------------
Example of how to add built-in histogram attribute plot. If `main.bar.color` is not specified as black, elements contained in black intersection size bars will be represented as gray in attribute plots.
```{r, fig.width=12, fig.height=7, out.width="850px",tidy=TRUE, fig.align='center'}
upset(movies, main.bar.color = "black", queries = list(list(query = intersects, params = list("Drama"), active = T)), attribute.plots = list(gridrows = 50, plots = list(list(plot = histogram, x = "ReleaseDate", queries = F), list(plot = histogram, x = "AvgRating", queries = T)), ncols = 2))
```

<br>

Example 2: Built-In Attribute Scatter Plot
-------------
Example of how to add built-in attribute scatter plot. If `main.bar.color` not specified as black, elements contained in black intersection size bars will be represented as gray in attribute plots.
<br> <br>
*notice the use of query.legend*
```{r, fig.width=12, fig.height=7,out.width="850px",tidy=TRUE, fig.align='center'}
upset(movies, main.bar.color = "black", queries = list(list(query = intersects, params = list("Drama"), color = "red", active = F), list(query = intersects, params = list("Action", "Drama"), active = T), list(query = intersects, params = list("Drama", "Comedy", "Action"), color = "orange", active = T)), attribute.plots = list(gridrows = 45, plots = list(list(plot = scatter_plot, x = "ReleaseDate", y = "AvgRating", queries = T), list(plot = scatter_plot, x = "AvgRating", y = "Watches", queries = F)), ncols = 2), query.legend = "bottom")
```

<br>

Example 3: Creating a Custom Attribute Plot
-------------
Contents of `aes_string()` along with the `scale_color_identity()` function are **required** to pass in aesthetics and to make sure the correct colors are applied. A `plot.margin` of `c(0.5,0,0,1)` is **recommended**.
```{r, tidy=TRUE}
myplot <- function(mydata,x,y){
    plot <- (ggplot(data = mydata, aes_string(x=x, y=y, colour = "color")) + geom_point() +    scale_color_identity() + theme(plot.margin = unit(c(0,0,0,0), "cm")))
}

another.plot <- function(data, x, y){
  data$decades <- round_any(as.integer(unlist(data[y])), 10, ceiling)
  data <- data[which(data$decades >= 1970), ]
  myplot <- (ggplot(data, aes_string(x=x)) + 
               geom_density(aes(fill=factor(decades)), alpha = 0.4)
             +theme(plot.margin = unit(c(0,0,0,0), "cm"), legend.key.size = unit(0.4,"cm")))
}
```

Example of applying the `myplot` custom attribute plot defined above to the data.
```{r, fig.width=12, fig.height=7, out.width="850px",tidy=TRUE, fig.align='center'}
upset(movies, main.bar.color = "black", queries = list(list(query = intersects, params = list("Drama"), color = "red", active = F), list(query = intersects, params = list("Action", "Drama"), active = T), list(query = intersects, params = list("Drama", "Comedy", "Action"), color = "orange", active = T)), attribute.plots = list(gridrows = 45, plots = list(list(plot = myplot, x = "ReleaseDate", y = "AvgRating", queries = T), list(plot = another.plot, x = "AvgRating", y = "ReleaseDate", queries = F)), ncols = 2))
```

<br>

Example 4: Applying Everything at Once
-------------
Combining the built-in scatter plot and histogram plot with the `myplot` custom plot defined in the example above.
```{r, fig.width=12, fig.height=7,out.width="850px",tidy=TRUE, fig.align='center'}
upset(movies, main.bar.color = "black", mb.ratio = c(0.5,0.5), queries = list(list(query = intersects, params = list("Drama"), color = "red", active = F), list(query = intersects, params = list("Action", "Drama"), active = T), list(query = intersects, params = list("Drama", "Comedy", "Action"), color = "orange", active = T)), attribute.plots = list(gridrows=50, plots = list(list(plot = histogram, x = "ReleaseDate", queries = F), list(plot = scatter_plot, x = "ReleaseDate", y = "AvgRating", queries = T),list(plot = myplot, x = "AvgRating", y = "Watches", queries = F)), ncols = 3))
```