NodeColorSampler::NodeColorSampler(LidarProcessOctree& sLpo,const std::vector<Image2D*>& sImages,size_t imageMemorySize,const char* colorFileName) :lpo(sLpo), images(sImages), imageCacher(imageMemorySize), colorBuffer(new Color[lpo.getMaxNumPointsPerNode()]), colorDataSize(sizeof(Color)), colorFile(colorFileName,LidarFile::ReadWrite), numProcessedNodes(0),nextProgressUpdate((lpo.getNumNodes()+199)/200), numAssignedColors(0) { /* Allocate the color subsampling arrays: */ for(int i=0;i<8;++i) childColorBuffers[i]=new Color[lpo.getMaxNumPointsPerNode()]; /* Write the color file's header: */ colorFile.setEndianness(Misc::LittleEndian); LidarDataFileHeader dfh((unsigned int)(colorDataSize)); dfh.write(colorFile); /* Register all images in the image list: */ for(std::vector<Image2D*>::const_iterator iIt=images.begin();iIt!=images.end();++iIt) imageCacher.registerImage(*iIt); }
LidarProcessOctree::LidarProcessOctree(const char* lidarFileName,size_t sCacheSize) :indexFile(getLidarPartFileName(lidarFileName,"Index").c_str()), pointsFile(getLidarPartFileName(lidarFileName,"Points").c_str()), offset(OffsetVector::zero), numSubdivideCalls(0),numLoadedNodes(0), lruHead(0),lruTail(0) { indexFile.setEndianness(Misc::LittleEndian); pointsFile.setEndianness(Misc::LittleEndian); /* Read the octree file header: */ LidarOctreeFileHeader ofh(indexFile); /* Initialize the root node's domain: */ root.domain=ofh.domain; /* Initialize the tree structure: */ maxNumPointsPerNode=ofh.maxNumPointsPerNode; /* Calculate the memory and GPU cache sizes: */ size_t memNodeSize=sizeof(Node)+size_t(maxNumPointsPerNode)*sizeof(LidarPoint); cacheSize=(unsigned int)(sCacheSize/memNodeSize); if(cacheSize==0U) Misc::throwStdErr("LidarProcessOctree::LidarProcessOctree: Specified memory cache size too small"); std::cout<<"Cache size: "<<cacheSize<<" memory nodes"<<std::endl; /* Read the root node's structure: */ LidarOctreeFileNode rootfn; rootfn.read(indexFile); root.childrenOffset=rootfn.childrenOffset; root.numPoints=rootfn.numPoints; root.dataOffset=rootfn.dataOffset; root.detailSize=rootfn.detailSize; /* Get the total number of nodes by dividing the index file's size by the size of one octree node: */ numNodes=size_t((indexFile.getSize()-LidarOctreeFileHeader::getFileSize())/LidarFile::Offset(LidarOctreeFileNode::getFileSize())); /* Read the point file's header: */ LidarDataFileHeader dfh(pointsFile); pointsRecordSize=LidarFile::Offset(dfh.recordSize); if(root.numPoints>0) { /* Load the root node's points: */ root.points=new LidarPoint[maxNumPointsPerNode]; // Always allocate maximum to prevent memory fragmentation pointsFile.setReadPosAbs(LidarDataFileHeader::getFileSize()+pointsRecordSize*root.dataOffset); pointsFile.read(root.points,root.numPoints); } ++numLoadedNodes; /* Try loading an offset file: */ try { IO::FilePtr offsetFile(IO::openFile(getLidarPartFileName(lidarFileName,"Offset").c_str())); offsetFile->setEndianness(Misc::LittleEndian); /* Read the original offset vector: */ offsetFile->read<OffsetVector::Scalar>(offset.getComponents(),3); /* Invert the offset transformation: */ offset=-offset; } catch(IO::File::OpenError err) { /* Ignore the error */ } /* Initialize the node cache: */ numCachedNodes=1U; }
