import argparse
import fsspec
import rasterio as rio # noqa
import xarray as xr
from rasterio.warp import calculate_default_transformResampling with Rioxarray (Local storage, NetCDF file, H5NetCDF driver)
def warp_resample(dataset, zoom=0):
from common import earthaccess_args, target_extent
te = target_extent[zoom]
# Define filepath, driver, and variable information
args = earthaccess_args[dataset]
src = f'earthaccess_data/{args["filename"]}'
# Define source and target projection
dstSRS = "EPSG:3857"
srcSRS = "EPSG:4326"
width = height = 256
# Specify fsspec caching since default options don't work well for raster data
fsspec_caching = {
"cache_type": "none",
}
fs = fsspec.filesystem("file")
with fs.open(src, **fsspec_caching) as f:
# Open dataset
da = xr.open_dataset(f, engine="h5netcdf", mask_and_scale=True)[
args["variable"]
]
if dataset == "gpm_imerg":
# Transpose and rename dims to align with rioxarray expectations
da = da.rename({"lon": "x", "lat": "y"}).transpose("time", "y", "x")
# Set input dataset projection
da = da.rio.write_crs(srcSRS)
da = da.rio.clip_box(
*te,
crs=dstSRS,
)
# Define affine transformation from input to output dataset
dst_transform, w, h = calculate_default_transform(
srcSRS,
dstSRS,
da.rio.width,
da.rio.height,
*da.rio.bounds(),
dst_width=width,
dst_height=height,
)
# Reproject dataset
return da.rio.reproject(dstSRS, shape=(h, w), transform=dst_transform)if __name__ == "__main__":
if "get_ipython" in dir():
# Just call warp_resample if running as a Jupyter Notebook
da = warp_resample("gpm_imerg")
else:
# Configure dataset via argpase if running via CLI
parser = argparse.ArgumentParser(description="Set environment for the script.")
parser.add_argument(
"--dataset",
default="mursst",
help="Dataset to resample.",
choices=["gpm_imerg", "mursst"],
)
parser.add_argument(
"--zoom",
default=0,
help="Zoom level for tile extent.",
)
user_args = parser.parse_args()
da = warp_resample(user_args.dataset, int(user_args.zoom))