isoron/multirow
Archived
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Add benchmark script and instances

Browse Source
This commit is contained in:
Alinson S. Xavier
2017-04-28 17:12:39 -04:00
parent 7098f65110
commit 43894daa81
1152 changed files with 496112 additions and 7 deletions
Download Patch File Download Diff File Expand all files Collapse all files

41
infinity/benchmark/scripts/render.sage Normal file
View File

@@ -0,0 +1,41 @@
import sys
import math
M=3
ZERO=1e-10
def angle_cmp(v):
return math.atan2(v[0], v[1])
for fname in sys.argv[1:]:
load(fname)
nrays = len(pi)
frat = f.apply_map(lambda x : x.nearby_rational(max_denominator=1000))
vertices = [(f+R[i]/pi[i]).apply_map(lambda x: x.nearby_rational(max_denominator=1000)) for i in range(nrays)]
poly = Polyhedron(vertices=vertices)
print "Writing %s.tex..." % fname
texfile = open("%s.tex" % fname, "w")
texfile.write("\\draw[fill,fill opacity=0.1] ")
for v in sorted(poly.vertices(), key=angle_cmp):
texfile.write("(%s, %s) -- " % (v[0], v[1]))
texfile.write("cycle;\n")
#texfile.write("\\draw (%s, %s) circle [radius=1.5pt];\n" % (frat[0], frat[1]))
for v in vertices:
texfile.write("\\draw[dashed] (%s,%s) -- (%s,%s);\n" % (frat[0], frat[1], v[0], v[1]))
texfile.close()
print "Writing %s.png..." % fname
p0 = sum([arrow(f, f + R[i] / pi[i], color='blue') for i in range(nrays)])
pf = list_plot([f], color='red', pointsize=30, zorder=-1)
p1 = poly.plot(color='blue', alpha=0.2)
p3 = list_plot(
[(x,y) for x in range(-M,M+1) for y in range(-M,M+1)],
color='black', figsize=20, pointsize=30, zorder=1)
output = "%s.png" % fname
save(p0+pf+p3+p1, output, xmin=-M, ymin=-M, xmax=M, ymax=M)

47
infinity/benchmark/scripts/render.sage.py Normal file
View File

@@ -0,0 +1,47 @@
# This file was *autogenerated* from the file scripts/render.sage
from sage.all_cmdline import * # import sage library
_sage_const_3 = Integer(3); _sage_const_1 = Integer(1); _sage_const_0 = Integer(0); _sage_const_0p2 = RealNumber('0.2'); _sage_const_1000 = Integer(1000); _sage_const_1en10 = RealNumber('1e-10'); _sage_const_30 = Integer(30); _sage_const_20 = Integer(20)
import sys
import math
M=_sage_const_3
ZERO=_sage_const_1en10
def angle_cmp(v):
return math.atan2(v[_sage_const_0 ], v[_sage_const_1 ])
for fname in sys.argv[_sage_const_1 :]:
load(fname)
nrays = len(pi)
frat = f.apply_map(lambda x : x.nearby_rational(max_denominator=_sage_const_1000 ))
vertices = [(f+R[i]/pi[i]).apply_map(lambda x: x.nearby_rational(max_denominator=_sage_const_1000 )) for i in range(nrays)]
poly = Polyhedron(vertices=vertices)
print "Writing %s.tex..." % fname
texfile = open("%s.tex" % fname, "w")
texfile.write("\\draw[fill,fill opacity=0.1] ")
for v in sorted(poly.vertices(), key=angle_cmp):
texfile.write("(%s, %s) -- " % (v[_sage_const_0 ], v[_sage_const_1 ]))
texfile.write("cycle;\n")
#texfile.write("\\draw (%s, %s) circle [radius=1.5pt];\n" % (frat[0], frat[1]))
for v in vertices:
texfile.write("\\draw[dashed] (%s,%s) -- (%s,%s);\n" % (frat[_sage_const_0 ], frat[_sage_const_1 ], v[_sage_const_0 ], v[_sage_const_1 ]))
texfile.close()
print "Writing %s.png..." % fname
p0 = sum([arrow(f, f + R[i] / pi[i], color='blue') for i in range(nrays)])
pf = list_plot([f], color='red', pointsize=_sage_const_30 , zorder=-_sage_const_1 )
p1 = poly.plot(color='blue', alpha=_sage_const_0p2 )
p3 = list_plot(
[(x,y) for x in range(-M,M+_sage_const_1 ) for y in range(-M,M+_sage_const_1 )],
color='black', figsize=_sage_const_20 , pointsize=_sage_const_30 , zorder=_sage_const_1 )
output = "%s.png" % fname
save(p0+pf+p3+p1, output, xmin=-M, ymin=-M, xmax=M, ymax=M)

