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Nature Figure Making Skill

Nature风格图表制作技能指南

A complete guide for producing publication-quality matplotlib figures matching Nature journal standards. Derived from the 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.
一份制作符合《Nature》期刊标准、达到出版级质量的matplotlib图表的完整指南。 本指南源自figures4papers代码仓库 （相关论文发表于Nature Machine Intelligence及顶级机器学习会议），并结合2026年《Nature》期刊中涵盖材料科学、基因组学、 神经科学、植物生物学及临床研究的样本进行了直接视觉观察后的扩展。
配色原则：优先选择所有面板统一的方法族配色，而非最大化色调区分。 对于《Nature Machine Intelligence》风格的密集图表页面，请使用
references/api.md
中描述的低饱和度
NMI pastel
配色系列，且绿色/红色主要用于表示增益、下降及其他方向性提示。

Quick-start: Mandatory rcParams

快速入门：必选rcParams配置

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.
请在每个脚本开头添加以下配置：
python
import matplotlib.pyplot as plt

plt.rcParams['font.family'] = 'sans-serif'
plt.rcParams['font.sans-serif'] = ['Arial']
plt.rcParams['svg.fonttype'] = 'none'          # SVG/PDF中的可编辑文本
plt.rcParams['font.size'] = 16                 # 大型柱状图面板使用24
plt.rcParams['axes.spines.right'] = False
plt.rcParams['axes.spines.top'] = False
plt.rcParams['axes.linewidth'] = 2.5           # 大型柱状图用3，紧凑布局用2
plt.rcParams['legend.frameon'] = False
仅当已安装LaTeX且需要含大量数学公式的标签时，才使用
text.usetex = True
。

Default operating stance

默认操作准则

  • 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.
  • 首先将所需图表归类为以下四种原型之一： 
    定量网格图
    、
    示意图主导的复合图
    、
    图像面板+定量数据图
    或
    非对称多模态混合图
    。
  • 优先选择一个核心面板搭配辅助证据面板，而非用等尺寸子图填满画布。
  • 图表和示意图的背景保持白色；仅在显微镜/体绘制图像面板中使用黑色背景。
  • 当类别位置固定或图例会导致不必要的视线移动时，优先使用直接标签而非图例。
  • 每个图表使用一套克制的配色方案：通常包含一个中性系列、一个信号系列和一个强调系列。
  • 当用户要求通用的
    Nature
    风格而非机器学习/NMI特定风格时，请先阅读
    references/nature-2026-observations.md
    再选择布局。

When to load this skill

何时启用本技能

  • 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".
  • 为目标期刊为《Nature》、NeurIPS、ICLR或同类会议的论文、幻灯片或报告制作matplotlib图表。
  • 涉及分组柱状图、趋势线、热图、雷达图、多面板网格或PDF/SVG/高DPI输出的需求。
  • 任何提及“Nature风格”、“出版级图表”、“论文图表”或“高质量科学绘图”的场景。

When NOT to load

何时不启用

  • 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.
  • 使用Plotly、Altair、Bokeh或其他交互式/网页优先的绘图工具。
  • 仅用于探索性数据分析（EDA）且无出版目标的图表。
  • 主要工作流程涉及3D、GIS或非matplotlib工具。
  • 以Illustrator / Figma为核心的布局工作流程。

Related files

相关文件

FileOpen when
references/design-theory.mdTypography, color theory, layout rationale, export policy
references/api.mdPALETTE, helper function signatures, validation rules
references/common-patterns.mdUltra-wide panels, legend-only axes, print-safe bars
references/nature-2026-observations.mdReal 
Nature
page archetypes: schematic-led composites, dark image plates, clinical triptychs, asymmetric hero layouts
references/tutorials.mdEnd-to-end walkthroughs: bars, trends, heatmaps
references/chart-types.mdRadar, 3D sphere, fill_between, scatter patterns
文件打开场景
references/design-theory.md排版、配色理论、布局原理、导出规范
references/api.md配色方案、辅助函数签名、验证规则
references/common-patterns.md超宽面板、仅图例轴、打印安全柱状图
references/nature-2026-observations.md《Nature》真实页面原型：示意图主导的复合图、深色图像面板、临床三联图、非对称核心布局
references/tutorials.md完整流程教程：柱状图、趋势图、热图
references/chart-types.md雷达图、3D球体图、填充折线图、散点图样式