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Diffstat (limited to 'src/explicitsimulation.cpp')
-rw-r--r-- | src/explicitsimulation.cpp | 139 |
1 files changed, 139 insertions, 0 deletions
diff --git a/src/explicitsimulation.cpp b/src/explicitsimulation.cpp new file mode 100644 index 0000000..281e7e5 --- /dev/null +++ b/src/explicitsimulation.cpp | |||
@@ -0,0 +1,139 @@ | |||
1 | #include "genetic/explicitsimulation.h" | ||
2 | #include "genetic/operator.h" | ||
3 | #include "genetic/fitnessfunction.h" | ||
4 | |||
5 | #include <bu/random.h> | ||
6 | #include <bu/sio.h> | ||
7 | |||
8 | using namespace Bu; | ||
9 | |||
10 | Genetic::ExplicitSimulation::ExplicitSimulation( Genetic::Operator *pOper, | ||
11 | Genetic::FitnessFunction *pFunc, int iPopSize, float fKeep, | ||
12 | float fRandom, bool bKeepBest ) : | ||
13 | pOper( pOper ), | ||
14 | pFunc( pFunc ), | ||
15 | iPopSize( iPopSize ), | ||
16 | fKeep( fKeep ), | ||
17 | fRandom( fRandom ), | ||
18 | bKeepBest( bKeepBest ) | ||
19 | { | ||
20 | for( int j = 0; j < iPopSize; j++ ) | ||
21 | { | ||
22 | xPop.addPhenotype( pOper->random() ); | ||
23 | } | ||
24 | |||
25 | updateFitness(); | ||
26 | } | ||
27 | |||
28 | Genetic::ExplicitSimulation::~ExplicitSimulation() | ||
29 | { | ||
30 | delete pOper; | ||
31 | delete pFunc; | ||
32 | } | ||
33 | |||
34 | void Genetic::ExplicitSimulation::timestep() | ||
35 | { | ||
36 | PhenotypeList lNew; | ||
37 | |||
38 | int iChildren = iPopSize*(1.0-fKeep-fRandom); | ||
39 | |||
40 | // Create children | ||
41 | for( int j = 0; j < iChildren; j++ ) | ||
42 | { | ||
43 | PhenotypeList lParents; | ||
44 | for( int k = 0; k < pOper->parentCount(); k++ ) | ||
45 | lParents.append( xPop.getPhenotype( selectWeighted() ) ); | ||
46 | lNew.append( pOper->mate( lParents ) ); | ||
47 | } | ||
48 | |||
49 | // Select phenotypes for keeping | ||
50 | int iKeep = iPopSize*fKeep; | ||
51 | FitnessHash hTempFitness; | ||
52 | for( int j = 0; j < iKeep; j++ ) | ||
53 | { | ||
54 | Genetic::PhenotypeId id = selectWeighted(); | ||
55 | lNew.append( xPop.takePhenotype( id ) ); | ||
56 | hTempFitness.insert( id, hFitness.get( id ) ); | ||
57 | hFitness.erase( id ); | ||
58 | dTotalFitness -= hTempFitness.get( id ); | ||
59 | } | ||
60 | |||
61 | if( bKeepBest && hFitness.has( uMaxFitness ) ) | ||
62 | { | ||
63 | lNew.append( xPop.takePhenotype( uMaxFitness ) ); | ||
64 | hTempFitness.insert( uMaxFitness, hFitness.get( uMaxFitness ) ); | ||
65 | hFitness.erase( uMaxFitness ); | ||
66 | dTotalFitness -= hTempFitness.get( uMaxFitness ); | ||
67 | } | ||
68 | |||
69 | // Fill in the remainder with random phenotypes | ||
70 | while( lNew.getSize() < iPopSize ) | ||
71 | { | ||
72 | lNew.append( pOper->random() ); | ||
73 | } | ||
74 | |||
75 | // Refill the population | ||
76 | hFitness = hTempFitness; | ||
77 | xPop.clear(); | ||
78 | xPop.timestep(); | ||
79 | for( PhenotypeList::iterator i = lNew.begin(); i; i++ ) | ||
80 | { | ||
81 | xPop.addPhenotype( *i ); | ||
82 | } | ||
83 | |||
84 | updateFitness(); | ||
85 | } | ||
86 | |||
87 | Genetic::PhenotypeId Genetic::ExplicitSimulation::selectWeighted() | ||
88 | { | ||
89 | double dSel = Bu::Random::randNorm()*dTotalFitness; | ||
90 | double dRun = 0.0; | ||
91 | |||
92 | for( FitnessHash::iterator i = hFitness.begin(); i; i++ ) | ||
93 | { | ||
94 | dRun += *i; | ||
95 | if( dSel < dRun ) | ||
96 | return i.getKey(); | ||
97 | } | ||
98 | |||
99 | sio << "Genetic::ExplicitSimulation::selectWeighted() - failed, picked max" | ||
100 | << sio.nl; | ||
101 | |||
102 | return uMaxFitness; | ||
103 | } | ||
104 | |||
105 | void Genetic::ExplicitSimulation::updateFitness() | ||
106 | { | ||
107 | dMinFitness = -1.0; | ||
108 | dTotalFitness = 0.0; | ||
109 | for( Population::iterator i = xPop.begin(); i; i++ ) | ||
110 | { | ||
111 | double dFitness; | ||
112 | if( hFitness.has( i.getKey() ) ) | ||
113 | { | ||
114 | dFitness = hFitness.get( i.getKey() ); | ||
115 | } | ||
116 | else | ||
117 | { | ||
118 | dFitness = (*pFunc)( *i ); | ||
119 | if( dFitness < 0.0 ) | ||
120 | dFitness = 0.0; | ||
121 | hFitness.insert( i.getKey(), dFitness ); | ||
122 | } | ||
123 | dTotalFitness += dFitness; | ||
124 | if( dMinFitness < 0.0 ) | ||
125 | { | ||
126 | dMinFitness = dMaxFitness = dFitness; | ||
127 | uMaxFitness = i.getKey(); | ||
128 | } | ||
129 | else if( dMinFitness > dFitness ) | ||
130 | { | ||
131 | dMinFitness = dFitness; | ||
132 | } | ||
133 | else if( dMaxFitness < dFitness ) | ||
134 | { | ||
135 | dMaxFitness = dFitness; | ||
136 | uMaxFitness = i.getKey(); | ||
137 | } | ||
138 | } | ||
139 | } | ||