void Consensus::findConsensus(const vector<Point2f> & points, const vector<int> & classes,
const float scale, const float rotation,
Point2f & center, vector<Point2f> & points_inlier, vector<int> & classes_inlier)
{
FILE_LOG(logDEBUG) << "Consensus::findConsensus() call";
//If no points are available, reteurn nan
if (points.size() == 0)
{
center.x = numeric_limits<float>::quiet_NaN();
center.y = numeric_limits<float>::quiet_NaN();
FILE_LOG(logDEBUG) << "Consensus::findConsensus() return";
return;
}
//Compute votes
vector<Point2f> votes(points.size());
for (size_t i = 0; i < points.size(); i++)
{
votes[i] = points[i] - scale * rotate(points_normalized[classes[i]], rotation);
}
t_index N = points.size();
float * D = new float[N*(N-1)/2]; //This is a lot of memory, so we put it on the heap
cluster_result Z(N-1);
//Compute pairwise distances between votes
int index = 0;
for (size_t i = 0; i < points.size(); i++)
{
for (size_t j = i+1; j < points.size(); j++)
{
//TODO: This index calculation is correct, but is it a good thing?
//int index = i * (points.size() - 1) - (i*i + i) / 2 + j - 1;
D[index] = norm(votes[i] - votes[j]);
index++;
}
}
FILE_LOG(logDEBUG) << "Consensus::MST_linkage_core() call";
MST_linkage_core(N,D,Z);
FILE_LOG(logDEBUG) << "Consensus::MST_linkage_core() return";
union_find nodes(N);
//Sort linkage by distance ascending
std::stable_sort(Z[0], Z[N-1]);
//S are cluster sizes
int* S = (int*)alloca((2*N-1)*sizeof(int));
//TODO: Why does this loop go to 2*N-1? Shouldn't it be simply N? Everything > N gets overwritten later
for(int i = 0; i < 2*N-1; i++)
{
S[i] = 1;
}
t_index parent = 0; //After the loop ends, parent contains the index of the last cluster
for (node const * NN=Z[0]; NN!=Z[N-1]; ++NN)
{
// Get two data points whose clusters are merged in step i.
// Find the cluster identifiers for these points.
t_index node1 = nodes.Find(NN->node1);
t_index node2 = nodes.Find(NN->node2);
// Merge the nodes in the union-find data structure by making them
// children of a new node
// if the distance is appropriate
if (NN->dist < thr_cutoff)
{
parent = nodes.Union(node1, node2);
S[parent] = S[node1] + S[node2];
}
}
//Get cluster labels
int* T = (int*)alloca(N*sizeof(int));
for (t_index i = 0; i < N; i++)
{
T[i] = nodes.Find(i);
}
//Find largest cluster
int S_max = distance(S, max_element(S, S + 2*N-1));
//Find inliers, compute center of votes
points_inlier.reserve(S[S_max]);
classes_inlier.reserve(S[S_max]);
center.x = center.y = 0;
for (size_t i = 0; i < points.size(); i++)
{
//If point is in consensus cluster
if (T[i] == S_max)
{
points_inlier.push_back(points[i]);
classes_inlier.push_back(classes[i]);
center.x += votes[i].x;
center.y += votes[i].y;
}
}
center.x /= points_inlier.size();
center.y /= points_inlier.size();
delete[] D;
FILE_LOG(logDEBUG) << "Consensus::findConsensus() return";
}
SEXP fastcluster(SEXP const N_, SEXP const method_, SEXP D_, SEXP members_) {
SEXP r = NULL; // return value
try{
/*
Input checks
*/
// Parameter N: number of data points
PROTECT(N_);
if (!IS_INTEGER(N_) || LENGTH(N_)!=1)
Rf_error("'N' must be a single integer.");
const int N = *INTEGER_POINTER(N_);
if (N<2)
Rf_error("N must be at least 2.");
const std::ptrdiff_t NN = static_cast<std::ptrdiff_t>(N)*(N-1)/2;
UNPROTECT(1); // N_
// Parameter method: dissimilarity index update method
PROTECT(method_);
if (!IS_INTEGER(method_) || LENGTH(method_)!=1)
Rf_error("'method' must be a single integer.");
const int method = *INTEGER_POINTER(method_) - 1; // index-0 based;
if (method<METHOD_METR_SINGLE || method>METHOD_METR_MEDIAN) {
Rf_error("Invalid method index.");
}
UNPROTECT(1); // method_
// Parameter members: number of members in each node
auto_array_ptr<t_float> members;
if (method==METHOD_METR_AVERAGE ||
method==METHOD_METR_WARD ||
method==METHOD_METR_CENTROID) {
members.init(N);
if (Rf_isNull(members_)) {
for (t_index i=0; i<N; ++i) members[i] = 1;
}
else {
PROTECT(members_ = AS_NUMERIC(members_));
if (LENGTH(members_)!=N)
Rf_error("'members' must have length N.");
const t_float * const m = NUMERIC_POINTER(members_);
for (t_index i=0; i<N; ++i) members[i] = m[i];
UNPROTECT(1); // members
}
}
// Parameter D_: dissimilarity matrix
PROTECT(D_ = AS_NUMERIC(D_));
if (LENGTH(D_)!=NN)
Rf_error("'D' must have length (N \\choose 2).");
const double * const D = NUMERIC_POINTER(D_);
// Make a working copy of the dissimilarity array
// for all methods except "single".
