Update app.py

app.py

@@ -1,34 +1,10 @@
-import streamlit as st
-import numpy as np
-import plotly.graph_objects as go
-
-# Safe function evaluation
-def safe_eval(func_str, x_val):
-    """ Safely evaluates the function at a given x value. """
-    allowed_names = {"x": x_val, "np": np}
-    try:
-        return eval(func_str, {"__builtins__": None}, allowed_names)
-    except Exception as e:
-        raise ValueError(f"Error evaluating the function: {e}")
-
-# Function derivative using finite difference method
-def derivative(func_str, x_val, h=1e-5):
-    """ Numerically compute the derivative of the function at x using finite differences. """
-    return (safe_eval(func_str, x_val + h) - safe_eval(func_str, x_val - h)) / (2 * h)
-
-# Tangent line equation
-def tangent_line(func_str, x_val, x_range):
-    """ Compute the tangent line at a given x value. """
-    y_val = safe_eval(func_str, x_val)
-    slope = derivative(func_str, x_val)
-    return slope * (x_range - x_val) + y_val
-
-# Callback to reset session state
-def reset_state():
-    st.session_state.x = st.session_state.starting_point
-    st.session_state.iteration = 0
-    st.session_state.x_vals = [st.session_state.starting_point]
-    st.session_state.y_vals = [safe_eval(st.session_state.func_input, st.session_state.starting_point)]
+# Use text input for the user to define a function
+func_input = st.text_input(
+    "Enter a function of 'x':", 
+    st.session_state.func_input, 
+    key="func_input", 
+    on_change=reset_state
+)
 
 # Predefined function buttons
 predefined_functions = {
@@ -38,212 +14,12 @@ predefined_functions = {
     "log(x)": "np.log(x)"
 }
 
