/**
* Constructor for FlexCompRowMatrix
*
* @param A Matrix to copy contents from
* @param deep True for a deep copy, false for a reference copy. A reference copy can only be made
* of an <code>FlexCompRowMatrix</code>
*/
public FlexCompRowMatrix(Matrix A, boolean deep) {
super(A);
rowD = new SparseVector[numRows];
if (deep) {
for (int i = 0; i < numRows; ++i) rowD[i] = new SparseVector(numColumns);
set(A);
} else {
FlexCompRowMatrix Ar = (FlexCompRowMatrix) A;
for (int i = 0; i < numRows; ++i) rowD[i] = Ar.getRow(i);
}
}
/**
* Important method used in compute CCA
*
* @param X
* @return
*/
public static FlexCompRowMatrix computeSparseInverseSqRoot(FlexCompRowMatrix X) {
FlexCompRowMatrix diagInvEntries = new FlexCompRowMatrix(X.numRows(), X.numColumns());
System.out.println("++Beginning Sparse Inverse Sq. Root++");
for (MatrixEntry e : X) {
if (e.row() == e.column() && e.get() != 0) {
diagInvEntries.set(e.row(), e.column(), 1 / Math.sqrt(e.get()));
}
if (e.row() == e.column() && e.get() == 0) {
diagInvEntries.set(e.row(), e.column(), 10000); // Some large
// value
}
}
System.out.println("++Finished Sparse Inverse Sq. Root++");
return diagInvEntries;
}
public static FlexCompRowMatrix transform(FlexCompRowMatrix a) {
Iterator<MatrixEntry> aIt = a.iterator(); // iterating over the elements
// in the matrix
double ent = 0;
while (aIt.hasNext()) {
MatrixEntry ment = aIt.next();
ent = ment.get();
if (true) ent = Math.log(ent); // log transform, a good thing to do I
// guess
if (true) ent = Math.sqrt(ent); // this is also a valid thing to do
a.set(ment.row(), ment.column(), ent); // Performing tranforms on
// the matrix
}
return a;
}
public void reset(int r, int c) {
for (FlexCompRowMatrix cell : this.matrix) {
cell.set(r, c, 0);
}
}
