Update app.py

app.py

@@ -39,242 +39,245 @@ if "x" not in st.session_state:
     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")
+# Check for query parameters to navigate from home.py
+if st.experimental_get_query_params().get("page") == ["gradient-descent"]:
+    # Full-width layout
+    st.set_page_config(layout="wide")
 
-# CSS Styles for Borders, Font, Reduced Padding, and Custom Border Color
-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;
-    }
-    /* Custom borders for input fields */
-    .stTextInput input, .stNumberInput input {
-        border: 2px solid #001A6E;
-        border-radius: 5px;
-        padding: 10px;
-    }
-    /* Tooltip styling */
-    .tooltip {
-        position: relative;
-        display: inline-block;
-        cursor: pointer;
-    }
-    .tooltip .tooltiptext {
-        visibility: hidden;
-        opacity: 0;
-        width: 300px;
-        background-color: #001A6E;
-        color: #fff;
-        text-align: center;
-        border-radius: 5px;
-        padding: 5px;
-        position: absolute;
-        z-index: 1;
-        bottom: 125%; /* Position the tooltip above */
-        left: 50%;
-        margin-left: -150px;
-        transition: opacity 0.3s;
-    }
-    .tooltip:hover .tooltiptext {
-        visibility: visible;
-        opacity: 1;
-    }
-    </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")
-
-    # Tooltip with instructions when hovering over the function input label
+    # CSS Styles for Borders, Font, Reduced Padding, and Custom Border Color
     st.markdown(
         """
-        <div class="tooltip">
-            <label for="func_input">Enter a function of 'x':</label>
-            <span class="tooltiptext">
-                **How to input your function:**
-                - Please give the inputs as mentioned below                
-                - x^n as  x**n,                
-                - sin(x) as np.sin(x)                
-                - log(x) as np.log(x),                
-                - e^x or exp(x) as np.exp(x).
-            </span>
-        </div>
+        <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;
+        }
+        /* Custom borders for input fields */
+        .stTextInput input, .stNumberInput input {
+            border: 2px solid #001A6E;
+            border-radius: 5px;
+            padding: 10px;
+        }
+        /* Tooltip styling */
+        .tooltip {
+            position: relative;
+            display: inline-block;
+            cursor: pointer;
+        }
+        .tooltip .tooltiptext {
+            visibility: hidden;
+            opacity: 0;
+            width: 300px;
+            background-color: #001A6E;
+            color: #fff;
+            text-align: center;
+            border-radius: 5px;
+            padding: 5px;
+            position: absolute;
+            z-index: 1;
+            bottom: 125%; /* Position the tooltip above */
+            left: 50%;
+            margin-left: -150px;
+            transition: opacity 0.3s;
+        }
+        .tooltip:hover .tooltiptext {
+            visibility: visible;
+            opacity: 1;
+        }
+        </style>
         """,
-        unsafe_allow_html=True
-    )
-    
-    # Use text input for the user to define a function, but no `value` argument
-    func_input = st.text_input(
-        "👇", 
-        key="func_input", 
-        on_change=reset_state
+        unsafe_allow_html=True,
     )
 
-    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
-    )
+    # Page Layout
+    st.title("🌟 Gradient Descent Interactive Tool 🌟")
 
-    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)}")
+    col1, col2 = st.columns([1, 2])
 
-# 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]
+    # Left Section: User Input
+    with col1:
+        st.subheader("🔧 Define Your Function")
+
+        # Tooltip with instructions when hovering over the function input label
+        st.markdown(
+            """
+            <div class="tooltip">
+                <label for="func_input">Enter a function of 'x':</label>
+                <span class="tooltiptext">
+                    **How to input your function:**
+                    - Please give the inputs as mentioned below                
+                    - x^n as  x**n,                
+                    - sin(x) as np.sin(x)                
+                    - log(x) as np.log(x),                
+                    - e^x or exp(x) as np.exp(x).
+                </span>
+            </div>
+            """,
+            unsafe_allow_html=True
+        )
 
-        fig = go.Figure()
+        # Use text input for the user to define a function
+        func_input = st.text_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)}")
 
-        # 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"
-        ))
+    # 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]
 
-        # 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"
-        ))
+            fig = go.Figure()
 
-        # Tangent line at the current gradient descent point
-        current_x = st.session_state.x
-        tangent_x = np.linspace(-10, 10, 200)  # Adjusting range to cover entire plot
-        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"
-        ))
+            # 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"
+            ))
 
-        # 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, min(max(y_plot) + 5, 1000)],  # Limiting the max y to 1000
-                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,
+            # 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(-10, 10, 200)
+            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, min(max(y_plot) + 5, 1000)], 
+                    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
+            # Axis lines for quadrants
+            fig.add_shape(type="line", x0=-10, x1=10, y0=0, y1=0, line=dict(color="white", width=2))
+            fig.add_shape(type="line", x0=0, x1=0, y0=-100, y1=100, line=dict(color="white", width=2))
 
-        st.plotly_chart(fig, use_container_width=True)
+            st.plotly_chart(fig, use_container_width=True)
 
-    except Exception as e:
-        st.error(f"⚠️ Error in visualization: {str(e)}")
+        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}")
 
-    # 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}")