Merge branch 'master' of eclectronics.org@eclectronics.org:rotor

Conflicts:
	rotord/src/nodes_audio_analysis.cpp

1 files changed, 121 insertions, 5 deletions

diff --git a/rotord/src/nodes_audio_analysis.cpp b/rotord/src/nodes_audio_analysis.cpp
index ea44048..f077d41 100644
--- a/rotord/src/nodes_audio_analysis.cpp
+++ b/rotord/src/nodes_audio_analysis.cpp
@@ -93,7 +93,7 @@ namespace Rotor{
 			if (i.second.values.size()) {
 				data+=" (";
 				bool first=true;
-				for (auto j: i.second.values) {	
+				for (auto j: i.second.values) {
 					if (first){
 						first=false;
 					}
@@ -101,7 +101,7 @@ namespace Rotor{
 					data=data+toString(j);
 				}
 				data+=") ";
-			}	
+			}
 			data+="]";
 		}
 		return data;
@@ -109,6 +109,10 @@ namespace Rotor{
 	bool sortsegments(std::pair<int,double> i,std::pair<int,double> j){
 		return (i.second<j.second);
 	}
+
+	bool sortseggrps(std::pair<double,vector<pair<double,int> > > i,std::pair<double,vector<pair<double,int> > > j){
+		return (i.first<j.first);
+	}
 	void Intensity_segmenter::cleanup(){
 		//algorithm idea:
 		//get average tempo and intensity for each segment and store them
@@ -131,10 +135,34 @@ namespace Rotor{
 		analysers["segmenter"].cleanup();
 		analysers["tempo"].cleanup();
 		analysers["intensity"].cleanup();
+
+		//combine with similarity numbers
+		// 1. count similarity numbers
+
+		map<int,vector<int> > similarities;
+
+		//what do we want to know about these similarities?
+		// how many are there? map.size()
+		// how many members are in each one? map[item].size()
+		// which members are they? auto m: map[item]
+
+		uint32_t i=0;
+		for (auto f:analysers["segmenter"].features) {
+			if (f.second.values.size()) {
+				int group=f.second.values[0];
+				if (similarities.find(group)==similarities.end()){
+					similarities[group]={};
+				}
+				similarities[group].push_back(i);
+			}
+			i++;
+		}
+		for (auto s:similarities) cerr<<"group "<<s.first<<" count: "<<s.second.size()<<endl;
+
 		cerr<<analysers["segmenter"].features.size()<<" segments"<<endl;
 		cerr<<analysers["tempo"].features.size()<<" tempo features"<<endl;
 		cerr<<analysers["intensity"].features.size()<<" intensity features"<<endl;
-		uint32_t i=0;
+		i=0;
 		double min_tempo=9999999.0;
 		double min_intensity=9999999.0;
 		double max_tempo=0.0;
@@ -182,11 +210,15 @@ namespace Rotor{
 		}
 		//make relative scale 0.0-1.0 and save weighted totals
 		vector< pair<int,double>> totals;
+		vector<double> totalsmap;
 		for (i=0;i<tempos.size();i++){
 			tempos[i]=(tempos[i]-min_tempo)/(max_tempo-min_tempo);
 			intensities[i]=(intensities[i]-min_intensity)/(max_intensity-min_intensity);
 			totals.push_back(make_pair(i,(tempos[i]*parameters["tempo_weight"]->value)+(intensities[i]*parameters["intensity_weight"]->value)));
+			totalsmap.push_back((tempos[i]*parameters["tempo_weight"]->value)+(intensities[i]*parameters["intensity_weight"]->value));
 		}
+
+		/*
 		//sort and convert to features
 		std::sort(totals.begin(),totals.end(),sortsegments);
 		for (i=0;i<totals.size();i++) {
@@ -214,10 +246,94 @@ namespace Rotor{
 				cerr<<endl;
 			}
 		}
+
 		for (i=0;i<totals.size();i++){
 			vampHost::feature f;
 			f.values.push_back((double)i-bucketoffsets[i]);
 			features[times[totals[i].first]]=f;
-		}			
+		}
+		*/
+
+		/*
+sort intensity totals
+find out how many segments will share levels apart from similarity levels
+start with a structure:
+map<inputnum,vector<pair<tempo,inputnum>>
+start grouping by similarity
+if there are more similarity groups than wantedgroups, start by grouping similarities
+otherwise take biggest similarity groups and split them by intensity
+if there are still too many groups, merge closest smallest groups
+finally sort by intensity to map output
+
+nned to retrieve total intensity by segment
+		*/
+		//  segment  group_intensity   seg_intense segment
+		vector<pair<double,vector<pair<double,int> > > > seggrps;
+		for (i=0;i<totalsmap.size();i++){
+		    vector<pair<double,int> > data;
+		    data.push_back(make_pair(totalsmap[i],i));
+			seggrps.push_back(make_pair(totalsmap[i],data));
+		}
+		for (auto s:similarities){
+			if (s.second.size()>1){
+				for (int j=s.second.size()-1;j>0;j--){
+				seggrps[s.second[0]].second.push_back(make_pair(totalsmap[s.second[j]],s.second[j]));
+				//keep running average// should be by area?
+				seggrps[s.second[0]].first+=(totalsmap[s.second[j]]*(1.0/max(1,(int)seggrps[s.second[0]].second.size()-1)));
+				double div=seggrps[s.second[0]].second.size()==1?1.0:((double)seggrps[s.second[0]].second.size()-1/(double)seggrps[s.second[0]].second.size());
+				//neat! this gives 1,1/2,2/3,3/4..
+				seggrps[s.second[0]].first*=div;
+				seggrps.erase(seggrps.begin()+s.second[j]);
+				}
+			}
+		}
+		cerr<<"similarities assigned, "<<(totalsmap.size()-seggrps.size())<<" segments merged"<<endl;
+		//sort the contents by intensity
+		std::sort(seggrps.begin(),seggrps.end(),sortseggrps);
+		//possible mergers will be with groups with adjacent intensity
+		while (seggrps.size()>(int)parameters["levels"]->value){
+			//reduce similarity groups
+			//decide the best 2 to merge
+			vector<double> diffs;
+			for (int j=0;j<seggrps.size()-1;j++) diffs.push_back(seggrps[j+1].first-seggrps[j].first);
+			int smallest=0;
+			for (int j=1;j<diffs.size();j++) if (diffs[i]<diffs[smallest]) smallest=i;
+			for (int j=0;j<seggrps[smallest].second.size();j++) {
+				seggrps[smallest+1].second.push_back(seggrps[smallest].second[j]);
+			}
+			seggrps.erase(seggrps.begin()+smallest);
+		}
+		cerr<<"intensities merged, "<<seggrps.size()<<" levels remain"<<endl;
+		while (seggrps.size()<(int)parameters["levels"]->value) {
+			//split groups
+		}
+
+		map<int,int> outputvalues;
+		for (int j=0;j<seggrps.size();j++){
+			for (int k=0;k<seggrps[j].second.size();k++){
+				outputvalues[seggrps[j].second[k].second]=j;
+			}
+		}
+
+
+		for (i=0;i<totals.size();i++){
+			vampHost::feature f;
+			f.values.push_back(outputvalues[i]);
+			features[times[totals[i].first]]=f;
+		}
 	}
-}
\ No newline at end of file
+}
+
+/*
+A data structure to represent segments and their mapping to output levels
+how do we merge the intensity groups with the similarities?
+
+we create a list
+
+
+
+
+... we iterate through the list of segments and place the right output number
+
+
+*/