predict.Ptmodels {cycleRtools} | R Documentation |
Given a Ptmodels object
, the predict.Ptmodels will produce a named
numeric vector of either time (seconds) or power (watts) values according to
the x
and y
arguments
## S3 method for class 'Ptmodels' predict(object, x, xtype = c("pwr", "time"), ...)
object |
an object of class "Ptmodels". |
x |
the value for which to make a prediction. |
xtype |
what is |
... |
further arguments passed to or from other methods. |
a named numeric vector of predicted values. Names correspond to their respective models.
data(Pt_prof) # Example power-time profile. P <- Pt_prof$pwr tsec <- Pt_prof$time mdls <- Pt_model(P, tsec) ## Model. print(mdls) ## What is the best predicted 20 minute power? predict(mdls, x = 60 * 20, xtype = "time") ## How sustainable is 500 Watts? predict(mdls, x = 500, xtype = "P") / 60 # Minutes. ## Create some plots of the models. par(mfrow = c(2, 2), mar = c(3.1, 3.1, 1.1, 1.1)) plotargs <- alist(x = tsec, y = P, cex = 0.2, ann = FALSE, bty = "l") mapply(function(f, m) { do.call(plot, plotargs) curve(f(x), col = "red", add = TRUE) title(main = paste0(rownames(m),"; RSE = ", round(m$RSE, 2))) legend("topleft", legend = m$formula, bty = "n") return() }, f = mdls$Pfn, m = split(mdls$table, seq_len(nrow(mdls$table))))