Skip to main content

Precisely spaced subplots

Project 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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

faceted-0.1-py2.py3-none-any.whl (7.0 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file faceted-0.1-py2.py3-none-any.whl.

File metadata

  • Download URL: faceted-0.1-py2.py3-none-any.whl
  • Upload date:
  • Size: 7.0 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.6.7

File hashes

Hashes for faceted-0.1-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 42e75ccf80b73a40b8fb4e10f76a603eca00491438265182878ab30db0f465e5
MD5 1dce39c289f1b6746f225692f4570d13
BLAKE2b-256 375caa10116a87359d0e6fd11ee7c1bf8e79f35792c20572be0914f2acc1694d

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page