void TargethExp()
{
var dt = DateTime.Now;
var dt_name = dt.ToString("yyyyMMddHHmm");
var seeds = new List <int>()
{
3
}; //0,1,2
double sensor_weight = 0.8; //0.8
int steps = 2000;
dt = DateTime.Now;
dt_name = dt.ToString("yyyyMMddHHmm");
//Parallel.For(0, seeds, seed =>
osm_setting = new OSMSetting(ExperimentType.AAT_LFR_Normal_Each_Exponential);
Parallel.ForEach(seeds, seed =>
{
/* リストで定義されているクラスの引数には任意個数セットできる．出力は全体の直積*/
new TargetH_Experiment()
.SetGraphs(new List <GraphEnum>()
{
GraphEnum.Grid2D, GraphEnum.BA, GraphEnum.WS
}) //グラフをセット
.SetAlgos(new List <AlgoEnum>()
{
AlgoEnum.AAT
}) //意見共有アルゴリズムをセット
.SetNetworkSize(new List <int>()
{
100, 300, 500, 1000
}) //ネットワークサイズ(ノード数)をセット
.SetDims(new List <int>()
{
2
}) //意見の種類
.SetSensorWeight(sensor_weight) //環境とセンサの間のリンクの重みをセット.これはリストじゃあない
.SetSensorSizeRate(new List <double>()
{
0.05
}) //環境情報を認識するエージェントの割合を設定
.SetMaliciousSensorSizeRate(new List <double>()
{
0.00
}) //誤った環境情報を認識するエージェントの割合を設定
//.SetSensorFixSize(10)
.SetBeliefUpdater(new BeliefUpdater(BeliefUpdateFunctionEnum.SameOpinionAdjustBayse).SetSensorWeightMode(SensorWeightEnum.DependSensorRate)) //信念値更新式
.SetSubjectName("test") //実験名？
.SetEnvDistWeights(new List <double>()
{
0.5
}) //環境からセンサエージェントへの意見の種類に関する確率分布
.SetMaliciousEnvDistWeights(new List <double>()
{
0.0
}) //誤った環境からセンサエージェントへの重みをセット
.SetCommonCuriocity(0.1) //
//.SetTargetHs(new List<double>() {0.5, 0.525, 0.55, 0.575, 0.6, 0.625, 0.65, 0.675, 0.7, 0.725, 0.75, 0.775, 0.8, 0.825, 0.85, 0.875, 0.9, 0.925, 0.95, 0.975,1 }) //目標意見形成率
.SetTargetHs(new List <double>()
{
0.9
}) //.SetTargetHs(Enumerable.Range(20, 21).Select(x => x * 0.025).ToList())
.SetLogFolder(dt_name, "gdwt_size_grid_0.95") //ログフォルダ名
.SetRounds(new List <int>()
{
500
}) //ラウンド数 (繰り返し数)をセット
.SetSteps(steps) //ステップ数(1ラウンドあたりの更新数)をセット
.SetOpinionThreshold(0.9) //意見形成の閾値.0.9
//.SetOpinionThreshold(0.8)
.SetDynamics(new List <bool>()
{
false
}) //ダイナミクス？
.SetEnvDistModes(new List <EnvDistributionEnum> {
EnvDistributionEnum.Exponential
})
.SetInfoWeightRates(new List <double>()
{
1.0
}) //昔の名残
.SetCommonWeights(new List <double>()
{
0.5
}) //OSM_Onlyにしか使わない.事前に重みが分かってるとき用ってことか
//.SetCommonWeights(Enumerable.Range(0, 21).Select(x => x * 0.05).ToList())
.SetBadSensorMode(new List <bool>()
{
false
}) // BadSensorモードの有無
.SetOpinionShareNum(new List <int>()
{
1
}) //意見発信回数
.SetSensorArrangement(new List <SensorArrangementEnum>()
{
SensorArrangementEnum.Random
}) //センサの配置方法
.SetAdditionalShareCommunityOnly(new List <bool>()
{
false
}) //Badコミュニティのみの追加意見発信か否か
.SetOsmSetting(osm_setting)
.Run(seed);
});
Environment.Exit(0);
}
public void SetOsmSetting(OSMSetting osm_setting)
{
this.osm_setting = osm_setting;
}
void Test()
{
this.osm_setting = new OSMSetting(ExperimentType.AAT_SW_Normal_Random_Exponential);
int agent_size = osm_setting.agent_size;
int dim = osm_setting.dim;
int correct_dim = osm_setting.correct_dim;
int malicious_dim = osm_setting.malicious_dim;
AlgoEnum algo = osm_setting.algo;
double targeth = osm_setting.targeth;
double common_weight = osm_setting.common_weight;
double common_curiocity = osm_setting.common_curiocity;
double sensor_weight = osm_setting.sensor_weight;
double dist_weight = osm_setting.dist_weight;
double malicious_dist_weight = osm_setting.malicious_dist_weight;
int sensor_size = osm_setting.sensor_size;
//int malicious_sensor_size = (int)(0.04 * agent_size);
int malicious_sensor_size = osm_setting.malicious_sensor_size;
var op_form_threshold = osm_setting.op_form_threshold;
int sample_size = osm_setting.sample_size;
int change_round = osm_setting.change_round;
bool bad_sensor_mode = osm_setting.bad_sensor_mode;
int opinion_share_num = osm_setting.opinion_share_num;
bool is_add_share_only_community = osm_setting.add_share_only_community;
EnvDistributionEnum env_distribution = osm_setting.env_distribution;
BeliefUpdateFunctionEnum belief_update = osm_setting.belief_update;
