/*
* Matrix mult but with min-plus, and iterative. Each min-plus operation
* that changes the path inserts it into a new queue
*/
public SparseMatrix apsp() {
SparseMatrix shortestPaths = new SparseMatrix(this);
SparseMatrix currentPairs = new SparseMatrix(this.rowDim, this.colDim);
SparseMatrix newPairs = new SparseMatrix(this.rowDim, this.colDim);
newPairs = new SparseMatrix(this);
for (int d = 0; d < this.rowDim; d++) {
shortestPaths.set(d, d, 0.0);
}
for (int d = 0; d < this.rowDim; d++) {
newPairs.set(d, d, 0.0);
}
while (!newPairs.isEmpty()) {
currentPairs = new SparseMatrix(newPairs);
newPairs = new SparseMatrix(this.rowDim, this.colDim);
for (int r : currentPairs.rows) {
Counter row = currentPairs.getRow(r);
for (int c : row.keySet()) {
Counter oRow = this.getRow(c);
for (int oc : oRow.keySet()) {
double pathLength = currentPairs.get(r, c) + oRow.get(oc);
if (pathLength < shortestPaths.getPath(r, oc)) {
newPairs.set(r, oc, pathLength);
shortestPaths.set(r, oc, pathLength);
}
}
}
}
}
return shortestPaths;
}
public static Counter ConstrainedEig(SparseMatrix mat, SparseMatrix orthogMat) {
double trimEps = 0;
int iterLimit = 10000;
long start;
long end;
Counter vector = new Counter();
int vecLen = mat.colDim;
for (int i = 0; i < vecLen; i++) {
// vector.add(i, 1.0/Math.sqrt(vecLen));
vector.add(i, Math.random() - 0.5);
}
Counter oldVector = new Counter();
// vector = mat.multiply(vector);
// for(int r: orthogMat.rows){
// Counter orthogRow = orthogMat.getRow(r);
// vector.orthogonalize(orthogRow);
//// System.out.println(vector.dot(orthogRow));
// }
double norm = 0;
double sim = 0;
double diff = 1.0;
double diffNeg = 1.0;
int t = 0;
start = System.currentTimeMillis();
while (diff > Math.pow(10.0, -16.0) && diffNeg > Math.pow(10.0, -16.0) && t < iterLimit) {
t += 1;
// vector.trimKeys(trimEps);
oldVector = new Counter(vector);
vector = mat.multiply(vector);
for (int r : orthogMat.rows) {
Counter orthogRow = orthogMat.getRow(r);
// System.out.println("before: "+vector.dot(orthogRow));
vector.orthogonalize(orthogRow);
// System.out.println("after: "+vector.dot(orthogRow));
}
norm = 0;
norm = vector.norm();
vector.multiply(1.0 / norm);
diff = 0;
diffNeg = 0;
Set<Integer> vecOldUnion = vector.concreteKeySet();
vecOldUnion.addAll(oldVector.concreteKeySet());
for (int i : vecOldUnion) {
// for(int i = 0; i < mat.colDim; i++){
diff += (oldVector.get(i) - vector.get(i)) * (oldVector.get(i) - vector.get(i));
diffNeg += (oldVector.get(i) + vector.get(i)) * (oldVector.get(i) + vector.get(i));
}
sim = vector.dot(oldVector);
// System.out.println(diff+" "+diffNeg+" "+sim+" "+norm+"
// "+vector.dot(orthogMat.getRow(0)));
// System.out.println(vector.toString());
// System.out.println(oldVector.toString());
}
System.out.println(norm + " " + orthogMat.rows.size() + " " + sim);
// System.out.println(mat.toStringValues());
end = System.currentTimeMillis();
System.out.println("Time: " + (end - start) + " iterations: " + t);
return vector;
}
public void removeEntries(SparseMatrix redundant) {
for (int r : redundant.getRows()) {
Counter row = redundant.getRow(r);
for (int c : row.keySet()) {
this.remove(r, c);
}
}
}
public SparseMatrix add(SparseMatrix other) {
SparseMatrix sum = new SparseMatrix(this.rowDim, this.colDim);
sum = new SparseMatrix(this);
for (int r : other.rows) {
sum.addRow(r, other.getRow(r));
}
return sum;
}
public SparseMatrix multiply(SparseMatrix other) {
SparseMatrix mult = new SparseMatrix(this.rowDim, other.colDim);
for (int r : rows) {
// System.out.println("multiplying row: "+ r);
Counter row = this.getRow(r);
// for(int c: other.cols){
// Counter col = other.getCol(c);
// double dotProd = row.dot(col);
// System.out.println(row.toString()+" "+col.toString()+" "+dotProd);
// mult.set(r, c, dotProd);
// }
for (int c : row.keySet()) {
Counter oRow = other.getRow(c);
for (int oc : oRow.keySet()) {
mult.add(r, oc, row.get(c) * oRow.get(oc));
}
}
}
return mult;
}
