feat(FXC-3536): add log and symlog plot scale

[damiano-flex]

Greptile Overview

Updated On: 2025-10-03 10:54:12 UTC

Summary

This PR adds logarithmic and symmetric logarithmic scaling support to Tidy3D's plotting functionality. The changes enhance the visualization capabilities by expanding the available scale options from just linear ('lin') and decibel ('dB') to include logarithmic ('log') and symmetric logarithmic ('symlog') scales.

The implementation involves two main components: First, the PlotScale type definition in tidy3d/components/types/base.py is updated to include the new scale options. Second, the plotting infrastructure in tidy3d/components/scene.py is modified to handle these new scales using matplotlib's normalization objects (LogNorm and SymLogNorm).

The core plotting methods like plot_structures_eps and plot_structures_property now accept a scale parameter and use appropriate matplotlib normalizations instead of simple vmin/vmax parameters. For symmetric logarithmic scaling, the implementation includes sophisticated logic to calculate appropriate linear threshold (linthresh) values, particularly for doping concentration data where values can span many orders of magnitude and include both positive and negative values.

This enhancement integrates seamlessly with Tidy3D's existing plotting architecture and follows matplotlib's standard conventions. The change is particularly valuable for electromagnetic simulations where field data, power quantities, and material properties often span wide dynamic ranges that benefit from logarithmic visualization.

Important Files Changed

Changed Files

Filename	Score	Overview
tidy3d/components/types/base.py	5/5	Added 'log' and 'symlog' options to PlotScale type definition
tidy3d/components/scene.py	4/5	Implemented log/symlog scaling in plotting methods with normalization logic and linthresh calculation

Confidence score: 4/5

• This PR is safe to merge with minimal risk of breaking existing functionality
• Score reflects well-structured implementation following matplotlib conventions, though the complex linthresh calculation logic needs attention
• Pay close attention to the symlog threshold calculation methods in scene.py