[1fa077]: TestKDTree.c Maximize Restore History

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TestKDTree.c    140 lines (111 with data), 3.7 kB

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#include "AutoPanoSift.h"
// 2d example point class
struct sPoint3{
IKDTreeDomain base;
double* coords;
double x;
double y;
double z;
};
typedef struct sPoint3 Point3;
int Point3_GetDimensionCount(Point3* self) {
return (3);
}
int Point3_GetDimensionElement (Point3* self, int dim)
{
return self->coords[dim];
}
Point3* Point3_new0()
{
Point3* self = (Point3*)malloc(sizeof(Point3));
self->base.getDimensionCount = (int ( *)(IKDTreeDomain *)) Point3_GetDimensionCount;
self->base.getDimensionElement = (int ( *)(IKDTreeDomain *,int))Point3_GetDimensionElement;
self->x = 0;
self->y = 0;
self->z = 0;
self->coords = (double*)malloc(sizeof(double)*3);
return self;
}
Point3* Point3_new (double x, double y, double z)
{
Point3* self = Point3_new0();
self->x = x;
self->y = y;
self->z = z;
self->coords[0]=x;
self->coords[1]=y;
self->coords[2]=z;
return self;
}
void Point3_delete(Point3* self)
{
free(self->coords);
free(self);
}
Random* Point3_rnd = NULL;
Point3* Point3_CreateRandomPoint3 (double minX, double maxX,
double minY, double maxY,
double minZ, double maxZ)
{
double x = Random_NextDouble (Point3_rnd) * (maxX - minX) + minX;
double y = Random_NextDouble (Point3_rnd) * (maxY - minY) + minY;
double z = Random_NextDouble (Point3_rnd) * (maxZ - minZ) + minZ;
return (Point3_new (x, y, z));
}
int main (int argc, char* argv[])
{
Point3 * target, *pt, *NN;
KDTree* kd;
double dist;
int n;
ArrayList* Point3s = ArrayList_new0 (Point3_delete);
Point3_rnd = Random_new0 ();
// try searching for a random target
target = Point3_CreateRandomPoint3 (-100.0, 100.0, -100.0, 100.0, -100.0, 100.0);
WriteLine ("target is \nS %f %f %f", target->x, target->y, target->z);
for ( n = 0 ; n < 20 ; ++n) {
pt = Point3_CreateRandomPoint3 (-100.0, 100.0, -100.0, 100.0, -100.0, 100.0);
WriteLine ("P %f %f %f (distance: %f)", pt->x, pt->y, pt->z, sqrt((double)KDTree_DistanceSq((IKDTreeDomain *)pt, (IKDTreeDomain *)target)));
ArrayList_AddItem (Point3s, pt);
}
WriteLine ("\nbuilding kd-tree");
kd = KDTree_CreateKDTree (Point3s);
WriteLine ("search for nearest neighbour");
Point3* NN = (Point3*)KDTree_NearestNeighbour (kd, (IKDTreeDomain*)target, &dist);
if (NN == NULL) {
WriteLine ("no nn found");
} else {
WriteLine ("nearest is (distance %f):\nNN %f %f %f",
dist, NN->x, NN->y, NN->z);
}
{
WriteLine ("search for 3 nearests neighbours");
SortedLimitedList* nnlist = KDTree_NearestNeighbourList(kd, (IKDTreeDomain*)target, &dist, 3);
WriteLine ("nearest distance is %f", dist);
int i;
for(i=0; i<SortedLimitedList_Count(nnlist); i++) {
KDTreeBestEntry* be = (KDTreeBestEntry*) SortedLimitedList_GetItem(nnlist, i);
Point3* nn = (Point3*)be->neighbour;
WriteLine ("N1 %f %f %f # distance %f",
nn->x, nn->y, nn->z, be->distance);
}
SortedLimitedList_delete(nnlist);
}
{
WriteLine ("BBF search for 3 nearests neighbours");
SortedLimitedList* nnlist = KDTree_NearestNeighbourListBBF(kd, (IKDTreeDomain*)target, 3, 20);
int i;
for(i=0; i<SortedLimitedList_Count(nnlist); i++) {
KDTreeBestEntry* be = (KDTreeBestEntry*) SortedLimitedList_GetItem(nnlist, i);
Point3* nn = (Point3*)be->neighbour;
WriteLine ("N2 %f %f %f # distance %f",
nn->x, nn->y, nn->z, be->distance);
}
SortedLimitedList_delete(nnlist);
}
Point3_delete(target);
KDTree_delete(kd);
ArrayList_delete(Point3s);
Random_delete(Point3_rnd);
return 0;
}