[
https://issues.apache.org/jira/browse/MATH-230?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12655868#action_12655868
]
Sujit Pal commented on MATH-230:
--------------------------------
Apologies for not getting back earlier on this, I had a chance to look at the
diff this morning. I will work on making the SparseMatrix tests pass this
evening and post the patch tomorrow morning.
However, looking at the patch, I notice that this method is used to find the
key to the internal map for storing the entry:
+ private int computeKey(int row, int column) {
+ return row * columnDimension + column;
+ }
This effectively flattens out the matrix so a matrix like this:
1 2 3 4
5 6 7 8
9 10 11 12
is flattened out to:
1 2 3 4 5 6 7 8 9 10 11 12
Now if you wanted to look for entry (1,2) you look for entry (1*4 + 2) = 6. So
we will always get a unique key for a given matrix position, given that by
specifying the row and column dimension we are always specifying a fixed size
rectangular matrix.
This is quite beautiful and clever (note to Ismael: Thanks for doing this, and
I wish I had thought of this :-)).
But the question is: do we still need an open-addressed map structure? It seems
to me that we can now just represent the sparse matrix internally with a
Map<Integer,Double>? That way we don't even have to think about whether we want
to put it as an inner class or in utils.
Thoughts?
> Implement Sparse Matrix Support
> -------------------------------
>
> Key: MATH-230
> URL: https://issues.apache.org/jira/browse/MATH-230
> Project: Commons Math
> Issue Type: Improvement
> Affects Versions: 2.0
> Environment: N/A
> Reporter: Sujit Pal
> Assignee: Luc Maisonobe
> Priority: Minor
> Fix For: 2.0
>
> Attachments: math-230.diff, patch.txt,
> RealMatrixImplPerformanceTest.java, SparseRealMatrixImpl.java,
> SparseRealMatrixImplTest.java
>
>
> 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.
> 1) RealMatrix.java:
> - added a new method setEntry(int, int, double) to set data into a matrix
> 2) RealMatrixImpl.java:
> - 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
> MatrixUtils.createSparseRealMatrix().
> but using SparseRealMatrixImpl.
> 8) Verified that all JUnit tests pass.
--
This message is automatically generated by JIRA.
-
You can reply to this email to add a comment to the issue online.
