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    * contributor license agreements.  See the NOTICE file distributed with
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    * CS licenses this file to You under the Apache License, Version 2.0
    * (the "License"); you may not use this file except in compliance with
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    *   http://www.apache.org/licenses/LICENSE-2.0
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  package org.orekit.estimation.measurements;
  
  import java.util.List;
  
  import org.hipparchus.geometry.euclidean.threed.Vector3D;
  import org.hipparchus.linear.MatrixUtils;
  import org.hipparchus.stat.descriptive.StreamingStatistics;
  import org.hipparchus.stat.descriptive.rank.Median;
  import org.hipparchus.util.FastMath;
  import org.junit.jupiter.api.Assertions;
  import org.junit.jupiter.api.Test;
  import org.orekit.errors.OrekitException;
  import org.orekit.estimation.Context;
  import org.orekit.estimation.EstimationTestUtils;
  import org.orekit.orbits.OrbitType;
  import org.orekit.orbits.PositionAngleType;
  import org.orekit.propagation.Propagator;
  import org.orekit.propagation.SpacecraftState;
  import org.orekit.propagation.conversion.NumericalPropagatorBuilder;
  import org.orekit.time.AbsoluteDate;
  import org.orekit.utils.Differentiation;
  
  public class PVTest {
  
      /** Compare observed values and estimated values.
       *  Both are calculated with a different algorithm
       */
      @Test
      public void testValues() {
  
          Context context = EstimationTestUtils.eccentricContext("regular-data:potential:tides");
  
          final NumericalPropagatorBuilder propagatorBuilder =
                          context.createBuilder(OrbitType.EQUINOCTIAL, PositionAngleType.TRUE, false,
                                                1.0e-6, 60.0, 0.001);
  
          // Create perfect right-ascension/declination measurements
          final Propagator propagator = EstimationTestUtils.createPropagator(context.initialOrbit,
                                                                             propagatorBuilder);
          final List<ObservedMeasurement<?>> measurements =
                          EstimationTestUtils.createMeasurements(propagator,
                                                                 new PVMeasurementCreator(),
                                                                 1.0, 3.0, 300.0);
  
          propagator.clearStepHandlers();
  
          // Prepare statistics for PV values difference
          final StreamingStatistics[] pvDiffStat = new StreamingStatistics[6];
          for (int i = 0; i < 6; i++) {
              pvDiffStat[i] = new StreamingStatistics();
          }
  
          for (final ObservedMeasurement<?> measurement : measurements) {
  
              // Propagate to measurement date
              final AbsoluteDate datemeas  = measurement.getDate();
              SpacecraftState    state     = propagator.propagate(datemeas);
  
              // Estimate the PV value
              final EstimatedMeasurementBase<?> estimated = measurement.estimateWithoutDerivatives(new SpacecraftState[] { state });
  
              // Store the difference between estimated and observed values in the stats
              for (int i = 0; i < 6; i++) {
                  pvDiffStat[i].addValue(FastMath.abs(estimated.getEstimatedValue()[i] - measurement.getObservedValue()[i]));
              }
          }
  
          // Mean and std errors check
          for (int i = 0; i < 3; i++) {
              // Check position values
              Assertions.assertEquals(0.0, pvDiffStat[i].getMean(), 3.74e-7);
              Assertions.assertEquals(0.0, pvDiffStat[i].getStandardDeviation(), 2.21e-7);
  
              // Check velocity values
              Assertions.assertEquals(0.0, pvDiffStat[i+3].getMean(), 1.29e-10);
              Assertions.assertEquals(0.0, pvDiffStat[i+3].getStandardDeviation(), 7.82e-11);
          }
  
          // Test measurement type
          Assertions.assertEquals(PV.MEASUREMENT_TYPE, measurements.get(0).getMeasurementType());
      }
  
      /** Test the values of the state derivatives using a numerical.
      * finite differences calculation as a reference
      */
     @Test
     public void testStateDerivatives() {
 
         Context context = EstimationTestUtils.eccentricContext("regular-data:potential:tides");
 
         final NumericalPropagatorBuilder propagatorBuilder =
                         context.createBuilder(OrbitType.KEPLERIAN, PositionAngleType.TRUE, true,
                                               1.0e-6, 60.0, 0.001);
 
