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Installation docs updates #306

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update README
kafitzgerald Dec 31, 2025
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first round of install docs updates
kafitzgerald Dec 31, 2025
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update install docs
kafitzgerald Dec 31, 2025
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15 changes: 5 additions & 10 deletions README.md
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Expand Up @@ -9,26 +9,21 @@ This package provides over 30 diagnostic calculations, several interpolation rou
Installation
----------------------------

conda install -c conda-forge wrf-python
conda install conda-forge::wrf-python

Documentation
----------------------------------

http://wrf-python.rtfd.org
https://wrf-python.readthedocs.io


Citation
------------------

If you use this software, please cite it as described at the [WRF-Python - Citation](
https://wrf-python.readthedocs.io/en/latest/citation.html) page.
If you use this software, please cite it as described in the [documentation](
https://wrf-python.readthedocs.io/en/latest/citation.html).


--------------------

*The National Center for Atmospheric Research is sponsored by the National
Science Foundation. Any opinions, findings and conclusions or recommendations
expressed in this material do not necessarily reflect the views of the
National Science Foundation.*


*This material is based upon work supported by the NSF National Center for Atmospheric Research, a major facility sponsored by the U.S. National Science Foundation and managed by the University Corporation for Atmospheric Research. Any opinions, findings and conclusions or recommendations expressed in this material do not necessarily reflect the views of the U.S. National Science Foundation.*
123 changes: 15 additions & 108 deletions doc/source/installation.rst
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Installation
============

Required Dependencies
----------------------

- Python 3.9+
- numpy (1.11 or later; 1.14 required to build on Windows)
- wrapt (1.10 or later)
- setuptools (38.0 or later)


Highly Recommended Packages
----------------------------

- xarray (0.7.0 or later)
- PyNIO (1.4.3 or later)
- netCDF4-python (1.2.0 or later)


Plotting Packages
-------------------------

- PyNGL (1.4.3 or later)
- matplotlib (1.4.3 or later)
- cartopy (0.13 or later)
- basemap (1.0.8 or later)


Installing via Conda
---------------------

The easiest way to install wrf-python is using
`Conda <http://conda.pydata.org/docs/>`_::
`Conda <https://docs.conda.io>`_::

conda install -c conda-forge wrf-python
conda install conda-forge::wrf-python

.. note::

If you use conda to install wrf-python on a supercomputer like
Yellowstone or Cheyenne, we recommend that you do not load any python
If you use Conda to install WRF-Python on a supercomputer like
Derecho or Casper, we recommend that you do not load any Python
related modules via the 'module load' command. The packages installed
by the 'module load' system will not play nicely with packages installed
via conda.
by the 'module load' system may not play nicely with packages installed
via Conda.

Further, some systems will install python packages to a ~/.local directory,
which will be found by the miniconda python interpreter and cause various
Further, some systems will install Python packages to a ~/.local directory,
which will be found by the Conda Python interpreter and cause various
import problems. If you have a ~/.local directory, we strongly suggest
renaming it (mv ~/.local ~/.local_backup).


Installing on Yellowstone
----------------------------

On Yellowstone, wrf-python can also be installed using the module load system,
if this is preferred over using conda.

Unfortunately, because wrf-python requires newer dependencies, it is not
available using the 'all-python-libs' module, so many of the dependencies
need to be manually installed (most are for xarray).

Also, make sure you are running in the gnu/4.8.2 compiler environment or
you will get import errors for a missing libquadmath library when you
go to import wrf-python.

To install::
WRF-Python on NSF NCAR HPC
--------------------------

module load gnu/4.8.2 or module swap intel gnu/4.8.2
module load python/2.7.7
module load numpy/1.11.0 wrapt/1.10.10 scipy/0.17.1 bottleneck/1.1.0 numexpr/2.6.0 pyside/1.1.2 matplotlib/1.5.1 pandas/0.18.1 netcdf4python/1.2.4 xarray/0.8.2
module load wrf-python/1.0.1
WRF-Python is included in the `NCAR Python Library <https://ncar-hpc-docs.readthedocs.io/en/latest/environment-and-software/user-environment/package-managers/conda/#the-ncar-python-library>`_ on the NSF NCAR HPC systems or can be installed using a supported package manager of your choice.


Installing via Source Code
--------------------------

Installation via source code will require a Fortran and C compiler in order
to run f2py. You can get them
`here <https://gcc.gnu.org/wiki/GFortranBinaries>`_.
to run F2PY.

The source code is available via github:
The source code is available on GitHub:

https://github.com/NCAR/wrf-python

Or PyPI:

https://pypi.python.org/pypi/wrf-python

To install, if you do not need OpenMP support, change your working directory
To install, change your working directory
to the wrf-python source directory and run::

$ pip install .

Beginning with wrf-python 1.1, OpenMP is supported, but preprocessing the
ompgen.F90 file is required, which also requires running f2py to
build the .pyf file. To simplify this process, you can use the build scripts in
the *build_scripts* directory as a guide, or just call the script directly.

Below is a sample from a build script for GNU compiler with OpenMP enabled:

.. code-block:: none

cd ../fortran/build_help

gfortran -o sizes -fopenmp omp_sizes.f90

python sub_sizes.py

cd ..

gfortran -E ompgen.F90 -fopenmp -cpp -o omp.f90

f2py *.f90 -m _wrffortran -h wrffortran.pyf --overwrite-signature

cd ..

python setup.py clean --all

python setup.py config_fc --f90flags="-mtune=generic -fopenmp" build_ext --libraries="gomp" build

pip install .

Beginning with numpy 1.14, f2py extensions can now be built using the MSVC
compiler and mingw gfortran compiler. Numpy 1.14 is required to build
wrf-python for Python 3.5+.

.. note::

If you are building on a supercomputer and receiving linker related
errors (e.g. missing symbols, undefined references, etc), you probably
need to unset the LDFLAGS environment variable. System administrators on
supercomputing systems often define LDFLAGS for you so that you don't need
to worry about where libraries like NetCDF are installed. Unfortunately,
this can cause problems with the numpy.distutils build system. To fix,
using the build command from above::

$ unset LDFLAGS python setup.py config_fc --f90flags="-mtune=generic -fopenmp" build_ext --libraries="gomp" build



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