```
library(deeptime)
# Load ggplot2
library(ggplot2)
# Load ggtree
library(ggtree)
# Load paleotree for some example data
library(paleotree)
data(RaiaCopesRule)
```

Combining multiple plots together into figures is a key component of
developing publishable data visualizations. Many other packages provide
ways to combine and arrange plots. For example, the
`gridExtra`

package has the `grid.arrange()`

function which allows the user to arrange plots in fairly complex
layouts. However, the main drawback (for most cases) of this function is
that the components of the plots (axes, labels, panels, etc.) are not
aligned. The `ggarrange()`

function in the `egg`

package uses a 3x3 decomposition of
the individual plots to align some of the plot components. The central
cells correspond to the core panels, surrounded by axes, legends,
etc.

**deeptime** expands on this functionality with
`ggarrange2()`

to perform 7x7 decomposition of individual
plots, as shown below. This ensures that more components of the
individual plots are aligned with one another (e.g., the axis labels,
the axis tick labels). The central cell corresponds to the plot
panel(s), the rectangle of cells around that corresponds to the axes,
the rectangle of cells around that corresponds to the axis titles, and
the rectangle of cells around that corresponds to legends.

```
<- ggplot(mtcars, aes(mpg, wt, colour = factor(cyl))) +
p1 geom_point() +
theme_classic(base_size = 20)
ggarrange2(p1, debug = TRUE)
```

With this 7x7 decomposition process, it becomes very simple to combine plots into single figures with properly aligned components.

```
<- ggplot(ammoniteTraitsRaia) +
p1 geom_point(aes(x = Log_D, y = FD)) +
labs(x = "Body size", y = "Suture complexity") +
theme_classic()
<- ggplot(ammoniteTraitsRaia) +
p2 geom_point(aes(x = Log_D, y = log_dur)) +
labs(x = "Body size", y = "Stratigraphic duration (myr)") +
theme_classic()
<- ggarrange2(p1, p2, widths = c(2, 1), draw = FALSE) gg1
```

You can chain calls to `ggarrange2()`

to accomplish highly
complex combinations and arrangements:

```
<- ggtree(ammoniteTreeRaia, position = position_nudge(x = -ammoniteTreeRaia$root.time)) +
p3 coord_geo(
xlim = c(-415, -66), ylim = c(-2, Ntip(ammoniteTreeRaia)), pos = "bottom",
size = 4, abbrv = FALSE, neg = TRUE
+
) scale_x_continuous(breaks = seq(-425, -50, 25), labels = -seq(-425, -50, 25)) +
theme_tree2() +
theme(plot.margin = margin(7, 11, 7, 11))
ggarrange2(gg1, p3, nrow = 2, heights = c(1, 2))
```

You can also accomplish complex plot layouts by supplying a matrix of
integers to the `layout`

argument, like with the base R
`layout()`

function. This can be used to insert empty plots
or change the order of plots. Note that repeating a number will
duplicate a plot, not expand it across multiple plot spots.

```
ggarrange2(p1, p2, p3,
layout = matrix(c(1, 2, 0, 3), nrow = 2, byrow = TRUE),
widths = c(1, 3)
)
```

Note that I provide no guarantee that `ggarrange2()`

solves every problem when arranging plots. The following other options
may also be very useful:

- The
`{cowplot}`

package has the`cowplot::plot_grid()`

function which accomplishes many of the same features as`ggarrange2()`

. - The
`{patchwork}`

has very intuitive tools for combining and arranging plots (e.g, using mathematical symbols).