|
1
|
|
|
# Author: Simon Blanke |
|
2
|
|
|
# Email: [email protected] |
|
3
|
|
|
# License: MIT License |
|
4
|
|
|
|
|
5
|
|
|
import numpy as np |
|
6
|
|
|
|
|
7
|
|
|
from ..search_space import SearchSpace |
|
8
|
|
|
from ..model import Model |
|
9
|
|
|
from ..init_position import InitSearchPosition |
|
10
|
|
|
|
|
11
|
|
|
|
|
12
|
|
|
class Candidate: |
|
13
|
|
|
def __init__( |
|
14
|
|
|
self, obj_func, func_para, search_space, init_para, memory, verb, hyperactive |
|
15
|
|
|
): |
|
16
|
|
|
self.obj_func = obj_func |
|
17
|
|
|
self.func_para = func_para |
|
18
|
|
|
self.search_space = search_space |
|
19
|
|
|
self.memory = memory |
|
20
|
|
|
self.verb = verb |
|
21
|
|
|
|
|
22
|
|
|
self.space = SearchSpace(search_space, verb) |
|
23
|
|
|
self.model = Model(obj_func, func_para, verb, hyperactive) |
|
24
|
|
|
self.init = InitSearchPosition(init_para, self.space, verb) |
|
25
|
|
|
|
|
26
|
|
|
self.memory_dict = {} |
|
27
|
|
|
self.memory_dict_new = {} |
|
28
|
|
|
|
|
29
|
|
|
self._score = -np.inf |
|
30
|
|
|
self._pos = None |
|
31
|
|
|
|
|
32
|
|
|
self.score_best = -np.inf |
|
33
|
|
|
self.pos_best = None |
|
34
|
|
|
self.para_best = None |
|
35
|
|
|
|
|
36
|
|
|
self.score_list = [] |
|
37
|
|
|
self.pos_list = [] |
|
38
|
|
|
|
|
39
|
|
|
self.eval_times = [] |
|
40
|
|
|
self.iter_times = [] |
|
41
|
|
|
|
|
42
|
|
|
if not memory: |
|
43
|
|
|
self.mem = None |
|
44
|
|
|
self.eval_pos = self.eval_pos_noMem |
|
45
|
|
|
else: |
|
46
|
|
|
self.mem = None |
|
47
|
|
|
self.eval_pos = self.eval_pos_Mem |
|
48
|
|
|
|
|
49
|
|
|
@property |
|
50
|
|
|
def score(self): |
|
51
|
|
|
return self._score |
|
52
|
|
|
|
|
53
|
|
|
@score.setter |
|
54
|
|
|
def score(self, value): |
|
55
|
|
|
self.score_list.append(value) |
|
56
|
|
|
self._score = value |
|
57
|
|
|
|
|
58
|
|
|
@property |
|
59
|
|
|
def pos(self): |
|
60
|
|
|
return self._score |
|
61
|
|
|
|
|
62
|
|
|
@pos.setter |
|
63
|
|
|
def pos(self, value): |
|
64
|
|
|
self.pos_list.append(value) |
|
65
|
|
|
self._pos = value |
|
66
|
|
|
|
|
67
|
|
|
def base_eval(self, pos, nth_iter): |
|
68
|
|
|
para = self.space.pos2para(pos) |
|
69
|
|
|
results = self.model.eval(para) |
|
70
|
|
|
|
|
71
|
|
|
if results["score"] > self.score_best: |
|
72
|
|
|
self.score_best = results["score"] |
|
73
|
|
|
self.pos_best = pos |
|
74
|
|
|
self.para_best = para |
|
75
|
|
|
|
|
76
|
|
|
self.verb.p_bar.best_since_iter = nth_iter |
|
77
|
|
|
|
|
78
|
|
|
return results |
|
79
|
|
|
|
|
80
|
|
|
def eval_pos_noMem(self, pos, nth_iter): |
|
81
|
|
|
results = self.base_eval(pos, nth_iter) |
|
82
|
|
|
return results["score"] |
|
83
|
|
|
|
|
84
|
|
|
def eval_pos_Mem(self, pos, nth_iter, force_eval=False): |
|
85
|
|
|
pos.astype(int) |
|
86
|
|
|
pos_tuple = tuple(pos) |
|
87
|
|
|
|
|
88
|
|
|
if pos_tuple in self.memory_dict and not force_eval: |
|
89
|
|
|
return self.memory_dict[pos_tuple]["score"] |
|
90
|
|
|
else: |
|
91
|
|
|
results = self.base_eval(pos, nth_iter) |
|
92
|
|
|
self.memory_dict[pos_tuple] = results |
|
93
|
|
|
self.memory_dict_new[pos_tuple] = results |
|
94
|
|
|
|
|
95
|
|
|
return results["score"] |
|
96
|
|
|
|
|
97
|
|
|
def get_score(self, pos_new, nth_iter): |
|
98
|
|
|
score_new = self.eval_pos(pos_new, nth_iter) |
|
99
|
|
|
self.verb.p_bar.update_p_bar(1, self.score_best) |
|
100
|
|
|
|
|
101
|
|
|
if score_new > self.score_best: |
|
102
|
|
|
self.score = score_new |
|
103
|
|
|
self.pos = pos_new |
|
104
|
|
|
|
|
105
|
|
|
return score_new |
|
106
|
|
|
|
SimonBlanke /
Hyperactive
