siaplotlib 0.2.1

Provide an easy to use interface for plotting oceanographic data.

SIAPLOTLIB

Version: 0.2.1

Python library as part of the SIA project. Its aim is to provide an easy to use interface for plotting oceanic data.

Page of the project: https://sia-information-system.github.io/sia-website

Table of content

• Install
  • Requirements before installation
  • Production mode
  • Development mode
• Tests
• Documentation
• Contributions

Install

Requirements before installation

This package depends on Cartopy v0.21.1, which is a package that in order to be installed by pip needs to have some C/C++ libraries available in the host operating system, which it's not a problem in Linux or MacOS, but it is on Windows. See the Cartopy installation docs to see how to install required dependencies on Linux and MacOS.

If you are on Windows, in order to simplify the installation of this package, we recommend to use the pre-built Cartopy binaries distributed by conda (anaconda/miniconda). Once you have conda, you can install Cartopy with the following command:

conda install cartopy=0.21.1

Before install this package make sure you have the C/C++ library installed on your operating system to build Cartopy, or have the pre-built binaries installed on the environment you are going to use.

Production mode

You can install this package from PyPI using:

pip install siaplotlib

To install the package from source code, clone the repo from GitHub and run the following command in the package root directory (where the pyproject.toml file is located):

pip install .

See local installation for details.

Development mode

NOTE: For development it's recommended to use an isolated environment. You can use tools like anaconda / minionda or virtualenv to create this kind of environments. On Windows, due to the reasons exposed in the Requirements before installation section, we highly recommend to use conda as environments manager. If you are on other operating systen, you don't use conda and you decide to store the environment in the root directory of the project, name the environment as venv since this name of directory is ignored by git.

To install the package in development mode (--editable), run the following command in the package root directory (where de pyproject.toml file is located):

pip install --editable .[dev]

See local installation for details.

To increase the version number, the package bumpver is used. Read the docs to see how to use it.

Tests

Make sure to have the following files used to create the visualizations, you can download them here.

• global-analysis-forecast-phy-001-024-GLOBAL_ANALYSIS_FORECAST_PHY_001_024-TDS-date-2022-11-13-time-10h-31m-10s-857022ms.nc
• global-analysis-forecast-phy-001-024-GLOBAL_ANALYSIS_FORECAST_PHY_001_024-TDS-date-2022-11-13-time-13h-27m-31s-211639ms-monthly.nc
• time-series.png
• heatmap.gif

Once done, place them in tmp/data/.

Make sure to have installed the package, whether in production or development mode.

Then go to the test directory and run the following command to start the testing module:

python test_chart_builders.py

Tests are written with unittest framework, so alternative ways of running the test are described in its documentation.

Documentation

Read the documentation for this package here.

Contributions

Rules are:

• First ask to maintainers if the new proposed feature can be added. You can open an issue on GitHub.
• Document every new feature added.
• Add tests for each new feature.