Our review
Scaffolds matplotlib figure code for publication-ready topological data analysis visuals, following the conventions of a specific codebase.
Strengths
- Enforces consistent colors, sizes, and style constants from the project
- Outputs publication-grade figures (PDF/PNG)
- Provides ready-to-use templates for persistence diagrams, null histograms, etc.
- Automatically places files in the correct output directory (paper, supplement, or working)
Limitations
- Requires the `trajectory_tda` codebase to be present and configured
- Only supports the figure types defined in the templates
- Style constants are fixed and cannot be overridden on the fly
When you need to generate a standardized figure for a paper using the `trajectory_tda` library and want to ensure visual consistency.
If you need a custom figure outside the available templates or are working outside the `trajectory_tda` project context.
Security analysis
SafeThe skill only provides guidance on writing matplotlib code using predefined constants and does not instruct any system commands, network access, or data exfiltration. No execution risk is present.
No concerns found
Examples
/tda-figure-spec persistence-diagram P01-B/tda-figure-spec null-histogram P01-A/tda-figure-spec/tda-figure-spec — Generate Publication-Ready TDA Figures
Scaffold matplotlib figure code following the established trajectory_tda/viz/ conventions.
Uses PUBLICATION_RC, DPI, FIGSIZE_*, STATE_COLORS, and _save_figure from the
codebase — never ad-hoc sizes or colours.
Usage
/tda-figure-spec [figure-type] [paper-number]
Example: /tda-figure-spec persistence-diagram P01-B
Example: /tda-figure-spec null-histogram P01-A
Example: /tda-figure-spec (interactive)
Style constants (always import from trajectory_tda/viz/constants.py)
from trajectory_tda.viz.constants import (
DPI, FIGSIZE_FULL, FIGSIZE_WIDE, FIGSIZE_HALF, FIGSIZE_SQUARE,
PUBLICATION_RC, STATE_COLORS, STATES, STATE_LABELS, REGIME_LABELS,
)
import matplotlib.pyplot as plt
plt.rcParams.update(PUBLICATION_RC)
Figure size guide
| Use case | Constant | Size |
|---|---|---|
| Single full-width plot | FIGSIZE_FULL | 190mm × 120mm |
| Wide two-panel | FIGSIZE_WIDE | 190mm × 104mm |
| Half-width single panel | FIGSIZE_HALF | 90mm × 120mm |
| Square heatmap | FIGSIZE_SQUARE | 90mm × 90mm |
Save function (always use this pattern)
def _save_figure(fig, output_dir: Path, name: str) -> None:
output_dir.mkdir(parents=True, exist_ok=True)
fig.savefig(output_dir / f"{name}.pdf", format="pdf")
fig.savefig(output_dir / f"{name}.png", format="png", dpi=DPI)
Colour rules
- State space: always
STATE_COLORSdict — nevertab10or default cycle - Observations:
#2d6a2e(green); Null:steelblue; Dim 0: green; Dim 1:#1a237e - Regimes:
plt.cm.tab10withREGIME_LABELSorder - Sequential/diverging:
viridis,plasma,RdBu_r— neverjet
Annotation standards
- p-values: write
p=0.003, notp<0.01 - Axes: remove top and right spines; keep bottom and left
- Legends:
frameon=False - Subplot labels:
ax.text(0.02, 0.97, "(a)", transform=ax.transAxes, ...)
Figure templates available
| Template | When to use |
|---|---|
| plot_persistence_diagram(diagram, dim, ax) | Scatter birth-death pairs |
| plot_barcode(diagram, dim, ax) | Feature lifetimes sorted by persistence |
| plot_null_histogram(observed, null_dist, p_value, dim, ax) | Permutation test result |
| plot_landscape_comparison(obs, null, grid, ax) | L² landscape distance (mandatory) |
Output paths
| Context | Path | Naming |
|---|---|---|
| Production paper figure | papers/PXX/figures/ | fig{N}_{desc}.{pdf\|png} |
| Supplement | papers/PXX/figures/ | figS{N}_{desc}.{pdf\|png} |
| Working / exploratory | figures/{domain}/ | YYYYMMDD_{desc}.png |
Working figures must not be saved to papers/PXX/figures/ — that is for production only.
Prompt Engineering
Data & AI
Prompt engineering best practices and templates to maximize AI outputs.
Data Visualization
Data & AI
Generates data visualizations and charts tailored to your data.
RAG Architecture Setup
Data & AI
Setup guide for RAG (Retrieval-Augmented Generation) architectures.