hydromt.gis.DataArray.vector.from_gdf#

static gis.DataArray.vector.from_gdf(gdf: GeoDataFrame, data: Any, coords: dict | None = None, dims: tuple | None = None, name: str | None = None, index_dim: str | None = 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