public void test11() throws Throwable {
java.lang.Double var0 = new java.lang.Double((-1.0d));
java.lang.Double var1 = new java.lang.Double(0.0d);
java.lang.Double var2 = new java.lang.Double((-1.0d));
double[] var3 = new double[] {var0, var1, var2};
org.apache.commons.math.linear.ArrayRealVector var4 =
new org.apache.commons.math.linear.ArrayRealVector(var3);
java.lang.Double var5 = new java.lang.Double((-1.0d));
java.lang.Double var6 = new java.lang.Double(0.0d);
java.lang.Double var7 = new java.lang.Double((-1.0d));
double[] var8 = new double[] {var5, var6, var7};
org.apache.commons.math.linear.ArrayRealVector var9 =
new org.apache.commons.math.linear.ArrayRealVector(var8);
org.apache.commons.math.linear.RealVector var10 =
var4.ebeDivide((org.apache.commons.math.linear.RealVector) var9);
java.lang.Double var11 = new java.lang.Double((-1.0d));
java.lang.Double var12 = new java.lang.Double(10.0d);
java.lang.Double var13 = new java.lang.Double(100.0d);
int var14 =
org.apache.commons.math.util.MathUtils.compareTo(
(double) var11, (double) var12, (double) var13);
org.apache.commons.math.linear.RealVector var15 = var9.mapPowToSelf((double) var13);
java.lang.Double[] var16 = new java.lang.Double[] {var13};
org.apache.commons.math.linear.ArrayRealVector var17 =
new org.apache.commons.math.linear.ArrayRealVector(var16);
org.apache.commons.math.linear.RealVector var18 = var17.mapCbrtToSelf();
org.apache.commons.math.linear.RealVector var19 = var17.mapFloorToSelf();
org.apache.commons.math.linear.RealVector var20 = var17.mapCosh();
org.apache.commons.math.linear.RealVector var21 = var17.mapAcos();
java.lang.Double var22 = new java.lang.Double((-1.0d));
double[] var23 = new double[] {var22};
org.apache.commons.math.linear.OpenMapRealVector var24 =
new org.apache.commons.math.linear.OpenMapRealVector(var23);
java.lang.Double var25 = new java.lang.Double((-1.0d));
double[] var26 = new double[] {var25};
org.apache.commons.math.linear.OpenMapRealVector var27 =
new org.apache.commons.math.linear.OpenMapRealVector(var26);
org.apache.commons.math.linear.OpenMapRealVector var28 = var24.add(var27);
org.apache.commons.math.linear.OpenMapRealVector var29 =
new org.apache.commons.math.linear.OpenMapRealVector(var28);
java.lang.Double var30 = new java.lang.Double((-1.0d));
java.lang.Double var31 = new java.lang.Double(0.0d);
java.lang.Double var32 = new java.lang.Double((-1.0d));
double[] var33 = new double[] {var30, var31, var32};
org.apache.commons.math.linear.ArrayRealVector var34 =
new org.apache.commons.math.linear.ArrayRealVector(var33);
java.lang.Double var35 = new java.lang.Double((-1.0d));
java.lang.Double var36 = new java.lang.Double(0.0d);
java.lang.Double var37 = new java.lang.Double((-1.0d));
double[] var38 = new double[] {var35, var36, var37};
org.apache.commons.math.linear.ArrayRealVector var39 =
new org.apache.commons.math.linear.ArrayRealVector(var38);
org.apache.commons.math.linear.RealVector var40 =
var34.ebeDivide((org.apache.commons.math.linear.RealVector) var39);
java.lang.Double var41 = new java.lang.Double(0.0d);
java.lang.Double var42 = new java.lang.Double((-1.0d));
java.lang.Double var43 = new java.lang.Double((-1.0d));
int var44 =
org.apache.commons.math.util.MathUtils.compareTo(
(double) var41, (double) var42, (double) var43);
org.apache.commons.math.linear.RealVector var45 = var34.mapDivide((double) var42);
org.apache.commons.math.linear.RealVector var46 = var29.mapSubtractToSelf((double) var42);
