bachelorThesis/machine_time_waste/statuses_total_time.ipynb

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{
"cells": [
{
"cell_type": "markdown",
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"id": "instructional-perfume",
"metadata": {},
"source": [
"# Statuses total time\n",
"Sums the times instances spend in one of each states in the diagram saved as\n",
"\"statuses.drawio\". Unknown times are summed as \"unknown\""
]
},
{
"cell_type": "code",
"execution_count": 1,
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"id": "indirect-galaxy",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import sys\n",
"import pandas\n",
"import seaborn as sns\n",
"import matplotlib as mpl\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "code",
"execution_count": 2,
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"id": "phantom-vaccine",
"metadata": {},
"outputs": [],
"source": [
"# QUEUE = set([\"0-2\", \"1-2\", \"assumptions:\", \"1-1\", \"1-0\"])\n",
"# RESUB = set([\"4-1\", \"4-0\", \"5-1\", \"6-1\", \"7-1\", \"8-1\", \"assumptions:\", \"5-0\", \"6-0\", \"7-0\", \\\n",
"# \"8-0\"])\n",
"# READY = set([\"0-3\", \"2-3\", \"0-9\", \"2-9\", \"9-3\", \"2-7\", \"2-8\", \"9-7\", \"9-8\", \\\n",
"# \"9-9\", \"0-7\", \"0-8\", \"assumptions:\", \"2-0\", \"2-4\", \"9-4\", \"9-1\"])\n",
"# RUN = set([\"3-1\", \"3-10\", \"3-4\", \"3-5\", \"3-6\", \"3-7\", \"3-8\", \"10-5\", \"10-6\", \\\n",
"# \"10-7\", \"10-8\", \"10-4\", \"10-10\", \"10-1\", \"assumptions:\", \"3-0\", \"10-0\", \"3-3\"])\n",
"\n",
"QUEUE = set([\"0-2\", \"1-2\"])\n",
"ENDED = set([\"5-1\", \"6-1\", \"7-1\", \"8-1\"])\n",
"READY = set([\"0-3\", \"0-9\", \"2-3\", \"2-9\", \"9-3\", \"9-9\"])\n",
"RUN = set([\"3-1\", \"3-4\", \"3-5\", \"3-6\", \"3-7\", \"3-8\", \"3-10\", \"10-1\", \"10-4\", \"10-5\", \"10-6\", \"10-7\", \"10-8\", \"10-10\"])\n",
"EVICT = set([\"4-1\", \"4-0\"])"
]
},
{
"cell_type": "code",
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"execution_count": 3,
"id": "reported-cabinet",
"metadata": {},
"outputs": [],
"source": [
"def to_name(et):\n",
" if et == 4: \n",
" return 'EVICT'\n",
" elif et == 5: \n",
" return 'FAIL'\n",
" elif et == 6:\n",
" return 'FINISH'\n",
" elif et == 7:\n",
" return 'KILL'\n",
" elif et == 8:\n",
" return 'LOST'\n",
" else:\n",
" return 'NO_TERM'\n",
"\n",
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"def create_df(cluster):\n",
" obj = {}\n",
"\n",
" filename=\"/home/claudio/google_2019/thesis_queries/machine_time_waste/\" + cluster + \"_state_changes.json\"\n",
