Pith. sign in

REVIEW

The Simplex Projection: Lossless Visualization of 4D Compositional Data on a 2D Canvas

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2403.11141 v1 pith:7BJK62CT submitted 2024-03-17 cs.GR

Marvin Schmitt , Yuga Hikida , Stefan T Radev , Filip Sadlo , Paul-Christian Bürkner This is my paper · ORCID
classification cs.GR
keywords datacompositionalsimplexvisualizationcanvaslosslessplotsprojection
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
read the original abstract

The simplex projection expands the capabilities of simplex plots (also known as ternary plots) to achieve a lossless visualization of 4D compositional data on a 2D canvas. Previously, this was only possible for 3D compositional data. We demonstrate how our approach can be applied to individual data points, point clouds, and continuous probability density functions on simplices. While we showcase our visualization technique specifically for 4D compositional data, we offer rigorous proofs that support its extension to compositional data of any (finite) dimensionality.

Discussion (0). Continue with ORCID to comment.

Pith tools