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benchmarks_other_libraries.jl
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benchmarks_other_libraries.jl
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# Benchmark with other Game Theory libraries: GameTheory.jl, Nashpy, pygambit
using Pkg
cd(@__DIR__)
Pkg.activate(".")
using BenchmarkTools
using StrategicGames
using GameTheory
using CSV, DataFrames
using PyCall
#ENV["JULIA_PYTHONCALL_EXE"] = "/home/lobianco/.pyenv/shims/python3"
#import PythonCall
#using Nash.jl # https://github.com/KrainskiL/Nash.jl
#import StrategicGames: nash_se2
const nash = PyCall.pyimport("nashpy") # Equiv. of Python `import nashpy as nash`
const pygambit = PyCall.pyimport("pygambit")
# ------------------------------------------------------------------------------
# Preliminary set up....
bms = DataFrame(benchmark_name = String[], library = String[], method = String[], time = Float64[], memory = Union{Float64,Missing}[], alloc = Union{Int64,Missing}[], neqs = Int64[], notes=String[])
macro binfo(bexpr)
runexpr = quote
b = @benchmark $bexpr
return (median(b).time, median(b).memory, median(b).allocs)
end
return eval(runexpr)
end
py"""
import numpy as np
import pygambit
def setGambitGame2pInt(P1,P2):
p1 = np.array(P1, dtype=pygambit.Rational)
p2 = np.array(P2, dtype=pygambit.Rational)
return pygambit.Game.from_arrays(p1,p2)
def setGambitGame3pInt(P1,P2,P3):
p1 = np.array(P1, dtype=pygambit.Rational)
p2 = np.array(P2, dtype=pygambit.Rational)
p3 = np.array(P3, dtype=pygambit.Rational)
return pygambit.Game.from_arrays(p1,p2,p3)
def setGambitGame2pDec(P1,P2):
p1 = np.array(P1, dtype=pygambit.Decimal)
p2 = np.array(P2, dtype=pygambit.Decimal)
print(p1)
return pygambit.Game.from_arrays(p1,p2)
"""
# For test
res = @binfo rand(2,2)
push!(bms,["Test","rand","rand(2,2)",res...,1,""])
CSV.write("bms.csv",bms)
# ------------------------------------------------------------------------------
# Test 1 - small 3x2 game
game_name = "small_3x2"
u = [(3,3) (3,2);
(2,2) (5,6);
(0,3) (6,1)]
payoff = expand_dimensions(u)
small_3x2_StrategicGames = payoff
small_3x2_GameTheory = NormalFormGame(payoff)
small_3x2_nash = nash.Game(payoff[:,:,1], payoff[:,:,2])
small_3x2_gambit = py"""setGambitGame2pInt"""(payoff[:,:,1],payoff[:,:,2])
eqs = nash_cp(small_3x2_StrategicGames,verbosity=NONE)
neqs = 1
res = @binfo nash_cp($small_3x2_StrategicGames,verbosity=NONE)
push!(bms,[game_name,"StrategicGames","nash_cp",res...,neqs,""])
eqs = nash_se(small_3x2_StrategicGames,max_samples=Inf, mt=true)
neqs = length(eqs)
res = @binfo nash_se($small_3x2_StrategicGames,max_samples=Inf)
push!(bms,[game_name,"StrategicGames","nash_se",res...,neqs,""])
eqs = hc_solve(small_3x2_GameTheory)
neqs = length(eqs)
res = @binfo hc_solve($small_3x2_GameTheory)
push!(bms,[game_name,"GameTheory","hc_solve",res..., neqs,""])
eqs = support_enumeration(small_3x2_GameTheory)
neqs = length(eqs)
res = @binfo support_enumeration($small_3x2_GameTheory)
