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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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   * Unless required by applicable law or agreed to in writing, software
   * distributed under the License is distributed on an "AS IS" BASIS,
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   * See the License for the specific language governing permissions and
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  package org.orekit.estimation.sequential;
  
  import java.util.List;
  
  import org.orekit.annotation.DefaultDataContext;
  import org.orekit.propagation.PropagationType;
  import org.orekit.propagation.Propagator;
  import org.orekit.propagation.SpacecraftState;
  import org.orekit.propagation.analytical.tle.TLEJacobiansMapper;
  import org.orekit.propagation.analytical.tle.TLEPartialDerivativesEquations;
  import org.orekit.propagation.analytical.tle.TLEPropagator;
  import org.orekit.propagation.conversion.OrbitDeterminationPropagatorBuilder;
  import org.orekit.propagation.integration.AbstractJacobiansMapper;
  import org.orekit.utils.ParameterDriversList;
  
  /** Class defining the process model dynamics to use with a {@link KalmanEstimator}.
   * <p>
   * This class is an adaption of the {@link KalmanModel} class
   * but for the {@link TLEPropagator TLE propagator}.
   * </p>
   * @author Romain Gerbaud
   * @author Maxime Journot
   * @author Bryan Cazabonne
   * @author Thomas Paulet
   * @since 11.0
   */
  public class TLEKalmanModel extends AbstractKalmanModel {
  
      /** Kalman process model constructor (package private).
       * @param propagatorBuilders propagators builders used to evaluate the orbits.
       * @param covarianceMatricesProviders providers for covariance matrices
       * @param estimatedMeasurementParameters measurement parameters to estimate
       * @param measurementProcessNoiseMatrix provider for measurement process noise matrix
       */
      public TLEKalmanModel(final List<OrbitDeterminationPropagatorBuilder> propagatorBuilders,
                            final List<CovarianceMatrixProvider> covarianceMatricesProviders,
                            final ParameterDriversList estimatedMeasurementParameters,
                            final CovarianceMatrixProvider measurementProcessNoiseMatrix) {
          // call super constructor
          super(propagatorBuilders, covarianceMatricesProviders, estimatedMeasurementParameters,
                measurementProcessNoiseMatrix, new TLEJacobiansMapper[propagatorBuilders.size()]);
      }
  
      /** {@inheritDoc} */
      @Override
      @DefaultDataContext
      protected void updateReferenceTrajectories(final Propagator[] propagators,
                                                 final PropagationType pType,
                                                 final PropagationType sType) {
  
          // Update the reference trajectory propagator
          setReferenceTrajectories(propagators);
  
          // Jacobian mappers
          final AbstractJacobiansMapper[] mappers = getMappers();
  
          for (int k = 0; k < propagators.length; ++k) {
              // Link the partial derivatives to this new propagator
              final String equationName = KalmanEstimator.class.getName() + "-derivatives-" + k;
              final TLEPartialDerivativesEquations pde = new TLEPartialDerivativesEquations(equationName, (TLEPropagator) getReferenceTrajectories()[k]);
  
              // Reset the Jacobians
              final SpacecraftState rawState = getReferenceTrajectories()[k].getInitialState();
              final SpacecraftState stateWithDerivatives = pde.setInitialJacobians(rawState);
              ((TLEPropagator) getReferenceTrajectories()[k]).resetInitialState(stateWithDerivatives);
              mappers[k] = pde.getMapper();
          }
  
          // Update Jacobian mappers
          setMappers(mappers);
  
      }
  
      /** {@inheritDoc} */
      @Override
      @DefaultDataContext
      protected void analyticalDerivativeComputations(final AbstractJacobiansMapper mapper, final SpacecraftState state) {
          ((TLEJacobiansMapper) mapper).analyticalDerivatives(state);
      }
  
  }