AgentSkillsCN

bio-reporting-figure-export

以适当的分辨率、尺寸与排版,导出多种格式的出版级图表。当您需要为期刊投稿准备图表,为演示文稿制作矢量图形,或在不同分析中保持图表风格的一致性时,请使用此方法。

SKILL.md
--- frontmatter
name: bio-reporting-figure-export
description: Exports publication-ready figures in various formats with proper resolution, sizing, and typography. Use when preparing figures for journal submission, creating vector graphics for presentations, or ensuring consistent figure styling across analyses.
tool_type: mixed
primary_tool: matplotlib

Publication-Ready Figure Export

Python (matplotlib)

python
import matplotlib.pyplot as plt

# Set publication defaults
plt.rcParams.update({
    'font.size': 8,
    'font.family': 'Arial',
    'axes.linewidth': 0.5,
    'lines.linewidth': 1,
    'figure.dpi': 300
})

fig, ax = plt.subplots(figsize=(3.5, 3))  # Single column width
# ... create plot ...

# Save in multiple formats
fig.savefig('figure1.pdf', bbox_inches='tight', dpi=300)
fig.savefig('figure1.png', bbox_inches='tight', dpi=300)
fig.savefig('figure1.svg', bbox_inches='tight')

R (ggplot2)

r
library(ggplot2)

p <- ggplot(data, aes(x, y)) + geom_point() +
  theme_classic(base_size = 8) +
  theme(text = element_text(family = 'Arial'))

# PDF for vector graphics
ggsave('figure1.pdf', p, width = 3.5, height = 3, units = 'in')

# High-res PNG
ggsave('figure1.png', p, width = 3.5, height = 3, units = 'in', dpi = 300)

# TIFF (some journals require)
ggsave('figure1.tiff', p, width = 3.5, height = 3, units = 'in',
       dpi = 300, compression = 'lzw')

Journal Requirements

Journal TypeFormatResolutionWidth
Most journalsPDF/EPSVector3.5" (1-col), 7" (2-col)
Online-onlyPNG300 DPIVariable
PrintTIFF300-600 DPIColumn width

Multi-panel Figures

python
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec

fig = plt.figure(figsize=(7, 5))  # Two-column width
gs = GridSpec(2, 3, figure=fig)

ax1 = fig.add_subplot(gs[0, 0])
ax2 = fig.add_subplot(gs[0, 1:])
ax3 = fig.add_subplot(gs[1, :])

# Add panel labels
for ax, label in zip([ax1, ax2, ax3], ['A', 'B', 'C']):
    ax.text(-0.1, 1.1, label, transform=ax.transAxes,
            fontsize=10, fontweight='bold')

fig.savefig('figure_multipanel.pdf', bbox_inches='tight')

Color Considerations

  • Use colorblind-friendly palettes (viridis, cividis)
  • Ensure sufficient contrast for grayscale printing
  • Maintain consistency across all figures

Related Skills

  • data-visualization/ggplot2-fundamentals - Creating plots in R
  • data-visualization/heatmaps-clustering - Complex visualizations
  • data-visualization/multipanel-figures - Figure composition