push!(bms,[game_name,"GameTheory","support_enumeration",res..., neqs,""])
eqs = lrsnash(small_3x2_GameTheory)
neqs = length(eqs)
res = @binfo lrsnash($small_3x2_GameTheory)
push!(bms,[game_name,"GameTheory","lrsnash",res..., neqs,""])
eqs_gen = small_3x2_nash.vertex_enumeration(); eqs = [eq for eq in eqs_gen]
neqs= length(eqs)
res = @binfo begin eqs = $small_3x2_nash.vertex_enumeration(); [eq for eq in eqs] end
res = (res[1], missing, missing)
push!(bms,[game_name,"nashpy","vertex_enumeration",res...,neqs,""])
eqs_gen = small_3x2_nash.lemke_howson_enumeration(); eqs = [eq for eq in eqs_gen]
neqs= length(eqs)
res = @binfo begin eqs = $small_3x2_nash.lemke_howson_enumeration(); [eq for eq in eqs] end
res = (res[1], missing, missing)
push!(bms,[game_name,"nashpy","lemke_howson_enumeration",res...,neqs,"repeated results"])
eqs_gen = small_3x2_nash.support_enumeration(); eqs = [eq for eq in eqs_gen]
neqs= length(eqs)
res = @binfo begin eqs = $small_3x2_nash.support_enumeration(); [eq for eq in eqs] end
res = (res[1], missing, missing)
push!(bms,[game_name,"nashpy","support_enumeration",res...,neqs,""])
eqs = pygambit.nash.lcp_solve(small_3x2_gambit)
neqs= length(eqs)
res = @binfo pygambit.nash.lcp_solve(small_3x2_gambit)
res = (res[1], missing, missing)
push!(bms,[game_name,"pygambit","lcp_solve",res...,neqs,""])
solver = pygambit.nash.ExternalEnumPolySolver()
eqs = solver.solve(small_3x2_gambit)
neqs= length(eqs)
res = @binfo solver.solve(small_3x2_gambit)
res = (res[1], missing, missing)
push!(bms,[game_name,"pygambit","ExternalEnumPolySolver",res...,neqs,""])
CSV.write("bms.csv",bms)
# ------------------------------------------------------------------------------
# Test 2 - mid rand 6x7 game
game_name = "rand_6x7"
#payoff = rand(1:1000,6,7,2)
p1 = [
253 646 641 395 258 153 375
713 17 145 582 338 258 145
174 265 282 588 80 996 478
346 517 963 829 976 735 334
492 106 199 986 278 658 407
506 288 439 345 549 869 986]
p2 = [
296 23 932 537 515 130 679
491 49 315 432 977 799 777
284 761 914 268 313 864 25
75 944 444 209 804 452 502
869 837 950 707 755 452 9
579 794 747 272 929 288 780
]
payoff = cat(p1,p2,dims=3)
rand_6x7_StrategicGames = payoff
rand_6x7_GameTheory = NormalFormGame(payoff)
rand_6x7_nash = nash.Game(payoff[:,:,1], payoff[:,:,2])
rand_6x7_gambit = py"""setGambitGame2pInt"""(payoff[:,:,1],payoff[:,:,2])
eqs = nash_cp(rand_6x7_StrategicGames)
neqs = 0
res = @binfo nash_cp($rand_6x7_StrategicGames,verbosity=NONE)
push!(bms,[game_name,"StrategicGames","nash_cp",res...,neqs,""])
eqs = nash_se(rand_6x7_StrategicGames,max_samples=Inf)
neqs = length(eqs)
res = @binfo nash_se($rand_6x7_StrategicGames,max_samples=Inf)
push!(bms,[game_name,"StrategicGames","nash_se",res...,neqs,""])
eqs = hc_solve(rand_6x7_GameTheory)
neqs = length(eqs)
res = @binfo hc_solve($rand_6x7_GameTheory)
push!(bms,[game_name,"GameTheory","hc_solve",res..., neqs,""])
eqs = support_enumeration(rand_6x7_GameTheory)
neqs = length(eqs)