         // create perfect range measurements
         final Propagator propagator = EstimationTestUtils.createPropagator(context.initialOrbit,
                                                                            propagatorBuilder);
         final List<ObservedMeasurement<?>> measurements =
                         EstimationTestUtils.createMeasurements(propagator,
                                                                new PVMeasurementCreator(),
                                                                1.0, 3.0, 300.0);
         propagator.clearStepHandlers();
 
         double[] errorsP = new double[3 * 6 * measurements.size()];
         double[] errorsV = new double[3 * 6 * measurements.size()];
         int indexP = 0;
         int indexV = 0;
         for (final ObservedMeasurement<?> measurement : measurements) {
 
             final AbsoluteDate    date      = measurement.getDate();
             final SpacecraftState state     = propagator.propagate(date);
             final double[][]      jacobian  = measurement.estimate(0, 0, new SpacecraftState[] { state }).getStateDerivatives(0);
 
             // compute a reference value using finite differences
             final double[][] finiteDifferencesJacobian =
                 Differentiation.differentiate(state1 -> measurement.
                        estimateWithoutDerivatives(new SpacecraftState[] { state1 }).
                        getEstimatedValue(), measurement.getDimension(),
                                               propagator.getAttitudeProvider(), OrbitType.CARTESIAN,
                                               PositionAngleType.TRUE, 1.0, 3).value(state);
 
             Assertions.assertEquals(finiteDifferencesJacobian.length, jacobian.length);
             Assertions.assertEquals(finiteDifferencesJacobian[0].length, jacobian[0].length);
             for (int i = 0; i < jacobian.length; ++i) {
                 for (int j = 0; j < jacobian[i].length; ++j) {
                     final double relativeError = FastMath.abs((finiteDifferencesJacobian[i][j] - jacobian[i][j]) /
                                                               finiteDifferencesJacobian[i][j]);
                     if (j < 3) {
                         errorsP[indexP++] = relativeError;
                     } else {
                         errorsV[indexV++] = relativeError;
                     }
                 }
             }
 
         }
 
         // median errors
         Assertions.assertEquals(0.0, new Median().evaluate(errorsP), 2.1e-10);
         Assertions.assertEquals(0.0, new Median().evaluate(errorsV), 2.1e-10);
 
     }
 
     /** Test the PV constructor with standard deviations for position and velocity given as 2 double.
      */
     @Test
     public void testPVWithSingleStandardDeviations() {
 
         // Context
         Context context = EstimationTestUtils.eccentricContext("regular-data:potential:tides");
 
         // Dummy P, V, T
         final Vector3D     position = context.initialOrbit.getPosition();
         final Vector3D     velocity = context.initialOrbit.getPVCoordinates().getVelocity();
         final AbsoluteDate date     = context.initialOrbit.getDate();
 
         // Initialize standard deviations and weight
         final double sigmaP     = 10.;
         final double sigmaV     = 0.1;
         final double baseWeight = 0.5;
 
         // Reference covariance matrix and correlation coefficients
         final double[][] Pref = new double[6][6];
         for (int i = 0; i < 3; i++) {
             Pref[i][i]     = FastMath.pow(sigmaP, 2);
             Pref[i+3][i+3] = FastMath.pow(sigmaV, 2);
         }
         final double[][] corrCoefRef = MatrixUtils.createRealIdentityMatrix(6).getData();
 
         // Reference propagator numbers
         final ObservableSatellite[] sats = {
             new ObservableSatellite(0),
             new ObservableSatellite(2)
         };
 
         // Create PV measurements
         final PV[] pvs = new PV[2];
         pvs[0] = new PV(date, position, velocity, sigmaP, sigmaV, baseWeight, sats[0]);
         pvs[1] = new PV(date, position, velocity, sigmaP, sigmaV, baseWeight, sats[1]);
 
         // Tolerance
         final double eps = 1e-20; // tolerance
 
         // Check data
         for (int k = 0; k < pvs.length; k++) {
             final PV pv = pvs[k];
 
             // Propagator numbers
             Assertions.assertEquals(sats[k].getPropagatorIndex(), pv.getSatellites().get(0).getPropagatorIndex());
 
             // Weights
             for (int i = 0; i < 6; i++) {
                 Assertions.assertEquals(baseWeight, pv.getBaseWeight()[i], eps);
             }
             // Sigmas
             for (int i = 0; i < 3; i++) {
                 Assertions.assertEquals(sigmaP, pv.getTheoreticalStandardDeviation()[i]  , eps);
                 Assertions.assertEquals(sigmaV, pv.getTheoreticalStandardDeviation()[i+3], eps);
             }
             // Covariances
             final double[][] P = pv.getCovarianceMatrix();
             // Substract with ref and get the norm
             final double normP = MatrixUtils.createRealMatrix(P).subtract(MatrixUtils.createRealMatrix(Pref)).getNorm1();
             Assertions.assertEquals(0., normP, eps);
 
