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Plots.jl
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#Performance profiles for Mosek, Cplex and Gurobi.
using DelimitedFiles
using BenchmarkProfiles, Plots
dat = readdlm( "Results for Solvers.in" )
for i in 1:1:99
for j in 1:1:3
if dat[i,j]>=360
dat[i,j] = Inf
end
end
end
p = performance_profile(PlotsBackend(), dat,
["Mosek", "Cplex", "Gurobi"],
legend = :topright,
ylims =(0,0.35),
#xaxis =
#scale = :none,
)
savefig(p,"ComSol1.pdf")
#DNN-SOCP detail process
using CSV
using DataFrames
using LazyStack
using Plots
df = CSV.read("Records for Iterations.csv", DataFrame)
#Iteration process of SOCP-based cutting plane method.
aa = [4,19,43]
dim = ["Dimension 30","Dimension 40","Dimension 50"]
plot_array = Any[]
for i in [1,2,3]
k = aa[i]
k = (k-1)*7+1
k_n = k
z_name = [SubString(df[1,k_n],5),SubString(df[1,k_n+7],5),SubString(df[1,k_n+14],5),SubString(df[1,k_n+21],5),SubString(df[1,k_n+28],5)]
k_x = k+1
x_time = rstack(df[:,k_x], df[:,k_x+7], df[:,k_x+14], df[:,k_x+21], df[:,k_x+28]; fill=missing)
k_y = k+3
y_gap = rstack(df[:,k_y], df[:,k_y+7], df[:,k_y+14], df[:,k_y+21], df[:,k_y+28]; fill=missing)
p = plot(x_time, y_gap,
#markershape = :hexagon,
markeralpha = 0.6,
markersize = 5,
markerstrokewidth = 0.1,
markerstrokealpha = 0.1,
#markerstrokecolor = :black,
#markerstrokestyle = :dot,
seriestype = :scatter,
label = permutedims(z_name),
legendfontsize = 5,
legend = :topright,
title = dim[i],
titlelocation = :left,
titlefontsize = 9,
legendfont = 6,
yticks=-0.2:0.2:1, ylims =(-0.2,1))
push!(plot_array,p)
end
#for dimension 60
k = 52
k = (k-1)*7+1
k_n = k
z_name = [SubString(df[1,k_n],5),SubString(df[1,k_n+7],5),SubString(df[1,k_n+14],5)]
k_x = k+4
x_time = rstack(df[:,k_x], df[:,k_x+7], df[:,k_x+14]; fill=missing)
k_y = k+3
y_gap = rstack(df[:,k_y], df[:,k_y+7], df[:,k_y+14]; fill=missing)
p = plot(x_time, y_gap,
#markershape = :hexagon,
markeralpha = 0.6,
markersize = 5,
markerstrokewidth = 0.1,
markerstrokealpha = 0.1,
#markerstrokecolor = :black,
#markerstrokestyle = :dot,
seriestype = :scatter,
label = permutedims(z_name),
legendfontsize = 5,
legend = :topright,
title = "Dimension 60",
titlelocation = :left,
titlefontsize = 9,
legendfont = 6,
yticks=-0.2:0.2:1, ylims =(-0.2,1))
push!(plot_array,p)
plot(plot_array...,
xlabel="Time(s)", ylabel="Relative gap (%)",
#xtickfontsize=18,
xguidefontsize=9,yguidefontsize=9,
layout=(2,2))
#plot!(size=(700,400))
savefig("Low1.pdf")
#Iteration process of SOCP-based cutting plane method for high dimensional instances.
aa = [64,73,82,91]
dim = ["Dimension 80","Dimension 90","Dimension 100","Dimension 125"]
plot_array = Any[]
for i in [1,2,3,4]
k = aa[i]
k = (k-1)*7+1
k_n = k
z_name = [SubString(df[1,k_n],5),SubString(df[1,k_n+7],5),SubString(df[1,k_n+14],5),SubString(df[1,k_n+21],5),SubString(df[1,k_n+28],5)]
k_x = k+4
x_time = rstack(df[:,k_x], df[:,k_x+7], df[:,k_x+14], df[:,k_x+21], df[:,k_x+28]; fill=missing)
k_y = k+3
y_gap = rstack(df[:,k_y], df[:,k_y+7], df[:,k_y+14], df[:,k_y+21], df[:,k_y+28]; fill=missing)
p = plot(x_time, y_gap,
#markershape = :hexagon,
markeralpha = 0.6,
markersize = 5,
markerstrokewidth = 0.1,
markerstrokealpha = 0.1,
#markerstrokecolor = :black,
#markerstrokestyle = :dot,
seriestype = :scatter,
label = permutedims(z_name),
legendfontsize = 5,
legend = :topright,
title = dim[i],
titlelocation = :left,
titlefontsize = 9,
legendfont = 6,
#ylims =(-0.2,1),
#yticks=-0.2:0.2:1
)
push!(plot_array,p)
end
plot(plot_array...,
xlabel="Time(s)", ylabel="Relative gap (%)",
#xtickfontsize=18,
xguidefontsize=9,yguidefontsize=9,
layout=(2,2))
#plot!(size=(700,400))
savefig("HigSca1.pdf")
#The iterative process of SOCP-based cutting plane method for high dimensional instance.
