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solve #139

if p.ctprod !== nothing
increase_nctprod(p)
return p.ctprod(v)::Vector{promote_type(T,U)}
return p.ctprod(v)::typeof(v).name.wrapper{promote_type(T,U), typeof(v).parameters[2]}
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@amontoison amontoison Mar 14, 2020

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typeof(v).parameters[2] represents the dimension of the Array if it's dense (1 for Vectors) or the type of Integer that is used for storing coefficients when it's sparse.

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Coverage Status

Coverage remained the same at 96.308% when pulling e585fb6 on amontoison:master into 1827fe9 on JuliaSmoothOptimizers:master.

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codecov bot commented Mar 14, 2020

Codecov Report

Merging #140 into master will not change coverage.
The diff coverage is 100%.

Impacted file tree graph

@@          Coverage Diff           @@
##           master    #140   +/-   ##
======================================
  Coverage    96.3%   96.3%           
======================================
  Files          14      14           
  Lines         623     623           
======================================
  Hits          600     600           
  Misses         23      23
Impacted Files Coverage Δ
src/operations.jl 100% <100%> (ø) ⬆️
src/adjtrans.jl 98.71% <100%> (ø) ⬆️

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dpo commented Mar 15, 2020

Do the Krylov.jl allocation tests pass?

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dpo commented Mar 15, 2020

Is it possible to add a test to check that #139 is solved?

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amontoison commented Mar 16, 2020

Yes, allocation tests pass in Krylov.jl and I added a test to check that the ouptut of A * v can be different than a Vector. I can only add another test with StridedMatrix / StridedVector for #139 if you want more tests.

@dpo dpo merged commit 1ebf3d6 into JuliaSmoothOptimizers:master Mar 20, 2020
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dpo commented Mar 20, 2020

Thank you.

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3 participants