ProbBreed (version 1.0.4.9)

plot.bpsi: Plots for the bpsi object

Description

Build plots using the outputs stored in the bpsi object.

Usage

# S3 method for bpsi
plot(x, ..., category = "BPSI")

Arguments

x

An object of class bpsi.

...

currently not used

category

A string indicating which plot to build. There are currently two types of visualizations. Set "Ranks" for bar plots along each trait and "BPSI" (default) for circular bar plots multitrait.

Author

José Tiago Barroso Chagas

References

Chagas, J. T. B., Dias, K. O. das G., Quintão Carneiro, V., de Oliveira, L. M. C., Nunes, N. X., Júnior, J. D. P., Carneiro, P. C. S., & Carneiro, J. E. de S. (2025). Bayesian probabilistic selection index in the selection of common bean families. Crop Science, 65(3).tools:::Rd_expr_doi("https://doi.org/10.1002/CSC2.70072")

See Also

bpsi

Examples

# \donttest{



mod = bayes_met(data = soy_pat,
                gen = "gen",
                loc = "env",
                repl = NULL,
                trait = "PH",
                reg = NULL,
                year = NULL,
                res.het = TRUE,
                iter = 2000, cores = 2, chain = 4)


mod2 = bayes_met(data = soy_pat,
                 gen = "gen",
                 loc = "env",
                 repl = NULL,
                 trait = "GY",
                 reg = NULL,
                 year = NULL,
                 res.het = TRUE,
                 iter = 2000, cores = 2, chain = 4)

mod3 = bayes_met(data = soy_pat,
                 gen = "gen",
                 loc = "env",
                 repl =  NULL,
                 trait = "NDM",
                 reg = NULL,
                 year = NULL,
                 res.het = TRUE,
                 iter = 2000, cores = 2, chain = 4)



models=list(mod,mod2,mod3)
names(models) <- c("PH","GY","NDM")
increase = c(FALSE,TRUE,FALSE)
names(increase) <- names(models)

probs = list()
for (i in names(models)) {
  outs <- extr_outs(model = models[[i]],
                    probs = c(0.05, 0.95),
                    verbose = TRUE)
  probs[[i]] <- prob_sup(
    extr = outs,
    int = .2,
    increase = increase[[i]],
    save.df = FALSE,
    verbose = TRUE
  )

}

index = bpsi(
  problist = probs,
  increase = increase,
  int = 0.1,
  lambda = c(1, 2, 1),
  save.df = FALSE
)

plot(index, category = "BPSI")
plot(index, category = "Ranks")
# }