diff bayesianArraySrc/BayesianArrayStructure.cpp @ 0:c4f9e49226eb

Initialising repository. Live osc input registered. Files analysed offline.

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/bayesianArraySrc/BayesianArrayStructure.cpp	Tue Jan 31 13:54:17 2012 +0000
@@ -0,0 +1,585 @@
+/*
+ *  BayesianArrayStructure.cpp
+ *  midiCannamReader
+ *
+ *  Created by Andrew on 17/07/2011.
+ *  Copyright 2011 QMUL. All rights reserved.
+ *
+ */
+
+//look at reset speed to one - what does this do? - get rid of?
+
+
+#include "BayesianArrayStructure.h"
+
+BayesianArrayStructure::BayesianArrayStructure(){
+	printf("Bayesian structure: DeFault constructor called");
+
+	usingIntegratedTempoEstimate = true;// use max index
+	
+	relativeSpeedLikelihoodStdDev = 5.0;
+	
+	prior.createVector(1);
+	likelihood.createVector(1);
+	posterior.createVector(1);
+
+	speedPriorValue = 1.0;//default value for the speed prior
+	speedEstimate = speedPriorValue;
+	
+	lastEventTime = 0;//ofGetElapsedTimeMillis();
+
+	tmpBestEstimate = 0;
+	crossUpdateTimeThreshold = 60;
+	priorWidth = 50;
+	
+}
+
+BayesianArrayStructure::BayesianArrayStructure(int length){
+	printf("BAYESIAN STURCTURE CREATED LENGTH: %i\n", length);
+	//this constructor isnt called  it seems
+	prior.createVector(length);
+	likelihood.createVector(length);
+	posterior.createVector(length);
+	
+	lastEventTime = 0;
+	
+
+}
+
+
+
+void BayesianArrayStructure::resetSize(int length){
+	printf("BAYESIAN STRUCTURE size is : %i\n", length);
+	
+	prior.createVector(length);
+	likelihood.createVector(length);
+	posterior.createVector(length);
+	
+	acceleration.createVector(length);
+	
+}
+
+void BayesianArrayStructure::resetSpeedSize(int length){
+	printf("BAYESIAN reset SPEED size is : %i\n", length);
+	
+	relativeSpeedPrior.createVector(length);
+	relativeSpeedLikelihood.createVector(length);
+	relativeSpeedPosterior.createVector(length);
+	tmpPosteriorForStorage.createVector(length);
+	
+	
+
+}
+
+void BayesianArrayStructure::setRelativeSpeedScalar(double f){
+	relativeSpeedPrior.scalar = f;
+	relativeSpeedPosterior.scalar = f;
+	relativeSpeedLikelihood.scalar = f;
+}
+
+void BayesianArrayStructure::resetSpeedToOne(){
+	relativeSpeedPrior.zero();
+	relativeSpeedPosterior.zero();
+	relativeSpeedLikelihood.zero();
+	
+	
+	relativeSpeedPosterior.addGaussianShape(100, 20, 0.8);
+	relativeSpeedPosterior.renormalise();
+	relativeSpeedPosterior.getMaximum();
+	
+	setSpeedPrior(speedPriorValue);
+	speedEstimate = speedPriorValue;
+	
+	prior.zero();
+	posterior.zero();
+	
+	posterior.addToIndex(0, 1);
+	posterior.renormalise();
+	
+}
+
+void BayesianArrayStructure::setSpeedPrior(double f){	
+	speedPriorValue = f;
+	int index = relativeSpeedPosterior.getRealTermsAsIndex(speedPriorValue);
+	relativeSpeedPosterior.zero();
+	relativeSpeedPosterior.addGaussianShape(index, priorWidth, 0.8);
+	relativeSpeedPosterior.renormalise();
+	relativeSpeedPosterior.getMaximum();
+	relativeSpeedPrior.copyFromDynamicVector(relativeSpeedPosterior);
+	printf("BAYES STRUCTU ' SPEED PRIOR %f . index %i\n", speedPriorValue, index);
+	
+}
+
+
+void BayesianArrayStructure::setPositionDistributionScalar(double f){
+	if (f > 0){
+	prior.scalar = f;
