nikhilkarnati/Gradient_descent_visualizer

1import streamlit as st2import numpy as np3import plotly.graph_objs as go4import sympy as sp5 6# Streamlit Page Configuration7st.set_page_config(page_title="Gradient Descent Visualizer", layout="wide")8 9# Sidebar Inputs10st.sidebar.header("Gradient Descent Settings")11func_input = st.sidebar.text_input("Enter a function (use 'x'):", "x**2")12learning_rate = st.sidebar.number_input("Learning Rate", min_value=0.001, max_value=1.0, value=0.1, step=0.01)13initial_x = st.sidebar.number_input("Initial X", min_value=-10.0, max_value=10.0, value=5.0, step=0.1)14 15# Reset Session State When Function Changes16if "previous_func" not in st.session_state or st.session_state.previous_func != func_input:17    st.session_state.current_x = initial_x18    st.session_state.iteration = 019    st.session_state.path = [(initial_x, 0)]20    st.session_state.previous_func = func_input21 22# Symbolic Computation23x = sp.symbols('x')24try:25    func = sp.sympify(func_input)26    derivative = sp.diff(func, x)27    func_np = sp.lambdify(x, func, 'numpy')28    derivative_np = sp.lambdify(x, derivative, 'numpy')29except Exception as e:30    st.error(f"Invalid function: {e}")31    st.stop()32 33# Gradient Descent Step34def step_gradient_descent(current_x, lr):35    grad = derivative_np(current_x)36    next_x = current_x - lr * grad37    return next_x, grad38 39# Perform Next Iteration40if st.sidebar.button("Next Iteration"):41    next_x, _ = step_gradient_descent(st.session_state.current_x, learning_rate)42    st.session_state.path.append((st.session_state.current_x, func_np(st.session_state.current_x)))43    st.session_state.current_x = next_x44    st.session_state.iteration += 145 46# Calculate Actual Minima47critical_points = sp.solve(derivative, x)48actual_minima = [p.evalf() for p in critical_points if derivative_np(p) == 0 and sp.diff(derivative, x).evalf(subs={x: p}) > 0]49 50# Generate Graph Data51x_vals = np.linspace(-15, 15, 1000)52y_vals = func_np(x_vals)53 54# Plotly Visualization55fig = go.Figure()56 57# Function Plot58fig.add_trace(go.Scatter(59    x=x_vals, y=y_vals, mode='lines',60    line=dict(color='blue', width=2),61    hoverinfo='none'62))63 64# Gradient Descent Path65path = st.session_state.path66x_path, y_path = zip(*[(pt[0], func_np(pt[0])) for pt in path])67fig.add_trace(go.Scatter(68    x=x_path, y=y_path, mode='markers+lines',69    marker=dict(color='red', size=8),70    line=dict(color='red', width=2),71    hoverinfo='none'72))73 74# Highlight Current Point75fig.add_trace(go.Scatter(76    x=[st.session_state.current_x], y=[func_np(st.session_state.current_x)],77    mode='markers', marker=dict(color='orange', size=12),78    name="Current Point", hoverinfo='none'79))80 81# Highlight Actual Minima82if actual_minima:83    minima_x = [float(p) for p in actual_minima]84    minima_y = [func_np(p) for p in minima_x]85    fig.add_trace(go.Scatter(86        x=minima_x, y=minima_y,87        mode='markers', marker=dict(color='green', size=14, symbol='star'),88        name="Actual Minima", hoverinfo='text',89        text=[f"x = {x_val:.4f}, f(x) = {y_val:.4f}" for x_val, y_val in zip(minima_x, minima_y)]90    ))91 92# Add Cross-Axes (X and Y lines)93fig.add_trace(go.Scatter(94    x=[-15, 15], y=[0, 0], mode='lines',95    line=dict(color='black', width=1, dash='dash'),96    hoverinfo='none'97))98fig.add_trace(go.Scatter(99    x=[0, 0], y=[-15, 15], mode='lines',100    line=dict(color='black', width=1, dash='dash'),101    hoverinfo='none'102))103 104# Layout Configuration105fig.update_layout(106    title="Gradient Descent Visualization",107    xaxis=dict(108        title="X",109        zeroline=True, zerolinewidth=1, zerolinecolor='black',110        tickvals=np.arange(-15, 16, 5),111        range=[-15, 15]112    ),113    yaxis=dict(114        title="f(X)",115        zeroline=True, zerolinewidth=1, zerolinecolor='black',116        tickvals=np.arange(-15, 16, 5),117        range=[-15, 15]118    ),119    showlegend=False,120    hovermode="closest",121    dragmode="pan",  # Corrected line: removed extra space122    autosize=True,123)124 125# Fullscreen and Export Options126st.markdown("### Gradient Descent Visualization")127st.plotly_chart(fig, use_container_width=True)128 129# Display Current Point130st.write(f"**Current Point (x):** {st.session_state.current_x:.4f}")131 132# Display Iteration History below the graph133st.write("### Iteration History:")134for i, (x_val, _) in enumerate(st.session_state.path):135    st.write(f"Iteration {i+1}: x = {x_val:.4f}")