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visualization-facebook.jl
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visualization-facebook.jl
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using LightGraphs
using DelimitedFiles
using SparseArrays
using MAT
using Random
using JLD2,FileIO
using PyCall
using PyPlot
using Statistics
include("PageRank.jl")
include("SLQcvx.jl") # this includes SLQ.jl
include("common.jl")
include("CRDlgc.jl")
include("LocalClusteringObjs.jl")
#datasets = ["Colgate88.mat","Rice31.mat","Johns Hopkins55.mat","Simmons81.mat"]
records_crd_3 = load("results/records-crd-h-3.jld2")
records_crd_5 = load("results/records-crd-h-5.jld2")
records_acl = load("results/records-acl.jld2")
records_slq_0 = load("results/records-slq-0.jld2")
records_slq_1 = load("results/records-slq-1.jld2")
records_hk = load("results/records-hk.jld2")
records_nonlinear_diffusion = load("results/records-nld.jld2")
records_sl = load("results/records-sl-5.jld2")
records_gcn = load("results/records-gcn.jld2")
datasets = ["UCLA26.mat","Brown11.mat","Duke14.mat","UPenn7.mat","Yale4.mat","Stanford3.mat","MIT8.mat","Cornell5.mat"]
records = [records_crd_3,records_acl,records_slq_0,records_slq_1,records_hk,records_nonlinear_diffusion,records_sl]
years = [2008,2009]
ntrials = 50
nmethods = length(records)
slq_ids = [3,4]
color = "#F2AA4CFF"
for file in datasets
for year in years
fig,ax = subplots(1,1,figsize=(4,2))
f1 = []
for tmp in records_slq_0[file][year]
if tmp[2] < 1
push!(f1,2*tmp[3]*tmp[4]/(tmp[3]+tmp[4]))
end
end
patches = ax.violinplot(f1,vert=false,showextrema=false)
patch = patches["bodies"][1]
patch.set_facecolor(color)
patch.set_edgecolor("k")
patch.set_alpha(0.6)
ax.plot([minimum(f1),maximum(f1)],[1,1],color="k")
ax.set_xlim(minimum(f1),maximum(f1))
ax.spines["top"].set_visible(false)
ax.spines["right"].set_visible(false)
ax.spines["left"].set_visible(false)
ax.spines["bottom"].set_visible(false)
ax.yaxis.set_ticklabels([])
ax.tick_params(axis="y", which="both", length=0)
ax.xaxis.set_ticklabels([])
ax.tick_params(axis="x", which="both", length=0)
fig.tight_layout(pad=0)
name = split(file,".")[1]
year = Int(year)
val = round(median(f1),digits=1)
println("$name $year $val")
fig.savefig("figures/$name-$year-slq-0.pdf",bbox_inches="tight",pad_inches=0)
end
end
for file in datasets
for year in years
fig,ax = subplots(1,1,figsize=(4,2))
f1 = []
for tmp in records_slq_1[file][year]
if tmp[2] < 1
push!(f1,2*tmp[3]*tmp[4]/(tmp[3]+tmp[4]))
end
end
patches = ax.violinplot(f1,vert=false,showextrema=false)
patch = patches["bodies"][1]
patch.set_facecolor(color)
patch.set_edgecolor("k")
patch.set_alpha(0.6)
ax.plot([minimum(f1),maximum(f1)],[1,1],color="k")
ax.set_xlim(minimum(f1),maximum(f1))
ax.spines["top"].set_visible(false)
ax.spines["right"].set_visible(false)
ax.spines["left"].set_visible(false)
ax.spines["bottom"].set_visible(false)
ax.yaxis.set_ticklabels([])
ax.tick_params(axis="y", which="both", length=0)
ax.xaxis.set_ticklabels([])
ax.tick_params(axis="x", which="both", length=0)
fig.tight_layout(pad=0)
name = split(file,".")[1]
year = Int(year)
val = round(median(f1),digits=1)
