plottify

The plottify package is makes matplotlib plots more legible. It's a thin wrapper around matplotlib that automatically adjusts font sizes, scatter point sizes, line widths, etc. according to the figure size.

Installation

pip install plottify

Usage

The plottify interface is extremely simple and relies on one central function, autosize(). After you've created a plot, simply call autosize() and the sizes will be adjusted:

from plottify import autosize
import matplotlib.pyplot as plt

plt.scatter(x, y)
autosize()
plt.show()

If you have a matplotlib figure object, you can pass it as an argument to autosize:

autosize(fig)

Demonstration

By default, matplotlib sets the sizes of these objects to pre-specified values, regardless of the figure size. This can result in tiny fonts or sizes for larger figures:

Plottify's autosize function adjusts these sizes automatically to make them more legible:

When we change the figure size, plottify automatically adjusts the objects' sizes:

Bugs and feature requests

Please report any bugs or feature requests as a GitHub issue.

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Comments

packaging improvements
Content:

cleanup uncecessary import

cleanup repo clog

add a top level .gitignore file

migrate and complete install metadata from setup.py to setup.cfg

add a badge to your README that link to PyPI

Notes: it is good practice to specify the minimal Python version you want to support in setup.cfg (or setup.py, I'm defaulting to setup.cfg because there are tools to help keep it tidy). I don't know what that version should be for this package, so I guessed 3.6, but feel free to edit this value.
opened by neutrinoceros 1

Feature request: use with subplots

autosize() is simply magical! But I am struggling to get it working with plt.subplots in matplotlib.

My script goes like:

fig, axis = plt.subplots(figsize=(6,6), ncols=4, nrows=4)
for i in range(0, 4):
            for j in range(0, 4):
            # a class that makes plots in certain axis:
           gec.PlotClsHDP(i, j, ax=axis[i,j], **kwargs)
autosize(fig)
plt.show()

but the result is the following: Screenshot 2022-01-19 at 18 21 20