Update app.py

app.py

@@ -1,21 +1,150 @@
+# import streamlit as st
+# import numpy as np 
+# import sympy as sp
+# import plotly.graph_objs as go
+
+# st.set_page_config(page_title="Gradient Descent Visualizer", layout="wide")
+
+
+# # Custom CSS for styling
+# st.markdown("""
+#     <style>
+#     /* Page background */
+#     .stApp {
+#         background-color: #f9f9f9;
+#         font-family: 'Segoe UI', sans-serif;
+#     }
+
+#     /* Title */
+#     h1 {
+#         text-align: center;
+#         color: #2C3E50;
+#         font-size: 38px !important;
+#         font-weight: bold;
+#         margin-bottom: 20px;
+#     }
+
+#     /* Input boxes */
+#     .stTextInput > div > div > input {
+#         border: 2px solid #3498DB;
+#         border-radius: 8px;
+#         padding: 8px;
+#     }
+
+#     /* Buttons */
+#     div.stButton > button {
+#         background-color: #3498DB;
+#         color: white;
+#         border-radius: 10px;
+#         padding: 10px 24px;
+#         font-size: 16px;
+#         border: none;
+#         transition: 0.3s;
+#     }
+#     div.stButton > button:hover {
+#         background-color: #2980B9;
+#         transform: scale(1.05);
+#     }
+
+#     /* Success / Error messages */
+#     .stAlert {
+#         border-radius: 8px;
+#     }
+
+#     /* Chart section */
+#     .block-container {
+#         padding-top: 2rem;
+#         padding-bottom: 2rem;
+#     }
+#     </style>
+# """, unsafe_allow_html=True)
+
+
+# st.title("Gradient Descent Visualizer")
+
+# x = sp.Symbol("x")
+# # User input function, starting point, and learning rate
+# func_input = st.text_input("Enter Function", "x^2")
+# start_point = float(st.text_input("Starting Point", "2"))
+# learning_rate = float(st.text_input("Learning Rate", "0.01"))
+
+# if st.button("Set Up") or 'func' not in st.session_state or 'points' not in st.session_state:
+#     try:
+#         expr = func_input.replace("^", "**")
+#         expr_final = sp.sympify(expr)
+#         func = sp.lambdify(x, expr_final, "numpy")
+#         grad = sp.diff(expr_final, x)
+#         gradient_func = sp.lambdify(x, grad, "numpy")
+        
+#         st.session_state.func = func
+#         st.session_state.gradient_func = gradient_func
+#         st.session_state.points = [start_point]
+#         st.session_state.step = 0
+#         st.success("Function and Gradient Set Up Successfully!")
+    
+#     except Exception as e:
+#         st.error(f"Error setting up function: {e}")
+
+# # Gradient Descent Iteration button
+# if 'func' in st.session_state and 'gradient_func' in st.session_state:
+#     if st.button("Next Iteration"):
+#         try:
+#             # Get the current point and gradient value
+#             x_old = float(st.session_state.points[-1])
+#             grad_val = st.session_state.gradient_func(x_old)
+#             x_new = x_old - learning_rate * grad_val
+            
+#             # Append the new point to the list of points
+#             st.session_state.points.append(x_new)
+#             st.session_state.step += 1
+
+#             st.success(f"Iteration {st.session_state.step} Complete!")
+
+#         except Exception as e:
+#             st.error(f"Error in iteration: {e}")
+
+# # Creating the plot
+# if 'func' in st.session_state and len(st.session_state.points) > 0:
+#     try:
+#         # Create x-values for plotting the function
+#         x_val = np.linspace(-10, 10, 500)
+#         y_val = st.session_state.func(x_val)
+        
+#         iter_points = np.array(st.session_state.points)
+#         iter_y = st.session_state.func(iter_points)
+
+#         trace1 = go.Scatter(x=x_val, y=y_val, mode="lines", name="Function", line=dict(color="blue"))
+#         trace2 = go.Scatter(x=iter_points, y=iter_y, mode="markers+lines", name="Gradient Descent Path", marker=dict(color="red"))
+#         trace3 = go.Scatter(x=[iter_points[-1]], y=[iter_y[-1]], mode='markers+text', 
+#                             marker=dict(color='green', size=15), 
+#                             text=[f"{iter_points[-1]:.6f}"], textposition="top center", 
+#                             name="Current Point")
+        
+#         layout = go.Layout(
+#             title=f"Iteration {st.session_state.step}",
+#             xaxis=dict(title="x - axis"),
+#             yaxis=dict(title="y - axis")
+#         )
+        
+#         fig = go.Figure(data=[trace1, trace2, trace3], layout=layout)
+#         st.plotly_chart(fig, use_container_width=True)
+#         st.success(f"Current Point = {iter_points[-1]}")
+
+#     except Exception as e:
+#         st.error(f"Plot error: {e}")
+
+
 import streamlit as st
 import numpy as np 
 import sympy as sp
 import plotly.graph_objs as go
 
