Hedgehogs

Scientific figures and reports for Python.

Hedgehogs prepares Matplotlib figures and presents tables, progress and status messages in notebooks and terminals.

• Journal-oriented figure presets for single- and double-column layouts.
• Colour-blind-friendly palettes, including Okabe–Ito and Paul Tol schemes.
• Consistent figure dimensions across local and remote notebook display and export.
• Clear tables, status messages and progress bars in notebooks, terminals and redirected logs.

Installation

Requires Python 3.10+. Install from a source checkout:

git clone https://github.com/PentagonToy/Hedgehogs.git
cd Hedgehogs
python -m pip install -e .

Usage Example

Figures

Choose the journal dimensions first, then draw with Matplotlib. The style supplies typography, line widths, marker sizes and outlines; finishing measures the complete figure and adjusts supported legend and bar-label placement.

import numpy as np
import matplotlib.pyplot as plt
import hedgehogs as hdg

fig_x, fig_y = hdg.figsize(name="science", column="single")
palette = hdg.get_palette("okabe-ito")
hdg.set_style(figure_size=(fig_x, fig_y), palette="okabe-ito")

x = np.linspace(0, 1, 25)
y = 2 * x + 0.1 * np.sin(20 * x)
fitted = np.polyval(np.polyfit(x, y, 1), x)

fig, ax = plt.subplots(figsize=(fig_x, fig_y))
ax.scatter(x, y, color=palette["blue"], label="Data")
ax.plot(x, fitted, color=palette["black"], label="Linear fit")
ax.set(xlabel="x", ylabel="y")
ax.legend()

hdg.plots.save("linear_fit.pdf", bbox_inches=None)
hdg.plots.show()

figsize() returns width and height in inches for science, nature, ieee or aps, with single or double columns. Presets provide starting dimensions; check the target journal's author instructions. Use an extensionless path with formats=("pdf", "png") for multiple outputs. Matplotlib arguments and artist properties remain editable.

Tree diagrams and pairplots also return editable Matplotlib objects. Keep text readable at the final document width; select fewer variables or split crowded figures before reducing font size.

Tables

Display the same table in a notebook or terminal, then export its formatted values to CSV and LaTeX.

table = hdg.Table("Model comparison", columns=["Case", "RMSE"], formatters={"RMSE": ".3f"})
table.add_row("baseline", 0.0412)
table.add_row("model", 0.0184)
table.show()
table.to_csv("errors.csv")
table.to_latex("errors.tex", caption="Model errors", label="tab:errors")

Table.from_dataframe() accepts existing pandas and Polars DataFrames. The LaTeX output requires booktabs. Tables or accompanying data provide precise values; figures communicate patterns and comparisons.

Progress

Wrap an iterable with Progress to report progress in notebooks, terminals and redirected logs.

import time

for step in hdg.Progress(range(20), desc="Processing"):
    time.sleep(0.05)

For manually advanced work, Progress supports update(), metric reporting through set() and a context manager. See the progress reference.

Terminal output

hdg.echo("Reading data", tone="info")
hdg.echo("Run completed", tone="success")
hdg.rule("Summary")

Terminal output includes colour where supported. Redirected output remains plain; NO_COLOR and TERM=dumb disable colour.

Documentation and tutorials

Use the documentation roadmap for guides, API references and developer documentation. Runnable tutorials cover plots, tables, and CLI output.

Existing Onsaemiro code can replace its import with import hedgehogs as hdg. Wrap iterable work with hdg.Progress(iterable, ...) and use the standard time.sleep() for delays.