r.learn.ml2 bug fix to prediction when values in training map are not…

… labelled
OSGeo · May 29, 2020 · d033fe0 · d033fe0
1 parent 037e38d
commit d033fe0
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Showing 3 changed files with 8 additions and 5 deletions.
diff --git a/grass7/raster/r.learn.ml2/r.learn.predict/r.learn.predict.py b/grass7/raster/r.learn.ml2/r.learn.predict/r.learn.predict.py
@@ -156,11 +156,11 @@ def main():
         )
 
     # assign categories for classification map
-    if class_labels is not None and prob_only is False:
+    if class_labels and prob_only is False:
         rules = []
 
         for val, lab in class_labels.items():
-            rules.append(",".join([str(val), lab]))
+            rules.append(",".join([str(val), str(lab)]))
 
         rules = "\n".join(rules)
         rules_file = string_to_rules(rules)

diff --git a/grass7/raster/r.learn.ml2/r.learn.train/r.learn.train.py b/grass7/raster/r.learn.ml2/r.learn.train/r.learn.train.py
@@ -576,9 +576,12 @@ def main():
             y = y.flatten()
 
             with RasterRow(training_map) as src:
-                class_labels = {v: k for (k, v, m) in src.cats}
-
-                if "" in class_labels.values():
+
+                if mode == "classification":
+                    src_cats = {v: k for (k, v, m) in src.cats}
+                    class_labels = {k:k for k in np.unique(y)}
+                    class_labels.update(src_cats)
+                else:
                     class_labels = None
 
         elif training_points != "":

diff --git a/grass7/raster/r.learn.ml2/testsuite/test_keyvalue_result.txt b/grass7/raster/r.learn.ml2/testsuite/test_keyvalue_result.txt