aa = [64,73,82,91]
dim = ["Dimension 80","Dimension 90","Dimension 100","Dimension 125"]
bb = ["Instance","Computing time for each iteration","Number of added constraints","Relative gap to optimal value (%)","Cumulative computing time","The number of iterations","Total number of constraints"]
plot_array = Any[]
for m in [3,4,2,5]
k = 64
k = (k-1)*7+1
k_n = k
z_name = [SubString(df[1,k_n],5),SubString(df[1,k_n+7],5),SubString(df[1,k_n+14],5),SubString(df[1,k_n+21],5),SubString(df[1,k_n+28],5)]
k_x = k+5
x_time = rstack(df[:,k_x], df[:,k_x+7], df[:,k_x+14], df[:,k_x+21], df[:,k_x+28]; fill=missing)
k_y = k+m-1
y_gap = rstack(df[:,k_y], df[:,k_y+7], df[:,k_y+14], df[:,k_y+21], df[:,k_y+28]; fill=missing)
if m == 4
p = plot(x_time, y_gap, #w_tim,
#markershape = :hexagon,
markeralpha = 0.6,
markersize = 5,
markerstrokewidth = 0.1,
markerstrokealpha = 0.1,
#markerstrokecolor = :black,
#markerstrokestyle = :dot,
#seriestype = :scatter,
seriestype = :steppre,
label = permutedims(z_name),
legendfontsize = 5,
legend = :topright,
title = bb[m],
titlelocation = :left,
titlefontsize = 9,
legendfont = 6,
#ylims =(-0.2,1),
#yticks=-0.2:0.2:1
)
push!(plot_array,p)
elseif m == 5
p = plot(x_time, y_gap, #w_tim,
#markershape = :hexagon,
markeralpha = 0.6,
markersize = 5,
markerstrokewidth = 0.1,
markerstrokealpha = 0.1,
#markerstrokecolor = :black,
#markerstrokestyle = :dot,
#seriestype = :scatter,
seriestype = :steppre,
label = permutedims(z_name),
legendfontsize = 5,
legend = :topleft,
title = bb[m],
titlelocation = :left,
titlefontsize = 9,
legendfont = 6,
#ylims =(-0.2,1),
#yticks=-0.2:0.2:1
)
push!(plot_array,p)
else
p = plot(x_time, y_gap, #w_tim,
#markershape = :hexagon,
markeralpha = 0.6,
markersize = 5,
markerstrokewidth = 0.1,
markerstrokealpha = 0.1,
#markerstrokecolor = :black,
#markerstrokestyle = :dot,
#seriestype = :scatter,
seriestype = :steppre,
label = permutedims(z_name),
legendfontsize = 5,
legend = :bottomright,
title = bb[m],
titlelocation = :left,
titlefontsize = 9,
legendfont = 6,
#ylims =(-0.2,1),
#yticks=-0.2:0.2:1
)
push!(plot_array,p)
end
end
plot(plot_array...,
xlabel="The number of iterations", #ylabel="Gap(%)",
#xtickfontsize=18,
xguidefontsize=9,yguidefontsize=9,
layout=(2,2))
#plot!(size=(700,400))
savefig("AppPro2.pdf")
# The change of computing time for single iteration under different dimensions.
aa = [55,64,73,82]
dim = ["Dimension 70","Dimension 80","Dimension 90","Dimension 100"]
plot_array = Any[]
for i in [1,2,3,4]
k = aa[i]
k = (k-1)*7+1
k_n = k
z_name = [SubString(df[1,k_n],5),SubString(df[1,k_n+7],5),SubString(df[1,k_n+14],5),SubString(df[1,k_n+21],5),SubString(df[1,k_n+28],5)]
k_x = k+5
x_time = rstack(df[:,k_x], df[:,k_x+7], df[:,k_x+14], df[:,k_x+21], df[:,k_x+28]; fill=missing)
k_y = k+1
y_gap = rstack(df[:,k_y], df[:,k_y+7], df[:,k_y+14], df[:,k_y+21], df[:,k_y+28]; fill=missing)
p = plot(x_time, y_gap,
#markershape = :hexagon,
markeralpha = 0.6,
markersize = 5,
markerstrokewidth = 0.1,
markerstrokealpha = 0.1,
#markerstrokecolor = :black,
#markerstrokestyle = :dot,
seriestype = :scatter,
label = permutedims(z_name),
legendfontsize = 5,
legend = :topleft,
title = dim[i],
titlelocation = :left,
titlefontsize = 9,
legendfont = 6,
#ylims =(-0.2,1),
#yticks=-0.2:0.2:1
)
push!(plot_array,p)
end
plot(plot_array...,
xlabel="The number of iterations", ylabel="Time(s)",
#xtickfontsize=18,
xguidefontsize=9,yguidefontsize=9,
layout=(2,2))
#plot!(size=(700,400))
savefig("AppPro3.pdf")