set high ue but valid data as non-veg

opendatacube · Dec 2, 2024 · 30b6f13 · 30b6f13
1 parent 7e56476
commit 30b6f13
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Showing 2 changed files with 50 additions and 20 deletions.
diff --git a/odc/stats/plugins/lc_fc_wo_a0.py b/odc/stats/plugins/lc_fc_wo_a0.py
@@ -73,48 +73,76 @@ def native_transform(self, xx):
         xx = xx.drop_vars(["water"])
 
         # get valid wo pixels, both dry and wet
-        data = expr_eval(
+        wet = expr_eval(
             "where(a|b, a, _nan)",
             {"a": wet.data, "b": valid.data},
             name="get_valid_pixels",
             dtype="float32",
             **{"_nan": np.nan},
         )
 
-        # Pick out the fc pixels that have an unmixing error of less than the threshold
-        valid &= xx["ue"] < self.ue_threshold
+        # get high ue pixels
+        ue = expr_eval(
+            "where((a<_v), _nan, 1)",
+            {"a": xx["ue"].data},
+            name="get_high_ue",
+            dtype="float32",
+            **{"_v": self.ue_threshold, "_nan": np.nan},
+        )
         xx = xx.drop_vars(["ue"])
+
+        # Pick out the fc pixels that have an unmixing error of less than the threshold
+        valid = expr_eval(
+            "where(a&(b!=b), 1, 0)",
+            {"a": valid.data, "b": ue},
+            name="get_valid_pixels",
+            dtype="bool",
+        )
+        valid = xr.DataArray(valid, dims=xx["pv"].dims, coords=xx["pv"].coords)
+
         xx = keep_good_only(xx, valid, nodata=NODATA)
         xx = to_float(xx, dtype="float32")
-
-        xx["wet"] = xr.DataArray(data, dims=wet.dims, coords=wet.coords)
+        xx["wet"] = xr.DataArray(wet, dims=xx["pv"].dims, coords=xx["pv"].coords)
+        xx["ue"] = xr.DataArray(ue, dims=xx["pv"].dims, coords=xx["pv"].coords)
 
         return xx
 
     def fuser(self, xx):
 
         wet = xx["wet"]
+        ue = xx["ue"]
 
-        xx = _xr_fuse(xx.drop_vars(["wet"]), partial(_fuse_mean_np, nodata=np.nan), "")
+        xx = _xr_fuse(
+            xx.drop_vars(["wet", "ue"]),
+            partial(_fuse_mean_np, nodata=np.nan),
+            "fuse_fc",
+        )
 
         xx["wet"] = _nodata_fuser(wet, nodata=np.nan)
+        xx["ue"] = _nodata_fuser(ue, nodata=np.nan)
 
         return xx
 
     def _veg_or_not(self, xx: xr.Dataset):
-        # either pv or npv > bs: 1
+        # pv or npv > bs: 1
         # otherwise 0
         data = expr_eval(
             "where((a>b)|(c>b), 1, 0)",
-            {"a": xx["pv"].data, "c": xx["npv"].data, "b": xx["bs"].data},
+            {
+                "a": xx["pv"].data,
+                "c": xx["npv"].data,
+                "b": xx["bs"].data,
+                "d": xx["ue"].data,
+            },
             name="get_veg",
             dtype="uint8",
         )
 
-        # mark nans
+        # mark nans only if not valid & low ue
+        # if any high ue (c is not nan): 0
         data = expr_eval(
-            "where(a!=a, nodata, b)",
-            {"a": xx["pv"].data, "b": data},
+            "where((a!=a)&(c!=c), nodata, b)",
+            {"a": xx["pv"].data, "c": xx["ue"].data, "b": data},
             name="get_veg",
             dtype="uint8",
             **{"nodata": int(NODATA)},

diff --git a/tests/test_landcover_plugin_a0.py b/tests/test_landcover_plugin_a0.py
@@ -409,14 +409,15 @@ def test_reduce(fc_wo_dataset):
     xx = stats_veg.reduce(xx).compute()
     expected_value = np.array(
         [
-            [1, 255, 0, 255, 255, 255, 255],
-            [1, 255, 255, 255, 255, 255, 255],
-            [255, 0, 255, 255, 1, 255, 255],
-            [255, 255, 1, 255, 255, 255, 255],
-            [255, 255, 255, 255, 255, 255, 255],
-            [255, 1, 255, 255, 255, 255, 255],
-            [255, 255, 255, 255, 255, 255, 0],
-        ]
+            [1, 0, 0, 0, 0, 0, 0],
+            [1, 0, 0, 0, 0, 0, 0],
+            [0, 0, 0, 0, 1, 0, 0],
+            [0, 0, 1, 0, 0, 0, 0],
+            [0, 0, 0, 0, 0, 0, 0],
+            [0, 1, 0, 0, 0, 0, 0],
+            [0, 0, 0, 0, 0, 0, 0],
+        ],
+        dtype="uint8",
     )
 
     assert (xx.veg_frequency.data == expected_value).all()
@@ -430,7 +431,8 @@ def test_reduce(fc_wo_dataset):
             [255, 255, 255, 255, 255, 255, 255],
             [255, 0, 255, 255, 255, 0, 255],
             [255, 255, 255, 0, 255, 255, 1],
-        ]
+        ],
+        dtype="uint8",
     )
 
     assert (xx.water_frequency.data == expected_value).all()