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https://github.com/spencerkclark/faceted
Figures with precise control over overall width, plot aspect ratio, between-plot spacing, and colorbar dimensions.
https://github.com/spencerkclark/faceted
cartopy colorbars figure-dimensions matplotlib multi-panel-plots
Last synced: about 1 month ago
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Figures with precise control over overall width, plot aspect ratio, between-plot spacing, and colorbar dimensions.
- Host: GitHub
- URL: https://github.com/spencerkclark/faceted
- Owner: spencerkclark
- License: mit
- Created: 2017-11-14T13:39:54.000Z (almost 7 years ago)
- Default Branch: main
- Last Pushed: 2021-12-31T21:35:37.000Z (almost 3 years ago)
- Last Synced: 2024-06-11T16:53:04.422Z (5 months ago)
- Topics: cartopy, colorbars, figure-dimensions, matplotlib, multi-panel-plots
- Language: Python
- Homepage: https://faceted.readthedocs.io
- Size: 2.4 MB
- Stars: 15
- Watchers: 1
- Forks: 1
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-meteo - Faceted
README
faceted
=======
[](https://github.com/spencerkclark/faceted/actions) [](https://codecov.io/gh/spencerkclark/faceted) [](https://faceted.readthedocs.io/en/latest/?badge=latest) [](https://pypi.python.org/pypi/faceted/) [](https://github.com/python/black)
Figures with precise control over overall width, overall height,
plot aspect ratio, between-plot spacing, and colorbar dimensions.
Description
-----------
The purpose of this module is to make it easy to produce single-or-multi-panel
figures in `matplotlib` with strict dimensional constraints. For example,
perhaps you would like to make a figure that fits exactly within a column of a
manuscript *without any scaling*, and you would like the panels to be as large
as possible, but retain a fixed aspect ratio (height divided by width). Maybe
some (or all) of your panels require an accompanying colorbar. With
out of the box `matplotlib` tools this is actually somewhat tricky.
Internally, this module uses the flexible [`matplotlib` `AxesGrid` toolkit](https://matplotlib.org/2.0.2/mpl_toolkits/axes_grid/users/overview.html#axes-grid1),
with some additional logic to enable making these kinds of
dimensionally-constrained
panel plots with precise padding and colorbar size(s).
Another project with a similar motivation is [panel-plots](
https://github.com/ajdawson/panel-plots); however it does not have support
for adding colorbars to a dimensionally-constrained figure. One part of the
implementation there that inspired part of what is done here is the ability
to add user-settable padding to the edges of the figure (to add space for
axes ticks, ticklabels, and labels). This eliminates the need for using
`bbox_inches='tight'` when saving the figure, and enables you
to make sure that your figures are *exactly* the dimensions you need for your use.
I intend to keep the scope of this project quite limited. I want the results it
produces to remain extremely easy to understand and control. For more
complicated figure layouts, e.g. multiple panels with different sizes and
aspect ratios, and a more magical approach to setting figure boundary padding
and between-panel spacing, a library worth checking out is
[proplot](https://github.com/lukelbd/proplot). The ["smart tight layout" feature
it provides](https://proplot.readthedocs.io/en/stable/why.html#id5) is an impressive
automated method of solving some of the same problems addressed by this library.
For information on how to use `faceted`, see the documentation:
https://faceted.readthedocs.io/en/latest/.
Installation
------------
You can install `faceted` either from PyPI:
```
$ pip install faceted
```
or directly from source:
```
$ git clone https://github.com/spencerkclark/faceted.git
$ cd faceted
$ pip install -e .
```