ref #9 - verbindung zwischen watch und app geht
- watch startet automatisch auch app - bpm kommen in hoher geschwindigkeit an ref #19 - rückweisunsklasse etwas verbessert - fehlnde files hochgeladen für die bpm estimation
This commit is contained in:
toni
@@ -0,0 +1,31 @@
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package de.tonifetzer.conductorswatch.bpmEstimation;
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/**
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* Created by toni on 15/12/17.
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*/
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public class AccelerometerData {
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public double x,y,z;
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public long ts;
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public AccelerometerData(long ts, double x, double y, double z){
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this.ts = ts;
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this.x = x;
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this.y = y;
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this.z = z;
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}
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@Override
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public boolean equals(Object other){
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if (this == other)
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return true;
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if (!(other instanceof AccelerometerData)) {
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return false;
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}
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AccelerometerData ad = (AccelerometerData) other;
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return ts == ad.ts;
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}
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}
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@@ -0,0 +1,108 @@
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package de.tonifetzer.conductorswatch.bpmEstimation;
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import java.util.Arrays;
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/**
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* Created by toni on 16/12/17.
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*/
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public class AccelerometerInterpolator {
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private double[] mX;
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private double[] mY;
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private double[] mZ;
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private long[] mTsInterp;
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public AccelerometerInterpolator(AccelerometerWindowBuffer ab, double sampleRate_ms){
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long size = (ab.getYongest().ts - (ab.getOldest().ts - (long) sampleRate_ms)) / (long) sampleRate_ms;
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mTsInterp = new long[(int)size];
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int j = 0;
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for(long i = ab.getOldest().ts; i <= ab.getYongest().ts; i += sampleRate_ms){
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mTsInterp[j++] = i;
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}
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mX = interpLinear(ab.getTs(), ab.getX(), mTsInterp);
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mY = interpLinear(ab.getTs(), ab.getY(), mTsInterp);
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mZ = interpLinear(ab.getTs(), ab.getZ(), mTsInterp);
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}
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public long[] getTs(){
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return mTsInterp;
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}
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public double[] getX(){
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return mX;
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}
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public double[] getY(){
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return mY;
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}
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public double[] getZ(){
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return mZ;
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}
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private static double[] interpLinear(double[] x, double[] y, double[] xi) throws IllegalArgumentException {
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if (x.length != y.length) {
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throw new IllegalArgumentException("X and Y must be the same length");
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}
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if (x.length == 1) {
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throw new IllegalArgumentException("X must contain more than one value");
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}
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double[] dx = new double[x.length - 1];
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double[] dy = new double[x.length - 1];
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double[] slope = new double[x.length - 1];
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double[] intercept = new double[x.length - 1];
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// Calculate the line equation (i.e. slope and intercept) between each point
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for (int i = 0; i < x.length - 1; i++) {
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dx[i] = x[i + 1] - x[i];
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if (dx[i] == 0) {
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throw new IllegalArgumentException("X must be montotonic. A duplicate " + "x-value was found");
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}
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if (dx[i] < 0) {
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throw new IllegalArgumentException("X must be sorted");
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}
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dy[i] = y[i + 1] - y[i];
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slope[i] = dy[i] / dx[i];
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intercept[i] = y[i] - x[i] * slope[i];
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}
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// Perform the interpolation here
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double[] yi = new double[xi.length];
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for (int i = 0; i < xi.length; i++) {
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if ((xi[i] > x[x.length - 1]) || (xi[i] < x[0])) {
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yi[i] = Double.NaN;
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}
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else {
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int loc = Arrays.binarySearch(x, xi[i]);
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if (loc < -1) {
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loc = -loc - 2;
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yi[i] = slope[loc] * xi[i] + intercept[loc];
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}
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else {
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yi[i] = y[loc];
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}
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}
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}
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return yi;
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}
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private static double[] interpLinear(long[] x, double[] y, long[] xi) throws IllegalArgumentException {
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double[] xd = new double[x.length];
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for (int i = 0; i < x.length; i++) {
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xd[i] = x[i];
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}
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double[] xid = new double[xi.length];
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for (int i = 0; i < xi.length; i++) {
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xid[i] = xi[i];
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}
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return interpLinear(xd, y, xid);
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}
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}
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@@ -0,0 +1,74 @@
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package de.tonifetzer.conductorswatch.bpmEstimation;
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import de.tonifetzer.conductorswatch.utilities.Utils;
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import java.util.ArrayList;
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/**
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* Created by toni on 15/12/17.