boolean var47 = var17.equals((java.lang.Object) var42);
// Checks the contract: equals-hashcode on var15 and var45
assertTrue(
"Contract failed: equals-hashcode on var15 and var45",
var15.equals(var45) ? var15.hashCode() == var45.hashCode() : true);
// Checks the contract: equals-hashcode on var45 and var15
assertTrue(
"Contract failed: equals-hashcode on var45 and var15",
var45.equals(var15) ? var45.hashCode() == var15.hashCode() : true);
}
public void test4() throws Throwable {
java.lang.Double var0 = new java.lang.Double((-1.0d));
double[] var1 = new double[] {var0};
org.apache.commons.math.linear.OpenMapRealVector var2 =
new org.apache.commons.math.linear.OpenMapRealVector(var1);
int var3 = var2.getDimension();
java.lang.Double var4 = new java.lang.Double((-1.0d));
java.lang.Double var5 = new java.lang.Double(0.0d);
java.lang.Double var6 = new java.lang.Double((-1.0d));
double[] var7 = new double[] {var4, var5, var6};
org.apache.commons.math.linear.ArrayRealVector var8 =
new org.apache.commons.math.linear.ArrayRealVector(var7);
java.lang.Double var9 = new java.lang.Double((-1.0d));
java.lang.Double var10 = new java.lang.Double(0.0d);
java.lang.Double var11 = new java.lang.Double((-1.0d));
double[] var12 = new double[] {var9, var10, var11};
org.apache.commons.math.linear.ArrayRealVector var13 =
new org.apache.commons.math.linear.ArrayRealVector(var12);
org.apache.commons.math.linear.RealVector var14 =
var8.ebeDivide((org.apache.commons.math.linear.RealVector) var13);
java.lang.Double var15 = new java.lang.Double((-1.0d));
java.lang.Double var16 = new java.lang.Double(10.0d);
java.lang.Double var17 = new java.lang.Double(100.0d);
int var18 =
org.apache.commons.math.util.MathUtils.compareTo(
(double) var15, (double) var16, (double) var17);
org.apache.commons.math.linear.RealVector var19 = var13.mapPowToSelf((double) var17);
org.apache.commons.math.linear.ArrayRealVector var20 =
new org.apache.commons.math.linear.ArrayRealVector(var3, var17);
java.lang.Double var21 = new java.lang.Double((-1.0d));
double[] var22 = new double[] {var21};
org.apache.commons.math.linear.OpenMapRealVector var23 =
new org.apache.commons.math.linear.OpenMapRealVector(var22);
java.lang.Double var24 = new java.lang.Double((-1.0d));
double[] var25 = new double[] {var24};
org.apache.commons.math.linear.OpenMapRealVector var26 =
new org.apache.commons.math.linear.OpenMapRealVector(var25);
org.apache.commons.math.linear.OpenMapRealVector var27 = var23.add(var26);
org.apache.commons.math.linear.OpenMapRealVector var28 =
new org.apache.commons.math.linear.OpenMapRealVector(var27);
java.lang.Double var29 = new java.lang.Double((-1.0d));
java.lang.Double var30 = new java.lang.Double(0.0d);
java.lang.Double var31 = new java.lang.Double((-1.0d));
double[] var32 = new double[] {var29, var30, var31};
org.apache.commons.math.linear.ArrayRealVector var33 =
new org.apache.commons.math.linear.ArrayRealVector(var32);
java.lang.Double var34 = new java.lang.Double((-1.0d));
java.lang.Double var35 = new java.lang.Double(0.0d);
java.lang.Double var36 = new java.lang.Double((-1.0d));
double[] var37 = new double[] {var34, var35, var36};
org.apache.commons.math.linear.ArrayRealVector var38 =
new org.apache.commons.math.linear.ArrayRealVector(var37);
org.apache.commons.math.linear.RealVector var39 =
var33.ebeDivide((org.apache.commons.math.linear.RealVector) var38);
java.lang.Double var40 = new java.lang.Double(0.0d);
