reprojection works

test/stac_extension/test_raster.py

@@ -48,19 +48,18 @@ def create_raster_stac_item_v1() -> pystac.Item:
         stac_extensions=["https://stac-extensions.github.io/raster/v1.1.0/schema.json"],
     )
 
-    for asset_name in ["B01", "B02"]:
-        asset_href = f"https://example.com/data/{asset_name}.tif"
-        asset = pystac.Asset(href=asset_href, media_type="image/tiff", roles=["data"])
-        asset.extra_fields["raster:bands"] = [
-            dict(
-                nodata=0,
-                scale=0.1,
-                offset=-0.05,
-                spatial_resolution=10.0,
-                unit="meters",
-            )
-        ]
-        item.add_asset(asset_name, asset)
+    asset_href = f"https://example.com/data/B01.tif"
+    asset = pystac.Asset(href=asset_href, media_type="image/tiff", roles=["data"])
+    asset.extra_fields["raster:bands"] = [
+        dict(
+            nodata=0,
+            scale=0.1,
+            offset=-0.05,
+            spatial_resolution=10.0,
+            unit="meters",
+        )
+    ]
+    item.add_asset("B01", asset)
     return item
 
 
@@ -83,13 +82,12 @@ def create_raster_stac_item_v2() -> pystac.Item:
         stac_extensions=["https://stac-extensions.github.io/raster/v2.0.0/schema.json"],
     )
 
-    for asset_name in ["B01", "B02"]:
-        asset_href = f"https://example.com/data/{asset_name}.tif"
-        asset = pystac.Asset(href=asset_href, media_type="image/tiff", roles=["data"])
-        asset.extra_fields["nodata"] = 0
-        asset.extra_fields["raster:scale"] = 0.1
-        asset.extra_fields["raster:offset"] = -0.05
-        item.add_asset(asset_name, asset)
+    asset_href = f"https://example.com/data/B01.tif"
+    asset = pystac.Asset(href=asset_href, media_type="image/tiff", roles=["data"])
+    asset.extra_fields["nodata"] = 0
+    asset.extra_fields["raster:scale"] = 0.1
+    asset.extra_fields["raster:offset"] = -0.05
+    item.add_asset("B01", asset)
     return item
 