println("$name $year $val")
fig.savefig("figures/$name-$year-slq-1.pdf",bbox_inches="tight",pad_inches=0)
end
end
for file in datasets
for year in years
fig,ax = subplots(1,1,figsize=(4,2))
f1 = []
for tmp in records_crd_3[file][year]
if tmp[2] < 1 && tmp[3]*tmp[4] > 0
push!(f1,2*tmp[3]*tmp[4]/(tmp[3]+tmp[4]))
end
end
patches = ax.violinplot(f1,vert=false,showextrema=false)
patch = patches["bodies"][1]
patch.set_facecolor(color)
patch.set_edgecolor("k")
patch.set_alpha(0.6)
ax.plot([minimum(f1),maximum(f1)],[1,1],color="k")
ax.set_xlim(minimum(f1),maximum(f1))
ax.spines["top"].set_visible(false)
ax.spines["right"].set_visible(false)
ax.spines["left"].set_visible(false)
ax.spines["bottom"].set_visible(false)
ax.yaxis.set_ticklabels([])
ax.tick_params(axis="y", which="both", length=0)
ax.xaxis.set_ticklabels([])
ax.tick_params(axis="x", which="both", length=0)
fig.tight_layout(pad=0)
name = split(file,".")[1]
year = Int(year)
val = round(median(f1),digits=1)
println("$name $year $val")
fig.savefig("figures/$name-$year-crd-h-3.pdf",bbox_inches="tight",pad_inches=0)
end
end
for file in datasets
for year in years
fig,ax = subplots(1,1,figsize=(4,2))
f1 = []
for tmp in records_crd_5[file][year]
if tmp[2] < 1 && tmp[3]*tmp[4] > 0
push!(f1,2*tmp[3]*tmp[4]/(tmp[3]+tmp[4]))
end
end
patches = ax.violinplot(f1,vert=false,showextrema=false)
patch = patches["bodies"][1]
patch.set_facecolor(color)
patch.set_edgecolor("k")
patch.set_alpha(0.6)
ax.plot([minimum(f1),maximum(f1)],[1,1],color="k")
ax.set_xlim(minimum(f1),maximum(f1))
ax.spines["top"].set_visible(false)
ax.spines["right"].set_visible(false)
ax.spines["left"].set_visible(false)
ax.spines["bottom"].set_visible(false)
ax.yaxis.set_ticklabels([])
ax.tick_params(axis="y", which="both", length=0)
ax.xaxis.set_ticklabels([])
ax.tick_params(axis="x", which="both", length=0)
fig.tight_layout(pad=0)
name = split(file,".")[1]
year = Int(year)
val = round(median(f1),digits=1)
println("$name $year $val")
fig.savefig("figures/$name-$year-crd-h-5.pdf",bbox_inches="tight",pad_inches=0)
end
end
for file in datasets
for year in years
fig,ax = subplots(1,1,figsize=(4,2))
f1 = []
for tmp in records_acl[file][year]
if tmp[2] < 1 && tmp[3]*tmp[4] > 0
push!(f1,2*tmp[3]*tmp[4]/(tmp[3]+tmp[4]))
end
end
patches = ax.violinplot(f1,vert=false,showextrema=false)
patch = patches["bodies"][1]
patch.set_facecolor(color)
patch.set_edgecolor("k")
patch.set_alpha(0.6)
ax.plot([minimum(f1),maximum(f1)],[1,1],color="k")
ax.set_xlim(minimum(f1),maximum(f1))
ax.spines["top"].set_visible(false)
ax.spines["right"].set_visible(false)
ax.spines["left"].set_visible(false)
ax.spines["bottom"].set_visible(false)
ax.yaxis.set_ticklabels([])
ax.tick_params(axis="y", which="both", length=0)
ax.xaxis.set_ticklabels([])
ax.tick_params(axis="x", which="both", length=0)
fig.tight_layout(pad=0)
name = split(file,".")[1]
year = Int(year)
val = round(median(f1),digits=1)
println("$name $year $val")
fig.savefig("figures/$name-$year-acl.pdf",bbox_inches="tight",pad_inches=0)
end
end
for file in datasets
for year in years
fig,ax = subplots(1,1,figsize=(4,2))
f1 = []
for tmp in records_hk[file][year]
