panache.utils#

Functions

`align_bathymetry`(dataset, path_to_bathy_data)	Align bathymetric data to the resolution of the input dataset.
`check_time_format`(time_str)
`coordinate_range_bounds`(coordinate_range)
`define_parameters`(Zone)	Define region-specific parameters based on the selected zone.
`expand_grid`(**kwargs)	Create a DataFrame from the Cartesian product of input arrays.
`extract_dataframes_iterative`(data)	Efficiently extract all DataFrames from a nested dictionary using an iterative approach.
`extract_time_from_nc_file`(map_data)
`flatten_a_list`(lst)	Flatten a nested list into a single list.
`load_bathymetric_data`(path_to_bathy_data, ...)
`load_file`(file_name)
`resolve_preset_directions`(searching_strategies)	Resolve named search strategy presets into relative pixel directions.
`years_between_dates`(start_date, end_date)

panache.utils.align_bathymetry(dataset, path_to_bathy_data)[source]#

Align bathymetric data to the resolution of the input dataset.

Parameters:

dataset (xarray.DataArray) – The input dataset to which the bathymetry should be aligned.
parameters (dict) – Configuration parameters for plume detection.
path_to_bathy_data (str) – Path to the raw bathymetric map of the Zone (e.g. f’{work_dir}/RESULTS/{Zone}/Bathy_data.pkl’).

Returns:

The bathymetric data aligned to the input dataset’s resolution.

Return type:

xarray.DataArray

panache.utils.define_parameters(Zone)[source]#

Define region-specific parameters based on the selected zone.

Parameters:: Zone (str) – Name of the geographic zone (e.g., “BAY_OF_SEINE”, “BAY_OF_BISCAY”).
Returns:: A dictionary containing the parameters for the specified zone.
Return type:: dict

panache.utils.expand_grid(**kwargs)[source]#

Create a DataFrame from the Cartesian product of input arrays.

Parameters:: **kwargs (dict) – Keyword arguments where keys are column names and values are arrays.
Returns:: DataFrame representing the Cartesian product of input arrays.
Return type:: pandas.DataFrame

panache.utils.extract_dataframes_iterative(data)[source]#: Efficiently extract all DataFrames from a nested dictionary using an iterative approach.

panache.utils.flatten_a_list(lst)[source]#

Flatten a nested list into a single list.

panache.utils.load_bathymetric_data(path_to_bathy_data, min_lon, max_lon, min_lat, max_lat)[source]#

panache.utils.resolve_preset_directions(searching_strategies)[source]#

Resolve named search strategy presets into relative pixel directions.

Parameters:: searching_strategies (Mapping[str, str]) – A mapping from plume name to one of the available preset names.
Returns:: A dictionary where each plume name maps to the relative pixel directions used by the plume algorithm.
Return type:: dict

panache.utils.years_between_dates(start_date: str, end_date: str)[source]#