diff options
Diffstat (limited to 'rotord/src/nodes_audio_analysis.cpp')
| -rw-r--r-- | rotord/src/nodes_audio_analysis.cpp | 72 |
1 files changed, 2 insertions, 70 deletions
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; - } } } |