jplotlib

Problem

Some research notebooks need to look at dozens of generated or intermediate images at once: sampled tensors, model outputs, augmentation checks, or quick visual sanity tests. Rewriting the same matplotlib grid boilerplate every time was annoying enough that I packaged the pattern.

This was not meant to be a serious visualization framework. It was a small convenience library for a few research workflows.

Solution

jplotlib exposes a single main helper, GridPlot, for collecting images and displaying them as a compact matplotlib grid.

import numpy as np
import jplotlib as jpl

with jpl.GridPlot(width=20) as grid_plot:
    for _ in range(50):
        grid_plot.imshow(np.random.uniform(size=(100, 100, 3)))

The context manager keeps notebook code terse: append images as they are produced, then render the grid when the block exits.

How

• Stack: Python, matplotlib, setuptools.
• Core API: GridPlot(ncols=10, width=10).
• Behavior: collect images through imshow, compute rows from image count, call plt.subplots, hide axes, and display each image tile.
• Distribution: packaged as jplotlib; installable with pip install jplotlib.

Results

The library did what it needed to do for quick image inspection in a few research works. It made exploratory notebooks a little cleaner, especially when comparing many candidate outputs side by side.

The repo is now archived, which is the right status for it. Once I became more comfortable with plt.subplots, the package stopped needing to exist as an active dependency.

Lessons

The useful part was not abstraction for its own sake; it was capturing a repeated notebook gesture while I was still moving quickly through experiments. In hindsight, the project is a good reminder that some tools are allowed to be temporary: they solve a local friction, teach the underlying library, and then get retired.