address too many warnings from tests

odc/stats/plugins/lc_ml_treelite.py

@@ -219,7 +219,7 @@ def reduce(self, xx: xr.Dataset) -> xr.Dataset:
 
         res = self.aggregate_results_from_group(res)
         attrs = xx.attrs.copy()
-        dims = list(xx.dims.keys())[:2]
+        dims = list(xx.sizes.keys())[:2]
         data_vars = {"predict_output": xr.DataArray(res, dims=dims, attrs=attrs)}
         coords = {dim: xx.coords[dim] for dim in dims}
         return xr.Dataset(data_vars=data_vars, coords=coords, attrs=attrs)

tests/test_fc_percentiles.py

@@ -46,7 +46,6 @@ def dataset():
     coords = {
         "x": np.linspace(10, 20, band_1.shape[2]),
         "y": np.linspace(0, 5, band_1.shape[1]),
-        "spec": index,
     }
 
     data_vars = {
@@ -57,6 +56,7 @@ def dataset():
         "ue": xr.DataArray(band_3, dims=("spec", "y", "x")),
     }
     xx = xr.Dataset(data_vars=data_vars, coords=coords)
+    xx = xx.assign_coords(xr.Coordinates.from_pandas_multiindex(index, "spec"))
 
     return xx
 
@@ -110,10 +110,6 @@ def test_native_transform(dataset, bits):
 def test_fusing(dataset):
     stats_fcp = StatsFCP()
     xx = stats_fcp.native_transform(dataset)
-    for dim in xx.dims:
-        if isinstance(xx.get_index(dim), pd.MultiIndex):
-            xx = xx.reset_index(dim)
-    xx = xx.set_xindex("solar_day")
     xx = xx.groupby("solar_day").map(partial(StatsFCP.fuser, None))
     assert xx["band_1"].attrs["test_attr"] == 57
 
@@ -142,11 +138,6 @@ def test_fusing(dataset):
     # Test fusing with UE filter and sum 120 limit
     stats_fcp_ue30_sum120 = StatsFCP(ue_threshold=30, max_sum_limit=120)
     xx_ue30_sum120 = stats_fcp_ue30_sum120.native_transform(dataset)
-    for dim in xx_ue30_sum120.dims:
-        if isinstance(xx_ue30_sum120.get_index(dim), pd.MultiIndex):
-            xx_ue30_sum120 = xx_ue30_sum120.reset_index(dim)
-    xx_ue30_sum120 = xx_ue30_sum120.set_xindex("solar_day")
-
     xx_ue30_sum120 = xx_ue30_sum120.groupby("solar_day").map(
         partial(StatsFCP.fuser, None)
     )
@@ -164,10 +155,6 @@ def test_fusing(dataset):
 def test_reduce(dataset):
     stats_fcp = StatsFCP(count_valid=True)
     xx = stats_fcp.native_transform(dataset)
-    for dim in xx.dims:
-        if isinstance(xx.get_index(dim), pd.MultiIndex):
-            xx = xx.reset_index(dim)
-    xx = xx.set_xindex("solar_day")
     xx = xx.groupby("solar_day").map(partial(StatsFCP.fuser, None))
     xx = xx.compute()
     xx = stats_fcp.reduce(xx)

tests/test_gm_ls_bitmask.py

@@ -36,7 +36,6 @@ def dataset(usgs_ls8_sr_definition):
     coords = {
         "x": np.linspace(10, 20, band_red.shape[2]),
         "y": np.linspace(0, 5, band_pq.shape[1]),
-        "spec": index,
     }
     pq_flags_definition = {}
     for measurement in usgs_ls8_sr_definition["measurements"]:
@@ -55,6 +54,7 @@ def dataset(usgs_ls8_sr_definition):
         "QA_PIXEL": (("spec", "y", "x"), band_pq, attrs),
     }
     xx = xr.Dataset(data_vars=data_vars, coords=coords)
+    xx = xx.assign_coords(xr.Coordinates.from_pandas_multiindex(index, "spec"))
     xx["band_red"].attrs["nodata"] = 0
     return xx
 

tests/test_landcover_plugin_a0.py

@@ -47,14 +47,14 @@ def dataset_md():
     coords = {
         "x": np.linspace(10, 20, band_1.shape[2]),
         "y": np.linspace(0, 5, band_1.shape[1]),
-        "spec": index,
     }
     data_vars = {
         "band_1": xr.DataArray(
             band_1, dims=("spec", "y", "x"), attrs={"nodata": np.nan}
         ),
     }
     xx = xr.Dataset(data_vars=data_vars, coords=coords)
+    xx = xx.assign_coords(xr.Coordinates.from_pandas_multiindex(index, "spec"))
     return xx
 
 
@@ -301,7 +301,6 @@ def fc_wo_dataset():
     coords = {
         "x": np.linspace(10, 20, water.shape[2]),
         "y": np.linspace(0, 5, water.shape[1]),
-        "spec": index,
     }
     data_vars = {
         "water": xr.DataArray(water, dims=("spec", "y", "x"), attrs={"nodata": 1}),
@@ -311,6 +310,7 @@ def fc_wo_dataset():
         "bs": xr.DataArray(bs, dims=("spec", "y", "x"), attrs={"nodata": 255}),
     }
     xx = xr.Dataset(data_vars=data_vars, coords=coords)
+    xx = xx.assign_coords(xr.Coordinates.from_pandas_multiindex(index, "spec"))
 
     return xx
 

tests/test_landcover_plugin_a1.py

@@ -98,7 +98,6 @@ def dataset():
     coords = {
         "x": np.linspace(10, 20, wo_fq.shape[2]),
         "y": np.linspace(0, 5, wo_fq.shape[1]),
-        "spec": index,
     }
     data_vars = {
         "frequency": xr.DataArray(
@@ -122,6 +121,7 @@ def dataset():
         ),
     }
     xx = xr.Dataset(data_vars=data_vars, coords=coords)
+    xx = xx.assign_coords(xr.Coordinates.from_pandas_multiindex(index, "spec"))
     return xx
 
 

tests/test_lc_l34.py

@@ -103,7 +103,6 @@ def image_groups():
     coords = {
         "x": np.linspace(10, 20, l34.shape[2]),
         "y": np.linspace(0, 5, l34.shape[1]),
-        "spec": index,
     }
 
     data_vars = {
@@ -145,6 +144,7 @@ def image_groups():
     }
 
     xx = xr.Dataset(data_vars=data_vars, coords=coords)
+    xx = xx.assign_coords(xr.Coordinates.from_pandas_multiindex(index, "spec"))
     return xx
 
 

tests/test_lc_l4_ctv.py

@@ -24,7 +24,6 @@ def image_groups(l34, urban, cultivated, woody, pv_pc_50):
     coords = {
         "x": np.linspace(10, 20, l34.shape[2]),
         "y": np.linspace(0, 5, l34.shape[1]),
-        "spec": index,
     }
 
     data_vars = {
@@ -55,6 +54,7 @@ def image_groups(l34, urban, cultivated, woody, pv_pc_50):
         ),
     }
     xx = xr.Dataset(data_vars=data_vars, coords=coords)
+    xx = xx.assign_coords(xr.Coordinates.from_pandas_multiindex(index, "spec"))
     return xx
 
 

tests/test_lc_l4_natural_surface.py

@@ -33,7 +33,6 @@ def image_groups(l34, urban, woody, bs_pc_50, pv_pc_50, cultivated, water_freque
     coords = {
         "x": np.linspace(10, 20, l34.shape[2]),
         "y": np.linspace(0, 5, l34.shape[1]),
-        "spec": index,
     }
 
     data_vars = {
@@ -74,6 +73,7 @@ def image_groups(l34, urban, woody, bs_pc_50, pv_pc_50, cultivated, water_freque
         ),
     }
     xx = xr.Dataset(data_vars=data_vars, coords=coords)
+    xx = xx.assign_coords(xr.Coordinates.from_pandas_multiindex(index, "spec"))
     return xx
 
 

tests/test_lc_l4_nav.py

@@ -31,7 +31,6 @@ def image_groups(l34, urban, cultivated, woody, pv_pc_50, water_frequency):
     coords = {
         "x": np.linspace(10, 20, l34.shape[2]),
         "y": np.linspace(0, 5, l34.shape[1]),
-        "spec": index,
     }
 
     data_vars = {
@@ -67,6 +66,7 @@ def image_groups(l34, urban, cultivated, woody, pv_pc_50, water_frequency):
         ),
     }
     xx = xr.Dataset(data_vars=data_vars, coords=coords)
+    xx = xx.assign_coords(xr.Coordinates.from_pandas_multiindex(index, "spec"))
     return xx
 
 
@@ -238,10 +238,10 @@ def test_ntv_veg_cover():
     water_frequency = np.array(
         [
             [
-                [-999, -999, -999],
-                [-999, -999, -999],
-                [-999, -999, -999],
-                [-999, -999, -999],
+                [255, 255, 255],
+                [255, 255, 255],
+                [255, 255, 255],
+                [255, 255, 255],
             ]
         ],
         dtype="uint8",
@@ -339,10 +339,10 @@ def test_ntv_woody_veg_cover():
     water_frequency = np.array(
         [
             [
-                [-9999, -9999, -9999],
-                [-9999, -9999, -9999],
-                [-9999, -9999, -9999],
-                [-9999, -9999, -9999],
+                [255, 255, 255],
+                [255, 255, 255],
+                [255, 255, 255],
+                [255, 255, 255],
             ]
         ],
         dtype="uint8",
@@ -638,10 +638,10 @@ def test_ntv_herbaceous_veg_cover():
     water_frequency = np.array(
         [
             [
-                [-9999, -9999, -9999],
-                [-9999, -9999, -9999],
-                [-9999, -9999, -9999],
-                [-9999, -9999, -9999],
+                [255, 255, 255],
+                [255, 255, 255],
+                [255, 255, 255],
+                [255, 255, 255],
             ]
         ],
         dtype="uint8",

tests/test_lc_l4_ntv.py

@@ -28,7 +28,6 @@ def image_groups(l34, urban, cultivated, woody, pv_pc_50):
     coords = {
         "x": np.linspace(10, 20, l34.shape[2]),
         "y": np.linspace(0, 5, l34.shape[1]),
-        "spec": index,
     }
 
     data_vars = {
@@ -59,6 +58,7 @@ def image_groups(l34, urban, cultivated, woody, pv_pc_50):
         ),
     }
     xx = xr.Dataset(data_vars=data_vars, coords=coords)
+    xx = xx.assign_coords(xr.Coordinates.from_pandas_multiindex(index, "spec"))
     return xx
 
