Update app.py

app.py

@@ -1,3 +1,59 @@
 import os
 os.system("pip install numpy matplotlib pandas")
-import Hopapp.py
+import numpy as np
+import matplotlib.pyplot as plt
+import gradio as gr
+import pandas as pd
+
+
+def flatten(img : np.array) -> list[int] :
+    new : list[int] = []
+    for row in img:
+        for item in row:
+            new.append(int(item))
+    return new
+
+class Hopfield:
+    def __init__(self,patts):
+        self.E : list[int] = []
+        self.patts = patts
+        self.size = (4,4) 
+        self.Px :int = len(patts)
+        self.Py :int = len(patts[0])
+        
+        self.W : np.array = np.zeros((self.Py,self.Py),dtype=np.float16)
+    
+    def train(self):
+        
+        for i in range(self.Py):
+            for j in range(self.Py):
+                if i == j:
+                    self.W[i][j] = 0
+                    continue
+                
+                self.W[i][j] = (1 / self.Px) * sum([patt[i] * patt[j] for patt in self.patts])
+    
+    def Energy(self):
+        
+        return self.E
+    
+    def update(self,pattern):
+        
+        pattern_flat = flatten(pattern)
+        
+        
+        H : list[int] = []
+        for i in self.W:
+            
+            H.append((sum([w * s for w,s in zip(i, pattern_flat)])))
+        
+        H = np.array(H)
+        H = np.sign(H)
+        
+        E = 0
+        for i in range(self.Py):
+            for j in range(self.Py):
+                E += float(-0.5 * self.W[i][j] * H[i] * H[j])
+        self.E.append(E)
+        
+