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make_geocube

-geocube.api.core.make_geocube(vector_data: str | PathLike | GeoDataFrame, *, measurements: list[str] | None = None, datetime_measurements: list[str] | None = None, output_crs: Any | None = None, resolution: float | Iterable[float] | None = None, align: tuple[float, float] | None = None, geom: str | dict | BaseGeometry | Geometry | None = None, like: Dataset | DataArray | None = None, fill: float = nan, group_by: str | None = None, interpolate_na_method: Literal['linear', 'nearest', 'cubic'] | None = None, categorical_enums: dict[str, list] | None = None, rasterize_function: Callable[[...], ndarray[Any, dtype[_ScalarType_co]] | None] | None = None) Dataset[source]
+geocube.api.core.make_geocube(vector_data: str | PathLike | GeoDataFrame, *, measurements: list[str] | None = None, datetime_measurements: list[str] | None = None, output_crs: Any | None = None, resolution: float | Iterable[float] | None = None, align: tuple[float, float] | None = None, geom: str | dict | BaseGeometry | Geometry | None = None, like: Dataset | DataArray | None = None, fill: float = nan, group_by: str | None = None, interpolate_na_method: Literal['linear', 'nearest', 'cubic'] | None = None, categorical_enums: dict[str, list] | None = None, rasterize_function: Callable[[...], ndarray[tuple[int, ...], dtype[_ScalarType_co]] | None] | None = None) Dataset[source]

Rasterize vector data into an xarray object. Each attribute will be a data -variable in the xarray.Dataset.

+variable in the xarray.Dataset.

Parameters:
@@ -175,7 +175,7 @@

make_geocube

-geocube.rasterize.rasterize_image(*, geometry_array: GeoSeries, data_values: ndarray[Any, dtype[_ScalarType_co]] | IntegerArray, geobox: GeoBox, fill: float, merge_alg: MergeAlg = MergeAlg.replace, filter_nan: bool = False, all_touched: bool = False, **ignored_kwargs) ndarray[Any, dtype[_ScalarType_co]] | None[source]
+geocube.rasterize.rasterize_image(*, geometry_array: GeoSeries, data_values: ndarray[tuple[int, ...], dtype[_ScalarType_co]] | IntegerArray, geobox: GeoBox, fill: float, merge_alg: MergeAlg = MergeAlg.replace, filter_nan: bool = False, all_touched: bool = False, **ignored_kwargs) ndarray[tuple[int, ...], dtype[_ScalarType_co]] | None[source]

Rasterize a list of shapes+values for a given GeoBox.

Parameters:
@@ -199,14 +199,14 @@

rasterize

The vector data in the rasterized format.

Return type:
-

numpy.ndarray or None

+

numpy.ndarray or None

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-geocube.rasterize.rasterize_points_griddata(*, geometry_array: GeoSeries, data_values: ndarray[Any, dtype[_ScalarType_co]], grid_coords: dict[str, ndarray[Any, dtype[_ScalarType_co]]], fill: float, method: str = 'nearest', rescale: bool = False, filter_nan: bool = False, **ignored_kwargs) ndarray[Any, dtype[_ScalarType_co]] | None[source]
+geocube.rasterize.rasterize_points_griddata(*, geometry_array: GeoSeries, data_values: ndarray[tuple[int, ...], dtype[_ScalarType_co]], grid_coords: dict[str, ndarray[tuple[int, ...], dtype[_ScalarType_co]]], fill: float, method: str = 'nearest', rescale: bool = False, filter_nan: bool = False, **ignored_kwargs) ndarray[tuple[int, ...], dtype[_ScalarType_co]] | None[source]

This method uses scipy.interpolate.griddata to interpolate point data to a grid.

@@ -228,14 +228,14 @@

rasterize

:class:`numpy.ndarray`

Return type:
-

An interpolated numpy.ndarray.

+

An interpolated numpy.ndarray.

-geocube.rasterize.rasterize_points_radial(*, geometry_array: GeoSeries, data_values: ndarray[Any, dtype[_ScalarType_co]], grid_coords: dict[str, ndarray[Any, dtype[_ScalarType_co]]], method: str = 'linear', filter_nan=False, **ignored_kwargs) ndarray[Any, dtype[_ScalarType_co]] | None[source]
+geocube.rasterize.rasterize_points_radial(*, geometry_array: GeoSeries, data_values: ndarray[tuple[int, ...], dtype[_ScalarType_co]], grid_coords: dict[str, ndarray[tuple[int, ...], dtype[_ScalarType_co]]], method: str = 'linear', filter_nan=False, **ignored_kwargs) ndarray[tuple[int, ...], dtype[_ScalarType_co]] | None[source]

This method uses scipy.interpolate.Rbf to interpolate point data to a grid.

@@ -257,7 +257,7 @@

rasterize

:class:`numpy.ndarray`

Return type:
-

An interpolated numpy.ndarray.

+

An interpolated numpy.ndarray.

@@ -267,14 +267,14 @@

rasterize

-geocube.vector.vectorize(data_array: DataArray) GeoDataFrame[source]
+geocube.vector.vectorize(data_array: DataArray) GeoDataFrame[source]

Added in version 0.4.0.

Powered by: rasterio.features.shapes()

-

Convert 2D xarray.DataArray into +

Convert 2D xarray.DataArray into a geopandas.GeoDataFrame.

-

The nodata, CRS, and transform of the xarray.DataArray +

The nodata, CRS, and transform of the xarray.DataArray are determined using rioxarray.

Helpful references:

    @@ -283,7 +283,7 @@

    vectorize
    Parameters:
    -

    data_array (xarray.DataArray) – Input 2D DataArray raster.

    +

    data_array (xarray.DataArray) – Input 2D DataArray raster.

    Return type:

    geopandas.GeoDataFrame

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