"""
Demonstrate matplotlib animation of random values.
DataFrame version.

Use a uniformly distributed random number generator
in range(1, 7) to simulate die rolls. Dynamically
graph frequencies of the die faces.

Ronald Mak
Department of Applied Data Science
San Jose State University
"""

import random 
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import sys
from matplotlib import animation

def show_bar_chart(title, x_label, y_label, df, bar_toppers):
    """
    Display a bar chart.
    @param title the chart title.
    @param x_label the label for the x axis
    @param y_label the label for the y axis
    @param df the DataFrame containing the data to plot
    @param bar_toppers the text above each bar
    """
            
    plt.cla()  # clear old contents

    axes = sns.barplot(x='faces', y='frequencies', data=df)
    axes.set_title(title)
    axes.set(xlabel=x_label, ylabel=y_label)

    # Scale the y-axis by 10% to make room for text above the bars.
    axes.set_ylim(top=1.10*max(df['frequencies']))

    # Display the topper text above each patch (bar).
    for bar, topper in zip(axes.patches, bar_toppers):
        text_x = bar.get_x() + bar.get_width()/2  
        text_y = bar.get_height() 
        axes.text(text_x, text_y, topper, 
                  fontsize=11, ha='center', va='bottom')
    
def update_frame(frame_number, roll_count, faces, frequencies):
    """
    Update the bar plot contents for each animation frame.
    @param frame_number the frame number.
    @param roll_count the count of die rolls per frame.
    @param faces the die faces.
    @param frequencies the list of die face frequencies.
    """
    
    # Roll the die roll_count times and update the face frequencies.
    for _ in range(roll_count):
        frequencies[random.randrange(1, 7) - 1] += 1 

    # Set the percentages for the bar tops.
    total = sum(frequencies)
    percentages = [f'{f:,}\n{f/total:.1%}' for f in frequencies]
    
    # Create a DataFrame of the faces and frequencies.
    data = list(zip(faces, frequencies))
    df = pd.DataFrame(data, columns=['faces', 'frequencies'])
    
    # Display the bar chart for this frame.
    show_bar_chart(f'Face Frequencies for {total:,} Die Rolls ' +
                   f'(Frame {frame_number + 2})',
                   'Face Value', 'Frequency',
                   df, percentages)   

if __name__ == "__main__":
    # Read command-line arguments for the number of frames 
    # and the number of rolls per frame.
    number_of_frames = int(sys.argv[1])  
    rolls_per_frame  = int(sys.argv[2])  

    # Create the figure for the animation.
    sns.set_style('whitegrid')  # white background with gray grid lines
    figure = plt.figure('Rolling a Six-Sided Die [DataFrame version]')

    faces = list(range(1, 7))  # die faces for display on the x-axis
    frequencies = [0]*6        # six-element list of die frequencies

    # Configure and start the animation that calls function update_frame.
    die_animation = animation.FuncAnimation(
        figure, update_frame, repeat=False, 
        frames=number_of_frames - 1, interval=25,
        fargs=(rolls_per_frame, faces, frequencies))

    plt.show()

# Adapted and updated from:
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