110
infinity/benchmark/scripts/table-csv.rb Executable file
View File

@@ -0,0 +1,110 @@
#!/usr/bin/env ruby
require 'yaml'
def gmean(x, shift)
sum=0.0
x.each {|v| sum += Math.log(v+shift)}
sum /= x.size
Math.exp(sum)-shift
end
def mean(x)
sum=0.0
x.each {|v| sum += v}
sum /= x.size
end
data = YAML::load(File.open("data/data.yaml"))
n = 0
exact_cuts = []
exact_gaps = []
exact_times = []
greedy_cuts = []
greedy_gaps = []
greedy_times = []
mir_cuts = []
mir_gaps = []
percut_times = []
improv = []
missing = []
no_improvement = []
mir_differs = []
count = 1
print("instance,")
print("gmir,")
print("ginfty,")
print("gexact,")
print("improv,")
print("ttotal,")
print("tpercut,")
print("ncuts")
print("\n")
Dir[ARGV[0] + "*yaml"].sort.each do |f|
yaml = YAML::load(File.open(f))
instance = yaml['input-filename'].gsub("instances/", "").gsub(".pre.mps.gz", "")
d = data[instance]
obj_lp = yaml['obj-value'][0]
obj_ip = d['ip']
gap_pi = d[ARGV[1]]
obj_mir = yaml['obj-value'][1]
obj_greedy = yaml['obj-value'][2]
gap_mir = (obj_mir - obj_lp) / (obj_ip - obj_lp) * 100
gap_greedy = (obj_greedy - obj_lp) / (obj_ip - obj_lp) * 100
#gap_pi = [gap_pi, gap_greedy].max
improv_greedy = (gap_greedy - gap_mir) / (gap_pi - gap_mir) * 100
improv_greedy = 0 if improv_greedy.abs < 0.01
if (gap_mir - d['gmi']).abs > 1
mir_differs.push([instance, gap_mir, d['gmi']])
end
begin
time_percut = yaml['time-per-cut'][2] * 1000
rescue NoMethodError
time_percut = 0.0
end
percut_times.push(time_percut)
mir_gaps.push(gap_mir)
greedy_gaps.push(gap_greedy)
exact_gaps.push(gap_pi)
improv.push(improv_greedy)
print("%s," % instance.gsub("_", "\\_"))
print("%.1f," % (gap_mir))
print("%.1f," % (gap_greedy))
print("%.1f," % (gap_pi))
if (gap_pi - gap_mir).abs > 0.01
print("%.1f," % (improv_greedy))
else
print("%s," % "---")
end
print("%d:%02d," % [yaml['user-cpu-time'][2] / 60, yaml['user-cpu-time'][2] % 60])
print("%d ms," % (time_percut))
print("%d" % (yaml['added-cuts'][2]))
print("\n")
count += 1
end
mean_exact = mean(exact_gaps)
mean_greedy = mean(greedy_gaps)
mean_mir = mean(mir_gaps)
#print("\n%22s" % "")
#print("%8.2f%% " % mean_mir)
#print("%8.2f%% " % mean_greedy)
#print("%8.2f%% " % mean_exact)

