Mercurial > hg > segmenter-vamp-plugin
changeset 55:6eef91b899b7
Remove unneeded boost includes and generic arma namespace import
| author | Chris Cannam |
|---|---|
| date | Thu, 13 Jun 2013 12:31:32 +0100 |
| parents | 78c9e83939bd |
| children | e2e09a2196a9 |
| files | Makefile.linux64 segmentino/Segmentino.cpp |
| diffstat | 2 files changed, 30 insertions(+), 37 deletions(-) [+] |
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--- a/Makefile.linux64 Thu Jun 13 12:11:26 2013 +0100 +++ b/Makefile.linux64 Thu Jun 13 12:31:32 2013 +0100 @@ -1,7 +1,7 @@ -#CFLAGS := -O3 -fPIC -ftree-vectorize -I../armadillo-2.4.4/include -I../../vamp-plugin-sdk -I../../qm-dsp +CFLAGS := -O3 -fPIC -ftree-vectorize -CFLAGS := -Wall -g -fPIC +#CFLAGS := -Wall -g -fPIC CXXFLAGS := $(CFLAGS)
--- a/segmentino/Segmentino.cpp Thu Jun 13 12:11:26 2013 +0100 +++ b/segmentino/Segmentino.cpp Thu Jun 13 12:31:32 2013 +0100 @@ -27,10 +27,6 @@ #include <nnls-chroma/chromamethods.h> -#include <boost/numeric/ublas/matrix.hpp> -#include <boost/numeric/ublas/io.hpp> -#include <boost/math/distributions/normal.hpp> - #include <armadillo> #include <fstream> @@ -40,15 +36,12 @@ #include <vamp-sdk/Plugin.h> -using namespace boost::numeric; -using namespace arma; using std::string; using std::vector; using std::cerr; using std::cout; using std::endl; - #ifndef __GNUC__ #include <alloca.h> #endif @@ -1235,8 +1228,8 @@ { arma::vec sortV = arma::sort(v); int n = sortV.size(); - arma::vec x = arma::zeros<vec>(n+2); - arma::vec y = arma::zeros<vec>(n+2); + arma::vec x = arma::zeros<arma::vec>(n+2); + arma::vec y = arma::zeros<arma::vec>(n+2); x(0) = 0; x(n+1) = 100; @@ -1284,12 +1277,12 @@ else endWin = i+len-1; - outmat(i,span::all) = arma::max(inmat(span(startWin,endWin),span::all)); + outmat(i,arma::span::all) = + arma::max(inmat(arma::span(startWin,endWin),arma::span::all)); } } return outmat; - } // Null Parts @@ -1309,7 +1302,7 @@ Part newPart; newPart.n = 1; - uvec q = find(nullindices > 0); + arma::uvec q = find(nullindices > 0); for (int i=0; i<(int)q.size();++i) newPart.indices.push_back(q(i)); @@ -1417,7 +1410,7 @@ // Build a ObservationTOFeatures Matrix - arma::mat featVal = arma::zeros<mat>(nBeat,nFeatValues/2); + arma::mat featVal = arma::zeros<arma::mat>(nBeat,nFeatValues/2); for (int i = 0; i < nBeat; ++ i) for (int j = 0; j < nFeatValues/2; ++ j) @@ -1486,14 +1479,14 @@ potential_duplicates = trimatu(potential_duplicates); int nPartlengths = round((maxlength-minlength)/4)+1; - arma::vec partlengths = zeros<arma::vec>(nPartlengths); + arma::vec partlengths = arma::zeros<arma::vec>(nPartlengths); for (int i = 0; i < nPartlengths; ++ i) partlengths(i) = (i*4) + minlength; // initialise arrays - arma::cube simArray = zeros<arma::cube>(nBeat,nBeat,nPartlengths); - arma::cube decisionArray2 = zeros<arma::cube>(nBeat,nBeat,nPartlengths); + arma::cube simArray = arma::zeros<arma::cube>(nBeat,nBeat,nPartlengths); + arma::cube decisionArray2 = arma::zeros<arma::cube>(nBeat,nBeat,nPartlengths); for (int iLength = 0; iLength < nPartlengths; ++ iLength) // for (int iLength = 0; iLength < 20; ++ iLength) @@ -1505,36 +1498,36 @@ for (int iBeat = 0; iBeat < nUsedBeat; ++ iBeat) // looping over all columns (arbitrarily chosen columns) { - arma::uvec help2 = find(potential_duplicates(span(0,nUsedBeat-1),iBeat)==1); + arma::uvec help2 = find(potential_duplicates(arma::span(0,nUsedBeat-1),iBeat)==1); for (int i=0; i < (int)help2.size(); ++i) { // measure how well two length len segments go together int kBeat = help2(i); - arma::vec distrib = median_simmat(span(iBeat,iBeat+len-1),span(kBeat,kBeat+len-1)).diag(0); + arma::vec distrib = median_simmat(arma::span(iBeat,iBeat+len-1), arma::span(kBeat,kBeat+len-1)).diag(0); simArray(iBeat,kBeat,iLength) = quantile(distrib,quantilePerc); } } - arma::mat tempM = simArray(span(0,nUsedBeat-1),span(0,nUsedBeat-1),span(iLength,iLength)); - simArray.slice(iLength)(span(0,nUsedBeat-1),span(0,nUsedBeat-1)) = tempM + arma::trans(tempM) - (eye<mat>(nUsedBeat,nUsedBeat)%tempM); + arma::mat