anu_ctlab_io.netcdf
Read and write data from/to the ANU CTLab netcdf data format.
This is an optional extra module, and must be explicitly installed to be used (e.g., pip install anu_ctlab_io[netcdf]).
Package Contents
- anu_ctlab_io.netcdf.dataset_to_netcdf(dataset, path, datatype=None, dataset_id=None, max_file_size_mb=500.0, compression_level=0, history=None, **extra_attrs)
Write a
Datasetto netcdf format.- Parameters:
dataset (anu_ctlab_io._dataset.Dataset) – The
Datasetto write.path (pathlib.Path | str) – Path to write the netcdf file or directory (if splitting).
datatype (anu_ctlab_io._datatype.DataType | str | None) – Data type identifier. Inferred from dataset if None.
dataset_id (str | None) – Unique dataset identifier. Auto-generated if not provided.
max_file_size_mb (float | None) – Max file size in MB. Data exceeding this is split into multiple files along z-axis. Default 500MB. Set to None for single file.
compression_level (int) – NetCDF compression level (0-9). Default 0 (no compression).
history (anu_ctlab_io._parse_history.History | None) – History entries to add. Keys are identifiers, values are strings or parsed history dicts. If None, uses dataset’s history attribute.
extra_attrs (Any) – Additional global attributes to include.
- Return type:
None
- anu_ctlab_io.netcdf.dataset_from_netcdf(path, *, parse_history=True, **kwargs)
Loads a
Datasetfrom the path to a netcdf.This method is used by
Dataset.from_path, by preference call that constructor directly.- Parameters:
Path – The path to the netcdf or directory of split netcdf blocks to be loaded.
parse_history (bool) – Whether to parse the history of the netcdf file. Defaults to
True, but disableable because the parser is currently not guaranteed to succeed.kwargs (Any) – Currently this method consumes no kwargs, but will pass provided kwargs to
Xarray.open_mfdataset.path (pathlib.Path)
- Raises:
lark.exceptions.UnexpectedInput – Raised if
parse_history=Trueand the parser fails to parse the specific history provided.- Return type:
anu_ctlab_io._dataset.Dataset