+	posterior.scalar = f;
+	likelihood.scalar = f;
+	}
+}
+
+void BayesianArrayStructure::simpleExample(){
+	relativeSpeedPosterior.getMaximum();
+	relativeSpeedPrior.copyFromDynamicVector(relativeSpeedPosterior);
+}
+
+void BayesianArrayStructure::copyPriorToPosterior(){
+
+	for (int i = 0;i < prior.arraySize;i++){
+		posterior.array[i] = prior.array[i];
+	}
+}
+
+void BayesianArrayStructure::setStartPlaying(){
+	
+	lastEventTime = 0;
+	bestEstimate = 0;
+	lastBestEstimateUpdateTime = 0;
+	if (*realTimeMode)
+		lastBestEstimateUpdateTime = ofGetElapsedTimeMillis();
+	//cannot just be zero - offline bug
+	//printf("start playing - best estimate %f\n", lastBestEstimateUpdateTime);
+	
+	resetArrays();
+}
+
+void BayesianArrayStructure::resetArrays(){
+	//called when we start playing
+	
+	prior.zero();
+	likelihood.zero();
+	posterior.zero();
+	
+	updateCounter = 0;
+	
+	posterior.offset = -1000;
+	setNewDistributionOffsets(0);
+	
+	int zeroIndex = posterior.getRealTermsAsIndex(0);
+	
+	posterior.addGaussianShape(zeroIndex, 500, 1);
+	//	posterior.addToIndex(0, 1);
+	likelihood.addConstant(1);
+	
+	updateCounter = 0;
+	
+
+	printf("bayes reset arrays - best estimate %f\n", lastBestEstimateUpdateTime);
+	
+	setSpeedPrior(speedPriorValue);
+}
+
+
+void BayesianArrayStructure::zeroArrays(){
+	prior.zero();
+	likelihood.zero();
+	posterior.zero();
+	
+	relativeSpeedPrior.zero();
+	relativeSpeedPosterior.zero();
+	relativeSpeedLikelihood.zero();
+
+}
+
+
+void BayesianArrayStructure::updateTmpBestEstimate(const double& timeDifference){
+	//input is the time since the start of playing
+//	double timeDiff = ofGetElapsedTimeMillis() - lastEventTime;//lastBestEstimateUpdateTime;
+	double timeDiff = timeDifference;
+	if (*realTimeMode)
+		timeDiff = ofGetElapsedTimeMillis() - lastBestEstimateUpdateTime;
+
+	double tmp = relativeSpeedPosterior.getIntegratedEstimate();
+	tmpBestEstimate = posterior.getIndexInRealTerms(posterior.MAPestimate) + timeDiff*relativeSpeedPosterior.getIndexInRealTerms(relativeSpeedPosterior.integratedEstimate);
+	// 
+	//printf("tmp best %f and best %f time diff %f posterior MAP %f at speed %f\n", 0Estimate, bestEstimate, timeDifference, posterior.getIndexInRealTerms(posterior.MAPestimate), relativeSpeedPosterior.getIndexInRealTerms(relativeSpeedPosterior.integratedEstimate));
+	//lastBestEstimateUpdateTime = ofGetElapsedTimeMillis();
+}
+	
+void BayesianArrayStructure::updateBestEstimate(const double& timeDifference){
+//	double timeDiff = ofGetElapsedTimeMillis() - lastEventTime;//
+	
+	double timeDiff = timeDifference;
+	
+	//Using timedifferencfe here will make it go wrong. Is time since beginning of playing
+	
+	if (*realTimeMode)
+		timeDiff = ofGetElapsedTimeMillis() - lastBestEstimateUpdateTime;
+	
+	//lastbest is time we started playing
+	
+	if (usingIntegratedTempoEstimate)
+		speedEstimateIndex = relativeSpeedPosterior.getIntegratedEstimate();
+	else
+		speedEstimateIndex = relativeSpeedPosterior.MAPestimate;
+	
+	speedEstimate = relativeSpeedPosterior.getIndexInRealTerms(speedEstimateIndex);
+	bestEstimate = posterior.getIndexInRealTerms(posterior.MAPestimate) + timeDiff*speedEstimate;
+	
+}
+
+void BayesianArrayStructure::calculatePosterior(){
