Add xarray backends for fgmax and fgout gridded formats

examples/tsunami/chile2010_fgmax-fgout/use_xarray_backends.py

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+import glob
+
+try:
+    import rioxarray
+    import xarray as xr
+except:
+    "You must install xarray and rioxarray in order to use the xarray backends"
+    raise
+
+from clawpack.geoclaw.xarray_backends import FGMaxBackend, FGOutBackend
+
+# epsg code for lat-lon
+# Optionally, provide an epsg code to assign the associated coordinate system to the file.
+# default behavior assigns no coordinate system. Note that if no coordinate system is provided,
+# it will come in a GIS with coordinates associated with row and column number (not the x and y position
+# encoded in the netcdf).
+
+epsg_code = 4326
+
+# An example of a fgout grid.
+filename = "_output/fgout0001.b0001"
+# provide the .bxxx file if binary format is used or the
+# .qxxx file if ascii format is used.
+# the format, fg number, and frame number are inferred from the filename.
+
+ds = xr.open_dataset(
+    filename, engine=FGOutBackend, backend_kwargs={"epsg": epsg_code, "qmap": "geoclaw"}
+)
+# ds is now an xarray object. It can be interacted with directly or written to netcdf using
+ds.to_netcdf("fgout0001_0001.nc")
+
+# It is possible to combine all fgout files into a single netcdf file
+# using xr.open_mfdataset
+# https://docs.xarray.dev/en/stable/generated/xarray.open_mfdataset.html
+fgout_files = glob.glob("_output/fgout0001.b*")
+ds_all = xr.open_mfdataset(
+    fgout_files,
+    engine=FGOutBackend,
+    backend_kwargs={"epsg": epsg_code, "qmap": "geoclaw"},
+)
+
+print(ds_all)
+ds_all.to_netcdf("fgout_all.nc")
+
+# An example of a fgmax grid.
+filename = "_output/fgmax0001.txt"
+ds = xr.open_dataset(filename, engine=FGMaxBackend, backend_kwargs={"epsg": epsg_code})
+ds.to_netcdf("fgmax0001.nc")
+
+# To see the use of clipping, change the tfinal in setrun to something like 2*3600.0
+# the fgmax0001_clipped.nc will only be the area where the wave arrived within the considered time.
+filename = "_output/fgmax0001.txt"
+ds = xr.open_dataset(
+    filename, engine=FGMaxBackend, backend_kwargs={"epsg": epsg_code, "clip": True}
+)
+ds.to_netcdf("fgmax0001_clipped.nc")