Usage
python -m uclales_zarr.cli [source_data_path] [experiment_name] --data-kind [3d,xy,xz,yz]
This will write combined json-file that can be opened as zarr archive with in
path {source_file_path}__zarr/{experiment_name}.json
. Because UCLALES writes
files in NetCDF3 format each source file will be convered to NetCDF4 (written
to {source_file_path}__zarr/nc4
).
This can then be loaded in python with
import uclales_zarr
source_file_path = "{change this}" # e.g. `/nfs/data/rico_raw_gcss`
experiment_name = "{change this}" # e.g. `rico_gcss`
data_kind = "{change this}" # e.g. `3d`
ds = uclales_zarr.load(src_fp=source_file_path, exp_name=exp_name, data_kind=data_kind)
# `ds` is now a regular xr.Dataset you can use to access the full simulation
# data as if it is a single file
-
creation of individual json-files for 3D source files, NB: on fields at cell centers have correct coordinate (x, y, z) values for now. The staggered variables (velocities) need to be treated separately
-
support for creating coordinate values for staggered fields (velocities)
-
support for 2D cross-section fields
-
try natively using NetCDF3 rather than converting, this appears to be possible now with
ffspec
0.0.7
(fsspec/kerchunk#190) although there might be degradation in access speeds.