Merge pull request #32 from dpr1005/issue-31-Unify_ACC_&_MSE_graphs_o…

…f_tests_with_labels_based_on_given_percentages Issue 31 unify acc & mse graphs of tests with labels based on given percentages - DONE
dpuenteramirez · Dec 19, 2021 · bfa04dd · bfa04dd
2 parents 68a04b6 + 56bb3d4
commit bfa04dd
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Showing 15 changed files with 40 additions and 8 deletions.
diff --git a/Instance Selection Algorithms/plot_csv_percent.py b/Instance Selection Algorithms/plot_csv_percent.py
@@ -15,7 +15,7 @@ def test_unlabeled(dataset):
     folder = './test_unlabeled/'
 
     files = next(walk(folder), (None, None, []))[2]
-    
+
     for file in files:
         if '.csv' in file and ('KNN' in file or 'Tree' in file):
             name = folder + file
@@ -47,11 +47,11 @@ def test_unlabeled(dataset):
     axs[0, 0].set_ylabel('KNN')
     axs[1, 0].set_ylabel('Tree')
 
-    axs[1, 0].set_xlabel("Precision")
-    axs[1, 1].set_xlabel("Precision")
+    axs[1, 0].set_xlabel("So much per one labeled")
+    axs[1, 1].set_xlabel("So much per one labeled")
 
     plt.tight_layout()
-    plt.savefig(folder+dataset)
+    plt.savefig(folder + dataset)
     plt.show()
 
 
@@ -61,13 +61,45 @@ def plot_self_tarining(dataset):
     print(datasets)
 
 
+def plot_unlabeled_to_one():
+    df_knn_acc = pd.read_csv(
+        './test_unlabeled/test_unlabeled_cross_validation_KNN_acc.csv')
+    df_knn_mse = pd.read_csv(
+        './test_unlabeled/test_unlabeled_cross_validation_KNN_mse.csv')
+    df_tree_acc = pd.read_csv(
+        './test_unlabeled/test_unlabeled_cross_validation_Tree_acc.csv')
+    df_tree_mse = pd.read_csv(
+        './test_unlabeled/test_unlabeled_cross_validation_Tree_mse.csv')
+
+    knn_acc = df_knn_acc.to_numpy()
+    knn_mse = df_knn_mse.to_numpy()
+    tree_acc = df_tree_acc.to_numpy()
+    tree_mse = df_tree_mse.to_numpy()
+    datasets = [knn_acc, knn_mse, tree_acc, tree_mse]
+    str_datasets = ['KNN_acc', 'KNN_mse', 'Tree_acc', 'Tree_mse']
+
+    precision = np.array(df_knn_acc.keys()[1:])
+    precision = np.asfarray(precision)
+
+    for index, dataset in enumerate(datasets):
+
+        fig, ax = plt.subplots(figsize=(10, 10))
+        for d in dataset:
+            plt.plot(precision, d[1:])
+        ax.set_xlabel("So much per one labeled")
+        ax.set_ylabel('Correct prediction')
+        ax.set_title(str_datasets[index])
+
+        plt.tight_layout()
+        plt.savefig(f'./test_unlabeled/all_in_one_{str_datasets[index]}')
+
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--d', nargs=1)
     args = parser.parse_args()
 
     dataset = 'page-blocks' if args.d is None else str(args.d[0])
-    test_unlabeled(dataset)
-    #plot_self_tarining(dataset)
-
-
+    # test_unlabeled(dataset)
+    # plot_self_tarining(dataset)
+    plot_unlabeled_to_one()
diff --git a/Instance Selection Algorithms/test_unlabeled/all_in_one_KNN_acc.png b/Instance Selection Algorithms/test_unlabeled/all_in_one_KNN_acc.png
diff --git a/Instance Selection Algorithms/test_unlabeled/all_in_one_KNN_mse.png b/Instance Selection Algorithms/test_unlabeled/all_in_one_KNN_mse.png
diff --git a/Instance Selection Algorithms/test_unlabeled/all_in_one_Tree_acc.png b/Instance Selection Algorithms/test_unlabeled/all_in_one_Tree_acc.png
diff --git a/Instance Selection Algorithms/test_unlabeled/all_in_one_Tree_mse.png b/Instance Selection Algorithms/test_unlabeled/all_in_one_Tree_mse.png
diff --git a/Instance Selection Algorithms/test_unlabeled/banana.png b/Instance Selection Algorithms/test_unlabeled/banana.png
diff --git a/Instance Selection Algorithms/test_unlabeled/contraceptive.png b/Instance Selection Algorithms/test_unlabeled/contraceptive.png
diff --git a/Instance Selection Algorithms/test_unlabeled/page-blocks.png b/Instance Selection Algorithms/test_unlabeled/page-blocks.png
diff --git a/Instance Selection Algorithms/test_unlabeled/phoneme.png b/Instance Selection Algorithms/test_unlabeled/phoneme.png
diff --git a/Instance Selection Algorithms/test_unlabeled/segment.png b/Instance Selection Algorithms/test_unlabeled/segment.png
diff --git a/Instance Selection Algorithms/test_unlabeled/texture.png b/Instance Selection Algorithms/test_unlabeled/texture.png
diff --git a/Instance Selection Algorithms/test_unlabeled/titanic.png b/Instance Selection Algorithms/test_unlabeled/titanic.png
diff --git a/Instance Selection Algorithms/test_unlabeled/whinequality-red.png b/Instance Selection Algorithms/test_unlabeled/whinequality-red.png
diff --git a/Instance Selection Algorithms/test_unlabeled/whinequality-white.png b/Instance Selection Algorithms/test_unlabeled/whinequality-white.png
diff --git a/Instance Selection Algorithms/test_unlabeled/yeast.png b/Instance Selection Algorithms/test_unlabeled/yeast.png