-st.set_page_config(page_title="Gradient Descent Visualizer", layout="wide")
-
-
-# Custom CSS for styling
 st.markdown("""
     <style>
-    /* Page background */
     .stApp {
         background-color: #f9f9f9;
         font-family: 'Segoe UI', sans-serif;
     }
-
-    /* Title */
     h1 {
         text-align: center;
         color: #2C3E50;
@@ -23,15 +152,11 @@ st.markdown("""
         font-weight: bold;
         margin-bottom: 20px;
     }
-
-    /* Input boxes */
     .stTextInput > div > div > input {
         border: 2px solid #3498DB;
         border-radius: 8px;
         padding: 8px;
     }
-
-    /* Buttons */
     div.stButton > button {
         background-color: #3498DB;
         color: white;
@@ -45,13 +170,9 @@ st.markdown("""
         background-color: #2980B9;
         transform: scale(1.05);
     }
-
-    /* Success / Error messages */
     .stAlert {
         border-radius: 8px;
     }
-
-    /* Chart section */
     .block-container {
         padding-top: 2rem;
         padding-bottom: 2rem;
@@ -59,14 +180,14 @@ st.markdown("""
     </style>
 """, unsafe_allow_html=True)
 
-
 st.title("Gradient Descent Visualizer")
 
 x = sp.Symbol("x")
-# User input function, starting point, and learning rate
+
 func_input = st.text_input("Enter Function", "x^2")
 start_point = float(st.text_input("Starting Point", "2"))
 learning_rate = float(st.text_input("Learning Rate", "0.01"))
+num_iterations = int(st.text_input("Number of Iterations", "10"))
 
 if st.button("Set Up") or 'func' not in st.session_state or 'points' not in st.session_state:
     try:
@@ -85,28 +206,44 @@ if st.button("Set Up") or 'func' not in st.session_state or 'points' not in st.s
     except Exception as e:
         st.error(f"Error setting up function: {e}")
 
-# Gradient Descent Iteration button
 if 'func' in st.session_state and 'gradient_func' in st.session_state:
     if st.button("Next Iteration"):
         try:
-            # Get the current point and gradient value
             x_old = float(st.session_state.points[-1])
             grad_val = st.session_state.gradient_func(x_old)
             x_new = x_old - learning_rate * grad_val
-            
-            # Append the new point to the list of points
-            st.session_state.points.append(x_new)
-            st.session_state.step += 1
-
-            st.success(f"Iteration {st.session_state.step} Complete!")
 
+            tolerance = 0.001
+            if abs(x_new - x_old) < tolerance or abs(grad_val) < tolerance:
+                st.success(f"Reached Minima at x = {x_new:.6f}")
+            else:
+                st.session_state.points.append(x_new)
+                st.session_state.step += 1
+                st.success(f"Iteration {st.session_state.step} Complete!")
         except Exception as e:
             st.error(f"Error in iteration: {e}")
 
-# Creating the plot
+    if st.button("Run Iterations"):
+        try:
+            tolerance = 0.001
+            for i in range(num_iterations):
+                x_old = float(st.session_state.points[-1])
+                grad_val = st.session_state.gradient_func(x_old)
+                x_new = x_old - learning_rate * grad_val
+
+                if abs(x_new - x_old) < tolerance or abs(grad_val) < tolerance:
+                    st.success(f"Reached Minima early at x = {x_new:.6f} (after {i+1} steps)")
+                    break
+
+                st.session_state.points.append(x_new)
+                st.session_state.step += 1
+
+            st.success(f"Ran {st.session_state.step} Iterations in total")
+        except Exception as e:
+            st.error(f"Error in multiple iterations: {e}")
+
 if 'func' in st.session_state and len(st.session_state.points) > 0:
     try:
-        # Create x-values for plotting the function
         x_val = np.linspace(-10, 10, 500)
         y_val = st.session_state.func(x_val)
         
@@ -114,7 +251,8 @@ if 'func' in st.session_state and len(st.session_state.points) > 0:
         iter_y = st.session_state.func(iter_points)
 
         trace1 = go.Scatter(x=x_val, y=y_val, mode="lines", name="Function", line=dict(color="blue"))
-        trace2 = go.Scatter(x=iter_points, y=iter_y, mode="markers+lines", name="Gradient Descent Path", marker=dict(color="red"))
+        trace2 = go.Scatter(x=iter_points, y=iter_y, mode="markers+lines", 
+                            name="Gradient Descent Path", marker=dict(color="red"))
         trace3 = go.Scatter(x=[iter_points[-1]], y=[iter_y[-1]], mode='markers+text', 
                             marker=dict(color='green', size=15), 
                             text=[f"{iter_points[-1]:.6f}"], textposition="top center", 
@@ -129,8 +267,5 @@ if 'func' in st.session_state and len(st.session_state.points) > 0:
         fig = go.Figure(data=[trace1, trace2, trace3], layout=layout)
         st.plotly_chart(fig, use_container_width=True)
         st.success(f"Current Point = {iter_points[-1]}")
-
     except Exception as e:
         st.error(f"Plot error: {e}")
-
-