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*/
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public class AccelerometerWindowBuffer extends ArrayList<AccelerometerData> {
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private int mWindowSize;
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private int mOverlapSize;
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private int mOverlapCounter;
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public AccelerometerWindowBuffer(int windowSize, int overlap){
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mWindowSize = windowSize;
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mOverlapSize = overlap;
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mOverlapCounter = 1;
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}
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//TODO: add exception handling. falseArgument if ad has no numeric x,y,z
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public boolean add(AccelerometerData ad){
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//do not add duplicates!
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if(!isEmpty() && getYongest().equals(ad)){
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return false;
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}
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boolean r = super.add(ad);
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if (size() > mWindowSize){
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removeRange(0, size() - mWindowSize);
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}
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++mOverlapCounter;
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return r;
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}
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public boolean isNextWindowReady(){
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if((size() > mWindowSize / 2) && mOverlapCounter > mOverlapSize){
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mOverlapCounter = 1;
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return true;
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}
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return false;
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}
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public AccelerometerData getYongest() {
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return get(size() - 1);
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}
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public AccelerometerData getOldest() {
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return get(0);
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}
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public double[] getX(){
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return this.stream().mapToDouble(d -> d.x).toArray();
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}
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public double[] getY(){
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return this.stream().mapToDouble(d -> d.y).toArray();
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}
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public double[] getZ(){
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return this.stream().mapToDouble(d -> d.z).toArray();
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}
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public long[] getTs(){
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return this.stream().mapToLong(d -> d.ts).toArray();
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}
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public int getOverlapSize(){
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return mOverlapSize;
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}
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}
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@@ -0,0 +1,79 @@
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package de.tonifetzer.conductorswatch.bpmEstimation;
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import org.jtransforms.fft.DoubleFFT_1D;
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import de.tonifetzer.conductorswatch.utilities.Utils;
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import java.util.Arrays;
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/**
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* Created by toni on 15/12/17.
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*/
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public class AutoCorrelation {
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private int mMaxLag;
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private double[] mCorr;
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public AutoCorrelation(double[] data, int maxLag){
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mMaxLag = maxLag;
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mCorr = fft(data);
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}
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public double[] getCorr(){
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return mCorr;
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}
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private double[] fft(double[] data) {
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if(mMaxLag < 1){
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throw new RuntimeException("maxlag has to be greater 1");
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}
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int n = data.length;
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double[] x = Arrays.copyOf(data, n);
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int mxl = Math.min(mMaxLag, n - 1);
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int ceilLog2 = Utils.nextPow2(2*n -1);
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int n2 = (int) Math.pow(2,ceilLog2);
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// x - mean(x) (pointwise)
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double x_mean = Utils.mean(x);
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for(int i = 0; i < x.length; ++i){
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x[i] -= x_mean;
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}
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// double the size of x and fill up with zeros. if x is not even, add additional 0
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double[] x2 = new double[n2 * 2]; //need double the size for fft.realForwardFull (look into method description)
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Arrays.fill(x2, 0);
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System.arraycopy(x,0, x2, 0, x.length);
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// x_fft calculate fft 1D
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DoubleFFT_1D fft = new DoubleFFT_1D(n2);
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fft.realForwardFull(x2);
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// Cr = abs(x_fft).^2 (absolute with complex numbers is (r^2) + (i^2)
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double[] Cr = new double[n2 * 2];
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int j = 0;
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for(int i = 0; i < x2.length; ++i){
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Cr[j++] = Utils.sqr(x2[i]) + Utils.sqr(x2[i+1]);
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++i; //skip the complex part
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}
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// ifft(Cr,[],1)
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DoubleFFT_1D ifft = new DoubleFFT_1D(n2);
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ifft.realInverseFull(Cr, true);
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// remove complex part and scale/normalize
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double[] c1 = new double[n2];
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j = 0;
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for(int i = 0; i < Cr.length; ++i){
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c1[j++] = Cr[i] / Cr[0];
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++i; //skip the complex part
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}
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// Keep only the lags we want and move negative lags before positive lags.
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double[] c = new double[(mxl * 2) + 1];
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System.arraycopy(c1, 0, c, mxl, mxl + 1); // +1 to place the 1.0 in the middle of correlation
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System.arraycopy(c1, n2 - mxl, c, 0, mxl);
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return c;
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}
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}
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@@ -0,0 +1,199 @@
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package de.tonifetzer.conductorswatch.bpmEstimation;
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import de.tonifetzer.conductorswatch.utilities.MovingFilter;
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import de.tonifetzer.conductorswatch.utilities.SimpleKalman;
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import de.tonifetzer.conductorswatch.utilities.Utils;
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import java.util.ArrayList;
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import java.util.LinkedList;
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import java.util.List;
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/**
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* Created by toni on 17/12/17.
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*/
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public class BpmEstimator {
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private AccelerometerWindowBuffer mBuffer;
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private double mSampleRate_ms;
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private LinkedList<Double> mBpmHistory_X;
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private LinkedList<Double> mBpmHistory_Y;
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private LinkedList<Double> mBpmHistory_Z;
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private LinkedList<Double> mBpmHistory;
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private int mResetCounter;
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private int mResetLimit_ms;
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private MovingFilter mMvg;
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//private SimpleKalman mKalman;
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public BpmEstimator(AccelerometerWindowBuffer windowBuffer, double sampleRate_ms, int resetAfter_ms){
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mBuffer = windowBuffer;
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mSampleRate_ms = sampleRate_ms;
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mBpmHistory_X = new LinkedList<>();
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mBpmHistory_Y = new LinkedList<>();
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mBpmHistory_Z = new LinkedList<>();
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mBpmHistory = new LinkedList<>();
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mResetCounter = 0;
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mResetLimit_ms = resetAfter_ms;
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mMvg = new MovingFilter(2);
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//mKalman = new SimpleKalman();
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}
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public double estimate(){
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double sampleRate = mSampleRate_ms;
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if(sampleRate <= 0){
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sampleRate = Math.round(Utils.mean(Utils.diff(mBuffer.getTs())));
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}
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AccelerometerInterpolator interp = new AccelerometerInterpolator(mBuffer, sampleRate);
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//are we conducting?
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//just look at the newest 512 samples
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//List<AccelerometerData> subBuffer = mBuffer.subList(mBuffer.size() - 512, mBuffer.size());
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double[] xAutoCorr = new AutoCorrelation(interp.getX(), 512).getCorr();
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double[] yAutoCorr = new AutoCorrelation(interp.getY(), 512).getCorr();
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double[] zAutoCorr = new AutoCorrelation(interp.getZ(), 512).getCorr();
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Peaks pX = new Peaks(xAutoCorr, 50, 0.1f, 0, false);
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Peaks pY = new Peaks(yAutoCorr, 50, 0.1f, 0, false);
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Peaks pZ = new Peaks(zAutoCorr, 50, 0.1f, 0, false);
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mBpmHistory_X.add(pX.getBPM(sampleRate));
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mBpmHistory_Y.add(pY.getBPM(sampleRate));
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mBpmHistory_Z.add(pZ.getBPM(sampleRate));
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double estimatedBPM = getBestBpmEstimation(pX, pY, pZ);
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if(estimatedBPM != -1){
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//moving avg (lohnt dann, wenn wir viele daten haben)
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mMvg.add(estimatedBPM);
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mBpmHistory.add(mMvg.getAverage());
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//moving median (lohnt nur bei konstantem tempo, da wir nur ein tempo damit gut halten können.)
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//mMvg.add(estimatedBPM);
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//mBpmHistory.add(mMvg.getMedian());
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//kalman filter (lohnt dann, wenn wir konstantes tempo haben, mit startangabe!)
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//standard last element
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//mBpmHistory.add(estimatedBPM);
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//mResetCounter = 0;
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}
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else {
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int resetAfter = (int) Math.round(mResetLimit_ms / (mBuffer.getOverlapSize() * sampleRate));
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if(++mResetCounter > resetAfter){
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mBpmHistory.clear();
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mBuffer.clear();
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mMvg.clear();
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mResetCounter = 0;
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}
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return -1;
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}
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//last element
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return mBpmHistory.getLast();
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}
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public double getMeanBpm(){
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return Utils.mean(mBpmHistory);
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}
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public double getMedianBPM(){
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return Utils.median(mBpmHistory);
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}
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private double getBestBpmEstimation(Peaks peaksX, Peaks peaksY, Peaks peaksZ) throws IllegalArgumentException {
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int cntNumAxis = 0;
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double sumCorr = 0; //to prevent division by zero
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double sumRms = 0;
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double sumNumInter = 0;
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double corrMeanX = 0, corrRmsX = 0;
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int corrNumInterX = 0;
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if(peaksX.hasPeaks()){
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corrMeanX = Utils.geometricMean(peaksX.getPeaksValueWithoutZeroIdxAndNegativeValues());
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corrRmsX = Utils.rms(peaksX.getPeaksValueWithoutZeroIdx());
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corrNumInterX = Utils.intersectionNumber(peaksX.getData(), 0.2f);
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++cntNumAxis;
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sumCorr += corrMeanX;
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sumRms += corrRmsX;
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sumNumInter += corrNumInterX;
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}
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double corrMeanY = 0, corrRmsY = 0;
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int corrNumInterY = 0;
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if(peaksY.hasPeaks()){
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corrMeanY = Utils.geometricMean(peaksY.getPeaksValueWithoutZeroIdxAndNegativeValues());
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corrRmsY = Utils.rms(peaksY.getPeaksValueWithoutZeroIdx());
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corrNumInterY = Utils.intersectionNumber(peaksY.getData(), 0.2f);
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++cntNumAxis;
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sumCorr += corrMeanY;
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sumRms += corrRmsY;
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sumNumInter += corrNumInterY;
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}
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double corrMeanZ = 0, corrRmsZ = 0;
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int corrNumInterZ = 0;
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if(peaksZ.hasPeaks()){
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corrMeanZ = Utils.geometricMean(peaksZ.getPeaksValueWithoutZeroIdxAndNegativeValues());
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corrRmsZ = Utils.rms(peaksZ.getPeaksValueWithoutZeroIdx());
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corrNumInterZ = Utils.intersectionNumber(peaksZ.getData(), 0.2f);
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++cntNumAxis;
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sumCorr += corrMeanZ;
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sumRms += corrRmsZ;
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sumNumInter += corrNumInterZ;
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}
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//no peaks, reject
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if(cntNumAxis == 0){
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//throw new IllegalArgumentException("All Peaks are empty! -> Reject Estimation");
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return -1;
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}
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/*
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System.out.println("RMS-X: " + corrRmsX);
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System.out.println("GEO-X: " + corrMeanX);
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System.out.println("INTER-X: " + corrNumInterX);
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System.out.println("RMS-Y: " + corrRmsY);
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System.out.println("GEO-Y: " + corrMeanY);
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System.out.println("INTER-Y: " + corrNumInterY);
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System.out.println("RMS-Z: " + corrRmsZ);
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System.out.println("GEO-Z: " + corrMeanZ);
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System.out.println("INTER-Z: " + corrNumInterZ);
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*/
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//values to low, reject
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//TODO: this is a pretty simple assumption. first shot!
