scientific-plotting

name

scientific-plotting

description

Use when creating publication-quality matplotlib figures in Python — scientific line plots, scatter, error bars, heatmaps, contour, bar, histogram, 3D, multi-panel, log-scale, twin/inset axes, and colorbars. Applies APS journal styling (Helvetica, 8pt, inward ticks, brewer_set1 palette) with mathtext fallback when LaTeX isn't installed. Saves figures as 300 DPI PNG. Customization guidance for Nature, Science, IEEE column widths and fonts.

Scientific Plotting (pubplot-style)

Generate publication-quality matplotlib figures using APS-derived styling. Inspired by pubplot but self-contained: no pubplot package required.

When this applies

Use when the user:

• Asks to plot data for a paper, thesis, or journal submission
• Says "publication quality", "make this plot look professional", or names a journal (APS, Nature, Science, IEEE, ACS)
• Builds matplotlib figures and asks for consistent styling across multiple plots

Skip for:

• Plotly, seaborn-only, bokeh, or dashboard work
• General matplotlib debugging unrelated to styling
• Data analysis without producing a figure

Quick start

1. Copy the bundled module into the user's project root

   The file scripts/pubplot_style.py (in this skill directory) is a drop-in module. Copy it to wherever the user's plotting scripts live:

   cp <skill>/scripts/pubplot_style.py ./pubplot_style.py
   

2. In every plotting script, import and apply the style up front

   import matplotlib.pyplot as plt
   import numpy as np
   from pubplot_style import apply_style, linestyle_generator
   apply_style()           # APS defaults, LaTeX on, single-column figure
   # apply_style(latex=False)  # if LaTeX isn't installed
   # apply_style(columns=2)    # for a 6.75"-wide double-column figure
   

3. Build the plot using a recipe from references/recipes.md

4. Save as 300 DPI PNG

   fig.savefig("figure.png", dpi=300, bbox_inches="tight")
   

Decision tree

User wants	Read
Single line or multiple curves to distinguish	references/recipes.md § Line / Multi-curve
Scatter / error bars / shaded bands	references/recipes.md § Scatter, Errorbar
Heatmap or 2D field	references/recipes.md § Heatmap; references/colors.md for colormap choice
Bar, histogram, violin, box	references/recipes.md § Bar / Hist / Violin
Contour or 3D	references/recipes.md § Contour / 3D
Multi-panel figure with subplot labels	references/recipes.md § Multi-panel
Log-scale axes, twin axes, inset axes	references/recipes.md § Log-scale, Twin/Inset
Match Nature / Science / IEEE / ACS sizing	references/customization.md
Switch LaTeX ↔ mathtext, or LaTeX errors	references/customization.md § LaTeX, then troubleshooting.md
Any rendering error	references/troubleshooting.md

What apply_style() does

• Font: Helvetica (fallback Arial / DejaVu Sans), 8pt base
• Figure size: 3.375" × 2.295" (single column, APS default)
• Inward ticks on all four sides, minor ticks visible
• Frameless legend, compact spacing
• Default color cycle: BREWER_SET1 (8 colors + black)
• LaTeX rendering on by default with siunitx + Helvetica preamble
• Save defaults: 300 DPI PNG, bbox_inches="tight"

Pass latex=False for mathtext rendering when LaTeX is unavailable. Pass columns=2 for double-column figures.

Loading order for references

Don't pre-load all reference files. Load them as needed:

• references/recipes.md — when picking a plot type
• references/colors.md — when choosing a colormap beyond the default cycler
• references/customization.md — when targeting a non-APS journal, switching LaTeX↔mathtext, or tweaking figure sizes
• references/troubleshooting.md — only when a specific error appears

Boundary

This skill provides styling and recipes. It does NOT:

• Choose what data to plot
• Decide what story the figure tells
• Run statistical analysis
• Manage figure version control