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Switch between annual trends and age profiles

Source: R/plot-trends.R
plot_age_year.Rd

Display an age-year table with Annual trends and Age profiles buttons, using the same plots and controls as the dashboard. Each view retains its selected animation frame, axis scale, confidence intervals and legend selections.

Usage

plot_age_year(
  data,
  plot = plot_trend,
  x = ~year,
  xlab = "Year",
  frame = ~age,
  ...
)

Arguments

data

Data frame containing numeric year and age columns, plus the estimates or observations required by the plotting function.

plot

Function used to draw each view. Defaults to plot_trend(); use plot_obs_pred() for observations and predictions. A custom function must accept data, x, xlab, frame and additional plotting arguments, and return a Plotly object. Add custom layers inside that function.

x

Formula specifying x variable

xlab

Label for the x-axis.

frame

Formula selecting the initial view: ~ age for Annual trends (the default), or ~ year with x = ~ age for Age profiles. Other frame/axis combinations produce a single ordinary plot.

...

Additional arguments to pass to plotly::plot_ly() such as color, colors, etc.

Value

A browsable HTML container holding two Plotly widgets for age-year views. Other frame/axis combinations return the supplied plotting function's Plotly object, as do single-age tables. Modify individual plots through plot before assembly.

Details

The two views use separate widgets, without refitting or changing the input table. Projection boundaries appear only on year axes; projection years are identified in the age-profile selector and default hover text. Multiple displays can be embedded in the same HTML document independently. A single-age table instead returns an annual Plotly trend labeled with its age, without animation or view buttons. Use plot_trend() or plot_obs_pred() directly for a single view; their returned Plotly objects remain available for adding layers or changing layout.

See also

plot_trend(), plot_obs_pred(), add_plot_buttons(), vis_tam()

Examples

d <- expand.grid(year = 2000:2004, age = 1:3)
d$est <- exp(0.1 * (d$year - 2000) + 0.2 * d$age)
annual <- plot_age_year(d, ylab = "Abundance")
profiles <- plot_age_year(d, x = ~age, xlab = "Age", frame = ~year)
d$pred <- d$est
d$obs <- d$est * 1.1
catch_views <- plot_age_year(d, plot = plot_obs_pred, ylab = "Catch")
# Print a view to display it, or save it with htmltools::save_html().