Point<Dim> KDTree<Dim>::findNearestNeighbor(const Point<Dim> & query, int lo, int hi, int dim) const{
if(lo >= hi ) return points[lo]; //base case
int mid = (hi+lo)/2; //calculate the minPoint index
Point<Dim> temp;
Point<Dim> curr = points[mid];
dim = dim%Dim;
int direction=0;
if(smallerDimVal(query, points[mid], dim)){
direction = 0;
temp = findNearestNeighbor(query, lo, mid-1, dim+1); //left half
}
else{
direction =1;
temp = findNearestNeighbor(query, mid+1, hi, dim+1); //recusively call the function on the left half
}
Point<Dim> best;
if(shouldReplace(query, temp, curr) ) best= curr;
else best = temp;
int dimD = (curr[dim] - query[dim])*(curr[dim] - query[dim]);
int bestCurr = squareDistance(best, query);
if(dimD > bestCurr) return best;
else{
Point<Dim> t;
if(direction == 0)
t = findNearestNeighbor(query, mid+1, hi, dim+1);
else t = findNearestNeighbor(query, lo, mid-1,dim+1);
if(shouldReplace(query,t, best)) return best;
else return t;
}
}
Point<Dim> KDTree<Dim>::find(const Point<Dim> & query, int cur, int curDim, int a, int b) const
{
if(a == b) return points[a];
else
{
Point<Dim> temp;
double childdist = 0;
double parentdist2 = ((points[cur])[curDim] - query[curDim])*((points[cur])[curDim] - query[curDim]);
double parentdist = 0;
if(smallerDimVal(query, points[cur], curDim))
{
if (cur-1 < a) return points[cur];
else
{
temp = find(query, (a+cur-1)/2, (curDim+1)%Dim, a, cur-1);
for (int i = 0; i < Dim; i++)
{
childdist += ((temp[i]-query[i])*(temp[i]-query[i]));
parentdist += (((points[cur])[i]-query[i])*((points[cur])[i]-query[i]));
}
if (parentdist2 <= childdist)
{
Point<Dim> temp2;
if (cur+1 > b) temp2 = points[cur];
else temp2 = find(query, (cur+1+b)/2, (curDim+1)%Dim, cur+1, b);
if ((parentdist < childdist)||((parentdist == childdist)&&(points[cur] < temp))) temp = points[cur];
if (shouldReplace(query, temp, temp2)) return temp2;
else return temp;
}
else return temp;
}
}
else
{
if (cur+1 > b) return points[cur];
else
{
temp = find(query, (cur+1+b)/2, (curDim+1)%Dim, cur+1, b);
for (int i = 0; i < Dim; i++)
{
childdist += ((temp[i]-query[i])*(temp[i]-query[i]));
parentdist += (((points[cur])[i]-query[i])*((points[cur])[i]-query[i]));
}
if (parentdist2 <= childdist)
{
Point<Dim> temp2;
if (cur-1 < a) temp2 = points[cur];
else temp2 = find(query, (a+cur-1)/2, (curDim+1)%Dim, a, cur-1);
if ((parentdist < childdist)||((parentdist == childdist)&&(points[cur] < temp))) temp = points[cur];
if (shouldReplace(query, temp, temp2)) return temp2;
else return temp;
}
else return temp;
}
}
}
}
Point<Dim> KDTree<Dim>::walkThrough(const Point<Dim> &target, const Point<Dim> &ret, int lower, int upper, int curDim) const
{
//base case
if (lower == upper)
{
if (shouldReplace(target, ret, points[lower]))
{
return points[lower];
}
return ret;
}
// other
int median = (lower + upper)/2;
Point<Dim> ret2 = ret;
//a recording for which side are we going
int side = 0;//0:left, 1:right
if (smallerDimVal(points[median], target, curDim)&&upper>median)
//why do we have to check upper>median?
{
int dim2 = curDim+1;
if(dim2>=Dim)
dim2=dim2-Dim;
ret2 = walkThrough(target, ret, median+1, upper, dim2);
side=1;
}
if (smallerDimVal(target, points[median], curDim)&&lower<median)
{
int dim2 = curDim+1;
if(dim2>=Dim)
dim2=dim2-Dim;
ret2 = walkThrough(target, ret, lower, median-1, dim2);
side=0;
}
//Check if current node is closer than obtained above
if (shouldReplace(target, ret2, points[median]))
ret2 = points[median];
//prepare to check the other side
Point<Dim> m = points[median];//don't understand why can't point[median][Dim]
int distance=0;//distance we have now
for(int i=0; i< Dim; i++)
distance+= pow(target[i]-ret2[i],2);
if(pow(m[curDim]-target[curDim],2)<=distance)
{
int dim2 = curDim+1;
if(dim2>=Dim)
dim2=dim2-Dim;
if(side==0&&upper>median)//left has been checked, goto right
ret2 = walkThrough(target, ret2, median+1, upper, dim2 );
if(side==1&&lower<median)//goto left
ret2 = walkThrough(target, ret2, lower, median-1, dim2 );
}
return ret2;
}
Point<Dim> KDTree<Dim>::NearestNeighbor_helper(int curDim, const Point<Dim> &query, int bottom, int top, const Point<Dim> ¤tBest) const
{
Point<Dim> retVal = currentBest;//set a holder (call it return value) equal to currentBest to start
bool target = true; //initialize our target bool to true
if(bottom==top)
{
//this means were at a leaf
//we need to check if were wcloser than current best and return the appropriate currnent best
if(shouldReplace(query, currentBest, points[bottom])==true)
{
retVal = points[bottom];//set the return value
return retVal; //send that thing up!
}
retVal = currentBest; //otherwise return the currentBest
return retVal;
}
//declare the middle point
int middle = (bottom+top)/2;
//now lets get to work on tricky stuff
if(smallerDimVal(points[middle], query, curDim) && top > middle)
{
//recursive call to set retVal
retVal = NearestNeighbor_helper((curDim+1)%Dim, query, middle+1, top, currentBest);
target = false;
}
if (smallerDimVal(query, points[middle], curDim) && bottom <middle)
{
//recursive call to set retVal
retVal = NearestNeighbor_helper((curDim+1)%Dim, query, bottom, middle-1, currentBest);
target = true;
}
//look to see if the node were on is closer than what was obtained earlier
if(shouldReplace(query, retVal, points[middle]))
{
retVal = points[middle];//set retVal appropriately
}
//lots of TA guidance here this is still a little foggy
Point <Dim> holder = points[middle];
if(pow(holder[curDim] - query[curDim], 2) <= distance(query, retVal))
{
if(!target && bottom < middle)
{
retVal = NearestNeighbor_helper((curDim+1)%Dim, query, bottom, middle-1, retVal);//same as above but replace currentBest with retVal!
}
if(target && top > middle)
{
//recurisve call
retVal = NearestNeighbor_helper((curDim+1)%Dim, query, middle+1, top, retVal);//same as above but replace currentBest with retVal!
}
}
//AND FINALLY
return retVal;
}
