[petsc-users] (no subject)

[Ji Zhang]

Thanks. I think I find the right way.

Wayne

On Fri, Sep 16, 2016 at 11:33 AM, Ji Zhang <gotofd at gmail.com> wrote:

> Thanks for your warm help. Could you please show me some necessary
> functions or a simple demo code?
>
>
> Wayne
>
> On Fri, Sep 16, 2016 at 10:32 AM, Barry Smith <bsmith at mcs.anl.gov> wrote:
>
>>
>>   You should create your small m_ij matrices as just dense two
>> dimensional arrays and then set them into the big M matrix. Do not create
>> the small dense matrices as PETSc matrices.
>>
>>   Barry
>>
>>
>> > On Sep 15, 2016, at 9:21 PM, Ji Zhang <gotofd at gmail.com> wrote:
>> >
>> > I'm so apologize for the ambiguity. Let me clarify it.
>> >
>> > I'm trying to simulation interactions among different bodies. Now I
>> have calculated the interaction between two of them and stored in the
>> sub-matrix m_ij. What I want to do is to consider the whole interaction and
>> construct all sub-matrices m_ij into a big matrix M, just like this,
>> imaging the problem contain 3 bodies,
>> >
>> >          [  m11  m12  m13  ]
>> >  M =  |  m21  m22  m23  |   ,
>> >          [  m31  m32  m33  ]
>> >
>> > The system is huge that I have to use MPI and a lot of cups. A mcve
>> code is showing below, and I'm using a python wrap of PETSc, however, their
>> grammar is similar.
>> >
>> > import numpy as np
>> > from petsc4py import PETSc
>> >
>> > mSizes = (5, 8, 6)
>> > mij = []
>> >
>> > # create sub-matrices mij
>> > for i in range(len(mSizes)):
>> >     for j in range(len(mSizes)):
>> >         temp_m = PETSc.Mat().create(comm=PETSc.COMM_WORLD)
>> >         temp_m.setSizes(((None, mSizes[i]), (None, mSizes[j])))
>> >         temp_m.setType('mpidense')
>> >         temp_m.setFromOptions()
>> >         temp_m.setUp()
>> >         temp_m[:, :] = np.random.random_sample((mSizes[i], mSizes[j]))
>> >         temp_m.assemble()
>> >         mij.append(temp_m)
>> >
>> > # Now we have four sub-matrices. I would like to construct them into a
>> big matrix M.
>> > M = PETSc.Mat().create(comm=PETSc.COMM_WORLD)
>> > M.setSizes(((None, np.sum(mSizes)), (None, np.sum(mSizes))))
>> > M.setType('mpidense')
>> > M.setFromOptions()
>> > M.setUp()
>> > mLocations = np.insert(np.cumsum(mSizes), 0, 0)    # mLocations = [0,
>> mSizes]
>> > for i in range(len(mSizes)):
>> >     for j in range(len(mSizes)):
>> >         M[mLocations[i]:mLocations[i+1],
>> mLocations[j]:mLocations[j+1]] = mij[i*len(mSizes)+j][:, :]
>> > M.assemble()
>> >
>> > Thanks.
>> >
>> >
>> > 2016-09-16
>> > Best,
>> > Regards,
>> > Zhang Ji
>> > Beijing Computational Science Research Center
>> > E-mail: gotofd at gmail.com
>> >
>> >
>> >
>> >
>> >
>> > Wayne
>> >
>> > On Thu, Sep 15, 2016 at 8:58 PM, Matthew Knepley <knepley at gmail.com>
>> wrote:
>> > On Thu, Sep 15, 2016 at 4:23 AM, Ji Zhang <gotofd at gmail.com> wrote:
>> > Thanks Matt. It works well for signal core. But is there any solution
>> if I need a MPI program?
>> >
>> > It unclear what the stuff below would mean in parallel.
>> >
>> > If you want to assemble several blocks of a parallel matrix that looks
>> like serial matrices, then use
>> >
>> >   http://www.mcs.anl.gov/petsc/petsc-current/docs/manualpages
>> /Mat/MatGetLocalSubMatrix.html
>> >
>> >   Thanks,
>> >
>> >      Matt
>> >
>> > Thanks.
>> >
>> > Wayne
>> >
>> > On Tue, Sep 13, 2016 at 9:30 AM, Matthew Knepley <knepley at gmail.com>
>> wrote:
>> > On Mon, Sep 12, 2016 at 8:24 PM, Ji Zhang <gotofd at gmail.com> wrote:
>> > Dear all,
>> >
>> > I'm using petsc4py and now face some problems.
>> > I have a number of small petsc dense matrices mij, and I want to
>> construct them to a big matrix M like this:
>> >
>> >          [  m11  m12  m13  ]
>> >     M =  |  m21  m22  m23  |   ,
>> >          [  m31  m32  m33  ]
>> > How could I do it effectively?
>> >
>> > Now I'm using the code below:
>> >
>> >     # get indexes of matrix mij
>> >     index1_begin, index1_end = getindex_i( )
>> >     index2_begin, index2_end = getindex_j( )
>> >     M[index1_begin:index1_end, index2_begin:index2_end] = mij[:, :]
>> > which report such error messages:
>> >
>> >     petsc4py.PETSc.Error: error code 56
>> >     [0] MatGetValues() line 1818 in /home/zhangji/PycharmProjects/
>> petsc-petsc-31a1859eaff6/src/mat/interface/matrix.c
>> >     [0] MatGetValues_MPIDense() line 154 in
>> /home/zhangji/PycharmProjects/petsc-petsc-31a1859eaff6/src/m
>> at/impls/dense/mpi/mpidense.c
>> >
>> > Make M a sequential dense matrix.
>> >
>> >    Matt
>> >
>> >     [0] No support for this operation for this object type
>> >     [0] Only local values currently supported
>> >
>> > Thanks.
>> >
>> >
>> > 2016-09-13
>> > Best,
>> > Regards,
>> > Zhang Ji
>> > Beijing Computational Science Research Center
>> > E-mail: gotofd at gmail.com
>> >
>> >
>> >
>> >
>> >
>> > --
>> > What most experimenters take for granted before they begin their
>> experiments is infinitely more interesting than any results to which their
>> experiments lead.
>> > -- Norbert Wiener
>> >
>> >
>> >
>> >
>> > --
>> > What most experimenters take for granted before they begin their
>> experiments is infinitely more interesting than any results to which their
>> experiments lead.
>> > -- Norbert Wiener
>> >
>>
>>
>
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