add z-score result

eval.py

@@ -30,9 +30,10 @@ def eval(pred_path, label_path):
 
 
 if __name__ == '__main__':
-    with open('pre_test.sh', 'r') as f:
-        pred_dir = f.readline()
-        pred_dir = pred_dir.split()[5].split('/')[-1]
-    pred_result = './predict/{}/test.txt'.format(pred_dir)
+    # with open('pre_test.sh', 'r') as f:
+    #     pred_dir = f.readline()
+    #     pred_dir = pred_dir.split()[5].split('/')[-1]
+    # pred_result = './predict/{}/test.txt'.format(pred_dir)
+    pred_result = './predict/lr-1e-5-batch-32-e-10-layer9-0429-z-10-step-74133/test.txt'
     test_label_path = './data/test_ic50'
     eval(pred_result, test_label_path)

predict/lr-1e-5-batch-32-e-10-layer3-0429-z-10-step-74133/eval_results

+RMSE : 1.0464617506947576 ; Pearson Correlation Coefficient : 0.7087386087513284
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predict/lr-1e-5-batch-32-e-10-layer3-0429-z-100-step-74133/eval_results

+RMSE : 1.077407260875347 ; Pearson Correlation Coefficient : 0.6837182462635899
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predict/lr-1e-5-batch-32-e-10-layer9-0429-z-10-step-74133/eval_results

-RMSE : 9.781247479007378 ; Pearson Correlation Coefficient : 0.7332126683709378
+RMSE : 1.3901506777912391 ; Pearson Correlation Coefficient : 0.7332126683709385
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utils/analyse.txt

+6.339674062480976
+1.4751794034241978

utils/normalize_data.py

@@ -18,12 +18,29 @@ def z_score(data, save, enlarge):
         for aff in tqdm(new_affinity):
             f.write(str(aff) + '\n')
 
+def reform(input_file_path, result_save_path, average, std, enlarge):
+    with open(input_file_path, 'r') as f:
+        res = f.readlines()
+    with open(result_save_path, 'w') as f:
+        for line in tqdm(res):
+            data = float(line.strip())
+            ori = ((data / enlarge) * std) + average
+            f.write(str(ori) + '\n')
 
 
 
 
 if __name__ == '__main__':
-    data = '../data/train_ic50'
-    save = '../data/train_z_1_ic50'
-    enlarge = 1
-    z_score(data, save, enlarge)
+    average = 6.339674062480976
+    std = 1.4751794034241978
+
+    # gengerate z-score dataset
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+    # data = '../data/train_ic50'
+    # save = '../data/train_z_1_ic50'
+    # enlarge = 1
+    # z_score(data, save, enlarge)
+
+    # reform result
+    result = '../predict/lr-1e-5-batch-32-e-10-layer9-0429-z-10-step-74133/test_10.txt'
+    save = '../predict/lr-1e-5-batch-32-e-10-layer9-0429-z-10-step-74133/test.txt'
+    reform(result, save, average, std, 100)
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