comparison src/AudioEventMatcher.cpp @ 7:33dedfe32893

kick, snare and bass windowed. Likelihoods in dedicated screen regions

 
 
 const int matchWindowWidth = 6000;
 
 AudioEventMatcher::AudioEventMatcher(){
-	bayesPositionWindow.setToRelativeSize(0, 0.4, 1, 0.2);
-	bayesTempoWindow.setToRelativeSize(0, 0.8, 1, 0.2);
-	bayesLikelihoodWindow.setToRelativeSize(0, 0.6, 1, 0.2);
-	
+
 	setArraySizes();
 	
 	usingRealTime = false;
 	bayesianStruct.realTimeMode = &usingRealTime;
-}
-
+	recentPitch = 0;
+}
+
+void AudioEventMatcher::setWindowDimensions(){
+	double startHeight = recordedTracks.numberOfAudioTracks * recordedTracks.trackScreenHeight;
+	double heightAvailable = 1 - startHeight;
+	heightAvailable /= 3.0;
+	
+	bayesPositionWindow.setToRelativeSize(0, startHeight, 1, heightAvailable);
+	bayesLikelihoodWindow.setToRelativeSize(0, startHeight + 1*heightAvailable, 1, heightAvailable);
+	bayesTempoWindow.setToRelativeSize(0, startHeight + 2*heightAvailable, 1, heightAvailable);
+	
+	
+}
 
 void AudioEventMatcher::setArraySizes(){
 	bayesianStruct.resetSpeedSize(200);
 	bayesianStruct.setRelativeSpeedScalar(0.01);
 	bayesianStruct.setSpeedPrior(1.0);

 	bayesPositionWindow.drawOutline();
 	bayesTempoWindow.drawOutline();
 	
 	//draw the scrolling audio tracks
 	recordedTracks.drawTracks();
+
+
 	
 	ofSetColor(255);
 //	bayesianStruct.relativeSpeedPrior.drawVector(0, 200, bayesTempoWindow);
 	
 	drawBayesianDistributions();

 	
 	//bayesianStruct.posterior.drawVector(bayesianStruct.posterior.getRealTermsAsIndex(0), bayesianStruct.posterior.getRealTermsAsIndex(screenWidthMillis), bayesPositionWindow);
 	
 	//	bayesianStruct.relativeSpeedPosterior.drawVector(0, bayesianStruct.relativeSpeedPosterior.getRealTermsAsIndex(2), bayesTempoWindow);
 	
+	ofDrawBitmapString("pitch "+ofToString(recentPitch, 2)+", Time "+ofToString(recentTime, 0), 20, 20);
 }
 	
 void AudioEventMatcher::drawBayesianDistributions(){
 	
 	

 	ofDrawBitmapString(tmpStr, 20, 180);
 	
 	ofDrawBitmapString("screenamp "+ofToString(screenWidthMillis), 20, 100);
 	
 	
+	
+	//draw track by track likelihoods
+	for (int i = 0; i <recordedTracks.numberOfAudioTracks;i++){
+		ofSetColor(200,255,50);
+		likelihoodVisualisation[i].drawConstrainedVector(startIndex, endIndex, 0, ofGetWidth(), recordedTracks.loadedAudioFiles[i].fileLoader.onsetDetect.window);		
+	}
+	
 }
 
 void AudioEventMatcher::newPitchEvent(const int& channel, const double& pitchIn, const double& timeIn){
+	if (pitchIn > 0){
 	liveInput.addPitchEvent(pitchIn, timeIn);
 	
 	//tmp print stuff
 	printf("New pitch MAP post estimate now %i, ", bayesianStruct.posterior.MAPestimate);
 	double tmp  = bayesianStruct.posterior.getMAPestimate();
 	printf(" getting it %f and offset %f == %f ms\n", tmp,  bayesianStruct.posterior.offset, bayesianStruct.posterior.getIndexInRealTerms(tmp));
 	
