Affects Version/s: 2.0
Fix Version/s: 2.0
I needed a way to deal with large sparse matrices using commons-math RealMatrix, so I implemented it. The SparseRealMatrixImpl is a subclass of RealMatrixImpl, and the backing data structure is a Map<Point,Double>, where Point is a struct like inner-class which exposes two int parameters row and column. I had to make some changes to the existing components to keep the code for SparseRealMatrixImpl clean. Here are the details.
- added a new method setEntry(int, int, double) to set data into a matrix
- changed all internal calls to data[i][j] to getEntry(i,j).
- for some methods such as add(), subtract(), premultiply(), etc, there
was code that checked for ClassCastException and had two versions,
one for a generic RealMatrix and one for a RealMatrixImpl. This has
been changed to have only one that operates on a RealMatrix. The
result is something like auto-type casting. So if:
RealMatrixImpl.add(RealMatrix) returns a RealMatrixImpl
SparseRealMatrixImpl.add(RealMatrix) returns a SparseRealMatrixImpl
3) SparseRealMatrixImpl added as a subclass of RealMatrixImpl.
4) LUDecompositionImpl changed to use a clone of the passed in RealMatrix
instead of its data block, and now it uses clone.getEntry(row,col)
calls instead of data[row][col] calls.
5) LUDecompositionImpl returned RealMatrixImpl for getL(), getU(), getP()
and solve(). It now returns the same RealMatrix impl that is passed
in through its constructor for these methods.
6) New test for SparseRealMatrixImpl, mimics the tests in RealMatrixImplTest,
7) New static method to create SparseRealMatrixImpl out of a double in
but using SparseRealMatrixImpl.
8) Verified that all JUnit tests pass.