In alex-conanec/optisure:

knitr::opts_chunk$set(echo = TRUE)

library(MOOVaR)
library(dplyr)
library(tidyr)
t = system.time({
  res = tune_nsga(param_fixed = list(p = 3, n_lev = c(rep(2,3), 5),
                                     d1 = 13,
                                     d2 = 4,
                                     B = 15),
                  param = list(
                    k_tournament = 2:10,
                    crossing_over_method = factor(c("uniforme", "bloc")),
                    n_echange = 2:8,
                    n_bloc = 2:5,
                    mutation_method = factor(c("simple", "mixte")),
                    freq_m = seq(0, 1, 0.1),
                    TT = 10:60,
                    N = 30:100
                  ), N = 40, TT = 20, base_N_MC = 30, mc_cores = 15, seed=1234)
})

res_simu = list(t = t, res = res)
saveRDS(res_simu, file = "res_tunage_nsga.RDS")

library(tidyverse)
library(MOOVaR)

res_simu = readRDS("res_tunage_nsga.RDS")

cat("Duree du calcul:", res_simu$t[3]%/%3600, "h", res_simu$t[3]%%3600 %/% 60, "min\n")


qlt_plot = plot(res_simu$res, choice = "qlt", mc_cores = 2)
qlt_plot + ylab("HI") + theme_minimal()

plot(res_simu$res, choice = "evol")

PF_plot = plot(res_simu$res, choice = "PF", as_list_plot = TRUE)

library(plotly)
s_y = subplot(PF_plot$p_y,
              titleY = TRUE, titleX = TRUE, nrows = 1,
              margin = c(0.1, 0.1, 0.1, 0.1),
              widths = c(0.3, 0.4, 0.3))

s_x = subplot(PF_plot$p_x, titleX = TRUE,
              nrows = 2,
              margin = c(0.02, 0.1, 0.02, 0.3/2))


ggplotly(subplot(s_y, s_x, nrows = 2,
                            margin = c(0.05, 0.05, 0.05,
                                       0.4/2),
                            titleY = TRUE, titleX = TRUE,
                            heights = c(0.5, 0.5)
)) %>%
  highlight(on = "plotly_selected", off = "plotly_deselect",
            color = "red", persistent = FALSE) %>%
  config(
    toImageButtonOptions = list(
      format = "svg",
      filename = "myplot",
      width = 600,
      height = 700
    )
  )

X = res_simu$res$X
Y = res_simu$res$Y

table(X$freq_m)
table(X$crossing_over_method)

reg1bis=lm(Y$accuracy~., data=X)
summary(reg1bis)

ggplot(data.frame(X, Y)) +
  geom_point(aes(x = t, y=N_eval, colour = mutation_method))+
  xlab("temps (en sec)") +
  ylab("N évaluations") +
  guides(colour = guide_legend(title = "Méthode mut.")) +
  theme_bw()

res_simu$res$res_nsga = res_nsga_run(res = res_simu$res, id = c(19, 22, 23), mc_cores = 2)
comp_plot = plot(res=res_simu$res, choice = "comp", id = c(19, 22, 23), mc_cores = 2)
comp_plot + theme_bw() + xlab("T")

alex-conanec/optisure documentation built on Dec. 19, 2021, 12:27 a.m.