"\n",
" with open(filename, 'r') as f:\n",
" obj = json.loads(f.read())\n",
" \n",
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" data = {'Last termination': [], 'time_type': [], 'time_ms': []}\n",
" totals = {}\n",
" \n",
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" def add_record(et, tt, time):\n",
" data['Last termination'].append(to_name(et))\n",
" data['time_type'].append(tt)\n",
" data['time_ms'].append(time)\n",
"\n",
" for pair in obj[\"data\"]:\n",
" qt = et = rt = xt = vt = ut = 0\n",
"\n",
" pair[0] = 0 if pair[0] is None else pair[0]\n",
"\n",
" x = pair[1]\n",
" for k in x.keys():\n",
" if k in QUEUE:\n",
" qt += x[k]\n",
" elif k in ENDED:\n",
" et += x[k]\n",
" elif k in READY:\n",
" rt += x[k]\n",
" elif k in RUN:\n",
" xt += x[k]\n",
" elif k in EVICT:\n",
" vt += x[k]\n",
" else:\n",
" ut += x[k]\n",
"\n",
" add_record(pair[0], 'queued', qt)\n",
" add_record(pair[0], 'ended', et)\n",
" add_record(pair[0], 'ready', rt)\n",
" add_record(pair[0], 'running', xt)\n",
" add_record(pair[0], 'evicted', vt)\n",
" add_record(pair[0], 'unknown', ut)\n",
" totals[pair[0]] = qt + et + rt + xt + vt + ut\n",
" \n",
" return (pandas.DataFrame(data, columns=['Last termination', 'time_type', 'time_ms']), totals)"
]
},
{
"cell_type": "markdown",
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"id": "generous-spencer",
"metadata": {},
"source": [
"## Graph 1: Absolute total time spent per status per \"last termination\" type"
]
},
{
"cell_type": "code",
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"execution_count": 4,
"id": "immediate-amino",
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"metadata": {},
"outputs": [],
"source": [
"def graph_1(df, cluster):\n",
" sns.set_theme(style=\"ticks\")\n",
" g = sns.histplot(df, x=\"Last termination\", weights=\"time_ms\", shrink=.5,\n",
" hue=\"time_type\", multiple=\"dodge\", discrete=True)\n",
" g.set_yscale(\"log\")\n",
" g.set_ylabel(\"Total microseconds\") \n",
" g.set_title(\"Cluster \" + cluster + \": Absolute total time spent per status per \\\"last termination\\\" type\")\n",
" #g.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)"
]
},
{
"cell_type": "markdown",
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"id": "painful-enhancement",
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"metadata": {},
"source": [
"## Graph 2: Relative total time spent per status per \"last termination\" type\n",
"\n",
"Values are proportions on total for each \"last termination\" type"
]
},
{
"cell_type": "code",
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"execution_count": 5,
"id": "oriented-morning",
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"metadata": {},
"outputs": [],
"source": [
"def graph_2(df, cluster, totals):\n",
" df = df.copy()\n",
" for i in [0,4,5,6,7,8]:\n",
" df.loc[df[\"Last termination\"] == to_name(i), \"time_ms\"] = df[\"time_ms\"][df[\"Last termination\"] == to_name(i)] / totals[i]\n",
"\n",
" h = sns.histplot(df, x=\"Last termination\", \n",
" weights=\"time_ms\", shrink=.5, common_bins=True,\n",
" hue=\"time_type\", multiple=\"stack\", discrete=True)\n",
" fig, ax = plt.subplots()\n",
" #ax.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
" h.set_title(\"Cluster \" + cluster + \": Relative total time spent per status per \\\"last termination\\\" type\") "
]
},
{
"cell_type": "code",
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"execution_count": 8,
"id": "passing-african",
"metadata": {},
"outputs": [
{
"data": {
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"image/png": "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
"text/plain": [
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"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
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"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAcgAAAEdCAYAAACIUvd2AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAABXqUlEQVR4nO3deVxN+f8H8Ff3tmmTSinLDM1IlnRTYUQUQtE6MonK2LKbGVNDZMnSMEIYYzczzBhEisFYapj5CTPIEhlfS/ue0naXzu+PpjPdui1X3W7L+/l49OB8zvb+nHvOfd+zfT4KDMMwIIQQQogYjrwDIIQQQloiSpCEEEKIBJQgCSGEEAkoQRJCCCESUIIkhBBCJKAESQghhEjQ6AQZHh6OL774oiliaXK//fYbbG1twePx8Pjx40YtKzk5GSYmJhAKhU0UXQU7Ozv8+eefTbpMeQkMDERYWFiDp1+1ahV27dolw4gIqUlWx3JLIMtj6uzZs5gxY4ZMlt1SNShBRkVFwc3NDTweDzY2Npg5cybu3LnTZEHIaocNDQ3FypUrcffuXfTt27dB88TFxcHExAR79+5t0liaQmOTqbTzN2XyjoiIwCeffCJWtnbtWsyfP79Jlt/SxMXFYcSIEfIOQyJJn0VdWnNCCQwMREREBCIiIhAYGNiky67v+JDHPtBUx5Skz3zSpEk4ePBgkyzbzs4OQMU2TE5OljjdtGnTcOLEiUavrzHqTZCHDh3Chg0bMHfuXPzxxx+4du0avLy8cOXKleaIr0FqO3BTU1Px4YcfSrWsM2fOQFtbG5GRkU0RGiHNQiQSyTsEuWuNCbwuba0+rVGdCbKwsBA7duzAqlWrMHbsWKipqUFJSQl2dnYICAioMb2kX0xVf2XFx8fDzc0NFhYW+Oijj7Bx40YAgLe3NwDAysoKPB4Pd+/eBQCcPHkS48ePh5WVFT799FOkpKSwyzUxMcHRo0cxduxYjB07VmydfD4fPB4PIpEIzs7OGD16dIM2RnFxMS5cuIBVq1bh1atXePDgQY1pTp06BRsbG9jY2ODAgQNseW11A4ArV67A0dERlpaWmDZtGp4/fy5x/dUvUVbdnsuWLUNqairmzp0LHo+Hffv2AQDu3buHKVOmwNLSEpMmTUJcXJzEZdc2f22x1