+	//posterior.doProduct(prior, likelihood);
+	
+	int i;
+	for (i = 0;i < posterior.length;i++){
+		posterior.array[i] = likelihood.array[i] * prior.array[i];
+	}
+	
+	posterior.renormalise();
+	
+}
+
+
+
+
+void BayesianArrayStructure::setNewDistributionOffsets(const double& newOffset){
+	prior.offset = newOffset;
+	likelihood.offset = newOffset;
+	//posterior.offset = newOffset;
+}
+
+
+void BayesianArrayStructure::crossUpdateArrays(DynamicVector& position, DynamicVector& speed, double timeDifference){
+	//set the cutoff for offset of position first! XXX
+	
+//	printf("time difference %f, ", timeDifference);
+	
+	double timeDifferenceInPositionVectorUnits = timeDifference / prior.scalar;
+	
+
+	prior.zero();//kill prior
+	calculateNewPriorOffset(timeDifference);//set new prior offset here
+	
+	if (timeDifferenceInPositionVectorUnits > crossUpdateTimeThreshold)
+		complexCrossUpdate(timeDifferenceInPositionVectorUnits);
+	else
+		translateByMaximumSpeed(timeDifferenceInPositionVectorUnits);	
+			
+
+	updateCounter++;
+	prior.renormalise();
+
+}
+
+void BayesianArrayStructure::complexCrossUpdate(const double& timeDifferenceInPositionVectorUnits){
+	int distanceMoved, newPriorIndex;
+	
+	double speedValue = relativeSpeedPosterior.offset;
+	
+	for (int i = 0;i < relativeSpeedPosterior.arraySize;i++){
+		
+	//	double speedValue = relativeSpeedPosterior.getIndexInRealTerms(i);//so for scalar 0.01, 50 -> speed value of 0.5
+		
+		//so we have moved 
+		distanceMoved = round(timeDifferenceInPositionVectorUnits * speedValue);//round the value
+	
+		if (relativeSpeedPosterior.array[i] != 0){
+			double speedContribution = relativeSpeedPosterior.array[i];
+			//	printf("speed [%i] gives %f moved %i in %f units \n", i, speedValue, distanceMoved, timeDifferenceInPositionVectorUnits);
+			
+			newPriorIndex = posterior.offset - prior.offset + distanceMoved;
+			
+			for (int postIndex = 0;postIndex < posterior.arraySize;postIndex++){
+				//old posterior contributing to new prior
+			//	newPriorIndex = postIndex + posterior.offset - prior.offset + distanceMoved;
+				
+				if (newPriorIndex >= 0 && newPriorIndex < prior.arraySize){
+					prior.addToIndex(newPriorIndex, posterior.array[postIndex]*speedContribution);
+				}
+				
+				newPriorIndex++;//optimised code - the commented line above explains how this works
+			}//end for
+			
+			
+		}//if not zero
+		speedValue += relativeSpeedPosterior.scalar;
+		//optimised line
+		//as we wanted:
+		//	double speedValue = relativeSpeedPosterior.getIndexInRealTerms(i);//so for scalar 0.01, 50 -> speed value of 0.5
+	}//end speed
+}
+
+
+
+void BayesianArrayStructure::translateByMaximumSpeed(const double& timeDifferenceInPositionVectorUnits){
+
+	int distanceMoved, newPriorIndex;
+	
+	double speedValue = relativeSpeedPosterior.getIndexInRealTerms(relativeSpeedPosterior.integratedEstimate);
+	//so for scalar 0.01, 50 -> speed value of 0.5
+	double speedContribution = relativeSpeedPosterior.array[relativeSpeedPosterior.integratedEstimate];
+		//so we have moved 
+		distanceMoved = round(timeDifferenceInPositionVectorUnits * speedValue);//round the value