tempM = simArray(arma::span(0,nUsedBeat-1), arma::span(0,nUsedBeat-1), arma::span(iLength,iLength)); + simArray.slice(iLength)(arma::span(0,nUsedBeat-1), arma::span(0,nUsedBeat-1)) = tempM + arma::trans(tempM) - (arma::eye<arma::mat>(nUsedBeat,nUsedBeat)%tempM); // convolution - arma::vec K = arma::zeros<vec>(3); + arma::vec K = arma::zeros<arma::vec>(3); K << 0.01 << 0.98 << 0.01; for (int i=0; i < (int)simArray.n_rows; ++i) { arma::rowvec t = arma::conv((arma::rowvec)simArray.slice(iLength).row(i),K); - simArray.slice(iLength)(i,span::all) = t.subvec(1,t.size()-2); + simArray.slice(iLength)(i, arma::span::all) = t.subvec(1,t.size()-2); } // take only over-average bars that do not overlap - arma::mat temp = arma::zeros<mat>(simArray.n_rows, simArray.n_cols); - temp(span::all, span(0,nUsedBeat-1)) = simArray.slice(iLength)(span::all,span(0,nUsedBeat-1)); + arma::mat temp = arma::zeros<arma::mat>(simArray.n_rows, simArray.n_cols); + temp(arma::span::all, arma::span(0,nUsedBeat-1)) = simArray.slice(iLength)(arma::span::all, arma::span(0,nUsedBeat-1)); for (int i=0; i < (int)temp.n_rows; ++i) for (int j=0; j < nUsedBeat; ++j) @@ -1576,7 +1569,7 @@ for (int iBeat=0; iBeat < nBeat; ++iBeat) if (currLogicSum(iBeat) > 1) { - arma::vec t = decisionArray2.slice(iLength)(span::all,iBeat); + arma::vec t = decisionArray2.slice(iLength)(arma::span::all,iBeat); double currSum = sum(t); int count = 0; @@ -1615,8 +1608,8 @@ double m = t.max(); - bestval(span::all,1) = bestval(span::all,1) / m; - bestval(span::all,0) = bestval(span::all,0) + bestval(span::all,1); + bestval(arma::span::all,1) = bestval(arma::span::all,1) / m; + bestval(arma::span::all,0) = bestval(arma::span::all,0) + bestval(arma::span::all,1); arma::mat bestval2; for (int i=0; i < (int)bestval.n_cols; ++i) @@ -1633,14 +1626,14 @@ arma::vec t1 = currbestvals.col(0); double ma; - uword maIdx; + arma::uword maIdx; ma = t1.max(maIdx); if ((maIdx == 0)&&(ma == 0)) break; int bestLength = lrint(partlengths(currbestvals(maIdx,1))); - arma::rowvec bestIndices = decisionArray2.slice(currbestvals(maIdx,1))(currbestvals(maIdx,2),span::all); + arma::rowvec bestIndices = decisionArray2.slice(currbestvals(maIdx,1))(currbestvals(maIdx,2), arma::span::all); arma::rowvec bestIndicesMap = arma::zeros<arma::rowvec>(bestIndices.size()); for (int i=0; i < (int)bestIndices.size(); ++i) @@ -1657,7 +1650,7 @@ // Save results in the structure Part newPart; newPart.n = bestLength; - uvec q1 = find(bestIndices > 0); + arma::uvec q1 = find(bestIndices > 0); for (int i=0; i < (int)q1.size();++i) newPart.indices.push_back(q1(i)); @@ -1667,7 +1660,7 @@ newPart.level = kSeg+1; parts.push_back(newPart); - uvec q2 = find(valid_sets==1); + arma::uvec q2 = find(valid_sets==1); for (int i=0; i < (int)q2.size(); ++i) { @@ -1678,7 +1671,7 @@ for (int i=0; i<s; ++i) mask1(i+s-1) = 1; - arma::rowvec Ind = decisionArray2.slice(bestval2(iSet,1))(bestval2(iSet,2),span::all); + arma::rowvec Ind = decisionArray2.slice(bestval2(iSet,1))(bestval2(iSet,2), arma::span::all); arma::rowvec IndMap = arma::zeros<arma::rowvec>(Ind.size()); for (int i=0; i < (int)Ind.size(); ++i) if (Ind(i)>0) @@ -1706,7 +1699,7 @@ parts.push_back(newPart); } - arma::vec bar = linspace(1,nBeat,nBeat); + arma::vec bar = arma::linspace(1,nBeat,nBeat); Part np = nullpart(parts,bar); parts.push_back(np); @@ -1742,7 +1735,7 @@ int nBeat = quantisedChromagram.size(); // Number of feature vector int nFeatValues = quantisedChromagram[0].values.size(); // Number of values for each feature vector - arma::mat synchTreble = arma::zeros<mat>(nBeat,nFeatValues/2); + arma::mat synchTreble = arma::zeros<arma::mat>(nBeat,nFeatValues/2); for (int i = 0; i < nBeat; ++ i) for (int j = 0; j < nFeatValues/2; ++ j) @@ -1750,7 +1743,7 @@ synchTreble(i,j) = quantisedChromagram[i].values[j]; } - arma::mat synchBass = arma::zeros<mat>(nBeat,nFeatValues/2); + arma::mat synchBass = arma::zeros<arma::mat>(nBeat,nFeatValues/2); for (int i = 0; i < nBeat; ++ i) for (int j = 0; j < nFeatValues/2; ++ j)