168
infinity/benchmark/scripts/table.rb Executable file
View File

@@ -0,0 +1,168 @@
#!/usr/bin/env ruby
require 'yaml'
def gmean(x, shift)
sum=0.0
x.each {|v| sum += Math.log(v+shift)}
sum /= x.size
Math.exp(sum)-shift
end
def mean(x)
sum=0.0
x.each {|v| sum += v}
sum /= x.size
end
data = YAML::load(File.open("data/data.yaml"))
n = 0
exact_cuts = []
exact_gaps = []
exact_times = []
greedy_cuts = []
greedy_gaps = []
greedy_times = []
mir_cuts = []
mir_gaps = []
percut_times = []
improv = []
missing = []
no_improvement = []
mir_differs = []
count = 1
print("%4s " % "")
print("%16s " % "instance")
print("%9s " % "g-mir")
print("%9s " % "g-infty")
print("%9s " % "g-exact")
print("%9s " % "improv")
print("%9s " % "t-total")
print("%9s " % "t-per-cut")
print("%6s " % "n-cuts")
print("\n")
Dir[ARGV[0] + "*yaml"].sort.each do |f|
yaml = YAML::load(File.open(f))
instance = yaml['input-filename'].gsub("instances/", "").gsub(".pre.mps.gz", "")
d = data[instance]
obj_lp = yaml['obj-value'][0]
obj_ip = d['ip']
gap_pi = d[ARGV[1]]
obj_mir = yaml['obj-value'][1]
obj_greedy = yaml['obj-value'][2]
gap_mir = (obj_mir - obj_lp) / (obj_ip - obj_lp) * 100
gap_greedy = (obj_greedy - obj_lp) / (obj_ip - obj_lp) * 100
#gap_pi = [gap_pi, gap_greedy].max
improv_greedy = (gap_greedy - gap_mir) / (gap_pi - gap_mir) * 100
improv_greedy = 0 if improv_greedy.abs < 0.01
if (gap_mir - d['gmi']).abs > 1
mir_differs.push([instance, gap_mir, d['gmi']])
end
begin
time_percut = yaml['time-per-cut'][2] * 1000
rescue NoMethodError
time_percut = 0.0
end
percut_times.push(time_percut)
mir_gaps.push(gap_mir)
greedy_gaps.push(gap_greedy)
exact_gaps.push(gap_pi)
improv.push(improv_greedy)
print("%4d " % count)
print("%16s " % instance)
print("%8.2f%% " % (gap_mir))
print("%8.2f%% " % (gap_greedy))
print("%8.2f%% " % (gap_pi))
if (gap_pi - gap_mir).abs > 0.01
print("%8.2f%% " % (improv_greedy))
else
print("%8s " % "---")
end
print("%6d:%02d " % [yaml['user-cpu-time'][2] / 60, yaml['user-cpu-time'][2] % 60])
print("%6d ms " % (time_percut))
print("%6d " % (yaml['added-cuts'][2]))
print("\n")
count += 1
end
mean_exact = mean(exact_gaps)
mean_greedy = mean(greedy_gaps)
mean_mir = mean(mir_gaps)
#ncuts_exact = gmean(exact_cuts, 10)
#ncuts_greedy = gmean(greedy_cuts, 10)
#ncuts_mir = gmean(mir_cuts, 10)
#
#time_exact = gmean(exact_times, 5)
#time_greedy = gmean(greedy_times, 5)
#time_percut = gmean(percut_times, 5)
#
print("\n%22s" % "")
print("%8.2f%% " % mean_mir)
print("%8.2f%% " % mean_greedy)
print("%8.2f%% " % mean_exact)
#print("%8.1f%% " % mean(improv))
#print(" %8d " % ncuts_mir)
#print("%8d " % ncuts_greedy)
#print("%8d " % ncuts_exact)
#print("%4d:%02d " % [time_greedy / 60, time_greedy % 60])
#print("%4d:%02d " % [time_exact / 60, time_exact % 60])
#print(" %4.0f ms" % time_percut)
print("\n")
#print("%30s" % "")
#print("%5.1f%% " % ((mean_greedy / mean_mir - 1) * 100))
#print("%5.1f%% " % ((mean_exact / mean_mir - 1) * 100))
#print("\n")
print("%34s" % "")
print("%6.2f%% " % ((mean_greedy - mean_mir) / (mean_exact - mean_mir) * 100))
print("\n")
if missing.size > 0
print("Missing data:\n")
missing.each do |m|
print(" %s\n" % m)
end
end
#if mir_differs.size > 0
# print("MIR differs:\n")
# mir_differs.each do |m|
# print("%4d %16s %6.2f %6.2f\n" % [count, m[0], m[1], m[2]])
# count += 1
# end
# print("\n")
#end
print("Disabled:\n")
Dir["instances/off/*"].each do |f|
print("%4d %16s\n" % [count, f.gsub("instances/off/", "").gsub(".pre.mps.gz", "")])
count += 1
end
print("\n")
print("Error:\n")
Dir[ARGV[0] + "*.err*"].sort.each do |f|
instance = f.gsub("greedy/", "").gsub(".pre.err.", " ").split(" ")
print("%4d %-30s %4d\n" % [count, instance[0], instance[1]])
count += 1
end

