I'm trying to solve a least-squares problem using sparse QR, but:
julia> size(A)
(3140,1988)
julia> nnz(A)
8510
julia> size(b)
(3140,)
julia> typeof(A)
SparseMatrixCSC{Float64,Int64}
julia> A \ b
ERROR: Base.SparseMatrix.CHOLMOD.CHOLMODException("")
in convert at sparse/cholmod.jl:867
in factorize at sparse/linalg.jl:854
in \ at linalg/generic.jl:326
The matrix A is rank deficient, but I don't think that's the source of the
problem. I get the same exception if I regularize the problem.
This is with Julia 0.4.6. The relevant portion of sparse/cholmod.jl is:
856 function convert{Tv<:VTypes}(::Type{Sparse}, A::SparseMatrixCSC{Tv,
SuiteSparse_long}, stype::Integer)
857 o = allocate_sparse(A.m, A.n, length(A.nzval), true, true, stype,
Tv)
858 s = unsafe_load(o.p)
859 for i = 1:length(A.colptr)
860 unsafe_store!(s.p, A.colptr[i] - 1, i)
861 end
862 for i = 1:length(A.rowval)
863 unsafe_store!(s.i, A.rowval[i] - 1, i)
864 end
865 unsafe_copy!(s.x, pointer(A.nzval), length(A.nzval))
866
867 @isok check_sparse(o)
868
869 return o
870 end
How can I find out more about what's gone wrong?