/** Incomplete beta function for variable objects. Evaluates the continued fraction for imcomplete beta function. \param _a \f$a\f$ \param _b \f$b\f$ \param _x \f$x\f$ \param MAXIT Maximum number of iterations for the continued fraction approximation in betacf. \return Incomplete beta function \f$I_x(a,b)\f$ \n\n The implementation of this algorithm was inspired by "Numerical Recipes in C", 2nd edition, Press, Teukolsky, Vetterling, Flannery, chapter 2 */ dvariable betacf(const dvariable& _a, const dvariable& _b, const dvariable& _x, int MAXIT) { double qab,qam,qap; double a=value(_a); double b=value(_b); double x=value(_x); qab=a+b; qap=a+1.0; qam=a-1.0; dvector c1(0,MAXIT); dvector c(1,MAXIT); dvector d1(0,MAXIT); dvector d(1,MAXIT); dvector del(1,MAXIT); dvector h1(0,MAXIT); dvector h(1,MAXIT); dvector aa(1,MAXIT); dvector aa1(1,MAXIT); c1(0)=1.0; d1(0)=1.0/(1.0-qab*x/qap); h1(0)=d1(0); int m = 1; for (; m <= MAXIT; m++) { int i=m; int m2=2*m; aa(i)=m*(b-m)*x/((qam+m2)*(a+m2)); d(i)=1.0/(1.0+aa(i)*d1(i-1)); c(i)=1.0+aa(i)/c1(i-1); h(i) = h1(i-1)*d(i)*c(i); aa1(i) = -(a+m)*(qab+m)*x/((a+m2)*(qap+m2)); d1(i)=1.0/(1.0+aa1(i)*d(i)); c1(i)=1.0+aa1(i)/c(i); del(i)=d1(i)*c1(i); h1(i) = h(i)*del(i); if (fabs(del(i)-1.0) < EPS) break; } if (m > MAXIT) { cerr << "a or b too big, or MAXIT too small in cumulative beta function" " routine" << endl; m=MAXIT; } int mmax=m; dvariable hh; value(hh)=h1(mmax); dvector dfc1(0,MAXIT); dvector dfc(1,MAXIT); dvector dfd1(0,MAXIT); dvector dfd(1,MAXIT); dvector dfh1(0,MAXIT); dvector dfh(1,MAXIT); dvector dfaa(1,MAXIT); dvector dfaa1(1,MAXIT); dvector dfdel(1,MAXIT); dfc1.initialize(); dfc.initialize(); dfaa1.initialize(); dfaa.initialize(); dfd1.initialize(); dfd.initialize(); dfh1.initialize(); dfh.initialize(); dfdel.initialize(); dfh1(mmax)=1.0; double dfqab=0.0; double dfqam=0.0; double dfqap=0.0; double dfa=0.0; double dfb=0.0; double dfx=0.0; for (m=mmax;m>=1;m--) { /* int i=m; m2=2*m; aa(i)=m*(b-m)*x/((qam+m2)*(a+m2)); d(i)=1.0/(1.0+aa(i)*d1(i-1)); c(i)=1.0+aa(i)/c1(i-1); h(i) = h1(i-1)*d(i)*c(i); aa1(i) = -(a+m)*(qab+m)*x/((a+m2)*(qap+m2)); d1(i)=1.0/(1.0+aa1(i)*d(i)); c1(i)=1.0+aa1(i)/c(i); del(i)=d1(i)*c1(i); h1(i) = h(i)*del(i); */ int i=m; int m2=2*m; //h1(i) = h(i)*del(i); dfh(i)+=dfh1(i)*del(i); dfdel(i)+=dfh1(i)*h(i); dfh1(i)=0.0; //del(i)=d1(i)*c1(i); dfd1(i)+=dfdel(i)*c1(i); dfc1(i)+=dfdel(i)*d1(i); dfdel(i)=0.0; //c1(i)=1.0+aa1(i)/c(i); dfaa1(i)+=dfc1(i)/c(i); dfc(i)-=dfc1(i)*aa1(i)/(c(i)*c(i)); dfc1(i)=0.0; //d1(i)=1.0/(1.0+aa1(i)*d(i)); double sq=square(d1(i)); dfaa1(i)-=dfd1(i)*sq*d(i); dfd(i)-=dfd1(i)*sq*aa1(i); dfd1(i)=0.0; //aa1(i) = -(a+m)*(qab+m)*x/((a+m2)*(qap+m2)); dfx -= dfaa1(i) * (a+m)*(qab+m)/((a+m2)*(qap+m2)); dfa += dfaa1(i) * aa1(i)* (1.0/(a+m) - 1.0/(a+m2)); dfqab += dfaa1(i) * aa1(i)/(qab+m); dfqap += dfaa1(i) * aa1(i)* (-1.0/(qap+m2)); dfaa1(i)=0.0; //h(i) = h1(i-1)*d(i)*c(i); dfh1(i-1)+=dfh(i)*d(i)*c(i); dfd(i)+=dfh(i)*h1(i-1)*c(i); dfc(i)+=dfh(i)*h1(i-1)*d(i); dfh(i)=0.0; //c(i)=1.0+aa(i)/c1(i-1); dfaa(i)+=dfc(i)/c1(i-1); dfc1(i-1)-=dfc(i)*aa(i)/square(c1(i-1)); dfc(i)=0.0; //d(i)=1.0/(1.0+aa(i)*d1(i-1)); dfaa(i)-=dfd(i)*square(d(i))*d1(i-1); dfd1(i-1)-=dfd(i)*square(d(i))*aa(i); dfd(i)=0.0; //aa(i)=m*(b-m)*x/((qam+m2)*(a+m2)); dfx+=dfaa(i)* m*(b-m)/((qam+m2)*(a+m2)); dfb+=dfaa(i)* m*x/((qam+m2)*(a+m2)); dfa-=dfaa(i)*aa(i)/(a+m2); dfqam-=dfaa(i)*aa(i)/(qam+m2); dfaa(i)=0.0; } /* c1(0)=1.0; d1(0)=1.0/(1.0-qab*x/qap); h1(0)=d1(0); */ //h1(0)=d1(0); dfd1(0)+=dfh1(0); dfh1(0)=0.0; //d1(0)=1.0/(1.0-qab*x/qap); double sq1=square(d1(0))/qap; dfx+=dfd1(0)*sq1*qab; dfqab+=dfd1(0)*sq1*x; dfqap-=dfd1(0)*sq1*qab*x/qap; dfd1(0)=0.0; /* qab=a+b; qap=a+1.0; qam=a-1.0; */ //qam=a-1.0; dfa+=dfqam; //qap=a+1.0; dfa+=dfqap; //qab=a+b; dfa+=dfqab; dfb+=dfqab; gradient_structure::GRAD_STACK1->set_gradient_stack(default_evaluation3ind, &(value(hh)) ,&(value(_a)),dfa ,&(value(_b)),dfb ,&(value(_x)),dfx); return hh; }