EasyPlotLib 0.2.1

A simple plotting library

EasyPlotLib

Matplotlib styles and helpers for publication-quality SCI-journal figures (Nature / Science / Cell / NEJM / Lancet / PNAS / AGU / AMS).

_{Built with the bundled nature style — see the full gallery.}

Install

pip install EasyPlotLib

Quick start

import EasyPlotLib as epl
import matplotlib.pyplot as plt
import numpy as np

# Style + journal column width + color palette in one call.
epl.journal_style("nat1", palette="nature", nrows=1, ncols=2)

fig, axs = plt.subplots(1, 2)
x = np.linspace(0, 2 * np.pi, 200)
for n, ax in enumerate(axs):
    for k in range(3):
        ax.plot(x, np.sin(x + k), label=f"series {k}")
    ax.set_xlabel("x")
    ax.set_ylabel("amplitude")
    ax.annotate(**epl.subplot_labels(n, "a"))      # bold panel labels a, b …

# Editable vector (PDF) + 600-dpi raster.
epl.save_pub(fig, "figures/fig1", formats=("pdf", "png"))

API

Function	Description
journal_style(key, palette=, base_style=, nrows=, ncols=, apply=)	Apply style + size + palette in one call. Returns the figsize dict.
figsizes(key, ...)	rcParams dict with a journal column figure size. Keys: nat1/2, aaas1/2, pnas1..3, agu1..4, ams1..4.
subplot_labels(n, style)	Args for ax.annotate(**...). Styles: a, A, (a), a), a.
set_palette(name, ax=None) / get_palette(name, n=)	Set the color cycle / return raw hex list.
PALETTES	Qualitative palettes: nature, science, nejm, lancet, jama, muted, semantic, nmi, comparison, imaging, bright.
SEMANTIC	Role-based colors (blue_main=hero, green_strong=gain, red_strong=drop, delta_up/down, neutrals, accents).
shades(color, n)	n shades of one hue, light→base — related methods (e.g. a baseline trio, stacked-area family).
alpha_ramp(color, n)	One hue at graduated opacity — the standard ablation encoding.
COLORMAPS	Recommended continuous colormaps for heatmaps/images: sequential, sequential_warm, diverging, grayscale.
save_pub(fig, path, formats=, dpi=)	Save to multiple formats with editable vector text.
cartopy_plot_tickmarks(ax, gl)	Clean lon/lat tick labels for cartopy maps.

Color scheme guidance

Every recurring nature-style color pattern is abstracted into one small, shared API so a whole figure stays consistent (the examples/gallery.py panels all draw from it):

• One restrained palette per figure. Use a unified family across panels rather than maximizing hue variety; reduce saturation before adding categories.
• Assign color by meaning, not by index. SEMANTIC reserves blue_main for the proposed/hero method and green/red for gains/drops. Never remap the same method to a different hue in another panel.
• Many-method comparison → get_palette("comparison"): soft pastel baselines with related methods sharing a hue family, and one saturated hero (put your method last).
• Related methods / one family → shades(color, n): graduated lightness of a single hue (baseline trios, stacked-area bands).
• Ablations → alpha_ramp(color, n): one hue, opacity carries the ordering.
• Continuous data (heatmaps, density, images) → a perceptual colormap from COLORMAPS — sequential for magnitude, diverging for signed values.
• Microscopy → imaging accents (cyan/magenta) on a black background.

Chart-type gallery

examples/gallery.py renders one publication-styled panel per common archetype. Every panel sources its colors from the abstracted API above, so a method keeps its hue across the whole figure (blue = hero, grey = baseline):

python examples/gallery.py   # writes PNGs to examples/gallery/

Method comparison · get_palette("comparison")	Ablation · alpha_ramp()	Trend + CI · SEMANTIC
Heatmap · COLORMAPS["sequential"]	Scatter / bubble · SEMANTIC	Radar / polar · SEMANTIC
Violin + box · shades()	Forest / interval · SEMANTIC	Stacked area · shades()

Style notes

The bundled nature style uses 7 pt sans (TeX Gyre Heros / Helvetica), an open frame (no top/right spines), and export settings that keep text editable in Illustrator/Inkscape (pdf.fonttype=42, svg.fonttype=none) at 600 dpi.

Claude Code skill

A personal sci-figure skill (~/.claude/skills/sci-figure/) walks Claude through the publication workflow and is auto-invoked on plotting tasks in any project where EasyPlotLib is installed.