List of usage examples for org.apache.commons.math3.linear Array2DRowRealMatrix setColumn
public void setColumn(final int column, final double[] array) throws OutOfRangeException, MatrixDimensionMismatchException
From source file:lanchester.MultiArena.java
public void step() { int numFoes = forces.size(); if (isMyTurn == null) { isMyTurn = new boolean[numFoes][numFoes]; stanceArray = new int[numFoes][numFoes]; currentFloor = new double[numFoes][numFoes]; for (int i1 = 0; i1 < numFoes; i1++) { int ind1 = forceMap.get(forces.get(i1)); for (int i2 = 0; i2 < numFoes; i2++) { int ind2 = forceMap.get(forces.get(i2)); isMyTurn[i1][i2] = true; if (i1 == i2) { stanceArray[i1][i2] = AthenaConstants.ALLIED_POSTURE; currentFloor[i1][i2] = 0.; } else { stanceArray[i1][i2] = initializeStance(forces.get(i1), forces.get(i2)); setFloor(i1, i2);//w w w . jav a 2 s . co m } } } } Array2DRowRealMatrix mat = getMat(); EigenDecomposition eigen = new EigenDecomposition(mat); double det = eigen.getDeterminant(); double[] eVals = eigen.getRealEigenvalues(); // for(int i1=0;i1<eVals.length;i1++){ // System.out.println("eVals["+i1+"] = "+eVals[i1]); // } if (eigen.hasComplexEigenvalues()) { System.out.println("Complex eigenvalues"); for (int i1 = 0; i1 < forces.size(); i1++) { AthenaForce f = forces.get(i1); System.out.println(f.getName() + " has " + f.getForceSize() + " forces remaining"); } } double[] initialNums = getInitialNumbers(forces); Array2DRowRealMatrix eVectors = (Array2DRowRealMatrix) eigen.getV(); LUDecomposition lu = new LUDecomposition(eVectors); double det2 = lu.getDeterminant(); double[] coeffs = new double[numFoes]; for (int i1 = 0; i1 < numFoes; i1++) { Array2DRowRealMatrix tmpMat = (Array2DRowRealMatrix) eVectors.copy(); tmpMat.setColumn(i1, initialNums); LUDecomposition tmpLU = new LUDecomposition(tmpMat); double tmpDet = tmpLU.getDeterminant(); coeffs[i1] = tmpDet / det2; } MultiTimeStep currentStep = new MultiTimeStep(numFoes); currentTime += timeStep; currentStep.setTime(currentTime); for (int i1 = 0; i1 < numFoes; i1++) { double updatedForce = 0.; for (int i2 = 0; i2 < numFoes; i2++) { updatedForce += coeffs[i2] * eVectors.getEntry(i1, i2) * Math.exp(eVals[i2] * timeStep); // updatedForce+=coeffs[i2]*eVectors.getEntry(i2, i1)*Math.exp(eVals[i2]*timeStep); // updatedForce+=coeffs[i1]*eVectors.getEntry(i2, i1)*Math.exp(eVals[i1]*timeStep); } forces.get(i1).updateForce(updatedForce); currentStep.setForceNumber(updatedForce, i1); } history.add(currentStep); // eVectors. // this.currentTime++; // Truncator truncator = new Truncator(); if (true) { // System.out.println("time = " + time); } }
From source file:MultivariateNormalDistribution.java
/** * Creates a multivariate normal distribution with the given mean vector and * covariance matrix./*from ww w . j a v a2 s .c o m*/ * <br/> * The number of dimensions is equal to the length of the mean vector * and to the number of rows and columns of the covariance matrix. * It is frequently written as "p" in formulae. * * @param rng Random Number Generator. * @param means Vector of means. * @param covariances Covariance matrix. * @throws DimensionMismatchException if the arrays length are * inconsistent. * @throws SingularMatrixException if the eigenvalue decomposition cannot * be performed on the provided covariance matrix. * @throws NonPositiveDefiniteMatrixException if any of the eigenvalues is * negative. */ public MultivariateNormalDistribution(RandomGenerator rng, final double[] means, final double[][] covariances) throws SingularMatrixException, DimensionMismatchException, NonPositiveDefiniteMatrixException { super(rng, means.length); final int dim = means.length; if (covariances.length != dim) { throw new DimensionMismatchException(covariances.length, dim); } for (int i = 0; i < dim; i++) { if (dim != covariances[i].length) { throw new DimensionMismatchException(covariances[i].length, dim); } } this.means = MathArrays.copyOf(means); covarianceMatrix = new Array2DRowRealMatrix(covariances); // Covariance matrix eigen decomposition. final EigenDecomposition covMatDec = new EigenDecomposition(covarianceMatrix); // Compute and store the inverse. covarianceMatrixInverse = covMatDec.getSolver().getInverse(); // Compute and store the determinant. covarianceMatrixDeterminant = covMatDec.getDeterminant(); // Eigenvalues of the covariance matrix. final double[] covMatEigenvalues = covMatDec.getRealEigenvalues(); for (int i = 0; i < covMatEigenvalues.length; i++) { if (covMatEigenvalues[i] < 0) { throw new NonPositiveDefiniteMatrixException(covMatEigenvalues[i], i, 0); } } // Matrix where each column is an eigenvector of the covariance matrix. final Array2DRowRealMatrix covMatEigenvectors = new Array2DRowRealMatrix(dim, dim); for (int v = 0; v < dim; v++) { final double[] evec = covMatDec.getEigenvector(v).toArray(); covMatEigenvectors.setColumn(v, evec); } final RealMatrix tmpMatrix = covMatEigenvectors.transpose(); // Scale each eigenvector by the square root of its eigenvalue. for (int row = 0; row < dim; row++) { final double factor = FastMath.sqrt(covMatEigenvalues[row]); for (int col = 0; col < dim; col++) { tmpMatrix.multiplyEntry(row, col, factor); } } samplingMatrix = covMatEigenvectors.multiply(tmpMatrix); }
From source file:lanchester.MultiArena2.java
public void step() { boolean aboveFloor = true; double currentCycle = 0.; int numFoes = forces.size(); if (isMyTurn == null) { isMyTurn = new boolean[numFoes][numFoes]; stanceArray = new int[numFoes][numFoes]; currentFloor = new double[numFoes][numFoes]; for (int i1 = 0; i1 < numFoes; i1++) { int ind1 = forceMap.get(forces.get(i1)); for (int i2 = 0; i2 < numFoes; i2++) { int ind2 = forceMap.get(forces.get(i2)); isMyTurn[i1][i2] = true; if (i1 == i2) { stanceArray[i1][i2] = AthenaConstants.ALLIED_POSTURE; currentFloor[i1][i2] = 0.; } else { stanceArray[i1][i2] = initializeStance(forces.get(i1), forces.get(i2)); setFloor(i1, i2);//www . j a v a 2 s . c o m } } } } Array2DRowRealMatrix mat = getMat(); EigenDecomposition eigen = new EigenDecomposition(mat); double det = eigen.getDeterminant(); double[] eVals = eigen.getRealEigenvalues(); // for(int i1=0;i1<eVals.length;i1++){ // System.out.println("eVals["+i1+"] = "+eVals[i1]); // } if (eigen.hasComplexEigenvalues()) { System.out.println("Complex eigenvalues"); for (int i1 = 0; i1 < forces.size(); i1++) { AthenaForce f = forces.get(i1); System.out.println(f.getName() + " has " + f.getForceSize() + " forces remaining"); } } double[] initialNums = getInitialNumbers(forces); Array2DRowRealMatrix eVectors = (Array2DRowRealMatrix) eigen.getV(); LUDecomposition lu = new LUDecomposition(eVectors); double det2 = lu.getDeterminant(); double[] coeffs = new double[numFoes]; for (int i1 = 0; i1 < numFoes; i1++) { Array2DRowRealMatrix tmpMat = (Array2DRowRealMatrix) eVectors.copy(); tmpMat.setColumn(i1, initialNums); LUDecomposition tmpLU = new LUDecomposition(tmpMat); double tmpDet = tmpLU.getDeterminant(); coeffs[i1] = tmpDet / det2; } aboveFloor = true; int cntr = 0; int numGone; do { MultiTimeStep currentStep = new MultiTimeStep(numFoes); currentTime += timeStep; currentCycle += timeStep; currentStep.setTime(currentTime); numGone = 0; for (int i1 = 0; i1 < numFoes; i1++) { double updatedForce = 0.; if (forces.get(i1).getForceSize() > lb) { for (int i2 = 0; i2 < numFoes; i2++) { // updatedForce += coeffs[i2] * eVectors.getEntry(i1, i2) * Math.exp(eVals[i2] * timeStep); updatedForce += coeffs[i2] * eVectors.getEntry(i1, i2) * Math.exp(eVals[i2] * currentCycle); if (updatedForce < 1.) { updatedForce = 0.; numGone++; } // updatedForce+=coeffs[i2]*eVectors.getEntry(i2, i1)*Math.exp(eVals[i2]*timeStep); // updatedForce+=coeffs[i1]*eVectors.getEntry(i2, i1)*Math.exp(eVals[i1]*timeStep); } } else { updatedForce = lb / 2.; numGone++; } forces.get(i1).updateForce(updatedForce); currentStep.setForceNumber(updatedForce, i1); } history.add(currentStep); aboveFloor = checkAboveFloors(); cntr++; } while (aboveFloor && cntr < 2000 && (numFoes - numGone) > 1); for (int i1 = 0; i1 < numFoes; i1++) { for (int i2 = 0; i2 < numFoes; i2++) { if (i1 == i2) { stanceArray[i1][i2] = AthenaConstants.ALLIED_POSTURE; currentFloor[i1][i2] = 0.; } else { stanceArray[i1][i2] = initializeStance(forces.get(i1), forces.get(i2)); setFloor(i1, i2); } } } // eVectors. // this.currentTime++; // Truncator truncator = new Truncator(); if (numFoes - numGone == 1) { loneSurvivor = true; // System.out.println("time = " + time); } }
