PLS: Lint

Author: VesnaT

Orange/regression/pls.py

@@ -25,14 +25,14 @@ def __init__(self, pls_model):
         self.pls_model = pls_model
 
     def _transform_with_numpy_output(self, X, Y):
-        pls = self.pls_model.skl_model
         """
         # the next command does the following
         x_center = X - pls._x_mean
         y_center = Y - pls._y_mean
         t = x_center @ pls.x_rotations_
         u = y_center @ pls.y_rotations_
         """
+        pls = self.pls_model.skl_model
         t, u = pls.transform(X, Y)
         return np.hstack((t, u))
 
@@ -70,7 +70,7 @@ def predict(self, X):
         return vals
 
     def __str__(self):
-        return 'PLSModel {}'.format(self.skl_model)
+        return f"PLSModel {self.skl_model}"
 
     def _get_var_names(self, n, prefix):
         names = [f"{prefix}{postfix}" for postfix in range(1, n + 1)]
@@ -170,8 +170,8 @@ def incompatibility_reason(self, domain):
 if __name__ == '__main__':
     import Orange
 
-    data = Orange.data.Table('housing')
+    housing = Orange.data.Table('housing')
     learners = [PLSRegressionLearner(n_components=2, max_iter=100)]
-    res = Orange.evaluation.CrossValidation()(data, learners)
+    res = Orange.evaluation.CrossValidation()(housing, learners)
     for learner, ca in zip(learners, Orange.evaluation.RMSE(res)):
-        print("learner: {}\nRMSE: {}\n".format(learner, ca))
+        print(f"learner: {learner}\nRMSE: {ca}\n")

Orange/regression/tests/test_pls.py

@@ -8,13 +8,14 @@
 from Orange.regression import PLSRegressionLearner
 
 
-def table(rows, attr, vars):
-    attr_vars = [ContinuousVariable(name="Feature %i" % i) for i in
+def table(rows, attr, variables):
+    attr_vars = [ContinuousVariable(name=f"Feature {i}") for i in
                  range(attr)]
-    class_vars = [ContinuousVariable(name="Class %i" % i) for i in range(vars)]
+    class_vars = [ContinuousVariable(name=f"Class {i}") for i in
+                  range(variables)]
     domain = Domain(attr_vars, class_vars, [])
     X = np.random.RandomState(0).random((rows, attr))
-    Y = np.random.RandomState(1).random((rows, vars))
+    Y = np.random.RandomState(1).random((rows, variables))
     return Table.from_numpy(domain, X=X, Y=Y)
 
 

Orange/widgets/model/owpls.py

@@ -33,16 +33,15 @@ class Warning(OWBaseLearner.Warning):
     max_iter = Setting(500)
 
     def add_main_layout(self):
-
-        self.optimization_box = gui.vBox(
+        optimization_box = gui.vBox(
             self.controlArea, "Optimization Parameters")
-        self.ncomps_spin = gui.spin(
-            self.optimization_box, self, "n_components", 1, 50, 1,
+        gui.spin(
+            optimization_box, self, "n_components", 1, 50, 1,
             label="Components: ",
             alignment=Qt.AlignRight, controlWidth=100,
             callback=self.settings_changed)
-        self.n_iters = gui.spin(
-            self.optimization_box, self, "max_iter", 5, 1000000, 50,
+        gui.spin(
+            optimization_box, self, "max_iter", 5, 1000000, 50,
             label="Iteration limit: ",
             alignment=Qt.AlignRight, controlWidth=100,
             callback=self.settings_changed,

Orange/widgets/model/tests/test_owpls.py

@@ -11,8 +11,9 @@ def setUp(self):
                                          stored_settings={"auto_apply": False})
         self.init()
         self.parameters = [
-            ParameterMapping('max_iter', self.widget.n_iters),
-            ParameterMapping('n_components', self.widget.ncomps_spin)]
+            ParameterMapping('max_iter', self.widget.controls.max_iter),
+            ParameterMapping('n_components', self.widget.controls.n_components)
+        ]
 
 
 if __name__ == "__main__":