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Question about your convexLS solver #16
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Hi @pramanc, A good reference that I would recommend is the book "Numerical Methods for Least Squares Problems" by Ake Bjorck.
I wrote a little bit (not very completed) about my implementation here: https://uh-ir.tdl.org/handle/10657/1824 |
Re: A is zero matrix problem A in solveP function should not be zero. It is positive definite due to the construction, it is actually A^T*A (A transposed * A). |
@binhhuyle Thank you for your reply! zero matrix problem actually happens in solveP function: the matrix (q2[np-2].transpose()*indexing_row_col(aTa, idx.head(np), idx.head(np))*q2[np-2]) sometimes will be zero matrix ======================================================= Thank you again! Really amazing work! |
Hello, hope both of you are doing well. After solving p it contains nan values and zeros. Which results in iMin being -1. Just debugged the values after the solve and I am doing something terribly wrong. |
@robertjoosten Hi, Can you supply the data(aTa, aTb, x, idx, np, affine, p) passed in solveP? |
Hello @pramanc I've narrowed it down a bit further. I think it goes wrong because of nan values introduced in m during the computeTransformations step. m looks fine when it comes in ( identity matrix ) Here are some debug values for values in the SparseMatrix::InnerIterator in compute_vuT it row I really doubt this is related to the original issue anymore, happy to take the discussion away from this thread |
well, definitely your sparse matrix w is wrong to make it value(6.15434e+255),you can check the fbxreader part to see if you get right weight matrix w |
Hi, It's me again!
I met a problem when calculate the gradient ( solveP function) .
when calculate z by solve the linear system A * z = b
some times A is zero matrix-> cause the calculated z is nan.
I am reading the code of convexLS solver, but can't find any reference.
Would you please tell me some reference of the convexLS solver?
Thanks!
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