#!/usr/bin/env python
import numpy as np #numerical stuff
import sys
# import argparse

import prettyplotlib as ppl # makes nicer colors and generally better to look at graphs
import matplotlib.pyplot as plt
import matplotlib as mpl
from prettyplotlib import brewer2mpl

from itertools import cycle
import colorsys

# parser = argparse.ArgumentParser(description='Generate graph.')
# parser.add_argument('filename', type=str, nargs=1, default='exp-02.csv', help='Filename')
# args = parser.parse_args()

# change font to Open Sans (has some kerning issues, though)
mpl.rcParams.update({'font.family':'Open Sans'})
# mpl.rcParams.update({'text.usetex':'true'})
color_cycle = cycle(mpl.rcParams['axes.color_cycle'])

# get name of file to process
# inputFileName = args.filename[0]
inputFileName = "exp-01.csv"

# load csv file with EPOCHTIME;NOFPROCESSES
data = np.loadtxt(inputFileName)
# data = np.loadtxt(inputFileName, delimiter=";")

# fig, ax = plt.subplots(figsize=(14,8)) #shorthand
fig = plt.figure(figsize=(7,4))
ax = fig.add_subplot(1, 1, 1)
currentColor = next(color_cycle)
ppl.plot(ax, data[:,0], data[:,1], label="Runtime", linewidth=2, color=currentColor)

fig2 = plt.figure(figsize=(7,4))
ax2 = fig2.add_subplot(1, 1, 1)
currentColor = next(color_cycle)
ppl.plot(ax2, data[:,0], data[:,2], label="Performance", linewidth=2, color=currentColor)
# ax.set_xticks(printList)
# ax.set_xticklabels(humanName);
ax.set_xlabel("Number of Hits")
ax.set_ylabel("Time / s")
ax.grid(axis='y', color='0.3', linestyle=':', antialiased=True)
ax2.set_xlabel("Number of Hits")
ax2.set_ylabel("Performance / Mhits/s")
ax2.grid(axis='y', color='0.3', linestyle=':', antialiased=True)
# ax.axis('tight')
# ax.set_yscale('log')
# ax.set_xscale('log')

# position of ticks
ppl.legend(ax, loc=0, prop={'size':12})
ppl.legend(ax2, loc=0, prop={'size':12})

plt.tick_params(axis='both', which='major', direction='in', bottom=True)

# fig.savefig('chromeProcessesPerTime.png', dpi=200)
fig.savefig("bunched-time--python" + '.pdf', dpi=50, bbox_inches='tight')
fig2.savefig("bunched-perf--python" + '.pdf', dpi=50, bbox_inches='tight')
# fig.savefig('chromeProcessesPerTime.svg', dpi=200)
plt.show()