-
Notifications
You must be signed in to change notification settings - Fork 3
/
Copy pathjoes_charter.py
executable file
·196 lines (183 loc) · 9 KB
/
joes_charter.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
from pylab import *
import csv
#from jmoo_problems import *
#from jmoo_algorithms import *
from jmoo_properties import *
from utility import *
fignum = 0
data = []
heads = []
best = []
foam = []
RRS_scores = []
RRS = []
for p,prob in enumerate(problems):
data.append([])
heads.append([])
best.append([])
foam.append([])
RRS.append([])
RRS_scores.append([])
for a,alg in enumerate(algorithms):
finput = open("Data/results_" + prob.name + "-p" + str(MU) + "-d" + str(len(prob.decisions)) + "-o" + str(len(prob.objectives)) + "_" + alg.name + ".datatable", 'rb')
f2input = open(DATA_PREFIX + RRS_TABLE + "_" + prob.name + "-p" + str(MU) + "-d" + str(len(prob.decisions)) + "-o" + str(len(prob.objectives)) + "_" + alg.name + DATA_SUFFIX, 'rb')
reader = csv.reader(finput, delimiter=',')
reader2 = csv.reader(f2input, delimiter=',')
data[p].append( [] )
heads[p].append( [] )
best[p].append( [] )
foam[p].append( [] )
RRS[p].append( [] )
RRS_scores[p].append( [] )
for o,obj in enumerate(prob.objectives):
foam[p][a].append([])
foam[p][a][o] = {}
RRS[p][a].append([])
RRS[p][a][o] = {}
for i,row in enumerate(reader2):
for j,col in enumerate(row):
if i == 0:
print col
RRS_scores[p][a].append([float(col.strip("%)( "))])
else:
RRS_scores[p][a][j].append(float(col.strip("%)( ")))
for o,obj in enumerate(prob.objectives):
n = RRS_scores[p][a][-1][-1]
n = (int(round(n/5.0)*5.0))
if n in RRS[p][a][o]: RRS[p][a][o][n].append(float(RRS_scores[p][a][o][-1]))
else: RRS[p][a][o][n] = [float(RRS_scores[p][a][o][-1])]
for i,row in enumerate(reader):
if not str(row[0]) == "0":
for j,col in enumerate(row):
if i == 0:
heads[p][a].append(col)
data[p][a].append([])
best[p][a].append(999999)
else:
if not col == "":
data[p][a][j].append(float(col.strip("%)(")))
if data[p][a][j][-1] < best[p][a][j]: best[p][a][j] = data[p][a][j][-1]
# row is now read
if i > 0:
for o,obj in enumerate(prob.objectives):
n = data[p][a][0][-1]
n = (int(round(n/20.0)*20.0))
if n in foam[p][a][o]: foam[p][a][o][n].append(float(data[p][a][o*3+2][-1]))
else: foam[p][a][o][n] = [float(data[p][a][o*3+2][-1])]
# all rows read
# Interpolate foam keys
for doit in range(5):
for o,obj in enumerate(prob.objectives):
keys = sorted(foam[p][a][o].keys())
for key,nextkey in zip(keys[0:-1], keys[1:]):
foam[p][a][o][(nextkey-key)/2 + key] = foam[p][a][o][key]
keys = sorted(foam[p][a][o].keys())
"""
if alg.name == "GALE":
skips = 5
dur = 20000
else:
skips = 100
dur = 20000
for o,obj in enumerate(prob.objectives):
for n in range(0, dur):
nk = (int(round(n/float(skips))*float(skips)))
if nk >= dur: nk = dur - skips
nk1 = nk
nk2 = nk
while len(foam[p][a][o][n]) == 0: # and (nk1 < dur or nk2 >= 0):
if nk1 < dur and len(foam[p][a][o][n]) == 0 and len(foam[p][a][o][nk1]) > 0:
for na in range(n, nk1):
foam[p][a][o][na].append(min(foam[p][a][o][nk1]) if obj.lismore else max(foam[p][a][o][nk1]))
if nk2 >= 0 and len(foam[p][a][o][n]) == 0 and len(foam[p][a][o][nk2]) > 0:
for na in range(nk2+1, n+1):
foam[p][a][o][na].append(min(foam[p][a][o][nk2]) if obj.lismore else max(foam[p][a][o][nk2]))
nk1 = nk1 + skips
#nk1 = (int(round(nk1/float(5.0))*float(5.0)))
nk2 = nk2 - skips
#nk2 = (int(round(nk2/float(5.0))*float(5.0)))
for n in range(0, 20000):
# print n, len(foam[p][a][o][n])
if len(foam[p][a][o][n]) == 0: foam[p][a][o][n].append(prob.referencePoint[o])
"""
fignum = 0
colors = ['r', 'b', 'g']
