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A Julia package to contain non-standard matrix factorizations

License: Other

Julia 100.00%

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ralphas adeeps1 jishnub ranocha tsgut

matrixfactorizations.jl's Issues

Cholesky and Inverse Cholesky in one pass

Hello,

I wrote a function for computing the Cholesky factor and its inverse in one pass. For small matrices this appears considerably faster than computing the Cholesky factor and inverting it with LinearAlgebra. Would that be interesting for this package?

For the moment being i am hosting it in the PosDefManifold.jl package
as the choInv function

Here is a quick benchmark:

using PosDefManifold, BenchmarkTools
P=randP(10)

using LinearAlgebra

function t(P)
       C=cholesky(P)
       return C.L, inv(C.L)
end

julia> @benchmark(t(P))
BenchmarkTools.Trial:
  memory estimate:  3.69 KiB
  allocs estimate:  12
  --------------
  minimum time:     40.800 μs (0.00% GC)
  median time:      47.201 μs (0.00% GC)
  mean time:        48.117 μs (0.00% GC)
  maximum time:     291.300 μs (0.00% GC)
  --------------
  samples:          10000
  evals/sample:     1

using function choInv

julia> @benchmark(choInv(P))
BenchmarkTools.Trial:
  memory estimate:  6.09 KiB
  allocs estimate:  23
  --------------
  minimum time:     1.530 μs (0.00% GC)
  median time:      1.690 μs (0.00% GC)
  mean time:        2.883 μs (14.91% GC)
  maximum time:     563.430 μs (98.69% GC)
  --------------
  samples:          10000
  evals/sample:     10

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`checknonsingular(::Int64, ::Val{true})` removed in Julia 1.7

Causes test error at https://github.com/JuliaMatrices/MatrixFactorizations.jl/blob/22208192872a12a556e2d1fc5c52725642a15cb9/src/ul.jl#L181

Package without license

Which license does this package have?

v2.1.1 results an invalidation that accesses undefined refs

With Julia +1.9.

Note that, the issue doesn't appear with v2.1.0.

Repro:

] add FastAlmostBandedMatrix, MatrixFactorizations@2.1.1

Or,

] add NonlinearSolve, MatrixFactorizations@2.1.1
        Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. To see why use `status --outdated -m`
[ Info: Precompiling NonlinearSolve [8913a72c-1f9b-4ce2-8d82-65094dcecaec]
WARNING: Method definition *(MatrixFactorizations.LayoutQ{T} where T, MatrixFactorizations.LayoutQ{T} where T) in module MatrixFactorizations at C:\Users\user\.julia\packages\MatrixFactorizations\wSXzP\src\MatrixFactorizations.jl:124 overwritten at C:\Users\user\.julia\packages\MatrixFactorizations\wSXzP\src\MatrixFactorizations.jl:70.
  ** incremental compilation may be fatally broken for this module **

WARNING: Method definition *(MatrixFactorizations.LayoutQ{T} where T, MatrixFactorizations.LayoutQ{T} where T) in module MatrixFactorizations at C:\Users\user\.julia\packages\MatrixFactorizations\wSXzP\src\MatrixFactorizations.jl:124 overwritten at C:\Users\user\.julia\packages\MatrixFactorizations\wSXzP\src\MatrixFactorizations.jl:70.
  ** incremental compilation may be fatally broken for this module **

ERROR: LoadError: UndefRefError: access to undefined reference
Stacktrace:
 [1] getindex
   @ .\essentials.jl:13 [inlined]
 [2] invalidation_leaves(invlist::Vector{Any})
   @ PrecompileTools C:\Users\user\.julia\packages\PrecompileTools\L8A3n\src\invalidations.jl:42
 [3] recompile_invalidations(__module__::Module, expr::Any)
   @ PrecompileTools C:\Users\user\.julia\packages\PrecompileTools\L8A3n\src\invalidations.jl:23
 [4] top-level scope
   @ C:\Users\user\.julia\packages\NonlinearSolve\KlGj2\src\NonlinearSolve.jl:10
 [5] include
   @ .\Base.jl:457 [inlined]
 [6] include_package_for_output(pkg::Base.PkgId, input::String, depot_path::Vector{String}, dl_load_path::Vector{String}, load_path::Vector{String}, concrete_deps::Vector{Pair{Base.PkgId, UInt128}}, source::Nothing)
   @ Base .\loading.jl:2049
 [7] top-level scope
   @ stdin:3
in expression starting at C:\Users\user\.julia\packages\NonlinearSolve\KlGj2\src\NonlinearSolve.jl:1
in expression starting at stdin:3
ERROR: Failed to precompile NonlinearSolve [8913a72c-1f9b-4ce2-8d82-65094dcecaec] to "C:\\Users\\user\\.julia\\compiled\\v1.9\\NonlinearSolve\\jl_83D6.tmp".
Stacktrace:
 [1] error(s::String)
   @ Base .\error.jl:35
 [2] compilecache(pkg::Base.PkgId, path::String, internal_stderr::IO, internal_stdout::IO, keep_loaded_modules::Bool)
   @ Base .\loading.jl:2294
 [3] compilecache
   @ .\loading.jl:2167 [inlined]
 [4] _require(pkg::Base.PkgId, env::String)
   @ Base .\loading.jl:1805
 [5] _require_prelocked(uuidkey::Base.PkgId, env::String)
   @ Base .\loading.jl:1660
 [6] macro expansion
   @ .\loading.jl:1648 [inlined]
 [7] macro expansion
   @ .\lock.jl:267 [inlined]
 [8] require(into::Module, mod::Symbol)
   @ Base .\loading.jl:1611

Add blocked QR factorization

https://www.netlib.org/lapack/explore-html/dd/d9a/group__double_g_ecomputational_gaddcf152e87deec6123a1899f6f51101e.html#gaddcf152e87deec6123a1899f6f51101e

`Val{false}`/`Val{true}` -> `NoPivot`, `ColumnMaximum`

See Here's the relevant commit: JuliaLang/julia@e0ecc55#diff-8d1e6cd3179ba632a02c2d34dbd7a98dad914325c262d7d7e2ddb84a3a6496af

Unpacking of Q, from ql decomp fails for tall matrix.

MatrixFactorizations = v"0.9.6"
LinearAlgebra = v"0.0.0" ?!? #sorry but I don't why this is reporting 0.0.0
Julia = v"1.6.7"

using MatrixFactorizations,LinearAlgebra,Test
A=randn(8,4)
Q, L = ql(A)
@test norm(Q*L-A)<1e-14 #Fine with typeof(Q) == QLPackedQ
QM=Matrix(Q)
@test norm(QM*L-A)<1e-14 #Fails after unpacking.

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