+					//	printf("speed [%i] gives %f moved %i in %f units \n", i, speedValue, distanceMoved, timeDifferenceInPositionVectorUnits);
+			
+			for (int postIndex = 0;postIndex < posterior.arraySize;postIndex++){
+				//old posterior contributing to new prior
+				newPriorIndex = postIndex + posterior.offset - prior.offset + distanceMoved;
+				if (newPriorIndex >= 0 && newPriorIndex < prior.arraySize){
+					prior.addToIndex(newPriorIndex, posterior.array[postIndex]*speedContribution);
+				}
+				
+			}
+	
+}
+
+void BayesianArrayStructure::addGaussianNoiseToSpeedPosterior(const double& std_dev){
+	tmpPosteriorForStorage.copyFromDynamicVector(relativeSpeedPosterior);
+	
+	for (int i = 0;i < relativeSpeedPosterior.length;i++){
+		tmpPosteriorForStorage.addGaussianShape(i, std_dev, relativeSpeedPosterior.array[i]);
+		}
+												
+	tmpPosteriorForStorage.renormalise();
+	
+	relativeSpeedPosterior.copyFromDynamicVector(tmpPosteriorForStorage);											
+}
+
+
+void BayesianArrayStructure::addTriangularNoiseToSpeedPosterior(const double& std_dev){
+	tmpPosteriorForStorage.copyFromDynamicVector(relativeSpeedPosterior);
+	
+	for (int i = 0;i < relativeSpeedPosterior.length;i++){
+		//adding a linear amount depending on distance
+		tmpPosteriorForStorage.addTriangularShape(i, std_dev*2.0, relativeSpeedPosterior.array[i]);
+	}
+	
+	tmpPosteriorForStorage.renormalise();
+	
+	relativeSpeedPosterior.copyFromDynamicVector(tmpPosteriorForStorage);											
+}
+
+void BayesianArrayStructure::calculateNewPriorOffset(const double& timeDifference){
+	
+	double maxSpeed = relativeSpeedPosterior.getIndexInRealTerms(relativeSpeedPosterior.integratedEstimate);
+	//	printf("Maxspeed is %f\n", maxSpeed);
+	
+	double priorMax = posterior.getMaximum();
+	double distanceTravelled = maxSpeed * (timeDifference / prior.scalar);
+	double newMaxLocation = posterior.MAPestimate + distanceTravelled;
+	//	printf("MAP: %i, tim df %f, distance %f, new location %f\n", posterior.MAPestimate, timeDifference, distanceTravelled, newMaxLocation);
+	
+}
+
+
+void BayesianArrayStructure::decaySpeedDistribution(double timeDifference){
+	
+	// commented for the moment
+	 double relativeAmount = max(1.0, timeDifference/1000.);
+//	printf("decay %f around %i \n", timeDifference, relativeSpeedPosterior.MAPestimate);
+	relativeAmount *= speedDecayAmount;
+	relativeSpeedPosterior.renormalise();
+	relativeSpeedPosterior.addGaussianShape(relativeSpeedPosterior.MAPestimate, speedDecayWidth, relativeAmount);
+	
+	relativeSpeedPosterior.renormalise();
+	double newMax = relativeSpeedPosterior.getMaximum();
+	
+	//old code
+//	relativeSpeedPosterior.addGaussianShape(relativeSpeedPosterior.MAPestimate, speedDecayWidth, 10);
+	//relativeSpeedPosterior.addConstant(1);
+	
+	/*
+	relativeSpeedPrior.copyFromDynamicVector(relativeSpeedPosterior);
+	relativeSpeedLikelihood.zero();
+	relativeSpeedLikelihood.addConstant(0.2);
+	relativeSpeedLikelihood.addGaussianShape(relativeSpeedPosterior.maximumValue, speedDecayWidth, relativeAmount);
+	relativeSpeedPosterior.doProduct(relativeSpeedPrior, relativeSpeedLikelihood);
+	relativeSpeedPosterior.renormalise();
+	 */
+	
+
+	
+}
+
+void BayesianArrayStructure::setLikelihoodToConstant(){
+	//set new likelihood
