int Cluster_ReadInfo::Cluster() {
BufferedLine infile;
if (infile.OpenFileRead( filename_ )) return Err(0);
const char* ptr = infile.Line();
if (ptr == 0) return Err(1);
ArgList infoLine( ptr, " " );
int nclusters = infoLine.getKeyInt("#Clustering:", -1);
if (nclusters == -1) return Err(2);
int nframes = infoLine.getKeyInt("clusters", -1);
if (nframes == -1) return Err(3);
if (nframes != (int)FrameDistances_.Nframes()) {
mprinterr("Error: # frames in cluster info file (%i) does not match"
" current # frames (%zu)\n", nframes, FrameDistances_.Nframes());
return 1;
}
// Scan down to clusters
while (ptr[0] == '#') {
ptr = infile.Line();
if (ptr == 0) return Err(1);
// Save previous clustering info. Includes newline.
if (ptr[1] == 'A' && ptr[2] == 'l' && ptr[3] == 'g')
algorithm_.assign( ptr + 12 ); // Right past '#Algorithm: '
}
// Read clusters
ClusterDist::Cframes frames;
for (int cnum = 0; cnum != nclusters; cnum++) {
if (ptr == 0) return Err(1);
frames.clear();
// TODO: Check for busted lines?
for (int fidx = 0; fidx != nframes; fidx++) {
if (ptr[fidx] == 'X')
frames.push_back( fidx );
}
AddCluster( frames );
mprintf("\tRead cluster %i, %zu frames.\n", cnum, frames.size());
ptr = infile.Line();
}
infile.CloseFile();
mprintf("\tCalculating the distances between each cluster based on centroids.\n");
CalcClusterDistances();
return 0;
}
static double AvgCalc_Std( DataSet_1D const& dsIn, ClusterDist::Cframes const& cframesIn ) {
double val = 0.0;
for (ClusterDist::Cframes_it frm = cframesIn.begin(); frm != cframesIn.end(); ++frm)
val += dsIn.Dval( *frm );
return (val / (double)cframesIn.size());
}