From 502a92835949c5da869e1748790e6e090b9c4f94 Mon Sep 17 00:00:00 2001
From: Comment <tim@gray.(none)>
Date: Tue, 10 Dec 2013 01:50:19 +0000
Subject: branch rollback

---
 rotord/src/nodes_audio_analysis.cpp | 72 ++-----------------------------------
 1 file changed, 2 insertions(+), 70 deletions(-)

(limited to 'rotord/src')

diff --git a/rotord/src/nodes_audio_analysis.cpp b/rotord/src/nodes_audio_analysis.cpp
index f077d41..2a39d8c 100644
--- a/rotord/src/nodes_audio_analysis.cpp
+++ b/rotord/src/nodes_audio_analysis.cpp
@@ -122,7 +122,7 @@ namespace Rotor{
 
 		//how to group with similarity?
 		//segments come with similarity groups
-		// 1 - are the wanted segments less than discovered?
+		// 1 - are the wanted git checksegments less than discovered?
 		// N - do nothing
 		// 2 - get intensity and tempo averages
 		// 2 - count the groups
@@ -218,7 +218,7 @@ namespace Rotor{
 			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++) {
@@ -252,75 +252,7 @@ namespace Rotor{
 			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;
-		}
 	}
 }
 
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