[FIX] : Add Explicit flag to supplementary Table learner output

Orange/widgets/classify/owlogisticregression.py

@@ -5,7 +5,7 @@
 
 from Orange.data import Table, Domain, ContinuousVariable, StringVariable
 from Orange.classification.logistic_regression import LogisticRegressionLearner
-from Orange.widgets import settings, gui
+from Orange.widgets import widget, settings, gui
 from Orange.widgets.utils.owlearnerwidget import OWBaseLearner
 
 
@@ -18,7 +18,7 @@ class OWLogisticRegression(OWBaseLearner):
 
     LEARNER = LogisticRegressionLearner
 
-    outputs = [("Coefficients", Table)]
+    outputs = [("Coefficients", Table, widget.Explicit)]
 
     penalty_type = settings.Setting(1)
     C_index = settings.Setting(61)

Orange/widgets/classify/owsvmclassification.py

@@ -5,7 +5,7 @@
 
 from Orange.data import Table
 from Orange.classification.svm import SVMLearner, NuSVMLearner
-from Orange.widgets import settings, gui
+from Orange.widgets import widget, settings, gui
 from Orange.widgets.utils.owlearnerwidget import OWBaseLearner
 
 
@@ -127,7 +127,7 @@ class OWSVMClassification(OWBaseSVM):
 
     LEARNER = SVMLearner
 
-    outputs = [("Support vectors", Table)]
+    outputs = [("Support vectors", Table, widget.Explicit)]
 
     C_SVC, Nu_SVC = 0, 1
     svmtype = settings.Setting(0)

Orange/widgets/regression/owlinearregression.py

@@ -6,7 +6,7 @@
 from Orange.regression.linear import (
     LassoRegressionLearner, LinearRegressionLearner,
     RidgeRegressionLearner, ElasticNetLearner)
-from Orange.widgets import settings, gui
+from Orange.widgets import widget, settings, gui
 from Orange.widgets.utils.owlearnerwidget import OWBaseLearner
 
 
@@ -19,7 +19,7 @@ class OWLinearRegression(OWBaseLearner):
 
     LEARNER = LinearRegressionLearner
 
-    outputs = [("Coefficients", Table)]
+    outputs = [("Coefficients", Table, widget.Explicit)]
 
     #: Types
     REGULARIZATION_TYPES = ["No regularization", "Ridge regression (L2)",

Orange/widgets/regression/owsvmregression.py

@@ -6,7 +6,7 @@
 
 from Orange.data import Table
 from Orange.regression import SVRLearner, NuSVRLearner
-from Orange.widgets import settings, gui
+from Orange.widgets import widget, settings, gui
 from Orange.widgets.classify.owsvmclassification import OWBaseSVM
 
 
@@ -19,7 +19,7 @@ class OWSVMRegression(OWBaseSVM):
 
     LEARNER = SVRLearner
 
-    outputs = [("Support vectors", Table)]
+    outputs = [("Support vectors", Table, widget.Explicit)]
 
     #: SVR types
     Epsilon_SVR, Nu_SVR = 0, 1

Orange/widgets/widget.py

@@ -765,6 +765,8 @@ def __init__(self, text, persistent_id, icon=None, moreurl=None):
 #: Signal handlers with this flag have (object, id: object) -> None signature.
 Multiple = widget_description.Multiple
 #: Applies to user interaction only.
+#: Only connected if specifically requested (in a dedicated "Links" dialog)
+#: or it is the only possible connection.
 Explicit = widget_description.Explicit
 #: Dynamic output type.
 #: Specifies that the instances on the output will in general be

doc/development/source/tutorial-channels.rst

@@ -208,3 +208,16 @@ and - nothing will really happen:
 
 That is, no window with a query on which channels to connect to will
 open, as the default *"Train Data"* was selected.
+
+
+*****************
+Explicit Channels
+*****************
+
+
+Some times when a widget has multiple outputs of different types, some
+of them should not be subject to this automatic default connection selection.
+An example of this is in Orange's `Logistic Regression` widget that outputs
+a suplimentary 'Coefficients' data table. Such outputs can be marked with
+and :attr:`~Orange.widgets.widget.Explicit` flag ensuring they are never
+selected for a default connection.

doc/development/source/widget.rst

@@ -113,6 +113,13 @@ Input/Output flags:
    can be connected to any input which can accept a subtype of the
    declared output type.
 
+.. attribute:: Explicit
+
+   Outputs with an explicit flag are never selected (auto connected) among
+   candidate connections. Connections are only established when there is
+   one unambiguous connection possible or through a dedicated 'Links'
+   dialog.
+
 .. autoclass:: InputSignal
 
 .. autoclass:: OutputSignal