 
@@ -98,59 +96,27 @@ class RasterTest(unittest.TestCase):
     def test_apply_offset_scaling(self):
         item_v1 = create_raster_stac_item_v1()
         item_v2 = create_raster_stac_item_v2()
-        ds_v1 = xr.Dataset()
-        ds_v1["B01"] = xr.DataArray(
+        da_v1 = xr.DataArray(
             data=np.array([[0, 3, 3], [1, 1, 1], [2, 2, 2]]),
             dims=("y", "x"),
             coords=dict(y=[5000, 5010, 5020], x=[7430, 7440, 7450]),
         )
-        ds_v1["B02"] = xr.DataArray(
-            data=np.array([[3, 3, 3], [1, 1, 1], [2, 0, 2]]),
-            dims=("y", "x"),
-            coords=dict(y=[5000, 5010, 5020], x=[7430, 7440, 7450]),
-        )
-        ds_v2 = ds_v1.copy()
-        ds_mod_v1 = apply_offset_scaling(ds_v1, item_v1, "B01")
-        ds_mod_v2 = apply_offset_scaling(ds_v2, item_v2, "B01")
-        ds_mod_expected = xr.Dataset()
-        ds_mod_expected["B01"] = xr.DataArray(
+        da_v2 = da_v1.copy()
+        da_mod_v1 = apply_offset_scaling(da_v1, item_v1, "B01")
+        da_mod_v2 = apply_offset_scaling(da_v2, item_v2, "B01")
+        da_mod_expected = xr.DataArray(
             data=np.array(
                 [[np.nan, 0.25, 0.25], [0.05, 0.05, 0.05], [0.15, 0.15, 0.15]]
             ),
             dims=("y", "x"),
             coords=dict(y=[5000, 5010, 5020], x=[7430, 7440, 7450]),
         )
-        ds_mod_expected["B02"] = xr.DataArray(
-            data=np.array([[3, 3, 3], [1, 1, 1], [2, 0, 2]]),
-            dims=("y", "x"),
-            coords=dict(y=[5000, 5010, 5020], x=[7430, 7440, 7450]),
-        )
-        xr.testing.assert_allclose(ds_mod_expected, ds_mod_v1)
-        xr.testing.assert_allclose(ds_mod_expected, ds_mod_v2)
-
-        ds_mod2_v1 = apply_offset_scaling(ds_mod_v1, item_v1, "B02")
-        ds_mod2_v2 = apply_offset_scaling(ds_mod_v2, item_v2, "B02")
-        ds_mod_expected2 = xr.Dataset()
-        ds_mod_expected2["B01"] = xr.DataArray(
-            data=np.array(
-                [[np.nan, 0.25, 0.25], [0.05, 0.05, 0.05], [0.15, 0.15, 0.15]]
-            ),
-            dims=("y", "x"),
-            coords=dict(y=[5000, 5010, 5020], x=[7430, 7440, 7450]),
-        )
-        ds_mod_expected2["B02"] = xr.DataArray(
-            data=np.array(
-                [[0.25, 0.25, 0.25], [0.05, 0.05, 0.05], [0.15, np.nan, 0.15]]
-            ),
-            dims=("y", "x"),
-            coords=dict(y=[5000, 5010, 5020], x=[7430, 7440, 7450]),
-        )
-        xr.testing.assert_allclose(ds_mod_expected2, ds_mod2_v1)
-        xr.testing.assert_allclose(ds_mod_expected2, ds_mod2_v2)
+        xr.testing.assert_allclose(da_mod_v1, da_mod_expected)
+        xr.testing.assert_allclose(da_mod_v2, da_mod_expected)
 
         with self.assertLogs("xcube.stac", level="WARNING") as cm:
-            ds_mod_v1 = apply_offset_scaling(ds_v1, item_v1, "B01", raster_version="v3")
-        xr.testing.assert_allclose(ds_v1, ds_mod_v1)
+            ds_mod_v1 = apply_offset_scaling(da_v1, item_v1, "B01", raster_version="v3")
+        xr.testing.assert_allclose(ds_mod_v1, da_v1)
         self.assertEqual(1, len(cm.output))
         msg = (
             "WARNING:xcube.stac:Stac extension raster exists only for version 'v1' "
@@ -160,8 +126,8 @@ def test_apply_offset_scaling(self):
 
         item_v1.stac_extensions = []
         with self.assertLogs("xcube.stac", level="WARNING") as cm:
-            ds__mod_v1 = apply_offset_scaling(ds_v1, item_v1, asset_name="B01")
-        xr.testing.assert_allclose(ds_v1, ds__mod_v1)
+            ds_mod_v1 = apply_offset_scaling(da_v1, item_v1, asset_name="B01")
+        xr.testing.assert_allclose(ds_mod_v1, da_v1)
         self.assertEqual(1, len(cm.output))
         msg = (
             "WARNING:xcube.stac:The item 'example-item' is not conform to "

test/test_href_parse.py

@@ -128,7 +128,7 @@ def test_assert_aws_s3_region_name(self):
         self.assertEqual(
             (
                 f"Region name {region_name!r} extracted from the href {href!r} "
-                f"is not supported by AWS S3"
+                "is not supported by AWS S3"
             ),
             f"{cm.exception}",
         )