+	relativeSpeedLikelihood.zero();
+	relativeSpeedLikelihood.addConstant(speedLikelihoodNoise);
+}
+
+
+void BayesianArrayStructure::updateTempoLikelihood(const double& speedRatio, const double& matchFactor){
+	
+	//speedratio is speed of played relative to the recording
+	
+	double index = relativeSpeedLikelihood.getRealTermsAsIndex(speedRatio);
+	//	printf("index of likelihood would be %f for ratio %f\n", index, speedRatio);
+	if (index >= 0 && index < relativeSpeedPrior.length){	
+		relativeSpeedLikelihood.addGaussianShape(index , relativeSpeedLikelihoodStdDev, matchFactor);
+	}
+}
+	
+
+
+void BayesianArrayStructure::updateTempoDistribution(){
+
+	//copy posterior to prior
+	relativeSpeedPrior.copyFromDynamicVector(relativeSpeedPosterior);
+
+	//update
+	relativeSpeedPosterior.doProduct(relativeSpeedPrior, relativeSpeedLikelihood);
+
+	//normalise
+	relativeSpeedPosterior.renormalise();
+		
+	relativeSpeedPosterior.getMaximum();	
+	
+	//relativeSpeedPosterior.updateIntegratedEstimate(); - could be swayed when off to side 
+	//so now limited to where there is room sround the MAP estimate
+	relativeSpeedPosterior.updateLimitedIntegratedEstimate();
+	
+	speedEstimate = relativeSpeedPosterior.getIndexInRealTerms(relativeSpeedPosterior.integratedEstimate);
+}
+
+
+void BayesianArrayStructure::calculateTempoUpdate(){
+	//copy posterior to prior
+	relativeSpeedPrior.copyFromDynamicVector(relativeSpeedPosterior);
+	
+	//update
+	relativeSpeedPosterior.doProduct(relativeSpeedPrior, relativeSpeedLikelihood);
+	
+	//normalise
+	relativeSpeedPosterior.renormalise();
+	
+	relativeSpeedPosterior.getMaximum();	
+	
+}
+
+
+void BayesianArrayStructure::drawArrays(){
+	
+	//bayesArray.drawFloatArray(&bayesArray.prior[0], 0, 200);
+	//bayesArray.drawFloatArray(&bayesArray.prior[0], 0, 200);
+	
+	int displaySize = prior.arraySize;
+	ofSetColor(0,0,255);
+	prior.drawVector(0, displaySize);
+	ofSetColor(0,255,0);
+	likelihood.drawVector(0, displaySize);
+	ofSetColor(255,0,255);
+	posterior.drawVector(0, displaySize);
+	
+	
+	
+}
+
+
+void BayesianArrayStructure::drawTempoArrays(){
+	ofSetColor(0,0,255);
+//	relativeSpeedPrior.drawVector(0, relativeSpeedPrior.arraySize);
+	
+	ofSetColor(0,150,255);
+	relativeSpeedLikelihood.drawVector(0, relativeSpeedLikelihood.arraySize);
+	
+//	relativeSpeedLikelihood.drawConstrainedVector(0, 199, 0, 1000);// relativeSpeedLikelihood.arraySize);	
+	ofSetColor(255,0,0);
+	relativeSpeedPosterior.drawVector(0, relativeSpeedPosterior.arraySize);
+	
+//	ofSetColor(0,0,255);
+//	tmpPosteriorForStorage.drawVector(0, tmpPosteriorForStorage.arraySize);
+	
+	ofSetColor(255,255, 255);
+	ofLine(screenWidth/2, 0, screenWidth/2, ofGetHeight());//middle of screen
+	
+	ofSetColor(25, 0, 250);
+	double fractionOfScreen = ((double)relativeSpeedPosterior.integratedEstimate / relativeSpeedPosterior.length);
+	ofLine(screenWidth * fractionOfScreen, 0, screenWidth * fractionOfScreen, ofGetHeight());
+	
+	ofSetColor(255, 0, 20);
+	fractionOfScreen = ((double)relativeSpeedPosterior.MAPestimate / relativeSpeedPosterior.length);
+	ofLine(screenWidth * fractionOfScreen, 0, screenWidth * fractionOfScreen, ofGetHeight());
+	 
+	
+}
+
+
