Use identity check for comparison to a singleton

ema_workbench/analysis/logistic_regression.py

@@ -59,9 +59,9 @@ def calculate_covden(fitted_model, x, y, step=0.1):
 def calculate_covden_for_treshold(predicted, y, threshold):
     """Helper function for calculating coverage and density"""
 
-    tp = np.sum(((predicted > threshold) == True) & (y == True))
-    fp = np.sum(((predicted > threshold) == True) & (y == False))
-    fn = np.sum(((predicted > threshold) == False) & (y == True))
+    tp = np.sum(((predicted > threshold) is True) & (y is True))
+    fp = np.sum(((predicted > threshold) is True) & (y is False))
+    fn = np.sum(((predicted > threshold) is False) & (y is True))
 
     precision = tp / (tp + fp)
     recall = tp / (tp + fn)

ema_workbench/analysis/scenario_discovery_util.py

@@ -156,7 +156,7 @@ def _determine_restricted_dims(box_limits, box_init):
     """
     cols = box_init.columns.values
     restricted_dims = cols[
-        np.all(box_init.values == box_limits.values, axis=0) == False
+        np.all(box_init.values == box_limits.values, axis=0) is False
     ]
     #     restricted_dims = [column for column in box_init.columns if not
     #            np.all(box_init[column].values == box_limits[column].values)]

ema_workbench/connectors/simio_connector.py

@@ -89,7 +89,7 @@ def __init__(
 
         """
         super().__init__(name, wd=wd, model_file=model_file)
-        assert main_model != None
+        assert main_model is not None
         self.main_model_name = main_model
         self.output = {}
         self.n_replications = n_replications

ema_workbench/em_framework/samplers.py

@@ -161,7 +161,7 @@ def sample(self, distribution, size):
         # corner case fix (try siz=49)
         # is not a proper fix, it means that perc is wrong
         # so your intervals are wrong
-        samples = samples[np.isnan(samples) == False]
+        samples = samples[np.isnan(samples) is False]
 
         return samples
 

test/test_analysis/test_scenario_discovery_util.py

@@ -163,14 +163,14 @@ def test_compare(self):
         # all dimensions different
         a = np.array([(0, 1), (0, 1)], dtype=[("a", np.float), ("b", np.float)])
         b = np.array([(1, 1), (0, 0)], dtype=[("a", np.float), ("b", np.float)])
-        test = sdutil._compare(a, b) == False
+        test = sdutil._compare(a, b) is False
         self.assertTrue(np.all(test))
 
         # dimensions 1 different and dimension 2 the same
         a = np.array([(0, 1), (0, 1)], dtype=[("a", np.float), ("b", np.float)])
         b = np.array([(1, 1), (0, 1)], dtype=[("a", np.float), ("b", np.float)])
         test = sdutil._compare(a, b)
-        test = (test[0] == False) & (test[1] == True)
+        test = (test[0] is False) & (test[1] is True)
         self.assertTrue(test)
 
     def test_plot_box(self):