clouddrift.adapters.laser

clouddrift.adapters.laser#

Adapt the LASER 15-minute interpolated drifter trajectories to RaggedArray.

The upstream dataset is hosted by GRIIDC at https://doi.org/10.7266/N7W0940J and distributed as a zip archive containing the ASCII drifter trajectories file and a README.

Example#

>>> from clouddrift.adapters import laser
>>> ra = laser.to_raggedarray()
>>> ds = ra.to_xarray()

References#

Eric D’Asaro, Cedric Guigand, Angelique Haza, Helga Huntley, Guillaume Novelli, Tamay Ozgokmen, Ed Ryan. 2017. Lagrangian Submesoscale Experiment (LASER) surface drifters, interpolated to 15-minute intervals. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University-Corpus Christi. https://doi.org/10.7266/N7W0940J

Functions

get_dataframe([tmp_path, skip_download])

Get the LASER dataset as a pandas DataFrame.

to_raggedarray([tmp_path, skip_download])

Return the LASER dataset as a RaggedArray instance.

clouddrift.adapters.laser.get_dataframe(tmp_path: str | None = None, skip_download: bool = False) DataFrame[source]#

Get the LASER dataset as a pandas DataFrame.

Parameters#

tmp_pathstr, optional

Temporary path where intermediary files are stored. If None, uses the default LASER adapter temp path.

skip_downloadbool, optional

If True, skip re-downloading the archive if it already exists in tmp_path. Default is False.

clouddrift.adapters.laser.to_raggedarray(tmp_path: str | None = None, skip_download: bool = False) RaggedArray[source]#

Return the LASER dataset as a RaggedArray instance.

Parameters#

tmp_pathstr, optional

Temporary path where intermediary files are stored. If None, uses the default LASER adapter temp path.

skip_downloadbool, optional

If True, skip re-downloading the archive if it already exists in tmp_path. Default is False.