res = @binfo support_enumeration($rand_6x7_GameTheory)
push!(bms,[game_name,"GameTheory","support_enumeration",res..., neqs,""])
eqs = lrsnash(rand_6x7_GameTheory)
neqs = length(eqs)
res = @binfo lrsnash($rand_6x7_GameTheory)
push!(bms,[game_name,"GameTheory","lrsnash",res..., neqs,""])
eqs_gen = rand_6x7_nash.vertex_enumeration(); eqs = [eq for eq in eqs_gen]
neqs= length(eqs)
res = @binfo begin eqs = $rand_6x7_nash.vertex_enumeration(); [eq for eq in eqs] end
res = (res[1], missing, missing)
push!(bms,[game_name,"nashpy","vertex_enumeration",res...,neqs,""])
eqs_gen = rand_6x7_nash.lemke_howson_enumeration(); eqs = [eq for eq in eqs_gen]
neqs= length(eqs)
res = @binfo begin eqs = $rand_6x7_nash.lemke_howson_enumeration(); [eq for eq in eqs] end
res = (res[1], missing, missing)
push!(bms,[game_name,"nashpy","lemke_howson_enumeration",res...,neqs,"repeated results"])
eqs_gen = rand_6x7_nash.support_enumeration(); eqs = [eq for eq in eqs_gen]
neqs= length(eqs)
res = @binfo begin eqs = $rand_6x7_nash.support_enumeration(); [eq for eq in eqs] end
res = (res[1], missing, missing)
push!(bms,[game_name,"nashpy","support_enumeration",res...,neqs,""])
CSV.write("bms.csv",bms)
eqs = pygambit.nash.lcp_solve(rand_6x7_gambit)
neqs= length(eqs)
res = @binfo pygambit.nash.lcp_solve(rand_6x7_gambit)
res = (res[1], missing, missing)
push!(bms,[game_name,"pygambit","lcp_solve",res...,neqs,""])
solver = pygambit.nash.ExternalEnumPolySolver()
eqs = solver.solve(rand_6x7_gambit) # takes a while !!!!
neqs= length(eqs)
#res = @binfo solver.solve(rand_6x7_gambit) # takes even more !
#res = (res[1], missing, missing)
res = (5.8840781273e11, missing, missing) # swap comments to run the test, takes ~ 2 hours on a good laptop
push!(bms,[game_name,"pygambit","ExternalEnumPolySolver",res...,neqs,""])
CSV.write("bms.csv",bms)
# ------------------------------------------------------------------------------
# Test 3 - rand decimal 6x5 game
game_name = "rand_dec_6x5"
# Note that I can't get Gambit working with decimal data, not even expressed as rational:
# This would both result in "TypeError: payoff argument should be a numeric type instance"
# g = pygambit.Game.from_arrays(np.array([[11/10,21/10,31/10],[41/10,51/10,61/10]], dtype = pygambit.Rational),np.array([[101/100,201/100,301/100],[401/100,501/100,601/600]], dtype = pygambit.Rational))
# g = pygambit.Game.from_arrays(np.array([[1.1,2.1,3.1],[4.1,5.1,6.1]], dtype = pygambit.Decimal),np.array([[10.1,20.1,30.1],[40.1,50.1,60.1]], dtype = pygambit.Decimal))
#payoff = rand(6,5,2)
p1 = [
0.843789 0.0777291 0.0265584 0.664203 0.716576
0.399443 0.356958 0.54122 0.817734 0.22748
0.346581 0.632591 0.712136 0.250977 0.797303
0.315566 0.861972 0.089729 0.801083 0.386999
0.895148 0.279619 0.83699 0.844866 0.871585
0.0835494 0.647902 0.0942865 0.405726 0.542989]
p2 = [
0.443203 0.810953 0.904374 0.270971 0.293723
0.527435 0.72811 0.4115 0.496543 0.453296
0.689995 0.612925 0.201368 0.578151 0.572826
0.0396185 0.722874 0.486394 0.100332 0.527595