76
infinity/benchmark/scripts/time.rb Executable file
View File

@@ -0,0 +1,76 @@
#!/usr/bin/env ruby
require 'yaml'
def gmean(x, shift)
sum=0.0
x.each {|v| sum += Math.log(v+shift)}
sum /= x.size
Math.exp(sum)-shift
end
def mean(x)
sum=0.0
x.each {|v| sum += v}
sum /= x.size
end
mip_values = YAML::load(File.open("mip-value.yaml"))
n = 0
times = []
mir_gaps = []
greedy_gaps = []
i=1
ARGV.each do |f|
yaml = YAML::load(File.open(f))
instance = yaml['input-filename'].gsub("instances/", "").gsub(".pre.mps.gz", "")
time_greedy = yaml['user-cpu-time'][2]
times.push(time_greedy)
mip_value = mip_values[instance]
lp_value = yaml['obj-value'][0]
mir_value = yaml['obj-value'][1]
greedy_value = yaml['obj-value'][2]
next if lp_value == mip_value
mir_gap = (mir_value - lp_value) / (mip_value - lp_value)
greedy_gap = (greedy_value - lp_value) / (mip_value - lp_value)
mir_ncuts = yaml['added-cuts'][1]
greedy_ncuts = yaml['added-cuts'][2]
mir_gaps.push(mir_gap)
greedy_gaps.push(greedy_gap)
print("%20s " % instance)
print("%14.2f " % lp_value)
print("%14.2f " % mip_value)
print("| %14.2f " % mir_value)
print("%14.2f " % greedy_value)
print("| %5.1f%% " % (mir_gap * 100))
print("%5.1f%% " % (greedy_gap * 100))
print("| %8d " % mir_ncuts)
print("%8d " % greedy_ncuts)
print("| %4d:%02d " % [yaml['user-cpu-time'][2] / 60, yaml['user-cpu-time'][2] % 60])
print("\n")
i += 1
end
greedy_gap = mean(greedy_gaps) * 100
mir_gap = mean(mir_gaps) * 100
time_greedy = gmean(times, 10)
print("\n%85s" % "")
print("%5.1f%% " % mir_gap)
print("%5.1f%% " % greedy_gap)
print("%21s %4d:%02d" % ["", time_greedy / 60, time_greedy % 60])
print("\n%92s" % "")
print("%5.1f%% " % ((greedy_gap / mir_gap - 1) * 100))
print("\n")