private static void modi(DoubleMatrix syndrome, int radix) {
for (int i = 0; i < syndrome.getRows(); i++) {
for (int j = 0; j < syndrome.getColumns(); j++) {
syndrome.put(i, j, ((int) syndrome.get(i, j)) % radix);
}
}
}
public StateSpaceModel(
DoubleMatrix state_transition_matrix,
DoubleMatrix observation_matrix,
DoubleMatrix transition_covariance_matrix,
DoubleMatrix observation_covariance_matrix,
DoubleMatrix initial_state_mean,
DoubleMatrix initial_state_covariance,
DoubleMatrix[] observations) {
dimension_of_states_ = observation_matrix.getColumns();
dimension_of_observations_ = observation_matrix.getRows();
observation_matrix_ref_ = observation_matrix;
if (!state_transition_matrix.isSquare()
|| state_transition_matrix.getRows() != dimension_of_states_) {
throw new MatrixDimensionMismatchException(
state_transition_matrix.getRows(),
state_transition_matrix.getColumns(),
dimension_of_states_,
dimension_of_states_);
}
state_transition_matrix_ref_ = state_transition_matrix;
if (!transition_covariance_matrix.isSquare()
|| transition_covariance_matrix.getRows() != dimension_of_states_) {
throw new MatrixDimensionMismatchException(
transition_covariance_matrix.getRows(),
transition_covariance_matrix.getColumns(),
dimension_of_states_,
dimension_of_states_);
}
transition_covariance_matrix_ref_ = transition_covariance_matrix;
if (!observation_covariance_matrix.isSquare()
|| observation_covariance_matrix.getRows() != dimension_of_observations_) {
throw new MatrixDimensionMismatchException(
observation_covariance_matrix.getRows(),
observation_covariance_matrix.getColumns(),
dimension_of_observations_,
dimension_of_observations_);
}
observation_covariance_matrix_ref_ = observation_covariance_matrix;
if (initial_state_mean.getRows() != dimension_of_states_
|| initial_state_mean.getColumns() != 1) {
throw new MatrixDimensionMismatchException(
initial_state_mean.getRows(), initial_state_mean.getColumns(), dimension_of_states_, 1);
}
initial_state_mean_ref_ = initial_state_mean;
if (!initial_state_covariance.isSquare()
|| initial_state_covariance.getRows() != dimension_of_states_) {
throw new MatrixDimensionMismatchException(
initial_state_covariance.getRows(),
initial_state_covariance.getColumns(),
dimension_of_states_,
dimension_of_states_);
}
initial_state_covariance_ref_ = initial_state_covariance;
number_of_observations_ = observations.length;
observations_ref_ = observations;
estimated_state_means_ = new DoubleMatrix[number_of_observations_];
estimated_state_covariances_ = new DoubleMatrix[number_of_observations_];
predicted_observation_means_ = new DoubleMatrix[number_of_observations_];
predicted_observation_covariances_ = new DoubleMatrix[number_of_observations_];
estimated_means_ = new DoubleMatrix[number_of_observations_];
estimated_covariances_ = new DoubleMatrix[number_of_observations_];
UpdateFilteredStates();
CalculateLogLikelihood();
}
