from matplotlib import pyplot as plt
import matplotlib.ticker as tkr
import numpy as np
import json

def sizeof_fmt(x, pos):
    if x<0:
        return ""
    for x_unit in ['bytes', 'kB', 'MB', 'GB', 'TB']:
        if x < 1024.0:
            return "%3.1f %s" % (x, x_unit)
        x /= 1024.0

def plot_sizes(meta:dict):
    x = np.arange(np.max([int(k) for k in meta.keys()]))
    y = np.array([meta.get(str(i), {}).get('size', 0) for i in x])

    cumulative = np.cumsum(y)
    #cumulative = cumulative / np.max(cumulative)

    y[y<1000000000] = 0

    fig, ax = plt.subplots(2,1)
    ax[0].bar(x, y)
    ax[0].set_yscale('log')

    ax[0].yaxis.set_major_formatter(tkr.FuncFormatter(sizeof_fmt))

    ax[1].plot(x, cumulative)
    ax[1].yaxis.set_major_formatter(tkr.FuncFormatter(sizeof_fmt))
    plt.show()

if __name__ == "__main__":
    with open('metadata.json', 'r') as jfile:
        meta = json.load(jfile)

    del meta['108']


    plot_sizes(meta)