Incremental commit on Xarray accessor

geoutils/raster/accessor.py

@@ -1,20 +1,15 @@
 """
-geoutils.accessor provides an Xarray accessor "rst" mirroring the API of the Raster class.
+Module for the Xarray accessor "rst" mirroring the API of the Raster class.
 """
 
 import numpy as np
 import rasterio as rio
 import rioxarray as rioxr
 import xarray as xr
-from geocube.vector import vectorize
-from pyproj import CRS
 
+import geoutils as gu
 from geoutils._typing import NDArrayNum
-from geoutils.projtools import _get_bounds_projected, _get_footprint_projected
-from geoutils.raster import Raster, RasterType
-from geoutils.raster.sampling import subsample_array
-from geoutils.vector import Vector
-
+from geoutils.raster.base import RasterBase, RasterType
 
 def open_raster(filename: str, **kwargs):
 
@@ -32,170 +27,17 @@ def open_raster(filename: str, **kwargs):
 
 
 @xr.register_dataarray_accessor("rst")
-class RasterAccessor:
+class RasterAccessor(RasterBase):
     def __init__(self, xarray_obj: xr.DataArray):
         self._obj = xarray_obj
 
-    # First, properties that need to be parsed differently than in Raster
-    @property
-    def crs(self):
-        return self._obj.rio.crs
-
-    @property
-    def transform(self):
-        return self._obj.rio.transform(recalc=True)
-
-    @property
-    def nodata(self):
-        return self._obj.rio.nodata
-
-    @property
-    def height(self):
-        return self._obj.rio.height
-
-    @property
-    def width(self):
-        return self._obj.rio.width
-
-    @property
-    def shape(self):
-        return self._obj.rio.shape
-
-    @property
-    def res(self):
-        return self._obj.rio.resolution(recalc=True)
-
-    @property
-    def bounds(self):
-        return self._obj.rio.bounds(recalc=True)
-
-    @property
-    def count(self):
-        return self._obj.rio.count
-
-    def reproject(self):
-
-        # Copy logic of Raster.reproject()
-
-        # Perform final reprojection operation with RioXarray
-        # reproj_obj = self._obj.rio.reproject(dst_crs, resolution, shape, transform, resampling, nodata, **kwargs)
-        reproj_obj = None
-
-        return reproj_obj
-
-    def crop(self):
-
-        # Copy logic of Raster.crop()
-
-        # Perform final cropping operation with RioXarray
-        # clipped_obj = self._obj.rio.clip_box(minx, miny, maxx, maxy, crs, *kwargs)
-        clipped_obj = None
-
-        return clipped_obj
-
-    def proximity(self):
-
-        # Copy logic of Raster.proximity()
-
-        proximity = None
-
-        return proximity
-
-    def polygonize(self):
-
-        # Copy logic of Raster.polygonize()
-
-        gdf_polygonize = vectorize(self._obj)
-
-        return Vector(gdf_polygonize)
-
-    def georeferenced_grid_equal(self: xr.DataArray, raster: RasterType | xr.DataArray) -> bool:
-
-        return all([self.shape == raster.shape, self.transform == raster.transform, self.crs == raster.crs])
-
-    def get_footprint_projected(self, out_crs: CRS, densify_pts: int = 5000) -> Vector:
-        """
-        Get raster footprint projected in a specified CRS.
-
-        The polygon points of the vector are densified during reprojection to warp
-        the rectangular square footprint of the original projection into the new one.
-
-        :param out_crs: Output CRS.
-        :param densify_pts: Maximum points to be added between image corners to account for non linear edges.
-         Reduce if time computation is really critical (ms) or increase if extent is not accurate enough.
-        """
-
-        return Vector(
-            _get_footprint_projected(bounds=self.bounds, in_crs=self.crs, out_crs=out_crs, densify_pts=densify_pts)
-        )
-
-    def get_bounds_projected(self, out_crs: CRS, densify_pts: int = 5000) -> rio.coords.BoundingBox:
-        """
-        Get raster bounds projected in a specified CRS.
-
-        :param out_crs: Output CRS.
-        :param densify_pts: Maximum points to be added between image corners to account for non linear edges.
-         Reduce if time computation is really critical (ms) or increase if extent is not accurate enough.
-
-        """
-        # Max points to be added between image corners to account for non linear edges
-        # rasterio's default is a bit low for very large images
-        # instead, use image dimensions, with a maximum of 50000
-        densify_pts = min(max(self.width, self.height), densify_pts)
-
-        # Calculate new bounds
-        new_bounds = _get_bounds_projected(self.bounds, in_crs=self.crs, out_crs=out_crs, densify_pts=densify_pts)
-
-        return new_bounds
-
-    def subsample(
-        self,
-        subsample: float | int,
-        return_indices: bool = False,
-        random_state: np.random.RandomState | int | None = None,
-    ) -> NDArrayNum | tuple[NDArrayNum, ...]:
-        """
-        Randomly subsample the raster. Only valid values are considered.
-
-        :param subsample: If <= 1, a fraction of the total pixels to extract. If > 1, the number of pixels.
-        :param return_indices: Whether to return the extracted indices only.
-        :param random_state: Random state or seed number.
-
-        :return: Array of subsampled valid values, or array of subsampled indices.
-        """
-
-        return subsample_array(
-            array=self.data, subsample=subsample, return_indices=return_indices, random_state=random_state
-        )
-
-    def to_raster(self):
+    def to_raster(self) -> RasterBase:
         """
         Convert to geoutils.Raster object.
 
         :return:
         """
-
-        return Raster.from_array(data=self._obj.data, crs=self.crs, transform=self.transform, nodata=self.nodata)
-
-    def xy2ij(self):
-
-        # Copy exact logic of raster
-        return
-
-    def ij2xy(self):
-
-        # Copy exact logic of raster
-        return
-
-    def outside_image(self):
-
-        # Copy exact logic of raster
-        return
-
-    def show(self):
-
-        # Copy exact logic of raster
-        return
+        return gu.Raster.from_array(data=self._obj.data, crs=self.crs, transform=self.transform, nodata=self.nodata)
 
 
 @xr.register_dataarray_accessor("sat")