What is Reddit's opinion of Paraview?

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Paraview is the go to visualization software for OpenFOAM, and a very powerful VTK tool.

You may run into issues with file formats, depending on how you stored your data and where it's from. Paraview can handle data from most major CFD packages. If it's basically a csv or txt file, I'd suggest using python with the matplotlib library.

pvserver is your friend. Start one in parallel on your machine and then connect to it with ParaView.

If it is compiled correctly it is simply

1. mpirun -np 6 pvserver

2. Open new paraview GUI go to file>connect and make a new connection with localhost 11111

I just tested this again with 4.1.0 (an old on on my machine) and this works fine.

You would have to learn how to use OpenFoam, a free, open source Computational Fluid Dynamics software package.

[Simulating Wind Over Terrain: How to Build an OpenFOAM Case

from GRASS GIS Digital Elevation Models ](http://www4.ncsu.edu/~ejhardi2/OF_GRASS_Geom.pdf)

You'd then view the results in Paraview. But you need a powerful computer to carry out CFD, a supercomputer is ideal.

Yep. You can use a Delauney filter to wrap the point cloud and then you can go nuts on it with contour plots. You can do this in the GUI or just script it with python for your own batch post processing scripts.

According to this you can do it: http://www.paraview.org/Wiki/ParaView/Vector_Graphics_Export

I just tried it on PV4.1 and it seemed to just make a raster eps (checked it out in inkscape). I'd say try it out, I might have been setting it up wrong (export or import).

I think the xml format has more features, supporting for example data compression. Another advantage is that PVD files, which can contain time information of your vtk files, only support the xml formats.

On the other hand, the legacy format is much easier to generate, so I'd recommend you that if you don't need the extra features.

Maybe try Paraview. It's used by Sandia and Los Alamos Labs etc. for visualisation of complex 3D data.

Here Paraview was used to visualise Lidar topography and a CFD plume dispersal simulation:

https://www.youtube.com/watch?v=6u2wCaD_oFM

I would recommend Paraview which uses VTK. I would also recommend using GRASS GIS to get files into the VTK format. Alternatively, you can download Paraview Geo which is basically just Paraview with additional geo-formats supported - although it is usually a couple versions behind in its release cycle. Paraview is a far superior 3D data visualizer than NVIZ, although NVIZ is great in a pinch.

All software I mentioned here are free/open source

I recognize the interface, though it is not a 3D modelling application, but rather a 3D viewing application where you can check the results of a simulation.

The geometry in the video looks like a pressure distribution over the floating turbine.

The name of the program is paraview, and I normally use it to view and process computational fluid dynamics results made in OpenFOAM.

So I basically do computational linear algebra for my day job...

You absolutely need to be proficient in some programming language before you take a class like that. You need to be able to take an algorithm written in math notation and turn that into working code. You can certainly write linear algebra codes in java or C++ (the latter being heavily preferred for computational stuff.) You'll also need to know how to turn numerical data into visual plots, which can range from dumping CSV files to be post-processed in excel, to doing much more advanced visualizations.

"Knowledge of a scientific programming language" can mean different things, but if they specifically mean something like matlab or python/numpy/scipy, it's more just because those things can more easily bring all the tools you need into one place. A lot of students are so horrifically bad at coding it's easier to just have them work in matlab. You can ask a prof in advance if it's okay to do all the assignments in the language of choice, and it should be.

For a very simple 2d model, something like matlab/octave or Python's matplotlib (or even excel) will work fine. For anything more, I'd suggest writing the data to legacy VTK format (pdf), which is well suited to plotting finite elements (e.g. beams). You can then plot this in paraview, which is a fully-featured postprocessing package that will do pretty much anything with a bit of effort.

I'm sure there are many answers but if it were me, I would use ParaView (http://www.paraview.org/). You can then use the wrapper to wrap your intersected STL surfaces and export to STL. You can do this with:

1. Import your STLs

2. Highlight all of them and use the append geometry filter

3. Select shrink filter and set to shrink factor to 1

4. With the keyword "shrink" selected in the object inspector, select extract surface.

5. Go to file>save data> and export your STL

it should provide you with a union of all your STL surfaces.

On http://www.paraview.org/download/ there is a drop-down list under the "Nightly build".

In this list I can see a lot of different things, including a lot of "ParaView-x.x.x-xxx-xxxxxxxx-Qt4-Windows-xxbits.exe".

Aren't those the binary executables for paraview on windows ?

try looking at the paraview guide since the stuff is in the foam user guide in relation to the older version of paraview.

i hope this is the right place for the guide
http://www.paraview.org/documentation/

I would look at Paraview. It's an excellent open source scientific data viewer/post processor. You should be able to build a vtk file (www.vtk.org/VTK/img/file-formats.pdf) pretty easily. There are also some good examples in the manual. Here's a page on building the file with Python.

You might even be able to get away with a .csv file ([x coord, y coord, z coord, temp]); depending on how sophisticated you want it to look.

Monochromatic gradients are better for comparing data, because people automatically assume color transitions imply an important boundary, when in reality the transition point is usually chosen arbitrarily by the software. There's actually a push to remove "rainbow" maps from scientific literature, since it can color [pun intended] the reader's interpretations.

Sources: http://www.jwave.vt.edu/~rkriz/Projects/create_color_table/color_07.pdf http://www.sandia.gov/~kmorel/documents/ColorMaps/ColorMaps.pdf http://www.paraview.org/ParaView3/index.php/Default_Color_Map

(Sorry, that got a little pedantic and off-topic. Fuck the Lions!)