Update to Raster.dtype refactorisation and cast_nodata logic from…

… GeoUtils (GlacioHack#498)

dev-environment.yml

@@ -9,11 +9,11 @@ dependencies:
   - matplotlib=3.*
   - pyproj>=3.4,<4
   - rasterio>=1.3,<2
-  - scipy=1.*
+  - scipy>=1.0,<1.13
   - tqdm
   - scikit-image=0.*
   - scikit-gstat>=1.0
-  - geoutils>=0.1.2
+  - geoutils>=0.1.4,<0.2
 
   # Development-specific, to mirror manually in setup.cfg [options.extras_require].
   - pip

environment.yml

@@ -9,11 +9,11 @@ dependencies:
   - matplotlib=3.*
   - pyproj>=3.4,<4
   - rasterio>=1.3,<2
-  - scipy=1.*
+  - scipy>=1.0,<1.13
   - tqdm
   - scikit-image=0.*
   - scikit-gstat>=1.0
-  - geoutils>=0.1.2
+  - geoutils>=0.1.4,<0.2
   - pip
 
    # To run CI against latest GeoUtils

requirements.txt

@@ -7,9 +7,9 @@ numpy==1.*
 matplotlib==3.*
 pyproj>=3.4,<4
 rasterio>=1.3,<2
-scipy==1.*
+scipy>=1.0,<1.13
 tqdm
 scikit-image==0.*
 scikit-gstat>=1.0
-geoutils>=0.1.2
+geoutils>=0.1.4,<0.2
 pip

tests/test_coreg/test_biascorr.py

@@ -560,10 +560,10 @@ def test_deramp__synthetic(self, fit_args, order: int) -> None:
         deramp = biascorr.Deramp(poly_order=order)
         elev_fit_args = fit_args.copy()
         if isinstance(elev_fit_args["to_be_aligned_elev"], gpd.GeoDataFrame):
-            bias_elev = bias_dem.to_pointcloud(data_column_name="z", subsample=20000).ds
+            bias_elev = bias_dem.to_pointcloud(data_column_name="z", subsample=30000).ds
         else:
             bias_elev = bias_dem
-        deramp.fit(elev_fit_args["reference_elev"], to_be_aligned_elev=bias_elev, subsample=10000, random_state=42)
+        deramp.fit(elev_fit_args["reference_elev"], to_be_aligned_elev=bias_elev, subsample=20000, random_state=42)
 
         # Check high-order fit parameters are the same within 10%
         fit_params = deramp._meta["fit_params"]

xdem/dem.py

@@ -162,6 +162,7 @@ def from_array(
         nodata: int | float | None = None,
         area_or_point: Literal["Area", "Point"] | None = None,
         tags: dict[str, Any] = None,
+        cast_nodata: bool = True,
         vcrs: Literal["Ellipsoid"]
         | Literal["EGM08"]
         | Literal["EGM96"]
@@ -180,13 +181,21 @@ def from_array(
         :param nodata: Nodata value.
         :param area_or_point: Pixel interpretation of the raster, will be stored in AREA_OR_POINT metadata.
         :param tags: Metadata stored in a dictionary.
+        :param cast_nodata: Automatically cast nodata value to the default nodata for the new array type if not
+            compatible. If False, will raise an error when incompatible.
         :param vcrs: Vertical coordinate reference system.
 
         :returns: DEM created from the provided array and georeferencing.
         """
         # We first apply the from_array of the parent class
         rast = SatelliteImage.from_array(
-            data=data, transform=transform, crs=crs, nodata=nodata, area_or_point=area_or_point, tags=tags
+            data=data,
+            transform=transform,
+            crs=crs,
+            nodata=nodata,
+            area_or_point=area_or_point,
+            tags=tags,
+            cast_nodata=cast_nodata,
         )
         # Then add the vcrs to the class call (that builds on top of the parent class)
         return cls(filename_or_dataset=rast, vcrs=vcrs)
@@ -300,7 +309,7 @@ def to_vcrs(
         zz_trans = _transform_zz(crs_from=src_ccrs, crs_to=dst_ccrs, xx=xx, yy=yy, zz=zz)
 
         # Update DEM
-        self._data = zz_trans.astype(self.dtypes[0])  # type: ignore
+        self._data = zz_trans.astype(self.dtype)  # type: ignore
 
         # Update vcrs (which will update ccrs if called)
         self.set_vcrs(new_vcrs=vcrs)