Initial commit

README.md

+The source code of retrosynthesis prediction.
\ No newline at end of file

dataset/uspto50k/data_process.py

+import pandas as pd
+import numpy as np
+from rdchiral import template_extractor
+from tqdm import tqdm
+import multiprocessing
+
+cores = multiprocessing.cpu_count()
+pool = multiprocessing.Pool(cores)
+
+template_train = pd.read_csv('/notebooks/Codes/brs/USPTO/schneider50k/template_train.csv')
+template_test = pd.read_csv('/notebooks/Codes/brs/USPTO/schneider50k/template_test.csv')
+template_val = pd.read_csv('/notebooks/Codes/brs/USPTO/schneider50k/template_val.csv')
+
+raw_data = pd.concat((template_train,template_test,template_val))
+
+
+
+def extract(reaction):
+    try:
+        return template_extractor.extract_from_reaction(reaction)
+    except KeyboardInterrupt:
+        raise KeyboardInterrupt
+    except Exception as e:
+        return 'Err'
+
+reactions = [{'_id': reaction[0], 'reactants': reaction[2].split('>>')[0], 'products': reaction[2].split('>>')[1]} for reaction in raw_data.values]
+
+# templates = pool.map(extract, tqdm(reactions))
+
+templates = [extract(reaction) for reaction in tqdm(reactions)]
+
+print(123)
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results/uspto50k/result_final_top1.csv

+loss,accuracy
+0.004026058129966259,61.567686462707464
+0.0037154078017920256,60.84783043391322
+0.003669698955491185,61.2877424515097
+0.004232234321534634,61.187762447510494
+0.004387203138321638,60.64787042591482
+0.003995717503130436,61.2877424515097
+0.00400707870721817,60.887822435512895
+0.0044508883729577065,60.96780643871226
+0.004024198278784752,61.2877424515097
+0.003794693388044834,61.087782443511294

results/uspto50k/result_final_top10.csv

+loss,accuracy
+0.0035638760309666395,87.64247150569886
+0.0031065840739756823,87.84243151369726
+0.003881766926497221,87.5624875024995
+0.0045944699086248875,87.76244751049789
+0.0034541983623057604,87.84243151369726
+0.004402834922075272,87.60247950409918
+0.004115797113627195,87.80243951209758
+0.0042515951208770275,87.54249150169966
+0.0036142636090517044,87.74245150969806
+0.005122682545334101,87.84243151369726

results/uspto50k/result_final_top3.csv

+loss,accuracy
+0.004491719417273998,78.94421115776845
+0.0037716312799602747,79.2241551689662
+0.003074276028200984,78.88422315536893
+0.003592598019167781,79.40411917616477
+0.0029139474499970675,79.3241351729654
+0.004435064736753702,79.2241551689662
+0.0036734032910317183,78.6642671465707
+0.003433571895584464,78.96420715856829
+0.003273188369348645,79.16416716656668
+0.0036596572026610374,79.124175164967

results/uspto50k/result_final_top5.csv

+loss,accuracy
+0.003986424766480923,83.90321935612877
+0.004227079451084137,83.80323935212958
+0.004254240542650223,84.02319536092782
+0.0042970869690179825,83.88322335532894
+0.0040547908283770084,84.06318736252749
+0.003926473669707775,83.94321135772846
+0.003974240738898516,83.74325134973006
+0.005630603991448879,83.98320335932813
+0.004349200986325741,83.84323135372925
+0.0041490886360406876,83.80323935212958