Deprecate A_ldiv_B!(SparseMatrixCSC, StrideVecOrMat) thereby fixing #10787

Author: andreasnoack

NEWS.md

@@ -45,6 +45,9 @@ Library improvements
 Deprecated or removed
 ---------------------
 
+  * The method `A_ldiv_B!(SparseMatrixCSC, StrideVecOrMat)` has been deprecated in favor
+    of versions that require the matrix to in factored form ([#13496]).
+
 Julia v0.4.0 Release Notes
 ==========================
 

base/deprecated.jl

@@ -843,6 +843,7 @@ for f in (:remotecall, :remotecall_fetch, :remotecall_wait)
     end
 end
 
+#13465
 @deprecate cov(x::AbstractVector; corrected=true, mean=Base.mean(x)) covm(x, mean, corrected)
 @deprecate cov(X::AbstractMatrix; vardim=1, corrected=true, mean=Base.mean(X, vardim)) covm(X, mean, vardim, corrected)
 @deprecate cov(x::AbstractVector, y::AbstractVector; corrected=true, mean=(Base.mean(x), Base.mean(y))) covm(x, mean[1], y, mean[2], corrected)
@@ -854,3 +855,6 @@ end
 @deprecate cor(X::AbstractVecOrMat, Y::AbstractVecOrMat; vardim=1, mean=(Base.mean(X, vardim), Base.mean(Y, vardim))) corm(X, mean[1], Y, mean[2], vardim)
 
 @deprecate_binding SparseMatrix SparseArrays
+
+#13496
+@deprecate A_ldiv_B!(A::SparseMatrixCSC, B::StridedVecOrMat) A_ldiv_B!(factorize(A), B)

base/sparse/linalg.jl

@@ -165,20 +165,6 @@ function spmatmul{Tv,Ti}(A::SparseMatrixCSC{Tv,Ti}, B::SparseMatrixCSC{Tv,Ti};
 end
 
 ## solvers
-function A_ldiv_B!(A::SparseMatrixCSC, b::AbstractVecOrMat)
-    if eltype(b)<:Complex; A = complex(A); end
-
-    if istril(A)
-        # TODO: Fix diagonal case. Diagonal(A.nzval) needs to handle
-        # the case where there are zeros on the diagonal and error out.
-        # It also does not work in the complex case. VBS.
-        #if istriu(A); return A_ldiv_B!(Diagonal(A.nzval), b); end
-        return fwdTriSolve!(A, b)
-    end
-    if istriu(A); return bwdTriSolve!(A, b); end
-    return A_ldiv_B!(lufact(A),b)
-end
-
 function fwdTriSolve!(A::SparseMatrixCSC, B::AbstractVecOrMat)
 # forward substitution for CSC matrices
     n = length(B)

test/sparsedir/sparse.jl

@@ -126,7 +126,6 @@ for i = 1:5
     @test (maximum(abs(a\b - full(a)\b)) < 1000*eps())
     @test (maximum(abs(a'\b - full(a')\b)) < 1000*eps())
     @test (maximum(abs(a.'\b - full(a.')\b)) < 1000*eps())
-    @test (maximum(abs(A_ldiv_B!(a,copy(b)) - full(a)\b)) < 1000*eps())
 
     a = speye(5) + tril(0.1*sprandn(5, 5, 0.2) + 0.1*im*sprandn(5, 5, 0.2))
     b = randn(5,3)
@@ -145,7 +144,6 @@ for i = 1:5
     @test (maximum(abs(a\b - full(a)\b)) < 1000*eps())
     @test (maximum(abs(a'\b - full(a')\b)) < 1000*eps())
     @test (maximum(abs(a.'\b - full(a.')\b)) < 1000*eps())
-    @test (maximum(abs(A_ldiv_B!(a,copy(b)) - full(a)\b)) < 1000*eps())
 
     a = speye(5) + triu(0.1*sprandn(5, 5, 0.2) + 0.1*im*sprandn(5, 5, 0.2))
     b = randn(5,3)
@@ -164,7 +162,6 @@ for i = 1:5
     @test (maximum(abs(a\b - full(a)\b)) < 1000*eps())
     @test (maximum(abs(a'\b - full(a')\b)) < 1000*eps())
     @test (maximum(abs(a.'\b - full(a.')\b)) < 1000*eps())
-    @test (maximum(abs(A_ldiv_B!(a,copy(b)) - full(a)\b)) < 1000*eps())
 
     a = spdiagm(randn(5)) + im*spdiagm(randn(5))
     b = randn(5,3)