Merge pull request #1071 from EnMAP-Box/1070-classification-layer-acc…

…uracy-report-keyerror-accuracy resolved #1070
EnMAP-Box · Jan 20, 2025 · abd1e02 · abd1e02
2 parents 5c3a667 + d074094
commit abd1e02
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Showing 2 changed files with 35 additions and 2 deletions.
diff --git a/enmapboxprocessing/algorithm/classificationperformancesimplealgorithm.py b/enmapboxprocessing/algorithm/classificationperformancesimplealgorithm.py
@@ -16,7 +16,8 @@
 from enmapboxprocessing.rasterreader import RasterReader
 from enmapboxprocessing.reportwriter import MultiReportWriter, HtmlReportWriter, CsvReportWriter
 from enmapboxprocessing.utils import Utils
-from qgis.core import QgsProcessingContext, QgsProcessingFeedback, QgsRasterLayer, QgsVectorLayer
+from qgis.core import QgsProcessingContext, QgsProcessingFeedback, QgsRasterLayer, QgsVectorLayer, \
+    QgsProcessingException
 
 
 @typechecked
@@ -124,6 +125,8 @@ def processAlgorithm(
             feedback.pushInfo('Estimate statistics and create report')
             classValues = [c.value for c in categoriesReference]
             classNames = [c.name for c in categoriesReference]
+            if not np.isin(yMap, classValues).all():
+                raise QgsProcessingException('Predicted values not matching reference classes.')
             stats = accuracyAssessment(yReference, yMap, classNames, classValues)
 
             self.writeReport(filename, stats, classNamesMatching)

diff --git a/...s/enmap-box/enmapboxprocessing/algorithm/test_ClassificationPerformanceSimpleAlgorithm.py b/...s/enmap-box/enmapboxprocessing/algorithm/test_ClassificationPerformanceSimpleAlgorithm.py
@@ -10,7 +10,7 @@
 from enmapboxprocessing.typing import Category
 from enmapboxprocessing.utils import Utils
 from enmapboxtestdata import landcover_map_l3
-from qgis.core import QgsRasterLayer, QgsMapLayer
+from qgis.core import QgsRasterLayer, QgsMapLayer, QgsProcessingException
 
 
 class TestClassificationPerformanceSimpleAlgorithm(TestCase):
@@ -129,3 +129,33 @@ def test_twoClass(self):
         self.assertEqual(77, int(stats['overallAccuracy'] * 100))
         self.assertListEqual([100, 33], [int(v * 100) for v in stats['usersAccuracy']])
         self.assertListEqual([75, 100], [int(v * 100) for v in stats['producersAccuracy']])
+
+    def test_issue1070(self):
+        # handle unclassified data
+        categories = [Category(1, 'c1', '#000000'), Category(2, 'c2', '#000000')]
+        writer1 = self.rasterFromArray([[[1, 2]]], 'observation.tif')
+        writer1.close()
+        raster1 = QgsRasterLayer(writer1.source())
+        renderer = Utils().palettedRasterRendererFromCategories(raster1.dataProvider(), 1, categories)
+        raster1.setRenderer(renderer.clone())
+        raster1.saveDefaultStyle(QgsMapLayer.StyleCategory.AllStyleCategories)
+
+        writer2 = self.rasterFromArray([[[0, 2]]], 'prediction.tif')  # introduce unclassified data
+        writer2.close()
+        raster2 = QgsRasterLayer(writer2.source())
+        renderer = Utils().palettedRasterRendererFromCategories(raster2.dataProvider(), 1, categories)
+        raster2.setRenderer(renderer.clone())
+        raster2.saveDefaultStyle(QgsMapLayer.StyleCategory.AllStyleCategories)
+
+        alg = ClassificationPerformanceSimpleAlgorithm()
+        alg.initAlgorithm()
+        parameters = {
+            alg.P_CLASSIFICATION: writer2.source(),
+            alg.P_REFERENCE: writer1.source(),
+            alg.P_OPEN_REPORT: self.openReport,
+            alg.P_OUTPUT_REPORT: self.filename('report.html'),
+        }
+        try:
+            self.runalg(alg, parameters)
+        except QgsProcessingException as error:
+            assert str(error) == 'Predicted values not matching reference classes.'