processing.select#

Functions

`convert_geo_to_LCC`(coord, ds)	Convert the geographic coordinates to Lambert Conformal Coordinates.
`convert_geo_to_rot`(coord, ds)	Converts a geographic (longitude, latitude) point to a rotated pole (rlon, rlat) point.
`get_shapefile_mask`(ds, shapefile_path)	Generates a mask from a shapefile to apply to an xarray Dataset.
`select_point`(ds, lat_point, lon_point[, ...])	Select a point from the dataset based on the provided geographic coordinates.
`select_region`(ds, region)	Selects a specific geographical region from an xarray Dataset based on given region bounds.

convert_geo_to_LCC(coord: tuple, ds: Dataset)[source]#

Convert the geographic coordinates to Lambert Conformal Coordinates.

Parameters:

coord (tuple) – Geographic coordinates as a (longitude, latitude) pair in degrees.
ds (xarray.Dataset) – The input dataset containing the Lambert Conformal Conic grid information.

Returns:

The corresponding Lambert Conformal Coordinates as (x, y) in meters.

Return type:

tuple

convert_geo_to_rot(coord: tuple, ds: Dataset)[source]#

Converts a geographic (longitude, latitude) point to a rotated pole (rlon, rlat) point.

Parameters:

coord (list or tuple) – Geographic coordinates as a (longitude, latitude) pair in degrees.
ds (xarray.Dataset) – The input dataset containing the rotated pole grid information (e.g., from a COSMO-CLM file).

Returns:

The corresponding rotated pole coordinates as [rlon, rlat] in degrees.

Return type:

list

get_shapefile_mask(ds: Dataset, shapefile_path: Path)[source]#

Generates a mask from a shapefile to apply to an xarray Dataset.

This function reads a shapefile using Geopandas, converts it to the WGS84 coordinate reference system (CRS), and creates a mask that can be applied to the input xarray Dataset. The mask identifies the grid cells that fall within the shapefile’s region.

Parameters:

ds (xr.Dataset) – Input xarray Dataset containing longitude and latitude coordinates.
shapefile_path (Path) – Path to the shapefile to be used for masking.

Returns:

mask_shp – A boolean mask array where grid cells within the shapefile region are marked as True, and those outside are marked as False.

Return type:

xr.Dataset

Notes

The shapefile is converted to the WGS84 CRS (EPSG:4326) before creating the mask.
The function uses the regionmask library to generate the mask.

Examples

>>> import xarray as xr
>>> from pathlib import Path
>>> ds = xr.open_dataset('path_to_your_dataset.nc')
>>> shapefile = Path('path_to_your_shapefile.shp')
>>> mask = get_shapefile_mask(ds, shapefile)

select_point(ds: Dataset, lat_point: float, lon_point: float, projection: str = None)[source]#

Select a point from the dataset based on the provided geographic coordinates.

Parameters:

ds (xarray.Dataset) – The input dataset from which to select the point.
lon_point (float) – Geographic longitude coordinate
lat_point (float) – Geographic latitude coordinate
projection (str, optional) – The projection of the dataset. The point will be projected to the dataset’s coordinate system before selection. Currently supported projections are ‘rotated_pole’ and ‘lcc’ (Lambert Conformal Coordinates).

Returns:

The dataset subset at the nearest point to the specified coordinates.

Return type:

xarray.Dataset

select_region(ds: Dataset, region: str)[source]#

Selects a specific geographical region from an xarray Dataset based on given region bounds.

Parameters:

ds (xr.Dataset) – The input xarray Dataset from which to select the region.
region (str) – The name of the region to select. This should correspond to a key in the region_bounds dictionary, which defines the latitude and longitude bounds

Returns:

A new xarray Dataset containing only the data within the specified region.

Return type:

xr.Dataset

Examples

>>> ds_region = select_region(ds, 'europe')