A small utility to compute the squarest pair of divisors for an integer.
Project description
# squarest-divisors
A small utility to compute the squarest pair of divisors for an integer.
# Installation
Install from PyPI:
```
$ pip install sqdiv
```
# Usage
The original intended usage is with `matplotlib`, to automatically figure out how many rows and columns are needed based on the number of subplots I actually need to plot.
Let's say I had a series of 11 things I needed to plot on a `matplotlib` figure, something akin to a [`seaborn.FacetGrid`](https://seaborn.pydata.org/generated/seaborn.FacetGrid.html), but with some custom things added.
```python
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec
from sqdiv import n_rows_cols
height = 3
nrows, ncols = n_rows_cols(len(labels)) # len(labels) == 11
fig = plt.figure(figsize=(ncols * height, nrows * height))
gs = GridSpec(nrows=nrows, ncols=ncols)
# Now, setup the axes to plot on.
axes = dict()
for i, c in enumerate(labels):
# This allows us to share axes across the plots.
if i != 0:
axes[c] = fig.add_subplot(gs[i], sharey=axes[labels[0]])
else:
axes[c] = fig.add_subplot(gs[i])
axes[c].set_title(f'{c}')
axes[c].set_xlabel('x')
axes[c].set_ylabel('y')
# Below here, plot to your heart's content on each axes object.
```
The trivial case (1 by number of items) is not provided as part of the functionality because, hey, it's trivial!
# Feature Requests
Contributions are welcome. If you'd like to submit something, let's discuss on the [GitHub Issues tracker](https://github.com/ericmjl/squarest-divisors/issues) first.
Because `sqdiv` is currently maintained by volunteers and has no fiscal support, any feature requests will be prioritized according to what maintainers encounter as a need in our day-to-day jobs. Please temper expectations accordingly.
A small utility to compute the squarest pair of divisors for an integer.
# Installation
Install from PyPI:
```
$ pip install sqdiv
```
# Usage
The original intended usage is with `matplotlib`, to automatically figure out how many rows and columns are needed based on the number of subplots I actually need to plot.
Let's say I had a series of 11 things I needed to plot on a `matplotlib` figure, something akin to a [`seaborn.FacetGrid`](https://seaborn.pydata.org/generated/seaborn.FacetGrid.html), but with some custom things added.
```python
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec
from sqdiv import n_rows_cols
height = 3
nrows, ncols = n_rows_cols(len(labels)) # len(labels) == 11
fig = plt.figure(figsize=(ncols * height, nrows * height))
gs = GridSpec(nrows=nrows, ncols=ncols)
# Now, setup the axes to plot on.
axes = dict()
for i, c in enumerate(labels):
# This allows us to share axes across the plots.
if i != 0:
axes[c] = fig.add_subplot(gs[i], sharey=axes[labels[0]])
else:
axes[c] = fig.add_subplot(gs[i])
axes[c].set_title(f'{c}')
axes[c].set_xlabel('x')
axes[c].set_ylabel('y')
# Below here, plot to your heart's content on each axes object.
```
The trivial case (1 by number of items) is not provided as part of the functionality because, hey, it's trivial!
# Feature Requests
Contributions are welcome. If you'd like to submit something, let's discuss on the [GitHub Issues tracker](https://github.com/ericmjl/squarest-divisors/issues) first.
Because `sqdiv` is currently maintained by volunteers and has no fiscal support, any feature requests will be prioritized according to what maintainers encounter as a need in our day-to-day jobs. Please temper expectations accordingly.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
sqdiv-0.1.tar.gz
(2.7 kB
view hashes)
Built Distribution
sqdiv-0.1-py3-none-any.whl
(2.6 kB
view hashes)