Merge pull request #402 from GispoCoding/401-fix-unify-raster-grids

Fix unify raster grids metadata copying

eis_toolkit/raster_processing/unifying.py

@@ -4,83 +4,90 @@
 from beartype.typing import List, Literal, Sequence, Tuple
 from rasterio import warp
 from rasterio.enums import Resampling
+from rasterio.profiles import Profile
 
 from eis_toolkit.exceptions import InvalidParameterValueException
 from eis_toolkit.raster_processing.resampling import RESAMPLE_METHOD_MAP
 
 
+def _calculate_snapped_grid(
+    raster: rasterio.io.DatasetReader, dst_crs: rasterio.crs.CRS, dst_resolution: Tuple[float, float]
+) -> Tuple[warp.Affine, int, int]:
+    dst_transform, dst_width, dst_height = warp.calculate_default_transform(
+        raster.crs, dst_crs, raster.width, raster.height, *raster.bounds, resolution=dst_resolution
+    )
+    # The created transform might not be aligned with the base raster grid, so
+    # we still need to snap/align the transformation to closest grid corner
+    x_distance_to_grid = dst_transform.c % dst_resolution[0]
+    y_distance_to_grid = dst_transform.f % dst_resolution[1]
+
+    if x_distance_to_grid > dst_resolution[0] / 2:  # Snap towards right
+        c = dst_transform.c - x_distance_to_grid + dst_resolution[0]
+    else:  # Snap towards left
+        c = dst_transform.c - x_distance_to_grid
+
+    if y_distance_to_grid > dst_resolution[1] / 2:  # Snap towards up
+        f = dst_transform.f - y_distance_to_grid + dst_resolution[1]
+    else:  # Snap towards bottom
+        f = dst_transform.f - y_distance_to_grid
+
+    # Create new transform with updated corner coordinates
+    dst_transform = warp.Affine(
+        dst_transform.a,  # Pixel size x
+        dst_transform.b,  # Shear parameter
+        c,  # Up-left corner x-coordinate
+        dst_transform.d,  # Shear parameter
+        dst_transform.e,  # Pixel size y
+        f,  # Up-left corner y-coordinate
+    )
+    return dst_transform, dst_width, dst_height
+
+
 def _unify_raster_grids(
     base_raster: rasterio.io.DatasetReader,
     rasters_to_unify: Sequence[rasterio.io.DatasetReader],
     resampling_method: Resampling,
     same_extent: bool,
-) -> List[Tuple[np.ndarray, dict]]:
+) -> List[Tuple[np.ndarray, Profile]]:
 
     dst_crs = base_raster.crs
     dst_width = base_raster.width
     dst_height = base_raster.height
     dst_transform = base_raster.transform
     dst_resolution = (base_raster.transform.a, abs(base_raster.transform.e))
 
-    out_rasters = [(base_raster.read(), base_raster.meta.copy())]
-    out_meta = base_raster.meta.copy()
+    out_rasters = [(base_raster.read(), base_raster.profile.copy())]
 
     for raster in rasters_to_unify:
+        out_profile = raster.profile.copy()
 
         # If we unify without clipping, things are more complicated and we need to
         # calculate corner coordinates, width and height, and snap the grid to nearest corner
         if not same_extent:
-            dst_transform, dst_width, dst_height = warp.calculate_default_transform(
-                raster.crs, dst_crs, raster.width, raster.height, *raster.bounds, resolution=dst_resolution
-            )
-            # The created transform might not be aligned with the base raster grid, so
-            # we still need to snap/align the transformation to closest grid corner
-            x_distance_to_grid = dst_transform.c % dst_resolution[0]
-            y_distance_to_grid = dst_transform.f % dst_resolution[1]
-
-            if x_distance_to_grid > dst_resolution[0] / 2:  # Snap towards right
-                c = dst_transform.c - x_distance_to_grid + dst_resolution[0]
-            else:  # Snap towards left
-                c = dst_transform.c - x_distance_to_grid
-
-            if y_distance_to_grid > dst_resolution[1] / 2:  # Snap towards up
-                f = dst_transform.f - y_distance_to_grid + dst_resolution[1]
-            else:  # Snap towards bottom
-                f = dst_transform.f - y_distance_to_grid
-
-            # Create new transform with updated corner coordinates
-            dst_transform = warp.Affine(
-                dst_transform.a,  # Pixel size x
-                dst_transform.b,  # Shear parameter
-                c,  # Up-left corner x-coordinate
-                dst_transform.d,  # Shear parameter
-                dst_transform.e,  # Pixel size y
-                f,  # Up-left corner y-coordinate
-            )
-
-            out_meta["transform"] = dst_transform
-            out_meta["width"] = dst_width
-            out_meta["height"] = dst_height
+            dst_transform, dst_width, dst_height = _calculate_snapped_grid(raster, dst_crs, dst_resolution)
 
         # Initialize output raster arrary
         dst_array = np.empty((base_raster.count, dst_height, dst_width))
-        dst_array.fill(base_raster.meta["nodata"])
+        nodata = out_profile["nodata"]
+        dst_array.fill(nodata)
 
         src_array = raster.read()
 
         out_image = warp.reproject(
             source=src_array,
             src_crs=raster.crs,
             src_transform=raster.transform,
-            src_nodata=raster.meta["nodata"],
+            src_nodata=nodata,
             destination=dst_array,
             dst_crs=dst_crs,
             dst_transform=dst_transform,
-            dst_nodata=base_raster.meta["nodata"],
+            dst_nodata=nodata,
             resampling=resampling_method,
         )[0]
 
-        out_rasters.append((out_image, out_meta))
+        out_profile.update({"transform": dst_transform, "width": dst_width, "height": dst_height, "crs": dst_crs})
+
+        out_rasters.append((out_image, out_profile))
 
     return out_rasters
 
@@ -91,7 +98,7 @@ def unify_raster_grids(
     rasters_to_unify: Sequence[rasterio.io.DatasetReader],
     resampling_method: Literal["nearest", "bilinear", "cubic", "average", "gauss", "max", "min"] = "nearest",
     same_extent: bool = False,
-) -> List[Tuple[np.ndarray, dict]]:
+) -> List[Tuple[np.ndarray, Profile]]:
     """Unifies (reprojects, resamples, aligns and optionally clips) given rasters relative to base raster.
 
     Args:
@@ -104,7 +111,7 @@ def unify_raster_grids(
             as the base raster. Expands smaller rasters with nodata cells. Defaults to False.
 
     Returns:
-        List of unified rasters' data and metadata. First element is the base raster.
+        List of unified rasters' data and profiles. First element is the base raster.
 
     Raises:
         InvalidParameterValueException: Rasters to unify is empty.