java.lang.Double var41 = new java.lang.Double((-1.0d));
java.lang.Double var42 = new java.lang.Double((-1.0d));
int var43 =
org.apache.commons.math.util.MathUtils.compareTo(
(double) var40, (double) var41, (double) var42);
org.apache.commons.math.linear.RealVector var44 = var33.mapDivide((double) var41);
org.apache.commons.math.linear.RealVector var45 = var28.mapSubtractToSelf((double) var41);
org.apache.commons.math.linear.RealVector var46 = var20.projection(var45);
// Checks the contract: equals-hashcode on var19 and var44
assertTrue(
"Contract failed: equals-hashcode on var19 and var44",
var19.equals(var44) ? var19.hashCode() == var44.hashCode() : true);
// Checks the contract: equals-hashcode on var44 and var19
assertTrue(
"Contract failed: equals-hashcode on var44 and var19",
var44.equals(var19) ? var44.hashCode() == var19.hashCode() : true);
}
private int getMaxDeltaVIdx() { // only Vmag are considered here
ArrayRealVector temp = (ArrayRealVector) this.getPredStepSolver().getDeltaV().mapAbs();
return temp.getMaxIndex();
}
public void test13() throws Throwable {
java.lang.Double var0 = new java.lang.Double((-1.0d));
double[] var1 = new double[] {var0};
org.apache.commons.math.linear.OpenMapRealVector var2 =
new org.apache.commons.math.linear.OpenMapRealVector(var1);
java.lang.Double var3 = new java.lang.Double((-1.0d));
double[] var4 = new double[] {var3};
org.apache.commons.math.linear.OpenMapRealVector var5 =
new org.apache.commons.math.linear.OpenMapRealVector(var4);
org.apache.commons.math.linear.OpenMapRealVector var6 = var2.add(var5);
org.apache.commons.math.linear.OpenMapRealVector var7 =
new org.apache.commons.math.linear.OpenMapRealVector(var6);
java.lang.Double var8 = new java.lang.Double((-1.0d));
java.lang.Double var9 = new java.lang.Double(0.0d);
java.lang.Double var10 = new java.lang.Double((-1.0d));
double[] var11 = new double[] {var8, var9, var10};
org.apache.commons.math.linear.ArrayRealVector var12 =
new org.apache.commons.math.linear.ArrayRealVector(var11);
java.lang.Double var13 = new java.lang.Double((-1.0d));
java.lang.Double var14 = new java.lang.Double(0.0d);
java.lang.Double var15 = new java.lang.Double((-1.0d));
double[] var16 = new double[] {var13, var14, var15};
org.apache.commons.math.linear.ArrayRealVector var17 =
new org.apache.commons.math.linear.ArrayRealVector(var16);
org.apache.commons.math.linear.RealVector var18 =
var12.ebeDivide((org.apache.commons.math.linear.RealVector) var17);
java.lang.Double var19 = new java.lang.Double(0.0d);
java.lang.Double var20 = new java.lang.Double((-1.0d));
java.lang.Double var21 = new java.lang.Double((-1.0d));
int var22 =
org.apache.commons.math.util.MathUtils.compareTo(
(double) var19, (double) var20, (double) var21);
org.apache.commons.math.linear.RealVector var23 = var12.mapDivide((double) var20);
org.apache.commons.math.linear.RealVector var24 = var7.mapSubtractToSelf((double) var20);
double var25 = var7.getSparcity();
java.lang.Double var26 = new java.lang.Double((-1.0d));
double[] var27 = new double[] {var26};
org.apache.commons.math.linear.OpenMapRealVector var28 =
new org.apache.commons.math.linear.OpenMapRealVector(var27);
int var29 = var28.getDimension();
java.lang.Double var30 = new java.lang.Double((-1.0d));
java.lang.Double var31 = new java.lang.Double(0.0d);
java.lang.Double var32 = new java.lang.Double((-1.0d));
double[] var33 = new double[] {var30, var31, var32};
