updated combined dataset

affinity-data-combined.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:23fc7754161e313ca4f702a5730fd1265dae9f877f2a2047a02039a3d385b036
-size 1786935004
+oid sha256:9fe95d2ceff77b1785c3280f6f8a8dd3ca0c442035049061d1a69ae0c36e0330
+size 909234669

combine_data.py

@@ -1,12 +1,23 @@
 import pandas as pd
+import numpy as np
 
 def combine_csv_files(csv_file_list):
     # Read and combine all CSV files into a single dataframe
     combined_df = pd.concat([pd.read_csv(file) for file in csv_file_list], ignore_index=True)
     
     # Remove duplicate rows
-    combined_df = combined_df.drop_duplicates()
-    
+    combined_df = combined_df.drop_duplicates(subset=['seq', 'smiles_can', 'neg_log10_affinity_M'])
+
+    # Aggregate duplicates more efficiently using agg function
+    combined_df = combined_df.groupby(['seq', 'smiles_can']).agg(
+        neg_log10_affinity_M=('neg_log10_affinity_M', 'mean')
+    ).reset_index()
+
+    np.random.seed(42)
+    mask_value_5 = combined_df['neg_log10_affinity_M'] == 5
+    rows_to_keep = ~mask_value_5 | (mask_value_5 & (np.random.rand(len(combined_df)) < 0.3))
+    combined_df = combined_df[rows_to_keep].reset_index(drop=True)
+
     # Sort by neg_log10_affinity_M
     combined_df = combined_df.sort_values('neg_log10_affinity_M', ascending=False)