0.0671089 0.318471 0.968878 0.0495921 0.803702
0.207152 0.848768 0.445008 0.293703 0.239207
]
payoff = cat(p1,p2,dims=3)
rand_dec_6x5_StrategicGames = payoff
rand_dec_6x5_GameTheory = NormalFormGame(payoff)
rand_dec_6x5_GameTheory_rat = NormalFormGame(Rational.(payoff))
rand_dec_6x5_nash = nash.Game(payoff[:,:,1], payoff[:,:,2])
eqs = nash_cp(rand_dec_6x5_StrategicGames)
neqs = 1
res = @binfo nash_cp($rand_dec_6x5_StrategicGames,verbosity=NONE)
push!(bms,[game_name,"StrategicGames","nash_cp",res...,neqs,""])
eqs = nash_se(rand_dec_6x5_StrategicGames,max_samples=Inf)
neqs = length(eqs)
res = @binfo nash_se($rand_dec_6x5_StrategicGames,max_samples=Inf)
push!(bms,[game_name,"StrategicGames","nash_se",res...,neqs,""])
eqs = hc_solve(rand_dec_6x5_GameTheory)
neqs = length(eqs)
res = @binfo hc_solve($rand_dec_6x5_GameTheory)
push!(bms,[game_name,"GameTheory","hc_solve",res..., neqs,""])
eqs = support_enumeration(rand_dec_6x5_GameTheory)
neqs = length(eqs)
res = @binfo support_enumeration($rand_dec_6x5_GameTheory)
push!(bms,[game_name,"GameTheory","support_enumeration",res..., neqs,""])
eqs = lrsnash(rand_dec_6x5_GameTheory_rat)
neqs = length(eqs)
res = @binfo lrsnash($rand_dec_6x5_GameTheory_rat)
push!(bms,[game_name,"GameTheory","lrsnash",res..., neqs,""])
eqs_gen = rand_dec_6x5_nash.vertex_enumeration(); eqs = [eq for eq in eqs_gen]
neqs= length(eqs)
res = @binfo begin eqs = $rand_dec_6x5_nash.vertex_enumeration(); [eq for eq in eqs] end
res = (res[1], missing, missing)
push!(bms,[game_name,"nashpy","vertex_enumeration",res...,neqs,""])
eqs_gen = rand_dec_6x5_nash.lemke_howson_enumeration(); eqs = [eq for eq in eqs_gen]
neqs= length(eqs)
res = @binfo begin eqs = $rand_dec_6x5_nash.lemke_howson_enumeration(); [eq for eq in eqs] end
res = (res[1], missing, missing)
push!(bms,[game_name,"nashpy","lemke_howson_enumeration",res...,neqs,"repeated results"])
eqs_gen = rand_dec_6x5_nash.support_enumeration(); eqs = [eq for eq in eqs_gen]
neqs= length(eqs)
res = @binfo begin eqs = $rand_dec_6x5_nash.support_enumeration(); [eq for eq in eqs] end
res = (res[1], missing, missing)
push!(bms,[game_name,"nashpy","support_enumeration",res...,neqs,""])
CSV.write("bms.csv",bms)
# ------------------------------------------------------------------------------
# Test 4 - rand 4x4x2 game
game_name = "rand_4x4x2"
#payoff = rand(1:1000,4,4,2,3)
p1 = [656 207 580 548; 208 337 496 805; 640 422 152 691; 89 183 56 167;;; 44 789 965 925; 917 475 148 990; 78 563 732 25; 424 110 965 431]
p2 = [955 92 480 205; 436 135 802 301; 206 316 346 699; 912 470 317 787;;; 207 536 967 212; 990 335 573 61; 865 455 698 356; 200 141 978 848]
p3 = [364 963 199 81; 332 994 362 972; 421 780 852 150; 72 308 723 828;;; 737 785 653 960; 389 791 125 709; 421 483 10 404; 552 622 161 810]
payoff = cat(p1,p2,p3,dims=4)
rand_4x4x2_StrategicGames = payoff
rand_4x4x2_GameTheory = NormalFormGame(payoff)
rand_4x4x2_gambit = py"""setGambitGame3pInt"""(payoff[:,:,:,1],payoff[:,:,:,2],payoff[:,:,:,3])
