Remove unnecessary use of comprehension

Author: deepsource-autofix[bot]

implementation_tests/plots/csvs_to_plots.py

@@ -30,20 +30,20 @@ def main():
             else:
                 order_acc.append(precision)
                 acc_df.append(pd.read_csv(file))
-    order_mse = [(i, x) for i, x in enumerate(order_mse)]
-    order_acc = [(i, x) for i, x in enumerate(order_acc)]
+    order_mse = list(enumerate(order_mse))
+    order_acc = list(enumerate(order_acc))
     order_mse.sort(key=lambda x: x[1])
     order_acc.sort(key=lambda x: x[1])
 
-    datasets = np.array([x for x in mse_df[0]['dataset']])
+    datasets = np.array(list(mse_df[0]['dataset']))
     index = [idx for idx, elem in enumerate(datasets) if dataset in elem][0]
 
-    acc_algorithms = np.array([[x for x in df.iloc[index][1:]] for df in
+    acc_algorithms = np.array([list(df.iloc[index][1:]) for df in
                                acc_df])
     acc_algorithms = np.array([acc_algorithms[x] for x, _ in order_acc])
     acc_algorithms = acc_algorithms.astype(float)
 
-    mse_algorithms = np.array([[x for x in df.iloc[index][1:]] for df in
+    mse_algorithms = np.array([list(df.iloc[index][1:]) for df in
                                mse_df])
     mse_algorithms = np.array([mse_algorithms[x] for x, _ in order_mse])
     mse_algorithms = mse_algorithms.astype(float)

implementation_tests/plots/plot_csv_percent.py

@@ -30,7 +30,7 @@ def test_unlabeled(dataset):
                 else:
                     tree_mse_df = pd.read_csv(name)
 
-    datasets = np.array([x for x in knn_acc_df['dataset']])
+    datasets = np.array(list(knn_acc_df['dataset']))
     index = [idx for idx, elem in enumerate(datasets) if dataset in elem][0]
 
     precision = np.array(knn_acc_df.keys()[1:])

implementation_tests/test_instance_selection.py

@@ -115,8 +115,8 @@ def arff2sk_dataset(dataset_path):
         tar_names = np.array(dataset['attributes'][-1][1]).astype(int)
         tar = tt.astype(int)
     except ValueError:
-        tar_names = np.array([x for x in range(len(dataset['attributes'][-1][
-                                                       1]))])
+        tar_names = np.array(list(range(len(dataset['attributes'][-1][
+                                                       1]))))
         relation = {}
         for index, target in enumerate(dataset['attributes'][-1][1]):
             relation[target] = index

instance_selection/_RNN.py

@@ -48,8 +48,8 @@ def filter(self, samples, y):
         samples, y = cnn.filter(samples, y)
         samp_set = transform(samples, y)
 
-        data = deque([x for x in samp_set['data']])
-        target = deque([x for x in samp_set['target']])
+        data = deque(list(samp_set['data']))
+        target = deque(list(samp_set['target']))
 
         for instance in zip(samp_set.data, samp_set.target):
             (sample, class_sample) = instance