add some

eval.py

+import numpy as np
+import re
+
+
+def eval_result(pred, label):
+    pred = np.array(pred)
+    label = np.array(label)
+    num = len(pred)
+    diff = pred - label
+    mse = np.sum(np.power(diff, 2)) / num
+    rmse = np.sqrt(mse)
+    pearson_co = np.corrcoef(pred, label)
+
+    return rmse, pearson_co
+
+
+def eval(pred_path, label_path):
+    with open(pred_path, 'r') as f:
+        pred = f.readlines()
+        pred = [float(i.strip()) for i in pred]
+    with open(label_path, 'r') as f:
+        label = f.readlines()
+        label = [float(i.strip()) for i in label]
+    remse, r_mat = eval_result(pred, label)
+    r = r_mat[0, 1]
+    save_path = pred_path.replace('test.txt', 'eval_results')
+    with open(save_path, 'w') as f:
+        f.write('RMSE : {} ; Pearson Correlation Coefficient : {}'.format(remse, r))
+    print('RMSE : {} ; Pearson Correlation Coefficient : {}'.format(remse, r))
+
+
+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)
+    pred_result = './predict/lr-1e-5-batch-32-e-10-layer3-0503-z-1-step-82370/test.txt'
+    test_label_path = './data/test_ic50'
+    eval(pred_result, test_label_path)

pre_test.sh

+CUDA_VISIBLE_DEVICES=1 python run_interaction.py --task=test --b=64 --output=./predict/lr-1e-5-batch-32-e-10-layer3-0503-z-1-step-65896 --config=./config/config_layer_3.json --init=./model/lr-1e-5-batch-32-e-10-layer3-0503-z-1/epoch-7-step-65896-loss-0.39236504916727866.pth --do_eval='True'
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