Merge remote-tracking branch 'origin/master' into profile

src/linalg/rankUpdate.jl

@@ -60,9 +60,11 @@ function rankUpdate!(α::T, A::SparseMatrixCSC{T}, C::Diagonal{T}) where T <: Nu
     rv = rowvals(A)
     for j in 1:n
         nzr = nzrange(A, j)
-        length(nzr) == 1 || throw(ArgumentError("A*A' has off-diagonal elements"))
-        k = nzr[1]
-        @inbounds dd[rv[k]] += α * abs2(nz[k])
+        if !isempty(nzr)
+            length(nzr) == 1 || throw(ArgumentError("A*A' has off-diagonal elements"))
+            k = nzr[1]
+            @inbounds dd[rv[k]] += α * abs2(nz[k])
+        end
     end
     C
 end

src/modelterms.jl

@@ -470,6 +470,24 @@ function Base.Ac_mul_B(A::ScalarFactorReTerm{T,V,R},
     end
 end
 
+function Base.Ac_mul_B(A::VectorFactorReTerm, B::ScalarFactorReTerm)
+    nzeros = copy(A.wtz)
+    k, n = size(nzeros)
+    rowind = Matrix{Int32}(k, n)
+    refs = A.f.refs
+    bwtz = B.wtz
+    for j in 1:n
+        bwtzj = bwtz[j]
+        offset = k * (refs[j] - 1)
+        for i in 1:k
+            rowind[i, j] = i + offset
+            nzeros[i, j] *= bwtzj
+        end
+    end
+    sparse(vec(rowind), Vector{Int32}(repeat(B.f.refs, inner=k)), vec(nzeros),
+           k * nlevs(A), nlevs(B))
+end
+
 function Base.Ac_mul_B(A::VectorFactorReTerm{T}, B::VectorFactorReTerm{T}) where T
     if A === B
         l = vsize(A)

src/pls.jl

@@ -5,10 +5,12 @@ Convert sparse `S` to `Diagonal` if `S` is diagonal or to `full(S)` if
 the proportion of nonzeros exceeds `threshold`.
 """
 function densify(S::SparseMatrixCSC, threshold::Real = 0.3)
+    dropzeros!(S)
     m, n = size(S)
     if m == n && isdiag(S)  # convert diagonal sparse to Diagonal
         Diagonal(diag(S))
-    elseif nnz(S)/(*(size(S)...)) ≤ threshold # very sparse matrices left as is
+    elseif nnz(S)/(*(size(S)...)) ≤ threshold ||   # very sparse matrices left as is
+        all(d -> iszero(d) || d == 1, diff(S.colptr))
         S
     else
         full(S)

test/FactorReTerm.jl

@@ -116,6 +116,10 @@ end
     @test isa(vrp, UniformBlockDiagonal{Float64})
     @test size(vrp) == (36, 36)
 
+    scl = ScalarFactorReTerm(slp[:G], Array(slp[:U]), Array(slp[:U]), :G, ["U"], 1.0)
+
+    @test sparse(corr)'sparse(scl) == corr'scl
+
     @test MixedModels.Λ_mul_B!(Vector{Float64}(36), corr, ones(36)) == repeat([0.5, 1.0], outer=18)
 
     @testset "reweight!" begin