import matplotlib.pyplot as plt
import numpy as np
import ipywidgets as widgets
from IPython.display import display

# Sample data
x = np.linspace(0, 10, 100)
y = np.sin(x) * np.exp(-x/5)

# Main Matplotlib Plot
fig, ax = plt.subplots(figsize=(8, 6))
ax.plot(x, y, 'b-', linewidth=2, label='sin(x) * exp(-x/5)')
ax.set_xlabel('X values')
ax.set_ylabel('Y values')
ax.set_title('Plot Centered using ipywidgets')
ax.legend()
ax.grid(True, alpha=0.3)

# Output widget to capture the plot
output = widgets.Output()

# Capture the plot in the Output widget
with output:
    plt.show()

# Clear the current figure to prevent duplicate display
plt.close(fig)

# Create a container to center the output
# Using HBox with layout properties to center horizontally
centered_container = widgets.HBox(
    children=[output],
    layout=widgets.Layout(
        display='flex',
        justify_content='center',  # Center horizontally
        align_items='center',      # Center vertically
        width='100%',             # Full width container
        min_height='400px'        # Minimum height for vertical centering
    )
)

# OPtions to Further Customize the Output widget's layout
output.layout = widgets.Layout(
    #border='2px solid #ddd',      # Add border around the plot
    #padding='20px',               # Add padding inside the border
    #margin='10px',                # Add margin outside the border
    #border_radius='10px',         # Rounded corners
    #box_shadow='0 4px 8px rgba(0,0,0,0.1)',  # Subtle shadow
    #background_color='#fafafa'    # Light background
)

display(centered_container)

# Example of a more complex layout with title and controls

def create_advanced_centered_plot():
    # Create figure
    fig, ax = plt.subplots(figsize=(10, 6))
    
    # Plot data
    x = np.linspace(0, 2*np.pi, 100)
    y = np.sin(x)
    ax.plot(x, y, 'r-', linewidth=3)
    ax.set_title('Advanced Centered Layout Example')
    ax.set_xlabel('X')
    ax.set_ylabel('sin(X)')
    ax.grid(True)
    
    # Create output widget for the plot
    plot_output = widgets.Output()
    
    with plot_output:
        plt.show()
    
    plt.close(fig)
    
    # Title widget
    title_widget = widgets.HTML(
        value="<h2 style='text-align: center; color: #333;'>Interactive Plot Display</h2>",
        layout=widgets.Layout(margin='0 0 20px 0')
    )
    
    # Create control buttons with actual functionality
    refresh_btn = widgets.Button(
        description='Refresh With Noise',
        button_style='info',
        layout=widgets.Layout(width='150px')
    )
    
    # Function to refresh the plot with new random data
    def refresh_plot(button):
        # Clear the current output
        plot_output.clear_output(wait=True)
        
        # Generate new random data
        x = np.linspace(0, 2*np.pi, 100)
        y = np.sin(x) + np.random.normal(0, 0.1, len(x))  # Add some noise
        
        # Create new figure
        fig, ax = plt.subplots(figsize=(10, 6))
        ax.plot(x, y, 'r-', linewidth=3)
        ax.set_title(f'Refreshed Plot - {np.random.randint(1, 1000)}')
        ax.set_xlabel('X')
        ax.set_ylabel('sin(X) + noise')
        ax.grid(True)
        
        # Display in the output widget
        with plot_output:
            plt.show()
        
        plt.close(fig)
    
    # Connect the button to the function
    refresh_btn.on_click(refresh_plot)
    
    # Button container (centered)
    button_container = widgets.HBox(
        children=[refresh_btn],
        layout=widgets.Layout(
            display='flex',
            justify_content='center',
            margin='20px 0 0 0'
        )
    )
    
    # Style the plot output
    plot_output.layout = widgets.Layout(
        border='3px solid #2196F3',
        border_radius='15px',
        padding='25px',
        background_color='white',
        box_shadow='0 6px 12px rgba(0,0,0,0.15)'
    )
    
    # Main container with vertical layout
    main_container = widgets.VBox(
        children=[title_widget, plot_output, button_container],
        layout=widgets.Layout(
            display='flex',
            align_items='center',     # Center all children horizontally
            width='100%',
            padding='30px',
            background_color='#f5f5f5',
            border_radius='10px'
        )
    )
    
    return main_container

# Display the advanced version
print("Advanced centered layout:")
advanced_layout = create_advanced_centered_plot()
display(advanced_layout)