source: issm/oecreview/Archive/18296-19100/ISSM-18914-18915.diff@ 19102

Index: ../trunk-jpl/src/c/classes/kriging/Observations.cpp
===================================================================
--- ../trunk-jpl/src/c/classes/kriging/Observations.cpp (revision 18914)
+++ ../trunk-jpl/src/c/classes/kriging/Observations.cpp (revision 18915)
@@ -627,31 +627,24 @@
     double *obs          = NULL;
     Observation observation=Observation(x_interp,y_interp,0.);
     std::vector<Observation> kNN;
-    
-    /*If radius is not provided or is 0, return all observations*/
-    if(radius==0.)
-    {
-        kNN=(this->covertree->getRoot())->getObservations();
-    }
-    else
-    {
-        kNN=(this->covertree->kNearestNeighbors(observation, maxdata));
-               //cout << "kNN's size: " << kNN.size() << endl;
-               
-    }
+
+        kNN=(this->covertree->kNearestNeighbors(observation, maxdata));
+        //cout << "kNN's size: " << kNN.size() << endl;
        
        //kNN is sort from closest to farthest neighbor
        //searches for the first neighbor that is out of radius
        //deletes and resizes the kNN vector
        vector<Observation>::iterator it;
-       for (it = kNN.begin(); it != kNN.end(); ++it) {
-               //(*it).print();
-               //cout << "\n" << (*it).distance(observation) << endl;
-               if ((*it).distance(observation) > radius) {
-                       break;
+       if(radius>0.){
+               for (it = kNN.begin(); it != kNN.end(); ++it) {
+                       //(*it).print();
+                       //cout << "\n" << (*it).distance(observation) << endl;
+                       if ((*it).distance(observation) > radius) {
+                               break;
+                       }
                }
+               kNN.erase(it, kNN.end());
        }
-       kNN.erase(it, kNN.end());
     
        /*Allocate vectors*/
        x   = new double[kNN.size()];
@@ -660,7 +653,7 @@
 
        /*Loop over all observations and fill in x, y and obs*/
        int i = 0;
-       for (it = kNN.begin(); it != kNN.end(); ++it) {
+       for(it = kNN.begin(); it != kNN.end(); ++it) {
                (*it).WriteXYObs((*it), &x[i], &y[i], &obs[i]);
                i++;
        }
@@ -668,5 +661,5 @@
     *px=x;
     *py=y;
     *pobs=obs;
-       *pnobs = kNN.size();
+        *pnobs = kNN.size();
 }/*}}}*/