import numpy as np
import matplotlib.pyplot as plt

from numpy.random import random


def get_group_averages(num_groups, group_size):
    averages = []

    rand_values = random(num_groups * group_size)
    curr_num = 0
    for i, num in enumerate(rand_values):
        curr_num += num

        if i % group_size == 0:
            averages.append(curr_num / group_size)
            curr_num = 0

    return averages


def get_bins(values, num_bins, min_val = 0, max_val = 1):
    bins = [0 for _ in range(num_bins)]
    
    value_range = abs(min_val - max_val)
    bin_size = value_range / num_bins

    for value in values:
        for curr_bin in range(num_bins):
            bin_start = curr_bin * bin_size
            bin_end = bin_start + bin_size

            if value > bin_start and value < bin_end:
                bins[curr_bin] += 1
                break

    return bins


def main(argv):
    from argparse import ArgumentParser
    parser = ArgumentParser()
    parser.add_argument('num_values')
    parser.add_argument('group_size')
    parser.add_argument('num_bins')
    args = parser.parse_args(argv[1:])

    num_values = int(args.num_values)
    group_size = int(args.group_size)
    num_bins = int(args.num_bins)

    values = get_group_averages(num_values, group_size)
    bins = get_bins(values, num_bins)

    plt.plot(bins)
    plt.savefig('out.png')


if __name__ == '__main__':
    from sys import argv
    main(argv)