is stored column major in a single array, as follows:
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for (int i = 0; i < x.length; i++) { for (int j = 0; j < x.length; j++) { dist[i][j] = dist(i,j); } } return new DenseMatrix(dist); }
70717273747576777879
if (fListener != null) fListener.update(mds); return mds.points(); } public MultidimensionalScaling similarities(double[][] matrix) { DenseMatrix d = SymmetricMatrix.fromSquare(matrix); d.apply(Function.COSINE_TO_DISSIMILARITY); fdistances = d; return this; }
29303132333435
for (int j = 0; j < path.length; j++) { path[i][j] = Math.min(path[i][j], path_i_k + path[k][j]); } } } return new DenseMatrix(path); }
8586878889909192939495
this.comm = A.getCommunicator(); rank = comm.rank(); size = comm.size(); A0 = new DenseMatrix(size, size); b0 = new DenseVector(size); lu = new DenseLU(size, size); Ai = new double[size]; if (rank == root) {
113114115116117118119120121122123
207208209210211212213214215216217218219
private void solveCoarseSystem(boolean transpose) { for (int i = 0; i < size; ++i) b0.set(i, zi0[i][0]); if (transpose) lu.transSolve(new DenseMatrix(b0, false)); else lu.solve(new DenseMatrix(b0, false)); double[] data = b0.getData(); for (int i = 0; i < size; ++i) zi0[i][0] = data[i]; }
333334335336337338339340341342
@Override protected Matrix createMatrix(Communicator comm) { int n = x.size(); Matrix Al = new DenseMatrix(localLength[rank], localLength[rank]); Matrix Bl = new DenseMatrix(localLength[rank], n); return new DistRowMatrix(n, n, comm, Al, Bl); }
361362363364365366367368369370
@Override protected Matrix createMatrix(Communicator comm) { int n = x.size(); Matrix Al = new DenseMatrix(localLength[rank], localLength[rank]); Matrix Bl = new DenseMatrix(n, localLength[rank]); return new DistColMatrix(n, n, comm, Al, Bl); }
3334353637383940
@Override protected void createPrimary() throws Exception { int n = Utilities.getInt(1, max); int m = Utilities.getInt(1, max); A = new DenseMatrix(n, m); Ad = Utilities.populate(A); }
4647484950515253545556
} @Override protected void setUp() throws Exception { int n = Utilities.getInt(1, max); A = new DenseMatrix(n, n); Utilities.populate(A); Utilities.addDiagonal(A, 1); while (Utilities.singular(A)) Utilities.addDiagonal(A, 1);