plot.py

#!/bin/env python3
# SPDX-License-Identifier: BSD-3-Clause
#
# Authors: Alexander Jung <alexander.jung@neclab.eu>
#
# Copyright (c) 2020, NEC Europe Ltd., NEC Corporation. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
#
# 1. Redistributions of source code must retain the above copyright
#    notice, this list of conditions and the following disclaimer.
# 2. Redistributions in binary form must reproduce the above copyright
#    notice, this list of conditions and the following disclaimer in the
#    documentation and/or other materials provided with the distribution.
# 3. Neither the name of the copyright holder nor the names of its
#    contributors may be used to endorse or promote products derived from
#    this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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import os
import csv
import sys
import fire
import numpy as np
from time import gmtime
from time import strftime
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
from common import sizeof_fmt, common_style, mk_groups, KBYTES, SMALL_SIZE, MEDIUM_SIZE, LARGE_SIZE
from os import listdir, makedirs

import pprint
pp = pprint.PrettyPrinter(indent=4)

def plot(data=None, output=None):
  WORKDIR = os.getcwd()
  RESULTSDIR = data
  RESULTEXT = '.csv'
  GROUP_BAR_WIDTH = .8
  DEFAULT = '_'

  files = []
  labels = []
  apps = []
  memstats = {}
  memusage_max = 0 # maximum observed memory size
  total_apps = 0
  bar_colors = {
    'nginx': '#0C8828',
    'redis': '#CE1216',
    'hello': 'dimgray',
    'sqlite': '#4BA3E1'
  }

  labels = {
    'unikraft': 'Unikraft',
    'docker': 'Docker',
    'hermitux': 'Hermitux',
    'lupine': 'Lupine',
    'osv': 'OSv',
    'rump': 'Rumprun',
    'microvm': 'Linux\nMicroVM'
  }

  for f in os.listdir(RESULTSDIR):
    if f.endswith(RESULTEXT):
      index = f.replace(RESULTEXT,'')
      unikernel = index

      if unikernel not in memstats:
        memstats[unikernel] = {}

      with open(os.path.join(RESULTSDIR, f), 'r') as csvfile:
        csvdata = csv.reader(csvfile, delimiter="\t")
        
        next(csvdata) # skip header

        for row in csvdata:
          app = row[0]

          memusagemb = int(row[1]) * KBYTES * KBYTES
          memstats[unikernel][app] = memusagemb
          
          if memusagemb > memusage_max:
            memusage_max = memusagemb

  # General style
  common_style(plt)

  memusage_max += KBYTES * KBYTES * 14 # add MB "margin"

  # Setup matplotlib axis
  fig = plt.figure(figsize=(8, 5))
  renderer = fig.canvas.get_renderer()

  # image size axis
  ax1 = fig.add_subplot(1,1,1)
  ax1.set_ylabel("Minimum Memory Requirement")
  ax1.grid(which='major', axis='y', linestyle=':', alpha=0.5, zorder=0)
  ax1_yticks = np.arange(0, memusage_max, step=KBYTES*KBYTES * 8)
  ax1.set_yticks(ax1_yticks, minor=False)
  ax1.set_yticklabels([sizeof_fmt(ytick) for ytick in ax1_yticks])
  ax1.set_ylim(0, memusage_max)

  # Plot coordinates
  scale = 1. / len(memstats.keys())
  xlabels = []

  # Adjust margining
  # fig.subplots_adjust(bottom=.) #, top=1)

  i = 0
  line_offset = 0
  for unikernel in ['unikraft', 'docker', 'rump', 'hermitux', 'lupine', 'osv', 'microvm']:
    xlabels.append(labels[unikernel])
    apps = memstats[unikernel]

    # Plot a line beteween unikernel applications
    if i > 0:
      line = plt.Line2D([i * scale, i * scale], [-.02, 1],
          transform=ax1.transAxes, color='black',
          linewidth=1)
      line.set_clip_on(False)
      ax1.add_line(line)

    j = 0
    bar_width = GROUP_BAR_WIDTH / len(apps.keys())
    bar_offset = (bar_width / 2) - (GROUP_BAR_WIDTH / 2)

    # Plot each application
    for app_label in sorted(apps):
      app = memstats[unikernel][app_label]

      print(unikernel, app_label, app)

      bar = ax1.bar([i + 1 + bar_offset], app,
        label=app_label,
        align='center',
        zorder=3,
        width=bar_width,
        color=bar_colors[app_label],
        linewidth=.5
      )
      
      ax1.text(i + 1.02 + bar_offset, app + 1000000, sizeof_fmt(app),
        ha='center',
        va='bottom',
        fontsize=LARGE_SIZE,
        linespacing=0,
        #bbox=dict(pad=-.6, facecolor='white', linewidth=0),
        rotation='vertical'
      )

      bar_offset += bar_width
      j += 1

    i += 1

  # sys.exit(1)

  # set up x-axis labels
  xticks = range(1, len(xlabels) + 1)
  ax1.set_xticks(xticks)
  ax1.set_xticklabels(xlabels, fontsize=LARGE_SIZE, rotation=40, ha='right', rotation_mode='anchor')
  # ax1.set_xticklabels(xlabels, fontsize=LARGE_SIZE, fontweight='bold')
  ax1.set_xlim(.5, len(xlabels) + .5)
  ax1.yaxis.grid(True, zorder=0, linestyle=':')
  ax1.tick_params(axis='both', which='both', length=0)

  # Create a unique legend
  handles, labels = plt.gca().get_legend_handles_labels()
  by_label = dict(zip(labels, handles))
  leg = plt.legend(by_label.values(), by_label.keys(),
    loc='upper left',
    ncol=2,
    fontsize=LARGE_SIZE,
  )
  leg.get_frame().set_linewidth(0.0)

  plt.setp(ax1.lines, linewidth=.5)

  # Save to file
  fig.tight_layout()
  fig.savefig(output) #, bbox_extra_artists=(ax1,), bbox_inches='tight')


if __name__ == '__main__':
  fire.Fire(plot)