In order to use ParaView remotely you will also need an ssh client and a terminal program. Use the following link to download the correct ParaView client binary version for your desktop environment: ParaView binaries. The version number that you install must identically match the version installed at NERSC. This ensures client-server compatibility. It is recommended that you use the binaries provided by Kitware on your workstation matching the NERSC installed version. Running ParaView remotely in a client-server configuration involves establishing an ssh tunnel to the login node, launching the ParaView server, and connecting the server to the client over the tunnel via a socket. The following describes the steps you will take to install ParaView on your desktop and configure it so that you can launch parallel jobs on remote systems from within the ParaView GUI. The ParaView client (or simply paraview) will run on your desktop while the server will run at the remote supercomputing site. ParaView was developed to analyze extremely large datasets using distributed memory computing resources and can be run on supercomputers to analyze terascale datasets, as well as on laptops for smaller data. The data exploration can be done interactively in 3D or programmatically using ParaView's batch processing capabilities. ParaView users can quickly build visualizations to analyze their data using both qualitative and quantitative techniques. The associated files provided above are slightly modified versions of the FDTD - Plasmonic bullseye example and the Nanobeam PC Modulator example.ParaView is an open-source, multi-platform data analysis and visualization application. Also, when using Glyphs with large datasets, it may be necessary to disable the 'mask points' option in the Glyph filter. Use the Glyph filter to create vector plots (as shown in the video). For example, only export from monitors that collect data at a single frequency. It is possible to configure ParaView to interpret this data in a more appropriate way, but the easiest solution is to export datasets that do not have non-spatial parameters. ![]() Actually, ParaView will interpret it as a single electric field attribute that has 150 vector components (50 frequency points x 3 vector components). Ideally, this should be recognized as 50 different sets of vector electric field data. This can complicate your analysis, particularly with vector data.įor example, suppose you have a dataset that contains vector electric field data as a function of x,y,z, and frequency (at 50 frequency points). ![]() The most important difference is that the concept of non-spatial parameters is a less fundamental component of the. vtk data structures are quite similar, there are a few differences. The vtksave command converts the Lumerical dataset into a form that can be imported to ParaView (.vtk file). Each dataset can contain multiple attributes. ![]() Attributes can be scalar or vector quantities. electric field) as a function of both spatial (x,y,z) and non-spatial parameters (eg. Lumerical datasets are used to store attributes (eg. vtk files Datasets with non-spatial parameters ![]() This video shows how the vtksave script command can be used to export simulation data from Lumerical's products, and demonstrates how some of the basic ParaView features (including surface plots, clipping and slicing planes, contours, and glyphs) can be used to create sophisticated visualizations of simulation data. Please consult the ParaView website to access their documentation and other technical resources. Lumerical does not provide technical support for Paraview. ParaView users can quickly build visualizations to analyze their data using qualitative and quantitative techniques. ParaView is an open-source, multi-platform data analysis and visualization application. While these functions are sufficient for the majority of data analysis, there may be situations that require more sophisticated tools. Lumerical's software provide a variety of built in data visualization functions, including line, image and vector plots. Learn how ParaView can be used to create advanced visualizations of Lumerical simulation data.
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