#!/usr/bin/python

import matplotlib as mpl

mpl.use('Agg')

import os, errno, time, sys, pylab

from scipy import *

from scipy import optimize

from scipy import special

from scipy import stats

#import numpy as np

import matplotlib.cm as cm

import matplotlib.ticker as ticker

from datetime import datetime

import logging, csv

from os.path import basename, exists

plotdir = os.path.abspath('.') + '/results'

if not os.path.exists(plotdir):

    os.makedirs(plotdir)

    print "Created plotdir: %s" % (plotdir)

logdir = os.path.abspath('.') + '/log'

def stdev(v):

    """

    Return the Bessel corrected standard deviation of a series of measurements

    """

    return sqrt(len(v) * (mean(square(v)) - mean(v)**2) / (len(v) - 1))

def mysql_querytimes():

    """

    """

    # The s15 mysql query timing results taken from

    # https://confluence.lsstcorp.org/display/DM/S15+Large+Scale+Tests

    # Values on website are reported in seconds

    counts = [47.75, 40.99, 48.33]

    shortrunning = [0.09, 0.33]

    fullscans = [247.61, 244.24, 1088.09, 1077.38, 898.61]

    joins = [1381.44, 1291.38]

    neighbor = [676.02]

    mysqls15 = asarray(counts + shortrunning + fullscans + joins + neighbor)

    #tms = [ts * 1000 for ts in mysqls15]

    return mysqls15

def monetdb_querytimes(qlog):

    """

    """

    # From the qlog name, we can deduce the query number

    # and run type

    qtime = []

    with open(qlog, 'rb') as csvfile:

        qreader = csv.reader(csvfile, delimiter=';')

        for row in qreader:

            run = int(row[0])

            qtime.append(float(row[1])) # unit is ms

    #for i in range(len(qtime)):

    #    print "%s: qtime = %s" % (i, qtime[i])

    return mean(qtime), stdev(qtime)

def plot_results():

    """

    """

    logdir = 'sql/s15/log'

    plotdir = '.'

    plotfiles = []

    node = "stones10"

    dbversion = "dec2016sp1"

    # We have hot and cold runs

    runtype = ['hot', 'cold']

    #runtype = ['hot']

    # We divide the queries in five groups

    counts = ['q01', 'q02', 'q03']

    shortrunning = ['q04', 'q05']

    fullscans = ['q06', 'q07', 'q08', 'q09', 'q10']

    joins = ['q11', 'q12']

    neighbor = ['q13']

    queries = asarray(counts + shortrunning + fullscans + joins + neighbor)

    mysqls15 = mysql_querytimes()

    monetdbs15 = {}

    for temp in runtype:

        monetdbs15[temp] = {}

        monetdbs15[temp]['qt_avg'] = []

        monetdbs15[temp]['qt_std'] = []

        for qnr in queries:

            qlog = logdir + "/%s.%s.%s.%s.log" % (qnr, temp, node, dbversion)

            #print "qlog = %s" % (qlog)

            if not exists(qlog):

                sys.exit("Run timings. Log file %s does not exist (yet)." % (qlog))

            qt_avg, qt_std = monetdb_querytimes(qlog)

            print "%s qnr: %s: qt_avg = %s; qt_std = %s" % (temp, qnr, qt_avg, qt_std)

            monetdbs15[temp]['qt_avg'].append(qt_avg)

            monetdbs15[temp]['qt_std'].append(qt_std)

    mhot_t = [t * 0.001 for t in monetdbs15['hot']['qt_avg']]

    mhot_s = [s * 0.001 for s in monetdbs15['hot']['qt_std']]

    mcold_t = [t * 0.001 for t in monetdbs15['cold']['qt_avg']]

    mcold_s = [s * 0.001 for s in monetdbs15['cold']['qt_std']]

    #print "monetdbs15 = %s" % (monetdbs15)

    fig = pylab.figure(figsize=(28,8))

    ax = fig.add_subplot(111)

    width = 0.2

    ekw = dict(ecolor='k', lw=2, capsize=5, capthick=2)

    r1 = ax.bar(arange(len(mysqls15)), mysqls15, width, color='gray' \

               ,error_kw=ekw,label='MySQL')

    r2 = ax.bar(arange(len(mcold_t)) + width, mcold_t, width, yerr=mcold_s, color='dodgerblue' \

               ,error_kw=ekw,label='MonetDB cold')

    r3 = ax.bar(arange(len(mhot_t)) + 2 * width, mhot_t, width, yerr=mhot_s, color='red' \

               ,error_kw=ekw,label='MonetDB hot')

    ax.set_ylabel('Time [s]', fontsize='25')

    ax.set_xticks(arange(len(mysqls15)) + width)

    ax.set_xticklabels([q.upper() for q in queries])

    #ax.set_ylim(ymin=10, ymax=35000)

    ax.set_ylim(ymin=0.001, ymax=10000)

    ax.set_yscale("log")

    #ax.legend(loc='upper right')

    ax.legend(loc='upper left', fontsize='25')

    for i in range(len(ax.get_xticklabels())):

        #ax.get_xticklabels()[i].set_size('xx-large')

        ax.get_xticklabels()[i].set_size('25')

    for i in range(len(ax.get_yticklabels())):

        #ax.get_yticklabels()[i].set_size('xx-large')

        ax.get_yticklabels()[i].set_size('25')

    pylab.grid(True)

    fname = 'baseline_lsst_queries.eps'

    plotfile = plotdir + '/' + fname

    plotfiles.append(plotfile)

    pylab.savefig(plotfile, dpi=400, bbox_inches='tight')

    print plotfile

    return plotfile

def main():

    #query = sys.argv[1]

    plot_results()

if __name__ == '__main__':

    main()