salem.DatasetAccessor.roi

DatasetAccessor.roi(self, shape=None, geometry=None, grid=None, corners=None, crs=wgs84, roi=None, all_touched=False, other=None)

Make a region of interest (ROI) for the dataset.

All grid points outside the ROI will be masked out.

Parameters:

ds : Dataset or DataArray

form the ROI from the extent of the Dataset or DataArray

shape : str

path to a shapefile

geometry : geometry

a shapely geometry (don’t forget the crs keyword)

grid : Grid

a Grid object which extent will form the ROI

corners : tuple

a ((x0, y0), (x1, y1)) tuple of the corners of the square to subset the dataset to (don’t forget the crs keyword)

crs : crs, default wgs84

coordinate reference system of the geometry and corners

roi : ndarray

if you have a mask ready, you can give it here

all_touched : boolean

pass-through argument for rasterio.features.rasterize, indicating that all grid cells which are clipped by the shapefile defining the region of interest should be included (default=False)

other : scalar, DataArray or Dataset, optional

Value to use for locations in this object where cond is False. By default, these locations filled with NA. As in http://xarray.pydata.org/en/stable/generated/xarray.DataArray.where.html