import matplotlib.pyplot as plt
import numpy as np
import gradio as gr

def plot_forecast(final_year, cryptocurrencies, noise, show_legend, point_style, line_colors):
    start_year = 2020
    x = np.arange(start_year, final_year + 1)
    year_count = x.shape[0]
    plt_format = ({"cross": "X", "line": "-", "circle": "o--"})[point_style]
    
    fig = plt.figure()
    ax = fig.add_subplot(111)
    
    for i, crypto in enumerate(cryptocurrencies):
        series = np.arange(0, year_count, dtype=float)
        series = series**2 * (i + 1)
        series += np.random.rand(year_count) * noise
        ax.plot(x, series, plt_format, label=crypto, color=line_colors[i % len(line_colors)])
    
    if show_legend:
        plt.legend()
    
    ax.set_xlabel("Year")
    ax.set_ylabel("Value")
    ax.set_title(f"Cryptocurrency Forecast from {start_year} to {final_year}")
    
    return fig

# Create a color palette for the plot
def generate_color_palette():
    return ["#1f77b4", "#ff7f0e", "#2ca02c", "#d62728", "#9467bd"]

demo = gr.Interface(
    plot_forecast,
    [
        gr.Radio([2025, 2030, 2035, 2040], label="Project to:", info="Select the forecast year."),
        gr.CheckboxGroup(["Bitcoin", "Ethereum", "Litecoin"], label="Cryptocurrency Selection", info="Choose which cryptocurrencies to forecast."),
        gr.Slider(1, 100, label="Noise Level", info="Adjust the level of random noise added to the data."),
        gr.Checkbox(label="Show Legend", info="Toggle the display of the legend."),
        gr.Dropdown(["cross", "line", "circle"], label="Point Style", info="Choose the marker style for the plot."),
        gr.ColorPicker(label="Line Colors", value="#1f77b4", info="Choose line colors for the plot.", show_alpha=False),  # Color picker for lines
    ],
    outputs=gr.Plot(label="Forecast Plot", format="png"),
    layout="vertical",  # Improved layout for better organization
    title="Cryptocurrency Forecasting Tool",  # Added title
    theme="huggingface",  # Applying a predefined theme for better look and feel
)

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