tspplot.jl

###################################################
# FUNÇÃO PARA PLOTAR SOLUÇÕES DO TSP
#
# Autor: Leonardo D. Secchin
# Data : 23/03/2023
# leonardosecchin.github.io/metaheuristicas/
###################################################

using Plots
using Random

function tspplot(tsp, sol, title = "")
    # número de cidades
    n = tsp.dimension

    # tamanho da imagem
    xmin = minimum(tsp.nodes[:,1])
    xmax = maximum(tsp.nodes[:,1])
    ymin = minimum(tsp.nodes[:,2])
    ymax = maximum(tsp.nodes[:,2])

    # adiciona 5% de folga nas lateriais
    folga = 0.05*max( xmax-xmin, ymax-ymin )

    fig = plot(title=tsp.name*"\n"*title, xlims=(xmin-folga,xmax+folga), ylims=(ymin-folga,ymax+folga), aspect_ratio=:equal, leg=false)

    # plota cidades
    for i = 1:n
        fig = scatter!([tsp.nodes[i,1]], [tsp.nodes[i,2]], color="red", mark=:o, markersize=3)
    end

    # plota solução
    for i = 1:(length(sol)-1)
        fig = plot!( [tsp.nodes[sol[i],1], tsp.nodes[sol[i+1],1]], [tsp.nodes[sol[i],2], tsp.nodes[sol[i+1],2]], color="black", lw=0.5)
    end
    # plot o segmento entre a última cidade e a primeira
    fig = plot!( [tsp.nodes[sol[end],1], tsp.nodes[sol[1],1]], [tsp.nodes[sol[end],2], tsp.nodes[sol[1],2]], color="black", lw=0.5)

    display(fig)
end