Author: Jake Conway and Nils Gehlenborg

# Attribute Plots

#### Jake Conway and Nils Gehlenborg

For all examples the movies data set contained in the package will be used.

    library(UpSetR)
    library(ggplot2)
    library(grid)
    library(plyr)
    movies <- read.csv(system.file("extdata", "movies.csv", package = "UpSetR"),
        header = T, sep = ";")

## 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).

## 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.

    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))

## 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.
notice the use of query.legend

    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")

## 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.

    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.

    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))

## 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.

    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))

## Example 5: Intersection Box Plots

Box plots that show the distribution of an attribute across all intersections. Can display a maximum of two box plot summaries at once. The `boxplot.summary` parameter takes a vector of one or two attribute names.

    upset(movies, boxplot.summary = c("AvgRating", "ReleaseDate"))