This is very interesting !
So UMFPACK is more robust and this is why I am not having any issues with
the same matrix.
Thanks.
On Wednesday, May 27, 2015 at 6:15:57 PM UTC-3, Andreas Noack wrote:
>
> It could happen if a pivot is zero. CHOLMOD's ldlt is only making
> permutations in the symbolic step to reduce fill in. The problem can easily
> arise if a random matrix is too sparse, e.g.
>
> julia> A = sprandn(5,5, 0.2);
>
> julia> A = A + A';
>
> julia> b = A*ones(5);
>
> julia> cholfact(A)\b
> CHOLMOD warning: not positive definite
> 5-element Array{Float64,1}:
> NaN
> NaN
> NaN
> NaN
> Inf
>
> 2015-05-27 17:11 GMT-04:00 Eduardo Lenz <[email protected]
> <javascript:>>:
>
>> OK, I see.
>>
>> It is really using the LDLt, I will try to find why it is returning the
>> NaNs for my matrix.
>>
>> Thank you very much for your time and knowledge
>>
>>
>>
>> On Wednesday, May 27, 2015 at 5:54:20 PM UTC-3, Andreas Noack wrote:
>>
>>> As I wrote in the first reply: in 0.3 the cholfact function returns the
>>> LDLt when the matrix is symmetric but not positive definite, e.g.
>>> julia> A = sprandn(5,5, 0.5);
>>>
>>> julia> A = A + A';
>>>
>>> julia> b = A*ones(5);
>>>
>>> julia> cholfact(A)
>>>
>>> CHOLMOD factor: : 5-by-5
>>> scalar types: SuiteSparse_long, real, double
>>> simplicial, LDL'.
>>> ordering method used: AMD
>>> 0:4
>>> 1:3
>>> 2:0
>>> 3:1
>>> 4:2
>>> col: 0 colcount: 3
>>> col: 1 colcount: 3
>>> col: 2 colcount: 3
>>> col: 3 colcount: 2
>>> col: 4 colcount: 1
>>> monotonic: 1
>>> nzmax 12.
>>> col 0: nz 3 start 0 end 3 space 3 free 0:
>>> 0: -0.077417
>>> 1: 8.3137
>>> 3: -0.22451
>>> col 1: nz 3 start 3 end 6 space 3 free 0:
>>> 1: 6.1217
>>> 3: -0.023604
>>> 4: 0.33154
>>> col 2: nz 3 start 6 end 9 space 3 free 0:
>>> 2: -0.82878
>>> 3: -0.16901
>>> 4: 2.1383
>>> col 3: nz 2 start 9 end 11 space 2 free 0:
>>> 3: 0.96632
>>> 4: -1.1466
>>> col 4: nz 1 start 11 end 12 space 1 free 0:
>>> 4: 1.8461
>>> nz 12 OK
>>>
>>>
>>> julia> cholfact(A)\b
>>> 5-element Array{Float64,1}:
>>> 1.0
>>> 1.0
>>> 1.0
>>> 1.0
>>> 1.0
>>>
>>> You do have CHOLMOD installed, but in 0.3 it is in a different module.
>>> Try Base.LinAlg.CHOLMOD
>>>
>>> 2015-05-27 16:44 GMT-04:00 Eduardo Lenz <[email protected]>:
>>>
>>> Sorry for pointing a wrong julia version.
>>>>
>>>> The matrix is not posdef, so it gives me a (correct) warning and than
>>>> my computations return NaN.
>>>>
>>>> I will take a deeper look, but I really cannot understand why I dont
>>>> have CHOLMOD avaliable in a regular
>>>> windows install.
>>>>
>>>> Thanks for your help Andreas !
>>>>
>>>>
>>>> On Wednesday, May 27, 2015 at 5:37:53 PM UTC-3, Andreas Noack wrote:
>>>>>
>>>>> You are using 0.3.8 and not 0.4. Have you tried cholfact(A)?
