ldcpy 0.5

A library for lossy compression of netCDF files using xarray

Lossy Data Compression for Python

ldcpy is a utility for gathering and plotting metrics from NetCDF or Zarr files using the Pangeo stack. It also contains a number of statistical and visual tools for gathering metrics and comparing Earth System Model data files.

Documentation and usage examples are available here.

Installation using Conda (recommended)

Ensure conda is up to date and create a clean Python (3.6+) environment:

conda update conda
conda create --name ldcpy python=3.8
conda activate ldcpy

Now install ldcpy:

conda install -c conda-forge ldcpy

Alternative Installation

Ensure pip is up to date, and your version of python is at least 3.6:

pip install --upgrade pip
python --version

Install cartopy using the instructions provided at https://scitools.org.uk/cartopy/docs/latest/installing.html.

Then install ldcpy:

pip install ldcpy

Accessing the tutorial

If you want access to the tutorial notebook, clone the repository (this will create a local repository in the current directory):

git clone https://github.com/NCAR/ldcpy.git

Start by enabling Hinterland for code completion and code hinting in Jupyter Notebook and then opening the tutorial notebook:

jupyter nbextension enable hinterland/hinterland
jupyter notebook

The tutorial notebook can be found in docs/source/notebooks/SampleNotebook.ipynb, feel free to gather your own metrics or create your own plots in this notebook!