sigmod.10.31.buffering.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
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   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 0 Axes>"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import operator\n",
    "import os\n",
    "from collections import Counter, defaultdict\n",
    "from functools import statefulMap\n",
    "\n",
    "import pandas as pd\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as mpatches\n",
    "import numpy as np\n",
    "import probscale\n",
    "import itertools\n",
    "import csv\n",
    "\n",
    "from pathlib import Path\n",
    "\n",
    "plt.rcParams.update({'font.size': 14, 'figure.autolayout': True})\n",
    "\n",
    "class Result:\n",
    "    def __init__(self, path):\n",
    "        self.path = Path(\"results\").joinpath(path, \"flamestream\")\n",
    "    \n",
    "    def lat_data(self):\n",
    "        with open(self.path.joinpath(\"latency/lat.data\"), 'r') as file:\n",
    "            return list(filter(lambda x: x > 0, map(lambda x: int(x) / 1E6, file.read().split(\", \"))))\n",
    "    \n",
    "    def notification_await_times(self):\n",
    "        with open(self.path.joinpath(\"notification_await_times.csv\"), 'r') as file:\n",
    "            return list(map(lambda row: int(row[0]) / 1E6, csv.reader(file)))\n",
    "        \n",
    "    def duration(self):\n",
    "        with open(self.path.joinpath(\"duration.txt\"), 'r') as file:\n",
    "            return int(file.read())\n",
    "        \n",
    "    def durations(self):\n",
    "        with open(self.path.joinpath(\"durations.txt\"), 'r') as file:\n",
    "            return list(map(int, file.read().split(\", \")))\n",
    "    \n",
    "    def throughput_hz(self, skip=0):\n",
    "        durations = self.durations()\n",
    "        return (len(durations) - skip) / (durations[-1] - durations[skip]) * 1E9\n",
    "\n",
    "    def plot_latencies_evolution(self, **kwargs):\n",
    "        plot_quantiles_evolution(self.lat_data(), **kwargs)\n",
    "        \n",
    "    def acker(self):\n",
    "        partitions = [\n",
    "            dict([line.split(\" = \") for line in Path(path).read_text().splitlines()])\n",
    "            for path in self.path.glob('acker/*')\n",
    "        ]\n",
    "        keys = sum(tuple(map(lambda partition: tuple(partition.keys()), partitions)), ())\n",
    "        return defaultdict(lambda: 0, {\n",
    "          key: sum(int(partition[key]) for partition in partitions)\n",
    "          for key in keys\n",
    "        })\n",
    "    \n",
    "    def min_time_updates_sent(self):\n",
    "      return self.acker()['minTimeUpdatesSent'] * self.vars()['parallelism']\n",
    "    \n",
    "    def traffic(self):\n",
    "        acker = self.acker()\n",
    "        vars = self.vars()\n",
    "        return acker.get('bufferedMessagesHandled', 0) + self.min_time_updates_sent() +\\\n",
    "          (acker['acksReceived'] + acker['heartbeatsReceived']\n",
    "           if vars['worker_environment']['LOCAL_ACKER_FLUSH_COUNT'] == 0\n",
    "           else 0)\\\n",
    "               + self.class_addressed_items_number().get('com.spbsu.flamestream.example.bl.WatermarksVsAckerGraph.Watermark', 0)\n",
    "    \n",
    "    def vars(self):\n",
    "      return json.loads(self.path.joinpath(\"../vars.json\").read_text())\n",
    "    \n",
    "    def class_addressed_items_number(self):\n",
    "        partitions = [\n",
    "            dict([line.split(\",\") for line in Path(path).read_text().splitlines()])\n",
    "            for path in self.path.glob('class_addressed_items_number/*')\n",
    "        ]\n",
    "        keys = sum(tuple(map(lambda partition: tuple(partition.keys()), partitions)), ())\n",
    "        return {\n",
    "          key: sum(int(partition.get(key, 0)) for partition in partitions)\n",
    "          for key in keys\n",
    "        }\n",
    "    \n",
    "    def snapshots(self):\n",
    "        partitions = [\n",
    "            dict([line.split(\",\") for line in Path(path).read_text().splitlines()])\n",
    "            for path in self.path.glob('snapshots/*.csv')\n",
    "        ]\n",
    "        keys = sum(tuple(map(lambda partition: tuple(partition.keys()), partitions)), ())\n",
    "        return defaultdict(lambda: 0, {\n",
    "          key: sum(int(partition[key]) for partition in partitions)\n",
    "          for key in keys\n",
    "        })\n",
    "    \n",
    "    def vertex_snapshots(self):\n",
    "        partitions = [\n",
    "            csv.DictReader(Path(path).read_text().splitlines())\n",
    "            for path in self.path.glob('vertex_snapshots/*.csv')\n",
    "        ]\n",
    "        keys = set(sum(map(lambda partition: tuple(partition.fieldnames), partitions), ()))\n",
    "        partitions = list(map(list, partitions))\n",
    "        return defaultdict(lambda: (), {\n",
    "          key: tuple(map(\n",
    "             lambda partition_row: statefulMap(operator.add, partition_row, 0),\n",
    "             itertools.zip_longest(\n",
    "               *(list(int(row[key]) for row in partition) for partition in partitions),\n",
    "               fillvalue=0,\n",
    "             ),\n",
    "           ))\n",
    "          for key in keys\n",
    "        })\n",
    "    \n",
    "    def snapshot_duration(self):\n",
    "      return self.vars()['worker_environment']['SNAPSHOTS_DURATION_MS']\n",
    "        \n",
    "    def last_in_window_notification_await_times(self):\n",
    "      return [min(slice) for slice in each_slice(\n",
    "        self.notification_await_times(),\n",
    "        self.vars()['tracking_frequency'] * self.vars()['parallelism'],\n",
    "      )]\n",
    "        \n",
    "def plot_bars_by_legend(legend_x_y):\n",
    "  fig, axs = plt.subplots()\n",
    "  xs = sorted(set(x for x_y in legend_x_y.values() for x in x_y.keys()))\n",
    "  bar_x = np.arange(len(xs))\n",
    "  margin = 0.3\n",
    "  width = (1 - margin) / len(legend_x_y)\n",
    "  border = (1 - margin - width) / 2\n",
    "  for bar_x_offset, (legend, x_y) in zip(np.linspace(-border, border, len(legend_x_y)), legend_x_y.items()):\n",
    "    axs.bar(bar_x + bar_x_offset, [x_y[x] for x in xs], width, label=legend)\n",
    "\n",
    "  axs.set_xticks(bar_x)\n",
    "  axs.set_xticklabels(xs)\n",
    "  axs.legend()\n",
    "  fig.tight_layout()\n",
    "  return fig, axs\n",
    "      \n",
    "def plot_quantiles_evolution(data, window_size=100, q=0.95, stabilize=True):\n",
    "    quantiles = []\n",
    "    prev_quantile = None\n",
    "    is_stable = not stabilize\n",
    "    for window in each_slice(data, window_size):\n",
    "        quantile = np.quantile(window, q)\n",
    "        if is_stable:\n",
    "            quantiles.append(quantile)\n",
    "        elif prev_quantile and prev_quantile < quantile:\n",
    "            is_stable = True\n",
    "            quantiles.append(prev_quantile)\n",
    "            quantiles.append(quantile)\n",
    "        else:\n",
    "            prev_quantile = quantile\n",
    "        prev_window = window\n",
    "    if not is_stable:\n",
    "        raise \"has not stabilized\"\n",
    "    plt.plot(quantiles)\n",
    "        \n",
    "def results_path(parallelism=3, rate=5, watermarks=False):\n",
    "    return Path(f\"results/sigmod/parallelism={parallelism}/distributed_acker={False}/rate={rate}/watermarks={watermarks}/iterations=10/flamestream\")\n",
    "\n",
    "def plot_probabilities(results_by_legends, legend_title=None, plot_title=None):\n",
    "    fig, ax = plt.subplots(figsize=(10,10))\n",
    "    ax.legend(results_by_legends.keys(), title=legend_title)\n",
    "    for result in results_by_legends.values():\n",
    "        plt.plot(*probscale.plot_pos(result.lat_data()))\n",
    "    plt.xlabel('Percentile')\n",
    "    plt.ylabel('Latency, ns')\n",
    "    plt.title(plot_title)\n",
    "    plt.show()\n",
    "    \n",
    "def plot_percentile(percentile, results_by_rates):\n",
    "    fig, ax = plt.subplots(figsize=(10,10))\n",
    "    plt.plot(\n",
    "        results_by_rates.keys(),\n",
    "        [np.percentile(result.lat_data(), percentile) for result in results_by_rates.values()],\n",
    "        marker='o'\n",
    "    )\n",
    "    plt.xlabel('Rate')\n",
    "    plt.ylabel(f\"Latencies {percentile} percentile, ns\")\n",
    "    \n",
    "def plot_percentile_by_throughput(percentile, results):\n",
    "    plt.plot(*plottable_percentile_by_throughput(percentile, results))\n",
    "    \n",
    "def plottable_percentile_by_throughput(percentile, results):\n",
    "    return (\n",
    "        [result.throughput() for result in results],\n",
    "        [np.percentile(result.lat_data(), percentile) for result in results]\n",
    "    )\n",
    "\n",
    "def plot_throughput_by_number_of_iterations(results):\n",
    "    plt.plot(\n",
    "        [result.iterations for result in results],\n",
    "        [result.throughput() for result in results],\n",
    "    )\n",
    "    \n",
    "def show_max_throughput(result_factory, bad_rate, max_rate):\n",
    "    pass\n",
    "\n",
    "def plot_throughput_by_parallelism(results):\n",
    "    plt.plot(\n",
    "        [result.parallelism for result in results],\n",
    "        [result.throughput_hz() for result in results],\n",
    "    )\n",
    "    \n",
    "def plot_latencies_barh(results_by_labels, ax):\n",
    "    plot_barh({\n",
    "      label: result.lat_data()\n",
    "      for label, result in results_by_labels.items()\n",
    "    }, ax)\n",
    "        \n",
    "def plot_barh(label_numbers, ax):\n",
    "    w = .70\n",
    "    ind_fs = [1, 2.0, 3.0]\n",
    "\n",
    "    def do_plot(q, c):\n",
    "        ax.barh(\n",
    "          range(1, len(label_numbers) + 1),\n",
    "          [np.percentile(result, q) for result in label_numbers.values()],\n",
    "          color=c, height=w, left=0,\n",
    "        )\n",
    "\n",
    "    do_plot(99, '.8')\n",