From source file:lanchester.MultiArena3.java
public void step() { boolean aboveFloor = true; double currentCycle = 0.; int numFoes = forces.size(); if (isMyTurn == null) { isMyTurn = new boolean[numFoes][numFoes]; stanceArray = new int[numFoes][numFoes]; currentFloor = new double[numFoes][numFoes]; currentCeiling = new double[numFoes][numFoes]; for (int i1 = 0; i1 < numFoes; i1++) { int ind1 = forceMap.get(forces.get(i1)); for (int i2 = 0; i2 < numFoes; i2++) { int ind2 = forceMap.get(forces.get(i2)); isMyTurn[i1][i2] = true; if (i1 == i2) { stanceArray[i1][i2] = AthenaConstants.ALLIED_POSTURE; currentFloor[i1][i2] = 0.; currentCeiling[i1][i2] = 100.; } else { stanceArray[i1][i2] = initializeStance(forces.get(i1), forces.get(i2)); setFloor(i1, i2);//from www .ja v a 2s .c o m setCeiling(i1, i2); } } } } Array2DRowRealMatrix mat = getMat(); EigenDecomposition eigen = new EigenDecomposition(mat); double det = eigen.getDeterminant(); double[] eVals = eigen.getRealEigenvalues(); if (eigen.hasComplexEigenvalues()) { System.out.println("Complex eigenvalues"); for (int i1 = 0; i1 < forces.size(); i1++) { MultiForce f = forces.get(i1); System.out.println(f.getName() + " has " + f.getNumber() + " forces remaining"); } } double[] initialNums = getInitialNumbers(forces); Array2DRowRealMatrix eVectors = (Array2DRowRealMatrix) eigen.getV(); LUDecomposition lu = new LUDecomposition(eVectors); double det2 = lu.getDeterminant(); double[] coeffs = new double[numFoes]; for (int i1 = 0; i1 < numFoes; i1++) { Array2DRowRealMatrix tmpMat = (Array2DRowRealMatrix) eVectors.copy(); tmpMat.setColumn(i1, initialNums); LUDecomposition tmpLU = new LUDecomposition(tmpMat); double tmpDet = tmpLU.getDeterminant(); coeffs[i1] = tmpDet / det2; } aboveFloor = true; boolean belowCeiling = true; int cntr = 0; int numGone; do { timeStep = determineTimeStep(); MultiTimeStep currentStep = new MultiTimeStep(numFoes); currentTime += timeStep; currentCycle += timeStep; currentStep.setTime(currentTime); numGone = 0; for (int i1 = 0; i1 < numFoes; i1++) { double updatedForce = 0.; if (stillAlive[i1]) { for (int i2 = 0; i2 < numFoes; i2++) { updatedForce += coeffs[i2] * eVectors.getEntry(i1, i2) * Math.exp(eVals[i2] * currentCycle); } if (updatedForce < 1.) { updatedForce = lb; stillAlive[i1] = false; numGone++; } } else { numGone++; updatedForce = lb; } forces.get(i1).updateForce(updatedForce); currentStep.setForceNumber(updatedForce, i1); } history.add(currentStep); aboveFloor = checkAboveFloors(); belowCeiling = checkBelowCeilings(); cntr++; } while (aboveFloor && belowCeiling && cntr < 2000 && (numFoes - numGone) > 1); for (int i1 = 0; i1 < numFoes; i1++) { for (int i2 = 0; i2 < numFoes; i2++) { if (i1 == i2) { stanceArray[i1][i2] = AthenaConstants.ALLIED_POSTURE; currentFloor[i1][i2] = 0.; } else { stanceArray[i1][i2] = initializeStance(forces.get(i1), forces.get(i2)); setFloor(i1, i2); } } } // eVectors. // this.currentTime++; // Truncator truncator = new Truncator(); if (numFoes - numGone == 1) { loneSurvivor = true; // System.out.println("time = " + time); } }
From source file:lanchester.MultiArena4.java
