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bio-reporting-figure-export

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.

インストール方法を見る

含まれるファイル(3)

  • SKILL.md3.2 KB
  • examples/publication_figures.py5.6 KB
  • usage-guide.md1.6 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Version Compatibility

Reference examples tested with: ggplot2 3.5+, matplotlib 3.8+

Before using code patterns, verify installed versions match. If versions differ:

  • Python: pip show <package> then help(module.function) to check signatures
  • R: packageVersion('<pkg>') then ?function_name to verify parameters

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Publication-Ready Figure Export

"Export figures for publication" → Save plots as high-resolution PDF/SVG/TIFF with journal-required DPI and dimensions.

  • Python: fig.savefig('fig.pdf', dpi=300, bbox_inches='tight')
  • R: ggsave('fig.pdf', width=7, height=5, units='in')

Python (matplotlib)

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)

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

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

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

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