    "    do_plot(90, '.6')\n",
    "    do_plot(75, '.4')\n",
    "    do_plot(50, '.2')\n",
    "\n",
    "    plt.gca().invert_yaxis()\n",
    "\n",
    "    for tick in ax.xaxis.get_major_ticks():\n",
    "      tick.label.set_fontsize(60)\n",
    "\n",
    "    ax.set_yticklabels([])\n",
    "\n",
    "    ax.set_xlabel('Latency(ms)', fontsize=60)\n",
    "\n",
    "    for i, label in enumerate(label_numbers):\n",
    "        ax.text(np.percentile(label_numbers[label], 99) + 10, i + 1, label, fontsize = 60)\n",
    "\n",
    "    patch_99 = mpatches.Patch(color='.8', label='99 %-ile')\n",
    "    patch_90 = mpatches.Patch(color='.6', label='95 %-ile')\n",
    "    patch_75 = mpatches.Patch(color='.4', label='75 %-ile')\n",
    "    patch_50 = mpatches.Patch(color='.2', label='50 %-ile')\n",
    "    ax.legend(\n",
    "      handles=[patch_99, patch_90, patch_75, patch_50][::-1],\n",
    "      fontsize = 60, frameon=False, bbox_to_anchor=(1, 1), ncol=1,\n",
    "    )\n",
    "\n",
    "    for spine in plt.gca().spines.values():\n",
    "        spine.set_visible(False)\n",
    "        \n",
    "def each_slice(generator, n):\n",
    "    group = []\n",
    "    for element in generator:\n",
    "        group.append(element)\n",
    "        if len(group) == n:\n",
    "            yield group\n",
    "            group = []\n",
    "\n",
    "    if group:\n",
    "        yield group\n",
    "\n",
    "fig = plt.gcf()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   },
   "outputs": [],
   "source": [
    "from glob import glob\n",
    "import json\n",
    "from pathlib import Path\n",
    "\n",
    "all_results = [\n",
    "  Result(Path(path).absolute())\n",
    "  for path in glob('results/sigmod.10.31_/*')\n",
    "  if Path(path).joinpath(\"vars.json\").exists()\n",
    "]\n",
    "\n",
    "def result_grouper_key(result):\n",
    "  return (\n",
    "    result.vars()['tracking'],\n",
    "    result.vars().get('distributed_acker'),\n",
    "    result.vars()['worker_environment']['LOCAL_ACKER_FLUSH_COUNT'],\n",
    "  )\n",
    "\n",
    "tracking_results = {\n",
    "  'Markers' if tracking == 'watermarking' else\n",
    "  'Disabled' if tracking == 'disabled' else\n",
    "    (\"trAcker\"):\n",
    "        list(results)\n",
    "    for (tracking, distributed_acker, local_acker_flush_count), results in itertools.groupby(\n",
    "      sorted([\n",
    "        result\n",
    "        for result in all_results\n",
    "      ], key=result_grouper_key),\n",
    "      key=result_grouper_key,\n",
    "    )\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "outputs": [
    {
     "data": {
      "text/plain": "{'Markers': [defaultdict(<function __main__.Result.snapshots.<locals>.<lambda>>,\n              {'buffering_duration': 20313768980,\n               'buffered_count': 1412,\n               0: 0}),\n  defaultdict(<function __main__.Result.snapshots.<locals>.<lambda>>,\n              {'buffering_duration': 3002536916, 'buffered_count': 459, 0: 0}),\n  defaultdict(<function __main__.Result.snapshots.<locals>.<lambda>>,\n              {'buffering_duration': 64517591940,\n               'buffered_count': 2376,\n               0: 0})],\n 'trAcker': [defaultdict(<function __main__.Result.snapshots.<locals>.<lambda>>,\n              {'buffering_duration': 54477243832,\n               'buffered_count': 650,\n               0: 0}),\n  defaultdict(<function __main__.Result.snapshots.<locals>.<lambda>>,\n              {'buffering_duration': 15576950300,\n               'buffered_count': 472,\n               0: 0}),\n  defaultdict(<function __main__.Result.snapshots.<locals>.<lambda>>,\n              {'buffering_duration': 901439727, 'buffered_count': 44, 0: 0})]}"
     },
     "metadata": {},
     "output_type": "execute_result",
     "execution_count": 76
    }
   ],
   "source": [
    "{\n",
    "  legend: sorted([\n",
    "    (result.snapshots())\n",
    "    for result in results\n",
    "    # if result.vars()['iterations'] == 100\n",
    "    #     and result.vars()['parallelism'] == 15\n",
    "  ], key=lambda tuple: tuple[0])\n",
    "  for legend, results in tracking_results.items()\n",
    "}"
   ],
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    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
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  {
   "cell_type": "code",
   "execution_count": 77,
   "outputs": [
    {
     "name": "stderr",
     "text": [
      "/usr/local/lib/python3.7/site-packages/matplotlib/figure.py:2366: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n  warnings.warn(\"This figure includes Axes that are not compatible \"\n"
     ],
     "output_type": "stream"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 0 Axes>"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.gcf()\n",
    "plt.legend([\n",
    "  plt.plot(*zip(*sorted([\n",
    "    (\n",
    "      result.vars()['worker_environment']['SNAPSHOTS_DURATION_MS'],\n",
    "      result.snapshots()['buffering_duration'] / 1E9,\n",
    "    )\n",
    "    for result in results\n",
    "  ])), marker='o') and legend\n",
    "  for legend, results in tracking_results.items()\n",
    "], title='Tracking')\n",
    "plt.xlabel('Snapshot duration (ms)')\n",
    "plt.ylabel('Sum buffering duration (s)')\n",
    "plt.show()\n",
    "plt.draw()\n",
    "fig.savefig('buffering_sum_duration.png')\n",
    "None"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "outputs": [
    {
     "name": "stderr",
     "text": [
      "/usr/local/lib/python3.7/site-packages/matplotlib/figure.py:2366: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n  warnings.warn(\"This figure includes Axes that are not compatible \"\n"
     ],
     "output_type": "stream"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 0 Axes>"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plot_bars_by_legend({\n",
    "  legend: {\n",
    "    result.vars()['worker_environment']['SNAPSHOTS_DURATION_MS']: \n",
    "      result.snapshots()['buffering_duration'] / 1E9\n",
    "    for result in results\n",
    "  }\n",
    "  for legend, results in tracking_results.items()\n",
    "})\n",
    "plt.xlabel('Snapshot duration (ms)')\n",
    "plt.ylabel('Sum buffering duration (s)')\n",
    "plt.show()\n",
    "plt.draw()\n",
    "fig.savefig('buffering_sum_duration_bars.png')\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "outputs": [
    {
     "name": "stderr",
     "text": [
      "/usr/local/lib/python3.7/site-packages/matplotlib/figure.py:2366: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n  warnings.warn(\"This figure includes Axes that are not compatible \"\n"
     ],
     "output_type": "stream"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 0 Axes>"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.gcf()\n",
    "plt.legend([\n",
    "  plt.plot(*zip(*sorted([\n",
    "    (\n",
    "      result.vars()['worker_environment']['SNAPSHOTS_DURATION_MS'],\n",
    "      result.snapshots()['buffering_duration'] / result.snapshots()['buffered_count'] / 1E9,\n",
    "    )\n",
    "    for result in results\n",
    "  ])), marker='o') and legend\n",
    "  for legend, results in tracking_results.items()\n",
    "], title='Tracking')\n",
    "plt.xlabel('Snapshot duration (ms)')\n",
    "plt.ylabel('Average buffering duration (s)')\n",
    "plt.show()\n",
    "plt.draw()\n",
    "fig.savefig('buffering_average_duration.png')\n",
    "None"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "outputs": [
    {
     "name": "stderr",
     "text": [
      "/usr/local/lib/python3.7/site-packages/matplotlib/figure.py:2366: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n  warnings.warn(\"This figure includes Axes that are not compatible \"\n"
     ],
     "output_type": "stream"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 0 Axes>"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plot_bars_by_legend({\n",
    "  legend: {\n",
    "    result.vars()['worker_environment']['SNAPSHOTS_DURATION_MS']: \n",
    "      result.snapshots()['buffering_duration'] / result.snapshots()['buffered_count'] / 1E9\n",
    "    for result in results\n",
    "  }\n",
    "  for legend, results in tracking_results.items()\n",
    "})\n",
    "plt.xlabel('Snapshot duration (ms)')\n",
    "plt.ylabel('Average buffering duration (s)')\n",
    "plt.show()\n",
    "plt.draw()\n",
    "fig.savefig('buffering_average_duration_bars.png')\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "outputs": [
    {
     "name": "stderr",
     "text": [
      "/usr/local/lib/python3.7/site-packages/matplotlib/figure.py:2366: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n  warnings.warn(\"This figure includes Axes that are not compatible \"\n"
     ],
     "output_type": "stream"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 0 Axes>"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.gcf()\n",
    "plt.legend([\n",
    "  plt.plot(*zip(*sorted([\n",
    "    (result.vars()['worker_environment']['SNAPSHOTS_DURATION_MS'], result.snapshots()['buffered_count'])\n",
    "    for result in results\n",
    "  ])), marker='o') and legend\n",
    "  for legend, results in tracking_results.items()\n",
    "], title='Tracking')\n",
    "plt.xlabel('Snapshot duration (ms)')\n",
    "plt.ylabel('Buffered elements count')\n",
    "plt.show()\n",
    "plt.draw()\n",
    "fig.savefig('buffering_count.png')\n",
    "None"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "outputs": [
    {
     "name": "stderr",
     "text": [
      "/usr/local/lib/python3.7/site-packages/matplotlib/figure.py:2366: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n  warnings.warn(\"This figure includes Axes that are not compatible \"\n"
     ],
     "output_type": "stream"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 0 Axes>"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plot_bars_by_legend({\n",
    "  legend: {\n",
    "    result.vars()['worker_environment']['SNAPSHOTS_DURATION_MS']: \n",
    "      result.snapshots()['buffered_count']\n",
    "    for result in results\n",
    "  }\n",
    "  for legend, results in tracking_results.items()\n",
    "})\n",
    "plt.xlabel('Snapshot duration (ms)')\n",
    "plt.ylabel('Buffered elements count')\n",
    "plt.show()\n",
    "plt.draw()\n",
    "fig.savefig('buffering_count_bars.png')\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "outputs": [
    {
     "name": "stderr",
     "text": [
      "/usr/local/lib/python3.7/site-packages/matplotlib/figure.py:2366: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n  warnings.warn(\"This figure includes Axes that are not compatible \"\n"
     ],
     "output_type": "stream"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 0 Axes>"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.legend([\n",
    "  plot_quantiles_evolution(result.lat_data(), q=0.5) or result.snapshot_duration()\n",
    "  for result in sorted(tracking_results['trAcker'], key=lambda result: result.snapshot_duration())\n",
    "], title='Snapshot duration')\n",
    "plt.xticks([])\n",
    "plt.xlabel('Element number')\n",
    "plt.ylabel('Latencies (ms)')\n",
    "plt.show()\n",
    "plt.draw()\n",
    "fig.savefig('buffering_latencies_evolution_acker.png')\n",
    "None"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "outputs": [
    {
     "name": "stderr",
     "text": [
      "/usr/local/lib/python3.7/site-packages/matplotlib/figure.py:2366: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n  warnings.warn(\"This figure includes Axes that are not compatible \"\n"
     ],
     "output_type": "stream"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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wePFi5s6dy6pVq1iyZAkvvvhiYjXV+++/n1NPPZU1a9Ywfvz4Af086WYtIGMyRHLigQWgwWfdunXU19dz7rnnJvaFQiFOO+00Xn75ZQBqa2spKiripJNOSpQ5+eSTKSwsTJTJJdYCMiZD5HIX3C1/XMn7dbsG9J6TRpRw8xeO6rPr1dfXA1BZWZmyv7Kykk2bNiXKlJeXp6zFIyJUVFQkzs8l1gIyJkNYF5zJNQPaAhKRg4E7gAuAYmAt8G+q+px3XICbgTlAGfAqcJWqrky6RhnwH8DF3q6ngGtUNTfTSEzWSA46ubYmUF+2RNKlqqoKgIaGBkaPHp3Y39DQkDhWVVVFY2MjqppoBakqW7ZsSZTJJQPWAhKRocBLgAAXAhOBa4AtScWuA6719p/gHVsmIsVJZRYDxwPnedvxwMP9XX9j+ltyt5u1gAafcePGUVVVxbJlyxL7Ojo6eOGFFxJjPtXV1bS0tFBbW5soU1tbS2tra8q4UK4YyBbQdcBmVf3npH3r4i+81s984A5VfdLbNxs3CM0E7heRibhB5xRVrfXKzAVeEJHxqrpmYD6KMX0v5UFUC0AZqaWlhY8++giAWCzGhg0beOuttxg2bBijR49m/vz53H777UyYMIEjjzyS2267jaKiImbOnAnAxIkTOe+885g7dy4PPPAAAHPnzuWiiy7KuQw4GNgxoEuAV0XkcRHZIiJvicjVsns0bhxQBSyNn6Cq7cDzQPxPg2qgBUhOF3kJaE0qY8yglNICyrEkhMFi+fLlTJkyhSlTptDe3s7NN9/MlClT+OEPfwjAddddx7e+9S2uuuoqpk6dyubNm1m6dCnFxbs7cRYvXsyxxx7LjBkzmDFjBsceeywPP5ybnTgD2QI6FJgH3IM7DnQccJ937Ge4wQegoct5DcBI73UV0KiqGj+oqioiW5LOTyEic3DHlFL6ZY3JNJaGnfnOOOMMkn797EFEqKmpoaamZq9lysrKeOSRR/qhdoPPQLaAfMAKVf2+qr6pqg/iJhNc1Z83VdUHVHWqqk4tLy/vz1sZ85nYXHAm1wxkANoMvN9l3yog3iyJJ8FXdilTmXSsHihP6raLjx1VJJUxZlCyueBMrhnIAPQS0HWU7UjgE+/1OtwgMj1+UEQKgFPZPeZTCxThjgXFVQOFpI4LGTPo5PKDqCY3DeQY0D3AyyJyI/A4MAX4d+AGSIzlLARuEJHVwAfATbhJB4u9MqtEZAluRtwc77r3A3+yDDgz2NmDqCbXDFgAUtXXReQS4HbgB8AG7+svkootAELAz9n9IOq5qtqcVGYmbvLCX733TwFX92/tjel/KS0gC0AmBwzoTAiq+mfgz/s4rkCNt+2tTBPw9b6umzHplpIFZ11wJgfYXHDGZAjrgjO5xgKQMRkil+eCM7nJApAxGcLmgjO5xgKQMRnCHkQ1ucYCkDEZwlpAma+mpgYRSdmSl1FQVWpqahgxYgShUIgzzjiDlStXplyjqamJWbNmUVpaSmlpKbNmzWLHjtxcTcYCkDEZwtKwB4fx48ezefPmxPbuu+8mji1YsIC77rqL++67j9dff52KigqmT59Oc/PuJ0lmzpzJihUrWLJkCUuWLGHFihXMmjUrHR8l7WxJbmMyhM2EMDgEAoFuF49TVRYuXMj111/PpZdeCsCiRYuoqKhg8eLFzJ07l1WrVrFkyRJefPFFqqvdCV3uv/9+Tj31VNasWZNzSzJYC8iYDGFzwQ0Oa9euZcSIEYwbN47LLruMtWvXArBu3Trq6+s599xzE2VDoRCnnXYaL7/szhRWW1tLUVFRyuJzJ598MoWFhYkyucRaQMZkiJxuAT19PdS/u/9yfanqaDj/jl6dcuKJJ/LQQw8xYcIEtmzZwm233cZJJ53EypUrqa9350OurEydT7myspJNmzYBUF9fT3l5OUnzKSMiVFRUJM7PJRaAjMkQ0VgUQVDUxoAy1Pnnn5/yftq0aRx66KEsWrSIadOmpalWg5cFIGMyhKMO+f58OpyO3GsB9bIlkimKioo46qij+PDDD7nkkksAaGhoSFn8sqGhITFmVFVVRWNjI6qaaAWpKlu2bOl2XCnb2RiQMRnCiTkE/UH3tbWABoWOjg5Wr17NwQcfzLhx46iqqmLZsmUpx1944YXEmE91dTUtLS3U1tYmytTW1tLa2poyLpQrrAVkTIaIt4CaabYAlKG+853v8IUvfIHRo0ezZcsWfvSjH9Ha2srs2bMREebPn8/tt9/OhAkTOPLII7ntttsoKipi5syZAEycOJHzzjuPuXPn8sADDwAwd+5cLrroopzLgAMLQMZkjHgAApsLLlNt3LiRr371q2zdupXy8nKmTZvGK6+8wpgxYwC47rrraG9v56qrrqKpqYkTTzyRpUuXUlxcnLjG4sWLueaaa5gxYwYAF198MT/72c/S8nnSzQKQMRnCiTkEfdYFl8l+85vf7PO4iFBTU0NNTc1ey5SVlfHII4/0cc0GJxsDMiZDOOoQ8AUISCD3khBMTrIAZEyGiMai+MWP3+e3B1FNTuhVF5yI5AMjcJfNblTVxn6plTE5yFEHn/jwiY9YLLb/E4wZ5PbbAhKRYhH5NxF5HtgJfAS8B9SLyAYR+S8ROaG/K2pMtnNiSV1wNgZkcsA+A5CIfBtYD3wDWAZ8ETgOOBKoBmpwW1HLRGSJiBzRn5U1Jps56uzugrMsOJMD9tcFNw04XVXf28vx14Bfi8j/C1wJnA582If1MyZnOOrg9/nxi99aQCYn7DMAqer/6clFVLUT+EWf1MiYHBVPw/b7LACZ3HDAWXAiEhKRc0RkTF9WyJhcFdUofp+fgASsC87khB4HIBF5SETmea/zcLvflgJrROT8fZ7snlMjItplq086Ll6ZOhFpF5FnReSoLtcoE5GHRWSntz0sIkN7/GmNyWBOzB0D8omPmFoWnMl+vWkBzQBe8V5fDBQDVbiJCDU9vMYa4OCk7eikY9cB1wLXACcAW3CTG4qTyiwGjgfO87bjgYd78RmMyVjxJISAzx5ENbmhNwGoDDcogPvL/0lV3QL8BpjUw2tEVbU+aWsEt/UDzAfuUNUnvaSH2bhBbqZXZqJ33zmqWquqtcBc4CIRyb1Z/EzWicaiiSQEexA1Mz3//PNcfPHFjBw5EhHhoYceSjmuqtTU1DBixAhCoRBnnHEGK1euTCnT1NTErFmzKC0tpbS0lFmzZrFjx46UMu+++y6nn346oVCIkSNHcuutt6Kq/f3xBlxvAlA9MFlE/Litob95+4uASA+vcajXxbZORH4jIod6+8fhtqaWxguqajvwPBCfo7waaAGS1619CWhNKmPMoBXTWCIN21pAmamlpYXJkydz7733EgqF9ji+YMEC7rrrLu677z5ef/11KioqmD59Os3NzYkyM2fOZMWKFSxZsoQlS5awYsUKZs2alTi+a9cupk+fTmVlJa+//jr33nsvP/3pT7n77rsH5DMOpN7MhPBr4HGgDnCAv3v7TwRW9+D8V4HLvbIVwE3Ay944T3wlpoYu5zQAI73XVbizLyT+DFBVFZEtSefvQUTmAHOAlEWijMk0load+S644AIuuOACAC6//PKUY6rKwoULuf7667n00ksBWLRoERUVFSxevJi5c+eyatUqlixZwosvvkh1dTUA999/P6eeeipr1qxh/PjxPProo7S1tbFo0SJCoRCTJ09m9erV3H333Xz7299OWc57sOtxC0hVb8V9IPUB4BRVDXuHosBPenD+06r6W1V9R1X/Blzk3X9276vdc6r6gKpOVdWp5eXl/XkrYz6TaCxKQAIEfAHrghuE1q1bR319Peeee25iXygU4rTTTuPll92Om9raWoqKilIWnzv55JMpLCxMKXPqqaemtLBmzJhBXV0d69evH5gPM0B6NRecqj7Zzb5FB3JjVW0RkZXAEcAfvN2VwIakYpW4XX94X8tFROKtIG/sqCKpjDGDVrwFlItzwf3ktZ+wentPOlL6zoRhE/je57/XZ9err3d/DVVWVqbsr6ysZNOmTYky5eXlKa0YEaGioiJxfn19PaNGjdrjGvFj48aN67M6p1tvJyOtBE7G/aWf0npS1V49iCoiBcAE4BlgHW4QmQ68nnT8VOC73im1uONN1eweB6oGCkkdFzJmUIqnYVsXnMkVPQ5AIvJ14L8BAZqA5JQMZT8zIYjIncAfcVs4FcAPcIPHIm8sZyFwg4isBj7AHSNqwU29RlVXicgS4H5vXAfgfuBPqrqmp5/DmEyVnIadaw+i9mVLJF2qqtyh6IaGhpTx5oaGhsSxqqoqGhsbUdVEK0hV2bJlS0qZhobU4fD4+3iZbNGbLLgfAwuAQlWtUtWDk7YRPTh/FPAY7rNAvwc6gWmq+ol3fAFwD/BzYDnuc0Lnqmpz0jVmAm8Df/W2t4FZGJMFktOwrQU0+IwbN46qqiqWLVuW2NfR0cELL7yQGPOprq6mpaWF2traRJna2lpaW1tTyrzwwgt0dHQkyixbtowRI0YwduzYgfkwA6Q3XXAlwEOqBzY6qqqX7ee4sp+HWlW1Cfj6gdzfmExnadiZr6WlhY8++giAWCzGhg0beOuttxg2bBijR49m/vz53H777UyYMIEjjzyS2267jaKiImbOnAnAxIkTOe+885g7dy4PPPAAAHPnzuWiiy5i/Hj3ccaZM2dyyy23cPnll3PTTTfxwQcfcMcdd3DzzTdnVQYc9K4F9ChwYX9VxJhcl7Ikt7WAMtLy5cuZMmUKU6ZMob29nZtvvpkpU6bwwx/+EIDrrruOb33rW1x11VVMnTqVzZs3s3TpUoqLd0/osnjxYo499lhmzJjBjBkzOPbYY3n44d0TupSWlrJs2TLq6uqYOnUqV111Fddeey3f/va3B/zz9jfp6dO13vxvfwDCwLt0efjUS9POaFOnTtXly5enuxrGdOv4h4/nnyf9M+t3rWdD8wZ+f/HvB+zeq1atYuLEiQN2PzP47etnRkTeUNWp+7tGb7rg5uJOhbMVOJw9kxAyPgAZk8lyOQ3b5KbeBKAfANeq6j39VRljclVMY4kxIOuCM7miN2NAfuCp/qqIMbksHnBsSW6TS3oTgB4EvtZfFTEml8XX/7E0bJNLetMFNwT4FxGZAbzDnkkI/96XFTMml8TTruNzwVkatskFvQlAE4E3vdcTuhzLvoUqjBlA8clH07keUPLT+cbsS1+tTdTjAKSqZ/bJHY0xe4i3eNK1JHcwGKS9vZ0hQ4YM6H3N4NTe3k4wGPzM1+nNGJAxpp/Ex3wCvvR0wVVUVLBp0yba2tqycuVN0zdUlba2NjZt2kRFRcVnvt4+W0Ai8t/Aj5Lma9tbOcGdp82nqg/vq6wxZk/xrDef+NLSBVdSUgJAXV0dkUhPFzg2uSgYDFJZWZn4mfks9tcF9ynwjoi8ijuT9XLcFVE7gDJgEnAK8BVgPe7DqsaYXuqahp2OJISSkpI++aViTE/tMwCp6i0i8gvgX3GXtV7YpUgz8DfgClVd2j9VNCb7xWc+CPgCloZtcsZ+kxBUtRG4HbhdRMqA0UAId0qej9U6jI35zBJZcN56QI46lpVmsl5vl+Ruwl2MzhjThxJZcF4aNuxensGYbGVZcMZkgEQWnATw+/wp+4zJVhaAjMkAXR9EBWw+OJP1LAAZkwHiXXDxNGywFpDJfhaAjMkA3XbB2XxwJssdcAASkZCInCMiY/qyQsbkouQkhIC4uUHpmA/OmIHU4wAkIg+JyDzvdR7wGrAUWCMi5/dT/YzJCV0fRAVrAZns15sW0AzgFe/1xUAxUAXUeJsx5gAllmPwHkQFBnxCUmMGWm8CUBmwxXt9HvCkqm4BfoM7JU+viMj3RURF5GdJ+0REakSkTkTaReRZETmqy3llIvKwiOz0todFZGhv729MJkl+EDXeArIuOJPtehOA6oHJIuLHbQ39zdtfRJfF6fZHRKbhTu3zTpdD1wHXAtcAJ+AGvGUiUpxUZjFwPG4QPM97bROgmkEtkQXnS8qCsy44k+V6E4B+DTwOvAc4wN+9/ScCq3t6EREpBR4FvkHSrArejNrzgTtU9UlVfQ+YjdvVN9MrMxE36MxR1VpVrcWdAPUiERnfi89iTEaxB1HvVr8dAAAgAElEQVRNLupxAFLVW3GDxgPAKaoa9g5FgZ/04p4PAE+o6jNd9o/DHVNKTGqqqu3A88BJ3q5qoAV4Oem8l4DWpDLGDDopc8HFs+DsQVST5Xo7F9yT3exb1NPzReRfgcOBr3dzuMr72tBlfwMwMqlMY/IEqKqqIrIl6fyu95yD293H6NGje1pVYwZUfDbs5JkQrAVksl2vngMSkfNF5E8i8r6IHOLt+xcRObsH547HnVV7pqoO2IpXqvqAqk5V1anl5eUDdVtjeqW7LjjLgjPZrjfPAX0N+C3wIW53WXxBcD9u8sD+VAPDgZUiEhWRKHA6MM97vc0rV9nlvErcBAi8r+WSNEe997oiqYwxg068u83mgjO5pDctoOuAf1XVb+GO+8S9AhzXg/P/ABztlY1vy3HTuI8DPsANItPjJ4hIAXAqu8d8anGz7qqTrlsNFJI6LmTMoNLtg6jWBWeyXG/GgI7ADQBdtQD7XcdXVXcAO5L3iUgrsN3LeENEFgI3iMhq3IB0k3f9xd41VonIEuB+b2wH4H7gT6q6phefxZiM0t16QJaGbbJdbwJQHXAk8EmX/acBH/dRfRbgrrb6c9wHX18FzlXV5qQyM4H7gL96758Cru6j+xuTFl1XRE3eZ0y26k0AegD4DxH5F+/9ISJyKm7QqDmQm6vqGV3eK/uZ2sdblbW7LDpjBq14woG1gEwu6XEAUtUF3kOky4AC4BmgE7hTVX/eT/UzJick5oKzB1FNDuntc0A3isiPced+8wHvq2pLv9TMmBzS3YqoFoBMtutVAAJQ1Tbc7DVjTB9JJCGIdcGZ3LHPACQiTwFfV9Vd3uu9UtWL+7RmxuQQS8M2uWh/LaBtgCa9Nsb0g2gsik98iIjNBWdyxj4DkKpe0d1rY0zfctRJdL1ZC8jkit5MxVMlIqO62T9KRLpOn2OM6YWYxhLP/9gYkMkVvZmK5xHg/G72z8AWhDPmM4nGortbQJYFZ3JEbwLQVNy1ebp6wTtmjDlAjjqJrjfrgjO5ojcBKADkd7O/YC/7jTE95MScPVtA1gVnslxvAtCrwL91s/8q4PW+qY4xuclRJ5H9Fh8LshaQyXa9eRD1RuAfInIM8A9v31nAFOCcvq6YMbkkGovi87l/D9p6QCZX9LgFpKqv4K69sw74sretA6pV1dbiMeYzsDRsk4t6Oxfc29hM1Mb0OUedPdOwLQCZLNfrueBEZATuEtgprSdVXdFXlTIm1yQnIfjEhyCWhGCyXo8DkIhMwX0WaAIgXQ4r4O/DehmTU5LTsMHthrMWkMl2vV2Q7lPgX3FXR9V9FzfG9JQT250FB+66QNYCMtmuNwFoEjBFVT/or8oYk6ui6k5GGuf3+W1JbpP1evMc0LtAVX9VxJhc5sS6dMGJ31pAJuv1JgDdACwQkXNEpFJEhiVv/VVBY3JBTGOpXXC+gI0BmazXmy64v3lfl5I6/iNYEoIxn0lUoyktIJ/4LACZrNebAHRmv9XCmBznxByCgWDivXXBmVzQm5kQntvXtr/zReQqEXlHRHZ5W62IXJh0XESkRkTqRKRdRJ4VkaO6XKNMRB4WkZ3e9rCIDO3dRzYm83RNw7YuOJMLejMGhIgcLSI/E5GnReRgb98l3jNC+7MR+B5wPO7yDf8A/uDNLQdwHXAtcA1wArAFWCYixUnXWOydf563HY+tRWSyQDQWTRkD8ovf5oIzWa83K6Keizvr9UjcSUhD3qHDgJv3d76q/q+qPq2qH6nqB6p6I9AMVIuIAPOBO1T1SVV9D5gNFAMzvftPxA06c1S1VlVrgbnARSIyvqefw5hM5KizRxq2tYBMtutNC+hHwLdV9UtAOGn/s8Dne3NTEfGLyGVAEfAyMA43xXtpvIyqtuMugHeSt6saaPHKx70EtCaVMWZQcmK754IDGwMyuaE3SQiTgb90s3870KM0bBE5GqjFXcSuBfiSqr4rIvEA0tDllAbcFhe4AapRVRMZeKqqIrIFez7JDHLJs2GDF4CsBWSyXG9aQNvZHQySHY87vtMTa4DjgBOBXwKLRGRyL+rQayIyR0SWi8jyxsbG/ryVMQfM5oIzuag3AWgx8FMRGYX73E9ARE4H7gT+v55cQFXD3hjQG6r6feAt4FtAvVeksssplUnH6oFyb7wIcDPncGfmrmcvVPUBVZ2qqlPLy8t7Uk1jBlzybNhgc8GZ3NCbAHQT7gJ0n+CO3byPm8n2IvDjz3D/fO+69cD0+AERKQBOZfeYT6133+qk86uBQlLHhYwZdKIaTR0DsrngTA7o8RiQqkaAr4nID3C73XzAm6r6YU/OF5E7gD/jzqgdz247A7jQG8tZCNwgIquBD3ADXgtuywtVXSUiS4D7RWSOd9n7gT+p6pqefg5jMlHXFpAlIZhc0Jv1gH4I3Kmqa4G1SftDwHdV9db9XKIKdz2hKmAn8A5wvqr+1Tu+ADe1++dAGfAqcK6qNiddYyZwHxA/5yng6p5+BmMyVXdp2GEnvI8zjBn8epMFdzPwn0Bbl/1DvGP7DECqevl+jitQ4217K9OELQluslDXNOyABGjX9jTWyJj+15sxoPiko11Nwc2QM8YcoK5p2D7xWRecyXr7bQGJSDNu4FFgrYgkByE/7jM9/9k/1TMmN1gatslFPemCuxq39fNr4Ebc8Zu4MLDemxbHGHOAuluS2+aCM9luvwFIVRcBiMg64GUvG84Y00dUdY/1gKwFZHJBb9KwE0suiEgVkNfl+IY+rJcxOSOmMQBLwzY5pzdp2CW4KdD/hy7Bx2MrohpzAOItnZSZEGw9IJMDepMFdxdwLHAJ0IH7TM53ceeB+0rfV82Y3JAIQLYkt8kxvXkO6Hzgq6r6gog4wBuq+riIbMZdl+eJfqmhMVku3tVmXXAm1/SmBTQUdx44cDPhDvJe12Lr8RhzwOItnZQHUa0LzuSA3gSgj4FDvdergMu82ai/jD2IaswBi6dbd20BWRq2yXa9CUAPAcd4r+/A7XYLAz/FncfNGHMAuhsDsjRskwt6k4Z9T9Lrf4jIBGAq8KGqvtsflTMmF3Q3BmTrAZlc0JsWUApV3aCqvwd2ichv+7BOxuSU+Lo/KV1w1gIyOeCAA1CSocClfXAdY3JS4kFUS8M2OaYvApAx5jOId7V1nQsuprFEcDImG1kAMibNEl1wXZIQAGsFmaxmAciYNNvbg6jJx4zJRj1ZD+ip/RQp6aO6GJOT9vYgavIxY7JRT9Kwt/Xg+Lo+qIsxOSn+wKlPdndIxFtA9jCqyWY9WQ/oioGoiDG5qrvZsOPByJIQTDazMSBj0iweZKwLzuQaC0DGpNne5oJLPmZMNrIAZEya7W0uuORjxmSjAQtAIvJ9EXldRHaJSKOI/FFEJncpIyJSIyJ1ItIuIs+KyFFdypSJyMMistPbHhaRoQP1OYzpa909iGpp2CYXDGQL6AzgF7hrB50FRIG/iciwpDLXAdcC1wAnAFuAZSJSnFRmMXA8cJ63HQ883N+VN6a/dPcganwMKH7MmGzUmxVRPxNVnZH8XkRm4S5sdzLwR29tofnAHar6pFdmNm4QmgncLyITcYPOKapa65WZC7wgIuNVdc1AfR5j+kq8ldNdGnYsZllwJnulcwyo2Lt/k/d+HFAFLI0XUNV24Hl2r7haDbQALydd5yWgFVuV1QxSiSw4CYATgZizuwvOxoBMFktnALoXeAt3SW9wgw9AQ5dyDUnHqoBGVdX4Qe/1lqQyKURkjogsF5HljY2NfVV3Y/pMShfco/8PLLk+0R1nXXAmm6UlAInI3cApwKWq/fsnnqo+oKpTVXVqeXl5f97KmAOSMhdc4xpoXGNJCCYnDHgAEpF7gK8CZ6nq2qRD9d7Xyi6nVCYdqwfKvfGi+PUEqEgqY8ygkjIXXPt2aG+yNGyTEwY0AInIvewOPqu7HF6HG0SmJ5UvAE5l95hPLVCEOxYUVw0UkjouZMygkXgQ1YlAtAPamxIp2fYgqslmA5YFJyI/B2YBlwBNIhIfs2lR1RZVVRFZCNwgIquBD4CbcJMOFgOo6ioRWYKbETfHO/9+4E+WAWcGq8SDqJ3N7o6kFpDNBWey2YAFIGCe9/XvXfbfAtR4rxcAIeDnQBnwKnCuqjYnlZ8J3Af81Xv/FHB1P9TXmAGRGAPq8H7Mwy34vfRrGwMy2WwgnwOSHpRR3GBUs48yTcDX+6xixqTZ7hbQrsQ+f6QdsCw4k91sLjhj0iwRgDqSAlC41T1mLSCTxSwAGZNmibngugtAlgVnspgFIGPSLPEgavuOxL5AZ0vKMWOykQUgY9LMiTkIgq9jdwDyh5sTx4zJVhaAjEkzR72539qbIBACdmfEWRq2yWYWgIxJMyfmuM/9tDfB0ENA/ImEBHsQ1WQzC0DGpFlKCyg0DEJDEwHIkhBMNrMAZEyaORpvAe2AIcMgVJZ4JsjGgEw2swBkTJpFY1F37rf2JgiVQaiMQPtO95hlwZksZgHImDTb3QLaHYD8XkactYBMNrMAZEyaOfEVUCOtEBoKoWGJZ4IsC85kMwtAxqSZow7++Jt4C8i64EwOsABkTJp1G4A63QBkXXAmm1kAMibNnJiDX7038QAUP2Zp2CaLWQAyJs0cdXavixJy07AF8IvPHkQ1Wc0CkDFpFo1F8avXBPJaQOAGIGsBmWxmAciYNHPUwR/PdksOQPgsC85kNQtAxqSZE3MIxGIgfsgvdlOxAT9iXXAmq1kAMibNohrFp47b8hFJagFZEoLJbhaAjEmzmMbwx5xE4KGgFBA3AFkatsliFoCMSTO3Cy7qTkQK4PNDQSkBrAVkspsFIGPSLKpR/E50dwsIYMgw/Ko2BmSy2oAGIBE5TUSeEpFNIqIicnmX4yIiNSJSJyLtIvKsiBzVpUyZiDwsIju97WERGTqQn8OYvuTEnD0DUKgMv6q1gExWG+gWUBHwHvBNoL2b49cB1wLXACcAW4BlIlKcVGYxcDxwnrcdDzzcj3U2pl856uB3wnsEoIDGLACZrBbYf5G+o6p/Af4CICIPJR8TEQHmA3eo6pPevtm4QWgmcL+ITMQNOqeoaq1XZi7wgoiMV9U1A/VZjOkr0VjUHQPqEoB8Ox1LQjBZLZPGgMYBVcDS+A5VbQeeB07ydlUDLcDLSee9BLQmlTFmUHGcMD7VPbvgYo61gExWy6QAVOV9beiyvyHpWBXQqBqftwS811uSyhgzqMSciDv5aNcuuJiDY0kIJotlUgDqFyIyR0SWi8jyxsbGdFfHmD1EYxECyp4tIJRotCNt9TKmv2VSAKr3vlZ22V+ZdKweKPfGi4DE2FFFUpkUqvqAqk5V1anl5eV9XGVjPjsnFsVPN11wCo4FIJPFMikArcMNItPjO0SkADiV3WM+tbiZdNVJ51UDhaSOCxkzaDixqLseUDctoJgTTlu9jOlvA5oFJyJFwOHeWx8wWkSOA7ar6gYRWQjcICKrgQ+Am3CTDhYDqOoqEVmCmxE3x7vO/cCfLAPODFaORgnspQUUtQBksthAt4CmAm96Wwi4xXt9q3d8AXAP8HNgOXAwcK6qNiddYybwNvBXb3sbmDUQlTemP0Q1hg+B/JLdO70WkON0pq9ixvSzgX4O6FlA9nFcgRpv21uZJuDrfVw1Y9LGUQe/Pw98SX8Phoa5Y0BOJH0VM6afZdIYkDE5KaZKIFCQutObjDQaswBkspcFIGPSLEoMf9cA5A/glwCOBSCTxSwAGZNmjoI/ENpjv98fJGYPoposZgHI9DtVZe2OtTS22YPAXcU0RkwgEOwuAOURtbngTBYb0CQEkzt05yY+eGsRf921hr82r2NDpAkfPs4++GS+fsw3mFx+DKu3r+adxnfYsOMTJviHcUwsn4qOXRSXVSJDR8PQQ6CoEgL56f44/SY+15s/OGSPYypBIrF2OiIOBUH/gd1A1V3meyCpgipNHU1sat7Iro5ttHTuoCPczNThxzKiaASIu+ge/oH9FeTEHJo6m9jWvo3S/FKqCr0ZvCIdsPNT2PEJtDXB6BPR0kPojMbID/hIevadtkgbG1s2kufLY2zp2O5vpAo7PqHl01qcgjKCIz9HsGAoAV8g5Vp0NhNd9xzbNr5O+ZAKfIXDofAgqDyaWFE5G5s3UppfSml+af99U9LIAlAPNLc08M76v/P+tpWs3PExH7RuokwDHBr1c3hnmGGOj6i/iIivhF0BPw2BNjZKC3XaSqsToU2jRDRGAXkU+4ZQGiwhL+AHieIQJU+gCD/FMSgAHBEiIsRQShRKHYfCcCfbIi3UOe3US4QiDXCYfyhjCkZTXDCUbbEdNMR20RTrIOgfgk8KUSlEEBAHlRjiFzQoREQJAGX4KY3BEI2h4nN/KfiDFBcMo6SokvyCoaxufJ83G1eyur2OITE4LJLHoR0wNDaEjsIqYqUjyCstpzQYpCQvSLRtCy+t/wu10sSGYBCfKid0dDKrtY2NwQC/d55j2eYX3LVuvP+IAVWi3uuRkSilMYc8hTxVhsRihPCTp0EKCFGWV0Jl0UFUDCkhL9pJMNKORtqpi7byqXawKRYmEswnFhyCBocAihPuJBbpwCFAeEg5zpByfH4Bokh4B4SbKUYYqn6KVWmMtrHeaeUT7SCMMjQQoiy/jJGFB3P8kEM5vHMYBc3tlLEDf3QbO6Nb2eAPsE78bFBlhzi0+2K0E8GPMhwf5dEIJTGlbUg5raFyOvwh8sLNFLRuBqA1GuS9TTsJ+n28um4bT7yxkTKN0VIY5aqfzaChuJPtwXbyfUEKAwUUBUMU+0IUaAEBJx+iYRxtJRxroy3azK5YGzslQidQpn7K/IUMyx9GebCU8mAJBwVKaIq0Utexg4bILhxiFAQChPxB8gT80TDBaCf+GPgKD4aisVA4kmhbPU7zJzhtm2lH6fAHafP5caIdSGcTfmcXbURYHwyw079n0BRVPt/RySXNLRzkKGtDQ9lYUEJnoIAi9TPECaAKn0g76/wd1PkiBAmQJ/nkEaLcBwfH2hjWtp1dsTCfBAOsDwaJinCsBhnPUMq0is78obSHiujID7Kls466jjo2OU1s105iSb//J3SGObOtgwnhTtYGg3yQF2RjIEDpSzHyogXsjFbQ6hMieZ10BMLsDIRp8e1ulY4hxJmFh3N86XiaOjZT117Pho5GNnQ2sdHPHt+DQvUxWvMZTT5Doh2si+1idV6ADp+PUCzGEeEIYyMR6gIB3s/Pp80niMKhUsJxDGccAQKRbdC5jeZYB2tDxawNBKmXKEEJEJI8QpLHUPwMd6AiGkFE2BXIo9nvh0ABIwoqGVl4CFWFIxkiYQLaji/aQvGIs9kZPIJPt7dxyLAhHD+6jP4mSfN6Zr2pU6fq8uXLe33ew0tuY0HD4wAcEolwZDjCVr+fNXl5dPi6/+tydCTCoeEIhaoUxJQ8VZr9Prb7fDR5P5R5quSrEhVo9vlo9vloFx9BdcsLsNPno8Xv9pT6FIZG/RRFgnT6I2zJi6JJf00FVClzlE5RWn2+xC94cP/j56tS4H2NiLCzS5m9OSjqMKkzQpMvyAf5PsJ7+cxxflVGtpdSmnc6k4efw4SSQkYWRontrKOxbjVvtCxnB7sYw1CO8JczLDScj0MFrAp0sNbZwo62Jto6mhFtBwnj+CNEfA4dvhi6j1uLQmnUR0hjBHEIEAPAQYjiw0fMfeATIaoBComQpzF8wC6fjya/j50+H0MdZVREGRGGodpJuz/GDr+fD/KCbA64f7ONikTY4ffT4kvtxc6PxTjIiVEci1ESi+EIbPP72er30+rz4ff+bX1ADLw/NKBy09l80Hxu4jqTDi7h0IPu4zlnFT5VJoTDTAxHiAJtPh9tIjT5fWz3+2ny+fABhTEvYMd85Dt5SLQQNIDP30wk0MHOQIwGfyDl38+nynDHocD7mYggRASiIoQRokLKz1hc0Pu5LtAY+arkKcTUT5R8YrECijsLKAkXUBwpwOcUoLECIgRoKGpgY+lmWoPtSXVwf2YiSfXKiyljIsIhYfBJmIjPodkn7PL52eYL0uwX8jTAcCfE8FgIdSJsDOykMW/PLstQLMa4SITR4RiFkQJwColES2kICusLd9JQ0Jp4OCTkFFMsBxGkiXaa2SkORbEYFU6MgxzloKiP0nCA4kge7X6Ht4s6eafAn/ge+VQZHoWiSAgnfBDtzmiKCDM8Vk+lr5FwoJNNebAxCG0+YVhnIZH2Q2iMHEZZ8XaCBZtp9zVS5gQZ1xZhasc2mgNRXgvl8V5+kFiXf4uhEWFcJMqh0XaiAq3e75Ftfh+N/gA7vd8d+TGlJObgiLC9mz8MACbVTeHVnV8B4GsnjubHXzq623I9ISJvqOrU/ZWzFlAPHHPoxfyfjc1UFBxKydCR5JWUM2RYFSWFQwhLIzFpxedz8PkdAuQTYiTbm320dIQ56uBiDi0vxK8OhFuItu2gcWsjW1s6aWx1aGiN0uoEieYPxQkWIT4f4WiMcCRKzHEIBPMI+hX87YwoGcaI0kIqivMJ+H3saG/hg6bVbG/dgS92MJ0dJbRHYGRJkNGhTg4K7AR8RGM+wo6P7bta2bpjJ9t37KRD/Wh+GdFQiIhfiETDRMIRnEg7BbqNPN2Gn11UFh1ORcVxDC0fxahhQ6gsDbCheR3bOrYhToyWxk207NhKSyTKrkiUToKcMvnLnDDmEPx7CVQXd7Pv5C7vVZX129oI+ISq0gKCfh+RaJS3N2+mdv0GPtraSFs4TGu4k7DjcFBBJSOLRnJQ4RAiTozmjigdba2UDMljdEUZ44YXMjRf8W94icJ1S8lv+pCtRRP4tGgy6wsm0Jl3EL5gAQEfhPICFAT9FAR9dIQdmrdtwrd1DSdFmgiX+Pk0fwubtIEJwQryfRX4Y8M4uHAER5SUc0RejGB4J+GWHUTbmghrgJ1F42gOjSIcg+Ht6xm+fQXFzR/RVjaJnVXT6CgchaNCZzRGR8ThsPIiJo0oYXvHUXzY9CFHHXQUheJnS+MWNm7Zzuat22nauZOhoSAjhoY4uHQIwSEltAdKaPMXEwgEOagwj9JQEICtrZ1sbGpn67btOOF2WqPbaQ43MnxIGWOHHULl0FIijrKtuZ1tze20OT6CoRJC+QGCAtKygUDjcvw7PkRKx+KrOB7f8AkE/AGC0WaC7Y0UFJVRWnEIeQEfqkpjSycfb2mlflc7xflBygqDDB2SR3lxPoV5Pt7d+i5hJ8xB+VVEwyVEHAjlO6ivFZ8vyuiS0QR8Sb+eomG0pZ4PW0I8v66ZFz7cSmNzJ+KD7QhDhwT58rhhTBgl5Bc04otE0OZdBFpaKC48BEoOgYIS/N4vZEHw+yDP76c12kRTZDOTK46kJK8k9ecw0on4fOAPJvbFYkrdznYadnVwQkeU+u3r+LTpbXzBscBIoo6fIyuLOHbUUMYeVIjPJ3REHLa2dNIedlDc1HufCMUFAYryAxTmBfB18/+lI+LQ0hnlspiyo3MXdbvq6Yz46Yj4USefg4YUURoKUhhQJBbGiXQQi4Rx8krQQAGRWJiYKmiQaCSMtjfR1lLHlpaP2NZeT3ssj45YPu2xfEadeBxzDj6MQ4YNYVTZnmOS/cFaQMYYY/pUT1tAlgVnjDEmLSwAGWOMSQsLQMYYY9LCApAxxpi0sABkjDEmLSwAGWOMSQsLQMYYY9LCApAxxpi0sABkjDEmLXJqJgQRaQQ+SXc9jDEmy41R1fL9FcqpAGSMMSZzWBecMcaYtLAAZIwxJi0sAJmsJiLrReQ76a5HNhGRZ0XkZ+muhxn8LACZQUtEHhIR7WZ7Jd11OxAicoZX/+HprosxA8EWpDOD3d+AWV32hdNREfPZiEhQVSPprocZONYCMoNdp6rWd9m2762wiJSKyAMiskVEmkXkORGZmnT8chFpEZHzRWS1iLSJyFPeef8kIh+KyE4ReVhEQknniYhcJyIfi0i7iLwrIl9POj7Wa91cKiLLvOu+LyLT48eBZ7zijV7Zh/byGeItpbNF5FXvWstF5Piun2Mv5w3/LJ/VExCRe0Wkydt+KiK+pHvlichPRGSjd93XRWRGN3W5QEReE5EwMAOTUywAmZwhIgL8GRgJXARMAZ4H/iEiBycVzQeuBb4GnA1MBZ4EZgOXApd4589LOuc24ErgKmAS8H+B+0Xkwi7V+DHwH8CxwOvAb0SkCPjUuzbAUcDBwDf385H+L3A9cDywDXjU+4y9cSCfFa+8D6gG5gJzgPlJxx8ETgdmApOBRcAfReTYLtf5CXATMAF4tZd1N4Odqtpm26DcgIeAKNDSZftJUpn1wHe812d5x0NdrvMWcJ33+nJAgfFJx+8EHGB4l3v/yXtdCLQDp3a57kLgL97rsd515yYdH+ntO8V7f4b3fvh+Pne83IykfSd7+0YlfY6WvZw3/EA/q/f+WeADvOcIvX03ARu914cBMWB0l/v/AfhFl7pcmu6fI9vSt9kYkBnsnsf96zvZjr2U/RwwBLeLK3l/Ae4vzbhOVV2T9L4BqFfVrV32TfJeT/KuseT/b+fuWaOIwiiO/59ICIiksNDFL2Al2Ig2WimI4iew8jP40gUFC0ECsbJQBJs0FoJoZ1BQRANiQDGoSETRiKSLL0HQPRZ3xwyXWbKzWRg2OT8Iu5uZebizxZy9e5+diCj/snuUFIBlL0vPFzuPO7qMdy3dan2uUaPuuRaeSSqf61PgYkSMk2ZkAcxn7/MY8CCr87zGWG2DcQDZsPsl6X2P+46QLqYHK7Ytl57/ybYJyBfHxepX2MXjCeBTtl9+3P/XktS5QPf7VXi5dhEGRa02KQTKRitq1D3XXox0jtlXUWsle/2zRl3bYBxAtpm8AHYCbUkLA6w7D/wm3f8q/4RfR9G9t2X9Q2IJ2BoR45KKcN07gLqF/RERpVnQAWBR0nJEzJHCryXpYfcSttk5gGzYjUVEK/vfX0lLFfvOAE+AOxFxDqJB6x8AAAEHSURBVHgDtICjwIykx/0MQNL3iJgEJjtNAI+AbaSLclvStR5LfSTNHI5HxF1gRdKPNY7pZpY0u7gUEVOkpoe8kWA9dgFXIuIqsAc4S2rEQNK7iJgGbkbEaVLwbyet+yxIuj3AcdgQcxecDbvDwNfsb65qx86n9WOkdYjrwFvgFrCb1TWUfk0AF4AzwGvgPqmL7EOvBSR9Ac6TOuW+AX3fbUCpFf0kcAR4RVonm+i3XoVp0kxtlvRe3gCmSttPkTrhLpOC/h5wCN+N3kp8N2wzM2uEZ0BmZtYIB5CZmTXCAWRmZo1wAJmZWSMcQGZm1ggHkJmZNcIBZGZmjXAAmZlZIxxAZmbWiH+kXVLS5CsRoAAAAABJRU5ErkJggg==\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 0 Axes>"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.legend([\n",
    "  plot_quantiles_evolution(result.lat_data(), q=0.5) or result.snapshot_duration()\n",
    "  for result in sorted(tracking_results['Markers'], key=lambda result: result.snapshot_duration())\n",
    "], title='Snapshot duration')\n",
    "plt.xticks([])\n",
    "plt.xlabel('Element number')\n",
    "plt.ylabel('Latencies (ms)')\n",
    "plt.show()\n",
    "plt.draw()\n",
    "fig.savefig('buffering_latencies_evolution_watermarks.png')\n",
    "None"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "outputs": [
    {
     "name": "stderr",
     "text": [
      "/usr/local/lib/python3.7/site-packages/matplotlib/figure.py:2366: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n  warnings.warn(\"This figure includes Axes that are not compatible \"\n"
     ],
     "output_type": "stream"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.gcf()\n",
    "plt.legend([\n",
    "  plot_quantiles_evolution(result.lat_data(), q=0.5) or legend\n",
    "  for legend, results in tracking_results.items()\n",