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if(corrRmsX < 0.25 && corrRmsY < 0.25 && corrRmsZ < 0.25){
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return -1;
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}
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double quantityX = ((corrMeanX / sumCorr) + (corrRmsX / sumRms) + (corrNumInterX / sumNumInter)) / cntNumAxis;
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double quantityY = ((corrMeanY / sumCorr) + (corrRmsY / sumRms) + (corrNumInterY / sumNumInter)) / cntNumAxis;
|
||||
double quantityZ = ((corrMeanZ / sumCorr) + (corrRmsZ / sumRms) + (corrNumInterZ / sumNumInter)) / cntNumAxis;
|
||||
|
||||
//get best axis by quantity and estimate bpm
|
||||
if(quantityX > quantityY && quantityX > quantityZ){
|
||||
return mBpmHistory_X.getLast();
|
||||
}
|
||||
else if(quantityY > quantityZ){
|
||||
return mBpmHistory_Y.getLast();
|
||||
}
|
||||
else {
|
||||
return mBpmHistory_Z.getLast();
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,206 @@
|
||||
package de.tonifetzer.conductorswatch.bpmEstimation;
|
||||
|
||||
import de.tonifetzer.conductorswatch.utilities.Utils;
|
||||
|
||||
import java.util.LinkedList;
|
||||
|
||||
/**
|
||||
* Created by toni on 15/12/17.
|
||||
*/
|
||||
public class Peaks {
|
||||
|
||||
private LinkedList<Integer> mPeaksIdx; //provide the idx within the given data array
|
||||
private LinkedList<Integer> mPeaksPos; //the real position within the data-rang e.g. lag -1024 to 1024
|
||||
private LinkedList<Double> mPeaksValue; //the value at mPeaksPos
|
||||
|
||||
private double[] mData;
|
||||
|
||||
/**
|
||||
* Simple method for finding local maxima in an array
|
||||
* @param data input
|
||||
* @param width minimum distance between peaks
|
||||
* @param threshold minimum value of peaks
|
||||
* @param decayRate how quickly previous peaks are forgotten
|
||||
* @param isRelative minimum value of peaks is relative to local average
|
||||
* @return array of peaks
|
||||
*/
|
||||
public Peaks(double[] data, int width, double threshold, double decayRate, boolean isRelative){
|
||||
|
||||
this.mData = data;
|
||||
this.mPeaksIdx = new LinkedList<>();
|
||||
this.mPeaksPos = new LinkedList<>();
|
||||
this.mPeaksValue = new LinkedList<>();
|
||||
|
||||
//create the peaks
|
||||
simplePeakFinder(data, width, threshold, decayRate, isRelative);
|
||||
|
||||
updateLists();
|
||||
}
|
||||
|
||||
public LinkedList<Integer> getPeaksIdx() {
|
||||
return mPeaksIdx;
|
||||
}
|
||||
|
||||
public int[] getPeaksIdxAsArray() {
|
||||
return mPeaksIdx.stream().mapToInt(i->i).toArray();
|
||||
}
|
||||
|
||||
public LinkedList<Integer> getPeaksPos() {