-	matchNewPitchEvent(channel, pitchIn, timeIn);
+	matchNewPitchEvent(channel, pitchIn, timeIn);//main pitch matching fn
+
+	likelihoodVisualisation[1] = bayesianStruct.likelihood;
+		
+	recentPitch = pitchIn;//for drawing
+	recentTime = timeIn;
+	}
 }
 
 void AudioEventMatcher::newKickEvent(const double& timeIn){	
 //	liveInput.addKickEvent(timeIn);
 	matchNewOnsetEvent(0, timeIn);
+	likelihoodVisualisation[0] = bayesianStruct.likelihood;
 }
 
 void AudioEventMatcher::newKickEvent(const int& channel, const double& timeIn){
 //	liveInput.addKickEvent(timeIn);
 	matchNewOnsetEvent(channel, timeIn);
+	likelihoodVisualisation[0] = bayesianStruct.likelihood;
 }
 
 
 void AudioEventMatcher::newSnareEvent(const double& timeIn){
 	matchNewOnsetEvent(2, timeIn);
+	likelihoodVisualisation[2] = bayesianStruct.likelihood;
+}
+
+
+void AudioEventMatcher::newSnareEvent(const int& channel, const double& timeIn){
+	matchNewOnsetEvent(channel, timeIn);
+	likelihoodVisualisation[2] = bayesianStruct.likelihood;
 }
 
 //Needs just to set bounds for the matching process, not have TimeIn
 void AudioEventMatcher::matchNewOnsetEvent(const int& channel, const double& timeIn){
 

 	//start at beginning but OPTIMISE later
 	
 	
 	bayesianStruct.updateBayesianDistributions(timeIn);//moves the posterior up into prior given the time interval and calculates new offsets
 	
-	///set offsets
-//	bayesianStruct.likelihood.offset = bayesianStruct.prior.offset;
-	double pitchLikelihoodToNoise = 0.2;//more noise
+	//set the lielihoods by matching the pitched note
+	
+	double pitchLikelihoodToNoise = 0.6;//more noise
 	int numberOfMatches = 0;
 	bayesianStruct.likelihood.zero();//set to zero
 	
 	double quantity = 0;
 	if (channel <= recordedTracks.numberOfAudioTracks){
 		for (int i = 0;i < recordedTracks.loadedAudioFiles[channel].fileLoader.onsetDetect.chromaOnsets.size();i++){
 			
 			if (checkMatch(recordedTracks.loadedAudioFiles[channel].fileLoader.onsetDetect.chromaOnsets[i].aubioPitch, pitchIn)) {
-				quantity = getPitchDistance(recordedTracks.loadedAudioFiles[channel].fileLoader.onsetDetect.chromaOnsets[i].aubioPitch, pitchIn, 20);
+				quantity = getPitchDistance(recordedTracks.loadedAudioFiles[channel].fileLoader.onsetDetect.chromaOnsets[i].aubioPitch, pitchIn, 10);
 				bayesianStruct.likelihood.addGaussianShapeFromRealTime(recordedTracks.loadedAudioFiles[channel].fileLoader.onsetDetect.chromaOnsets[i].millisTime, 30, quantity);
 				recordedTracks.loadedAudioFiles[channel].fileLoader.onsetDetect.chromaOnsets[i].matched = true;
 				numberOfMatches++;
 			} 
 			else{

 			
 		}
 	}
 
 	if (numberOfMatches > 0){//no point updating unless there is a match
+	
 		bayesianStruct.likelihood.addConstant(numberOfMatches*(1-pitchLikelihoodToNoise)/(pitchLikelihoodToNoise*bayesianStruct.likelihood.length));
 
 	//tmp set likelihood constant and calculate using that
 	//bayesianStruct.likelihood.zero();
 	//bayesianStruct.likelihood.addConstant(1);
-	
+		
 		bayesianStruct.calculatePosterior();
 	}
 	
 }