@@ -1818,15 +1818,13 @@ for isunittri in (true, false), islowertri in (true, false)
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# build out-of-place left-division operations
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# broad method where elements are Numbers
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@eval function \ (A:: $tritype{<:TA,<:AbstractMatrix} , b:: SparseVector{Tb} ) where {TA<: Number ,Tb<: Number }
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- # A = $(applyxform ? :(xformA.data) : :(xformA) )
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TAb = $ (isunittri ?
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:(typeof (zero (TA)* zero (Tb) + zero (TA)* zero (Tb))) :
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:(typeof ((zero (TA)* zero (Tb) + zero (TA)* zero (Tb))/ one (TA))) )
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LinearAlgebra. ldiv! (convert (AbstractArray{TAb}, A), convert (Array{TAb}, b))
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end
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# fallback where elements are not Numbers
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@eval function \ (A:: $tritype , b:: SparseVector )
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- # A = $(applyxform ? :(xformA.parent) : :(xformA) )
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LinearAlgebra. ldiv! (A, copy (b))
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end
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@@ -1865,7 +1863,7 @@ for isunittri in (true, false), islowertri in (true, false)
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# the generic in-place left-division methods handle these cases, but
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# we can achieve greater efficiency where the triangular matrix provides
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- # good view support. hence the StridedMatrix restriction.
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+ # good view support, hence the StridedMatrix restriction.
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@eval function ldiv! (xA:: $xformtritype , b:: SparseVector )
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A = $ ( applyxform ? :(parent (parent (xA))) : :(parent (xA)) )
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# If b has no nonzero entries, the result is necessarily zero and this call
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