|
||||
return mPeaksPos;
|
||||
}
|
||||
|
||||
public double[] getPeaksPosAsArray() {
|
||||
return mPeaksPos.stream().mapToDouble(i -> i).toArray();
|
||||
}
|
||||
|
||||
public LinkedList<Double> getPeaksValue() {
|
||||
return mPeaksValue;
|
||||
}
|
||||
|
||||
public double[] getPeaksValueAsArray() {
|
||||
return mPeaksValue.stream().mapToDouble(i -> i).toArray();
|
||||
}
|
||||
|
||||
public double[] getData(){
|
||||
return mData;
|
||||
}
|
||||
|
||||
//TODO: implement findFalseDetectedPeaks
|
||||
public void improveResults(double[] data){
|
||||
|
||||
updateLists();
|
||||
}
|
||||
|
||||
public double[] getPeaksValueWithoutZeroIdx() {
|
||||
|
||||
double[] values = new double[mPeaksIdx.size() - 1];
|
||||
int mid = (mData.length / 2);
|
||||
int j = 0;
|
||||
for(int i = 0; i < mPeaksIdx.size(); ++i){
|
||||
if(!(mPeaksIdx.get(i) == mid)){
|
||||
values[j] = mPeaksValue.get(i);
|
||||
++j;
|
||||
}
|
||||
}
|
||||
return values;
|
||||
}
|
||||
|
||||
public double[] getPeaksValueWithoutNegativeValues() {
|
||||
|
||||
double[] values = new double[mPeaksIdx.size() - 1];
|
||||
int i = 0;
|
||||
for(Integer idx : mPeaksIdx) {
|
||||
double curVal = mPeaksValue.get(idx);
|
||||
if(curVal > 0){
|
||||
values[i] = curVal;
|
||||
++i;
|
||||
}
|
||||
}
|
||||
|
||||
return values;
|
||||
}
|
||||
|
||||
public double[] getPeaksValueWithoutZeroIdxAndNegativeValues(){
|
||||
double[] values = new double[mPeaksIdx.size() - 1];
|
||||
int mid = (mData.length / 2);
|
||||
int j = 0;
|
||||
for(int i = 0; i < mPeaksIdx.size(); ++i){
|
||||
double curVal = mPeaksValue.get(i);
|
||||
if(!(mPeaksIdx.get(i) == mid) && curVal > 0){
|
||||
values[j] = curVal;
|
||||
++j;
|
||||
}
|
||||
}
|
||||
return values;
|
||||
}
|
||||
|
||||
public boolean hasPeaks() {
|
||||
return mPeaksIdx.size() > 1;
|
||||
}
|
||||
|
||||
/**
|
||||
* Provides an estimation of beats per minute given a samplerate in milliseconds
|
||||
* @param sampleRate_ms
|
||||
* @return bpm if peaks found and conducting activity recognized, else -1
|
||||
*/
|
||||
public double getBPM(double sampleRate_ms){
|
||||
|
||||
//todo: rückweisungsklasse kann auch hier mit rein.
|
||||
if(hasPeaks()){
|
||||
|
||||
//todo diff and mean method for linkedlists for speed
|
||||
//return 60000 / Utils.mean(Utils.diff(mPeaksPos.stream().mapToDouble(i -> i * sampleRate_ms).toArray()));
|
||||
return 60000 / (sampleRate_ms * Utils.mean(Utils.diff(mPeaksPos.stream().mapToDouble(i -> i).toArray())));
|
||||
}
|
||||
|
||||
return -1;
|
||||
}
|
||||
|
||||
/**
|
||||
* updates the position and values of the found peaks.
|
||||
* call this if peaks are somewhat changed.
