Code Editor for app.py

import streamlit as st
import plotly.graph_objects as go
import numpy as np
from sklearn.datasets import make_blobs
import plotly.express as px

# Page config
st.set_page_config(layout="wide")
st.title("3D Data Visualization Explorer")

# Sidebar controls
viz_type = st.sidebar.selectbox(
    "Select Visualization",
    ["Spiral Helix", "Surface Plot", "3D Clusters"]
)

# Common plot settings
st.sidebar.subheader("Plot Settings")
marker_size = st.sidebar.slider("Marker Size", 2, 10, 5)
opacity = st.sidebar.slider("Opacity", 0.0, 1.0, 0.8)
colorscale = st.sidebar.selectbox(
    "Color Scheme",
    ["Viridis", "Plasma", "Inferno", "Magma", "Blues", "Reds"]
)

def generate_helix(n_points=100):
    t = np.linspace(0, 10*np.pi, n_points)
    noise = np.random.normal(0, 0.1, n_points)
    x = np.cos(t) + noise
    y = np.sin(t) + noise
    z = t/10 + noise
    return x, y, z

def generate_surface():
    x = np.linspace(-5, 5, 100)
    y = np.linspace(-5, 5, 100)
    X, Y = np.meshgrid(x, y)
    Z = np.sin(X) * np.cos(Y)
    return X, Y, Z

def generate_clusters():
    X, y = make_blobs(n_samples=150, n_features=3, centers=3, random_state=42)
    return X[:, 0], X[:, 1], X[:, 2], y

if viz_type == "Spiral Helix":
    # Animation speed control
    speed = st.sidebar.slider("Animation Speed", 0, 100, 50)
    
    x, y, z = generate_helix()
    
    fig = go.Figure(data=[go.Scatter3d(
        x=x, y=y, z=z,
        mode='markers',
        marker=dict(
            size=marker_size,
            opacity=opacity,
            color=z,
            colorscale=colorscale
        )
    )])
    
    # Add animation
    if speed > 0:
        frames = []
        for i in range(len(x)):
            frames.append(go.Frame(data=[go.Scatter3d(
                x=x[:i+1], y=y[:i+1], z=z[:i+1],
                mode='markers',
                marker=dict(
                    size=marker_size,
                    opacity=opacity,
                    color=z[:i+1],
                    colorscale=colorscale
                )
            )]))
        fig.frames = frames
        
        fig.update_layout(
            updatemenus=[dict(
                type="buttons",
                showactive=False,
                buttons=[dict(
                    label="Play",
                    method="animate",
                    args=[None, dict(frame=dict(duration=101-speed, redraw=True), fromcurrent=True)]
                )]
            )]
        )

elif viz_type == "Surface Plot":
    # Surface plot specific controls
    st.sidebar.subheader("Surface Settings")
    freq_x = st.sidebar.slider("X Frequency", 0.1, 2.0, 1.0)
    freq_y = st.sidebar.slider("Y Frequency", 0.1, 2.0, 1.0)
    show_contours = st.sidebar.checkbox("Show Contours", True)
    
    X, Y, Z = generate_surface()
    Z = np.sin(freq_x * X) * np.cos(freq_y * Y)
    
    fig = go.Figure(data=[go.Surface(
        x=X, y=Y, z=Z,
        opacity=opacity,
        colorscale=colorscale,
        contours=dict(
            x=dict(show=show_contours, highlight=True),
            y=dict(show=show_contours, highlight=True),
            z=dict(show=show_contours, highlight=True)
        )
    )])

else:  # 3D Clusters
    x, y, z, labels = generate_clusters()
    
    fig = go.Figure(data=[go.Scatter3d(
        x=x, y=y, z=z,
        mode='markers',
        marker=dict(
            size=marker_size,
            opacity=opacity,
            color=labels,
            colorscale=colorscale
        )
    )])

# Common layout settings
fig.update_layout(
    scene = dict(
        xaxis_title="X",
        yaxis_title="Y",
        zaxis_title="Z",
        aspectmode='cube'
    ),
    width=800,
    height=800,
    margin=dict(l=0, r=0, b=0, t=30)
)

# Display plot
st.plotly_chart(fig, use_container_width=True)

# Add plot description
if viz_type == "Spiral Helix":
    st.markdown("""
    **Spiral Helix Visualization**
    - 100 points forming a 3D helix with added Gaussian noise
    - Color intensity based on z-coordinate
    - Animated drawing option with adjustable speed
    """)
elif viz_type == "Surface Plot":
    st.markdown("""
    **Surface Plot Visualization**
    - Interactive 3D surface of z = sin(fx*x)*cos(fy*y)
    - Adjustable x and y frequencies
    - Optional contour lines on all axes
    """)
else:
    st.markdown("""
    **3D Clusters Visualization**
    - 3 clusters with 50 points each
    - Generated using scikit-learn's make_blobs
    - Color indicates cluster membership
    """)