private void init(WeightFunction weightFunction, BasesFunction baseFunction) {
this.weightFunction = weightFunction;
this.basesFunction = baseFunction;
final int baseDim = baseFunction.getDim();
A = new DenseMatrix64F(baseDim, baseDim);
A_x = new DenseMatrix64F(baseDim, baseDim);
A_y = new DenseMatrix64F(baseDim, baseDim);
As = new DenseMatrix64F[] {A, A_x, A_y};
B = new ArrayList<>(baseDim);
B_x = new ArrayList<>(baseDim);
B_y = new ArrayList<>(baseDim);
Bs = Arrays.asList(B, B_x, B_y);
for (ArrayList<TDoubleArrayList> tB : Bs) {
for (int i = 0; i < baseDim; i++) {
tB.add(new TDoubleArrayList(ShapeFunctionUtils2D.MAX_NODES_SIZE_GUESS));
}
}
gamma = new DenseMatrix64F(baseDim, 1);
gamma_x = new DenseMatrix64F(baseDim, 1);
gamma_y = new DenseMatrix64F(baseDim, 1);
ps_arr = new double[3][baseDim];
p = DenseMatrix64F.wrap(ps_arr[0].length, 1, ps_arr[0]);
p_x = DenseMatrix64F.wrap(ps_arr[1].length, 1, ps_arr[1]);
p_y = DenseMatrix64F.wrap(ps_arr[2].length, 1, ps_arr[2]);
tv = new DenseMatrix64F(baseDim, 1);
luSolver = new LinearSolverLu(new LUDecompositionAlt());
A_bak = new DenseMatrix64F(baseDim, baseDim);
}
@Override
public TDoubleArrayList[] values(
Coordinate pos,
List<? extends Coordinate> nodes,
TDoubleArrayList[] distSquares,
TDoubleArrayList infRads,
TDoubleArrayList[] results) {
if (null == distSquares) {
distSquares = this.distSquaresCache;
euclideanDistSqFun.setPosition(pos);
euclideanDistSqFun.sqValues(nodes, distSquares);
}
int ndsNum = nodes.size();
weightFunction.values(distSquares, infRads, nodesWeightsCache);
results = ShapeFunctionUtils2D.init4Output(results, diffOrder, ndsNum);
int diffDim = CommonUtils.len2DBase(diffOrder);
int baseDim = basesFunction.getDim();
Coordinate zero = new Coordinate(0, 0, 0);
Coordinate radCoord = new Coordinate(0, 0, 0);
for (int i = 0; i < diffDim; i++) {
As[i].zero();
ArrayList<TDoubleArrayList> tB = Bs.get(i);
for (int j = 0; j < baseDim; j++) {
TDoubleArrayList v = tB.get(j);
v.resetQuick();
v.ensureCapacity(ndsNum);
v.fill(0, ndsNum, 0);
}
}
basesFunction.setDiffOrder(0);
for (int diffDimIdx = 0; diffDimIdx < diffDim; diffDimIdx++) {
TDoubleArrayList weights_d = nodesWeightsCache[diffDimIdx];
DenseMatrix64F A_d = As[diffDimIdx];
ArrayList<TDoubleArrayList> B_d = Bs.get(diffDimIdx);
double[] tp = ps_arr[0];
int ndIdx = 0;
for (Coordinate nd : nodes) {
if (areBasesRelative) {
GeometryMath.minus(nd, pos, radCoord);
basesFunction.values(radCoord, ps_arr);
} else {
basesFunction.values(nd, ps_arr);
}
double weight_d = weights_d.getQuick(ndIdx);
for (int i = 0; i < baseDim; i++) {
double p_i = tp[i];
for (int j = 0; j < baseDim; j++) {
double p_ij = p_i * tp[j];
A_d.add(i, j, weight_d * p_ij);
}
B_d.get(i).set(ndIdx, weight_d * p_i);
}
ndIdx++;
}
}
basesFunction.setDiffOrder(diffOrder);
if (areBasesRelative) {
basesFunction.values(zero, ps_arr);
} else {
basesFunction.values(pos, ps_arr);
}
A_bak.set(A);
luSolver.setA(A_bak);
tv.set(p);
luSolver.solve(tv, gamma);
// CommonOps.solve(A, p, gamma);
ShapeFunctionUtils2D.multAddTo(gamma, B, results[0]);
if (diffOrder < 1) {
return results;
}
tv.zero();
CommonOps.mult(-1, A_x, gamma, tv);
CommonOps.add(p_x, tv, tv);
luSolver.solve(tv, gamma_x);
// CommonOps.solve(A, tv, gamma_x);
tv.zero();
CommonOps.mult(-1, A_y, gamma, tv);
CommonOps.add(p_y, tv, tv);
luSolver.solve(tv, gamma_y);
// CommonOps.solve(A, tv, gamma_y);
ShapeFunctionUtils2D.multAddTo(gamma_x, B, results[1]);
ShapeFunctionUtils2D.multAddTo(gamma, B_x, results[1]);
ShapeFunctionUtils2D.multAddTo(gamma_y, B, results[2]);
ShapeFunctionUtils2D.multAddTo(gamma, B_y, results[2]);
return results;
}