//round all neuronal node coordinates, and compute the average min distance matches for all places the neurons go through
NeuronDistSimple neuron_score_rounding_nearest_neighbor(const NeuronTree *p1, const NeuronTree *p2)
{
NeuronDistSimple ss;
if (!p1 || !p2) return ss;
V3DLONG p1sz = p1->listNeuron.size(), p2sz = p2->listNeuron.size();
if (p1sz<1 || p2sz<1) return ss;
double sum12, sum21;
V3DLONG nseg1, nseg2;
double sum12big, sum21big;
V3DLONG nseg1big, nseg2big;
sum12 = dist_directional_swc_1_2(nseg1, nseg1big, sum12big, p1, p2);
sum21 = dist_directional_swc_1_2(nseg2, nseg2big, sum21big, p2, p1);
qDebug() << "sum12="<<sum12 << "npoints1="<< nseg1 << "sum21="<< sum21 << "npoint2="<< nseg2;
qDebug() << "sum12big="<<sum12big << "npoints1big="<< nseg1big << "sum21big="<< sum21big << "npoint2big="<< nseg2big;
ss.dist_allnodes = (sum12/nseg1 + sum21/nseg2)/2.0;
if (nseg1big>0)
{
if (nseg2big>0)
ss.dist_apartnodes = (sum12big/nseg1big + sum21big/nseg2big)/2.0;
else
ss.dist_apartnodes = (sum12big/nseg1big);
}
else
{
if (nseg2big>0)
ss.dist_apartnodes = (sum21big/nseg2big);
else
ss.dist_apartnodes = 0;
}
ss.percent_apartnodes = (double(nseg1big)/nseg1 + double(nseg2big)/nseg2)/2.0;
return ss;
}
//round all neuronal node coordinates, and compute the average min distance matches for all places the neurons go through
NeuronDistSimple neuron_score_rounding_nearest_neighbor(const NeuronTree *p1, const NeuronTree *p2,bool bmenu)
{
NeuronDistSimple ss;
//===
if(bmenu)
{
bool ok1;
#ifndef USE_Qt5
V3DLONG d_thres_new = QInputDialog::getInteger(0, "change the default distance threshold",
"The visible-spatial-distance threshold of two neurons: ", d_thres, 2, 20, 1, &ok1);
#else
V3DLONG d_thres_new = QInputDialog::getInt(0, "change the default distance threshold",
"The visible-spatial-distance threshold of two neurons: ", d_thres, 2, 20, 1, &ok1);
#endif
if (ok1)
{
d_thres = d_thres_new;
}
}
//===
if (!p1 || !p2) return ss;
V3DLONG p1sz = p1->listNeuron.size(), p2sz = p2->listNeuron.size();
if (p1sz<2 || p2sz<2) {
cout<<"Input neurons has too few nodes, distance calculation requires at least two nodes." <<endl;
return ss; //requires two nodes at least
}
double sum12, sum21;
V3DLONG nseg1, nseg2;
double sum12big, sum21big;
double maxdist12 = -1, maxdist21 = -1; //set as some big numbers
V3DLONG nseg1big, nseg2big;
sum12 = dist_directional_swc_1_2(nseg1, nseg1big, sum12big, p1, p2, maxdist12);
sum21 = dist_directional_swc_1_2(nseg2, nseg2big, sum21big, p2, p1, maxdist21);
//qDebug() << "sum12="<<sum12 << "npoints1="<< nseg1 << "sum21="<< sum21 << "npoint2="<< nseg2;
//qDebug() << "sum12big="<<sum12big << "npoints1big="<< nseg1big << "sum21big="<< sum21big << "npoint2big="<< nseg2big;
//qDebug() << "maxdist12="<<maxdist12 << "maxdist21="<< maxdist21;
ss.dist_12_allnodes = sum12/nseg1;
ss.dist_21_allnodes = sum21/nseg2;
ss.dist_allnodes = (sum12/nseg1 + sum21/nseg2)/2.0;
if (nseg1big>0)
{
if (nseg2big>0)
ss.dist_apartnodes = (sum12big/nseg1big + sum21big/nseg2big)/2.0;
else
ss.dist_apartnodes = (sum12big/nseg1big);
}
else
{
if (nseg2big>0)
ss.dist_apartnodes = (sum21big/nseg2big);
else
ss.dist_apartnodes = 0;
}
ss.percent_apartnodes = (double(nseg1big)/nseg1 + double(nseg2big)/nseg2)/2.0;
ss.dist_max = (maxdist12<maxdist21) ? maxdist12 : maxdist21; //this max distance should refelect the meaningful measure.
// Becasue the two neurons (tracts) can have different starting and ending locations,
// the bigger one of maxdist12 and maxdist21 could simply reflect the big difference of
// of the starting locations of the two tracts. Thus I use the smaller one, which
// should correspond better to the max distance at the truck part of two tracts. PHC 20140318.
return ss;
}