A collection of diagnostic and interpolation routines for use with output from the Weather Research and Forecasting (WRF-ARW) Model.
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Installation
============
Required Dependencies
----------------------
- Python 2.7, 3.4, or 3.5
- numpy (1.9 or later)
- wrapt (1.10 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 install -c conda-forge wrf-python
While some bugs are currently being ironed out with the conda-forge
installation, wrf-python is also available at::
$ conda install -c bladwig wrf-python
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>`_.
The source code is available via github:
https://github.com/NCAR/wrf-python
To install, change to the wrf-python directory and run::
$ pip install .
Note that building on Win64 with Python 3.5+ and the mingw-64 compiler
is very difficult, due to incompatibilities with the runtime libraries and
lack of support from numpy's distutils. Improved support for these
configurations, along with numpy distutils support, should take place this
year. But for now, visual studio and the intel compiler may be required.
Otherwise, Python 2.7 or Python 3.4 is recommended.