add test for woody cover

tests/test_rf_models.py

@@ -5,6 +5,7 @@
     StatsCultivatedClass,
     generate_features,
 )
+from odc.stats.plugins.lc_treelite_woody import StatsWoodyCover
 from pathlib import Path
 import pytest
 import boto3
@@ -381,6 +382,33 @@ def test_genrate_features(cultivated_input_bands, input_arrays):
     assert np.allclose(res, expected_res, rtol=1e-6, atol=1e-8)
 
 
+@pytest.fixture(scope="module")
+def woody_input_bands():
+    return [
+        "nbart_blue",
+        "nbart_green",
+        "nbart_red",
+        "nbart_nir",
+        "nbart_swir_1",
+        "nbart_swir_2",
+        "classes_l3_l4",
+    ]
+
+
+@pytest.fixture(scope="module")
+def woody_results():
+    res = [
+        da.array([[20.1, 255.0], [19.5, 20.1]], dtype="float32"),
+        da.array([[19.5, 20.1], [255, 20.1]], dtype="float32"),
+    ]
+    return res
+
+
+@pytest.fixture(scope="module")
+def woody_classes():
+    return {"woody": 113, "herbaceous": 114}
+
+
 def test_preprocess_predict_intput(
     cultivated_input_bands,
     cultivated_model_path,
@@ -458,7 +486,47 @@ def test_cultivated_reduce(
     dask_client.register_plugin(cultivated.dask_worker_plugin)
     res = cultivated.reduce(input_datasets)
     assert res["cultivated_class"].attrs["nodata"] == 255
+    assert res["cultivated_class"].data.dtype == "uint8"
     assert (
         res["cultivated_class"].data.compute()
         == np.array([[112, 255], [112, 112]], dtype="uint8")
     ).all()
+
+
+def test_woody_aggregate_results(
+    woody_input_bands,
+    woody_model_path,
+    mask_bands,
+    woody_classes,
+    woody_results,
+):
+
+    woody_cover = StatsWoodyCover(
+        woody_classes, woody_model_path, mask_bands, input_bands=woody_input_bands
+    )
+    res = woody_cover.aggregate_results_from_group([woody_results[0]])
+    assert (res.compute() == np.array([[113, 255], [114, 113]], dtype="uint8")).all()
+    res = woody_cover.aggregate_results_from_group(woody_results)
+    assert (res.compute() == np.array([[114, 113], [114, 113]], dtype="uint8")).all()
+
+
+def test_woody_reduce(
+    woody_input_bands,
+    woody_model_path,
+    mask_bands,
+    woody_classes,
+    input_datasets,
+    dask_client,
+):
+    woody_inputs = input_datasets.sel(bands=woody_input_bands[:-1])
+    woody_cover = StatsWoodyCover(
+        woody_classes, woody_model_path, mask_bands, input_bands=woody_input_bands
+    )
+    dask_client.register_plugin(woody_cover.dask_worker_plugin)
+    res = woody_cover.reduce(woody_inputs)
+    assert res["woody_cover"].attrs["nodata"] == 255
+    assert res["woody_cover"].data.dtype == "uint8"
+    assert (
+        res["woody_cover"].data.compute()
+        == np.array([[114, 255], [114, 114]], dtype="uint8")
+    ).all()