Delete app.py

app.py

@@ -1,135 +0,0 @@
-import streamlit as st
-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
-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
-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
-x = sp.symbols('x')
-try:
-    func = sp.sympify(func_input)
-    derivative = sp.diff(func, x)
-    func_np = sp.lambdify(x, func, 'numpy')
-    derivative_np = sp.lambdify(x, derivative, 'numpy')
-except Exception as e:
-    st.error(f"Invalid function: {e}")
-    st.stop()
-
-# Gradient Descent Step
-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
-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
-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
-x_vals = np.linspace(-15, 15, 1000)
-y_vals = func_np(x_vals)
-
-# Plotly Visualization
-fig = go.Figure()
-
-# Function Plot
-fig.add_trace(go.Scatter(
-    x=x_vals, y=y_vals, mode='lines',
-    line=dict(color='blue', width=2),
-    hoverinfo='none'
-))
-
-# Gradient Descent Path
-path = st.session_state.path
-x_path, y_path = zip(*[(pt[0], func_np(pt[0])) for pt in path])
-fig.add_trace(go.Scatter(
-    x=x_path, y=y_path, mode='markers+lines',
-    marker=dict(color='red', size=8),
-    line=dict(color='red', width=2),
-    hoverinfo='none'
-))
-
-# Highlight Current Point
-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'
-))
-
-# Highlight Actual Minima
-if actual_minima:
-    minima_x = [float(p) for p in actual_minima]
-    minima_y = [func_np(p) for p in minima_x]
-    fig.add_trace(go.Scatter(
-        x=minima_x, y=minima_y,
-        mode='markers', marker=dict(color='green', size=14, symbol='star'),
-        name="Actual Minima", hoverinfo='text',
-        text=[f"x = {x_val:.4f}, f(x) = {y_val:.4f}" for x_val, y_val in zip(minima_x, minima_y)]
-    ))
-
-# Add Cross-Axes (X and Y lines)
-fig.add_trace(go.Scatter(
-    x=[-15, 15], y=[0, 0], mode='lines',
-    line=dict(color='black', width=1, dash='dash'),
-    hoverinfo='none'
-))
-fig.add_trace(go.Scatter(
-    x=[0, 0], y=[-15, 15], mode='lines',
-    line=dict(color='black', width=1, dash='dash'),
-    hoverinfo='none'
-))
-
-# Layout Configuration
-fig.update_layout(
-    title="Gradient Descent Visualization",
-    xaxis=dict(
-        title="X",
-        zeroline=True, zerolinewidth=1, zerolinecolor='black',
-        tickvals=np.arange(-15, 16, 5),
-        range=[-15, 15]
-    ),
-    yaxis=dict(
-        title="f(X)",
-        zeroline=True, zerolinewidth=1, zerolinecolor='black',
-        tickvals=np.arange(-15, 16, 5),
-        range=[-15, 15]
-    ),
-    showlegend=False,
-    hovermode="closest",
-    dragmode="pan",  # Corrected line: 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
-st.write(f"**Current Point (x):** {st.session_state.current_x:.4f}")
-
-# Display Iteration History below the graph
-st.write("### Iteration History:")
-for i, (x_val, _) in enumerate(st.session_state.path):
-    st.write(f"Iteration {i+1}: x = {x_val:.4f}")