Nomogram: Retain original compute_value

biolab · Apr 2, 2021 · c0174f9 · c0174f9
1 parent 704a837
commit c0174f9
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Showing 2 changed files with 24 additions and 0 deletions.
diff --git a/Orange/widgets/visualize/ownomogram.py b/Orange/widgets/visualize/ownomogram.py
@@ -1285,6 +1285,7 @@ def reconstruct_domain(original, preprocessed):
         for attr in preprocessed.attributes:
             cv = attr._compute_value.variable._compute_value
             var = cv.variable if cv else original[attr.name]
+            var = original[var.name] if var.name in original else attr
             if var in attrs:    # the reason for OrderedDict
                 continue
             attrs[var] = None   # we only need keys

diff --git a/Orange/widgets/visualize/tests/test_ownomogram.py b/Orange/widgets/visualize/tests/test_ownomogram.py
@@ -13,6 +13,7 @@
 from Orange.classification import (
     NaiveBayesLearner, LogisticRegressionLearner, MajorityLearner
 )
+from Orange.preprocess import Scale, Continuize
 from Orange.tests import test_filename
 from Orange.widgets.tests.base import WidgetTest
 from Orange.widgets.utils.state_summary import format_summary_details
@@ -306,6 +307,28 @@ def test_dots_stop_flashing(self):
         anim = animator._GraphicsColorAnimator__animation
         self.assertNotEqual(anim.state(), QPropertyAnimation.Running)
 
+    def test_reconstruct_domain(self):
+        data = Table("heart_disease")
+        cls = LogisticRegressionLearner()(data)
+        domain = OWNomogram.reconstruct_domain(cls.original_domain, cls.domain)
+        transformed_data = cls.original_data.transform(domain)
+        self.assertEqual(transformed_data.X.shape, data.X.shape)
+        self.assertFalse(np.isnan(transformed_data.X[0]).any())
+
+        scaled_data = Scale()(data)
+        cls = LogisticRegressionLearner()(scaled_data)
+        domain = OWNomogram.reconstruct_domain(cls.original_domain, cls.domain)
+        transformed_data = cls.original_data.transform(domain)
+        self.assertEqual(transformed_data.X.shape, scaled_data.X.shape)
+        self.assertFalse(np.isnan(transformed_data.X[0]).any())
+
+        disc_data = Continuize()(data)
+        cls = LogisticRegressionLearner()(disc_data)
+        domain = OWNomogram.reconstruct_domain(cls.original_domain, cls.domain)
+        transformed_data = cls.original_data.transform(domain)
+        self.assertEqual(transformed_data.X.shape, disc_data.X.shape)
+        self.assertFalse(np.isnan(transformed_data.X[0]).any())
+
 
 if __name__ == "__main__":
     unittest.main()