test/test_stack.py

@@ -0,0 +1,102 @@
+# The MIT License (MIT)
+# Copyright (c) 2024 by the xcube development team and contributors
+#
+# Permission is hereby granted, free of charge, to any person obtaining a
+# copy of this software and associated documentation files (the "Software"),
+# to deal in the Software without restriction, including without limitation
+# the rights to use, copy, modify, merge, publish, distribute, sublicense,
+# and/or sell copies of the Software, and to permit persons to whom the
+# Software is furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in all
+# copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NON INFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+# SOFTWARE.
+import unittest
+
+import numpy as np
+import xarray as xr
+
+from xcube_stac.stack import mosaic_take_first
+
+
+class UtilsTest(unittest.TestCase):
+
+    def test_mosaic_take_first(self):
+        list_ds = []
+        # first tile
+        data = np.array(
+            [
+                [[1, 2, 3], [4, 5, 6], [7, 8, 9]],
+                [[10, 11, 12], [13, 14, np.nan], [np.nan, np.nan, np.nan]],
+                [[19, 20, 21], [np.nan, np.nan, np.nan], [np.nan, np.nan, np.nan]],
+            ],
+            dtype=float,
+        )
+        dims = ("time", "lat", "lon")
+        coords = {
+            "time": np.array(
+                ["2025-01-01", "2025-01-02", "2025-01-03"], dtype="datetime64"
+            ),
+            "lat": [10.0, 20.0, 30.0],
+            "lon": [100.0, 110.0, 120.0],
+        }
+        da = xr.DataArray(data, dims=dims, coords=coords)
+        crs = xr.DataArray(np.array(0), attrs=dict(crs_wkt="testing"))
+        list_ds.append(xr.Dataset({"B01": da, "crs": crs}))
+        # second tile
+        data = np.array(
+            [
+                [[np.nan, np.nan, np.nan], [np.nan, np.nan, 106], [107, 108, 109]],
+                [[np.nan, np.nan, np.nan], [113, 114, 115], [116, 117, 118]],
+                [[np.nan, np.nan, 120], [121, 122, 123], [124, 125, 126]],
+            ],
+            dtype=float,
+        )
+        dims = ("time", "lat", "lon")
+        coords = {
+            "time": np.array(
+                ["2025-01-01", "2025-01-02", "2025-01-04"], dtype="datetime64"
+            ),
+            "lat": [10.0, 20.0, 30.0],
+            "lon": [100.0, 110.0, 120.0],
+        }
+        da = xr.DataArray(data, dims=dims, coords=coords)
+        crs = xr.DataArray(np.array(0), attrs=dict(crs_wkt="testing"))
+        list_ds.append(xr.Dataset({"B01": da, "crs": crs}))
+
+        # test only one tile
+        dts = np.array(["2025-01-01", "2025-01-02", "2025-01-03"], dtype="datetime64")
+        ds_test = mosaic_take_first(list_ds[:1], dts)
+        xr.testing.assert_allclose(ds_test, list_ds[0])
+
+        # test two tiles
+        dts = np.array(
+            ["2025-01-01", "2025-01-02", "2025-01-03", "2025-01-04"], dtype="datetime64"
+        )
+        ds_test = mosaic_take_first(list_ds, dts)
+        data = np.array(
+            [
+                [[1, 2, 3], [4, 5, 6], [7, 8, 9]],
+                [[10, 11, 12], [13, 14, 115], [116, 117, 118]],
+                [[19, 20, 21], [np.nan, np.nan, np.nan], [np.nan, np.nan, np.nan]],
+                [[np.nan, np.nan, 120], [121, 122, 123], [124, 125, 126]],
+            ],
+            dtype=float,
+        )
+        dims = ("time", "lat", "lon")
+        coords = {
+            "time": dts,
+            "lat": [10.0, 20.0, 30.0],
+            "lon": [100.0, 110.0, 120.0],
+        }
+        da = xr.DataArray(data, dims=dims, coords=coords)
+        crs = xr.DataArray(np.array(0), attrs=dict(crs_wkt="testing"))
+        ds_expected = xr.Dataset({"B01": da, "crs": crs})
+        xr.testing.assert_allclose(ds_test, ds_expected)