use of org.hipparchus.linear.QRDecomposition in project Orekit by CS-SI.
the class JacobiansMapper method setInitialJacobians.
/**
* Set the Jacobian with respect to state into a one-dimensional additional state array.
* <p>
* This method converts the Jacobians to Cartesian parameters and put the converted data
* in the one-dimensional {@code p} array.
* </p>
* @param state spacecraft state
* @param dY1dY0 Jacobian of current state at time t₁
* with respect to state at some previous time t₀
* @param dY1dP Jacobian of current state at time t₁
* with respect to parameters (may be null if there are no parameters)
* @param p placeholder where to put the one-dimensional additional state
* @see #getStateJacobian(SpacecraftState, double[][])
*/
void setInitialJacobians(final SpacecraftState state, final double[][] dY1dY0, final double[][] dY1dP, final double[] p) {
// set up a converter between state parameters and Cartesian parameters
final RealMatrix dY1dC1 = new Array2DRowRealMatrix(getdYdC(state), false);
final DecompositionSolver solver = new QRDecomposition(dY1dC1).getSolver();
// convert the provided state Jacobian to Cartesian parameters
final RealMatrix dC1dY0 = solver.solve(new Array2DRowRealMatrix(dY1dY0, false));
// map the converted state Jacobian to one-dimensional array
int index = 0;
for (int i = 0; i < STATE_DIMENSION; ++i) {
for (int j = 0; j < STATE_DIMENSION; ++j) {
p[index++] = dC1dY0.getEntry(i, j);
}
}
if (parameters.getNbParams() != 0) {
// convert the provided state Jacobian to Cartesian parameters
final RealMatrix dC1dP = solver.solve(new Array2DRowRealMatrix(dY1dP, false));
// map the converted parameters Jacobian to one-dimensional array
for (int i = 0; i < STATE_DIMENSION; ++i) {
for (int j = 0; j < parameters.getNbParams(); ++j) {
p[index++] = dC1dP.getEntry(i, j);
}
}
}
}
use of org.hipparchus.linear.QRDecomposition in project Orekit by CS-SI.
the class AngularCoordinates method inverseCrossProducts.
/**
* Find a vector from two known cross products.
* <p>
* We want to find Ω such that: Ω ⨯ v₁ = c₁ and Ω ⨯ v₂ = c₂
* </p>
* <p>
* The first equation (Ω ⨯ v₁ = c₁) will always be fulfilled exactly,
* and the second one will be fulfilled if possible.
* </p>
* @param v1 vector forming the first known cross product
* @param c1 know vector for cross product Ω ⨯ v₁
* @param v2 vector forming the second known cross product
* @param c2 know vector for cross product Ω ⨯ v₂
* @param tolerance relative tolerance factor used to check singularities
* @return vector Ω such that: Ω ⨯ v₁ = c₁ and Ω ⨯ v₂ = c₂
* @exception MathIllegalArgumentException if vectors are inconsistent and
* no solution can be found
*/
private static Vector3D inverseCrossProducts(final Vector3D v1, final Vector3D c1, final Vector3D v2, final Vector3D c2, final double tolerance) throws MathIllegalArgumentException {
final double v12 = v1.getNormSq();
final double v1n = FastMath.sqrt(v12);
final double v22 = v2.getNormSq();
final double v2n = FastMath.sqrt(v22);
final double threshold = tolerance * FastMath.max(v1n, v2n);
Vector3D omega;
try {
// create the over-determined linear system representing the two cross products
final RealMatrix m = MatrixUtils.createRealMatrix(6, 3);
m.setEntry(0, 1, v1.getZ());
m.setEntry(0, 2, -v1.getY());
m.setEntry(1, 0, -v1.getZ());
m.setEntry(1, 2, v1.getX());
m.setEntry(2, 0, v1.getY());
m.setEntry(2, 1, -v1.getX());
m.setEntry(3, 1, v2.getZ());
m.setEntry(3, 2, -v2.getY());
m.setEntry(4, 0, -v2.getZ());
m.setEntry(4, 2, v2.getX());
m.setEntry(5, 0, v2.getY());
m.setEntry(5, 1, -v2.getX());
final RealVector rhs = MatrixUtils.createRealVector(new double[] { c1.getX(), c1.getY(), c1.getZ(), c2.getX(), c2.getY(), c2.getZ() });
// find the best solution we can
final DecompositionSolver solver = new QRDecomposition(m, threshold).getSolver();
final RealVector v = solver.solve(rhs);
omega = new Vector3D(v.getEntry(0), v.getEntry(1), v.getEntry(2));
} catch (MathIllegalArgumentException miae) {
if (miae.getSpecifier() == LocalizedCoreFormats.SINGULAR_MATRIX) {
// handle some special cases for which we can compute a solution
final double c12 = c1.getNormSq();
final double c1n = FastMath.sqrt(c12);
final double c22 = c2.getNormSq();
final double c2n = FastMath.sqrt(c22);
if (c1n <= threshold && c2n <= threshold) {
// simple special case, velocities are cancelled
return Vector3D.ZERO;
} else if (v1n <= threshold && c1n >= threshold) {
// this is inconsistent, if v₁ is zero, c₁ must be 0 too
throw new MathIllegalArgumentException(LocalizedCoreFormats.NUMBER_TOO_LARGE, c1n, 0, true);
} else if (v2n <= threshold && c2n >= threshold) {
// this is inconsistent, if v₂ is zero, c₂ must be 0 too
throw new MathIllegalArgumentException(LocalizedCoreFormats.NUMBER_TOO_LARGE, c2n, 0, true);
} else if (Vector3D.crossProduct(v1, v2).getNorm() <= threshold && v12 > threshold) {
// simple special case, v₂ is redundant with v₁, we just ignore it
// use the simplest Ω: orthogonal to both v₁ and c₁
omega = new Vector3D(1.0 / v12, Vector3D.crossProduct(v1, c1));
} else {
throw miae;
}
} else {
throw miae;
}
}
// check results
final double d1 = Vector3D.distance(Vector3D.crossProduct(omega, v1), c1);
if (d1 > threshold) {
throw new MathIllegalArgumentException(LocalizedCoreFormats.NUMBER_TOO_LARGE, d1, 0, true);
}
final double d2 = Vector3D.distance(Vector3D.crossProduct(omega, v2), c2);
if (d2 > threshold) {
throw new MathIllegalArgumentException(LocalizedCoreFormats.NUMBER_TOO_LARGE, d2, 0, true);
}
return omega;
}
use of org.hipparchus.linear.QRDecomposition in project Orekit by CS-SI.
the class Orbit method createInverseJacobian.
/**
* Create an inverse Jacobian.
* @param type type of the position angle to use
* @return inverse Jacobian
*/
private double[][] createInverseJacobian(final PositionAngle type) {
// get the direct Jacobian
final double[][] directJacobian = new double[6][6];
getJacobianWrtCartesian(type, directJacobian);
// invert the direct Jacobian
final RealMatrix matrix = MatrixUtils.createRealMatrix(directJacobian);
final DecompositionSolver solver = new QRDecomposition(matrix).getSolver();
return solver.getInverse().getData();
}
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