if tmp[2] < 1 && tmp[3]*tmp[4] > 0
push!(f1,2*tmp[3]*tmp[4]/(tmp[3]+tmp[4]))
end
end
patches = ax.violinplot(f1,vert=false,showextrema=false)
patch = patches["bodies"][1]
patch.set_facecolor(color)
patch.set_edgecolor("k")
patch.set_alpha(0.6)
ax.plot([minimum(f1),maximum(f1)],[1,1],color="k")
ax.set_xlim(minimum(f1),maximum(f1))
ax.spines["top"].set_visible(false)
ax.spines["right"].set_visible(false)
ax.spines["left"].set_visible(false)
ax.spines["bottom"].set_visible(false)
ax.yaxis.set_ticklabels([])
ax.tick_params(axis="y", which="both", length=0)
ax.xaxis.set_ticklabels([])
ax.tick_params(axis="x", which="both", length=0)
fig.tight_layout(pad=0)
name = split(file,".")[1]
year = Int(year)
val = round(median(f1),digits=1)
println("$name $year $val")
fig.savefig("figures/$name-$year-hk.pdf",bbox_inches="tight",pad_inches=0)
end
end
for file in datasets
for year in years
fig,ax = subplots(1,1,figsize=(4,2))
f1 = []
for tmp in records_nonlinear_diffusion[file][year]
if tmp[2] < 1 && tmp[3]*tmp[4] > 0
push!(f1,2*tmp[3]*tmp[4]/(tmp[3]+tmp[4]))
end
end
patches = ax.violinplot(f1,vert=false,showextrema=false)
patch = patches["bodies"][1]
patch.set_facecolor(color)
patch.set_edgecolor("k")
patch.set_alpha(0.6)
ax.plot([minimum(f1),maximum(f1)],[1,1],color="k")
ax.set_xlim(minimum(f1),maximum(f1))
ax.spines["top"].set_visible(false)
ax.spines["right"].set_visible(false)
ax.spines["left"].set_visible(false)
ax.spines["bottom"].set_visible(false)
ax.yaxis.set_ticklabels([])
ax.tick_params(axis="y", which="both", length=0)
ax.xaxis.set_ticklabels([])
ax.tick_params(axis="x", which="both", length=0)
fig.tight_layout(pad=0)
name = split(file,".")[1]
year = Int(year)
val = round(median(f1),digits=1)
println("$name $year $val")
fig.savefig("figures/$name-$year-nld.pdf",bbox_inches="tight",pad_inches=0)
end
end
for file in datasets
for year in years
fig,ax = subplots(1,1,figsize=(4,2))
f1 = []
for tmp in records_sl[file][year]
if tmp[2] < 1 && tmp[3]*tmp[4] > 0
push!(f1,2*tmp[3]*tmp[4]/(tmp[3]+tmp[4]))
end
end
patches = ax.violinplot(f1,vert=false,showextrema=false)
patch = patches["bodies"][1]
patch.set_facecolor(color)
patch.set_edgecolor("k")
patch.set_alpha(0.6)
ax.plot([minimum(f1),maximum(f1)],[1,1],color="k")
ax.set_xlim(minimum(f1),maximum(f1))
ax.spines["top"].set_visible(false)
ax.spines["right"].set_visible(false)
ax.spines["left"].set_visible(false)
ax.spines["bottom"].set_visible(false)
ax.yaxis.set_ticklabels([])
ax.tick_params(axis="y", which="both", length=0)
ax.xaxis.set_ticklabels([])
ax.tick_params(axis="x", which="both", length=0)
fig.tight_layout(pad=0)
name = split(file,".")[1]
year = Int(year)
val = round(median(f1),digits=1)
println("$name $year $val")
fig.savefig("figures/$name-$year-sl-5.pdf",bbox_inches="tight",pad_inches=0)
end
end
for file in datasets
for year in years
fig,ax = subplots(1,1,figsize=(4,2))
f1 = []
for tmp in records_gcn[file][year]
if tmp[2] < 1 && tmp[3]*tmp[4] > 0
push!(f1,2*tmp[3]*tmp[4]/(tmp[3]+tmp[4]))
end
end
patches = ax.violinplot(f1,vert=false,showextrema=false)
patch = patches["bodies"][1]
patch.set_facecolor(color)
patch.set_edgecolor("k")
patch.set_alpha(0.6)
