[Paraview] Loading data from ParaView
Michael Gronager
Michael Gronager" <mpg at uni-c . dk
Mon, 15 Sep 2003 11:02:22 +0100
This is a multi-part message in MIME format.
------=_NextPart_000_00AB_01C37B78.D6E32C10
Content-Type: text/plain;
charset="iso-8859-1"
Content-Transfer-Encoding: 7bit
Hi Berk,
Attached please find a zip file containing the Plot3D function reader.
The README states:
This is compiled under vtkMy/IO/
It is based on a copy of the vtkPLOT3DReader, maby I should have done it
throug inheritance. But on the other hand the data selection mechanism(the
compute function) don't work properly becaus of missing data ie. VTK_RHOINF,
VTK_CINF ... .
I have encountered different types of blockmarkers. The reader is hardcoded
to read the specific plot3d files eksported from CFX.
I will gladly answer any quiestions about the reader to have it cleand up
and genralized.
ps. I'm sorry but I can not give you any of my test PLOT3D files.
pps. If you find any bugs please let me know.
Best Regards
Ulfar Mani Fridjonsson
(ulfar . mani . fridjonsson at uni-c . dk)
Best regards,
Michael
----- Original Message -----
From: "Berk Geveci" <berk . geveci at kitware . com>
To: "Michael Gronager" <mpg at uni-c . dk>
Cc: <paraview at paraview . org>
Sent: Thursday, September 11, 2003 2:53 PM
Subject: Re: [Paraview] Loading data from ParaView
> By the way, if anybody has code for reading unstructured PLOT3D
> files or functions that they want to contribute, I would be
> more than happy to clean it up and put it in VTK.
>
> -Berk
>
>
> On Thu, 2003-09-11 at 08:58, Michael Gronager wrote:
> > Hi Joonsuk Lee,
> >
> > I have a student that has actually written a Plot3D function file
importer
> > for
> > VTK.
> > If you can use the code you are free to get it.
> >
> > Actually we want to integrate it into ParaView as a loader. The docu
says
> > something about
> > using an XML descriptionfile should actully be enough to add a new
loader to
> > Paraview, however,
> > We haven't been able to find an actual pointer to how to do it or even
an
> > example ...
> >
> > Do you (or anyone else) know how to do it?
> >
> > Regards,
> >
> > Michael
> >
> > --
> > Michael Gronager, PhD
> > Research and Developement, VR-C
> > UNI-C
> > DTU Building 304
> > DK2800 Lyngby
> > DENMARK
> >
> > Phone: +45 3587 8889
> > Fax: +45 3587 8990
> > Direct: +45 3587 8966
> > Mobile: +45 2424 8207
> >
> > Email: mpg at uni-c . dk
> >
> > ----- Original Message -----
> > From: "Joonsuk Lee" <jlee at ariel . met . tamu . edu>
> > To: <paraview at paraview . org>
> > Sent: Wednesday, September 10, 2003 9:08 PM
> > Subject: [Paraview] Loading data from ParaView
> >
> >
> > > Dear All:
> > >
> > > I am a really beginner in using ParaView.
> > > This could be a naive qeustion but
> > > please let me know how I can read the
> > > data produced by FORTRAN?
> > > The file I want to read is function file,
> > > not Q file.
> > > And also how should I set output format
> > > in FORTRAN to be read by ParaView.
> > >
> > > Thanks in advance.
> > >
> > > Joonsuk
> > > ----------------------------------
> > > Joonsuk Lee
> > > Department of Atmoshperic Sciences
> > > Texas A&M University
> > > 3150 TAMU
> > > College Station, TX 77843-3150
> > > Phone: (979) 845-1680
> > > E-mail: jlee at ariel . met . tamu . edu
> > >
> > >
> > > _______________________________________________
> > > ParaView mailing list
> > > ParaView at paraview . org
> > > http://www . paraview . org/mailman/listinfo/paraview
> > >
> >
> > _______________________________________________
> > ParaView mailing list
> > ParaView at paraview . org
> > http://www . paraview . org/mailman/listinfo/paraview
>
>
> _______________________________________________
> ParaView mailing list
> ParaView at paraview . org
> http://www . paraview . org/mailman/listinfo/paraview
>
------=_NextPart_000_00AB_01C37B78.D6E32C10
Content-Type: application/x-zip-compressed;
name="Plot3D.zip"
Content-Transfer-Encoding: base64
Content-Disposition: attachment;
filename="Plot3D.zip"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------=_NextPart_000_00AB_01C37B78.D6E32C10--