var belief_updater = new BeliefUpdater(belief_update).SetSensorWeightMode(SensorWeightEnum.DependSensorRate);
GraphGeneratorBase graph_generator;
switch (osm_setting.select_graph)
{
case GraphEnum.WS:
graph_generator = new WS_GraphGenerator().SetNodeSize(agent_size).SetNearestNeighbors(6).SetRewireP(0.01);
break;
//case GraphEnum.PowerLawCluster:
//graph_generator = new PC_GraphGenerator().SetNodeSize(500).SetRandomEdges(3).SetAddTriangleP(0.1);
// break;
case GraphEnum.BA:
graph_generator = new BA_GraphGenerator().SetNodeSize(agent_size).SetAttachEdges(2);
break;
case GraphEnum.Grid2D:
graph_generator = new Grid2D_GraphGenerator().SetNodeSize(agent_size);
break;
//case GraphEnum.ER:
//graph_generator = new ER_GraphGenerator().SetNodeSize(agent_size).SetEdgeCreateP(0.01);
//break;
case GraphEnum.LFR:
graph_generator = new LFR_GraphGenerator().SetNodeSize(agent_size);
break;
default:
graph_generator = new LFR_GraphGenerator().SetNodeSize(agent_size);
break;
}
graph_generator.SetOsmSetting(osm_setting);
var pb = new ExtendProgressBar(100);
var graph = graph_generator.Generate(0, pb);
var layout = new KamadaKawai_LayoutGenerator(graph).Generate(pb);
//var layout = new Circular_LayoutGenerator(graph).Generate();
//LFRの時のみ
List <List <int> > communityList = new List <List <int> >();
if (osm_setting.select_graph == GraphEnum.LFR)
{
communityList = graph_generator.GetCommunity();
}
var init_belief_gene = new InitBeliefGenerator()
.SetInitBeliefMode(mode: InitBeliefMode.NormalNarrow);
//.SetInitBeliefMode(mode: InitBeliefMode.NormalWide);
var subject_test = new OpinionSubject("test", dim);
var sample_agent_test = new SampleAgent()
.SetInitBeliefGene(init_belief_gene)
.SetThreshold(op_form_threshold)
.SetSubject(subject_test)
.SetInitOpinion(Vector <double> .Build.Dense(dim, 0.0));
var sensor_gene = new SensorGenerator()
// .SetSensorSize((int)5);
.SetSensorSize(sensor_size, malicious_sensor_size);
int agent_gene_seed = 11;//4
var agent_gene_rand = new ExtendRandom(agent_gene_seed);
var agent_network = new AgentNetwork()
.SetRand(agent_gene_rand)
.GenerateNetworkFrame(graph)
//.ApplySampleAgent(sample_agent_1, mode: SampleAgentSetMode.RandomSetRate, random_set_rate: 0.5)
//.ApplySampleAgent(sample_agent_2, mode: SampleAgentSetMode.RemainSet)
.ApplySampleAgent(sample_agent_test, mode: SampleAgentSetMode.RemainSet)
.SetBadSensorMode(osm_setting.bad_sensor_mode)
.SetSensorArrange(osm_setting.sensor_arrange)
.SetCommnityList(communityList)
.GenerateSensor(sensor_gene)
.SetLayout(layout);
var bad_community_index = agent_network.GetBadCommunityIndex();
int update_step_seed = 1;
var update_step_rand = new ExtendRandom(update_step_seed);
OSMBase osm = new OSM_Only();
switch (algo)
{
case AlgoEnum.AAT:
var osm_aat = new AAT_OSM();
osm_aat.SetTargetH(targeth);
osm = osm_aat;
break;
default:
break;
}
osm.SetRand(update_step_rand);
osm.SetAgentNetwork(agent_network, opinion_share_num);
var subject_mgr_dic = new Dictionary <int, SubjectManager>();
subject_mgr_dic.Add(0, new SubjectManagerGenerator()
.Generate(subject_test, dist_weight, correct_dim, sensor_weight, env_distribution, malicious_dim, malicious_dist_weight));
//for (int i = 0; i < 1; i++)
//{
// subject_mgr_dic.Add(i * change_round, new SubjectManagerGenerator().Generate(subject_test, dist_weight, i % dim, sensor_rate, EnvDistributionEnum.Turara));
//}
osm.SetSubjectManagerDic(subject_mgr_dic);
osm.SetInitWeightsMode(mode: CalcWeightMode.FavorMyOpinion);
osm.SetOpinionIntroInterval(osm_setting.op_intro_interval);
osm.SetOpinionIntroRate(osm_setting.op_intro_rate);
//osm.SetSensorCommonWeight(0.70);
osm.SetBeliefUpdater(belief_updater);
osm.SetAddShareCommunityOnly(is_add_share_only_community);
osm.SetStopRound(osm_setting.stop_rounds);
this.MyOSM = osm;
this.MyAnimationForm.RegistOSM(osm, osm_setting.opinion_share_num, communityList, bad_community_index);
}
public TargetH_Experiment SetOsmSetting(OSMSetting osm_setting)
{
this.osm_setting = osm_setting;
return(this);
}