ax.plot([minimum(f1),maximum(f1)],[1,1],color="k")
ax.set_xlim(minimum(f1),maximum(f1))
ax.spines["top"].set_visible(false)
ax.spines["right"].set_visible(false)
ax.spines["left"].set_visible(false)
ax.spines["bottom"].set_visible(false)
ax.yaxis.set_ticklabels([])
ax.tick_params(axis="y", which="both", length=0)
ax.xaxis.set_ticklabels([])
ax.tick_params(axis="x", which="both", length=0)
fig.tight_layout(pad=0)
name = split(file,".")[1]
year = Int(year)
val = round(median(f1),digits=1)
println("$name $year $val")
fig.savefig("figures/$name-$year-gcn.pdf",bbox_inches="tight",pad_inches=0)
end
end
# fig,plt_axes = subplots(length(years),length(datasets[1]),figsize=(20,5),gridspec_kw=Dict("wspace"=>0.1))
# for (j,row_dataset) in enumerate(datasets)
# for (k,dataset) in enumerate(row_dataset)
# file = dataset
# ax = plt_axes[j,k]
# ax.spines["top"].set_visible(false)
# ax.spines["right"].set_visible(false)
# # ax.spines["left"].set_visible(false)
# ax.spines["bottom"].set_visible(false)
# for (y,year) in enumerate(years)
# tmp = zeros(ntrials,length(records))
# invalid_i = []
# for i in 1:ntrials
# for (f,record) in enumerate(records)
# pr,rc = record[file][year*1.0][i][3],record[file][year*1.0][i][4]
# tmp[i,f] = 2*pr*rc/(pr+rc)
# if 2*pr*rc/(pr+rc) == 1 || pr*rc == 0
# push!(invalid_i,i)
# end
# end
# end
# colors = ["#1f77b4", "#ff7f0e", "#2ca02c", "#d62728", "purple","brown"]
# valid_i = setdiff(1:ntrials,invalid_i)
# tmp = tmp[valid_i,:]
# pos = 2*collect(1:length(records)).+0.6*(y-1)
# bp = ax.violinplot(tmp,positions=pos,showextrema=false)
# ax.vlines(pos,minimum(tmp,dims=1),maximum(tmp,dims=1))
# ax.xaxis.set_ticklabels([])
# if k != 1
# ax.yaxis.set_ticklabels([])
# ax.tick_params(axis="y", which="both", length=0)
# ax.spines["left"].set_visible(false)
# end
# ax.tick_params(axis="x", which="both", length=0)
# for (l,patch) in enumerate(bp["bodies"])
# patch.set_facecolor(colors[l])
# patch.set_edgecolor("k")
# patch.set_alpha(0.6)
# end
# if k == 1 && j == 2
# plt_axes[1,2].legend(labels = ["CRD","ACL","SLQ (\$\\delta=0\$)","SLQ (\$\\delta=10^{-5}\$)","heat kernel","nonlin-diff"],
# handles=bp["bodies"],fancybox=true,shadow=true,loc=(-1.0,1.05),ncol=6,fontsize=18)
# end
# end
# for tick in ax.xaxis.get_major_ticks()
# tick.label.set_fontsize(18)
# end
# for tick in ax.yaxis.get_major_ticks()
# tick.label.set_fontsize(18)
# end
# ax.set_ylim(0,1)
# end
# end
# plt_axes[1,1].set_xlabel("UCLA",fontsize=20)
# plt_axes[1,2].set_xlabel("Brown",fontsize=20)
# plt_axes[1,3].set_xlabel("Duke",fontsize=20)
# plt_axes[1,4].set_xlabel("UPenn",fontsize=20)
# plt_axes[2,1].set_xlabel("Yale",fontsize=20)
# plt_axes[2,2].set_xlabel("Stanford",fontsize=20)
# plt_axes[2,3].set_xlabel("MIT",fontsize=20)
# plt_axes[2,4].set_xlabel("Cornell",fontsize=20)
# fig.savefig("figures/facebook_f1_score_h_5.pdf",format="pdf",bbox_inches="tight")
# gcf()
# # save("records_nonlinear_diffusion-1.5.jld2",records_nonlinear_diffusion)
# # save("records_nonlinear_diffusion-1.2.jld2",records_nonlinear_diffusion)
# # save("records_nonlinear_Lp_diffusion.jld2",records_nonlinear_Lp_diffusion)
# minimum(rand(3,3),dims=1)