Update app.py

app.py

@@ -3,23 +3,22 @@ import numpy as np
 import plotly.graph_objs as go
 import sympy as sp
 
-# Streamlit Page Configuration
 st.set_page_config(page_title="Gradient Descent Visualizer", layout="wide")
 
-# Sidebar Inputs
+# inputs
 st.sidebar.header("Gradient Descent Settings")
 func_input = st.sidebar.text_input("Enter a function (use 'x'):", "x**2")
 learning_rate = st.sidebar.number_input("Learning Rate", min_value=0.001, max_value=1.0, value=0.1, step=0.01)
 initial_x = st.sidebar.number_input("Initial X", min_value=-10.0, max_value=10.0, value=5.0, step=0.1)
 
-# Reset Session State When Function Changes
+# Reset when functin changes
 if "previous_func" not in st.session_state or st.session_state.previous_func != func_input:
     st.session_state.current_x = initial_x
     st.session_state.iteration = 0
     st.session_state.path = [(initial_x, 0)]
     st.session_state.previous_func = func_input
 
-# Symbolic Computation
+# Symbolic computation
 x = sp.symbols('x')
 try:
     func = sp.sympify(func_input)
@@ -30,28 +29,28 @@ except Exception as e:
     st.error(f"Invalid function: {e}")
     st.stop()
 
-# Gradient Descent Step
+# Gradient Descent Function
 def step_gradient_descent(current_x, lr):
     grad = derivative_np(current_x)
     next_x = current_x - lr * grad
     return next_x, grad
 
-# Perform Next Iteration
+# for next itertions
 if st.sidebar.button("Next Iteration"):
     next_x, _ = step_gradient_descent(st.session_state.current_x, learning_rate)
     st.session_state.path.append((st.session_state.current_x, func_np(st.session_state.current_x)))
     st.session_state.current_x = next_x
     st.session_state.iteration += 1
 
-# Calculate Actual Minima
+# Calculate actual minima
 critical_points = sp.solve(derivative, x)
 actual_minima = [p.evalf() for p in critical_points if derivative_np(p) == 0 and sp.diff(derivative, x).evalf(subs={x: p}) > 0]
 
-# Generate Graph Data
+# Generate graph
 x_vals = np.linspace(-15, 15, 1000)
 y_vals = func_np(x_vals)
 
-# Plotly Visualization
+
 fig = go.Figure()
 
 # Function Plot
@@ -71,12 +70,11 @@ fig.add_trace(go.Scatter(
     hoverinfo='none'
 ))
 
-# Highlight Current Point
+# Highlight the current point on graph
 fig.add_trace(go.Scatter(
     x=[st.session_state.current_x], y=[func_np(st.session_state.current_x)],
     mode='markers', marker=dict(color='orange', size=12),
-    name="Current Point", hoverinfo='none'
-))
+    name="Current Point", hoverinfo='none'))
 
 # Highlight Actual Minima
 if actual_minima:
@@ -118,18 +116,18 @@ fig.update_layout(
     ),
     showlegend=False,
     hovermode="closest",
-    dragmode="pan",  # Corrected line: removed extra space
+    dragmode="pan",  #removed extra space
     autosize=True,
 )
 
-# Fullscreen and Export Options
+
 st.markdown("### Gradient Descent Visualization")
 st.plotly_chart(fig, use_container_width=True)
 
-# Display Current Point
+#current point
 st.write(f"**Current Point (x):** {st.session_state.current_x:.4f}")
 
-# Display Iteration History below the graph
+#iteration history
 st.write("### Iteration History:")
 for i, (x_val, _) in enumerate(st.session_state.path):
     st.write(f"Iteration {i+1}: x = {x_val:.4f}")