import altair as alt
import gradio as gr
import numpy as np
import pandas as pd
from vega_datasets import data
import plotly.graph_objects as go

def plot_random_points_3d(num_points):
    # Generate random points in 3D space
    np.random.seed(42)  # Setting a seed for reproducibility
    x = np.random.randn(num_points)
    y = np.random.randn(num_points)
    z = np.random.randn(num_points)
    
    # Create a scatter plot
    fig = go.Figure(data=go.Scatter3d(
        x=x,
        y=y,
        z=z,
        mode='markers',
        marker=dict(
            size=5,
            color='blue',
            opacity=0.8
        )
    ))
    
    # Set axes labels and title
    fig.update_layout(
        scene=dict(
            xaxis=dict(title='X'),
            yaxis=dict(title='Y'),
            zaxis=dict(title='Z')
        ),
        title='3D Random Points'
    )
    
    # Return the figure
    return fig

def make_plot(plot_type):
    if plot_type == "multiline":
        source = data.stocks()

        highlight = alt.selection(type='single', on='mouseover',
                                fields=['symbol'], nearest=True)

        base = alt.Chart(source).encode(
            x='date:T',
            y='price:Q',
            color='symbol:N'
        )

        points = base.mark_circle().encode(
            opacity=alt.value(0)
        ).add_selection(
            highlight
        ).properties(
            width=600
        )

        lines = base.mark_line().encode(
            size=alt.condition(~highlight, alt.value(1), alt.value(3))
        )

        return points + lines
    elif plot_type == "3Dplot":
        return plot_random_points_3d(100)


with gr.Blocks() as demo:
    button = gr.Radio(label="Plot type",
                      choices=["multiline", "3Dplot"], value='3Dplot')
    plot = gr.Plot(label="Plot")
    button.change(make_plot, inputs=button, outputs=[plot])
    demo.load(make_plot, inputs=[button], outputs=[plot])


if __name__ == "__main__":
    demo.launch()