Fix NaNs in "longyearbyen_ddem" example

tests/test_spatialstats.py

@@ -39,17 +39,23 @@ def test_sample_multirange_variogram_default(self):
 
         # Check the variogram estimation runs for a random state
         df = xdem.spatialstats.sample_empirical_variogram(
-            values=diff.data, gsd=diff.res[0], subsample=50,
+            values=diff, subsample=50,
             random_state=42, runs=2)
 
         # With random state, results should always be the same
         assert df.exp[0] == pytest.approx(6.11, 0.01)
         # With a single run, no error can be estimated
         assert all(np.isnan(df.err_exp.values))
 
+        # Check that all type of coordinate inputs work
+        # Only the array and the ground sampling distance
+        df = xdem.spatialstats.sample_empirical_variogram(
+            values=diff.data, gsd=diff.res[0], subsample=50,
+            random_state=42, runs=2)
+
         # Test multiple runs
         df2 = xdem.spatialstats.sample_empirical_variogram(
-            values=diff.data, gsd=diff.res[0], subsample=50,
+            values=diff, subsample=50,
             random_state=42, runs=2, n_variograms=2)
 
         # Check that an error is estimated
@@ -68,7 +74,7 @@ def test_sample_multirange_variogram_methods(self, subsample_method):
 
         # Check the variogram estimation runs for several methods
         df = xdem.spatialstats.sample_empirical_variogram(
-            values=diff.data, gsd=diff.res[0], subsample=50, random_state=42,
+            values=diff, subsample=50, random_state=42,
             subsample_method=subsample_method)
 
         assert not df.empty
@@ -87,29 +93,29 @@ def test_sample_multirange_variogram_args(self):
         with pytest.warns(UserWarning):
             # An argument only use by cdist with a pdist method
             df = xdem.spatialstats.sample_empirical_variogram(
-                values=diff.data, gsd=diff.res[0], subsample=50, random_state=42,
+                values=diff, subsample=50, random_state=42,
                 subsample_method='pdist_ring', **cdist_args)
 
         with pytest.warns(UserWarning):
             # Same here
             df = xdem.spatialstats.sample_empirical_variogram(
-                values=diff.data, gsd=diff.res[0], subsample=50, random_state=42,
+                values=diff, subsample=50, random_state=42,
                 subsample_method='cdist_equidistant', runs=2, **pdist_args)
 
         with pytest.warns(UserWarning):
             # Should also raise a warning for a nonsense argument
             df = xdem.spatialstats.sample_empirical_variogram(
-                values=diff.data, gsd=diff.res[0], subsample=50, random_state=42,
+                values=diff, subsample=50, random_state=42,
                 subsample_method='cdist_equidistant', runs=2, **nonsense_args)
 
         # Check the function passes optional arguments specific to pdist methods without warning
         df = xdem.spatialstats.sample_empirical_variogram(
-            values=diff.data, gsd=diff.res[0], subsample=50, random_state=42,
+            values=diff, subsample=50, random_state=42,
             subsample_method='pdist_ring', **pdist_args)
 
         # Check the function passes optional arguments specific to cdist methods without warning
         df = xdem.spatialstats.sample_empirical_variogram(
-            values=diff.data, gsd=diff.res[0], subsample=50, random_state=42,
+            values=diff, subsample=50, random_state=42,
             subsample_method='cdist_equidistant', runs=2, **cdist_args)
 
     def test_multirange_fit_performance(self):

xdem/examples.py

@@ -7,6 +7,8 @@
 import urllib.request
 from distutils.dir_util import copy_tree
 
+import numpy as np
+
 import geoutils as gu
 import xdem
 
@@ -94,9 +96,10 @@ def process_coregistered_examples(overwrite: bool =False):
     nuth_kaab.fit(reference_raster.data, to_be_aligned_raster.data,
                   inlier_mask=inlier_mask, transform=reference_raster.transform)
     aligned_raster = nuth_kaab.apply(to_be_aligned_raster.data, transform=reference_raster.transform)
+    aligned_raster.data[~np.isfinite(aligned_raster)] = reference_raster.nodata
 
-    diff = gu.Raster.from_array((reference_raster.data - aligned_raster),
-                                transform=reference_raster.transform, crs=reference_raster.crs)
+    diff = reference_raster - \
+           gu.Raster.from_array(aligned_raster.data, transform=reference_raster.transform, crs=reference_raster.crs, nodata=reference_raster.nodata)
 
     # Save it so that future calls won't need to recreate the file
     os.makedirs(os.path.dirname(FILEPATHS_PROCESSED['longyearbyen_ddem']), exist_ok=True)

xdem/spatialstats.py

@@ -600,7 +600,7 @@ def sample_empirical_variogram(values: Union[np.ndarray, RasterType], gsd: float
     """
     # First, check all that the values provided are OK
     if isinstance(values, Raster):
-        coords = values.coords()
+        gsd = values.res[0]
         values, mask = get_array_and_mask(values.data)
     elif isinstance(values, (np.ndarray, np.ma.masked_array)):
         values, mask = get_array_and_mask(values)