org.apache.commons.math.linear.ArrayRealVector var34 =
new org.apache.commons.math.linear.ArrayRealVector(var33);
java.lang.Double var35 = new java.lang.Double((-1.0d));
java.lang.Double var36 = new java.lang.Double(0.0d);
java.lang.Double var37 = new java.lang.Double((-1.0d));
double[] var38 = new double[] {var35, var36, var37};
org.apache.commons.math.linear.ArrayRealVector var39 =
new org.apache.commons.math.linear.ArrayRealVector(var38);
org.apache.commons.math.linear.RealVector var40 =
var34.ebeDivide((org.apache.commons.math.linear.RealVector) var39);
java.lang.Double var41 = new java.lang.Double((-1.0d));
java.lang.Double var42 = new java.lang.Double(10.0d);
java.lang.Double var43 = new java.lang.Double(100.0d);
int var44 =
org.apache.commons.math.util.MathUtils.compareTo(
(double) var41, (double) var42, (double) var43);
org.apache.commons.math.linear.RealVector var45 = var39.mapPowToSelf((double) var43);
org.apache.commons.math.linear.ArrayRealVector var46 =
new org.apache.commons.math.linear.ArrayRealVector(var29, var43);
java.lang.Double var47 = new java.lang.Double((-1.0d));
java.lang.Double var48 = new java.lang.Double(10.0d);
java.lang.Double var49 = new java.lang.Double(1.0d);
java.lang.Double var50 = new java.lang.Double(1.0d);
boolean var51 = org.apache.commons.math.util.MathUtils.equals((double) var49, (double) var50);
int var52 =
org.apache.commons.math.util.MathUtils.compareTo(
(double) var47, (double) var48, (double) var49);
java.lang.Double var53 = new java.lang.Double((-1.0d));
java.lang.Double var54 = new java.lang.Double(0.0d);
java.lang.Double var55 = new java.lang.Double((-1.0d));
double[] var56 = new double[] {var53, var54, var55};
org.apache.commons.math.linear.ArrayRealVector var57 =
new org.apache.commons.math.linear.ArrayRealVector(var56);
java.lang.Double var58 = new java.lang.Double((-1.0d));
java.lang.Double var59 = new java.lang.Double(0.0d);
java.lang.Double var60 = new java.lang.Double((-1.0d));
double[] var61 = new double[] {var58, var59, var60};
org.apache.commons.math.linear.ArrayRealVector var62 =
new org.apache.commons.math.linear.ArrayRealVector(var61);
org.apache.commons.math.linear.RealVector var63 =
var57.ebeDivide((org.apache.commons.math.linear.RealVector) var62);
org.apache.commons.math.linear.RealVector var64 = var57.mapLog10ToSelf();
java.lang.Double var65 = new java.lang.Double(1.0d);
org.apache.commons.math.linear.RealVector var66 = var57.mapMultiplyToSelf((double) var65);
double var67 = org.apache.commons.math.util.MathUtils.indicator((double) var65);
java.lang.Double var68 = new java.lang.Double((-1.0d));
java.lang.Double var69 = new java.lang.Double(10.0d);
java.lang.Double var70 = new java.lang.Double(100.0d);
int var71 =
org.apache.commons.math.util.MathUtils.compareTo(
(double) var68, (double) var69, (double) var70);
double var72 =
org.apache.commons.math.util.MathUtils.normalizeAngle((double) var65, (double) var69);
java.lang.Integer var73 = new java.lang.Integer(10);
java.lang.Integer var74 = new java.lang.Integer(10);
double var75 =
org.apache.commons.math.util.MathUtils.binomialCoefficientLog((int) var73, (int) var74);
java.lang.Integer var76 = new java.lang.Integer(0);
java.lang.Long var77 = new java.lang.Long(100L);
int var78 = org.apache.commons.math.util.MathUtils.pow((int) var76, (long) var77);
double var79 =
org.apache.commons.math.util.MathUtils.binomialCoefficientLog((int) var74, (int) var76);
boolean var80 =
