gsplot

gsplot creates publication-quality scientific figures with a concise API on top of Matplotlib. It provides paper-aware layouts, plotting and styling helpers, validated immutable configuration, and opt-in metadata writing while returning native Matplotlib objects.

Warning

gsplot is still beta software. APIs and defaults may change between releases. Please report reproducible bugs through the GitHub issue tracker.

Highlights

• create multi-panel figures with Matplotlib-compatible Axes objects;

• load explicit, immutable defaults from a schema-versioned gsplot.json;

• add lines, scatter plots, legends, labels, ticks, and scientific styles;

• save and display one explicitly owned Figure at a time.

Example

The documentation build executes the source below and displays the PNG generated by that same run.

import numpy as np

import gsplot as gs

x = np.linspace(0, 2 * np.pi, 41)
fig, ax = gs.subplots("AB", size=(7, 3))
gs.line(ax["A"], x, np.sin(x), label=r"$\sin(x)$")
gs.scatter(ax["B"], x[::2], np.cos(x[::2]), label=r"$\cos(x)$", s=15)
gs.label(
    ax,
    ((r"$x$", r"$\sin(x)$"), (r"$x$", r"$\cos(x)$")),
    square=True,
    index="in",
)
gs.legend(ax)
gs.save(fig, "line_and_label.png", show=False, close=True)

Start with Getting started, follow the publication guide, browse the examples, or use the API reference.