Package: ccx2paraview
© Ihor Mirzov, 2019-2022Distributed under GNU General Public License v3.0Downloads|How to use|Screenshots|Your help|For developers|TODOCalculiX to Paraview converter (frd to vtk/vtu)ConvertsCalculiXASCII .frd-file to view and postprocess analysis results inParaview. Generates von Mises and principal components for stress and strain tensors.Creates separate file for each output interval - it makes possible to animate time history.Caution!If you have 300 time steps in the FRD, there will be 300 Paraview files. If you need one file - write output only for one step in your CalculiX model.Converter is tested onCalculiX examples. Here is how sometest loglooks like.FRD reader is tested to reduce processing time as much as possible. Now it's quite optimized and fast, but Python itself is slower than C/C++. Here we can do nothing, so, for example,Calmed convertermust be faster - another question is if it's able to read and convert any CalculiX results.How to useTo run this converter you'll needPython 3withnumpyandvtk:pip3 install numpy vtkPlease, pay attention that .frd-file type should be ASCII, not binary! Use keywords *NODE FILE, *EL FILE and *CONTACT FILE in your INP model to get results in ASCII format.Download released sources, unpack them and allow to be executed (give permissions).Run converter with command (both in Linux and in Windows):python3 ccx2paraview.py yourjobname.frd vtk
python3 ccx2paraview.py yourjobname.frd vtuAlso you can pass both formats to convert .frd to .vtk and .vtu at once.It is recommended to convert .frd to modern XML .vtu format - its contents are compressed. If you have more than one time step there will be additional XML file created -the PVD file. Open it in Paraview to read data from all time steps (all VTU files) at ones.Starting from ccx2paraview v3.0.0 legacy .vtk format is also fully supported - previously there were problems with component names.A snippet for Paraviewprogrammable filterto convert 6 components data array to full tensor:importnumpyasnpres=np.array([])pd=inputs[0].PointData['S']forxx,yy,zz,xy,yz,xzinpd:t=np.array([[xx,xy,xz],[xy,yy,yz],[xz,yz,zz]])res=np.append(res,t)tensor=dsa.VTKArray(res)tensor.shape=(len(pd),3,3)output.PointData.append(tensor,'S_tensor')A snippet for Paraview programmable filter to calculate eigenvalues and eigenvectors:importnumpyasnpeigenvalues=np.array([])eigenvectors=np.array([])pd=inputs[0].PointData['S']forxx,yy,zz,xy,yz,xzinpd:t=np.array([[xx,xy,xz],[xy,yy,yz],[xz,yz,zz]])w,v=np.linalg.eig(t)w_=np.absolute(w).tolist()i=w_.index(max(w_))eigenvalues=np.append(eigenvalues,w[i])# max abs eigenvalueeigenvectors=np.append(eigenvectors,v[i])# max principal vectoreigenvectors=dsa.VTKArray(eigenvectors)eigenvalues=dsa.VTKArray(eigenvalues)eigenvectors.shape=(len(pd),3)eigenvalues.shape=(len(pd),1)output.PointData.append(eigenvectors,'S_max_principal_vectors')output.PointData.append(eigenvalues,'S_max_eigenvalues')Attention!While developing this converter I'm using latest Python3, latest VTK and latest Paraview. If you have problems with opening conversion results in Paraview - update it.ScreenshotsConverted von Mises stress field with Turbo colormap:Converted translations field with Viridis colormap:Your helpPlease, you may:Star this project.Simply use this software and ask questions.Share your models and screenshots.Report problems byposting issues.For developersInstall package with dependacies:pip3 install numpy vtk ccx2paraviewIn your code use ccx2paraview package in this way:importloggingimportccx2paraviewlogging.basicConfig(level=logging.INFO,format='%(levelname)s:%(message)s')c=ccx2paraview.Converter(frd_file_name,['vtu'])c.run()If you have Python version >= 3.8 create binary withnuitka:pip3 install nuitka

In Windows:
set CC=C:\\MinGW64\\mingw64\\bin\\gcc.exe
python3 -m nuitka --follow-imports --mingw64 __init__.py

In Linux:
python3 -m nuitka --follow-imports __init__.pyIf you have Python version < 3.8 create binary withpyinstaller:pip3 install pyinstaller
pyinstaller __init__.py --onefileAlso there is a good way to create a binary with Cython (works fine for a signle module):sudo apt install cython3
cython3 -3 --embed -o ccx2paraview.c ccx2paraview.py
PYTHONLIBVER=python$(python3 -c 'import sys; print(".".join(map(str, sys.version_info[:2])))')$(python3-config --abiflags)
gcc -Os $(python3-config --includes) ccx2paraview.c -o ccx2paraview $(python3-config --ldflags) -l$PYTHONLIBVERReadhow to create packagesforpypi.org:python3 -m pip install --upgrade build twine
python3 -m build
python3 -m twine upload dist/*Read about VTKfile formatsand VTKunstructured grid. Remember that FRD file is node based, so element results are also stored at nodes after extrapolation from the integration points.TODOLog memory consumption.Which file is written faster: VTK or VTU? VTK is twice faster?Use threads for convertion and writing. Read FRD in the main thread.Read DAT files: it would be a killer feature if Paraview could visualize results in Gauss points. UseCCXStressReader.Multiprocessing for tests.Read binary .frd files.Contribute to meshio. FRD writer. Use meshio XDMF writer:https://github.com/calculix/ccx2paraview/issues/6Include an integer scalar containing each element’s GROUP or MATERIAL.Add element’s material tangent stiffness tensor. Easiest for the paraview user would be to provide it in the (deflected) global cartesian frame. This dataset is useful for checking input data for anisotropic materials, as well as for the stuff with inverse design of fields of this tensor. But it’s a lot more work to produce, especially with nonlinear materials. It’s almost as useful to see the highest principal value of the stiffness, as a scalar or a vector. (but for the vector you need to do the transformation)