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Hello,

I added the support of the following operations:

  • A + B
  • kron(A, B)

where both A and B are SparseMatrixCOO

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codecov bot commented Jun 11, 2024

Codecov Report

Attention: Patch coverage is 97.56098% with 1 line in your changes missing coverage. Please review.

Project coverage is 86.41%. Comparing base (acbecad) to head (949de13).
Report is 2 commits behind head on main.

Current head 949de13 differs from pull request most recent head 7d346ca

Please upload reports for the commit 7d346ca to get more accurate results.

Files Patch % Lines
src/coo_linalg.jl 97.56% 1 Missing ⚠️
Additional details and impacted files
@@            Coverage Diff             @@
##             main      #45      +/-   ##
==========================================
+ Coverage   85.39%   86.41%   +1.02%     
==========================================
  Files           4        4              
  Lines         363      405      +42     
==========================================
+ Hits          310      350      +40     
- Misses         53       55       +2     

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Thanks @albertomercurio for the PR! That's a great add.
I made some comments regarding the implementation.

@geoffroyleconte or @dpo would you have some time to check this PR too?

for j in eachindex(rowval_colvalA)
if rowval_colvalA[j] == rowval_colval[i]
nzval[i] += A.vals[j]
break
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If I am not wrong you assume here that each matrix has unique pair of (row, col) while I don't think it is necessary true.

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But they should be unique, right? I mean, we should merge them in the moment of creating the sparse matrix, no?

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Really sorry @albertomercurio , I completely lost track of this PR. There is a discussion on this https://github.com/orgs/JuliaSmoothOptimizers/discussions/51 , and the status is that QuadraticModels is not merging them by default.

rowval_colvalA = collect(zip(A.rows, A.cols))
rowval_colvalB = collect(zip(B.rows, B.cols))

rowval_colval = union(rowval_colvalA, rowval_colvalB)
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I think there should be a more efficient to do this. The union will iterate over both vectors, and to compute the sum you do it again. Would it be more efficient to do both at the same time?

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At the moment I don’t have anything in mind. Do you have an idea?

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Okay, let's create an issue on the package after this PR is merge to point out to this as a possible improvement.

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How does SparseMatrixCSC do it?

for j in eachindex(rowval_colvalB)
if rowval_colvalB[j] == rowval_colval[i]
nzval[i] += B.vals[j]
break
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see comment above

Bnnz = nnz(B)

if Annz == 0 || Bnnz == 0
return SparseMatrixCOO(Int[], Int[], T[], out_shape...)
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This should be tested in the unit tests too

albertomercurio and others added 2 commits June 12, 2024 16:26
Co-authored-by: Tangi Migot <tangi.migot@gmail.com>
Co-authored-by: Tangi Migot <tangi.migot@gmail.com>
@CarloLucibello
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What is missing here? It is a pity to not see this in

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tmigot commented Jun 17, 2025

Hi @CarloLucibello ! As you can see here there are comments that need to be adressed in this PR.
If you would like to pick up on @albertomercurio works, I think it's fine. We are a bit overloaded but would be very happy to help clarify the comments and review another PR.

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4 participants