hydromt.DataArray.vector.from_gdf

static DataArray.vector.from_gdf(gdf: GeoDataFrame, data: Any, coords: dict = None, dims: tuple = None, name: str = None, index_dim: str = None, keep_cols: bool = True, merge_index: str = 'gdf') → DataArray

Parse GeoDataFrame object with point geometries to DataArray.

DataArray will have geospatial attributes and be merged with array_like data.

Parameters:

• gdf (geopandas GeoDataFrame) – Spatial coordinates. The index should match the array_like index_dim and the geometry column may only contain Point geometries.

• data (array_like) – Values for this array. Must be an numpy.ndarray, ndarray like, or castable to an ndarray. If a self-described xarray or pandas object, attempts are made to use this array’s metadata to fill in other unspecified arguments. A view of the array’s data is used instead of a copy if possible.

• coords (sequence or dict of array_like, optional) – Coordinates (tick labels) to use for indexing along each dimension.

• dims (hashable or sequence of hashable, optional) – Name(s) of the data dimension(s). Must be either a hashable (only for 1D data) or a sequence of hashables with length equal to the number of dimensions. If this argument is omitted, dimension names default to ['dim_0', ... 'dim_n'].

• name (str, optional) – The name of the data set for metadata purposes.

• index_dim (str, optional) – Name of index dimension of data

• keep_cols (bool, optional) – If True, keep gdf columns as extra coordinates in dataset

• merge_index ({'gdf', 'inner'}, default 'gdf') –

  Type of merge to be performed between gdf and data.

  • gdf: use only keys from gdf index. Missing values will be filled with NaNs

  • inner: use intersection of gdf and data index.

Returns:

da – DataArray with geospatial coordinates

Return type:

xarray.DataArray