org.apache.commons.math.util.MathUtils.equalsIncludingNaN(
(double) var49, (double) var69, (int) var76);
org.apache.commons.math.linear.RealVector var81 = var46.mapMultiplyToSelf((double) var49);
org.apache.commons.math.linear.RealVector var82 = var7.mapPow((double) var49);
// Checks the contract: equals-hashcode on var23 and var45
assertTrue(
"Contract failed: equals-hashcode on var23 and var45",
var23.equals(var45) ? var23.hashCode() == var45.hashCode() : true);
// Checks the contract: equals-hashcode on var45 and var23
assertTrue(
"Contract failed: equals-hashcode on var45 and var23",
var45.equals(var23) ? var45.hashCode() == var23.hashCode() : true);
}
/**
* Solve an estimation problem using a least squares criterion.
*
* <p>This method set the unbound parameters of the given problem starting from their current
* values through several iterations. At each step, the unbound parameters are changed in order to
* minimize a weighted least square criterion based on the measurements of the problem.
*
* <p>The iterations are stopped either when the criterion goes below a physical threshold under
* which improvement are considered useless or when the algorithm is unable to improve it (even if
* it is still high). The first condition that is met stops the iterations. If the convergence it
* not reached before the maximum number of iterations, an {@link EstimationException} is thrown.
*
* @param problem estimation problem to solve
* @exception EstimationException if the problem cannot be solved
* @see EstimationProblem
*/
@Override
public void estimate(EstimationProblem problem) throws EstimationException {
initializeEstimate(problem);
// work matrices
double[] grad = new double[parameters.length];
ArrayRealVector bDecrement = new ArrayRealVector(parameters.length);
double[] bDecrementData = bDecrement.getDataRef();
RealMatrix wGradGradT = MatrixUtils.createRealMatrix(parameters.length, parameters.length);
// iterate until convergence is reached
double previous = Double.POSITIVE_INFINITY;
do {
// build the linear problem
incrementJacobianEvaluationsCounter();
RealVector b = new ArrayRealVector(parameters.length);
RealMatrix a = MatrixUtils.createRealMatrix(parameters.length, parameters.length);
for (int i = 0; i < measurements.length; ++i) {
if (!measurements[i].isIgnored()) {
double weight = measurements[i].getWeight();
double residual = measurements[i].getResidual();
// compute the normal equation
for (int j = 0; j < parameters.length; ++j) {
grad[j] = measurements[i].getPartial(parameters[j]);
bDecrementData[j] = weight * residual * grad[j];
}
// build the contribution matrix for measurement i
for (int k = 0; k < parameters.length; ++k) {
double gk = grad[k];
for (int l = 0; l < parameters.length; ++l) {
wGradGradT.setEntry(k, l, weight * gk * grad[l]);
}
}
// update the matrices
a = a.add(wGradGradT);
b = b.add(bDecrement);
}
}
try {
// solve the linearized least squares problem
RealVector dX = new LUDecompositionImpl(a).getSolver().solve(b);
// update the estimated parameters
for (int i = 0; i < parameters.length; ++i) {
parameters[i].setEstimate(parameters[i].getEstimate() + dX.getEntry(i));
}
} catch (InvalidMatrixException e) {
throw new EstimationException("unable to solve: singular problem");
}
previous = cost;
updateResidualsAndCost();
} while ((getCostEvaluations() < 2)
|| (Math.abs(previous - cost) > (cost * steadyStateThreshold)
&& (Math.abs(cost) > convergence)));
}