eqs = nash_cp(rand_4x4x2_StrategicGames)
neqs = 0
res = @binfo nash_cp($rand_4x4x2_StrategicGames,verbosity=NONE)
push!(bms,[game_name,"StrategicGames","nash_cp",res...,neqs,""])
eqs = nash_se(rand_4x4x2_StrategicGames,max_samples=Inf)
neqs = length(eqs)
res = @binfo nash_se($rand_4x4x2_StrategicGames,max_samples=Inf)
push!(bms,[game_name,"StrategicGames","nash_se",res...,neqs,"1 eq repeated"])
eqs = hc_solve(rand_4x4x2_GameTheory)
neqs = length(eqs)
res = @binfo hc_solve($rand_4x4x2_GameTheory)
push!(bms,[game_name,"GameTheory","hc_solve",res..., neqs,"2 eq missing"])
CSV.write("bms.csv",bms)
solver = pygambit.nash.ExternalEnumPolySolver()
eqs = solver.solve(rand_4x4x2_gambit)
neqs= length(eqs)
res = @binfo solver.solve(rand_4x4x2_gambit)
res = (res[1], missing, missing)
push!(bms,[game_name,"pygambit","ExternalEnumPolySolver",res...,neqs,"1 eq missed"])
CSV.write("bms.csv",bms)
# s = [[0.5531496062992137, 0.0, 0.0, 0.4468503937007864], [0.0, 0.0, 1.0, 0.0], [-9.755303440999721e-15, 1.0000000000000098]]
# StrategicGames.is_nash(payoff,s)
# ------------------------------------------------------------------------------
# Test 5 - mid rand 6x7 game first solution only
game_name = "rand_6x7_1st_eq"
#payoff = rand(1:1000,6,7,2)
p1 = [
253 646 641 395 258 153 375
713 17 145 582 338 258 145
174 265 282 588 80 996 478
346 517 963 829 976 735 334
492 106 199 986 278 658 407
506 288 439 345 549 869 986]
p2 = [
296 23 932 537 515 130 679
491 49 315 432 977 799 777
284 761 914 268 313 864 25
75 944 444 209 804 452 502
869 837 950 707 755 452 9
579 794 747 272 929 288 780
]
payoff = cat(p1,p2,dims=3)
rand_6x7_StrategicGames = payoff
rand_6x7_GameTheory = NormalFormGame(payoff)
rand_6x7_nash = nash.Game(payoff[:,:,1], payoff[:,:,2])
rand_6x7_gambit = py"""setGambitGame2pInt"""(payoff[:,:,1],payoff[:,:,2])
eqs = nash_se(rand_6x7_StrategicGames,max_samples=1,mt=true)
neqs = length(eqs)
res = @binfo nash_se($rand_6x7_StrategicGames,max_samples=1,mt=true)
push!(bms,[game_name,"StrategicGames","nash_se",res...,neqs,""])
eqs = hc_solve(rand_6x7_GameTheory,ntofind=1)
neqs = length(eqs)
res = @binfo hc_solve($rand_6x7_GameTheory,ntofind=1)
push!(bms,[game_name,"GameTheory","hc_solve",res..., neqs,""])
eqs_gen = rand_6x7_nash.vertex_enumeration(); eqs = py"next($eqs_gen)"
neqs= 1
res = @binfo begin eqs = $rand_6x7_nash.vertex_enumeration(); py"next($eqs)" end
res = (res[1], missing, missing)
push!(bms,[game_name,"nashpy","vertex_enumeration",res...,neqs,""])
eqs_gen = rand_6x7_nash.lemke_howson_enumeration(); eqs = py"next($eqs_gen)"
neqs= 1
res = @binfo begin eqs = $rand_6x7_nash.lemke_howson_enumeration(); py"next($eqs)" end
res = (res[1], missing, missing)
push!(bms,[game_name,"nashpy","lemke_howson_enumeration",res...,neqs,""])
eqs_gen = rand_6x7_nash.support_enumeration();
# eqs = py"next($eqs_gen)"
neqs= 0
res = @binfo begin eqs = $rand_6x7_nash.support_enumeration(); end
res = (res[1], missing, missing)
