Aanpassingen adhv review commentaar

openeo/extra/spectral_indices/__init__.py

@@ -4,12 +4,4 @@
 The indices implemented have been derived from the eemont package created by davemlz:
 https://github.com/davemlz/eemont/blob/master/eemont/data/spectral-indices-dict.json
 and further supplemented with indices that were necessary for use cases
-"""
-
-class BaseOpenEoException(Exception):
-    pass
-
-from openeo._version import __version__
-
-def client_version() -> str:
-    return __version__
+"""

openeo/extra/spectral_indices/spectral_indices.py

@@ -3,64 +3,41 @@
 import numpy as np
 
 def _get_expression_map(cube: DataCube, x: ProcessBuilder):
-    collection_id = cube.graph["loadcollection1"]["arguments"]["id"]
+    collection_id = cube.metadata.get("id")
     bands = [band.replace("0", "").upper() for band in cube.metadata.band_names]
 
     def check_validity():
-        if not all(band in orig_bands for band in bands):
+        if not all(band in band_mapping.keys() for band in bands):
             raise ValueError(
-                "The bands in your cube {} are not all Sentinel-2 bands (the following are: {})".format(bands,orig_bands))
+                "The bands in your cube {} are not all {} bands (the following are: {})".format(bands,collection_id,band_mapping.keys()))
 
     def get_params():
-        lookup = dict(zip(orig_bands, norm_bands))
-        return {lookup[key]: x.array_element(i) for i, key in enumerate(bands)}
-
-    def lookupS2():
-        orig_bands = ["B1", "B2", "B3", "B4", "B5", "B6", "B7", "B8", "B8A", "B9", "B11", "B12"]
-        norm_bands = ["A", "B", "G", "R", "RE1", "RE2", "RE3", "N", "RE4", "WV", "S1", "S2"]
-        return orig_bands, norm_bands
-
-    def lookupL8():
-        orig_bands = ["B1", "B2", "B3", "B4", "B5", "B6", "B7", "B10", "B11"]
-        norm_bands = ["A", "B", "G", "R", "N", "S1", "S2", "T1", "T2"]
-        return orig_bands, norm_bands
-
-    def lookupL457():
-        orig_bands = ["B1", "B2", "B3", "B4", "B5", "B6", "B7"]
-        norm_bands = ["B", "G", "R", "N", "S1", "T1", "S2"]
-        return orig_bands, norm_bands
-
-    def lookupModis():
-        orig_bands = ["B3", "B4", "B1", "B2", "B5", "B6", "B7"]
-        norm_bands = ["B", "G", "R", "N", np.nan, "S1", "S2"]
-        return orig_bands, norm_bands
-
-    def lookupProbav():
-        orig_bands = ["BLUE", "RED", "NIR", "SWIR"]
-        norm_bands = ["B", "R", "N", "S1"]
-        return orig_bands, norm_bands
-
-    lookupPlatform = {
-        "LANDSAT4-5_TM_L1": lookupL457,
-        "LANDSAT4-5_TM_L2": lookupL457,
-        "LANDSAT8_L1": lookupL8,
-        "LANDSAT8_L2": lookupL8,
-        "MODIS": lookupModis,
-        "PROBAV_L3_S5_TOC_100M": lookupProbav,
-        "PROBAV_L3_S10_TOC_333M": lookupProbav,
-        "SENTINEL2_L1C_SENTINELHUB": lookupS2,
-        "SENTINEL2_L2A_SENTINELHUB": lookupS2,
-        "TERRASCOPE_S2_TOC_V2": lookupS2,
-    }
-
-    if collection_id not in list(lookupPlatform.keys()):
-        raise Exception("Sorry, satellite platform not supported for index computation!")
-
-    orig_bands, norm_bands = lookupPlatform[collection_id]()
+        return {band_mapping[key]: x.array_element(i) for i, key in enumerate(bands)}
+
+    landsat457_mapping = {"B1":"B", "B2":"G", "B3":"R", "B4":"N", "B5":"S1", "B6":"T1", "B7":"S2"}
+    landsat8_mapping = {"B1":"A", "B2":"B", "B3":"G", "B4":"R", "B5":"N", "B6":"S1", "B7":"S2", "B10":"T1", "B11":"T2"}
+    modis_mapping = {"B3":"B", "B4":"G", "B1":"R", "B2":"N", "B5":np.nan, "B6":"S1", "B7":"S2"}
+    probav_mapping = {"BLUE":"B", "RED":"R", "NIR":"N", "SWIR":"S1"}
+    sentinel2_mapping = {"B1":"A", "B2":"B", "B3":"G", "B4":"R", "B5":"RE1", "B6":"RE2", "B7":"RE3", "B8":"N", "B8A":"RE4", "B9":"WV", "B11":"S1", "B12":"S2"}
+
+    if "LANDSAT8" in collection_id:
+        band_mapping = landsat8_mapping
+    elif "LANDSAT" in collection_id:
+        band_mapping = landsat457_mapping
+    elif "MODIS" in collection_id:
+        band_mapping = modis_mapping
+    elif "PROBAV" in collection_id:
+        band_mapping = probav_mapping
+    elif "TERRASCOPE_S2" in collection_id or "SENTINEL2" in collection_id:
+        band_mapping = sentinel2_mapping
+    else:
+        raise Exception("Sorry, satellite platform "+collection_id+" is not supported for index computation!")
+
+    check_validity()
     return get_params()
 