Tb9okWLMGzYMAwaNAhTp07Fs2fP6t2uz58/R3BwMO7duwcejwdLS8sa9a2s6759+zB06FDY2Njg8uXLiI2NhYODA6ytrbFnzx52meXl5di7dy9Gjx6NwYMHY/HixcjPz5e4/tzcXMyZMweWlpawtraGl5cXysvLAVTsn9999x0mTJgAKysrfPXVVygrK2PnvXbtGpydnWFpaYkpU6bgyZMn7Dg7OzscOHAAEydOxKBBg7BkyRKUlZWhuLgYs2bNQmZmJng8Hng8HjIyMmrEFRgYiFWrVsHPzw88Hg/e3t5i+/jz58/h5+cHa2trODg44Pz582LzBgcHY9asWTA3N5f4uUdERMDe3h48Hg92dnY4e/ZsrZ9FTEwMXFxcYGFhAVtbW4SHh7PLkXR8Vr+1Uv2MQ9K6JQkPD8eiRYuwZMkS8Hg8uLq6im3jjIwMLFy4EEOGDIGdnR2+//77GvN+8cUXsLCwwOnTpyWuoz6nTp3C+PHjwePxYG9vj59//pkdV9u+U9vxUam2faCu/bZyG544cQIjR46Ej48PIiIiMGXKFGzYsAGWlpawt7fH33//jYiICNja2mLo0KFi9ZZ0TB08eJA9pk6dOsVOK+1nXv3Kw99//w13d3cMGjQI7u7u+Pvvv9lx06ZNw7Zt2zBlyhTweDzMmDEDubm5Df5MwsLCcOfOHaxduxY8Hg9r167FmjVrsGnTJrHp5s6di8OHDwNo3LFcK6YOsbGxjKmpKSMQCGqdZseOHcznn3/OMAzD3Lx5kxk+fLjY+FGjRjF//PEHwzAMM3nyZOb06dMMwzDM27dvmbt37zIMwzBJSUlM7969xdbz22+/MaNHj2b++ecfRiAQMLt27WI8PT3Z8b1792Z8fX2ZvLw8pqSkRGJsvXv3Zl6+fMkODxo0iLl9+3atdTl9+jQzbNgwRigUMnPmzGHWrl3LjquMcenSpUxRURHz5MkTZvDgwfXW7X//+x8zcOBA5saNGwyfz2f27t3LjB49mikrK6uxfQICApitW7ey66y+PatOyzAMk56ezlhbWzMxMTGMSCRibty4wVhbWzM5OTkS61d9fmliq3TixAmmsLCQKSsrY0JCQphJkyax46rHX9WpU6eYKVOmiJVVnf7mzZuMqakpEx4ezvD5fOb48ePM4MGDmc8++4wpLCxkEhMTmQEDBjCvX79mGIZhDh8+zHz88cdMWloaU1ZWxqxcuZJZunSpxHVv2bKFWblyJcPn8xk+n8/cvn2bKS8vZ+vo6OjIpKamMnl5eYynpycb06NHj5ghQ4Yw9+7dY4RCIRMREcGMGjVKbPu4u7sz6enpTF5eHjNu3Djm2LFjEj87SQICAhhzc3Pm1q1bTFlZGbNu3Tp2GxUVFTEjRoxgTp48yQgEAubRo0eMtbU18+zZM3ZeCwsL5s6dO4xIJGJKS0vFll1UVMTweDzm+fPnDMMwTEZGBpOYmFjrZ3Hz5k3myZMnjEgkYhISEpihQ4cyv/32G8Mwko/Pqsd99WnqWnd1O3bsYPr27cv8+uuvDJ/PZ/bv38+MGjWK4fP5jEgkYlxdXZnw8HCmrKyMef36NWNnZ8f8/vvvYvP+9ttvjEgkqvV7oLrq9bl27Rrz6tUrpry8nImLi2PMzMyYhw8fMgxT/75T/fiovk2r7wN17beVcS1btowpKipiSkpKmFOnTjGmpqbMyZMnGaFQyGzdupWxtbVlVq9ezZSVlTHXr19nzM3Nmbdv3zIMI/mY2rZtG8Pn85mYmBjGzMyMyc/PZ8dL85lX3W/y8vIYS0tL5vTp04xAIGCioqIYS0tLJjc3l2EYhvH29mbs7e2Z//3vf0xJSQnj7e3NbN68uUGfTyVvb2/ml19+YYfv37/PDBs2jBGJRAzDMExOTg5jZmbGZGVlsZ/Hux7LtanzDDI/Px+dOnWCoqJigzN/XRQVFfH69Wvk5uZCXV0d5ubmtU77888/Y/bs2TA2NoaioiLmzp2LhIQEsV/Ys2fPhra2NlRVVRu0/jt37rC/mCU5c+YMxo8fDy6XCycnJ5w7dw4CgUBsmvnz50NNTQ0mJiZwc3NDdHR0nXU7f/48bG1tMWzYMCgpKeHTTz9FaWkpe5bcGJGRkRgxYgRsbW3B4XAwbNgw9O/fH7GxsQ2a/11i8/DwgIaGBpSVlbFw4UI8efIEhYWFja4LULEN/f39oaSkhAkTJiAvLw/Tp0+HhoYGPvzwQ3zwwQd4+vQpgIr9Y+nSpejSpQuUlZWxYMECXLx4UeJlKUVFRWRlZSE1NRVKSkqwtLSEgoICO37q1KkwNDSEtrY2/P39ce7cOQDA8ePH4enpiYEDB4LL5cLV1RVKSkq4d+8eO++0adNgYGAAbW1tjBo1CgkJCVLVeeTIkbCysoKysjKWLl2Ke/fuIS0tDTExMejatSvc3d2hqKiIvn37wsHBARcuXGDntbe3x6BBg8DhcKCiolJj2RwOB8+ePUNpaSn09fXrvN0wePBgmJiYgMPhoE+fPnB0dMStW7ekqsu7rrtfv34YN24clJSU4OfnBz6fj/v37+PBgwfIzc3FggULoKysjO7du2Py5MliZ9Lm5uYYPXo0OBxOg78Hqhs5ciR69OgBBQUFWFtbY9iwYewzFvXtO9JqyH67cOFCqKmpsfXp1q0b3N3dweVyMWHCBKSlpWH+/PlQVlaGjY0NlJWV8fr1a4nrU1RUxPz586GkpARbW1uoqanhxYsXABr3mcfExOC9996Di4sLFBUV4eTkhF69euHatWvsNG5ubujZsydUVVUxbtw4qY+N6szMzKCpqYn/+7//A1Dx/WVtbQ09PT12msYcy5LUmfm0tbWRl5cHoVDYJEly/fr12LFjB8aPH49u3bphwYIFGDVqlMRpU1NTsWHDBoSGhrJlDMMgIyMDXbt2BQA
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAcQAAAEdCAYAAACSbhf4AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAABNTElEQVR4nO3dd3xN9//A8VdulhERQiJWFa3GCJfETIwEiQghZmOVmkVU+1UxKrYaXytWqVnab6vUiBRVo7Sl1Rq1VSmRRSJCErk3N+f3h5/TXAmCm+n9fDw85JzzOZ9x7jn3fc/njI+ZoigKQgghxCtOk9cVEEIIIfIDCYhCCCEEEhCFEEIIQAKiEEIIAUhAFEIIIQAJiEIIIQRggoAYGhrKf/7zH1PUxeS+//57WrRogVar5dy5czlWzrFjx2jevPkLrz9p0iSWLl1qwhrljuDgYBYsWJDt9AW1naJgi4iIoEaNGqSlpeV1VUwuJ4+pHTt2MGDAgBzJO7/KVkDcuXMnAQEBaLVa3N3dGThwIMePHzdZJXJqh509ezYff/wxJ06coGbNmk9Nu3XrVpydndFqtdSvX5+OHTty4MABk9bnUTlvv/220bypU6cyfPhwk5fl6enJzz//nGPpnyY325kfvOyPopyU1WfxNAU5gAQHB7N161a2bt1KcHCwSfN+1vGRF/uAqY6prD7zjh07smbNGpPk7enpCTzchhEREVmm69OnD5s3b37p8l7GMwPi2rVrmTlzJkOHDuWnn37iwIEDBAYG8sMPP+RG/bLlSQduZGQkb7zxRrbzqVevHidOnOD48eMEBgbywQcfkJiYaKpqCmEyBoMhr6uQ5wpiwH6awtaeguipAfHevXssXryYSZMm0bZtW4oVK4alpSWenp6MHTs2U/qsfiFl/FV1+vRpAgICqF+/Pk2bNmXWrFkA9O7dGwA3Nze0Wi0nTpwA4JtvvqFdu3a4ubnx7rvvcvPmTTXfGjVqsGnTJtq2bUvbtm2NytTpdGi1WgwGA/7+/rRu3fr5NopGg7+/P8nJyVy7dk3Nc/bs2bRs2ZKmTZsyadIkHjx4kOX6K1eupHXr1mi1Wnx9ffn+++8BuHLlCiEhIZw8eRKtVourqytg3PXYrl07ozPTtLQ0GjduzNmzZwE4efIkPXv2xNXVlY4dO3Ls2LEs6zBmzBgiIyMZOnQoWq2WVatWAfDDDz/Qvn17XF1d6dOnD1euXHlq+qCgIJo1a0aDBg3o1asXly9ffub2y047H+0rq1atokmTJri7u7Nv3z4OHTqEt7c3DRs2ZMWKFWqe6enp6nZt1KgRo0aNIiEhIcvy4+PjGTJkCK6urjRs2JDAwEDS09OBh/vjp59+iq+vL25ubowbN47U1FR13QMHDuDv74+rqys9e/bkwoUL6jJPT09Wr15Nhw4daNCgAe+//z6pqakkJyczaNAgYmNj0Wq1aLVaYmJiMtUrODiYSZMm0b9/f7RaLb179zbap69cuUL//v1p2LAh3t7ehIeHG60bEhLCoEGDqFevXpaf+9atW/Hy8kKr1eLp6cmOHTue+FkcPHiQTp06Ub9+fVq0aEFoaKiaT1bH4+OXRh4/o8iq7KyEhoYSFBTE+++/j1arpXPnzkbbOCYmhpEjR9K4cWM8PT3ZsGFDpnX/85//UL9+fb799tssy3iWLVu20K5dO7RaLV5eXvzvf/9Tlz1p33nS8fHIk/aBp+23j7bh5s2badmyJf369WPr1q307NmTmTNn4urqipeXF3/88Qdbt26lRYsWNGnSxKjdWR1Ta9asUY+pLVu2qGmf9zN/vGfhjz/+oEuXLjRo0IAuXbrwxx9/qMv69OnDwoUL6dmzJ1qtlgEDBhAfH5/tz2TBggUcP36cqVOnotVqmTp1KlOmTOGTTz4xSjd06FDWrVsHvNyx/ETKUxw6dEhxdnZW9Hr9E9MsXrxY+fDDDxVFUZSjR48qHh4eRstbtWql/PTTT4qiKEr37t2Vb7/9VlEURbl//75y4sQJRVEU5caNG8qbb75pVM7333+vtG7dWvnrr78UvV6vLF26VOnRo4e6/M0331Teeecd5c6dO0pKSkqWdXvzzTeVa9euqdMNGjRQfvvttyzTbtmyRenZs6eiKIqSlpambNy4UalVq5Zy+/ZtRVEUZcaMGcqQIUOUO3fuKPfu3VOGDBmizJs3L8t2h4eHK9HR0YrBYFB27dql1K1bV4mJiclUziNjx45V5s+fryiKooSGhioffPCBuuzAgQOKj4+PoiiKEh0drTRs2FA5ePCgYjAYlCNHjigNGzZU4uLismxTxm2vKIry999/K3Xr1lWOHDmi6HQ6ZeXKlUrr1q2V1NTULNMriqJs3rxZuXfvnpKamqpMnz5d6dixY5b1ftr2zCr90aNHFWdnZyU0NFTR6XTKV199pTRq1Ej54IMPlHv37imXLl1S6tSpo1y/fl1RFEVZt26d0q1bNyUqKkpJTU1VPv74Y2X06NFZlj1v3jzl448/VnQ6naLT6ZTffvtNSU9PV9vYvn17JTIyUrlz547So0cPtU5nz55VGjdurJw8eVJJS0tTtm7dqrRq1cpo+3Tp0kWJjo5W7ty5o/j4+ChffPGF2p7H9/3HjR07VqlXr57y66+/Kqmpqcq0adPUbZSUlKQ0b95c+eabbxS9Xq+cPXtWadiwoXL58mV13fr16yvHjx9XDAaD8uDBA6O8k5KSFK1Wq1y5ckVRFEWJiYlRLl269MTP4ujRo8qFCxcUg8GgnD9/XmnSpIny/fffK4qS9fGY8Th/PM3Tyn7c4sWLlZo1ayrfffedotPplM8++0xp1aqVotPpFIPBoHTu3FkJDQ1VUlNTlevXryuenp7Kjz/+aLTu999/rxgMhice9497vD0HDhxQ/vnnHyU9PV05duyY4uLiopw5c0ZRlGfvO48fH49v08f3gaftt4/qNWbMGCUpKUlJSUlRtmzZojg7OyvffPONkpaWpsyfP19p0aKFMnnyZCU1NVU5fPiwUq9ePeX+/fuKomR9TC1cuFDR6XTKwYMHFRcXFyUhIUFd/jyfecb95s6dO4qrq6vy7bffKnq9Xtm5c6fi6uqqxMfHK4qiKL1791a8vLyUv//+W0lJSVF69+6tzJ07N1ufzyO9e/dWvv76a3X61KlTSrNmzRSDwaAoiqLExcUpLi4uyq1bt9TP40WP5Sd56hliQkICpUqVwsLCItuR/mksLCy4fv068fHxFC9enHr16j0x7f/+9z8GDx5MtWrVsLCwYOjQoZw/f97oF/XgwYOxs7OjSJEi2Sr/+PHj6i/krJw6dQpXV1dcXFyYPXs2c+bMwd7eHkVR+Prrrxk/fjx2dnbY2NgwZMgQdu3alWU+7dq1w9HREY1Gg6+vL6+99hqnT5/OVh07dOjA/v37SUlJAR5ev23fvj0A27dvp3nz5rRo0QKNRkOzZs2oXbs2hw4dylbe4eHhtGjRgmbNmmFpacm7777LgwcP1DPyrHTt2hUbGxusrKwYOXIkFy5c4N69e9kq71ksLCwYNmwYlpaW+Pr6cufOHfr27YuNjQ1vvPEG1atX5+LFi8DD/WH06NGUK1cOKysrRowYwZ49e7LsZrKwsODWrVtERkZiaWmJq6srZmZm6vJevXrh5OSEnZ0dw4YNUz/Hr776ih49elC3bl3Mzc3p3LkzlpaWnDx5Ul23T58+ODo6YmdnR6tWrTh//vxztblly5a4ublhZWXF6NGjOXnyJFFRURw8eJAKFSrQpUsXLCwsqFmzJt7e3uzevVtd18vLiwYNGqDRaLC2ts6Ut0aj4fLlyzx48AAHB4enXi5o1KgRNWrUQKPR8NZbb9G+fXt+/fXX52rLi5Zdq1YtfHx8sLS0pH///uh0Ok6dOsWff/5JfHw8I0aMwMrKikqVKtG9e3ejM+V69erRunVrNBpNto/7x7Vs2ZLKlStjZmZGw4YNadasmXpPxLP2neeVnf125MiRFCtWTG1PxYoV6dKlC+bm5vj6+hIVFcXw4cOxsrLC3d0dKysrrl+/nmV5FhYWDB8+HEtLS1q0aEGxYsW4evUq8HK
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAcgAAAEdCAYAAACIUvd2AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAABMxklEQVR4nO3deVxN+f8H8Ff3tpBKKqXEGNmyNN2ULIX2pF1kKlvKiIRZlDWR3c+WfQvDGBJSmuzrGGYYe/ZhkjZKSuvtdn5/+Hamq5OK2217Px8PD51zPueznHvufd/zued8PjIMwzAghBBCiBheXVeAEEIIqY8oQBJCCCEcKEASQgghHChAEkIIIRwoQBJCCCEcKEASQgghHL44QEZERODHH3+URF0ajS89JkOHDsW1a9ckWCPpsLS0xJUrV6qdvqG2kzRshw8fxrffflvX1agVtfmemjdvHjZs2FAreddX1QqQsbGxcHd3h0AggJmZGfz8/HD9+nWJVSI5ORldu3ZFSUmJxPL8UiEhIejZsycEAgH69OmDcePG4dmzZ7VSzurVq8XWHT9+