In IBAHCM/RPiR: Reproducible Programming in R

More on functions {.smaller}

Useful commands

• Functions
• Optional arguments
• Using ... to accept any arguments
• Using functions as arguments
• rbinom()

Functions

Functions carry out a fixed task using the arguments provided:

```{R, comment=""} subtract <- function(value, from) { from - value } subtract(value = 5, from = 3) subtract(from = 3, value = 5)

Naming the arguments makes it clearer what you are doing.

## Optional arguments

Make an argument optional by providing a default value:

```{R, comment=""}
increase <- function(value, by = 1) {
  value + by
}
increase(value = 5, by = 2)
increase(value = 5, by = 1)
increase(value = 5)

Using ... to accept any arguments

Some functions don't know what their arguments will be:

```{R, eval = FALSE} plot(x, y) plot(x, y, col="black") plot(x, y, type="l", lty=2)

The extra arguments get passed on to `plot.xy()` or some other function, which
does then the work.

## Using `...` to accept any arguments

Some functions don't know what their arguments will be:

```{R, eval = FALSE}
plot(x, y)
plot(x, y, col="black")
plot(x, y, type="l", lty=2)

The extra arguments get passed on to plot.xy() or some other function, which then does the work. It looks a bit like this:

### <b>
plot <- function(x, y, log = "", ...) {
### </b>
  xlabel <- deparse1(substitute(x))
  ylabel <- deparse1(substitute(y))
  xy <- xy.coords(x, y, xlabel, ylabel, log)
### <b>
  plot.xy(xy, ...)
}
### </b>

Using ... to accept any arguments

Here we do the same in plot_populations():

### <b>
plot_populations <- function(populations, new.graph=TRUE,
                             ylim=NA, lty=1, col=NA, ...) {
### </b>
  # -- lots of other code --
  if (new.graph) {
      # When it's a new plot, do labels and legends, etc.
### <b>
      plot(time, this.pop, ylim = ylim, xlab = "time",
           ylab = "population size", type = "l",
           col = line.cols[index], lty = line.ltys[index], ...)
### </b>
      # -- more code --
    } else { # Otherwise just draw the lines
### <b>
      graphics::lines(time, this.pop, col = line.cols[index],
                      lty = line.ltys[index], ...)
### </b>
    }
### <b>
}
### </b>

Using functions as arguments

```{R, eval = FALSE}

run_simple <- function(step_function, latest.df, end.time, ...)

{ population.df <- latest.df keep.going <- (latest.df$time < end.time) while (keep.going) {

data <- step_function(latest.df, ...)

latest.df <- data$updated.pop
population.df <- rbind(population.df, latest.df)
keep.going <- ((latest.df$time < end.time) &&
               (!data$end.experiment))

} row.names(population.df) <- NULL population.df }

## `rbinom()`

- Draw 1 random number

```r
rbinom(1, count, prob)

• How many infections have occurred if there are 50 animals and there is a probability of infection of 0.1 for each one?

rbinom(1, 50, 0.1)
rbinom(1, 50, 0.1)

IBAHCM/RPiR documentation built on Jan. 12, 2023, 7:41 p.m.