plotstyle 1.1.0

Matplotlib/seaborn style presets matching scientific journal requirements, with validation, export safety, and preview capabilities.

plotstyle

Matplotlib figures formatted for journal submission, automatically.

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PlotStyle makes it easy to produce Matplotlib figures that meet the exact typographic, dimensional, and export requirements of major academic journals. It also integrates with Seaborn, with more integrations planned. Pick a journal, create your figure, save it. PlotStyle handles the rest.

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Table of Contents

• Installation
• Quick Start
• Examples
  • Multi-panel figures
  • Color palettes
  • Colorblind and grayscale previews
  • Validation and submission export
• Supported Journals
• CLI
• Documentation
• Contributing
• Citation
• License

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Installation

Requires Python 3.10+ and Matplotlib >= 3.9.

pip install plotstyle

Optional extras:

pip install "plotstyle[color]"     # colorblind / grayscale previews
pip install "plotstyle[seaborn]"   # seaborn integration
pip install "plotstyle[all]"       # everything

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Quick Start

import numpy as np
import plotstyle

with plotstyle.use("nature") as style:
    fig, ax = style.figure(columns=1)   # sized to Nature's single-column width (89 mm)

    x = np.linspace(0, 2 * np.pi, 200)
    ax.plot(x, np.sin(x), label="sin(x)")
    ax.plot(x, np.cos(x), label="cos(x)")
    ax.set_xlabel("Phase (rad)")
    ax.set_ylabel("Amplitude (a.u.)")
    ax.legend()

    style.savefig(fig, "figure.pdf")    # 300 DPI minimum, TrueType fonts embedded

The with block is the recommended pattern. Matplotlib's rcParams are restored automatically when it exits, even if an exception occurs.

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Examples

Multi-panel figures

style.subplots() works like plt.subplots() but sizes the figure to the journal spec and adds panel labels automatically, styled to each journal's convention (A, B, C for Science; a, b, c for Nature; (a), (b), (c) for IEEE).

import numpy as np
import plotstyle

rng = np.random.default_rng(42)

with plotstyle.use("science") as style:
    fig, axes = style.subplots(nrows=2, ncols=2, columns=2)

    x = np.linspace(0, 10, 100)
    axes[0, 0].plot(x, np.sin(x), label="sin")
    axes[0, 0].plot(x, np.cos(x), label="cos")
    axes[0, 0].set_xlabel("x")
    axes[0, 0].set_ylabel("f(x)")
    axes[0, 0].legend()

    xs = rng.normal(0, 1, 60)
    ys = 0.7 * xs + rng.normal(0, 0.3, 60)
    axes[0, 1].scatter(xs, ys, s=12, alpha=0.7)
    axes[0, 1].set_xlabel("Variable X")
    axes[0, 1].set_ylabel("Variable Y")

    axes[1, 0].bar(["A", "B", "C", "D"], [3.2, 5.8, 4.1, 6.5])
    axes[1, 0].set_xlabel("Category")
    axes[1, 0].set_ylabel("Count")

    axes[1, 1].hist(rng.normal(0, 1, 500), bins=25, edgecolor="white", linewidth=0.5)
    axes[1, 1].set_xlabel("Value")
    axes[1, 1].set_ylabel("Frequency")

    style.savefig(fig, "multi_panel.pdf")

axes is always a 2-D NumPy array. Use axes[0, 0] to access a single panel or axes.flat to iterate. Pass panels=False to suppress the automatic labels.

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Color palettes

Each journal has a recommended colorblind-safe palette. plotstyle.palette() returns hex color strings, cycling if you need more than the palette length.

import matplotlib.pyplot as plt
import plotstyle

journals = ["nature", "science", "ieee", "acs"]
fig, axes = plt.subplots(len(journals), 1, figsize=(6, 0.6 * len(journals)))

for ax, journal in zip(axes, journals):
    pal = plotstyle.palette(journal, n=8)
    for i, color in enumerate(pal):
        ax.barh(0, 1, left=i, color=color, edgecolor="none", height=0.8)
    ax.set_xlim(0, 8)
    ax.set_yticks([])
    ax.set_ylabel(journal, rotation=0, ha="right", va="center")
    ax.set_xticks([])

fig.suptitle("Journal Color Palettes")
fig.tight_layout()
fig.savefig("palette_comparison.png", dpi=150)

Pass with_markers=True to get (color, linestyle, marker) tuples, useful for journals like IEEE that print in grayscale:

styled = plotstyle.palette("ieee", n=4, with_markers=True)
for color, ls, marker in styled:
    ax.plot(x, y, color=color, linestyle=ls, marker=marker)

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Colorblind and grayscale previews

Build a figure, then simulate how it looks under color vision deficiency or grayscale printing before you submit.

import numpy as np
import plotstyle

with plotstyle.use("nature") as style:
    colors = style.palette(n=4)
    fig, ax = style.figure(columns=1)
    x = np.linspace(0, 5, 80)
    for i, c in enumerate(colors):
        ax.plot(x, np.sin(x + i), color=c, linewidth=1.5, label=f"Series {i + 1}")
    ax.set_xlabel("Time (s)")
    ax.set_ylabel("Signal")
    ax.legend()

    cvd_fig = plotstyle.preview_colorblind(fig)
    cvd_fig.savefig("accessibility_colorblind.png", dpi=150, bbox_inches="tight")

    gray_fig = plotstyle.preview_grayscale(fig)
    gray_fig.savefig("accessibility_grayscale.png", dpi=150, bbox_inches="tight")

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Validation and submission export

Validate a figure against the journal's requirements, then export in all required formats at once.

report = plotstyle.validate(fig, journal="nature")
print(report)          # formatted compliance table
print(report.passed)   # True if everything is OK

for failure in report.failures:
    print(failure.message)         # what failed
    print(failure.fix_suggestion)  # how to fix it

paths = plotstyle.export_submission(
    fig,
    "figure1",
    journal="ieee",
    author_surname="Smith",     # IEEE prepends the surname prefix to filenames
    output_dir="submission/",
)
# Produces: submission/smith_figure1.pdf (and any other IEEE-required formats)

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Supported Journals

Key	Journal	Publisher
acs	ACS (JACS)	American Chemical Society
cell	Cell	Cell Press
elsevier	Elsevier	Elsevier
ieee	IEEE Transactions	IEEE
nature	Nature	Springer Nature
plos	PLOS ONE	Public Library of Science
prl	Physical Review Letters	American Physical Society
science	Science	AAAS
springer	Springer	Springer
wiley	Wiley	Wiley

Need another journal? See CONTRIBUTING.md.

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CLI

plotstyle list                                 # list all journal presets
plotstyle info <journal>                       # show spec details
plotstyle diff <journal_a> <journal_b>         # compare two journals
plotstyle fonts --journal <journal>            # check font availability
plotstyle validate <file> --journal <journal>  # validate a saved figure
plotstyle export <file> --journal <journal>    # print snippet for re-exporting

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Documentation

Full documentation at plotstyle.readthedocs.io:

• Installation guide
• Quick start tutorial
• API reference
• CLI reference
• FAQ

Working examples are in the examples/ directory.

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Contributing

See CONTRIBUTING.md for development setup, adding journal specs, and pull request guidelines.

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Citation

If PlotStyle helps your research, a citation or star is appreciated:

@misc{plotstyle,
  author  = {Kaushal, Rahul},
  title   = {PlotStyle: Publication-ready scientific figure presets for Matplotlib},
  year    = {2026},
  url     = {https://github.com/rahulkaushal04/plotstyle},
  note    = {Version 1.1.0},
}

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License

MIT © 2026 Rahul Kaushal