             // Correlation coef
             final double[][] corrCoef = pv.getCorrelationCoefficientsMatrix();
             // Substract with ref and get the norm
             final double normCorrCoef = MatrixUtils.createRealMatrix(corrCoef).subtract(MatrixUtils.createRealMatrix(corrCoefRef)).getNorm1();
             Assertions.assertEquals(0., normCorrCoef, eps);
         }
     }
 
     /** Test the PV constructor with standard deviations for position and velocity given as a 6-sized vector.
      */
     @Test
     public void testPVWithVectorStandardDeviations() {
 
         // Context
         Context context = EstimationTestUtils.eccentricContext("regular-data:potential:tides");
 
         // Dummy P, V, T
         final Vector3D     position = context.initialOrbit.getPosition();
         final Vector3D     velocity = context.initialOrbit.getPVCoordinates().getVelocity();
         final AbsoluteDate date     = context.initialOrbit.getDate();
 
         // Initialize standard deviations and weight
         final double[] sigmaP     = {10., 20., 30.};
         final double[] sigmaV     = {0.1, 0.2, 0.3};
         final double[] sigmaPV    = {10., 20., 30., 0.1, 0.2, 0.3};
         final double baseWeight = 0.5;
 
         // Reference covariance matrix and correlation coefficients
         final double[][] Pref = new double[6][6];
         for (int i = 0; i < 3; i++) {
             Pref[i][i]     = FastMath.pow(sigmaP[i], 2);
             Pref[i+3][i+3] = FastMath.pow(sigmaV[i], 2);
         }
         final double[][] corrCoefRef = MatrixUtils.createRealIdentityMatrix(6).getData();
 
         // Reference propagator numbers
         final ObservableSatellite[] sats = {
             new ObservableSatellite(0),
             new ObservableSatellite(2),
             new ObservableSatellite(0),
             new ObservableSatellite(10)
         };
 
         // Create PV measurements
         final PV[] pvs = new PV[4];
         pvs[0] = new PV(date, position, velocity, sigmaP, sigmaV, baseWeight, sats[0]);
         pvs[1] = new PV(date, position, velocity, sigmaP, sigmaV, baseWeight, sats[1]);
         pvs[2] = new PV(date, position, velocity, sigmaPV, baseWeight, sats[2]);
         pvs[3] = new PV(date, position, velocity, sigmaPV, baseWeight, sats[3]);
 
         // Tolerance
         final double eps = 1e-20; // tolerance
 
         // Check data
         for (int k = 0; k < pvs.length; k++) {
             final PV pv = pvs[k];
 
             // Propagator numbers
             Assertions.assertEquals(sats[k].getPropagatorIndex(), pv.getSatellites().get(0).getPropagatorIndex());
 
             // Weights
             for (int i = 0; i < 6; i++) {
                 Assertions.assertEquals(baseWeight, pv.getBaseWeight()[i], eps);
             }
             // Sigmas
             for (int i = 0; i < 3; i++) {
                 Assertions.assertEquals(sigmaP[i], pv.getTheoreticalStandardDeviation()[i]  , eps);
                 Assertions.assertEquals(sigmaV[i], pv.getTheoreticalStandardDeviation()[i+3], eps);
             }
             // Covariances
             final double[][] P = pv.getCovarianceMatrix();
             // Substract with ref and get the norm
             final double normP = MatrixUtils.createRealMatrix(P).subtract(MatrixUtils.createRealMatrix(Pref)).getNorm1();
             Assertions.assertEquals(0., normP, eps);
 
             // Correlation coef
             final double[][] corrCoef = pv.getCorrelationCoefficientsMatrix();
             // Substract with ref and get the norm
             final double normCorrCoef = MatrixUtils.createRealMatrix(corrCoef).subtract(MatrixUtils.createRealMatrix(corrCoefRef)).getNorm1();
             Assertions.assertEquals(0., normCorrCoef, eps);
         }
     }
 
     /** Test the PV constructor with two 3x3 covariance matrix (one for position, the other for velocity) as input.
      */
     @Test
     public void testPVWithTwoCovarianceMatrices() {
         // Context
         Context context = EstimationTestUtils.eccentricContext("regular-data:potential:tides");
 