public void step() { boolean aboveFloor = true; double currentCycle = 0.; int numFoes = forces.size(); if (isMyTurn == null) { isMyTurn = new boolean[numFoes][numFoes]; stanceArray = new int[numFoes][numFoes]; currentFloor = new double[numFoes][numFoes]; currentCeiling = new double[numFoes][numFoes]; for (int i1 = 0; i1 < numFoes; i1++) { // int ind1 = forceMap.get(forces.get(i1)); for (int i2 = 0; i2 < numFoes; i2++) { // int ind2 = forceMap.get(forces.get(i2)); isMyTurn[i1][i2] = true; if (i1 == i2) { stanceArray[i1][i2] = AthenaConstants.ALLIED_POSTURE; currentFloor[i1][i2] = 0.; currentCeiling[i1][i2] = 1000000.; } else { stanceArray[i1][i2] = initializeStance(forces.get(i1), forces.get(i2)); // setStances(i1,i2); setFloor(i1, i2);//from w w w .ja v a2 s . co m setCeiling(i1, i2); } } } } Array2DRowRealMatrix mat = getMat(); EigenDecomposition eigen = new EigenDecomposition(mat); double det = eigen.getDeterminant(); double[] eVals = eigen.getRealEigenvalues(); if (eigen.hasComplexEigenvalues()) { System.out.println("Complex eigenvalues"); for (int i1 = 0; i1 < forces.size(); i1++) { MultiForce f = forces.get(i1); System.out.println(f.getName() + " has " + f.getNumber() + " forces remaining"); } } double[] initialNums = getInitialNumbers(forces); Array2DRowRealMatrix eVectors = (Array2DRowRealMatrix) eigen.getV(); LUDecomposition lu = new LUDecomposition(eVectors); double det2 = lu.getDeterminant(); double[] coeffs = new double[numFoes]; for (int i1 = 0; i1 < numFoes; i1++) { Array2DRowRealMatrix tmpMat = (Array2DRowRealMatrix) eVectors.copy(); tmpMat.setColumn(i1, initialNums); LUDecomposition tmpLU = new LUDecomposition(tmpMat); double tmpDet = tmpLU.getDeterminant(); coeffs[i1] = tmpDet / det2; } aboveFloor = true; boolean belowCeiling = true; int cntr = 0; int numGone; do { timeStep = determineTimeStep(); MultiTimeStep currentStep = new MultiTimeStep(numFoes); currentTime += timeStep; currentCycle += timeStep; currentStep.setTime(currentTime); numGone = 0; for (int i1 = 0; i1 < numFoes; i1++) { double updatedForce = 0.; // if (forces.get(i1).getForceSize() > lb) { if (stillAlive[i1]) { for (int i2 = 0; i2 < numFoes; i2++) { // updatedForce += coeffs[i2] * eVectors.getEntry(i1, i2) * Math.exp(eVals[i2] * timeStep); updatedForce += coeffs[i2] * eVectors.getEntry(i1, i2) * Math.exp(eVals[i2] * currentCycle); // updatedForce+=coeffs[i2]*eVectors.getEntry(i2, i1)*Math.exp(eVals[i2]*timeStep); // updatedForce+=coeffs[i1]*eVectors.getEntry(i2, i1)*Math.exp(eVals[i1]*timeStep); } if (updatedForce < 1.) { updatedForce = lb; stillAlive[i1] = false; numGone++; } } else { updatedForce = lb; numGone++; } forces.get(i1).updateForce(updatedForce); currentStep.setForceNumber(updatedForce, i1); // for (int i2 = 0; i2 < numFoes; i1++) { // if (i1 != i2) { // // } // } } history.add(currentStep); aboveFloor = checkAboveFloors(); belowCeiling = checkBelowCeilings(); cntr++; } while (aboveFloor && belowCeiling && cntr < 2000 && (numFoes - numGone) > 1); for (int i1 = 0; i1 < numFoes; i1++) { for (int i2 = 0; i2 < numFoes; i2++) { if (i1 == i2) { stanceArray[i1][i2] = AthenaConstants.ALLIED_POSTURE; currentFloor[i1][i2] = 0.; } else { // stanceArray[i1][i2] = initializeStance(forces.get(i1), forces.get(i2)); setStances(i1, i2); setFloor(i1, i2); setCeiling(i1, i2); } } } // eVectors. // this.currentTime++; // Truncator truncator = new Truncator(); if (numFoes - numGone == 1) { loneSurvivor = true; // System.out.println("time = " + time); } }
From source file:net2.N2MultiArena.java
public void step() { boolean aboveFloor = true; double currentCycle = 0.; int numFoes = forces.size(); System.out.println("Num foes = " + numFoes); if (isMyTurn == null) { isMyTurn = new boolean[numFoes][numFoes]; stanceArray = new int[numFoes][numFoes]; currentFloor = new double[numFoes][numFoes]; currentCeiling = new double[numFoes][numFoes]; for (int i1 = 0; i1 < numFoes; i1++) { // int ind1 = forceMap.get(forces.get(i1)); for (int i2 = 0; i2 < numFoes; i2++) { // int ind2 = forceMap.get(forces.get(i2)); isMyTurn[i1][i2] = true; if (i1 == i2) { stanceArray[i1][i2] = AthenaConstants.ALLIED_POSTURE; currentFloor[i1][i2] = 0.; currentCeiling[i1][i2] = 1000000.; } else { stanceArray[i1][i2] = initializeStance(forces.get(i1), forces.get(i2)); setFloor(i1, i2);/*w w w .jav a 2 s . c om*/ setCeiling(i1, i2); } } } } Array2DRowRealMatrix mat = getMat(); EigenDecomposition eigen = new EigenDecomposition(mat); double det = eigen.getDeterminant(); double[] eVals = eigen.getRealEigenvalues(); if (eigen.hasComplexEigenvalues()) { System.out.println("Complex