clouddrift.adapters.gdp6h

This module provides functions and metadata that can be used to convert the 6-hourly Global Drifter Program (GDP) data to a clouddrift.RaggedArray instance.

Functions

download(url, tmp_path[, drifter_ids, ...])	Download individual NetCDF files from the AOML server.
preprocess(index, **kwargs)	Extract and preprocess the Lagrangian data and attributes.
to_raggedarray([drifter_ids, n_random_id, ...])	Download and process individual GDP 6-hourly files and return a RaggedArray instance with the data.

clouddrift.adapters.gdp6h.download(url: str, tmp_path: str, drifter_ids: list | None = None, n_random_id: int | None = None)

Download individual NetCDF files from the AOML server.

Parameters

drifter_idslist

List of drifter to retrieve (Default: all)

n_random_idint

Randomly select n_random_id drifter IDs to download (Default: None)

urlstr

URL from which to download the data (Default: GDP_DATA_URL). Alternatively, it can be GDP_DATA_URL_EXPERIMENTAL.

tmp_pathstr, optional

Path to the directory where the individual NetCDF files are stored (default varies depending on operating system; /tmp/clouddrift/gdp6h on Linux)

Returns

outlist

List of retrieved drifters

clouddrift.adapters.gdp6h.preprocess(index: int, **kwargs) → Dataset

Extract and preprocess the Lagrangian data and attributes.

This function takes an identification number that can be used to create a file or url pattern or select data from a Dataframe. It then preprocesses the data and returns a clean Xarray Dataset.

Parameters

indexint

Drifter’s identification number

Returns

dsxr.Dataset

Xarray Dataset containing the data and attributes

clouddrift.adapters.gdp6h.to_raggedarray(drifter_ids: list[int] | None = None, n_random_id: int | None = None, tmp_path: str = '/tmp/clouddrift/gdp6h') → RaggedArray

Download and process individual GDP 6-hourly files and return a RaggedArray instance with the data.

Parameters

drifter_idslist[int], optional

List of drifters to retrieve (Default: all)

n_random_idlist[int], optional

Randomly select n_random_id drifter NetCDF files

tmp_pathstr, optional

Path to the directory where the individual NetCDF files are stored (default varies depending on operating system; /tmp/clouddrift/gdp6h on Linux)

Returns

outRaggedArray

A RaggedArray instance of the requested dataset

Examples

Invoke to_raggedarray without any arguments to download all drifter data from the 6-hourly GDP feed:

>>> from clouddrift.adapters.gdp6h import to_raggedarray
>>> ra = to_raggedarray()

To download a random sample of 100 drifters, for example for development or testing, use the n_random_id argument:

>>> ra = to_raggedarray(n_random_id=100)

To download a specific list of drifters, use the drifter_ids argument:

>>> ra = to_raggedarray(drifter_ids=[54375, 114956, 126934])

Finally, to_raggedarray returns a RaggedArray instance which provides a convenience method to emit a xarray.Dataset instance:

>>> ds = ra.to_xarray()

To write the ragged array dataset to a NetCDF file on disk, do

>>> ds.to_netcdf("gdp6h.nc", format="NETCDF4")

Alternatively, to write the ragged array to a Parquet file, first create it as an Awkward Array:

>>> arr = ra.to_awkward()
>>> arr.to_parquet("gdp6h.parquet")