The eriplots library for Python makes it a little easier to create clean, client-ready figures, inspired by Trees, maps, and theorems among others.

The best way to install or use the library is directly from GitHub:

# pip
pip install git+https://github.com/ElderResearch/eriplots-python.git

# uv
uv add git+https://github.com/ElderResearch/eriplots-python.git

The library's utilities are organized along four directions:

1. Simple plot styles, with "profiles" for papers and slides
2. A streamlined subplots() workflow
3. Multi-format figure saving with automatic PNG compression
4. ERI-branded color palettes and colormaps

The eriplots library provides a simple, customizable matplotlib style via eri_style() that supports two "profiles" for common scenarios:

1. document: 10 pt base type, 4.5 in × 2.5 in figure at 300 DPI
2. presentation: 18 pt base type, 7 in × 4 in figure at 300 DPI

Both profiles apply a clean style with consistent spacing, reduced visual noise, and harmonically-scaled text elements.

import matplotlib.pyplot as plt
import eriplots as ep

# Document and Presentation profiles
plt.style.use(ep.eri_style(profile="document"))
plt.style.use(ep.eri_style(profile="presentation"))

# Further customizations
plt.style.use(ep.eri_style(base_size=12, base_family="serif"))

# Use in a context
with plt.style.context(ep.eri_style()):
    ...

The library also simplifies the fig, ax = plt.subplots() workflow, making it easier to set options directly in the function call.

import eriplots as ep

# All subplots have a given aspect, provided as a flat array
fig, axes = ep.subplots(nrows=3, ncols=5, aspect=0.618, flatten=True)

The eriplots library provides a save_figures() function that automatically store raster (PNG) and vector (PDF) copies of the figure by default. When available, optipng is applied to any created PNGs.

import eriplots as ep

# By default: "plot.png", "plot.pdf"
ep.save_figures(fig, "plot")

# Specify the formats: "plot.png"
ep.save_figures(fig, "plot", formats="png")

# Request WebP (requires Pillow with WebP support)
ep.save_figures(fig, "plot", formats=("pdf", "webp"))

# Disable PNG optimization
ep.save_figures(fig, "plot", optipng=False)

WebP support comes from Pillow; install with pip install "eriplots[webp]" (or pip install pillow) in an environment that has WebP codecs (e.g., libwebp) available.

Finally, the eriplots library provides an enumeration over colors related to ERI's branding with accompanying discrete and continuous color maps.

import eriplots as ep

# Individual colors
print(ep.colors.mediumblue)  # "#005E7B"
print(ep.colors.darkred)     # "#D0073A"

# Colormaps
import matplotlib.pyplot as plt
plt.imshow(data, cmap="eri_colors")  # Discrete colormap
plt.imshow(data, cmap="eri_red_cyan")  # Continuous colormap

We welcome contributions, both by raising issues and submitting pull requests!

The eriplots library is licensed under the MIT license (LICENSE.md or https://opensource.org/license/MIT).