import os
import matplotlib.pyplot as plt
from config import markers, colors

experiments = [f for f in os.listdir('../data')
    if f.startswith('memcached_conn_scan') and len(os.listdir(os.path.join('../data', f))) > 0]

def parse_memcached_output(s):
    lines = s.split('\n')
    qps = int(float(lines[6].split(' ')[3]))
    return qps

def parse_perf_stat(s):
    lines = s.split('\n')
    llc_misses_u = int(list(filter(None, lines[5].split(' ')))[0].replace(',', ''))
    llc_misses_k = int(list(filter(None, lines[6].split(' ')))[0].replace(',', ''))
    return llc_misses_u + llc_misses_k

def extract_conn_qps_exp(exp):
    ret = ([10, 20, 40, 80, 160, 240, 320], [], [])

    for f in ret[0]:
        with open(os.path.join('../data/', exp, 'c%d.txt' % (f,)), 'r') as fi:
            qps = parse_memcached_output(fi.read())
            ret[1].append(qps)

        with open(os.path.join('../data/', exp, 'stat_c%d.txt' % (f,)), 'r') as fi:
            misses = parse_perf_stat(fi.read()) / (qps * 30)
            ret[2].append(misses)

    return ret

def extract_conn_qps(threads, include_caladan = False):
    ret = dict()

    for exp in experiments:
        split = exp.split('.')
        if split[-1] != ('t' + str(threads)):
            continue

        if split[-2] == 'caladan' and not include_caladan:
            continue

        name = split[-2]
        if name[0].isdigit():
            name = 'default'

        ret[name] = extract_conn_qps_exp(exp)

    return ret

def show_plot(threads, include_caladan = False):
    plt.cla()
    if include_caladan:
        plt.title('Memcached connections vs QPS, %d threads, with Caladan' % (threads,), y = 1.05)
    else:
        plt.title('Memcached connections vs QPS, %d threads' % (threads,), y = 1.05)

    data = extract_conn_qps(threads, include_caladan)

    if include_caladan and threads == 1:
        # Because we cannot run caladan on 1 threads, we use the t2 data
        # but we half the QPS
        name = 'caladan'
        data[name] = extract_conn_qps_exp('memcached_conn_scan.5.4.0-136-generic.caladan.t2')
        data[name] = (data[name][0], [qps / 2 for qps in data[name][1]], data[name][2])

    for k in data:
       plt.plot(data[k][0], data[k][1], label = k, marker = markers[k], color = colors[k])

    plt.ticklabel_format(axis = 'both', style = 'sci', scilimits = (0, 4))
    plt.xlabel('Connections (per client w/ 7 * 8 clients)')
    plt.ylabel('QPS')

    plt.legend()
    if os.getenv('SAVE_FIGURE') != 'true':
        plt.rcParams.update({'font.size': 16})
        plt.show()
    else:
        if include_caladan:
            plt.savefig('../data/figs/memcached_conn_scan.t%d.caladan.png' % (threads,), dpi = 192)
        else:
            plt.savefig('../data/figs/memcached_conn_scan.t%d.png' % (threads,), dpi = 192)

    plt.cla()
    if include_caladan:
        plt.title('Memcached connections vs LLC misses, %d threads, with Caladan' % (threads,))
    else:
        plt.title('Memcached connections vs LLC misses, %d threads' % (threads,))

    for k in data:
        plt.plot(data[k][0], data[k][2], label = k, marker = markers[k], color = colors[k])

    plt.xlabel('Connections (per client w/ 7 * 8 clients)')
    plt.ylabel('LLC misses per request')

    plt.legend()
    if os.getenv('SAVE_FIGURE') != 'true':
        plt.rcParams.update({'font.size': 16})
        plt.show()
    else:
        if include_caladan:
            plt.savefig('../data/figs/memcached_conn_scan.llc_misses.t%d.caladan.png' % (threads,), dpi = 192)
        else:
            plt.savefig('../data/figs/memcached_conn_scan.llc_misses.t%d.png' % (threads,), dpi = 192)

show_plot(1)
show_plot(1, True)
show_plot(8)
show_plot(8, True)