# Adding geological timescales to plots

The main function of deeptime is `coord_geo()`, which functions just like `coord_trans()` from `{ggplot2}`. You can use this function to add highly customizable timescales to a wide variety of ggplots. Before we begin, let’s load some necessary packages first.

    # Load deeptime
    library(deeptime)
    # Load other packages
    library(ggplot2)
    library(dplyr)
    # Load divDyn for coral data
    library(divDyn)
    data(corals)
    # Load gsloid for oxygen isotope data
    library(gsloid)

## Adding geological timescales

First, let’s summarize some coral data from the `divDyn` package to generate a diversity curve that we’ll be able to plot:

    # this is not a proper diversity curve but it gets the point across
    coral_div <- corals %>%
      filter(stage != "") %>%
      group_by(period, stage) %>%
      summarise(n = n()) %>%
      mutate(stage_age = (stages$max_age[match(stage, stages$name)] +
        stages$min_age[match(stage, stages$name)]) / 2)

Now, we can plot the data and add a geological timescale. The default behavior is to add the ICS periods to the bottom axis. The data used for this is included in the package (`?periods`) along with data for `?eons`, `?stages`, `?epochs`, and `?eras`. Note that the function assumes that age is decreasing towards the present.

    ggplot(coral_div) +
      geom_line(aes(x = stage_age, y = n)) +
      scale_x_reverse("Age (Ma)") +
      ylab("Coral Genera") +
      coord_geo(xlim = c(250, 0), ylim = c(0, 1700)) +
      theme_classic()

### Scales on other axes

You can add the timescale to whichever axis you’d like by setting the `pos` argument. For example, `pos = "left"` can be used to put the timescale on the left axis. Also, note that we’re using the “Geomagnetic Polarity Chron” timescale here. This is one of more than 35 regional and global timescales that are available through deeptime from the Macrostrat database (see `get_scale_data()`).

    ggplot(lisiecki2005) +
      geom_line(aes(x = d18O, y = Time / 1000), orientation = "y") +
      scale_y_reverse("Time (Ma)") +
      scale_x_reverse() +
      coord_geo(
        dat = "Geomagnetic Polarity Chron", xlim = c(6, 2), ylim = c(6, 0),
        pos = "left", rot = 90
      ) +
      theme_classic()

### Add multiple timescales

You can also add multiple timescales by providing a list for `pos`. Other arguments can be lists or single values (either of which will be recycled if necessary). In this case we are adding the “Geomagnetic Polarity Chron” timescale to the left axis and the “Planktic foraminiferal Primary Biozones” timescale to the right axis.

    # uses the oxygen isotope data from above
    ggplot(lisiecki2005) +
      geom_line(aes(x = d18O, y = Time / 1000), orientation = "y") +
      scale_y_reverse("Time (Ma)") +
      scale_x_reverse() +
      coord_geo(
        dat = list("Geomagnetic Polarity Chron", "Planktic foraminiferal Primary Biozones"),
        xlim = c(6, 2), ylim = c(5.5, 0), pos = list("l", "r"),
        rot = 90, skip = "PL4", size = list(5, 4)
      ) +
      theme_classic()

### Stack multiple scales

You can even stack multiple timescales on the same side. Scales are added from the inside to the outside. Here we are stacking periods and eras.

    # uses the coral diversity data from above
    ggplot(coral_div) +
      geom_line(aes(x = stage_age, y = n)) +
      scale_x_reverse("Age (Ma)") +
      ylab("Coral Genera") +
      coord_geo(
        dat = list("periods", "eras"), xlim = c(250, 0), ylim = c(0, 1700),
        pos = list("b", "b"), abbrv = list(TRUE, FALSE)
      ) +
      theme_classic()

### Timescales and faceted plots

`coord_geo()` synergizes well with faceted plots. You can change on which facets the timescale is plotted by changing the `scales` argument in `facet_wrap()`. The default behavior is to only include the timescale on the bottom-most panel. This behavior works similarly with `facet_grid()`.