|
||||
*/
|
||||
private void updateLists(){
|
||||
//fill the position and the value lists
|
||||
for(Integer idx : mPeaksIdx){
|
||||
int mid = (mData.length / 2);
|
||||
mPeaksPos.add(idx - mid);
|
||||
|
||||
mPeaksValue.add(mData[idx]);
|
||||
}
|
||||
}
|
||||
|
||||
//TODO: findPeaks method identical to Matlab... with PeakProminence
|
||||
|
||||
private void simplePeakFinder(double[] data, int width, double threshold, double decayRate, boolean isRelative) {
|
||||
int maxp;
|
||||
int mid = 0;
|
||||
int end = data.length;
|
||||
double av = data[0];
|
||||
while (mid < end) {
|
||||
av = decayRate * av + (1 - decayRate) * data[mid];
|
||||
if (av < data[mid])
|
||||
av = data[mid];
|
||||
int i = mid - width;
|
||||
if (i < 0)
|
||||
i = 0;
|
||||
int stop = mid + width + 1;
|
||||
if (stop > data.length)
|
||||
stop = data.length;
|
||||
maxp = i;
|
||||
for (i++; i < stop; i++)
|
||||
if (data[i] > data[maxp])
|
||||
maxp = i;
|
||||
if (maxp == mid) {
|
||||
if (overThreshold(data, maxp, width, threshold, isRelative, av)){
|
||||
this.mPeaksIdx.add(new Integer(maxp));
|
||||
}
|
||||
}
|
||||
mid++;
|
||||
}
|
||||
}
|
||||
|
||||
private boolean overThreshold(double[] data, int index, int width,
|
||||
double threshold, boolean isRelative,
|
||||
double av) {
|
||||
int pre = 3;
|
||||
int post = 1;
|
||||
|
||||
if (data[index] < av)
|
||||
return false;
|
||||
if (isRelative) {
|
||||
int iStart = index - pre * width;
|
||||
if (iStart < 0)
|
||||
iStart = 0;
|
||||
int iStop = index + post * width;
|
||||
if (iStop > data.length)
|
||||
iStop = data.length;
|
||||
double sum = 0;
|
||||
int count = iStop - iStart;
|
||||
while (iStart < iStop)
|
||||
sum += data[iStart++];
|
||||
return (data[index] > sum / count + threshold);
|
||||
} else
|
||||
return (data[index] > threshold);
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,37 @@
|
||||
package de.tonifetzer.conductorswatch.utilities;
|
||||
|
||||
import java.util.LinkedList;
|
||||
|
||||
/**
|
||||
* Created by toni on 18/12/17.
|
||||
*/
|
||||
public class MovingFilter {
|
||||
|
||||
private int mSize;
|
||||
private double mTotal = 0d;
|
||||
private LinkedList<Double> mSamples = new LinkedList<>();
|
||||
|
||||
public MovingFilter(int size) {
|
||||
this.mSize = size;
|
||||
}
|
||||
|
||||
public void add(double x) {
|
||||
mTotal += x;
|
||||
mSamples.add(x);
|
||||
if(mSamples.size() > mSize){
|
||||
mTotal -= mSamples.remove();
|
||||
}
|
||||
}
|
||||
|
||||
public double getAverage() {
|
||||
return mTotal / mSamples.size();
|
||||
}
|
||||
|
||||
public double getMedian() {
|
||||
return Utils.median(mSamples);
|
||||
}
|
||||
|
||||
public void clear(){
|
||||
mSamples.clear();
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,33 @@
|
||||
package de.tonifetzer.conductorswatch.utilities;
|
||||
|
||||
/**
|
||||
* Created by toni on 18/12/17.
|
||||
*/
|
||||
public class SimpleKalman {
|
||||
|
||||
private double mSigmaUpdate;
|
||||
private double mSigmaPrediction;
|
||||
private double mMu;
|
||||
private double mSigma;
|
||||
|
||||
SimpleKalman(double initialMu, double initialSigma, double sigmaUpdate, double sigmaPrediction){
|
||||
mSigmaUpdate = sigmaUpdate;
|
||||
mSigmaPrediction = sigmaPrediction;
|
||||
mMu = initialMu;
|
||||
mSigma = initialSigma;
|
||||
}
|
||||
|
||||
public double update(double data){
|
||||
|
||||
//prediction
|
||||
mMu = mMu;
|
||||
mSigma += mSigmaPrediction;
|
||||
|
||||
//update
|
||||
double k = mSigma / (mSigma + mSigmaUpdate);
|
||||
mMu = mMu + k * (data - mMu);
|
||||
mSigma = (1 - k) * mSigma;
|
||||
|
||||
return mMu;
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user