- Fast and flexible visualization of large & complex datasets
- No need for expensive hardware
- Flexible data import, export and derivation mechanisms
- Different views and rendering styles for each use case
- Standard PC or Notebook
- 32 Bit or 64 Bit Windows or Linux operating system
- OpenGL-capable graphics hardware
- 2 GB Ram (4 GB recommended for larger datasets)
Hardware-Accelerated 3D Rendering
The powerful 3DView is your eye to the data. By directly displaying data on the geometry, it creates very intuitive visualizations of the dataset. Many different rendering styles can be combined and contribute to the final visualization. SimVis provides a wide variety of rendering techniques:
- Point-based Volume Renderer: draws one point for each cell to visualize the volume.
- Hardware-Accelerated Raycaster: shoots rays through the volume and accumulates color values to create a very intuitive dense visualization of the volume.
- Surface Renderer: renders the surface or a wireframe representation of the dataset.
- Slice Plane Renderer: allows to draw an arbitrary number of intersecting planes in the volume. Of course, all planes can be freely rotated or moved interactively and are updated instantly.
- Particle Renderer: draws precalculated particles (if a dataset includes some), and applies attributes to their color and size.
- Lines Renderer: calculates and draws streamlines and pathlines using the built-in integration engine.
All renderers apply color to the resulting image depending on an arbitrary attribute like temperature, velocity, pressure, or other values available in the dataset. The displayed attribute as well as the color mapping can be changed interactively at all times. Each renderer can also display a subset of the whole dataset based on a selection in other views.
Powerful Selection Techniques
To focus on interesting parts of your datasets, SimVis provides flexible selection methods. Selections are used to specify thresholds of interesting data ranges on the selected attribute(s). Multiple selections can be combined arbitrarily enabling more complex and thus powerful questions very intuitively. For example, an engineer's question of "show all areas of slow and hot flow, where a specific vorticity value is exceeded" can be translated into three selections on velocity, temperature and vorticity attributes, respectively.
In SimVis, selections can be performed visually by drawing regions of interest in most of the views. This method of graphically selecting data in an interactive way is called brushing. The concept of selecting data can also be extended to using non-binary selection mechanisms. This is supported by the concept of smooth brushing (i.e. partially selecting values) in SimVis. The flexible combination of multiple brushes is realized using logical operations. Of course, in addition to the fast method of visually brushing data, all parameters of the selections can be entered numerically if accuracy is needed.
All views of the SimVis system are linked, thus selection updates in one view are always propagated to all other views. SimVis comes with different selection views that allow selecting interesting subsets of the data:
- Scatterplot: a two-dimensional view used to plot two arbitrary attributes against each other. This allows to see and understand otherwise hidden correlations between different attributes. It also allows to query data items based on the shown correlations by brushing rectangular regions at real time. Our efficient implementation exploits features of the latest graphics hardware and makes finding and selecting data of interest simple and fast.
- Histogram: a powerful 1D histogram view used to display frequency information on the chosen attribute. Different display options include multiple vs. singular timestep visualization, zooming and panning, or focus & context discrimination based on selections.
- Curve View: a view used to plot time dependent function graphs (one function per volumetric cell) per attribute. This allows selecting data based on querying time-dependent behavior (e.g. rising temperatures).
- Parallel Coordinates: a view showing multiple attributes and the respective data distributions simultaneously. Each attribute is shown on one vertical axis. A data item is represented by connecting a polyline including the positions on each axis according to the respective data value of this attribute. By doing so for each data item, trends and outliers of data distributions and relations become easily visible and can be investigated by interactive selection mechanisms.
Feature definition tree
SimVis allows you to arrange graphical selections in a hierarchical tree to select more complex features of a dataset. Therefore, detailed queries like "show high temperatures at low pressures in a specific region of the dataset" can even be created by beginners.
Hardware accelerated 3D-rendering
Visualization is all about images. This is why SimVis pays special attention on serving you the fastest and most flexible results by providing many different hardware-accelerated renderers. Multiple renderers can be combined to create stunning visualizations that can also be exported to video files.
- point-based volumes
- GPU raycasting
- slice planes
The efficiency of exploration and visual analysis depends on interactivity. SimVis employs state-of-the-art algorithms that utilize today’s hardware in most efficient manners to ensure immediate feedback on any user-interaction. Thereby enabled realtime rendering is not only the basis for excellent results but also fun to work with.
Brushing, focus & context
Brushing describes the process of graphically selecting values of interest within any supporting view. Classified values are straightforwardly rendered in all connected views – including 3D renderers. SimVis furthermore introduces smooth brush- ing that allows for fuzzy selection and therefore improved classification workflow – expressed by outstanding images.
Focus and context visualization ensures emphasis on selected values while preserving a softened representation of their surroundings. Visualizing the context helps locating the focused parts within the shape of a dataset.
Multiple coordinated views
The unique flexibility of SimVis is based on a broad range of different views that are linked to each other. These views can be used to find and visually se- lect features, correlations and anomalies in a dataset. These selections are updated synchronously in other views displaying other attributes of the dataset.
SimVis supports scatterplots, histograms, curve views and parallel coordinates to supply you with the right tool for the right job. A key-element is the realtime 3D view that interactively visualizes selections created in other views directly on the 3D model of the dataset. SimVis supplies you with a rich set of 3D visualizations including volume rendering, intersection planes, surface models, particles and streamlines.
Import & Export Capabilities
No matter, where your data comes from, SimVis can either already read it, or can be extended easily. Converters for many different formats exist, and the list of supported formats is constantly growing. SimVis is not limited to displaying data stored in data files - it also provides a powerful data calculator that can be used to calculate new data dimensions using existing ones. The great flexibility of the calculator interface provides nearly unlimited possibilities for engineers with mathematical background.
SimVis comes with its own xml-based session file format. Sessions can be saved at any time to capture the current workspace including all options of each single view. This allows continuing the analysis process at a later point of time, sharing work with colleagues, or using it as a starting point for live demonstrations.
SimVis is not a one-way tool! Our flexibility with import formats also applies to export possibilities. Exporting visualizations to images or image series takes just a few clicks, and exporting data is just as easy as importing it. Even data that has been calculated at runtime can be exported.
SimVis is designed to run interactively on current consumer hardware. All visualization techniques are implemented using hardware acceleration to achieve optimal performance. If some tasks require more computation time, they are calculated in a different thread to keep the remaining components of the SimVis system responsive. However, SimVis requires OpenGL-capable graphics hardware and we also recommend at least 2 GB of system memory - depending on the size of your datasets, of course. By using OpenGL we do not restrict the use of SimVis to a specific operating system, but provide versions for Linux and Windows, supporting both, 32 and 64 bit architechtures.