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| import streamlit as st | |
| import numpy as np | |
| import sympy as sp | |
| import plotly.graph_objs as go | |
| st.markdown(""" | |
| <style> | |
| .stApp { | |
| background-color: #f9f9f9; | |
| font-family: 'Segoe UI', sans-serif; | |
| } | |
| h1 { | |
| text-align: center; | |
| color: #2C3E50; | |
| font-size: 38px !important; | |
| font-weight: bold; | |
| margin-bottom: 20px; | |
| } | |
| .stTextInput > div > div > input { | |
| border: 2px solid #3498DB; | |
| border-radius: 8px; | |
| padding: 8px; | |
| } | |
| 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); | |
| } | |
| .stAlert { | |
| border-radius: 8px; | |
| } | |
| .block-container { | |
| padding-top: 2rem; | |
| padding-bottom: 2rem; | |
| max-width: 1200px; | |
| } | |
| </style> | |
| """, unsafe_allow_html=True) | |
| st.title("Gradient Descent Visualizer") | |
| x = sp.Symbol("x") | |
| 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: | |
| 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}") | |
| if 'func' in st.session_state and 'gradient_func' in st.session_state: | |
| if st.button("Next Iteration"): | |
| try: | |
| 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 | |
| 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}") | |
| if st.button("Run Iterations"): | |
| try: | |
| 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 | |
| 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: | |
| 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"), | |
| width=1000, | |
| height=600 | |
| ) | |
| 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}") | |