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## frair methods
# Print for objects of class frfit
print.frfit <- function(x, ...){
cat('FUNCTIONAL RESPONSE FIT\n')
cat(paste0('\nResponse: ', x$response))
cat(paste0('\nDescription: ', as.character(frair_responses(show=FALSE)[[x$response]][2])))
cat(paste0('\nOptimised variables: ', paste0(x$optimvars, collapse=', ')))
cat(paste0('\nFixed variables: ', ifelse(test=!is.null(x$fixedvars), yes=paste(x$fixedvars, collapse=', '), no='NA')))
cat('\n')
cat('\nCoefficients:\n')
print(round(x$coefficients, 3))
cat('\nNOTE: It is recommended you inspect the raw fit too (see: ?frair_fit)\n')
}
plot.frfit <- function(x, xlab=x$xvar, ylab=x$yvar, ...){
plot(x$x, x$y, xlab=xlab, ylab=ylab, ...)
}
lines.frfit <- function(x, tozero=FALSE, ...){
fitfun <- get(x$response, pos = "package:frair")
if(tozero){
zero_answer <- fitfun(0, as.list(x$coefficients))
if(is.na(zero_answer)){
warning(c("The supplied function is undefined at zero.\n",
" Plotting to a minimum of 1e-04 instead."))
lowval <- 1e-04
} else {
lowval <- 0
}
newx <- seq(from=lowval, to=max(x$x), length.out = 50)
} else {
newx <- seq(from=min(x$x), to=max(x$x), length.out = 50)
}
newy <- fitfun(newx, as.list(x$coefficients))
lines(x=newx, y=newy, ...)
}
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