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Installation

Required Dependencies

  • Python 2.7, 3.4, or 3.5+
  • 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:

conda install -c 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 related modules via the 'module load' command. The packages installed by the 'module load' system will 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 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:

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

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.

The source code is available via 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 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:

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