fix: fix crash in resample_cube_spatial and remove odc-algo dependency (

#144)

remove odc-algo dependency

openeo_processes_dask/process_implementations/__init__.py

@@ -15,13 +15,6 @@
         "Did not load machine learning processes due to missing dependencies: Install them like this: `pip install openeo-processes-dask[implementations, ml]`"
     )
 
-try:
-    from .experimental import *
-except ImportError as e:
-    logger.warning(
-        "Did not load experimental processes due to missing dependencies. Install them like this: `pip install openeo-processes-dask[implementations, experimental]`"
-    )
-
 import rioxarray as rio  # Required for the .rio accessor on xarrays.
 
 import openeo_processes_dask.process_implementations.cubes._xr_interop

openeo_processes_dask/process_implementations/experimental/resample.py

@@ -1,4 +1,3 @@
-import odc.algo
 import rioxarray  # needs to be imported to set .rio accessor on xarray objects.
 
 from openeo_processes_dask.process_implementations.data_model import RasterCube
@@ -9,13 +8,6 @@
 def resample_cube_spatial(
     data: RasterCube, target: RasterCube, method="near", options=None
 ) -> RasterCube:
-    # NOTE: Using the odc-algo library is not great, because it is only a random collection of experimental opendatacube features
-    # but we've investigated all other available alternatives for resampling that are currently available with dask and none do the job.
-    # We've tested pyresample (did not work at all and requires loads of helper code),
-    # rasterio.reproject_match (loads all the data into memory to do gdal.warp) and odc-geo (doesn't support dask yet).
-    # Github issue tracking this feature in rioxarray: https://github.com/corteva/rioxarray/issues/119
-    # Github issue tracking this feature in odc-geo: https://github.com/opendatacube/odc-geo/issues/26
-
     methods_list = [
         "near",
         "bilinear",
@@ -31,8 +23,12 @@ def resample_cube_spatial(
         "q3",
     ]
 
+    # ODC reproject requires y to be before x
     required_dim_order = (
-        data.openeo.band_dims + data.openeo.temporal_dims + data.openeo.spatial_dims
+        data.openeo.band_dims
+        + data.openeo.temporal_dims
+        + tuple(data.openeo.y_dim)
+        + tuple(data.openeo.x_dim)
     )
 
     data_reordered = data.transpose(*required_dim_order, missing_dims="ignore")
@@ -47,13 +43,14 @@ def resample_cube_spatial(
             f"[{', '.join(methods_list)}]"
         )
 
-    resampled_data = odc.algo._warp.xr_reproject(
-        data_reordered, target_reordered.geobox, resampling=method
+    resampled_data = data_reordered.odc.reproject(
+        target_reordered.odc.geobox, resampling=method
     )
+
     resampled_data.rio.write_crs(target_reordered.rio.crs, inplace=True)
 
     try:
-        # xr_reproject renames the coordinates according to the geobox, this undoes that.
+        # odc.reproject renames the coordinates according to the geobox, this undoes that.
         resampled_data = resampled_data.rename(
             {"longitude": data.openeo.x_dim, "latitude": data.openeo.y_dim}
         )

pyproject.toml

@@ -31,7 +31,6 @@ rasterio = { version = "^1.3.4", optional = true }
 dask-geopandas = { version = ">=0.2.0,<1", optional = true }
 xgboost = { version = "^1.5.1", optional = true }
 rioxarray = { version = ">=0.12.0,<1", optional = true }
-odc-algo = { version = "==0.2.3", optional = true }
 openeo-pg-parser-networkx = { version = ">=2023.5.1", optional = true }
 odc-geo = { version = ">=0.3.2,<1", optional = true }
 stac_validator = { version = ">=3.3.1", optional = true }
@@ -50,7 +49,6 @@ pytest-cov = "^4.0.0"
 
 [tool.poetry.extras]
 implementations = ["geopandas", "xarray", "dask", "rasterio", "dask-geopandas", "rioxarray", "openeo-pg-parser-networkx", "odc-geo", "stackstac", "planetary_computer", "pystac_client", "stac_validator"]
-experimental = ["odc-algo"]
 ml = ["xgboost"]
 
 [tool.pytest.ini_options]