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For types that weren't subtypes of AbstractFloat, we used to try
to LU factorize without pivoting and only use pivoting when it failed.
This caused large numerical errors when computing the LU for element
types which promoted to float like numbers such as most integers.
The behavior was never documented and is error prone. Hence, this
PR removes the behavior.

Fixes JuliaLang/LinearAlgebra.jl#605. Alternative to #30953

For types that weren't subtypes of AbstractFloat, we used to try
to LU factorize without pivoting and only use pivoting when it failed.
This caused large numerical errors when computing the LU for element
types which promoted to float like numbers such as most integers.
The behavior was never documented and is error prone. Hence, this
PR removes the behavior.
@andreasnoack
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I think it would be good if we could try backporting this to 1.3 since many people have complained about JuliaLang/LinearAlgebra.jl#605. If PkgEval shows that it breaks too many packages (I don't expect that) then we can drop it.

fredrikekre added a commit that referenced this pull request Aug 23, 2019
fredrikekre added a commit that referenced this pull request Aug 24, 2019
KristofferC pushed a commit that referenced this pull request Aug 25, 2019
…2989)

For types that weren't subtypes of AbstractFloat, we used to try
to LU factorize without pivoting and only use pivoting when it failed.
This caused large numerical errors when computing the LU for element
types which promoted to float like numbers such as most integers.
The behavior was never documented and is error prone. Hence, this
PR removes the behavior.

(cherry picked from commit 5af3c2a)
KristofferC pushed a commit that referenced this pull request Aug 25, 2019
@KristofferC KristofferC mentioned this pull request Aug 25, 2019
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@KristofferC
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Note that this was merged even with a (correctly) red CI.

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LU instability for non-float matrices due to lack of pivoting

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