-# Initialize session state variables
-if "func_input" not in st.session_state:
-    st.session_state.func_input = "x**2 + x"
-if "x" not in st.session_state:
-    st.session_state.x = 4.0
-    st.session_state.iteration = 0
-    st.session_state.x_vals = [4.0]
-    st.session_state.y_vals = [safe_eval(st.session_state.func_input, 4.0)]
-
-# Full-width layout
-st.set_page_config(layout="wide")
-
-# CSS Styles for Borders, Font and Reduced Padding
-st.markdown(
-    """
-    <style>
-    * {
-        font-family: Cambria, Arial, sans-serif !important;
-    }
-    h1, h2, h3, h4, h5 {
-        text-align: center;
-        margin-top: 0;
-    }
-    input, .stButton button, .stDownloadButton button {
-        border: 2px solid #ea445a;
-        border-radius: 5px;
-        padding: 10px;
-    }
-    .stInfo, .stSuccess {
-        border: 2px solid #ea445a;
-        border-radius: 5px;
-        padding: 10px;
-    }
-    .stButton {
-        margin-top: 10px;
-    }
-    /* Reduced Padding at the top */
-    .css-1d391kg {
-        padding-top: 0.5rem;
-    }
-    /* Centering the legend in the plot */
-    .stPlotlyChart {
-        display: block;
-        margin: 0 auto;
-    }
-    /* Adjusting for full width without scrolling */
-    .css-1lcbvhc {
-        padding-left: 0;
-        padding-right: 0;
-    }
-    </style>
-    """,
-    unsafe_allow_html=True,
-)
-
-# Page Layout
-st.title("🌟 Gradient Descent Interactive Tool 🌟")
-
-col1, col2 = st.columns([1, 2])
-
-# Left Section: User Input
-with col1:
-    st.subheader("🔧 Define Your Function")
-    
-    # Display the predefined function buttons
-    st.write("Or choose a predefined function:")
-    cols = st.columns(4)
-    for i, (btn_label, func_value) in enumerate(predefined_functions.items()):
-        with cols[i]:
-            if st.button(btn_label):
-                st.session_state.func_input = func_value
-                reset_state()  # Ensure that the reset function is called to update the state
-                st.experimental_rerun()  # Re-run to ensure everything updates properly
-
-    # Use text input for the user to define a function
-    func_input = st.text_input(
-        "Enter a function of 'x':", 
-        st.session_state.func_input, 
-        key="func_input", 
-        on_change=reset_state
-    )
-
-    st.subheader("⚙️ Gradient Descent Parameters")
-    starting_point = st.number_input(
-        "Starting Point (X₀)", 
-        value=4.0, 
-        step=0.1, 
-        format="%.2f", 
-        key="starting_point", 
-        on_change=reset_state
-    )
-    learning_rate = st.number_input(
-        "Learning Rate (ŋ)", 
-        value=0.25, 
-        step=0.01, 
-        format="%.2f", 
-        key="learning_rate", 
-        on_change=reset_state
-    )
-
-    col3, col4 = st.columns(2)
-    with col3:
-        if st.button("🔄 Set Up Function"):
-            reset_state()
-    with col4:
-        if st.button("▶️ Next Iteration"):
-            try:
-                grad = derivative(st.session_state.func_input, st.session_state.x)
-                st.session_state.x = st.session_state.x - learning_rate * grad
-                st.session_state.iteration += 1
-                st.session_state.x_vals.append(st.session_state.x)
-                st.session_state.y_vals.append(safe_eval(st.session_state.func_input, st.session_state.x))
-            except Exception as e:
-                st.error(f"⚠️ Error: {str(e)}")
-
-# Right Section: Visualization
-with col2:
-    st.subheader("📊 Gradient Descent Visualization")
-    try:
-        # Plot the function and all current and previous gradient descent points
-        x_plot = np.linspace(-10, 10, 400)
-        y_plot = [safe_eval(st.session_state.func_input, x) for x in x_plot]
-
-        fig = go.Figure()
-
-        # Function curve
-        fig.add_trace(go.Scatter(
-            x=x_plot, 
-            y=y_plot, 
-            mode="lines+markers", 
-            line=dict(color="blue", width=2), 
-            marker=dict(size=4, color="blue", symbol="circle"),
-            name="Function"
-        ))
-
-        # All gradient descent points (red points without coordinates)
-        fig.add_trace(go.Scatter(
-            x=st.session_state.x_vals,
-            y=st.session_state.y_vals,
-            mode="markers",
-            marker=dict(color="red", size=10),
-            name="Gradient Descent Points"
-        ))
-
-        # Tangent line at the current gradient descent point
-        current_x = st.session_state.x
-        tangent_x = np.linspace(current_x - 5, current_x + 5, 200)  # Extended range for tangent line
-        tangent_y = tangent_line(st.session_state.func_input, current_x, tangent_x)
-        fig.add_trace(go.Scatter(
-            x=tangent_x,
-            y=tangent_y,
-            mode="lines",
-            line=dict(color="orange", width=3),
-            name="Tangent Line"
-        ))
-
-        # Dynamic zoom for better visibility
-        fig.update_layout(
-            xaxis=dict(
-                title="x-axis",
-                range=[-10, 10],
-                showline=True,
-                linecolor="white",
-                tickcolor="white",
-                tickfont=dict(color="white"),
-                ticks="outside",
-            ),
-            yaxis=dict(
-                title="y-axis",
-                range=[min(y_plot) - 5, max(y_plot) + 5],
-                showline=True,
-                linecolor="white",
-                tickcolor="white",
-                tickfont=dict(color="white"),
-                ticks="outside",
-            ),
-            plot_bgcolor="black",
-            paper_bgcolor="black",
-            title="",
-            margin=dict(l=10, r=10, t=10, b=10),
-            width=800,
-            height=400,
-            showlegend=True,
-            legend=dict(
-                x=1.1,
-                y=0.5,
-                xanchor="left",
-                yanchor="middle",
-                orientation="v",
-                font=dict(size=12, color="white"),
-                bgcolor="black",
-                bordercolor="white",
-                borderwidth=2,
-            )
-        )
-
-        # Axis lines for quadrants
-        fig.add_shape(type="line", x0=-10, x1=10, y0=0, y1=0, line=dict(color="white", width=2))  # x-axis
-        fig.add_shape(type="line", x0=0, x1=0, y0=-100, y1=100, line=dict(color="white", width=2))  # y-axis
-
-        st.plotly_chart(fig, use_container_width=True)
-
-    except Exception as e:
-        st.error(f"⚠️ Error in visualization: {str(e)}")
-
-    # Iteration stats and download
-    col5, col6 = st.columns(2)
-    col5.info(f"🧑‍💻 Iteration: {st.session_state.iteration}")
-    col6.success(f"✅ Current x: {st.session_state.x:.4f}, Current f(x): {st.session_state.y_vals[-1]:.4f}")
+# Display the predefined function buttons
+st.write("Or choose a predefined function:")
+cols = st.columns(4)
+for i, (btn_label, func_value) in enumerate(predefined_functions.items()):
+    with cols[i]:
+        if st.button(btn_label):
+            st.session_state.func_input = func_value
+            reset_state()  # Ensure that the reset function is called to update the state
+            st.rerun()  # Re-run to ensure everything updates properly