ldcpy 0.8

A library for lossy compression of netCDF files using xarray

Large Data Comparison 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.

AUTHORS:

Alex Pinard, Allison Baker, Dorit Hammerling

COPYRIGHT:

2020 University Corporation for Atmospheric Research

LICENSE:

Apache 2.0

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!