from matplotlib.font_manager import FontProperties
font = {'family' : 'sans-serif',
'weight' : 'normal',
'size' : 8}
matplotlib.rc('font', **font)
fontP = FontProperties()
fontP.set_size('x-small')
codes = ["rx", "b+", "g1"]
codes2= ["r-", "b-", "g-"]
colors= ["r", "b", "g"]
symbols=["x", "+", "1"]
line = "-"
dotted= "--"
algnames = [alg.name for alg in algorithms]
axy = [0,1,2,3]
axx = [0,0,0,0]
f, axarr = plt.subplots(max(2,max([len(prob.objectives) for prob in problems])), max(2,len(problems)))
for p,prob in enumerate(problems):
for o,obj in enumerate(prob.objectives):
maximum = -9999999.9
minimum = +9999999.9
if not o == 112:
o_o = o
if o > 4:
o_o = o - 1
for a,alg in enumerate(algorithms):
maximum = max(max(data[p][a][o*3+2]), maximum)
minimum = min(min(data[p][a][o*3+2]), minimum)
for a,alg in enumerate(algorithms):
if o == 0:
axarr[o_o][p].set_title(prob.name)
if p == 0:
axarr[o_o][p].set_ylabel(prob.objectives[o].name, rotation=90)
#axarr[o_o][p].plot([x for x in range(0,10000,10)], [100 for x in range(0,10000,10)], 'k-', [int(round(x/5.0)*5.0) for x in Data[p][a][0]], Data[p][a][o*3+2], codes[a],label=alg.name, markersize=1)
#axarr[o_o][p].plot([x for x in range(0,10000,10)], [best[p][a][o*3+2] for x in range(0,10000,10)], colors[a]+dotted, markersize=1)
#axarr[o_o][p].plot([x for x in Data[p][a][0]], [best[p][a][o*3+2] for x in Data[p][a][0]], codes2[a])
#axarr[o_o][p].plot([x for x in range(0,10000,10)], [100 for x in range(0,10000,10)], 'k-', [key for key in RRS[p][a][o].keys()], [getPercentile(RRS[p][a][o], 25), getPercentile(RRS[p][a][o], 50), getPercentile(RRS[p][a][o], 75)], codes[a],label=alg.name, markersize=4)
X = []
Y = []
for key in RRS[p][a][o]:
#print key, getPercentile(RRS[p][a][o][key], 25), getPercentile(RRS[p][a][o][key], 50), getPercentile(RRS[p][a][o][key], 75)
X += [key, key, key]
Y += [getPercentile(RRS[p][a][o][key], 25), getPercentile(RRS[p][a][o][key], 50), getPercentile(RRS[p][a][o][key], 75)]
for r in range(len(X)/3):
axarr[o_o][p].plot(X[r*3:(r+1)*3], Y[r*3:(r+1)*3], codes2[a],label=alg.name, markersize=1)
for r in range(3):
axarr[o_o][p].plot([X[(k)*3+r] for k in range(len(X)/3)], [Y[(k)*3+r] for k in range(len(X)/3)], colors[a]+["_", "o", "_"][r % 3],label=alg.name, markersize=[8, 3, 8][r])
axarr[o_o][p].plot([x for x in range(0,10000,10)], [100 for x in range(0,10000,10)], 'k-')
#axarr[o_o][p].plot([key for key in sorted(foam[p][a][o].keys())], [min(foam[p][a][o][key]) for key in sorted(foam[p][a][o].keys())], colors[a]+"-", markersize=1)
axarr[o_o][p].set_autoscale_on(False)
axarr[o_o][p].set_xlim([0, 10000])
axarr[o_o][p].set_xscale('log')
if maximum > 1000: axarr[o_o][p].set_yscale('log')
f.set_size_inches(2.75*4, 2.75*3)
"""
if obj.name == "Cost":
axarr[o_o][p].set_ylim([-10, 210])
elif obj.name == "Completion":
axarr[o_o][p].set_ylim([50, 150])
elif obj.name == "Idle":
axarr[o_o][p].set_ylim([-10, 210])
elif obj.name == "Score":
axarr[o_o][p].set_ylim([-10, 140])
else:
"""
axarr[o_o][p].set_ylim([minimum-(maximum-minimum)*0.10, maximum+(maximum-minimum)*0.10])
#if prob.name == "Viennet2":
# axarr[o_o][p].set_ylim([50, 110])
#xlabel("num evaluations")
#ylabel("% of initial")
#suptitle(prob.name, fontsize=11)
plt.subplots_adjust(top=0.85)
plt.subplots_adjust(bottom=0.15)
legend(loc='upper center', bbox_to_anchor=(-0.10, -0.10), ncol=3, prop=fontP)
#show()
fignum = len([name for name in os.listdir('Charts/' + date_folder_prefix)])
print fignum
plt.savefig('Charts/' + date_folder_prefix + '/figure' + str("%02d" % fignum) + "_" + "objectives_" + prob.name + "_" + tag + '.png', dpi=100)
cla()