swarmpal

swarmpal#

`apply_process`(data[, process_name, config])	Create a SwarmPAL process and apply it on the given data.
`apply_processes`(data, process_params)	Apply a list of processes to a dataset.
`fetch_data`(configurations)	Downloads list of datasets and returns a unified DataTree.
`make_process`([process_name, config])	Instantiates a PalProcess object with a given name and a configuration.
`quicklook`(data[, toolbox])	Create a quicklook plot based on the toolbox processes recorded in PAL_meta.

swarmpal.apply_process(data, process_name=None, config={})[source]#

Create a SwarmPAL process and apply it on the given data.

Parameters:

data (DataTree) – the data on which the process will be applied to.
process_name (Str) – the name of the process to apply. See … for a list of Toolboxes and their Processes.
config (dict) – parameters passed to the Toolbox.

swarmpal.apply_processes(data, process_params)[source]#

Apply a list of processes to a dataset.

Parameters:

swarmpal.fetch_data(configurations)[source]#

Downloads list of datasets and returns a unified DataTree.

Parameters:: configurations (List) – A list of configurations passed to create_paldata. TODO: describe the ‘schema’

swarmpal.make_process(process_name=None, config={})[source]#

Instantiates a PalProcess object with a given name and a configuration.

Parameters:

process_name (Str) – The name of the process to apply. Must be one of [‘FAC_single_sat’].
config (dict) – Parameters passed to the Toolbox’ process.

swarmpal.quicklook(data: xarray.DataTree, toolbox: str | None = None)[source]#

Create a quicklook plot based on the toolbox processes recorded in PAL_meta.

Parameters:

data (DataTree) – Data that has been processed by SwarmPAL
toolbox (str, optional) – Override toolbox selection (one of: ‘FAC’, ‘TFA’, ‘DSECS’). Case-insensitive. If omitted, the toolbox is auto-detected from PAL_meta.

Return type:

matplotlib.figure.Figure