    # uses the coral occurrence data from above
    coral_div_diet <- corals %>%
      filter(stage != "") %>%
      group_by(diet, stage) %>%
      summarise(n = n()) %>%
      mutate(stage_age = (stages$max_age[match(stage, stages$name)] +
        stages$min_age[match(stage, stages$name)]) / 2)

    ggplot(coral_div_diet) +
      geom_line(aes(x = stage_age, y = n)) +
      scale_x_reverse("Age (Ma)") +
      ylab("Coral Genera") +
      coord_geo(xlim = c(250, 0)) +
      theme_classic() +
      facet_wrap(~diet, nrow = 3)

By specifying `scales = "free_x"`, you can add a geological time scale to each panel.

    ggplot(coral_div_diet) +
      geom_line(aes(x = stage_age, y = n)) +
      scale_x_reverse("Age (Ma)") +
      ylab("Coral Genera") +
      coord_geo(xlim = c(250, 0)) +
      theme_classic() +
      facet_wrap(~diet, nrow = 3, scales = "free_x")

### Resize labels to fit inside interval rectangles

`coord_geo()` can use the `{ggfittext}` package to resize the interval labels. This can be enabled by setting `size` to `"auto"`. Additional arguments can be passed to `ggfittext::geom_fit_text()` as a list using the `fittext_args` argument.

    ggplot(coral_div) +
      geom_line(aes(x = stage_age, y = n)) +
      scale_x_reverse("Age (Ma)") +
      ylab("Coral Genera") +
      coord_geo(
        dat = "periods", xlim = c(250, 0), ylim = c(0, 1700),
        abbrv = FALSE, size = "auto", fittext_args = list(size = 20)
      ) +
      theme_classic()

## Scales on discrete axes

`coord_geo()` will automatically detect if your axis is discrete. The categories of the discrete axis (which can be reordered using the `limits` argument of `scale_x_discrete()`/`scale_y_discrete()`) should match the `name` column of the timescale data (`dat`). You can use the arguments of `theme()` and `scale_[x/y]_discrete()` to optionally remove the labels and tick marks.

    # use the coral occurrence data from above
    coral_div_dis <- corals %>%
      filter(period != "") %>%
      group_by(diet, period) %>%
      summarise(n = n()) %>%
      mutate(period_age = (periods$max_age[match(period, periods$name)] +
        periods$min_age[match(period, periods$name)]) / 2) %>%
      arrange(-period_age)

    ggplot(coral_div_dis) +
      geom_col(aes(x = period, y = n, fill = diet)) +
      scale_x_discrete("Period",
        limits = unique(coral_div_dis$period), labels = NULL,
        expand = expansion(add = .5)
      ) +
      scale_y_continuous(expand = c(0, 0)) +
      scale_fill_viridis_d("Diet") +
      ylab("Coral Genera") +
      coord_geo(expand = TRUE, skip = NULL, abbrv = TRUE) +
      theme_classic() +
      theme(axis.ticks.length.x = unit(0, "lines"))

### Custom discrete scales

You can also supply your own pre-discretized scale data by setting the `dat_is_discrete` parameter to `TRUE`. Custom scales should always have `name`, `max_age`, and `min_age` columns. Optional columns include `abbr` for abbreviations, `color` for background colors, and `lab_color` for interval label colors. You can even have one scale with auto-discretized intervals and one scale with pre-discretized intervals.

    eras_custom <- data.frame(
      name = c("Mesozoic", "Cenozoic"), max_age = c(0.5, 3.5),
      min_age = c(3.5, 6.5), color = c("#67C5CA", "#F2F91D")
    )

    ggplot(coral_div_dis) +
      geom_col(aes(x = period, y = n, fill = diet)) +
      scale_x_discrete(NULL,
        limits = unique(coral_div_dis$period), labels = NULL,
        expand = expansion(add = .5)
      ) +
      scale_y_continuous(expand = c(0, 0)) +
      scale_fill_viridis_d("Diet") +
      ylab("Coral Genera") +
      coord_geo(
        dat = list("periods", eras_custom), pos = c("b", "b"), expand = TRUE,
        skip = NULL, abbrv = list(TRUE, FALSE), dat_is_discrete = list(FALSE, TRUE)
      ) +
      theme_classic() +
      theme(axis.ticks.length.x = unit(0, "lines"))

## More advanced topics

Looking to learn about more advanced features of deeptime? Look no further:

- Plotting phylogenies with timescales
- Additional ggplot coordinate systems
- Plotting trait data
- Plotting temporal data
- Plotting geological/stratigraphical patterns
- Combining and arranging plots