eigenvalues"); for (int i1 = 0; i1 < forces.size(); i1++) { N2ForceUnit f = forces.get(i1); System.out.println(f.getName() + " has " + f.getNumber() + " forces remaining"); } } double[] initialNums = getInitialNumbers(forces); Array2DRowRealMatrix eVectors = (Array2DRowRealMatrix) eigen.getV(); LUDecomposition lu = new LUDecomposition(eVectors); double det2 = lu.getDeterminant(); double[] coeffs = new double[numFoes]; for (int i1 = 0; i1 < numFoes; i1++) { Array2DRowRealMatrix tmpMat = (Array2DRowRealMatrix) eVectors.copy(); tmpMat.setColumn(i1, initialNums); LUDecomposition tmpLU = new LUDecomposition(tmpMat); double tmpDet = tmpLU.getDeterminant(); coeffs[i1] = tmpDet / det2; } aboveFloor = true; boolean belowCeiling = true; // int cntr = 0; int numGone; // do { timeStep = determineTimeStep(); MultiTimeStep currentStep = new MultiTimeStep(numFoes); currentTime += timeStep; currentCycle += timeStep; currentStep.setTime(currentTime); numGone = 0; for (int i1 = 0; i1 < numFoes; i1++) { double updatedForce = 0.; // if (forces.get(i1).getForceSize() > lb) { if (stillAlive[i1]) { for (int i2 = 0; i2 < numFoes; i2++) { // updatedForce += coeffs[i2] * eVectors.getEntry(i1, i2) * Math.exp(eVals[i2] * timeStep); updatedForce += coeffs[i2] * eVectors.getEntry(i1, i2) * Math.exp(eVals[i2] * currentCycle); } if (updatedForce < 1.) { updatedForce = lb; stillAlive[i1] = false; numGone++; } } else { updatedForce = lb; numGone++; } forces.get(i1).updateForce(updatedForce); currentStep.setForceNumber(updatedForce, i1); } history.add(currentStep); aboveFloor = checkAboveFloors(); belowCeiling = checkBelowCeilings(); // cntr++; // } while (aboveFloor && belowCeiling && cntr < 2000 && (numFoes - numGone) > 1); for (int i1 = 0; i1 < numFoes; i1++) { for (int i2 = 0; i2 < numFoes; i2++) { if (i1 == i2) { stanceArray[i1][i2] = AthenaConstants.ALLIED_POSTURE; currentFloor[i1][i2] = 0.; } else { // stanceArray[i1][i2] = initializeStance(forces.get(i1), forces.get(i2)); setStances(i1, i2); setFloor(i1, i2); setCeiling(i1, i2); } } } if (numFoes - numGone == 1) { loneSurvivor = true; // System.out.println("time = " + time); } }
From source file:org.orekit.files.ccsds.OEMParserTest.java
@Test public void testParseOEM1() throws OrekitException, IOException { //// ww w .j a va 2s. c om final String ex = "/ccsds/OEMExample.txt"; final InputStream inEntry = getClass().getResourceAsStream(ex); final OEMParser parser = new OEMParser().withMu(CelestialBodyFactory.getEarth().getGM()); final OEMFile file = parser.parse(inEntry, "OEMExample.txt"); Assert.assertEquals(TimeSystem.UTC, file.getTimeSystem()); Assert.assertEquals("MARS GLOBAL SURVEYOR", file.getEphemeridesBlocks().get(0).getMetaData().getObjectName()); Assert.assertEquals("1996-062A", file.getEphemeridesBlocks().get(0).getMetaData().getObjectID()); Assert.assertEquals("MARS BARYCENTER", file.getEphemeridesBlocks().get(0).getMetaData().getCenterName()); Assert.assertEquals(1996, file.getEphemeridesBlocks().get(0).getMetaData().getLaunchYear()); Assert.assertEquals(62, file.getEphemeridesBlocks().get(0).getMetaData().getLaunchNumber()); Assert.assertEquals("A", file.getEphemeridesBlocks().get(0).getMetaData().getLaunchPiece()); Assert.assertFalse(file.getEphemeridesBlocks().get(0).getMetaData().getHasCreatableBody()); Assert.assertNull(file.getEphemeridesBlocks().get(0).getMetaData().getCenterBody()); Assert.assertEquals(new AbsoluteDate(1996, 12, 18, 12, 00, 0.331, TimeScalesFactory.getUTC()), file.getEphemeridesBlocks().get(0).getStartTime()); Assert.assertEquals(new AbsoluteDate(1996, 12, 28, 21, 28, 0.331, TimeScalesFactory.getUTC()), file.getEphemeridesBlocks().get(0).getStopTime()); Assert.assertEquals(new AbsoluteDate(1996, 12, 18, 12, 10, 0.331, TimeScalesFactory.getUTC()), file.getEphemeridesBlocks().get(0).getUseableStartTime()); Assert.assertEquals(new AbsoluteDate(1996, 12, 28, 21, 23, 