figrecipe 0.11.0

Reproducible matplotlib wrapper with mm-precision layouts

FigRecipe

Reproducible scientific figures as first-class objects

FigRecipe is a framework for creating reproducible, editable, and publication-ready scientific figures.

Instead of treating figures as static images, FigRecipe treats them as structured objects — with explicit data, layout, and style — that can be reproduced, edited, and shared.

Part of SciTeX™.

Why FigRecipe?

Most scientific figures are created by code, but cannot be reproduced once the code is lost or modified.

FigRecipe solves this by separating:

• What is plotted (data & semantics)
• How it is styled (layout, colors, typography)
• How it is edited (GUI or code)

This makes figures: reproducible · inspectable · editable after publication

Quick Start

pip install figrecipe

import figrecipe as fr
import numpy as np

fig, ax = fr.subplots()
ax.plot(np.sin(np.linspace(0, 10, 100)), id="sine")

fr.save(fig, "figure.png")  # → figure.png + figure.yaml

Reopen and edit later:

fig, ax = fr.load("figure.png")
fr.edit(fig)  # Launch GUI editor

CLI:

figrecipe edit figure.png      # Launch GUI editor
figrecipe reproduce fig.yaml   # Recreate figure
figrecipe extract fig.yaml     # Extract plotted data

What Makes FigRecipe Different?

🔹 Figures are first-class objects — Figures are not just images — they are structured, versionable artifacts.

🔹 Declarative, not imperative — You describe what the figure is, not just how to draw it.

🔹 GUI + Code coexist — The GUI is a frontend, not a black box. Everything is backed by a reproducible spec.

🔹 Millimeter-precise layout — Designed for journal figures, not dashboards.

Core Features

• Drop-in replacement for matplotlib.pyplot
• Fully reproducible figure recipes (.yaml)
• Publication-ready millimeter layout
• Interactive GUI editor
• Dark / light themes
• Works with existing matplotlib code

Save / Load Formats

fr.save(fig, "fig.png")     # fig.png + fig.yaml
fr.save(fig, "bundle/")     # directory bundle
fr.save(fig, "fig.zip")     # zip bundle

fr.load("fig.png")
fr.load("bundle/")
fr.load("fig.zip")

Format	Save	Load
PNG / PDF / SVG	✓	✓
YAML	✓	✓
Directory / ZIP	✓	✓

Style Presets

fr.list_presets()
fr.load_style("SCITEX")
fr.load_style("SCITEX_DARK")

Millimeter-based Layout

fig, ax = fr.subplots(
    axes_width_mm=60,
    axes_height_mm=40,
    margin_left_mm=15,
)

Figure Captions

fig.set_caption("Main figure description")
ax.set_caption("Panel A description")

Who Is This For?

FigRecipe is designed for researchers who:

• already use matplotlib or seaborn
• care about reproducibility and traceability
• want figures that survive revisions and collaboration
• are tired of re-writing plotting code

It is not meant to replace exploratory notebooks or quick plotting — it is meant to formalize results.

Philosophy

A scientific figure is not an image. It is a structured representation of knowledge.

FigRecipe treats figures as first-class scientific objects.

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AGPL-3.0 · [e-mail]