         // Dummy P, V, T
         final Vector3D     position = context.initialOrbit.getPosition();
         final Vector3D     velocity = context.initialOrbit.getPVCoordinates().getVelocity();
         final AbsoluteDate date     = context.initialOrbit.getDate();
 
         // Initialize standard deviations and weight
         final double[][] positionP = {{100., 400., 1200.}, {400., 400., 1800.}, {1200., 1800., 900.}};
         final double[][] velocityP = {{0.01, 0.04, 0.12 }, {0.04, 0.04, 0.18 }, {0.12 , 0.18 , 0.09}};
         final double baseWeight = 0.5;
 
         // Reference covariance matrix and correlation coefficients
         final double[][] Pref = new double[6][6];
         for (int i = 0; i < 3; i++) {
             for (int j = i; j < 3; j++) {
                 Pref[i][j]     = positionP[i][j];
                 Pref[j][i]     = positionP[i][j];
                 Pref[i+3][j+3] = velocityP[i][j];
                 Pref[j+3][i+3] = velocityP[i][j];
             }
         }
         final double[][] corrCoefRef3 = {{1., 2., 4.}, {2., 1., 3.}, {4., 3., 1.}};
         final double[][] corrCoefRef  = new double[6][6];
         for (int i = 0; i < 3; i++) {
             for (int j = i; j < 3; j++) {
                 corrCoefRef[i][j]     = corrCoefRef3[i][j];
                 corrCoefRef[j][i]     = corrCoefRef3[i][j];
                 corrCoefRef[i+3][j+3] = corrCoefRef3[i][j];
                 corrCoefRef[j+3][i+3] = corrCoefRef3[i][j];
             }
         }
 
         // Reference propagator numbers
         final ObservableSatellite[] sats = {
             new ObservableSatellite(0),
             new ObservableSatellite(2)
         };
 
         // Reference standard deviations
         final double[] sigmaP = {10., 20., 30.};
         final double[] sigmaV = {0.1, 0.2, 0.3};
 
         // Create PV measurements
         final PV[] pvs = new PV[2];
         pvs[0] = new PV(date, position, velocity, positionP, velocityP, baseWeight, sats[0]);
         pvs[1] = new PV(date, position, velocity, positionP, velocityP, baseWeight, sats[1]);
 
         // Tolerance
         final double eps = 6.7e-16; // tolerance
 
         // Check data
         for (int k = 0; k < pvs.length; k++) {
             final PV pv = pvs[k];
 
             // Propagator numbers
             Assertions.assertEquals(sats[k].getPropagatorIndex(), pv.getSatellites().get(0).getPropagatorIndex());
 
             // Weights
             for (int i = 0; i < 6; i++) {
                 Assertions.assertEquals(baseWeight, pv.getBaseWeight()[i], eps);
             }
             // Sigmas
             for (int i = 0; i < 3; i++) {
                 Assertions.assertEquals(sigmaP[i], pv.getTheoreticalStandardDeviation()[i]  , eps);
                 Assertions.assertEquals(sigmaV[i], pv.getTheoreticalStandardDeviation()[i+3], eps);
             }
             // Covariances
             final double[][] P = pv.getCovarianceMatrix();
             // Substract with ref and get the norm
             final double normP = MatrixUtils.createRealMatrix(P).subtract(MatrixUtils.createRealMatrix(Pref)).getNorm1();
             Assertions.assertEquals(0., normP, eps);
 
             // Correlation coef
             final double[][] corrCoef = pv.getCorrelationCoefficientsMatrix();
             // Substract with ref and get the norm
             final double normCorrCoef = MatrixUtils.createRealMatrix(corrCoef).subtract(MatrixUtils.createRealMatrix(corrCoefRef)).getNorm1();
             Assertions.assertEquals(0., normCorrCoef, eps);
         }
 
     }
 
     /** Test the PV constructor with one 6x6 covariance matrix as input.
      */
     @Test
     public void testPVWithCovarianceMatrix() {
         // Context
         Context context = EstimationTestUtils.eccentricContext("regular-data:potential:tides");
 
         // Dummy P, V, T
         final Vector3D     position = context.initialOrbit.getPosition();
         final Vector3D     velocity = context.initialOrbit.getPVCoordinates().getVelocity();
         final AbsoluteDate date     = context.initialOrbit.getDate();
 