0.331, TimeScalesFactory.getUTC()), file.getEphemeridesBlocks().get(0).getUseableStopTime()); Assert.assertEquals("HERMITE", file.getEphemeridesBlocks().get(0).getInterpolationMethod()); Assert.assertEquals(7, file.getEphemeridesBlocks().get(0).getInterpolationDegree()); ArrayList<String> ephemeridesDataLinesComment = new ArrayList<String>(); ephemeridesDataLinesComment.add("This file was produced by M.R. Somebody, MSOO NAV/JPL, 1996NOV 04. It is"); ephemeridesDataLinesComment.add("to be used for DSN scheduling purposes only."); Assert.assertEquals(ephemeridesDataLinesComment, file.getEphemeridesBlocks().get(0).getEphemeridesDataLinesComment()); CartesianOrbit orbit = new CartesianOrbit( new PVCoordinates(new Vector3D(2789.619 * 1000, -280.045 * 1000, -1746.755 * 1000), new Vector3D(4.73372 * 1000, -2.49586 * 1000, -1.04195 * 1000)), FramesFactory.getEME2000(), new AbsoluteDate("1996-12-18T12:00:00.331", TimeScalesFactory.getUTC()), CelestialBodyFactory.getEarth().getGM()); Assert.assertArrayEquals( orbit.getPVCoordinates().getPosition().toArray(), file.getEphemeridesBlocks().get(0) .getEphemeridesDataLines().get(0).getOrbit().getPVCoordinates().getPosition().toArray(), 1e-10); Assert.assertArrayEquals( orbit.getPVCoordinates().getVelocity().toArray(), file.getEphemeridesBlocks().get(0) .getEphemeridesDataLines().get(0).getOrbit().getPVCoordinates().getVelocity().toArray(), 1e-10); Assert.assertArrayEquals((new Vector3D(1, 1, 1)).toArray(), file.getEphemeridesBlocks().get(1).getEphemeridesDataLines().get(0).getAcceleration().toArray(), 1e-10); final Array2DRowRealMatrix covMatrix = new Array2DRowRealMatrix(6, 6); final double[] column1 = { 3.331349476038534e-04, 4.618927349220216e-04, -3.070007847730449e-04, -3.349365033922630e-07, -2.211832501084875e-07, -3.041346050686871e-07 }; final double[] column2 = { 4.618927349220216e-04, 6.782421679971363e-04, -4.221234189514228e-04, -4.686084221046758e-07, -2.864186892102733e-07, -4.989496988610662e-07 }; final double[] column3 = { -3.070007847730449e-04, -4.221234189514228e-04, 3.231931992380369e-04, 2.484949578400095e-07, 1.798098699846038e-07, 3.540310904497689e-07 }; final double[] column4 = { -3.349365033922630e-07, -4.686084221046758e-07, 2.484949578400095e-07, 4.296022805587290e-10, 2.608899201686016e-10, 1.869263192954590e-10 }; final double[] column5 = { -2.211832501084875e-07, -2.864186892102733e-07, 1.798098699846038e-07, 2.608899201686016e-10, 1.767514756338532e-10, 1.008862586240695e-10 }; final double[] column6 = { -3.041346050686871e-07, -4.989496988610662e-07, 3.540310904497689e-07, 1.869263192954590e-10, 1.008862586240695e-10, 6.224444338635500e-10 }; covMatrix.setColumn(0, column1); covMatrix.setColumn(1, column2); covMatrix.setColumn(2, column3); covMatrix.setColumn(3, column4); covMatrix.setColumn(4, column5); covMatrix.setColumn(5, column6); for (int i = 0; i < 6; i++) { for (int j = 0; j < 6; j++) { Assert.assertEquals(covMatrix.getEntry(i, j), file.getEphemeridesBlocks().get(2) .getCovarianceMatrices().get(0).getMatrix().getEntry(i, j), 1e-10); } } Assert.assertEquals(new AbsoluteDate("1996-12-28T21:29:07.267", TimeScalesFactory.getUTC()), file.getEphemeridesBlocks().get(2).getCovarianceMatrices().get(0).getEpoch()); Assert.assertEquals(FramesFactory.getEME2000(), file.getEphemeridesBlocks().get(2).getCovarianceMatrices().get(1).getFrame()); }
From source file:org.orekit.files.ccsds.OPMParserTest.java
@Test public void testParseOPM3() throws OrekitException, URISyntaxException { // simple test for OPM file, contains all mandatory information plus // Spacecraft parameters and the position/velocity Covariance Matrix. final String name = getClass().getResource("/ccsds/OPMExample3.txt").toURI().getPath(); OPMParser parser = new OPMParser().withConventions(IERSConventions.IERS_2010); final OPMFile file = parser.parse(name); Assert.assertEquals(// w ww . j av a 2s.c o m new AbsoluteDate(1998, 12, 18, 14, 28, 15.1172, TimeScalesFactory.getGMST(IERSConventions.IERS_2010, false)), file.getMetaData().getFrameEpoch()); // Check Data Covariance matrix Block ArrayList<String> dataCovMatrixComment = new