nature-figure

# Nature Figure Making Skill A complete guide for producing publication-quality matplotlib figures matching Nature journal standards. Derived from the [figures4papers](https://github.com/ChenLiu-1996/figures4papers) repository (papers published in *Nature Machine Intelligence* and top ML venues), then extended with direct visual observations from a 2026 `Nature` sample spanning materials science, genomics, neuroscience, plant biology and clinical studies. Color policy: prefer **unified method families across all panels** over maximal hue separation. For dense Nature Machine Intelligence-style figure pages, use the low-saturation `NMI pastel` family described in `references/api.md` and reserve green/red mainly for gains, drops, and other directional cues. ## Quick-start: Mandatory rcParams Always apply these at the top of every script: ```python import matplotlib.pyplot as plt plt.rcParams['font.family'] = 'sans-serif' plt.rcParams['font.sans-serif'] = ['Arial'] plt.rcParams['svg.fonttype'] = 'none' # editable text in SVG/PDF plt.rcParams['font.size'] = 16 # 24 for large bar panels plt.rcParams['axes.spines.right'] = False plt.rcParams['axes.spines.top'] = False plt.rcParams['axes.linewidth'] = 2.5 # 3 for big bars, 2 for compact plt.rcParams['legend.frameon'] = False ``` Use `text.usetex = True` only when LaTeX is installed and math-rich labels are required. ## Default operating stance - Start by classifying the requested figure into one of four archetypes: `quantitative grid`, `schematic-led composite`, `image plate + quant`, or `asymmetric mixed-modality figure`. - Prefer one **hero panel** plus subordinate evidence panels over filling the canvas with equal-sized subplots. - Keep the background white for plots and diagrams; switch to black only for microscopy / volume-rendering image plates. - Prefer direct labels over legends when categories are spatially fixed or the legend would force unnecessary eye travel. - Keep one restrained palette per figure: usually one neutral family, one signal family, and one accent family. - When the user asks for broad `Nature` style rather than ML/NMI-specific style, read `references/nature-2026-observations.md` before choosing layout. ## When to load this skill - Matplotlib figures for **papers, slides, or reports** targeting Nature, NeurIPS, ICLR, or similar venues. - Requests involving **grouped bars, trend lines, heatmaps, radar plots, multi-panel grids**, or **PDF/SVG/high-DPI** output. - Any mention of "Nature style", "publication figure", "paper figure", or "high-quality scientific plot". ## When NOT to load - Plotly, Altair, Bokeh, or other interactive/web-first plotting. - EDA-only plots without a publication target. - Primary workflow is 3D, GIS, or non-matplotlib tooling. - Illustrator / Figma–first layout. ## Related files | File | Open when | |------|-----------| | [references/design-theory.md](references/design-theory.md) | Typography, color theory, layout rationale, export policy | | [references/api.md](references/api.md) | PALETTE, helper function signatures, validation rules | | [references/common-patterns.md](references/common-patterns.md) | Ultra-wide panels, legend-only axes, print-safe bars | | [references/nature-2026-observations.md](references/nature-2026-observations.md) | Real `Nature` page archetypes: schematic-led composites, dark image plates, clinical triptychs, asymmetric hero layouts | | [references/tutorials.md](references/tutorials.md) | End-to-end walkthroughs: bars, trends, heatmaps | | [references/chart-types.md](references/chart-types.md) | Radar, 3D sphere, fill_between, scatter patterns |