         // Initialize standard deviations, weight and corr coeff
         final double[] sigmaPV = {10., 20., 30., 0.1, 0.2, 0.3};
         final double baseWeight = 0.5;
         final double[][] corrCoefRef = new double[6][6];
         for (int i = 0; i < 6; i++) {
             for (int j = 0; j < 6; j++) {
                 if (i == j) {
                     corrCoefRef[i][i] = 1.;
                 } else {
                     corrCoefRef[i][j] = i + j + 1;
                 }
             }
         }
 
         // Reference covariance matrix
         final double[][] Pref = new double[6][6];
         for (int i = 0; i < 6; i++) {
             for (int j = 0; j < 6; j++) {
                 Pref[i][j] = corrCoefRef[i][j]*sigmaPV[i]*sigmaPV[j];
             }
         }
 
         // Reference propagator numbers
         final ObservableSatellite[] sats = {
             new ObservableSatellite(0),
             new ObservableSatellite(2)
         };
 
         // Create PV measurements
         final PV[] pvs = new PV[2];
         pvs[0] = new PV(date, position, velocity, Pref, baseWeight, sats[0]);
         pvs[1] = new PV(date, position, velocity, Pref, baseWeight, sats[1]);
 
         // Tolerance
         final double eps = 1.8e-15; // tolerance
 
         // Check data
         for (int k = 0; k < pvs.length; k++) {
             final PV pv = pvs[k];
 
             // Propagator numbers
             Assertions.assertEquals(sats[k].getPropagatorIndex(), pv.getSatellites().get(0).getPropagatorIndex());
 
             // Weights
             for (int i = 0; i < 6; i++) {
                 Assertions.assertEquals(baseWeight, pv.getBaseWeight()[i], eps);
             }
             // Sigmas
             for (int i = 0; i < 6; i++) {
                 Assertions.assertEquals(sigmaPV[i], pv.getTheoreticalStandardDeviation()[i]  , eps);
             }
             // Covariances
             final double[][] P = pv.getCovarianceMatrix();
             // Substract with ref and get the norm
             final double normP = MatrixUtils.createRealMatrix(P).subtract(MatrixUtils.createRealMatrix(Pref)).getNorm1();
             Assertions.assertEquals(0., normP, eps);
 
             // Correlation coef
             final double[][] corrCoef = pv.getCorrelationCoefficientsMatrix();
             // Substract with ref and get the norm
             final double normCorrCoef = MatrixUtils.createRealMatrix(corrCoef).subtract(MatrixUtils.createRealMatrix(corrCoefRef)).getNorm1();
             Assertions.assertEquals(0., normCorrCoef, eps);
         }
 
     }
 
     /** Test exceptions raised if the covariance matrix does not have the proper size. */
     @Test
     public void testExceptions() {
         // Context
         Context context = EstimationTestUtils.eccentricContext("regular-data:potential:tides");
 
         // Dummy P, V, T
         final Vector3D     position = context.initialOrbit.getPosition();
         final Vector3D     velocity = context.initialOrbit.getPVCoordinates().getVelocity();
         final AbsoluteDate date     = context.initialOrbit.getDate();
         final double       weight   = 1.;
 
         // Build with two 3-sized vectors
         try {
             new PV(date, position, velocity, new double[] {0., 0., 0.}, new double[] {1.}, weight, new ObservableSatellite(0));
             Assertions.fail("An OrekitException should have been thrown");
         } catch (OrekitException e) {
             // An exception should indeed be raised here
         }
 
         // Build with one 6-sized vector
         try {
             new PV(date, position, velocity, new double[] {0., 0., 0.}, weight, new ObservableSatellite(0));
             Assertions.fail("An OrekitException should have been thrown");
         } catch (OrekitException e) {
             // An exception should indeed be raised here
         }
 
         // Build with two 3x3 matrices
         try {
             new PV(date, position, velocity, new double[][] {{0., 0.}, {0., 0.}},
                    new double[][] {{0., 0.}, {0., 0.}}, weight, new ObservableSatellite(0));
             Assertions.fail("An OrekitException should have been thrown");
         } catch (OrekitException e) {
             // An exception should indeed be raised here
         }
 
         // Build with one 6x6 matrix
         try {
             new PV(date, position, velocity, new double[][] {{0., 0.}, {0., 0.}}, weight, new ObservableSatellite(0));
             Assertions.fail("An OrekitException should have been thrown");
         } catch (OrekitException e) {
             // An exception should indeed be raised here
         }
     }
 }