auto_array_ptr<double> D__;
if (method!=METHOD_METR_SINGLE) {
D__.init(NN);
for (std::ptrdiff_t i=0; i<NN; ++i)
D__[i] = D[i];
}
UNPROTECT(1); // D_
/*
Clustering step
*/
cluster_result Z2(N-1);
switch (method) {
case METHOD_METR_SINGLE:
MST_linkage_core(N, D, Z2);
break;
case METHOD_METR_COMPLETE:
NN_chain_core<METHOD_METR_COMPLETE, t_float>(N, D__, NULL, Z2);
break;
case METHOD_METR_AVERAGE:
NN_chain_core<METHOD_METR_AVERAGE, t_float>(N, D__, members, Z2);
break;
case METHOD_METR_WEIGHTED:
NN_chain_core<METHOD_METR_WEIGHTED, t_float>(N, D__, NULL, Z2);
break;
case METHOD_METR_WARD:
NN_chain_core<METHOD_METR_WARD, t_float>(N, D__, members, Z2);
break;
case METHOD_METR_CENTROID:
generic_linkage<METHOD_METR_CENTROID, t_float>(N, D__, members, Z2);
break;
case METHOD_METR_MEDIAN:
generic_linkage<METHOD_METR_MEDIAN, t_float>(N, D__, NULL, Z2);
break;
default:
throw std::runtime_error(std::string("Invalid method."));
}
D__.free(); // Free the memory now
members.free(); // (not strictly necessary).
SEXP m; // return field "merge"
PROTECT(m = NEW_INTEGER(2*(N-1)));
int * const merge = INTEGER_POINTER(m);
SEXP dim_m; // Specify that m is an (N-1)×2 matrix
PROTECT(dim_m = NEW_INTEGER(2));
INTEGER(dim_m)[0] = N-1;
INTEGER(dim_m)[1] = 2;
SET_DIM(m, dim_m);
SEXP h; // return field "height"
PROTECT(h = NEW_NUMERIC(N-1));
double * const height = NUMERIC_POINTER(h);
SEXP o; // return fiels "order'
PROTECT(o = NEW_INTEGER(N));
int * const order = INTEGER_POINTER(o);
if (method==METHOD_METR_CENTROID ||
method==METHOD_METR_MEDIAN)
generate_R_dendrogram<true>(merge, height, order, Z2, N);
else
generate_R_dendrogram<false>(merge, height, order, Z2, N);
SEXP n; // names
PROTECT(n = NEW_CHARACTER(3));
SET_STRING_ELT(n, 0, COPY_TO_USER_STRING("merge"));
SET_STRING_ELT(n, 1, COPY_TO_USER_STRING("height"));
SET_STRING_ELT(n, 2, COPY_TO_USER_STRING("order"));
PROTECT(r = NEW_LIST(3)); // field names in the output list
SET_ELEMENT(r, 0, m);
SET_ELEMENT(r, 1, h);
SET_ELEMENT(r, 2, o);
SET_NAMES(r, n);
UNPROTECT(6); // m, dim_m, h, o, r, n
} // try
catch (const std::bad_alloc&) {
Rf_error( "Memory overflow.");
}
catch(const std::exception& e){
Rf_error( e.what() );
}
catch(const nan_error&){
Rf_error("NaN dissimilarity value.");
}
#ifdef FE_INVALID
catch(const fenv_error&){
Rf_error( "NaN dissimilarity value in intermediate results.");
}
#endif
catch(...){
Rf_error( "C++ exception (unknown reason)." );
}
return r;
}
