Getting started with LENAPY

Lenapy is a Python library designed to facilitate the processing and analysis of geophysical and climate datasets, such as those used in oceanography, geodesy, and Earth observation in general. Built on top of xarray and compatible with dask, it enables scalable workflows on multidimensional datasets using community standards for data formats (NetCDF) and metadata conventions (CF).

A key feature of lenapy is its ability to produce consistent computations of the Global Mean Sea Level components from various data sources, including satellite altimetry, GRACE/GRACE-FO, thermo-steric datasets, and climate model outputs.

Documentation

Documentation can be found at https://lenapy.readthedocs.io/en/latest/.

Installation

Step 1: Install Conda

To use Conda packages like lenapy, you first need to install Miniconda or Anaconda. Miniconda is a lightweight option, while Anaconda includes many preinstalled data science packages.

To install Miniconda (recommended for minimal setup):

1. Go to the Miniconda download page.
2. Download the installer for your operating system (Windows, macOS, or Linux).
3. Run the installer and follow the prompts. Make sure to:
   • Add Conda to your system’s PATH (if asked).
   • Allow the installer to initialize Conda automatically.

After installation, open a terminal (or Anaconda Prompt on Windows) and verify that Conda is installed by running:

conda --version

Step 2: Install lenapy Using Conda

Once Conda is installed, you can install lenapy by following these steps:

1. Create a new Conda environment (recommended):

conda create -n lenapy_env python=3.11

2. Activate the environment:

conda activate lenapy_env

3. Install lenapy:

conda install -c conda-forge lenapy

This installs lenapy and its dependencies from the conda-forge channel.

Use

In your python code, simply import the library with ::

import lenapy

You can now use all the functionalities of lenapy by adding the right suffix after your Dataset or DataArray ::

import xarray as xr
import lenapy
ds = lenapy.utils.geo.rename_data(xr.tutorial.open_dataset('air_temperature'))
ds.air.lngeo.mean(['latitude','longitude'],weights=['latitude']).lntime.climato().plot()

More complete notebooks tutorials and functions descriptions can be found in the documentation.

Notebooks tutorials

Functions reference

Contributing

We welcome contributions to lenapy!

Guidelines: https://lenapy.readthedocs.io/en/latest/contributing.html