👋 Hi Parflow maintainers! This is my first PR here - I'm Andrew Bennett, working with Laura Condon (@lecondon)& Reed Maxwell (@reedmaxwell) to develop some machine learning emulators of Parflow. In preparing the large datasets to feed the ML algorithms it became a bottleneck to read using the ParflowIO implementation of readers. This pull request implements simple and fast pure-python based readers and writers of PFB files, done by myself and Bill Hasling (@wh3248). This eliminates the need for the external ParflowIO dependency. I have also implemented a new backend for the xarray package that let's you open both .pfb files as well as .pfmetadata files directly into xarray datastructures. These are very useful for data wrangling and scientific analysis. This PR is a merge from my separate repo pf-xarray.

I recognize this is a rather large pull request so I'm happy to meet to discuss the finer points of the implementation. Currently there are some tests, but they are minimal and might be expanded to make sure things interoperate with the rest of the parflow ecosystem. Also, I'm not sure if I should be PRing against master - but I didn't see a staging branch like develop or next. Let me know if this should be changed!

Some basic usage of the new functionality:

import parflow as pf

# Read a pfb file as numpy array:
x = pf.read_pfb('/path/to/file.pfb')

# Read a pfb file as an xarray dataset:
ds = xr.open_dataset('/path/to/file.pfb', name='example')

# Write a pfb file with distfile:
pf.write_pfb('/path/to/new_file.pfb', x, 
             p=p, q=q, r=r, dist=True)