66 lines
1.1 KiB
R
66 lines
1.1 KiB
R
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#'
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#' Calculate the mean of a die.
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#'
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#' Calculate the mean.
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#'
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#' @param x A die
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#' @return The expected value of the die.
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#' @examples
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#' mean(d20)
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#'
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#' @export
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mean.Die <- function(x){
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return(sum(x$numbers*x$probs))
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}
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#'
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#' Print a die.
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#'
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#' Rolls a die a single time.
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#'
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#' @param x A die to roll.
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#' @param ... Other parameters to pass to \code{\link{roll}}
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#' @examples
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#' print(d20)
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#'
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#' @export
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print.Die <- function(x, ...){
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print(roll(x, ...))
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}
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#'
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#' Print a die's summary.
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#'
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#' Return the probabilities of a die for different rolls.
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#'
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#' @param x A die
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#' @return A vector of named probabilities for each outcome of the die.
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#' @examples
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#' summary(advantage(d20,d20))
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#' @export
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summary.Die <- function(x){
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probs <- x$probs
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names(probs) <- x$numbers
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return(probs)
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}
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#'
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#' Plot a die's summary.
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#'
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#' Plot the probabilities of a die for different rolls.
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#'
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#' @param x A die
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#' @return A ggplot2 plot.
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#' @examples
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#' plot(advantage(d20,d20))
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#'
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#' @export
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plot.Die <- function(x){
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data = data.frame(Number=x$numbers, Probability=x$probs)
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plt = ggplot(data, aes(x=Number, y=Probability)) + geom_col()
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return(plt)
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}
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