ArrayList<String>(); dataCovMatrixComment.add("toto"); dataCovMatrixComment.add("tata"); Assert.assertEquals(dataCovMatrixComment, file.getCovarianceComment()); Assert.assertTrue(file.hasCovarianceMatrix()); Assert.assertEquals(file.getCovRefFrame(), FramesFactory.getTEME()); Array2DRowRealMatrix covMatrix = new Array2DRowRealMatrix(6, 6); double[] column1 = { 3.331349476038534e-04, 4.618927349220216e-04, -3.070007847730449e-04, -3.349365033922630e-07, -2.211832501084875e-07, -3.041346050686871e-07 }; double[] column2 = { 4.618927349220216e-04, 6.782421679971363e-04, -4.221234189514228e-04, -4.686084221046758e-07, -2.864186892102733e-07, -4.989496988610662e-07 }; double[] column3 = { -3.070007847730449e-04, -4.221234189514228e-04, 3.231931992380369e-04, 2.484949578400095e-07, 1.798098699846038e-07, 3.540310904497689e-07 }; double[] column4 = { -3.349365033922630e-07, -4.686084221046758e-07, 2.484949578400095e-07, 4.296022805587290e-10, 2.608899201686016e-10, 1.869263192954590e-10 }; double[] column5 = { -2.211832501084875e-07, -2.864186892102733e-07, 1.798098699846038e-07, 2.608899201686016e-10, 1.767514756338532e-10, 1.008862586240695e-10 }; double[] column6 = { -3.041346050686871e-07, -4.989496988610662e-07, 3.540310904497689e-07, 1.869263192954590e-10, 1.008862586240695e-10, 6.224444338635500e-10 }; covMatrix.setColumn(0, column1); covMatrix.setColumn(1, column2); covMatrix.setColumn(2, column3); covMatrix.setColumn(3, column4); covMatrix.setColumn(4, column5); covMatrix.setColumn(5, column6); for (int i = 0; i < 6; i++) { for (int j = 0; j < 6; j++) { Assert.assertEquals(covMatrix.getEntry(i, j), file.getCovarianceMatrix().getEntry(i, j), 1e-15); } } // Check User defined Parameters Block HashMap<String, String> userDefinedParameters = new HashMap<String, String>(); userDefinedParameters.put("USER_DEFINED_EARTH_MODEL", "WGS-84"); userDefinedParameters.put("USER_DEFINED_TOTO", "TITI"); Assert.assertEquals(userDefinedParameters, file.getUserDefinedParameters()); }
From source file:org.pmad.gmm.MyMND.java
/** * Creates a multivariate normal distribution with the given mean vector and * covariance matrix.//from w w w .j a va 2 s.co m * <br/> * The number of dimensions is equal to the length of the mean vector * and to the number of rows and columns of the covariance matrix. * It is frequently written as "p" in formulae. * * @param rng Random Number Generator. * @param means Vector of means. * @param covariances Covariance matrix. * @throws DimensionMismatchException if the arrays length are * inconsistent. * @throws SingularMatrixException if the eigenvalue decomposition cannot * be performed on the provided covariance matrix. * @throws NonPositiveDefiniteMatrixException if any of the eigenvalues is * negative. */ public MyMND(RandomGenerator rng, final double[] means, final double[][] covariances) throws SingularMatrixException, DimensionMismatchException, NonPositiveDefiniteMatrixException { super(rng, means.length); final int dim = means.length; if (covariances.length != dim) { throw new DimensionMismatchException(covariances.length, dim); } for (int i = 0; i < dim; i++) { if (dim != covariances[i].length) { throw new DimensionMismatchException(covariances[i].length, dim); } } this.means = MathArrays.copyOf(means); double msum = 0; for (int i = 0; i < covariances.length; i++) { for (int j = 0; j < covariances.length; j++) { msum += covariances[i][j]; } } msum /= covariances.length * covariances.length; // System.out.print("in"); MyEDC covMatDec = null; double a = -1; while (true) { try { covarianceMatrix = new Array2DRowRealMatrix(covariances); covMatDec = new MyEDC(covarianceMatrix); // Compute and store the inverse. covarianceMatrixInverse = covMatDec.getSolver().getInverse(); a *= -1; break; } catch (NoDataException e) { e.printStackTrace(); } catch (NullArgumentException e) { e.printStackTrace(); } catch (MathArithmeticException e) { e.printStackTrace(); } catch (SingularMatrixException e) { // System.out.print("S"); for (int i = 0; i < covariances.length; i++) { double add = covariances[i][i] == 0 ? msum : covariances[i][i]; covariances[i][i] += new