Getting Started#
Prerequisites#
Familiarity with
xarray
, since this package is an extension of itWe highly recommend visiting the xarray tutorial and xarray documentation pages if you aren’t familiar with
xarray
.
xCDAT is distributed through conda, which is available through Anaconda and Miniconda.
We recommend following these steps to install Miniconda:
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh bash Miniconda3-latest-Linux-x86_64.sh
Then follow the instructions for installation. To have conda added to your path you will need to type
yes
in response to"Do you wish the installer to initialize Miniconda3 by running conda init?"
(we recommend that you do this). Note that this will modify your shell profile (e.g.,~/.bashrc
) to addconda
to your path.Note: After installation completes you may need to type
bash
to restart your shell (if you use bash). Alternatively, you can log out and log back in.
Installation#
Create a conda environment from scratch with
xcdat
(conda create)We recommend using the Conda environment creation procedure to install
xcdat
. The advantage with following this approach is that Conda will attempt to resolve dependencies (e.g.python >= 3.8
) for compatibility.To create an
xcdat
conda environment withxesmf
(a recommended dependency), run:>>> conda create -n <ENV_NAME> -c conda-forge xcdat xesmf >>> conda activate <ENV_NAME>
Note that
xesmf
is an optional dependency, which is required for usingxesmf
based horizontal regridding APIs inxcdat
.xesmf
is not currently supported on osx-arm64 or windows becauseesmpy
is not yet available on these platforms. Windows users can try WSL2 as a workaround.
Install
xcdat
in an existing conda environment (conda install)You can also install
xcdat
in an existing Conda environment, granted that Conda is able to resolve the compatible dependencies.>>> conda activate <ENV_NAME> >>> conda install -c conda-forge xcdat xesmf
Note: As above,
xesmf
is an optional dependency.[Optional] Some packages that are commonly used with
xcdat
can be installed either in step 1 or step 2 above:jupyterlab
: a web-based interactive development environment for notebooks, code, and data. This package also includesipykernel
.matplotlib
: a library for creating visualizations in Python.cartopy
: an add-on package formatplotlib
and specialized for geospatial data processing.