cool-maps 0.0.3

Helper functions around cartopy for plotting data on maps. These functions are written to easily generate nice-looking maps.

cool_maps

Wrapper functions around the cartopy for plotting data on maps. These functions are written to easily generate maps using some pre-defined settings that our lab, Rutgers Center for Ocean Observing Leadership, prefers to use.

• Free software: MIT license

Features

• TODO

Installation

conda create -n cool_maps python=3.9 conda activate cool_maps conda install –file requirements.txt

Stable release

To install cool_maps, run this command in your terminal:

$ pip install cool_maps

This is the preferred method to install cool_maps, as it will always install the most recent stable release.

If you don’t have pip installed, this Python installation guide can guide you through the process.

We also recommend using miniconda to manage your Python environments. Download and follow the Miniconda installation guide for the appropriate Miniconda installer for your operating system.

Make sure to add the channel, conda-forge, to your .condarc. You can find out more about conda-forge from their website:

You can do this with the following command:

conda config --add channels conda-forge

From sources

The sources for cool_maps can be downloaded from the Github repo.

You can either clone the public repository:

$ git clone git://github.com/rucool/cool_maps

Or download the tarball:

$ curl -OJL https://github.com/rucool/cool_maps/tarball/master

Once you have a copy of the source, you can should create a new conda/virtual environment following the Installation instructions above.

Running tests

After setting up your environment, you can run all of the tests, provided you install ‘pytest’:

$ pytest

Credits

This package was created with Cookiecutter and the conda/cookiecutter-conda-python project template.

History

0.0.2 (2022-07-19)

• Modified requirements.txt to use a lower version of cartopy that is faster.

0.0.1 (2022-05-20)

• Initial commit to GitHub