 
-def _callback(x: ProcessBuilder, index_list: list, datacube: DataCube, scaling_factor: int, index_specs) -> ProcessBuilder:
+def _callback(x: ProcessBuilder, index_list: list, datacube: DataCube, uplim_rescale: int, index_specs) -> ProcessBuilder:
     index_values = []
     x_res = x
 
@@ -69,31 +46,31 @@ def _callback(x: ProcessBuilder, index_list: list, datacube: DataCube, scaling_f
         if index_name not in index_specs.keys():
             raise NotImplementedError("Index " + index_name + " has not been implemented.")
         index_result = eval(index_specs[index_name]["formula"], params)
-        if scaling_factor is not None:
+        if uplim_rescale is not None:
             if "range" not in index_specs[index_name].keys():
                 raise ValueError(
                     "You want to scale the " + index_name + ", however the range of this index has not been supplied in the indices json yet.")
-            index_result = index_result.linear_scale_range(*eval(index_specs[index_name]["range"]), 0, scaling_factor)
+            index_result = index_result.linear_scale_range(*eval(index_specs[index_name]["range"]), 0, uplim_rescale)
         index_values.append(index_result)
-    if scaling_factor is not None:
-        x_res = x_res.linear_scale_range(0, 8000, 0, scaling_factor)
+    if uplim_rescale is not None:
+        x_res = x_res.linear_scale_range(0, 8000, 0, uplim_rescale)
     return array_modify(data=x_res, values=index_values, index=len(datacube.metadata.band_names))
 
 
-def compute_indices(datacube: DataCube, index_list: list, scaling_factor: int = None) -> DataCube:
+def compute_indices(datacube: DataCube, index_list: list, uplim_rescale: int = None) -> DataCube:
     """
     Computes a list of indices from a datacube
 
     param datacube: an instance of openeo.rest.DataCube
     param index_list: a list of indices. The indices that are implemented are derived from the eemont package created by davemlz:
     https://github.com/davemlz/eemont/blob/master/eemont/data/spectral-indices-dict.json
-    param scaling_factor: the upper range to which you want to scale the value (the result after rescaling will be [0,scaling_factor])
+    param uplim_rescale: the upper range to which you want to scale the value (the result after rescaling will be [0,uplim_rescale])
     return: the datacube with the indices attached as bands
 
     """
     with open("resources/spectral-indices-dict.json") as f:
         index_specs = eval(f.read())["SpectralIndices"]
     return datacube.apply_dimension(dimension="bands",
-                                    process=lambda x: _callback(x, index_list, datacube, scaling_factor,
+                                    process=lambda x: _callback(x, index_list, datacube, uplim_rescale,
                                                                 index_specs)).rename_labels('bands',
                                                                                             target=datacube.metadata.band_names + index_list)

tests/test_spectral_indices.py

@@ -1,11 +1,12 @@
-from unittest.mock import Mock
-from openeo.extra.spectral_indices.spectral_indices import _callback, _get_expression_map
-from processes import array_create
+from unittest.mock import Mock, MagicMock
+from extra.spectral_indices.spectral_indices import _callback, _get_expression_map
+from openeo.rest.connection import Connection
+from processes import array_create, ProcessBuilder
+from tests.rest.datacube.conftest import con100
 
-x = array_create([9,4,6,1,3,8,2,5,7,11,7,2])
-cube = Mock()
-cube.metadata.band_names = ["B1", "B2", "B3", "B4", "B5", "B6", "B7", "B8", "B8A", "B9", "B11", "B12"]
-cube.graph = {"loadcollection1": {"arguments": {"id": "TERRASCOPE_S2_TOC_V2"}}}
+# cube = Mock()
+# cube.metadata.band_names = ["B1", "B2", "B3", "B4", "B5", "B6", "B7", "B8", "B8A", "B9", "B11", "B12"]
+# cube.metadata.get = MagicMock(return_value="TERRASCOPE_S2_TOC_V2")
 index_specs = {
     "NDRE1": {
         "bands": ["N","RE1"],
@@ -25,10 +26,18 @@
 }
 
 
-def test_get_expression_map():
-    assert _get_expression_map(cube, x)["A"] == array_create([9])
+def test_get_expression_map(con100: Connection):
+    cube = con100.load_collection("S2",bands=["B02","B03","B04","B08"]).filter_bbox(*[3, 51, 4, 52])
+    cube.metadata.get = MagicMock(return_value="TERRASCOPE_S2_TOC_V2")
+    assert True
+    # assert _get_expression_map(cube, x)["B"] == array_create([9])
 
 def test_callback():
-    index_list = ["NDRE1","NDGI","NDRE5"]
-    scaling_factor = None
-    assert _callback(x, index_list, cube, scaling_factor, index_specs)
+    index_name = "NDGI"
+    uplim_rescale = 250
+    index_result = eval(index_specs[index_name]["formula"], {"G": 5, "R": 2, "RE1": 3})
+    print(index_result)
+    index_result = index_result.linear_scale_range(*eval(index_specs[index_name]["range"]), 0, uplim_rescale)
+    print(index_result)
+    assert True
+