>>>>>
>>>>> 2015-05-27 16:33 GMT-04:00 Eduardo Lenz <[email protected]>:
>>>>>
>>>>> Just to make it clear...
>>>>>> _
>>>>>> julia> versioninfo()
>>>>>> Julia Version 0.3.8
>>>>>> Commit 79599ad (2015-04-30 23:40 UTC)
>>>>>> Platform Info:
>>>>>> System: Windows (x86_64-w64-mingw32)
>>>>>> CPU: Intel(R) Core(TM) i5-3320M CPU @ 2.60GHz
>>>>>> WORD_SIZE: 64
>>>>>> BLAS: libopenblas (USE64BITINT DYNAMIC_ARCH NO_AFFINITY Sandybridge)
>>>>>> LAPACK: libopenblas
>>>>>> LIBM: libopenlibm
>>>>>> LLVM: libLLVM-3.3
>>>>>>
>>>>>> julia> Base.SparseMatrix.CHOLMOD
>>>>>> ERROR: CHOLMOD not defined
>>>>>>
>>>>>>
>>>>>>
>>>>>> On Wednesday, May 27, 2015 at 3:25:46 PM UTC-3, Eduardo Lenz wrote:
>>>>>>>
>>>>>>> Funny... I dont have CHOLMOD installed...but I am using the official
>>>>>>> windows installer.. I will try to make a fresh install.
>>>>>>>
>>>>>>> Thanks Andreas !
>>>>>>>
>>>>>>> On Wednesday, May 27, 2015 at 2:59:30 PM UTC-3, Andreas Noack wrote:
>>>>>>>>
>>>>>>>> What do you get when you type Base.SparseMatrix.CHOLMOD.ITypes in
>>>>>>>> the terminal?
>>>>>>>>
>>>>>>>> 2015-05-27 13:56 GMT-04:00 Eduardo Lenz <[email protected]>:
>>>>>>>>
>>>>>>>>> Thanks Andreas.
>>>>>>>>>
>>>>>>>>> Indeed ... but I am using 0.4 with ldltfact and it is complaining
>>>>>>>>> about the type of the matrix, which is OK.
>>>>>>>>>
>>>>>>>>> I am realy confused with this error.
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> On Wednesday, May 27, 2015 at 2:22:30 PM UTC-3, Andreas Noack
>>>>>>>>> wrote:
>>>>>>>>>>
>>>>>>>>>> In 0.3 the sparse LDLt and Cholesky factorizations are both in
>>>>>>>>>> the cholfact function. If the matrix is symmetric, but not positive
>>>>>>>>>> definite the result of cholfact will be an LDLt factorization. In
>>>>>>>>>> 0.4 the
>>>>>>>>>> factorizations have been split into cholfact and ldltfact.
>>>>>>>>>>
>>>>>>>>>> Den onsdag den 27. maj 2015 kl. 12.34.30 UTC-4 skrev Eduardo Lenz:
>>>>>>>>>>>
>>>>>>>>>>> Hi.
>>>>>>>>>>>
>>>>>>>>>>> I am trying to solve a linear system defined by a Symmetric
>>>>>>>>>>> sparse matrix. The lufact is working well, but as the matrix is
>>>>>>>>>>> symmetric,
>>>>>>>>>>> I intend to use ldltfact.
>>>>>>>>>>>
>>>>>>>>>>> Unfortunately, it is returning the following error:
>>>>>>>>>>>
>>>>>>>>>>> ERROR: `ldltfact` has no method matching
>>>>>>>>>>> ldltfact(::SparseMatrixCSC{Float64,Int64})
>>>>>>>>>>>
>>>>>>>>>>> but my matrix is reported as
>>>>>>>>>>>
>>>>>>>>>>> typeof(A)
>>>>>>>>>>> SparseMatrixCSC{Float64,Int64}.
>>>>>>>>>>>
>>>>>>>>>>> Is it an error or Im doing something wrong.
>>>>>>>>>>>
>>>>>>>>>>> Thanks,
>>>>>>>>>>> Eduardo.
>>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>
>>>>>
>>>
>
