From research-writing-assistant
Generates publication-quality Python plots for scientific papers using matplotlib/seaborn, top-journal color schemes like Nature/Science, 450 DPI PNG/SVG exports, and data manifests.
npx claudepluginhub norman-bury/research-writing-skillThis skill uses the workspace's default tool permissions.
本技能指导使用 Python 生成科研论文级别的数据图表。
Creates journal-ready scientific plots with matplotlib, seaborn, plotly. Supports multi-panel layouts, error bars, significance markers, colorblind-safe palettes, PDF/EPS/TIFF exports.
Creates publication-ready scientific figures with matplotlib/seaborn/plotly, including multi-panel layouts, error bars, significance annotations, colorblind-safe palettes, and journal formatting for Nature, Science, Cell.
Guides chart type selection by data structure, color palettes for accessibility/print, figure composition, and journal formatting for scientific publications. Use when preparing data visualizations for talks or submissions.
Share bugs, ideas, or general feedback.
本技能指导使用 Python 生成科研论文级别的数据图表。
默认环境名：research
激活命令：
conda activate research
必需库：
pip install matplotlib seaborn numpy pandas
如环境未配置，调用 environment-setup 技能。
任何数据图都必须先有数据文件和数据清单（data manifest）。默认路径：
figures/data-manifest.md
figures/data/<figure-name>.csv
figures/<section>/<figure-name>.py
figures/<section>/<figure-name>.png
figures/<section>/<figure-name>.svg
figures/data-manifest.md 至少记录：
| Figure | Data file | Real/mock | Source | Script | Outputs |
|---|
mock 或 synthetic 数据只允许用于规划版图表。文件名必须以 mock_ 或 synthetic_ 开头，并在图表、表格或章节草稿中保留 [待真实实验替换]。不得把 mock 数据写成“实验结果表明”。
| 用途 | DPI | 说明 |
|---|---|---|
| 期刊投稿 | 300-600 | 大多数期刊要求 |
| 顶刊投稿 | 450+ | Nature/Science等 |
| 屏幕展示 | 150 | PPT/网页 |
本技能默认使用 450 DPI
每张图同时输出两种格式：
| 类型 | 宽度（英寸） | 适用场景 |
|---|---|---|
| 单栏图 | 3.5 | 期刊单栏 |
| 双栏图 | 7.0 | 期刊双栏/全宽 |
| PPT图 | 10.0 | 演示文稿 |
NATURE_COLORS = ['#2E86AB', '#A23B72', '#F18F01', '#C73E1D', '#95C623']
CELL_COLORS = ['#4E79A7', '#F28E2B', '#E15759', '#76B7B2', '#59A14F', '#EDC948']
COLORBLIND_SAFE = ['#0077BB', '#33BBEE', '#009988', '#EE7733', '#CC3311', '#EE3377']
"""
Figure X: [图表标题]
论文章节: [所属章节]
"""
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.font_manager as fm
from pathlib import Path
# 中文字体配置
CHINESE_FONT = None
font_candidates = [
'/System/Library/Fonts/STHeiti Light.ttc',
'/System/Library/Fonts/PingFang.ttc',
]
for fp in font_candidates:
if Path(fp).exists():
CHINESE_FONT = fm.FontProperties(fname=fp)
break
plt.rcParams['axes.unicode_minus'] = False
# 顶刊配色
COLORS = ['#4E79A7', '#F28E2B', '#E15759', '#76B7B2', '#59A14F']
def setup_plot_style():
plt.rcParams.update({
'font.size': 10,
'axes.titlesize': 12,
'axes.labelsize': 10,
'axes.spines.top': False,
'axes.spines.right': False,
'axes.grid': True,
'grid.alpha': 0.3,
'legend.frameon': False,
'savefig.dpi': 450,
'savefig.bbox': 'tight',
})
def main():
setup_plot_style()
fig, ax = plt.subplots(figsize=(7, 5))
# === 绑定代码 ===
x = np.linspace(0, 10, 100)
ax.plot(x, np.sin(x), color=COLORS[0], label='Model A')
ax.plot(x, np.cos(x), color=COLORS[1], label='Model B')
if CHINESE_FONT:
ax.set_xlabel('时间 (s)', fontproperties=CHINESE_FONT)
ax.set_ylabel('幅值', fontproperties=CHINESE_FONT)
else:
ax.set_xlabel('Time (s)')
ax.set_ylabel('Amplitude')
ax.legend()
# === 绑定代码结束 ===
# 保存
output_dir = Path(__file__).parent
fig_name = Path(__file__).stem
plt.savefig(output_dir / f'{fig_name}.png', dpi=450)
plt.savefig(output_dir / f'{fig_name}.svg')
plt.show()
if __name__ == '__main__':
main()
ax.plot(x, y, color=COLORS[0], linewidth=1.5, marker='o', markersize=4)
ax.bar(x_pos, values, color=COLORS[:len(values)], edgecolor='white')
im = ax.imshow(matrix, cmap='RdBu_r', aspect='auto')
plt.colorbar(im, ax=ax)
bp = ax.boxplot(data_list, patch_artist=True)
for patch, color in zip(bp['boxes'], COLORS):
patch.set_facecolor(color)
ax.scatter(x, y, c=colors, s=sizes, alpha=0.6, cmap='viridis')
figures/
├── chapter1/
│ ├── fig1_overview.py
│ ├── fig1_overview.png
│ └── fig1_overview.svg
├── chapter2/
└── chapter3/
fig{序号}_{描述}.pyfig1_model_architecture.pyfrom matplotlib.font_manager import FontProperties
font = FontProperties(fname='/System/Library/Fonts/STHeiti Light.ttc')
ax.set_xlabel('中文标签', fontproperties=font)
plt.savefig('figure.png', dpi=450, bbox_inches='tight')
ax.legend(loc='upper left', bbox_to_anchor=(1.02, 1))