    "  for result in results\n",
    "  if result.vars()['worker_environment']['SNAPSHOTS_DURATION_MS'] == 100\n",
    "])\n",
    "None"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "outputs": [
    {
     "name": "stderr",
     "text": [
      "/usr/local/lib/python3.7/site-packages/matplotlib/figure.py:2366: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n  warnings.warn(\"This figure includes Axes that are not compatible \"\n"
     ],
     "output_type": "stream"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.gcf()\n",
    "plt.legend([\n",
    "  plot_quantiles_evolution(result.lat_data(), q=0.5) or legend\n",
    "  for legend, results in tracking_results.items()\n",
    "  for result in results\n",
    "  if result.vars()['worker_environment']['SNAPSHOTS_DURATION_MS'] == 500\n",
    "])\n",
    "None"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "outputs": [
    {
     "name": "stderr",
     "text": [
      "/usr/local/lib/python3.7/site-packages/matplotlib/figure.py:2366: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n  warnings.warn(\"This figure includes Axes that are not compatible \"\n"
     ],
     "output_type": "stream"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.gcf()\n",
    "plt.legend([\n",
    "  plot_quantiles_evolution(result.lat_data(), q=0.5) or legend\n",
    "  for legend, results in tracking_results.items()\n",
    "  for result in results\n",
    "  if result.vars()['worker_environment']['SNAPSHOTS_DURATION_MS'] == 1000\n",
    "])\n",
    "None"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "outputs": [
    {
     "name": "stderr",
     "text": [
      "/usr/local/lib/python3.7/site-packages/matplotlib/figure.py:2366: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n  warnings.warn(\"This figure includes Axes that are not compatible \"\n"
     ],
     "output_type": "stream"
    },
    {
     "data": {
      "text/plain": "<Figure size 2880x1440 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(40, 20))\n",
    "plot_barh({\n",
    "  legend: result.lat_data()[5000:5100]\n",
    "  for legend, results in tracking_results.items()\n",
    "  for result in results\n",
    "  if result.vars()['worker_environment']['SNAPSHOTS_DURATION_MS'] == 100\n",
    "}, ax)\n",
    "fig.savefig('buffering_latencies_barh_100.png')"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "outputs": [
    {
     "name": "stderr",
     "text": [
      "/usr/local/lib/python3.7/site-packages/matplotlib/figure.py:2366: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n  warnings.warn(\"This figure includes Axes that are not compatible \"\n"
     ],
     "output_type": "stream"
    },
    {
     "data": {
      "text/plain": "<Figure size 2880x1440 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(40, 20))\n",
    "plot_barh({\n",
    "  legend: result.lat_data()[5000:5100]\n",
    "  for legend, results in tracking_results.items()\n",
    "  for result in results\n",
    "  if result.vars()['worker_environment']['SNAPSHOTS_DURATION_MS'] == 500\n",
    "}, ax)\n",
    "fig.savefig('buffering_latencies_barh_500.png')"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "outputs": [
    {
     "name": "stderr",
     "text": [
      "/usr/local/lib/python3.7/site-packages/matplotlib/figure.py:2366: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n  warnings.warn(\"This figure includes Axes that are not compatible \"\n"
     ],
     "output_type": "stream"
    },
    {
     "data": {
      "text/plain": "<Figure size 2880x1440 with 1 Axes>",
      "image/png": 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mZWeAWZIkSZIkSZIkSZIkbZCmTJnCZZddllVvbAHmESNG1Lg+ZswY5s+fT7t27cozkCSpUUkpTY2IceQ+Mfl/IuKfKaXZte0XEccDJ6zjsmYFjLgQuBa4JaX0r9rckFJaCowFxkZET6pOZ94px6UdgBHAIQXMU3IppY8jog9wDXAGULGOW14Hzkkpjc+1WN0r83twSa6Tmte4Z0vgWOC7VH2tOlJ1kvVcqk6IHg38NaX02bpfUeMXEU2BQ3MsPZxSWl2CLZ7NUds+IrZMKX1Ugv511qShB5AkSZIkSZIkSZIkSVL9qKys5K677qrxmi+++IJ77rmnTBNJkhqpX+WpdwQmRkTn2jSJiBOAmn9wFSil9GhK6Re1DS/nuP//gB7AhDyXHBwRg4ocr2RSSotTSj8GdgcuAV4AZgMrgU+AN4E/A0cDe9YQXq6g6vTeNU0Dbs5zfbOIuAiYCfweOBjoBLSi6pTqnYFjqPq+vhkRx9ThZTYme1H19cn0t1I0TynNper7n2m/UvQvBQPMkiRJkiRJkiRJkiRJjdQzzzzD+++/v87r1nVKsyRJNUkpPQP8b57lHYHpEXFx9Sm9WSLiWxHxMHAv0HSNpVV5eq4oetgipJSWAN8D3spzyX+XcZwapZRmpJSuSCntn1LaJqXUIqW0WUppt5TSD1NKf00p5fu6AvwE+GZmLdepwBGxETAKuBJoXYvxtgX+Uh143tDtlaf+Rgn3mJ+jtm0J+9dJ03VfIkmSJEmSJEmSJEmSpPVRbYPJU6ZMYdq0aXTr1q1+B5IkNWbnAvsAe+ZYawVcDlwWEdOA94FPgXbAbsA2Oe5ZRVUwdniOtc9KMG9BUkqfRMSZwLM5lveJiF1SSjPKPVcpRUQH4LKM8r0ppb/nueU+4IgitroyIhanlDJPet6Q7JynfmlEVJZoj1y/MPCNEvWuMwPMkiRJkiRJkiRJkiRJjdCSJUt45JFHsupdunThrbeyD5C88847uf7668sxmiSpEUoprYiIw4DRVAWZcwmqAs65Qs5rqgSGAovyrM8rZsa6SilNiIhngP45lr8LrNcBZuDXwCZrPP8U+FmuCyPiFGBQjqUHgN8D04DmwP7AJcDemXtFxN9SSvlOtSYifktVyL0Y81NKOWf/mtg6T/3ket7XALMkSZIkSZIkSZIkSZLqzwMPPMDy5cuz6sOHD+eaa65h+vTpa9XvvfdefvOb39C0qXESSVJxUkpzIuJA4HbgB0W2WQycnFJ6LCJOzHPNR0X2LoUHyR1g3q/cg5RSROwHDMkoX55SyvpaR0Qz4OocbS5MKV2zxvNlwOMR8RTwCDBgjbWWwBXAcTWMdQywfS3Gz+U98oSvvyY2Wfcl9WLjBto3S5OGHkCSJEmSJEmSJEmSJEmlN2LEiKxa27ZtGTRoEEOGZOaT4OOPP2bMmDFlmEyS1JillJanlE6k6uTdCQXcugq4G+iaUnqsupbv9N13i5+wzp7OU9+lrFOUUEQ0AW6m6oTsL71B1UnKuRwNbJFReyYjvPyVlNIXwEnAwoylwRGxZeETNwobNdC+se5LysMAsyRJkiRJkiRJkiRJUiMzc+ZMXnjhhaz6McccQ8uWLTnxxBOpqKjIWs8VepYkqRgppRdSSn2BnYGfUHUC71TgQ2AlsAL4NzCWqpNyO6eUTk4pfbhGmx3ytH+9vuauhfeAyhz1rcs9SAmdCeyVUTu3Onicy9E5apfXtEFKaRHwh4xyM2BQrSZsfFY39AANzc/8kCRJkiRJkiRJkiRJG4Tnn3+e22+//avnb7/9ds7rhg4dWuuev/3tb2nXLt/hkOtWWVnJs88+y5NPPsnkyZOZOXMmn3zyCZ9//jnt27dn1113ZcSIEWy33XYF9c0XRD755JMB2HLLLenfvz9/+9vf1lofM2YM8+fPr9Nrqq0vvviC8ePH89xzzzF58mRmzZrF3LlzWbZsGRUVFWy88cZsvvnm7LLLLuy+++707t2bAw44gJYtW9b7bA3hnXfeYcyYMbzwwgvMmDGD999/n6VLl7J69WratGnDNttsQ9euXendu1y3PBoAACAASURBVDeDBg1im222Ket8L7/8MmPGjGHSpEnMmDGD+fPn89lnn7HJJpuw0047cc0119C3b9+yziRp/ZBSeht4m6oTfgvVJU99SvET1U1KqTIiFgDtM5baNMQ8dRURmwNXZpQfSimNq+G2/TKezwX+XovtHgIuzajtC/yxFvc2Nsvy1FullJaXdZIGYoBZkiRJkiRJkiRJkiRtEN5++21Gjhy5zutqc82Xhg8fnjPsG5H96dx33nnnV+HolBJ33nknV111Fe+++27O3h999BEfffQRCxcuLCjAXFlZyV133ZVV32677TjwwAO/ej5kyJCsAPMXX3zBvffey7nnnlvr/Qr1wQcfcP3113PHHXewaNGinNesWrWKefPmMW/ePN58801Gjx4NwEYbbcRhhx3GGWecwaGHHkqTJuX/8PHhw4dz2WWXZdUrKiq4+eabOfPMMwvq9+ijj/LrX/+af/zjH3mvWbRoEYsWLeLVV1/lwQcf5Kc//SkDBw7k8ssvp1u3bgW/hi/17NmTyZMnr1U7++yzuemmm756/swzz3DhhRfy0ksv5eyxYMECFixYwDvvvGOAWVJ96JGj9u+U0r/KPUiG7B/0669rgM3WeP4ZcEG+iyOiHdmnTb+cUkq12Ov16v6t1qhlnvz8lZTSDrXoub6ak6e+GTC7nIM0lPL/K06SJEmSJEmSJEmSJGkDtmDBAg466CBOO+20vOHluhg3bhzvv/9+Vv3EE09cK1g9ePBg2rTJPiwy3+nNdbV69WquuuoqunTpwnXXXZc3vFyTFStWMGrUKI444ghuueWWepgyv1WrVnHaaaflDC+3atWKRx55pKDw8rvvvkv//v056qijagwv51JZWcno0aPp0aMHF198MZWVlQXdXxtffPEFZ511FgcddFDe8LIk1aeI6AJ0zLH0TLlnWVNENGHtwO+X8p2o+7UVET2B0zLKV6eUsv8h8f/k+piGWv2DJqVUCcyqRb8NQebX4UuZJ3s3WgaYJUmSJEmSJEmSJEmSymT+/Pnsv//+jB8/vt72yBdAHjJkyFrPW7VqxdFHH5113SuvvML06dNLOtOCBQvo168fv/zlL1m+vDSfil4fod18li5dysCBA7njjjuy1tq1a8f48eMZOHBgrfuNGzeOnj171vl9sGrVKq688koGDx7MypUr69Qrs+/gwYO59dZbS9ZTkopwZJ76X8o6RbZO5M5erlen5kbVbzXdzNqv5W3gt+u4ddMctSUFbP1pLfptCKbkqe9b1ikaUNOGHkCSJEmSJEmSJEmSJGlDsHr1agYNGsSMGTOy1rbbbjs6d+5Mx44dSSkxe/ZspkyZwrJlhR3muHjxYkaNGpVV79mzJ7vuumtW/eSTT2bkyJFZ9TvvvJPrrruuoL3z+fjjj+nXrx+vvfZajdd17NiRzp0706FDB1q1asXChQuZN28er732Gp9//nlJZinG3LlzGTBgAJMnT85a23HHHRk7diw777xzrfuNHTuWwYMH1/ia2rVrR9euXdl8881p0aIFH3/8MW+88QYfffRRzusfffRRTj75ZB544IFaz1GT888/nzFjxmTVN998c3bbbTc6dOjw1VxTpkxhwYIFJdlXkjIMzVH7GBhX5jkyHZynPrOsU9TdqcA+GbWfppSK+aGb6nBt5Lyq8fsn8AXQLKN+IFDej5loIAaYJUmSJEmSJEmSJEnSBmHo0KEMHTr0q+cjRozglFNOyboupUIyOLV34403Mm3atK+eN23alB//+McMGzaMb37zm1nXr1ixglGjRrHZZrk+pT63Bx54IOcJxyeffHLO6/v27cu2227L+++v/Unx99xzD7/+9a9p2rRu0ZLPP/+cQYMG5Q0vt2rVinPPPZdjjjmGb33rW1QdBrm2lStXMnXqVB577DHuu+8+3n777TrNVIi33nqLww47jFmzsj/lfe+99+bxxx+nQ4cOte43depUjj322Jzh5VatWjFs2DCGDRvGHnvskfW1SCnx8ssvc+211/KXv2QfPvrggw9yyCGHcNppp9V6nlyee+65rBO4Bw8ezAUXXMB+++1HRUXFWmuVlZVMmDCBli1b1mlfSVpTRBwB7J5j6X9SSl+Ue54M389Tf7GsU9RBRHwDuCaj/FhK6Yla3L4oR23jArbPvPaTAu5tNFJKiyNiAtmB+IER0T6lNK8BxiqrXMeYS5IkSZIkSZIkSZIkqcTWDC9vv/32TJkyhd///vc5w8sAG220EccffzzbbbddrfcYMWJEVq1p06accMIJOa9v0qQJJ554Ylb9448/5oknapNhqtmFF17IpEmTcq4deeSRzJw5k2uuuYYePXrkDC8DNG/enL333pvLL7+cmTNnMn78ePr27Zv3+lKZNGkS3/nOd3KGl4844gieffbZgsLLK1as4Ljjjst5qnafPn2YOXPmV++HXK8tIujRowcPPvggjz/+OK1bt8665rzzzuPdd9+t9Uy5rBlebt26NY8//jh//etf6dWrV1Z4GareQ/369WO//far076S9KWIaA5cm2PpU+B/yjzOWiKiL9A3z3Ldf3CWzxVA+zWerwDOq+W983PUdqzNjVH1A65TRnlDPsY/+2MwoBXws3IP0hAMMEuSJEmSJEmSJEmSJJXRtttuy8SJE9l991wHSxbvrbfeyhkWPuyww2jfvn2OO6rkO505Vxi6EFOmTOGGG27IuTZs2DAeeeQRttpqq4L79u3bl/Hjx3PqqafWab6ajBo1iv79+7NgQXamatiwYYwePTpngLgm11xzDTNmzMiqH3300YwfP76gr8WAAQN46qmnaNZs7U+dX7p0KddemyvzV7gWLVowduxYBgwYUJJ+klSA3wB75Kj/qiFPpY2IzYBb8yxPTSlNz7P2tRIRewJnZZR/k1Kq1W/ApJTmAx9mlHtERG3yqF2pCuiuaUpt9m2k/gK8n6N+QUQcWOZZys4AsyRJkiRJkiRJkiRJUhndeuutbL/99iXvmy9wPGTIkBrv69q1Kz169MiqjxkzJmeAt7YuvvhiKisrs+oHH3wwt912G02a1C220rJlyzrdn8/NN9/M0UcfzfLly7PWhg8fzv/+7//StGnTgnouWLCA6667Lqu+1157cdddd+U82Xhd9t9/fy6//PKs+t13383ChQsL7pfpoosuonfv3nXuI0mFiIiLgHNzLL0GZP9FWnOvHSOiJH+RRcQmwChg5zyXlOa3R8rjJmDNHzzvAdcU2CPzN6Y6ALX5Wh9bi14bjJTSSuDCHEtNgYciIvsfaEWKiIMjYt9S9SsFA8ySJEmSJEmSJEmSJEllMmDAAA4//PCS962srOSuu+7Kqm+yySYMHDhwnffnOoV55cqV3HPPPUXN8+677zJmzJic89xxxx1UfYL810tKiV/84hf85Cc/yQpeN23alD/96U9ceumlRfW+/fbbWbp0aVb9xhtvrFMQ+/zzz6djx45r1T777LM6n5697bbb8vOf/7xOPSRteCLi+Ij4dURsV8S934iIu4ErcyyvAE5MKa0osO22wHMR8WxEHBoRhf+2SNVsewOTyR/QfR64v5je5RYRJwO9Msrnp5Syf2unZo/kqF28jr03Bc7JKK8CRhe4d6OSUrobyP5HE2wO/CMizq7De3fjiPhhREwB/gbsWodRS84AsyRJkiRJkiRJkiRJUpmcfvrp9dJ33LhxfPDBB1n1Y489lo022mid959wwgk5TxUuNgh79913k1LKqp9xxhlss802RfWsTytXruSkk07i2muzD9Bs3bo1jz76KKeeemrR/UeOHJlV69evH716ZWbICtOiRQuGDRuWVR8/fnyd+v7whz+kefPmdeohaYO0KfCfwLsR8Ux18HLnqOG3ViJit4i4GngXODHHJQkYklKaWoe5DgSeBD6KiFsi4siIqPGHUUS0iYgjImIM8BKwY55LFwInp1w/9L5mImJj4NcZ5b+llHKFkdflL8C8jFr/iPjvPHs3A+4GNstYGpVSml3E/o3NUGBmjnoLqk7MnhkRP42IfCeAAxARzSOie0ScHhGPU/U9GgHsWeJ5S6Kwz7OQJEmSJEmSJEmSJElSUdq0acMRRxxRL73zBY2HDBlSq/s7dOjAoYcemnVq8iuvvML06dP55je/WdA8uU5fjgjOPPPMgvqUw5IlSxg8eHDO0G/Hjh15/PHH6dmzZ9H9Z82axRtvvJFVP+6444ruuaa+ffty1VVXrVV78cUXSSkVfdJ1qWaTtMGqAPpVPwCWRMRrwHxgMdAc6ADsBnTM2aFKJfCjlNJfSjRXe+DM6gcRMR94p3qmRcBqqgK2HYE9WHe+cgnw3ZTSv0o0X30bDmyxxvOVwLnFNEoprYyIXwK3ZixdHRF7AjcA04FmwP7ApcDeGdeuAC4pZv/GJqU0PyIOA54BdshxSSeqvqY3RMQc4G2qwvOfAm2o+uWBzYEuVP35Wi8YYJYkSZIkSZIkSZIkSSqD7t2706xZs5L3Xbx4MaNGjcqqd+rUqaATfocMGZIzeDxixAh+97vf1brPihUrePnll7Pqe+21FzvumO8Ay4Yxe/ZsjjjiCKZNm5a1tvPOO/Pkk0/SuXPnOu0xYcKEnPVDDjmkTn2/1KNHj6zaggULmDlzJl26dCm4X+vWrenatWspRpOkL20M7FfgPZ8Cp6SUHq6Heb7UrvpRjOnAD1JKr5ZwnnoTEbsD52SUr08pzSi2Z0rptogYBByesXRc9WNdfp5Syv4Nnw1USundiNgfeBjYt4ZLt2DtIPp6q0lDDyBJkiRJkiRJkiRJkrQh2Guvveql7/3338/y5cuz6ieddFJBJ/AeeeSRbLLJJln1e+65h1WrVtW6z/Tp03Nev88++9S6Rzm8+uqr7LfffjnDy/vuuy8vvPBCncPLUHWKdaZWrVqx/fbb17k3wKabbkrTptlnGL7//vtF9evWrRtNmhgpktSgngW613N4uVhfAL8H9l5fwsvVbmLtA29nA1eUoO+xwLgi7rs0pXRjCfZvVFJKHwK9gYuBz0rc/iUg+x89DcgTmCVJkiRJkiRJkiRJksqgY8eO9dJ3xIgROesnnXRSQX022mgjjj32WG6//fa16nPnzmXs2LEMHDiwVn1mzZqVs96zZ8+C5qlPEyZMYPDgwSxatChr7cgjj+T++++nZcuWJdlr5syZWbWKigpOOeWUkvQHcgaOP/nkk6J61df7VNIG4R/AvcBhwGYF3puoCi5fl1LK/jiA4kwH/gs4EOhF1UnQxZoH3Ab8T3XIdL0REcdT9TVY089SSsvq2jultCwivgtcBPwMWNcPzw+A/0gpPVjXvRurlNIq4MqIuAM4FzgF6FBMK2AqMBb4c0rpzdJNWRoGmCVJkiRJkiRJkiRJksog1+nGdTVjxgxefPHFrPq3v/1tunTpUnC/IUOGZAWYoSokXdsA84cf5s51fV2CsatXr+awww7j888/z1o766yzuOmmm6ioqCjZfrNnz86qffrpp4wcObJke+RSbIC5Pt6nKspc4Ovxh0b1YW5DD1AfUkrTgRMjogLYE9gP+BawE7ADsCnQGlgFfAr8G3gT+DvwZErpXyWeZwHwG+A31TPtAnQHugGdgW2BrYG2QCugCbAI+KT6vzOBSdWPqdXB0vVKRLQGfptRnpBSur9Ue6SUPgcuiYhbge8DA6j6nneg6ns9l6og7aPAQymlUp8sXLSU0lBgaB171P7jLgrr+yHwi4i4iKoA/oFAD6reu1tR9WepAlgKLAEWAm9R9WdqOvBsSml+fcxWKgaYJUmSJEmSJEmSJEmSyqBNmzYl75nv9OUhQ4YU1a9Xr1506tQp6xTlxx9/nAULFrD55puvs8fSpUtz1jfddNOiZqoPucLL3bt35+abb855mnFdLF68uKT9amvJkiVF3Vcf71MV7owzztiioWeQipVSWg28XP34Wqie6fXqx70NPE7ZVJ+yvE2Z9poNXF/9UIlUv3cnVj8aldL+i0uSJEmSJEmSJEmSJEllUVlZyV133ZVVb9asGccdd1xRPSOCk046Kau+cuVK7r23dnmvlStX5qy3bdu2qJnqQ0T2YYlTpkzhlFNOYfXq1SXda8WKFSXtV1sppQbZV5IkqTY8gVmSJEmSJEmSJEmSJGk99PTTTzN79uysetu2bfmP//iPovvOmTMnZ33EiBGcc84567y/efPmOev5TmYut4qKCv74xz9y5plnZoV8//znP/P5559z991307RpaWI1FRUVJekjSZLUmBhgliRJkiRJkiRJkiRJWg+NGDEiZ33hwoWMHDmy5Pu9/PLLTJ8+nW9+85s1XtemTZuc9UWLFpV8pmKdfvrptGjRglNPPTXrxOUHHniAzz//nAceeCBvGLsQrVu3zqp17tyZd955p869JUmS1ldNGnoASZIkSZIkSZIkSZIkFWbx4sWMGjWq7PvmC02vacstt8xZnzt3bomnqZshQ4Zw77335jxpedSoUQwePJgVK1bUeZ8tttgiq7Zw4cI695UkSVqfGWCWJEmSJEmSJEmSJElaz9x///0lCdcW6p577mHVqlU1XtO5c+ec9cmTJ9fHSHXy/e9/n4ceeijnSctPPPEEAwcO5LPPPqvTHp06dcqqLV68mJUrV9apryRJ0vrMALMkSZIkSZIkSZIkSdJ6pjYnIdeHuXPnMnbs2Bqv2WOPPaioqMiq//Of/6yvserkqKOOYvTo0Wy00UZZa+PGjePwww9n6dKlRffv3r17Vi2lxEsvvVR0T0mSpPWdAWZJkiRJkiRJkiRJkrRBynXqLrDOE4Yb2owZM3jxxRez6r169SKlVLLH9OnTc+4/cuTIGudr2bIlPXv2zKq/8sorzJo1q7gXXc8OO+wwxowZQ+vWrbPWnnvuOQ4++GAWL15cVO/evXvnrE+YMKGofpIkSY2BAWZJkiRJkiRJkiRJkrRBatu2bc768uXLyzxJYe68886c9RNOOKGk++yxxx7sscceWfXHHnuMhQsX1njvgAEDsmqVlZXcdtttJZuv1Pr168dTTz3FxhtvnLX24osv0r9//3W+7lx69uzJVlttlVUfMWIEq1evLmpWSZKk9Z0BZkmSJEmSJEmSJEmStEHKF2CePXt2mSepvdWrV3PXXXdl1Zs2bcqxxx5b8v1yhaJXrlzJvffeW+N9J510EhGRVb/lllv48MMPSzZfqe2///48/fTTfOMb38hamzx5Mn379mXevHkF9YwIhgwZklV/55131vl1lCRJaqwMMEuSJEmSJEmSJEmSpA3SDjvskLP+6quvlneQAjz99NM5A8D9+vWjffv2Jd/v+OOPz1kfMWJEjfd16tSJgQMHZtUXLVrEaaedVorR6s0+++zD+PHjadeuXdbatGnTOOCAA/joo48K6nn22WfTokWLrPp5553Hu+++W/SskiRJ6ysDzJIkSZIkSZIkSZIkaYO0ww47sOmmm2bV77///gaYpnbyBYdznZRcCp07d2afffbJqk+ePHmdQe8rrriCJk2yoylPPvkkP/rRj6isrKzTbMuXL6/T/TXp3r07EyZMYIsttshae+ONN+jTpw/vv/9+rftts802nHfeeVn1hQsXMnDgwIJ61WTVqlXcd999/Otf/ypJP0mSpPpigFmSJEmSJEmSJEmSJG2w9t9//6zaww8/zGWXXcann37aABPlt2jRIkaPHp1Vb9GiBYMHD663ffOFo9d1CnO3bt04//zzc67dcsstHHPMMQWfZAzw/PPPc8ghh3DHHXcUfG8hdt99dyZOnMg222yTtfb222/Tp08fZs2aVet+l156KbvuumtW/fXXX2evvfbK+b2trTlz5nD99dez00478YMf/ID58+cX3UuSJKkcDDBLkiRJkiRJkiRJkqQN1tChQ3PWhw8fTocOHfj2t7/NMcccww9/+EOGDh2a9ShnUPT+++9nxYoVWfXDDz+cTTb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VSvsRmXn9MAP2tg79VaXroRHRVOS3nIjYFHhwpevvwM+GjCuBwypdq1F+D5I0rA0a2i8Zcdym45vOtyzzu/ldUneYk9vn5Jl4htx0rM+QJXVC72WLpvnszVsM1cn58ohYhfoLPTdR36lxUOZ3SZIEDL8Cc81RwwaRmdcCP690bRsRdxt2XElaIC5taG+zMsJM5PYEjq50rU25CR/E2OOa5vim80nSWETEI4EX9jX/EvjMDJ7WHD/1+SRpShGxEfDESte3Z/Dlk+lMMocG9dWna5o+98MRXpoBc7ukmXFtB89nfi/M75K6wJxcDJSTI2Iz4N6VrrMy86yho4LjgRuHjUuSJqSTz2qnOX7QPPpQYK1K+4mZuXi4kADvBSRJUk+rAubeW71bVrrOzszaCmxtHN/QvuuI40rSfLdKQ/tAW7JFxCLgIZWum4DfDBtUz/EN7YPm9kc0tNe2FWrj+IZ2rzmSZkxvy+hP9zXfCrxsxAdMU53THH8Hc7ykYT0NWFRp/9akA1lGV3PoTMX1K+o7d5nbJY3i7w3tm4w4bu34q3urn03H/F6Y3yV1gTm5mNW4MnMJ5eX/fveKiFGv2ZI0LiM9q+1ZUNedzPwbcE6l62ERMcxCjJIkaY5qe+HfqaH95FEDmWKMpnNKkoqtG9oHXQ1uG2D1SvupmXnLcCH906i5vfa524FThgun6N0UX17p2nGUcSVpGgewYs4+JDNPncFzmuPvYI6XNKzalskJ/HjSgQBExNrAvSpdl2VmUzHeoE6h5OJ+o+R2GHHeqHfNql0vt46INUcZW9KC9ouG9qYH9NOKiC0o2zH3q+0+2H+s+f0O5ndJs8qcvJxBc7LPkCUtZLVrBgz+rBa6O18+6fy+BnCfMYwtSZLmiLYFzNs3tP9p1ECmGKPpnJKkYveG9kFz80zm9r9QVhcd9Jz/1Fs9YcNK1wWZef2ogVH/+TaOiLuMYWxJWk5E7AC8oa/5fODAGT61Of4O5nhJrfVWfKmtSHNWZl456Xh6tqNsMd1v5NzeWx30b5Wu+013bEREw+duAf46YmhQ//lWovw+JGkY36BeQLbvCGO+sKH96wMca36/g/ld0mwzJ99h0JzsM2RJC1JE7ASsW+m6HrhgwDG6PF9ufpckSTOqbQHzVg3tZ40aCOVmvbYKXNM5JUnF8xrafzrg8TOW2zPzVuo351v2JlunMpPXHICzW55XkobSK347FFi5r+uVmXnDDJ/eHD/YeSWpydbA+pX2M/obImL9iHhxRBweEWdGxOKIWBIRF0fEqRFxVES8OSJ2HCBPTmU2cugaA2zPfFdgtUr7+b1rxqjM7ZLGKjPPBr5T6XpkRDyr7XgRsS3wukrXBcBhAwxhfl+e+V3SbDInL2+QnDyTvzOvFZK6rOk57YmZWXthsqaT8+W9+astKl1LqL+M05b5XZIktS5g3qKh/cIR4yAzbwMurXRtPurYkjRfRcRjad6655sDDrNFQ/vIub3nokrbasDG0xy3RUP7TMY11XklaVivAnbua/tWZn5/AufeoqHdHC9Jg2laaeycpf8REWtHxAcpD24+C+wD3BtYC1gF2ISycszjgPdRtv48PSKeNmRMWzS0z3YObeqf7bgkaSqvAq6utH8+Ip486CARsT3wQ2DNvq4EXpyZSwYYZouG9tnOo039sx2XJM2kLRraZzv3NfXPaly9ArfNKl23A5eMGBN4rZDUURGxIfCihu5vtBhqi4b22b7u3BVYtdJ+cYvi7KmY3yVJUusC5qYtJGqFx8O4uNK2WkSsM6bxJWneiIhVgA81dB+TmYNuGTcbuX2q807XP9txSdLAImJz4OC+5sWUQolJ6Gou7WpcktRv64b2ywEi4oHAH4E3sGLR2lS2Bb4REb+IiE1bxtTVHNrVuCSpUWZeCOwN3NjXtRrwnYj4SkQ8qOn4iNgyIj4A/IZ64darM/NHA4bT1Tza1bgkaSZ1Nfd1Na51qRe4/aO3gNWovFZI6qp3AbValisZbBeWpbqa37salyRJmkf6t7Gezp0b2murVAzjminOe+2YziFJ88VbKSu59UvgwBbjzGZun0pX45KkNj7FigVt7+gVSkxCV3NpV+OSpH5NxcVXRcSuwFG0K1zu91Dg1xGxV2b+fsBjuppDuxqXJE0pM0+IiEcDX2PF3QCfAzwnIq4Afg9cAdwGrE95GaVp98DFwMsz8ystQulqHu1qXJI0k7qa+xZkXJl5Q0TcyorPtb1WSJo1EbE78NKG7g9k5nUthluQ+R3vBSRJEu0LmJtWQl48aiDTjLPumMaXpHkhIh4BvKOh+8uZ+csWw3U1t3c1LkkaSEQ8B3h8X/PvgE9MMIyu5tKuxiVJ/TZuaL8H8B7qxctXA6dStkq+E2W7zZ16/11zd+AnEbFTZp4/QExdzaFdjUuSppWZv4yI+wOvp+yW0p9b7gw8eoChlgBfAt6VmRe0DKOrebSrcUnSTOpq7luocS0da/2+Nq8VkmZFRGwIfBmISvdfgf9oOeRCze/eC0iSJFZq+fna9j9QJmbH4eaW55WkBSciNqFsO1R7CeVi4LUth+xqbu9qXJI0rYi4MytOUt4OvHRMW2cOqqu5tKtxSVK/tRra38CKD1NOAh4HbJSZu2XmMzPzKZn5EGAj4EXARQ3jrQ98PSJWGSCmrubQrsYlSQPJzGsyc3/KiyUfpXx/b+NHwLaZ+ZIhipehu3m0q3FJ0kzqau5bqHFBPTavFZImLiIWAV+l3Df0ux3YLzOb8mmThZrfvReQJEmtC5ibHqTdOmog04wzyAM8SZr3ImI14DvA3SrdtwP7ZuaVLYftam7valySNIgPU4rVlvXJzDxpwnF0NZd2NS5J6tf0wKT/ZcL3Artk5tGZuUIOysxrM/NzwDbAsQ1jPhh44wAxdTWHdjUuSRpIRNw5Ig4GzgdeTfu58z2AMyPiGxGx4xAhdDWPdjUuSZpJXc19CzWuprG8VkiaDR+mfPeveW9m/nyIMRdqfvdeQJIktZ6EbZIzPE5t6w1JWlAiYiXKNqS7NHzk4Mw8Zoyn7Gpu72pckgRARDwGeEFf88XA22chnCZdzaVdjUvSwrVogM98KDPflpnTrtSZmYuBJwJND7NeExGrtwlw2eGHPG7QccztkuatiHgWcBblO/sGIwy1MvA04HcRcUhEjGPlsK7m0a7GJUkzqau5b77H1TSW1wpJExURr6S87FhzHHDAmE853/O79wKSJKl1AfMtDe39Kw8Nq+lNqnFuMSRJc9VHgac39H0FOHDIcbua27salyQ16hWd/Vel69WZee2k46G7ubSrcUlSv6Z8tdSpwNvaDNjbRvQFwA2V7o2AfYeMabZzaFfjkqQpRcS7ga8B61W6rwE+DuwNbAGsQ1mdf1Pg4cBbgD/WhgVeA/woItYcMJSu5tGuxiVJM6mruW+hxgX12LxWSJqYiHg65VltzenA0zLztiGHX6j53XsBSZLUuoC56YvCOFaSALhTQ/vNYxpfkuakiDgQeGVD95HAvpk57NuuXc3tXY1LkqZyIHDPvrajMvPwWYgFuptLuxqXJPWbLm8cmJnTFTmvIDPPBj7X0L33NId3NYd2NS5JahQRb6L5RZSPA5tl5qsy87uZeX5mLs7MJZl5cWb+IjPfD+wAPAO4qjLGrsC3I2KQFcS6mke7GpckzaSu5r6FGhfUY/NaIWkiIuKxwP9Qr685F3hsZtbuBwa1UPO79wKSJKl1AfM1De1rjRpIz9otzytJ815EvIbmLYdOAPbJzFtHOEVXc3tX45KkqojYEXhdX/ONwP+dhXCW6mou7WpcktRv8RR9FwPfG2Hs2or9AA+LiEVTHNfVHNrVuCSpKiJ2Ag5u6H5pr3B52l1UsjgceBBwSeUje9C8zfSyuppHuxqXJM2krua+hRoX1GPzWiFpxkXEw4BvUy+2vRh4TGZeNOJpFmp+915AkiS1LmC+sqG9tr3eMJrGaTqvJM1rEfFC4CMN3b8B9srMm0Y8TVdze1fjkqQV9ArNDmXFrdPemZnnzkJIS3U1l3Y1Lknqd8UUfSeM8iJhZp4OXFrpWgvYcYpDu5pDuxqXJDX5APUtiz+WmZ9pO1hmnkNZRf/2SvdBEdH0cH6prubRrsYlSTOpq7lvQcYVEWtQv2Z7rZA0o3ovPf4AWKPS/Q9K8fI5YzjVgszvU4xjfpckaQFpW8Bce7AGsPGogfRsUmm7GZh2pQtJmm8i4lnAZ4HaNqOnAY/LzKlWhBvUbOR2gMumOa6rcUlSzWuAB/a1nQ58eBZiWVZXc2lX45KkflPljd+OYfymMTab4piu5tCuxiVJK4iI+wKPqXRdAxw47LiZ+Wvga5WudYAXTHN4V/NoV+OSpJnU1dzX1biuBpZU2jeMiLbPomu8VkiauIjYFjgGWLfSfS3lOe2fxnS6rub3rsYlSZLmkbY3jec3tN991EB6q9bVvqCcl5k56viSNJdExJOAL1PP038B9sjMq8Z0uhnL7T13q7TdRH1b1WXNRlwAs7lSqqQ5KCLWB97Z15zAyzLzllkIaVnm+OWZ4yW1dd4UfaNuDzrVGBtMcUxXc2hX45Kkmj0b2g8fw3zLpxvanzDNcV3No12NS5JmUldzXyfj6j3HvaDStQi466hB4bVC0oRFxD2BY4ENK93XA0/IzJPHeMpO5nfgYuovqNx1TC+omN8lSdIKW1xPp2n7i3uNGghwD+rb//jlRNKCEhF7AF+nnqPPAx6dmU1vvA5jxnJ7RKxMffW4QV5OmclrDsA9G9q97khqa11W3ELuKuDFEfHiIcZrynN7R8QWlfYzMvN9DceY45dnjpfU1tlT9F09hvGbiuTuPMUxs5FDb6R51Z2lLqK8xLJaX/vmEbEoM2+bgbjA3C5pOA9raP/xGMb+FaWoYc2+9odOc5z5fXnmd0mzyZy8vEFy8jnUfz/3Ai4cOqLCa4WkiYmIe1DuCzatdN8MPDkzfz7m03ZyvjwzMyLOA+7d17Uqpb6nqfB6RuOSJEnzS9sC5tMa2u87aiBTjNF0TkmadyJiV+A7lBu/fhdRipf/PubTzmRuvzf1a820uT0zL46IK1ixeGOziFgzM68fMbbaz3fZmIvDJS1cGzD9FtFt3b/3p98JQFMBszn+DuZ4ScM4nbKqfsx2IMtoimnk3B4Ra1EeQPX743Qvp/Qeap0OPLCvaxXKNePPI4ZX+/lup/w+JKmtppXMRn5Qnpm3RMTfgfv0da0XEatn5o0Nh5rf72B+lzTbzMl3GDQnnwY8tmHME0YJCp8hS5qQiNiEUry8eaX7FuDpmTmOlx6X0/H58tNYsYB56ZijFjCb3yVJEm23dTilof0BowbCijfb051TkuaViHgwcCQrruIJcBmleLnpDdxRnEFZtaHfDr3VNUcxam6vfW4lYMfhwil6b09vVOn6/SjjSlIHmePvYI6X1FpmXgv8paF7vTGcYv2G9n80HdCLqbYy9F0iomnrzUHtRH2uaJTcDiPOG0XEKsD2la6zMvO6UcaWtGCt29B+5ZjGv6KhvSnvm9+XZ36XNKvMycsZNCf7DFnSnBYRdwaOBbaudN8GPDczvzeDIXR1vnzS+f1G4MwxjC1JkuaIVgXMmXkhcF6l614RUdtCo43dGtp/NuK4ktR5EbED8ENg7Ur3VcAemXnGTJw7M2+lbG/abzXgwSMOP2puP7HluIPymiNpQTDHL8ccL2lYTflq1HmQqcZoLGDu6WoOnam4dmHFbbLB3C5peE0rmK05pvHXamhfPM1x5vfC/C6pC8zJxazGFRF3Ah5S6To7My8eZWxJWioi1gWOAbardCfwwsw8fIbDWFDXnYi4O7BVpesXmXnbKGNLkqS5pe0KzAA/amh/wrBBRMQ6wCMqXWdk5t+HHVeS5oKIuA8lt9ZW4bkW+NfMPHWGw5iJ3B7A4ypdi6kX09WMPa5pjm86nyTNZeb4qc8nSdM5uqF91BdBphpjup1XJp1Djx3w+KbPPa537RiWuV3SuDW9KLLxmMbfpNJ2c2ZOV8Bsfi/M75K6wJxcDJSTM/N84K+Vrq0j4l5DRwW7U9+10muFpLGIiDWBH9C8ovArMvNLEwilq/Plv6T+AuiuEdH04uYgvBeQJEnAcAXM321of/YIcTwVWLXS/p0RxpSkzouILSgTjnepdF8P7JmZv51AKE25/VkjTHruBtS20zuytyLoIH4NXFJpf1hEbD5MUL2b6b0qXRcCk/hdS5pnMvO8zIxx/QH2azjVQQ3H7D5NiOZ4c7yk0fwQuKHSvltErDzsoBFxP+r3AZcBp09z+FHAkkr7k3oP3oaJZ0vqK5v9KjNr+XoFvZ27Tqp03YP6i+uDxBXAsypdN1H+biRpGJc2tA+Vq5YVEfemOb9Px/xufpfUHebk9jl5Jp4hP6eh3WfIkkYWEatRctfDGj7yusz8rwmF08n58sxcQrkm9lsNeMowcfWY3yVJEjBcAfPRwOWV9kf1Hr4N4/81tH9lyPEkqfMiYlPgx8DdK903AU/OzKZtecYqM08Hfl/puiew55DDjpzbe1sEHVbpiinGn85+1LdyPSwzbx9yTEnqLHM8YI6XNILeapnfrnRtAjxphKFf1tB+fGbmNDFdRVkdqN/aNL8IM51XUnJwv7ZzM//T0P7qluMs9URgy0r7kZl5zZBjStIvGtqfMuLqlQD7tDznP5nfAfO7pI4wJwPtc3JTXC+LiDu1DSoiNgKeWem6lMFXrJakqohYBTgceHTDR/49Mw+ZVDwdny8gPJAgAAAgAElEQVRvyu+vah8SRMT2lEVS+p2cmWcOM6YkSZq7Whcw91ZU+0xD9/vajhcRT6e+HcfxmfnHtuNJ0lwQERtSJti2qnQvAZ6WmT+ebFT8Z0P7uyNiUZuBIuLB1N+6PZv6pO9UPgXUbqJfERGbtYxrbeBtla7bgE+2jEuS5hJzvCSN5mMN7QcO+SD+njQXPXxtwGGacvvbezmxTTybAS+vdF0LtN0m9YvAdZX2p/auIW3iWgQc3ND98ZZxSdKyjmlo347mAuRpRcS6wOtbnrOf+V2SusOc3EJm/gH4eaVrU4YrcjuQssJnv0/1Cv0kaSgRsRLwZcoLHDXvzsx3TzCkpbo6X/594PxK+4MiYpj7p6a6Iu8FJElagIZZgRnKF4frK+17RsQLBx0kIjYBPtHQ3boYWpLmgt7DrKOBbSvdtwLPzsy2BWDj8GXKlkH9dgAOGHSQ3vZ5X6C+ksQH266AmZl/Ab5V6Vod+ELLwrtPUFbK63d4Zp7TJi5JmmPM8ZI0gsz8DfXCs+2BVg+0ImJVSsHBGpXu02jedrk/pmOpbx091VxLLZ5FlNy+eqX7k5l57aBj9eK6GqhtrxqU3N5mu+39Kdeqfr/KzBPaxCVJy8rMs4BTG7o/1XvRpJVePj0M2KDSfRNw5ICxmd8lqSPMyUPl5Pc2tB8UEdsNOkhEPIb6rjWLaS4sl6RBfZr6Cu8Ah2Tmv08ymKW6Ol/ee2nkg03niYi7DjpWROwHPKHSdQHw1TZxSZKk+WGoAubMvJTmG9BPRURtRbbl9L7EHAPcpdJ9VGYePUxsktRlEbEG5S3V2srztwMvyMzajemMy8ybgTc3dL8jIl453RgRsQ5wBPXi7NOAQ4cM7y3AzZX2RwJfmm7Vuyg+ADy/0n1jb3xJmrfM8ZI0Fq8Bbqm0vyEi3h0RtZc7lhMRawHfAx7e8JEDMzNbxPTahvbnR8T7p4upl2O/RMm5/aaa+5nOu4F/VNq3BY7oXVOm1Ls27V/pSsrfhSSN6h0N7XcGjouIXQYdKCLWp7yA8riGj3yiN6c+KPO7JHWHObmFzDySsvtkvzWAH0bENgPE9XDgG9SfYx+cmbWfW5IGEhEfBl7c0P2pzHzdJOOp6Op8+aeBP1faNwaOHqSIuVdHVHsBB+CNmVmbd5MkSfNctHsutsyBZcWgXwE7VrqT8gXmPZn5t77jVgOeS7mx3rhy7DXATpl57lCBSVKHRcQhNE/8XQAcN+ZTvqHtZF5EHEn9zVeAw4H9M/OMvmNWBp4MvB+orVJ0C7BrZv66TSx953hTb/yaU4A3Aj/pL/jobZn3PuoTxACvy8xDho1LksYtIvYFPl/pOigzDxxxbHO8JI0gIt5M845RvwX+nZKvbu07bm1gH8rWzJs2HH9oZr5kiJg+SX0raoCfAG/JzN/2HRPAo4EPADs1HPu0UV6ujIhnAP/b0H028Cbgu/1bP0fEtsA7Kb+vmo9l5quHjUuSlhURxwO7NXTfAnyFshvhKbUXTHoP6V9AmeupzXUDXA5sk5lXtozN/C5pwYmIvYG9B/joPkBtleEvDnDsGZnZahdYc3LruO5Jmc9Zu9K9GDgI+ExmLu47biPKNfWNwCqVY08CHp6ZS4aNTdLs6Ep+j4gnA99p6L4J+Dql1mVcDs3ME9se1NX58oh4GHACsHKl+1LgbcBXM/OmvuM2A94KvJT67o5HZOaTh41LkiTNbUMXMANExNbALymrUtTcTtmK76+UCd+7Ag+ifsO69PNPy8ymL42SNKdFxBcoD7YmZcvMPK/NARGxIfBrYKspPnYG8CfKm7obAQ+k+VoA8KrM/HibOCpxBfBtShFdk4uB3wFXAetQtr7bYorPfzMzmyZpJWlWzHABszlekkbQy1f/Czx9io9dBfyB8uDmTpS5kAf0/rvJbykvg9RW2JkuptUoD48ePMXHzqXMzywGNqAUUEy1Ms5HMvP1bWOpxPZR4FVTfOQKShHCPygrsm0LTLUi2y+B3S1YkDQuvUKpX1J/UW9ZV1Ly6BXAEkou3QrYeprjbgAeNczLfuZ3SQtRRBwIHDDDpzkhM3dvc4A5eai49qHcOzXtBnwjcDLwN2ARsCXld1YrioPyQtBDMvOcUeKSNDu6kt+nmHufKftl5hfaHtTl+fKIeC3wkSk+spgyz3UJZS5s615sTTsWnAXs0vaFT0mSNH+MVMAMEBEPBI6h3IyP4jbgJZk5yS+MkjRRc6GAGSAitqSsBr35GGI4IDPfOYZxlk4Ufxd47BiGOwp4yjBFIpI0k2aygLk3vjlekkYQEasAhwFPHdOQvwaeMMqDmojYAPgx9V2y2vpvyvzMyCsO9R64fQ7Yd9SxKA/lHp2ZV49hLEn6p4i4F3A0U7/kN4zFwLMy8wfDDmB+l7TQdKXArcac3F5EvJiyY29TEfOgrgD2yMxTRo9K0mzoSn6fKwXM0O358og4CNh/DEOdS3lp5oIxjCVJkuaoUW8YycyTgV0oqwsN63LKwzqLlyWpAzLzXMpqEseNMMx1wPPHVdgG0NtyaE/gYwy/hVMChwBPsrBN0kJkjpek0WTmLZQtTfen7DY1rNuBjwO7jbrKTO/4R9C8ffQgbgHenJkvHkchRS+uzMz9KNuEjvK7+hplhWqL2ySNXWaeBdyfUvw1Lj8H7j9K8TKY3yWpS8zJ7WXmocATKas/D+sU4MEWL0taaLo8X56ZBwD7AdePMMyPKfnd4mVJkha4kQuY4Z+TvA8CXgNc2OLQ64GPAvfJzGPGEYskaTwy8zLg0ZQVo//a4tAlwBeBbTPzyzMQ162Z+Wrg4cDxLQ8/DnhYZr4uM28dd2ySNFeY4yVpNL0igXdRtsD8BmVXqUHdTllBZ+fMfNW4HiBl5vWZ+SxKgcDvWsbzHUqh3QfGEUsltvdRVqo7one+QZ0M7JmZz8nMG2YiNkkCyMzrMvNFlBf9vgQMk5sTOBZ4CvAvvRcHxxGb+V2SOsKcPFRcRwH3oRTgtSl0uxB4NeW+6ZxxxyVJc0GX58t7K0tvS7l/avMCzV8oi6M8JjNHecFFkiTNEzGmF3zvGLBspfpY4PHAA4B7AusCiyjb5l0AnAb8CDjC1RUkqft629DtTnnTd2dga2A94E6UVTgvBP4I/AT4bmZeMsHYtgOeTLl53xbYCFgDuIGywv+fKSsffTczT59UXJI0rIjYEdi70nV8Zh4/A+czx0vSiCLibsBewCOB+wJ3A9amFLMtBv5OmQs5kZKzLp5ATLtQCiseAmwDbACsSsmhlwB/Ak4AvjOuIrsB49qScp3bjfK72oSS22+mbA19JvAr4HuZ+ZtJxSVJy4qIDYBdKTsP7kzJ6+v1/iwCrgGupnwnPYWSt07MzPMmEJv5XZI6wpzcOq71KfdNewDbA5tR7ptuo1xbz6YUhh8FHNPb/UaS1NPV+fKI2IRy3XkUsB3l/mktyoIoV1OKlk8CjqQ85xhvkZIkSZrTxl7ALEmSJEmSJEmSJEmSJEmSJElNVprtACRJkiRJkiRJkiRJkiRJkiQtHBYwS5IkSZIkSZIkSZIkSZIkSZoYC5glSZIkSZIkSZIkSZIkSZIkTYwFzJIkSZIkSZIkSZIkSZIkSZImxgJmSZIkSZIkSZIkSZIkSZIkSRNjAbMkSZIkSZIkSZIkSZIkSZKkibGAWZIkSZIkSZIkSZIkSZIkSdLEWMAsSZIkSZIkSZIkSZIkSZIkaWIsYJYkSZIkSZIkSZIkSZIkSZI0MRYwS5IkSZIkSZIkSZIkSZIkSZoYC5glSZIkSZIkSZIkSZIkSZIkTYwFzJIkSZIkSZIkSZIkSZIkSZImxgJmSZIkSZIkSZIkSZIkSZIkSRNjAbMkSZIkSZIkSZIkSZIkSZKkibGAWZIkSZIkSZIkSZIkSZIkSdLEWMAsSZIkSZIkdUhE7B0R2ffnpbMdl+4QET/s+/v5R0RsMNtxSZIkSZIkSZI0V0RmznYMkiRJkiRpRBGxHvCaStd5mfmFCYcjaUgRsTrwJ2CLZZr/AmyXmbfOSlBaQUTsBJwMxDLNn8zM/ztLIUmSJEmSJEmSNKdYwCxJkiRJ0jwQEVsA51a6TsjM3ScajKShRcRBwP59zftk5jdnIx41i4ivAs9epuk24IGZ+YdZCkmSJEmSJEmSpDnDAmZJkiRJkuYBC5hXNMWq1F/IzPMmHI40rYjYDDgTWG2Z5pMyc+dZCklTiIh7Uv6+Fi3TvGBzriRJkiRJkiRJbaw82wFIkiRJkiTNkPWAAyrtxwPnTTQSaTAHsHzxMsB7ZyMQTS8zz46IbwDPXKZ5t4j418w8erbikiRJkiRJkiRpLlhptgOQJEmSJEmSFrqIuDfwgr7mM4HvzEI4Gtz7Km3vmngUkiRJkiRJkiTNMRYwS5IkSZIkSbPvQGBRX9sHM/P2WYhFA8rM3wP9qy3vHBF7z0Y8kiRJkiRJkiTNFRYwS5IkSZIkSbMoIrYCntnXfBXw1VkIR+19stL2lolHIUmSJEmSJEnSHGIBsyRJkiRJkjS7XsOK83T/k5k3zkYwau1I4KK+tl0i4qGzEYwkSZIkSZIkSXOBBcySJEmSJEnSLImIdYH9Kl2fnXQsGk5m3gZ8vtL12knHIkmSJEmSJEnSXGEBsyRJkiRJkjR79gXW6ms7JTNPm4VYNLwvVtqeGhGbTjwSSZIkSZIkSZLmAAuYJUmSJEmSpNnzgkrbNycehUaSmX8F+ovOFwHPmYVwJEmSJEmSJEnqvJVnOwBJkiRJkjQ/RcRqwEOBhwDbAtsAdwXWAdYEFgNX9v78ETgBOCEzzx3yfBsCH1qmqX9V26XeEhH7DjjsoZl54pDxbAs8HngYcG/gbr2YArgOuAA4Hfgp8O3MvGyY8wwrInYEngo8HLgPsEEvtsuBy4BfAkcBx2bmkhmOZTPK7+qhlH8rm1H+nawKXE/5t7L093UK8KNeweicFhHbATtVur41ofOvDDwB2LMXx1bA2sCtwD+APwDHAF/JzKtajLs98HTK//v3BdanLKRwCfA34IfANzPzzLH9MOW8AewO/Avl59kGWI/yb2kV4EbgBsq/8fOAc4HfA78C/pyZOWII3wC272t7HsvnJUmSJEmSJEmSBMTo8/KSJEmSJGm2RcQWlGK8fidk5u4TjGMjSuHiPpTC3VWHGOYY4ODM/FnLc29B/Xcwiv0y8wstYlgJeAbwRuABLc5zG/B14IBRCnMj4jxg877mgzLzwGU+8wDgw5RCz0GcC7w5Mw8fNq6aXrHp3sDrgEcMMcQ5wBeB/87MCyvj7wt8vnLc0zJzbAXCEfER4LWVrntP93cZEe8F3tLXfGZmbjNiTLUJv+X+LUfEfsBBwD0GGPJ64J3AhzPztinOuzPwfuCRA4yZwKGUf1sDF0c3nHdVyr+jl1GK34dxKWXl60Mz85Qh49geOLXSdf/MrLVLkiRJkiRJkrRgrTTbAUiSJEmSpPkhIt4OXAz8J6WAcZjiZYDHAj+NiMMiYo1xxTfTeqvp/gL4Gu2KlwEWAc8GTouIN4w7tqUi4q3Abxi8eBlgS+DrEfHZXoH2OOLYDjiRstLwMMXLUFYLPgg4raH/f4GrK+0vHvJ8K+gVzj6/0nX8gIXoe1XafjJaVFOLiDUj4gjgcwxWvAxlxfT3A99t+n8yIt5GWbV7kOJlKKt9vwT4XUQMGkftvDtTiobfw/DFywAbA68AXv3/27vXMLvqKs/j35VEIEDkLvcxgiAqCqMIPMhFGVFuDcqlcbAFiTBeGdrpblsH7VZ0gB5mbFqEAQIPaS5qK6CAnbZRMDaiAjagyE1Qg4CEiyFAAgkhWfNiH+zi1P9Uztn71KlK1ffzPHkg67/32uvUOcWL8KuVug0y8w6q7c7tDqnbU5IkSZIkSZKkicoAsyRJkiRJ6pdXUQVx++Uo4IaI2KyPPUdFRBwG3ATs1rDVmsAZETGnX2HhF0XE2VQhz7rv0fFUodemcxxNFaLeo2mvluLXKTOfAy4uHL0rIpoEXYd6D7BRoT57VTe2QruvLxzNazjTSM9cG/g+5eB0Nw4CLmttzx7a9yzgf1HvszUTuD4iSl/HEUXEHlSvZ/sazx0tPyzUDhj4FJIkSZIkSZIkjXPTxnoASZIkSZI0KSwCftX65yJgJbAB1QbYHej8Q9ZvAr4eEftm5spBDNqrViD3YkYOby4A7gH+ALxAte11R2DjDtcfCywBPtanGf+Gartsu0eBe1v/nApsBuwCrNFproi4JjOvqDnHh4FzqLbvdrICuJvqa/Y4MB3YkCog3+um3vOA/95WmwLMAj7XY6+SEwq1hUA3X5/9O9RLAdh+uQTYva2WVFusHwKeogpkv5Hqs1DybqrP5Vfgj5uXP1647gHgfqr3cF3g1VTf6yWvptrw3PV27IhYH/gW8PIRLnsUuK81wxJgrdb1m7Rmmd7t83rwA+CIttpuEbFhZi4chedJkiRJkiRJkrRaMsAsSZIkSZJGw9PAd4CrgFsy87edLoyIGcAhVCHI9nAlwD7AycAXRnpgZs5nSDA2ImYCpee+PTPnjdSrWxGxFzCHcnj5KeBc4KLMvLdw7xSq1/sZyhtaPxoR12bmVQ3H3AfYe8jvV1IFrs8CbsvMbJtrBnAc8Hlg/UK/syJibmvDcdci4k+As+kcXr4ZOBP4bmY+2aHH5q3XchRwINXG6o4y866IuAHYq+1oVkSc0iQUHxHbAm8vHF2cmcu6aLF3ofZQZj5ad6ZVOK7tmYuotiZfmpkLhl7Y2rD8X6jej9KW6FMi4hJgZ176fbmCKjR+Tmbe2X5TRLwG+D/AwYWesyLivMy8pcvX83ngFYX601Sf7Usz855ON0fEVKrg9L7AoVTvZafgfi9+VqhNBfYEru5Df0mSJEmSJEmSJoRo+39UkiRJkiRpNTRCWPeHmfm2Ac1wAfAW4HTgisx8vsf7A/gQ8A8MDxI+C2zVKdjaod9MRjHAHBHrAXcBWxSO5wLHZOYfuux1NHARw1/3E8DrM/OxLvvMB145wiULgEO6CYlGxA5U22RLm3jfl5lf7WamVq8tgF9Sbd1utxj4CHBZe5h6FT3Xp9qufGxmbjvCdUcDlxWODsrMud0+r9D3NOBThaPXZ+ZdXdx/N8M3Es/NzIPqzjSk96q+jj8BDs3Mx1fRZ13gOmDXwvEnqTZZv/gaFlB9TW/tYr5zqb7X212UmbO6uH8a8BjDP08PAO/IzPtX1aPQcxOqzdLTM/Ove71/SJ91qELU7Vvlv5CZf1O3ryRJkiRJkiRJE02nv55VkiRJkiSpV1/IzJ0y82u9hpcBsnIu8F+ptgQPtTbwwX4M2UenUg4vXwAc3G14GaAVBj4caA+ebgycVHvCl3oU2KPbDbet7bXHdDg+rsdn/z3l8PIfgH0z89Jewsut+RZl5inAjqu49AqqIHi7E3p53lCtAO0HCkc/7jK8PAPYvnB0R92ZenAzsN+qwssAmbkYOBoofT+fxn+ElxcCe3UTXm45EfhVoX54REzv4v63Uv48zaoTXgbIzMcz83NNwsutPkuA3xSO3tKkryRJkiRJkiRJE40BZkmSJEmS1BeZ+UCf+lwJ/GPhqHbgtN9a251L88wDPtJrGBcgM78DfKlw9N8iYq1e+7W3Bz6QmaWN1CPN9D3g2sLRPhGxZjc9ImJn4MgOMx3ZbaC6k8x8bhXny4A5haODI6K0XbobB1PeTD27y/vfQPnP5e6tOU+3llBtz17S7Q2Z+WvKG6ynDvn3j/QSHM7M5VQB6HYvpwonr8o2hdrDmXl9tzOMsrsLtZ0HPoUkSZIkSZIkSeOYAWZJkiRJkjQenVqobR8Rrxj4JGUfA17WVlsBfDwzX2jQ94vA4rbaxsCfNugJ8M+Z+d2a915SqL2MVW8+ftGJQBTqZ2XmD2rO1KvzGL7dehq9b5J+USm8/hTwjS7vn9mh/lCtabp3Ts0Nxd8c4eymzOz2dQ/1bWB5od5N0HfTQu3BGjOMlocLtc263C4tSZIkSZIkSdKkYIBZkiRJkiSNO62Q5X2Fo10HPUu7iJgCvL9wdEVm3tmkd2Yuorztdt8mfYEzG9zbKWS8yqBpa0tzKXz9PFVYeyBan6frCkfHR0QpXN1RRGwN7F84uiwzn+2yzcwO9VLwtV8SOKfmvT8d4ewrdRq2Puv3FI526uL2UvB5kzpzjJJO7+MrBzqFJEmSJEmSJEnjmAFmSZIkSZI0XpU2xb554FMMtwvlDbD/1Kf+pcDwHg36LQbm1b05Mx8GniwcbdbF7XsD6xbql2fm43Vnqum8Qm0beg+Hz6L8Z2qze+jxnzrUH+lxll7clZnz69yYmU8Cj3Y4rrvZG+CuQm3zLu57rFDbNiL2bDBLP/2+Q73T+y5JkiRJkiRJ0qRjgFmSJEmSJI1XTxRqpeDwoO3Tof69PvX/90Jtu4jYqGa/mzJzRZOBKAdr1+vivk6B0ssbzFLXt4EFhfoJ3TZobd8+rnD0s8y8vYdZOn3tFvfQo1c/aXh/KXB+f2aWvk+b9Hx5F/d1ei3fiIjdGszTL0s61Lv5npEkSZIkSZIkaVIwwCxJkiRJkkZNRKwVEQdHxGcj4psR8fOIeCAiFkbE8ojITr+A9xdarj/o11Dwnwu1hzLzmT717xQI3apmv/k17xuq9Nq6CZru3KF+c4NZasnMF4ALC0fviYiNu2zzTuCVhfr5PY6zdqG2IjOX99inF/Mb3l8KV49Gz1WGfDPzfuAXhaPNgR9HxJURcUBErNFwvrqe7VBfZ6BTSJIkSZIkSZI0jk0b6wEkSZIkSdLEExG7AB8HDgNm9LH1eAgwb1eorRkRc/rUPzrUN6jZ78m6gwyxtFBbq4v7XlWoLcjMhxvOU9ds4NO89If61wCOAb7Uxf2lbc2Lga/1OEcpwPxcjz161fRzsGxAPdfs8t7PAVcW6lOA97R+PRUR1wHzgBuAO/qwjbwbnd7L0vsuSZIkSZIkSdKkZIBZkiRJkiT1TURsAJxGFfQcjb/5afoo9OzVloXaJsCxo/zcugHmJX2dojdbFGqPDnyKlsx8ICK+CxzYdnQ8qwgwR8SmwJ8Ujr6emaVNwr3qFFzvl05bgcdbz65k5rci4mzgYyNcth7VD1Ec1vr9koi4EbgOuDYzbx+l8Ub7vZQkSZIkSZIkabU3Gv8jUZIkSZIkTUIR8QqqLacfYvT+zGE8BAPXG6PnvnyMntvEuoXaooFP8VLnFmqvjYg9V3HfB4CXFeqza8xQCv52s9FaL3Ui8EUgu7x+HeCdwN8Bt0XEnRHx1xHR7+/pTj9oMZY/TCBJkiRJkiRJ0rjiBmZJkiRJktRYRKwN/AB43SoufQF4BHgQeBJY2vr1QuHaPYFt+zhmv4xV0HQ8hLd7tUah9szAp3ipuVSfv63b6icAPxrhvg8Waj/PzJtrzFAKME+NiJdl5vIa/SalzEzgsxHxLeBU4F09tngdcDrwyYj4InBmq2dTnQLMY7axWpIkSZIkSZKk8cYAsyRJkiRJ6oeT6Rxe/hVwIfBD4NZuA5oRMYfxGWBegX+rVbeeB9Zsq5W2Mg9MZq6IiAuAz7cdHRkRJ2XmsA3REfE2YLtCuzrbl6EK75fMABbW7DlpZeatwP4RsS1wDHAA8CZgapctNgS+BOwXEUdkZtOgcafP+FhvH5ckSZIkSZIkadzwf7ZJkiRJkqRGImJT4C8KRy8AJwE7ZOb/zsybetwuO6ZB1xEsKdRuzswY5V9zBv1C+2Bxobb+wKcY7gKGb/2eDryvw/UnFGrPAZfVfP7vOtQ3r9lPQGb+OjP/NjN3pQolH0S1mflHwLIuWhwAXBYRTbedb9Gh/kDDvpIkSZIkSZIkTRgGmCVJkiRJUlOHMHzLLsBfZuaXMzNr9t2wwUyjaUGhNl5nHWuPFGqbDnyKNpn5e+CawtGwoHJEbAgcXrj2m6VtzV3qFGTdsmY/tcnMpzNzbmaenJl7UQXn9wO+Ajw6wq3vBo5s+PjS+5h0Dq5LkiRJkiRJkjTpGGCWJEmSJElNHVSozQe+3LDveA1z/rZQ22TgU6weflOobR4R42HT8HmF2k4R8Za22vspB/TPb/Ds0tcFYKsGPTWCzFyamd/PzBOBrYHjgMc6XP7Jho8r/bdrQWYubdhXkiRJkiRJkqQJwwCzJEmSJElqavtC7aoGm5eJiI2A7eqPNKpuL9TWi4gdBj7J+Ff6WgHsNtApyq6lHCRu38J8fOGauzPzxgbP/iWwslB/TYOe6lJmLs/MOcAewMLCJW+KiCY/lPDaQq3T94IkSZIkSZIkSZOSAWZJkiRJktTUpoXa/IY99waiYY/nO9SnNex7Q4f62xr2nYg6fa0OH+gUBa2AfWmL8nsjYh2AiNgd2LFwzeyGz14C3FM4ekOTvupNZv4aOKNwFNR8L1qfnW0KRz+r00+SJEmSJEmSpInKALMkSZIkSWpqRqH2XMOeH254P8AzHerTG/a9HlhcqH+wYd+J6N8ovw9HtLZsj7WLGB50nwG8t/Xv7duYAZYBF/fh2bcUagaYB+/7Heob1+y3I+Ufvii935IkSZIkSZIkTVoGmCVJkiRJUlOLCrWt6jaLiJ2B/eqP80eLgSzUt2zSNDOXAV8vHO0SEQc06T3RZObzwD8VjtYCTh7wOMNk5mPAtwpHJ0TEDOCowtmVmfmHPjz+3wq1rSKitNFco6f0wwgAy2v2e3OhtgL4Uc1+kiRJkiRJkiRNSAaYJUmSJElSUwsKtXfWaRQRawD/SHmDaU8yM4HfFY52bNobOBNYWaifHxGb9aH/RHIW5SD5SRGx96CHKTi3UNsNOA1Yp3A2u0/P/W6H+j596q/uvLpD/fc1+729ULspM5+s2U+SJEmSJEmSpAnJALMkSZIkSWrqJ4XarhHxrl6aRMRU4ELgjX2ZqnJ7oXZoRKzVpGlm3glcVDjaCrgqIjZp0v9FEbFGRMyKiI370W8sZOYvKH3vm+kAAAglSURBVG9hngJcHhFvatI/IqY3uT8z5wH3FI4+VqjdD8xr8rwhz/098PPC0dv60X8ii4hPtDa198OHC7WlwN01+5UC6P9Ss5ckSZIkSZIkSROWAWZJkiRJktRUp3DeZRHxhm4aRMSGwOXAn/VtqsqPCrWtgK9GxFYNe/8V8FChvitwW0TsW7dxRGwdEZ8G5lOFutet22uc+B9AaQPtJsC8iHhvrw0jYkbra3RH0+GA87u87oLWZu9+uaZQK23w1UsdSvU9dm1EHNLa3N6TqHwROKhwPDczn67Rc0eqz3S7q3vtJUmSJEmSJEnSRDdtrAeQJEmSJEmjaoeImDMKfT+amc+2/v0a4D5gu7ZrNgJuiojTgP+XmU+0N2mFiI8C/iew4ZCjZ4BbKW8z7cWlwGkM/zOQ91BtYr6baqvuM8CKwv0XZGYpBE1mPhkRRwLXA+1bgLcErouIG4GvANdn5mOdhoyIGcDOwB7AYcBbgFjFa1ttZOYjEXEMcBXDf6B+BvC1iDgJOBP418xcVOoTERsBbwXeCxwCrAM81YcR5wCnAiNt5l5Oeet2E5cCn2mr7RARr8nMe/v8rIlov9avRRFxFTAX+Flm/qbTDRGxNrA/1Q8g7F64ZCVwRs153l2o3dHaQi5JkiRJkiRJkoYwwCxJkiRJ0sS2KXDsKPT9c+BZgMxc0dqEe3nhuunAKcDnIuIO4Let+zYCtgZe16H/R4F30DDAnJkLImI28JHC8RTg9a1fncyjvMX5xf4/jYgjqF57e4gZqrDtWwEi4j6qjc0LgWXAesD6wGbANkygwHJJZn4nIk4Ezu5wye7A14EVEXEn8CjwOLAmVbj9VcDMUZrtyYj4BnDMCJddPVIIveZz742Im6m2dg91OFWgWt1Zn+q/c8cCRMSTVD+YsJBq83dSBeVnAtsDI21s/r+Z+dOacxxeqF1Ss5ckSZIkSZIkSROaAWZJkiRJktRYZl4REWdQbTUtmQLs1Pq1Kidn5qUR8Y4+jfcXwC5UW437LjPnRsR+wDeBzUe4dDuGb6meVDLznIh4FjiXKphcMhV44+Cm+qPzGDnAPHuUnnsxwwPMh2GAuYkNqPf9fh7wqToPjIhtqLaoD7UC+GqdfpIkSZIkSZIkTXTtf2WnJEmSJElSXZ8CTqfadlrHUuD4zOxrcDMznwP2BM4AFvez95Bn3EgVur2U+q+/ZDlwNdUW2QkhM+cAewC396nlsn40ycwfA7/ocDwf+F4/nlNwMfB0W+3NETHSZvDJ7vk+93sG+PPM/HBmrqzZoxR+/3ZmPtxgLkmSJEmSJEmSJiwDzJIkSZIkqS8yc2Vmfho4kN7CqSuAK4AdM/PCUZrt+cz8JNWG5GOAc4AbgQeBRcALfXjGE5n5fuDNVEHmpTVbLQN+AHwC2DIzD83Mp5rON55k5q1UW7GPBX5es81dwF8Cr+3XXMBFHeoXNgi2jigznwFKn/sTRuN5E8RBwH7Al4H7GvR5AjgLeE1m/kPdJhExBZhVOPr7uj0lSZIkSZIkSZroIrOfS4EkSZIkSZIqEbEvsD+wF7AVsBEwjWoL8sPA3cAPgasz88HC/RsD67aVl2bmgtGcu18iYh3gncBbgZ2BmcArgOnASqqtr88AC4B7gXuAW4EbWlujJ43WtuEDgd2B7YEtqd77oPoaPU21Bflu4DbgXzPzgVGY43yGB4dXAK8czU26ETETuB+YOqS8kCrAXjcIP2lExCZUW713AV4NbAtsAcwA1qHa2Pw01Q8r/IrqM/RT4PuZubwPzz8Q+Oe28i2ZuWvT3pIkSZIkSZIkTVQGmCVJkiRJkjTptQLnj1CFXoe6JjMPGcDzLwH+rK08KzM7bYXWOBER36HaCj3U4Zl55VjMI0mSJEmSJEnS6mDKWA8gSZIkSZIkjQN/yvDwMsD5A3r+54EX2mp/FRExoOerhojYkWp7+FD/bnhZkiRJkiRJkqSRGWCWJEmSJEmS4EOF2sPAvwzi4Zl5PzCnrfxa4NBBPF+1fQpoD5l/diwGkSRJkiRJkiRpdWKAWZIkSZIkSZNaROwO7FY4ujAzVwxwlFOApW21Tw/w+epBRLwKOKqtfENmDiT0LkmSJEmSJEnS6swAsyRJkiRJkia7vy3UlgPnDnKIzHwQ+Lu28q4R8e5BzqGufQGYNuT3K4GTxmgWSZIkSZIkSZJWKwaYJUmSJEmSNGlFxJHA/oWjr2bmI4OeBzgdmN9WOy0ipo7BLOogInYCjm4rn5eZt43FPJIkSZIkSZIkrW4MMEuSJEmSJGnSiYgpEfE+YE7h+AXg1MFOVMnMpcAn2so7AB8cg3HU2elADPn9QuAzYzSLJEmSJEmSJEmrncjMsZ5BkiRJkiRJGjURcTyw54u/BTYAdgE273DL2Zn58UHMJkmSJEmSJEmSNBkZYJYkSZIkSdKEFhFzgGO7vPx3wBsz86nRm0iSJEmSJEmSJGlymzLWA0iSJEmSJEnjxGLgCMPLkiRJkiRJkiRJo8sAsyRJkiRJkgS/BPbKzFvGehBJkiRJkiRJkqSJbtpYDyBJkiRJkiSNgWeABcAtwOXA1Zm5YmxHkiRJkiRJkiRJmhwiM8d6BkmSJEmSJEmSJEmSJEmSJEmTxJSxHkCSJEmSJEmSJEmSJEmSJEnS5GGAWZIkSZIkSZIkSZIkSZIkSdLAGGCWJEmSJEmSJEmSJEmSJEmSNDAGmCVJkiRJkiRJkiRJkiRJkiQNjAFmSZIkSZIkSZIkSZIkSZIkSQNjgFmSJEmSJEmSJEmSJEmSJEnSwPx/14U1AqdGaG8AAAAASUVORK5CYII=\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(40, 20))\n",
    "plot_barh({\n",
    "  legend: result.lat_data()[5000:5100]\n",
    "  for legend, results in tracking_results.items()\n",
    "  for result in results\n",
    "  if result.vars()['worker_environment']['SNAPSHOTS_DURATION_MS'] == 1000\n",
    "}, ax)\n",
    "fig.savefig('buffering_latencies_barh_1000.png')"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "outputs": [
    {
     "data": {
      "text/plain": "Text(0, 0.5, 'Buffered elements')"
     },
     "metadata": {},
     "output_type": "execute_result",
     "execution_count": 91
    },
    {
     "name": "stderr",
     "text": [
      "/usr/local/lib/python3.7/site-packages/matplotlib/figure.py:2366: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n  warnings.warn(\"This figure includes Axes that are not compatible \"\n"
     ],
     "output_type": "stream"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.legend([\n",
    "  plt.plot(result.vertex_snapshots()['buffered_count']) and legend\n",
    "  for legend, results in tracking_results.items()\n",
    "  for result in results\n",
    "  if result.vars()['worker_environment']['SNAPSHOTS_DURATION_MS'] == 100\n",
    "])\n",
    "plt.xlabel('Vertex')\n",
    "plt.ylabel('Buffered elements')"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "outputs": [
    {
     "data": {
      "text/plain": "Text(0, 0.5, 'Total buffering duration (ns)')"
     },
     "metadata": {},
     "output_type": "execute_result",
     "execution_count": 92
    },
    {
     "name": "stderr",
     "text": [
      "/usr/local/lib/python3.7/site-packages/matplotlib/figure.py:2366: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n  warnings.warn(\"This figure includes Axes that are not compatible \"\n"
     ],
     "output_type": "stream"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.legend([\n",
    "  plt.plot(result.vertex_snapshots()['buffering_duration']) and legend\n",
    "  for legend, results in tracking_results.items()\n",
    "  for result in results\n",
    "  if result.vars()['worker_environment']['SNAPSHOTS_DURATION_MS'] == 100\n",
    "])\n",
    "plt.xlabel('Vertex')\n",
    "plt.ylabel('Total buffering duration (ns)')"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "outputs": [
    {
     "data": {
      "text/plain": "Text(0, 0.5, 'Buffered elements')"
     },
     "metadata": {},
     "output_type": "execute_result",
     "execution_count": 93
    },
    {
     "name": "stderr",
     "text": [
      "/usr/local/lib/python3.7/site-packages/matplotlib/figure.py:2366: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n  warnings.warn(\"This figure includes Axes that are not compatible \"\n"
     ],
     "output_type": "stream"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.legend([\n",
    "  plt.plot(result.vertex_snapshots()['buffered_count']) and legend\n",
    "  for legend, results in tracking_results.items()\n",
    "  for result in results\n",
    "  if result.vars()['worker_environment']['SNAPSHOTS_DURATION_MS'] == 500\n",
    "])\n",
    "plt.xlabel('Vertex')\n",
    "plt.ylabel('Buffered elements')"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "outputs": [
    {
     "data": {
      "text/plain": "Text(0, 0.5, 'Total buffering duration (ns)')"
     },
     "metadata": {},
     "output_type": "execute_result",
     "execution_count": 94
    },
    {
     "name": "stderr",
     "text": [
      "/usr/local/lib/python3.7/site-packages/matplotlib/figure.py:2366: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n  warnings.warn(\"This figure includes Axes that are not compatible \"\n"
     ],
     "output_type": "stream"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.legend([\n",
    "  plt.plot(result.vertex_snapshots()['buffering_duration']) and legend\n",
    "  for legend, results in tracking_results.items()\n",
    "  for result in results\n",
    "  if result.vars()['worker_environment']['SNAPSHOTS_DURATION_MS'] == 500\n",
    "])\n",
    "plt.xlabel('Vertex')\n",
    "plt.ylabel('Total buffering duration (ns)')"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "outputs": [
    {
     "data": {
      "text/plain": "Text(0, 0.5, 'Buffered elements')"
     },
     "metadata": {},
     "output_type": "execute_result",
     "execution_count": 95
    },
    {
     "name": "stderr",
     "text": [
      "/usr/local/lib/python3.7/site-packages/matplotlib/figure.py:2366: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n  warnings.warn(\"This figure includes Axes that are not compatible \"\n"
     ],
     "output_type": "stream"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.legend([\n",
    "  plt.plot(result.vertex_snapshots()['buffered_count']) and legend\n",
    "  for legend, results in tracking_results.items()\n",
    "  for result in results\n",
    "  if result.vars()['worker_environment']['SNAPSHOTS_DURATION_MS'] == 1000\n",
    "])\n",
    "plt.xlabel('Vertex')\n",
    "plt.ylabel('Buffered elements')"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "outputs": [
    {
     "data": {
      "text/plain": "Text(0, 0.5, 'Total buffering duration (ns)')"
     },
     "metadata": {},
     "output_type": "execute_result",
     "execution_count": 96
    },
    {
     "name": "stderr",
     "text": [
      "/usr/local/lib/python3.7/site-packages/matplotlib/figure.py:2366: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n  warnings.warn(\"This figure includes Axes that are not compatible \"\n"
     ],
     "output_type": "stream"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.legend([\n",
    "  plt.plot(result.vertex_snapshots()['buffering_duration']) and legend\n",
    "  for legend, results in tracking_results.items()\n",
    "  for result in results\n",
    "  if result.vars()['worker_environment']['SNAPSHOTS_DURATION_MS'] == 1000\n",
    "])\n",
    "plt.xlabel('Vertex')\n",
    "plt.ylabel('Total buffering duration (ns)')"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "outputs": [],
   "source": [
    "\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n",
     "is_executing": false
    }
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
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