push!(bms,[game_name,"nashpy","support_enumeration",res...,neqs,"no eq reported"])
CSV.write("bms.csv",bms)
# ------------------------------------------------------------------------------
# Test 6 - degenerated 3x2 game
game_name = "degenerated_3x2"
u = [(3,3) (3,3);
(2,2) (5,6);
(0,3) (6,1)]
payoff = expand_dimensions(u)
degenerated_3x2_StrategicGames = payoff
degenerated_3x2_GameTheory = NormalFormGame(payoff)
degenerated_3x2_nash = nash.Game(payoff[:,:,1], payoff[:,:,2])
degenerated_3x2_gambit = py"""setGambitGame2pInt"""(payoff[:,:,1],payoff[:,:,2])
eqs = nash_cp(degenerated_3x2_StrategicGames,verbosity=NONE)
neqs = 1
res = @binfo nash_cp($degenerated_3x2_StrategicGames,verbosity=NONE)
push!(bms,[game_name,"StrategicGames","nash_cp",res...,neqs,""])
eqs = nash_se(degenerated_3x2_StrategicGames,max_samples=Inf, mt=true)
neqs = length(eqs)
res = @binfo nash_se($degenerated_3x2_StrategicGames,max_samples=Inf)
push!(bms,[game_name,"StrategicGames","nash_se",res...,neqs,""])
eqs = hc_solve(degenerated_3x2_GameTheory)
neqs = length(eqs)
res = @binfo hc_solve($degenerated_3x2_GameTheory)
push!(bms,[game_name,"GameTheory","hc_solve",res..., neqs,""])
eqs = support_enumeration(degenerated_3x2_GameTheory)
neqs = length(eqs)
res = @binfo support_enumeration($degenerated_3x2_GameTheory)
push!(bms,[game_name,"GameTheory","support_enumeration",res..., neqs,""])
eqs = lrsnash(degenerated_3x2_GameTheory)
neqs = length(eqs)
res = @binfo lrsnash($degenerated_3x2_GameTheory)
push!(bms,[game_name,"GameTheory","lrsnash",res..., neqs,""])
eqs_gen = degenerated_3x2_nash.vertex_enumeration(); eqs = [eq for eq in eqs_gen]
neqs= length(eqs)
res = @binfo begin eqs = $degenerated_3x2_nash.vertex_enumeration(); [eq for eq in eqs] end
res = (res[1], missing, missing)
push!(bms,[game_name,"nashpy","vertex_enumeration",res...,neqs,""])
eqs_gen = degenerated_3x2_nash.lemke_howson_enumeration(); eqs = [eq for eq in eqs_gen]
neqs= length(eqs)
res = @binfo begin eqs = $degenerated_3x2_nash.lemke_howson_enumeration(); [eq for eq in eqs] end
res = (res[1], missing, missing)
push!(bms,[game_name,"nashpy","lemke_howson_enumeration",res...,neqs,"2 repeated results"])
eqs_gen = degenerated_3x2_nash.support_enumeration(); eqs = [eq for eq in eqs_gen]
neqs= length(eqs)
res = @binfo begin eqs = $degenerated_3x2_nash.support_enumeration(); [eq for eq in eqs] end
res = (res[1], missing, missing)
push!(bms,[game_name,"nashpy","support_enumeration",res...,neqs,""])
eqs = pygambit.nash.lcp_solve(degenerated_3x2_gambit)
neqs= length(eqs)
res = @binfo pygambit.nash.lcp_solve(degenerated_3x2_gambit)
res = (res[1], missing, missing)
push!(bms,[game_name,"pygambit","lcp_solve",res...,neqs,""])
solver = pygambit.nash.ExternalEnumPolySolver()
eqs = solver.solve(degenerated_3x2_gambit)
neqs= length(eqs)
res = @binfo solver.solve(degenerated_3x2_gambit)
res = (res[1], missing, missing)
push!(bms,[game_name,"pygambit","ExternalEnumPolySolver",res...,neqs,""])
CSV.write("bms.csv",bms)