#' Formats for power curve
#'
#' @keywords internal
#' @export
#' @rdname dfba_power_curve_method
#' @param object An object of class \code{\linkS4class{dfba_power_curve_out}}
#' @return No return value, called for side effect. Objects of class \code{\linkS4class{dfba_power_curve_out}} are printed.
setMethod("show", "dfba_power_curve_out", function(object) {
cat("Power results for the proportion of samples detecting effects"," ","\n")
cat(" ", "where the variates are distributed as a",object$model,"random variable","\n")
cat(" ", "and where the design is",object$design,"\n")
if(object$design=="paired"){cat(" ", "with a blocking max of ",object$block_max,"\n")}
cat(" ", "The number of Monte Carlo samples are:"," ","\n")
cat(" ", object$nsims," ","\n")
cat(" ", "Criterion for detecting an effect is"," ","\n")
cat(" ", object$effect_crit," ","\n")
cat("The n value per condition:"," ","\n")
cat(object$n," ","\n")
cat("Output Results:", "\n")
print(object$outputdf)
})
#' @export
#' @rdname dfba_power_curve_method
#' @param x An object of class \code{\linkS4class{dfba_power_curve_out}}
#' @return No return value, called for side effect. Method produces a plot of class \code{\linkS4class{dfba_power_curve_out}}
setMethod("plot",
signature("dfba_power_curve_out"),
function(x){
plot(x$outputdf$delta_value,
x$outputdf$Bayes_power,
type="b",
lty = 1,
ylim=c(0,1),
main=expression(cdots~"Frequentist"~ - "Bayesian"),
xlab="Delta",
ylab="Power Estimate")
lines(x$outputdf$delta_value,
x$outputdf$t_power,
type="b",
lty=3)
})
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