Fix

correlation_test_all.py

@@ -52,7 +52,8 @@ def main():
 
 
             if len(prev_price_dict[i["ticker"]]) > LEN_PREV:
             if len(prev_price_dict[i["ticker"]]) > LEN_PREV:
                 prev_price_dict[i["ticker"]].pop(0)
                 prev_price_dict[i["ticker"]].pop(0)
-            prev_price_dict[i["ticker"]].append(float(i["open"]))
+
+        prev_price_dict[i["ticker"]].append(float(i["open"]))
 
 
     for i in av_gain_turn_dict:
     for i in av_gain_turn_dict:
         if count_pos_dict[i] > 0 and count_turn_dict[i] > 0 and count_dict[i] > 0:
         if count_pos_dict[i] > 0 and count_turn_dict[i] > 0 and count_dict[i] > 0:

model.py

 import csv
 import csv
 
 
-import torch.nn as nn
-import torch
+# import torch.nn as nn
+# import torch
 import math
 import math
 import os
 import os
 import io
 import io
 import numpy as np
 import numpy as np
 import pandas as pd
 import pandas as pd
 import random
 import random
-from torch.utils.data import Dataset, DataLoader, random_split
-import torch.nn.functional as F
-from torchvision import transforms
+# from torch.utils.data import Dataset, DataLoader, random_split
+# import torch.nn.functional as F
+# from torchvision import transforms
 
 
 FILE_NAME = "historical_stock_prices.csv"
 FILE_NAME = "historical_stock_prices.csv"
 OUTPUT_FILE_NAME = "30-day-stocks.csv"
 OUTPUT_FILE_NAME = "30-day-stocks.csv"
@@ -177,5 +177,4 @@ def train():
                 correct = 0.0
                 correct = 0.0
 
 
 if __name__ == "__main__":
 if __name__ == "__main__":
-    make_dataset()
-    train()
+    make_dataset()
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