Nothing much yet.
TODO:
- dask chunks
- interface for classic vs mdim, and helpers
- indicators for presence of subdatasets, mdim-capability, driver recognition, GCPs/RCPs, geolocation arrays
Rinse and repeat, it's nowhere near working yet but I'm better at learning. Leaning heavily on rioxarray and the new backends doc.
p <- c("polars", "h5netcdf", "fsspec", "aiohttp", "requests", "xarray", "dask", "gdal"); reticulate::py_require(p); system("python3 -m pip install ."); reticulate::repl_python();
dsn0 = "vrt:///vsicurl/https://s3.ap-southeast-2.amazonaws.com/ausseabed-public-warehouse-bathymetry/L3/6009f454-290d-4c9a-a43d-00b254681696/Australian_Bathymetry_and_Topography_2023_250m_MSL_cog.tif?outsize=12,0"
dsn2 = "vrt:///vsicurl/https://projects.pawsey.org.au/idea-10.7289-v5sq8xb5/www.ncei.noaa.gov/data/sea-surface-temperature-optimum-interpolation/v2.1/access/avhrr/198109/oisst-avhrr-v02r01.19810901.nc?sd_name=sst"
dsn1 = "vrt:///vsicurl/https://s3.ap-southeast-2.amazonaws.com/ausseabed-public-warehouse-bathymetry/L3/6009f454-290d-4c9a-a43d-00b254681696/Australian_Bathymetry_and_Topography_2023_250m_MSL_cog.tif?outsize=12,0"
import gdx
be = gdx.gdx.GDALBackendEntryPoint()
be.open_dataset(dsn1)Please note that the gdx project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.