Improve the flow of several learning widgets

biolab · Dec 3, 2021 · 6176b2c · 6176b2c
1 parent a08cf60
commit 6176b2c
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Showing 4 changed files with 9 additions and 9 deletions.
diff --git a/Orange/widgets/model/owadaboost.py b/Orange/widgets/model/owadaboost.py
@@ -102,8 +102,7 @@ def set_base_learner(self, learner):
             self.base_estimator = learner or self.DEFAULT_BASE_ESTIMATOR
             self.base_label.setText(
                 "Base estimator: %s" % self.base_estimator.name.title())
-        if self.auto_apply:
-            self.apply()
+        self.learner = self.model = None
 
     def get_learner_parameters(self):
         return (("Base estimator", self.base_estimator),

diff --git a/Orange/widgets/model/owcalibratedlearner.py b/Orange/widgets/model/owcalibratedlearner.py
@@ -62,7 +62,7 @@ def add_main_layout(self):
     def set_learner(self, learner):
         self.base_learner = learner
         self._set_default_name()
-        self.unconditional_apply()
+        self.learner = self.model = None
 
     def _set_default_name(self):
 

diff --git a/Orange/widgets/model/owlinearregression.py b/Orange/widgets/model/owlinearregression.py
@@ -94,9 +94,6 @@ def add_main_layout(self):
         self.controls.alpha_index.setEnabled(self.reg_type != self.OLS)
         self.l2_ratio_slider.setEnabled(self.reg_type == self.Elastic)
 
-    def handleNewSignals(self):
-        self.apply()
-
     def _intercept_changed(self):
         self.apply()
 

diff --git a/Orange/widgets/model/owstack.py b/Orange/widgets/model/owstack.py
@@ -33,22 +33,26 @@ def add_main_layout(self):
     @Inputs.learners
     def set_learner(self, index: int, learner: Learner):
         self.learners[index] = learner
+        self.invalidate()
 
     @Inputs.learners.insert
     def insert_learner(self, index, learner):
         self.learners.insert(index, learner)
+        self.invalidate()
 
     @Inputs.learners.remove
     def remove_learner(self, index):
         self.learners.pop(index)
+        self.invalidate()
 
     @Inputs.aggregate
     def set_aggregate(self, aggregate):
         self.aggregate = aggregate
+        self.invalidate()
 
-    def handleNewSignals(self):
-        super().handleNewSignals()
-        self.apply()
+    def _invalidate(self):
+        self.learner = self.model = None
+        # ... and handleNewSignals will do the rest
 
     def create_learner(self):
         if not self.learners: