void TopicDetection (vector<Story> &corpus, int &numOfTopics)
{
cout << "> Start TopicDetection......" << endl;
numOfTopics = 6;
KMeans (corpus, numOfTopics);
//NaiveClustering (corpus, numOfTopics, 0.5);
cout << "> TopicDetection Done." << endl;
}
void inline unitTestKMeansRandomly(Group &test, std::ofstream &output) {
// 数据归一化
// normaliztion(test);
// 输出读入的数据
// puts("Print Input Data:");
// puts("=====================================");
// test.display();
// puts("=====================================\n");
// k 值
const unsigned k = 3;
/** 准备测试数据 */
// KMeans++
// std::vector<Group> centroid = buildInitialPointRandomly(k, test);
// Kmeans + Density initialize
// std::vector<Group> centroid = buildInitialPointDensity(k, test);
// KMeans
// std::vector<Group> centroid = buildInitialPoint(k, test);
output << "===============================================" << std::endl;
output << "buildInitialPointRandomly" << std::endl;
output << "===============================================" << std::endl;
// 重复运行测试
std::vector<Group> result;
std::vector<double> avg(k);
double SSE = 0;
// 记录每次的 SSE 值
std::vector<double> vecSSE;
time_t start = std::clock();
// 重复实验的次数
for (unsigned i = 0; i < TIMES; ++i) {
printf("running: %d\r", i);
result = KMeans(test, k, buildInitialPointRandomly(k, test), false);
SSE = 0;
for (unsigned j = 0; j < result.size(); ++j) {
SSE += result[j].getSumOfEuclideanDistance();
vecSSE.push_back(SSE / result.size());
}
}
time_t end = std::clock();
output << "The average of SSE = " << getAverage(vecSSE) << std::endl;
output << "The variance of SSE = " << getVariance(vecSSE) << std::endl;
output << "The running time is: " << double(end - start) / CLOCKS_PER_SEC << std::endl;
// printf("The average of SSE = %lf\n", getAverage(vecSSE));
// printf("The variance of SSE = %lf\n", getVariance(vecSSE));
printf("the running time is : %f\n", double(end - start) / CLOCKS_PER_SEC);
output << "===============================================" << std::endl;
// puts("===============================================");
// KMedoids(test, k, centroid);
}
void ConstrainedFire::Init(ObjReader * obj)
{
FireVertex vertex;
FireTriangle triangle;
int end;
//存储模型顶点
end = (int)obj->Positions.size();
for(int i=0;i<end;i++)
{
vertex.position = obj->Positions[i]*2.6;
m_Vertices.push_back(vertex);
}
//存储模型面信息
end = (int) obj->m_Object[0]->posIndices.size();
for(int i=0;i<end;)
{
triangle.index[0] = obj->m_Object[0]->posIndices[i++];
triangle.index[1] = obj->m_Object[0]->posIndices[i++];
triangle.index[2] = obj->m_Object[0]->posIndices[i++];
triangle.area = TriangleArea(triangle.index[0],triangle.index[1],triangle.index[2]);
m_Faces.push_back(triangle);
}
Normalize();//归一化顶点数据
Subdivide();//细分模型
objectImported =true;
objVertexNum = (int)m_Vertices.size();
numParticlesSecondExp=m_Vertices.size()*1.8;
KMeans(m_K);//聚类操作
GenerateQuadrantByKMean();//生成发射区域
//8个二次爆炸的粒子发生器的位置限制,注意顺序要与对象顶点分区编号对应
/*Point3f expP;
expP=modelCenter(m_Quadrant0);
expEmitter[0].pos.X()=expP.X();
expEmitter[0].pos.Y()=expP.Y();
expEmitter[0].pos.Z()=expP.Z();
expP=modelCenter(m_Quadrant1);
expEmitter[1].pos.X()=expP.X();
expEmitter[1].pos.Y()=expP.Y();
expEmitter[1].pos.Z()=expP.Z();
expP=modelCenter(m_Quadrant2);
expEmitter[2].pos.X()=expP.X();
expEmitter[2].pos.Y()=expP.Y();
expEmitter[2].pos.Z()=expP.Z();
expP=modelCenter(m_Quadrant3);
expEmitter[3].pos.X()=expP.X();
expEmitter[3].pos.Y()=expP.Y();
expEmitter[3].pos.Z()=expP.Z();
expP=modelCenter(m_Quadrant4);
expEmitter[4].pos.X()=expP.X();
expEmitter[4].pos.Y()=expP.Y();
expEmitter[4].pos.Z()=expP.Z();
expP=modelCenter(m_Quadrant5);
expEmitter[5].pos.X()=expP.X();
expEmitter[5].pos.Y()=expP.Y();
expEmitter[5].pos.Z()=expP.Z();
expP=modelCenter(m_Quadrant6);
expEmitter[6].pos.X()=expP.X();
expEmitter[6].pos.Y()=expP.Y();
expEmitter[6].pos.Z()=expP.Z();
expP=modelCenter(m_Quadrant7);
expEmitter[7].pos.X()=expP.X();
expEmitter[7].pos.Y()=expP.Y();
expEmitter[7].pos.Z()=expP.Z();*/
}