 

tests/test_lc_l4_water.py

@@ -29,7 +29,6 @@ def image_groups(l34, urban, cultivated, woody, bs_pc_50, pv_pc_50, water_freque
     coords = {
         "x": np.linspace(10, 20, l34.shape[2]),
         "y": np.linspace(0, 5, l34.shape[1]),
-        "spec": index,
     }
 
     data_vars = {
@@ -70,6 +69,7 @@ def image_groups(l34, urban, cultivated, woody, bs_pc_50, pv_pc_50, water_freque
         ),
     }
     xx = xr.Dataset(data_vars=data_vars, coords=coords)
+    xx = xx.assign_coords(xr.Coordinates.from_pandas_multiindex(index, "spec"))
     return xx
 
 

tests/test_lc_level3.py

@@ -61,7 +61,6 @@ def image_groups():
     coords = {
         "x": np.linspace(10, 20, l34.shape[2]),
         "y": np.linspace(0, 5, l34.shape[1]),
-        "spec": index,
     }
 
     data_vars = {
@@ -82,6 +81,7 @@ def image_groups():
         ),
     }
     xx = xr.Dataset(data_vars=data_vars, coords=coords)
+    xx = xx.assign_coords(xr.Coordinates.from_pandas_multiindex(index, "spec"))
     return xx
 
 

tests/test_pq_bitmask.py

@@ -36,7 +36,6 @@ def dataset(usgs_ls8_sr_definition):
     coords = {
         "x": np.linspace(10, 20, band_red.shape[2]),
         "y": np.linspace(0, 5, band_pq.shape[1]),
-        "spec": index,
     }
     pq_flags_definition = {}
     for measurement in usgs_ls8_sr_definition["measurements"]:
@@ -55,6 +54,7 @@ def dataset(usgs_ls8_sr_definition):
         "QA_PIXEL": (("spec", "y", "x"), band_pq, attrs),
     }
     xx = xr.Dataset(data_vars=data_vars, coords=coords, attrs=attrs)
+    xx = xx.assign_coords(xr.Coordinates.from_pandas_multiindex(index, "spec"))
     xx["band_red"].attrs["nodata"] = 0
     return xx
 

tests/test_rf_models.py

@@ -497,7 +497,7 @@ def test_cultivated_reduce(
     ).all()
 
     with pytest.raises(SystemExit) as excinfo:
-        cultivated.reduce(input_datasets.drop("classes_l3_l4"))
+        cultivated.reduce(input_datasets.drop_vars("classes_l3_l4"))
     assert excinfo.value.code == 0
 
 

tests/test_wofs.py

@@ -32,13 +32,13 @@ def dataset():
     coords = {
         "x": np.linspace(10, 20, band_1.shape[2]),
         "y": np.linspace(0, 5, band_1.shape[1]),
-        "spec": index,
     }
 
     data_vars = {
         "water": xr.DataArray(band_1, dims=("spec", "y", "x"), attrs={"nodata": 0}),
     }
     xx = xr.Dataset(data_vars=data_vars, coords=coords)
+    xx = xx.assign_coords(xr.Coordinates.from_pandas_multiindex(index, "spec"))
 
     return xx
 
@@ -78,10 +78,6 @@ def test_native_transform(dataset):
 def test_fusing(dataset):
     stats_wofs = StatsWofs()
     out_xx = stats_wofs.native_transform(dataset)
-    for dim in out_xx.dims:
-        if isinstance(out_xx.get_index(dim), pd.MultiIndex):
-            out_xx = out_xx.reset_index(dim)
-    out_xx = out_xx.set_xindex("solar_day")
 
     out_xx = out_xx.groupby("solar_day").map(partial(stats_wofs.fuser))
     out_xx.load()
@@ -113,11 +109,6 @@ def test_fusing(dataset):
 def test_reduce(dataset):
     stats_wofs = StatsWofs()
     out_xx = stats_wofs.native_transform(dataset)
-    for dim in out_xx.dims:
-        if isinstance(out_xx.get_index(dim), pd.MultiIndex):
-            out_xx = out_xx.reset_index(dim)
-    out_xx = out_xx.set_xindex("solar_day")
-
     out_xx = out_xx.groupby("solar_day").map(partial(stats_wofs.fuser))
     out_xx = stats_wofs.reduce(out_xx)
     assert out_xx.count_wet.attrs.get("nodata", 0) == -999