Random().nextDouble() * add * 0.01; } } // catch (MaxCountExceededException e) { //// e.printStackTrace(); //// System.out.print("M"+msum); // for (int i = 0; i < covariances.length; i++) { // for (int j = i; j < covariances.length; j++) { // double add = covariances[i][j] == 0?msum:covariances[i][j]; // add = new Random().nextDouble()*add*0.1*a; // covariances[i][j] += add; // covariances[j][i] += add; // } // } //// break; // } } // Compute and store the determinant. covarianceMatrixDeterminant = covMatDec.getDeterminant(); // Eigenvalues of the covariance matrix. final double[] covMatEigenvalues = covMatDec.getRealEigenvalues(); for (int i = 0; i < covMatEigenvalues.length; i++) { if (covMatEigenvalues[i] < 0) { throw new NonPositiveDefiniteMatrixException(covMatEigenvalues[i], i, 0); } } // Matrix where each column is an eigenvector of the covariance matrix. final Array2DRowRealMatrix covMatEigenvectors = new Array2DRowRealMatrix(dim, dim); for (int v = 0; v < dim; v++) { final double[] evec = covMatDec.getEigenvector(v).toArray(); covMatEigenvectors.setColumn(v, evec); } final RealMatrix tmpMatrix = covMatEigenvectors.transpose(); // Scale each eigenvector by the square root of its eigenvalue. for (int row = 0; row < dim; row++) { final double factor = FastMath.sqrt(covMatEigenvalues[row]); for (int col = 0; col < dim; col++) { tmpMatrix.multiplyEntry(row, col, factor); } } samplingMatrix = covMatEigenvectors.multiply(tmpMatrix); }
From source file:xyz.lejon.sampling.FastMultivariateNormalDistribution.java
/** * Creates a multivariate normal distribution with the given mean vector and * covariance matrix./* w w w. ja v a 2 s. c o m*/ * <br/> * The number of dimensions is equal to the length of the mean vector * and to the number of rows and columns of the covariance matrix. * It is frequently written as "p" in formulae. * * @param rng Random Number Generator. * @param means Vector of means. * @param covariances Covariance matrix. * @throws DimensionMismatchException if the arrays length are * inconsistent. * @throws SingularMatrixException if the eigenvalue decomposition cannot * be performed on the provided covariance matrix. * @throws NonPositiveDefiniteMatrixException if any of the eigenvalues is * negative. */ public FastMultivariateNormalDistribution(RandomGenerator rng, final double[] means, final double[][] covariances) throws SingularMatrixException, DimensionMismatchException, NonPositiveDefiniteMatrixException { super(rng, means.length); final int dim = means.length; if (covariances.length != dim) { throw new DimensionMismatchException(covariances.length, dim); } for (int i = 0; i < dim; i++) { if (dim != covariances[i].length) { throw new DimensionMismatchException(covariances[i].length, dim); } } this.means = MathArrays.copyOf(means); covarianceMatrix = new Array2DRowRealMatrix(covariances); // Covariance matrix eigen decomposition. final EigenDecomposition covMatDec = new EigenDecomposition(covarianceMatrix); // Compute and store the inverse. covarianceMatrixInverse = covMatDec.getSolver().getInverse(); // Compute and store the determinant. covarianceMatrixDeterminant = covMatDec.getDeterminant(); // Eigenvalues of the covariance matrix. final double[] covMatEigenvalues = covMatDec.getRealEigenvalues(); for (int i = 0; i < covMatEigenvalues.length; i++) { if (covMatEigenvalues[i] < 0) { throw new NonPositiveDefiniteMatrixException(covMatEigenvalues[i], i, 0); } } // Matrix where each column is an eigenvector of the covariance matrix. final Array2DRowRealMatrix covMatEigenvectors = new Array2DRowRealMatrix(dim, dim); final Array2DRowRealMatrix tmpMatrix = new Array2DRowRealMatrix(dim, dim); for (int v = 0; v < dim; v++) { final double factor = FastMath.sqrt(covMatEigenvalues[v]); final double[] evec = covMatDec.getEigenvector(v).toArray(); covMatEigenvectors.setColumn(v, evec); tmpMatrix.setRow(v, evec); for (int col = 0; col < dim; col++) { tmpMatrix.multiplyEntry(v, col, factor); } } samplingMatrix = covMatEigenvectors.multiply(tmpMatrix); }