Visualize predictions

# S3 method for aphylo_prediction_score
plot(
  x,
  y = NULL,
  main = "Prediction Accuracy: Observed versus predicted values",
  main.colorkey = "Probability of Functional Annotation",
  which.fun = seq_len(ncol(x$expected)),
  include.labels = NULL,
  labels.col = "black",
  leafs_only = TRUE,
  ...
)

Arguments

x: An object of class aphylo_prediction_score.
y: Ignored.
main: Passed to title.
main.colorkey: Character scalar. Title of the colorkey (optional).
which.fun: Integer vector. Which function to plot.
include.labels: Logical scalar. When TRUE, draws nice labels at each slice which by default are specified as the rownames of x$expected. This is mostly useful when the number of predictions is small.
labels.col: Character scalar. Color of the labels.
leafs_only: Logical. When TRUE (default) only plots the leaf nodes.
...: Ignored

Value

NULL (invisible) Generates a plot of the predictions.

Details

If include.labels = NULL and ncol(x$expected) > 40, then include.labels=FALSE by default.

Examples

set.seed(8783)
atree  <- raphylo(29)
ans    <- aphylo_mle(atree ~ mu_d + mu_s + Pi)
pred_s <- prediction_score(ans)

pred_s
#> Prediction score (H0: Observed = Random)
#> 
#>  N obs.      : 57
#>  alpha(0, 1) : 0.48, 0.52
#>  Observed    : 0.85 ***
#>  Random      : 0.50 
#>  P(<t)       : 0.0003
#> --------------------------------------------------------------------------------
#> Values scaled to range between 0 and 1, 1 being best.
#> 
#> Significance levels: *** p < .01, ** p < .05, * p < .10
#> AUC 0.94.
#> MAE 0.15.
plot(pred_s)