Field-Consistent Glyphs

  • ParaView
  • Python
  • C++
  • Linux
  • Visualization
The internship project developed a ParaView filter for “Field-Consistent Glyphs” that visualizes vector and tensor fields not with straight arrows but with curved, streamline-based shapes. Each glyph is created by integrating parallel and orthogonal streamlines, so its geometry follows the local field everywhere and reduces misinterpretation in strongly curved regions. On radial, rotational and saddle fields the approach shows the flow more clearly than standard arrows with significantly fewer glyphs but requires noticeably more computation time per glyph. Initial experiments with 3D tensor glyphs confirm the concept’s transferability and open perspectives for spatial, temporal and uncertainty extensions.

Task

Conventional arrow glyphs encode vectors exactly only at their origin; along the shaft, direction and magnitude can be misleading in curved or swirling fields. The central task of this internship was therefore:

Requirements analysis:
Identify where and why arrow glyphs fail and define criteria for a field-faithful representation.

Design of a field-consistent glyph scheme:
Develop a concept that incorporates both parallel and orthogonal information of the field yet can still be recognized as an “arrow”.

Implementation as a ParaView filter:
Realization in Python with a parameterizable interface (seed grid, step size, integration method, glyph variants) and a runnable Docker/VM environment.

Evaluation & comparison:
Testing on synthetic test fields, comparison with standard glyphs, measurement of clarity, glyph density and computation time.

Formulate outlook:
Sketch extensions in 3D, topology-driven placement, time dependence and uncertainty depiction

The goal was a practical prototype that gives researchers a more precise tool for exploring complex field data.

Approach

Development environment:
ParaView ran in an Ubuntu VM; a Python plug-in implemented the filter. The research group’s PRTL plug-in provided the PRTL “Python Model” source and supplied analytic test fields on regular grids.

Algorithm & pipeline:
1. Seed placement: grid or user-defined points.
2. Main streamline: forward and backward integration along the field direction (Euler or RK4, optionally normalized) forms the curved “spine”/main streamline of the glyph.
3. Shaft width: orthogonal integration from the spine start generates symmetrical side lines.
4. Arrow head: three variants – weighted combination (smooth), alternating “staircase” steps or Bézier interpolation – close the tip depending on data curvature and performance needs.
5. Parameter control: number of steps, step size, normalization, scale factor and head variant are interactively adjustable; sliders give live feedback in ParaView.

Results & analysis:
On radial, saddle and vortex fields each glyph reconstructed the local flow visibly more faithfully than straight arrows; at the same time a lower seed density was sufficient, making the picture appear decluttered. The price is an orders-of-magnitude higher integration effort, but this can prospectively be managed through adaptive seeding or parallelization.

Through these steps a modular, documented filter emerged that enables field-consistent glyphs for 2D vector fields and lays the foundation for 3D, time-dependent or uncertainty-laden extensions.