+void BayesianArrayStructure::drawArraysRelativeToTimeframe(const double& startTimeMillis, const double& endTimeMillis){
+
+	screenWidth = ofGetWidth();
+	
+	int startArrayIndex = 0;
+	
+	if (prior.getIndexInRealTerms(prior.arraySize-1) > startTimeMillis){
+		//i.e. the array is on the page
+	
+	while (prior.getIndexInRealTerms(startArrayIndex) < startTimeMillis){
+		startArrayIndex++;
+	}
+	int endArrayIndex = prior.arraySize-1;
+	//could find constraints here
+	if (prior.getIndexInRealTerms(prior.arraySize-1) > endTimeMillis)
+		endArrayIndex = (floor)((endTimeMillis - prior.offset)/prior.scalar);
+	
+	//so we need to figure where start and end array are on screen
+	int startScreenPosition, endScreenPosition;
+	double screenWidthMillis = endTimeMillis - startTimeMillis;
+		
+	startScreenPosition = (prior.getIndexInRealTerms(startArrayIndex) - startTimeMillis)*screenWidth/screenWidthMillis;
+	endScreenPosition = (double)(prior.getIndexInRealTerms(endArrayIndex) - startTimeMillis)*screenWidth/screenWidthMillis;
+		
+	ofSetColor(0,0,100);
+	string relativeString = " offset "+ofToString(prior.offset, 1);//starttimes("+ofToString(startTimeMillis)+", "+ofToString(endTimeMillis);
+	relativeString += ": index "+ofToString(startArrayIndex)+" , "+ofToString(endArrayIndex)+" [";
+//	relativeString += ofToString(prior.getIndexInRealTerms(endArrayIndex), 3)+"] (sc-width:"+ofToString(screenWidthMillis, 1)+")  ";
+	relativeString += " mapped to screen "+ofToString(startScreenPosition)+" , "+ofToString(endScreenPosition);
+//	ofDrawBitmapString(relativeString, 100, 180);
+	
+		
+		
+	ofSetColor(100,100,100);//255, 255, 0);
+	likelihood.drawConstrainedVector(startArrayIndex, endArrayIndex, startScreenPosition, endScreenPosition);
+
+//	ofSetColor(0,0,200);
+	ofSetColor(170,170,170);//00,200);
+	prior.drawConstrainedVector(startArrayIndex, endArrayIndex, startScreenPosition, endScreenPosition);
+		
+		ofSetColor(0,0,150);	
+//	ofSetColor(200, 0, 0);
+	posterior.drawConstrainedVector(startArrayIndex, endArrayIndex, startScreenPosition, endScreenPosition);
+		
+		
+//	ofSetColor(0, 200, 255);
+//	acceleration.drawConstrainedVector(startArrayIndex, endArrayIndex, startScreenPosition, endScreenPosition);
+		
+		
+	}
+
+}
+
+
+/*
+ 
+ void BayesianArrayStructure::updateTempoDistribution(const double& speedRatio, const double& matchFactor){
+ //speedratio is speed of played relative to the recording
+ 
+ double index = relativeSpeedLikelihood.getRealTermsAsIndex(speedRatio);
+ //	printf("\nindex of likelihood would be %f\n", index);
+ if (index >= 0 && index < relativeSpeedPrior.length){
+ //then we can do update
+ 
+ //set new likelihood
+ relativeSpeedLikelihood.zero();
+ relativeSpeedLikelihood.addConstant(speedLikelihoodNoise);
+ 
+ relativeSpeedLikelihood.addGaussianShape(index , 5, 0.5*matchFactor);
+ 
+ 
+ //copy posterior to prior
+ relativeSpeedPrior.copyFromDynamicVector(relativeSpeedPosterior);
+ 
+ //update
+ relativeSpeedPosterior.doProduct(relativeSpeedPrior, relativeSpeedLikelihood);
+ 
+ //normalise
+ relativeSpeedPosterior.renormalise();
+ 
+ relativeSpeedPosterior.getMaximum();	
+ }//end if within range
+ 
+ 
+ }
+ 
+ */
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