HKamphItp6bHWNKvibTaWV/U5y+OXK/FpzTkgGJpaYnk5GSEhITg8OHDEsu3Ou+PujgHJPWe4nrNFyxYgMmTJ0sk75CQECQnJ8PS0rLSdF27dsW///77xeV9iSoDZGRkJBYvXoyJEyfi999/x7lz5+Dl5YUzZ85Io37VUluBdfz48bh58yYuXrwILS0tzJ49u1bKIeRL1KcvlnWFYRiUlpbWdTUkil7XuvfJAJmbm4t169Zh3rx5sLW1haKiIuTk5GBpaYng4OAK6a9du4aBAweKrSvf7Xbnzh24u7vDyMgI/fv3x5IlSwAAPj4+AAATExMIBALcvHkTAHDo0CEMGTIEJiYmGD9+PF69esXm27VrV+zbtw+2trawtbXlrP/Ro0dhYWEBU1NTbNiwocZdgGWaNWuGIUOG4OHDh+y69PR0TJkyBX379oWlpSX27NlT6f5BQUEYMGAAevfuDW9vbzx58gQAcODAAcTGxmLHjh0QCASYOHGi2DFLT0+HgYEBsrOz2bwSExNhamoKoVBY5TEqj+sYl5aWYuPGjbCwsEC/fv0wY8YM5ObmVpo+KSkJo0ePhqmpKUxNTfHDDz8gJyenyuNXVTuBD9+2g4KC8OOPP0IgEMDJyQnPnz/Hli1b0K9fPwwaNAiXL19m88zNzcWsWbNgZmYGc3NzrF69GiKRiLP8ys67squAAwcOwMzMDGZmZtixYwe7X2lpKbZu3Qpra2uYmppi6tSp7GtRtu+RI0cwePBgmJqaYtOmTQCAixcvYsuWLfjtt98gEAjg7OzMWS9LS0ts2bIFDg4OMDExwcyZM1FUVMRuP3fuHFxcXGBsbIyRI0eKnX+WlpbYunUrnJycYGhoWOHDlGEYLF68GP369YORkRGcnJzw+PHjSl+LsnYKBAI4ODjg1KlTAIBnz54hNDQUt27dgkAggLGxMQBg1KhRiIqKYssrf8VRWdlcRo0ahf/7v/+Dh4cHjIyMEBAQIHa+37p1CyNHjoSxsTGcnZ3Fug9HjRqF1atXY+TIkfjmm2/w8uVLzjKqEh4ejkGDBsHIyAju7u5ivWM1/cwqU9k58Knz9vDhwxg5ciQWL14MU1NTREREICQkBPPnz4efnx8EAgFGjhyJ169fY9GiRTAxMYG9vT0SExPZcj9+T02dOhUzZsyAQCDA0KFDcffuXTZtTV/zj3seDh48CBsbG/Tp0wcTJ05Eeno6u61r167Yv38/bG1tYWxsjLCwMNRk0DZvb28AgIuLCwQCAeLj4+Ho6IizZ8+yaYRCIUxNTZGYmPhF7+VPYj7hwoULjL6+PiMUCitNs27dOuaHH35gGIZhrl69ypibm4ttt7CwYH7//XeGYRhmxIgRzJEjRxiGYZj3798zN2/eZBiGYV6+fMl06dJFrJxTp04x1tbWzNOnTxmhUMhs2LCB8fT0ZLd36dKFGTt2LPP27VumoKCgQr2ePHnCGBoaMn/99RdTVFTELF26lOnevTtbl7/++ovp3bt3pe0KDg5mVq1axTAMw+Tl5TE//vgj4+TkxDAMw4hEIsbNzY2JiIhgioqKmKSkJMbS0pK5ePFihWPCMAwTFRXF5ObmMkVFRUx4eDjj7OzMWQ7XMRs1ahRz4MABdtvSpUuZuXPnVusYlcd1jKOiohhra2smKSmJef/+PTN58mTmxx9/rDT9ixcvmMuXLzNFRUVMZmYm4+XlxYSHh3PW+1PHkyv9unXrmJ49ezIXL15khEIh89NPPzEWFhbMxo0bmeLiYubAgQOMhYUFu++kSZOYuXPnMnl5ecybN2+YYcOGMfv37+csu6rzbvr06UxeXh7z8OFDxtTUlK3Trl27mOHDhzOpqalMUVERM3fuXGb69Oli+86ePZspKChgHjx4wPTo0YN5+vQp257y5wAXCwsLZujQoUxKSgrz9u1bxtPTkz1G9+/fZ/r27cvcunWLKSkpYQ4fPsxYWFgwRUVF7L7Ozs5MSkoK5/l/8eJFxs3NjXn37h1TWlrKPH36lElPT6/0tYiPj2fS0tIYkUjEHD9+nPnmm2/Y9NHR0czIkSPF0vv4+DAHDx5kl8un+VTZH/Px8WHMzMyYR48eMXl5eUxgYCB73NLS0pg+ffow58+fZ0QiEXP58mWmT58+TGZmJrvvoEGDmMePHzNCoZApLi7+5PHmqivDMMzRo0eZrKwsRigUMjt27GD69+/PFBYWMgxTs8+sj3GdA586b6Ojoxl9fX1mz549jFAoZAoKCpjg4GCmT58+zN27d5nCwkJm1KhRjIWFBXPkyBGmpKSEWbVqFePj48Pmz/WeOn/+PFNSUsKsXLmSGT58OJu2pq95+fPmypUrTJ8+fZh79+4xRUVFzIIFCxgvLy82bZcuXZgJEyYw7969Y169esWYmpoyFy5cqPrFKadLly7Mixcv2OWtW7cyU6dOZZdPnTrFODo6MgzzZe/lT/nkFWR2djZatWoFWVnZakf+T5GVlUVSUhKysrLQokULGBoaVpr2119/xYQJE6CnpwdZWVlMnDgRDx48ELtCmjBhAlRVVdGsWbMK+yckJMDCwgLGxsaQl5dHUFAQZGRk2O3GxsZV/o66c+dOGBsbw8jICDdu3MDy5csBAHfv3kVWVhYCAwMhLy+Pdu3aYcSIEYiPj+fMx8PDA0pKSpCXl8eUKVPw8OFD9kqtKk5OToiLiwPw4Zt5fHw8nJycqn2MPiU2NhZjx45Fu3bt0KJFC3z//feIj4+vtGvnq6++woABAyAvLw81NTWMGzcOf/31V7XKqg5jY2OYm5tDVlYW9vb2ePv2LSZMmAA5OTk4ODjg1atXyMnJwZs3b3DhwgXMmjULioqKUFdXx9ixY3H8+HHOfKs67yZPngxFRUV07doV7u7u7PH+9ddfMX36dLRp0wby8vIIDAzEiRMnxI5PYGAgmjVrhm7duqFbt25iV3nV4e3tDW1tbaiqqiIgIIBtw4EDB+Dp6YlvvvkGfD4fbm5ukJOTw61bt9h9R40aBW1tbc7zX1ZWFnl5efjnn3/AMAz09PSgqalZaT2GDBkCLS0t8Hg8ODg44KuvvsKdO3dq1JbPLdvFxQVdunSBoqIipk6dioSEBIhEIsTExGDgwIEYNGgQeDweBgwYgJ49e+LChQvsvm5ubujcuTNkZWUhJyf3WfV1cXFhP+d8fX1RXFyM58+fs22p7mdWVapz3mpqamLUqFGQlZVlX1cbGxv07NkTCgoKsLGxgYKCAlxdXcHn8+Hg4IAHDx5UWmbv3r0xaNAg8Pl8uLi4iJ2fX/Kax8bGYtiwYejRowfk5eXx/fff49atW0hOTmbT+Pv7Q0VFBTo6OjA1Na3xe+Njzs7OuHDhAt6/fw8AOHbsWIXemS95L3P5ZORTVVXF27dvUVJSIpEguWjRIqxbtw5DhgyBrq4uAgMDYWFhwZk2JSUFixcvxrJly9h1DMMgPT0dbdu2BQBoa2tXWlZGRgbatGnDLjdv3hyqqqo1qq+vry+mT5+OlJQU+Pn54fnz5+j
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
2021-02-23 15:33:21 +00:00
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAc4AAAEdCAYAAACFTIcxAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAABNrUlEQVR4nO3deVwVVf/A8Q+7IpIrCOLyZGkuGSiIJaiACq6Ae4hbj/uC+mS5JmiuaWJiapqapY+ZaaLk9php+pSUT5r7mhvKohKCgNzLZX5/mPPzCihXuZfF7/v18iUzc2bOOXNn7vfOmZlzzBRFURBCCCFEgZgXdQGEEEKIkkQCpxBCCGEACZxCCCGEASRwCiGEEAaQwCmEEEIYQAKnEEIIYYDnDpxRUVGMHz++MMpiUhMnTiQyMhKA2NhYWrZsaZJ8fX19+fnnn59p3SNHjuDv71/IJTI+Q/dvSa2nKPn69u3Lpk2biroYhc7Y55SbmxvXr1832vaLmwIFzu3bt9O1a1fc3Nzw8vJi0KBBHDlypNAKERcXR7169cjOzi60bRpTvXr1cHV1xc3NDW9vb+bMmYNOpzNKPlevXlWn3d3d2b17d6HnY+iPn8L+sWSqehYXz/Pjydge/yyepqQGmtjYWPr27Qs8qHNhKsj5YepjoDDPqbw+86NHj1KjRo1C2XZsbCxRUVFERUXlmWbLli28/fbbz53X87B8WoI1a9awYsUKpk+fjpeXF1ZWVhw8eJAffvgBd3d3U5TxqbKzs7G0fGpVClV0dDS1atXi6tWrhIaGUqdOHXr27GnSMgjxNEVxbhQ3pW0fKIqCoiiYm8udtqLyxD2flpbG4sWLmTZtGu3atcPW1hYrKyt8fX2ZMGFCrvR5Nck9+svq+PHjdO3alSZNmvDWW28xZ84cAEJDQwHw8PDAzc2No0ePAvDtt9/Svn17PDw8+Oc//8mNGzfU7darV4/169fTrl072rVrl2f5w8LCaNGiBU2bNqVPnz5cuHChoPulwGrVqkWTJk04c+aMOu/HH38kMDAQd3d3evfuzdmzZ/Nc9/jx4/Tq1Qt3d3e8vLyYMWMGGo0GgD59+gAQGBiIm5sbO3bs0Nu/K1asICwsTG97M2fOZObMmcCDz27y5Ml4eXnh7e1NZGRknlfFP/30E5999hk7d+7Ezc2NLl26AJCYmMiwYcNo1qwZbdu25Ztvvnli+s2bN9O+fXvc3Nzw8/Pj66+/LtD+e1o94cEx9Pnnn9O5c2dcXV2ZPHkyt2/fZtCgQbi5uTFgwADu3r2rpj927Bi9e/fG3d2dLl26EBsbm2/+K1aswNvbGzc3N/z9/fnll1+AB1cNYWFhjB07Fjc3N4KDg/U+x8TEREaPHk3z5s3x9fXlyy+/VJdFRUUxZswY3n//fdzc3OjYsSMnTpwA4L333uPmzZsMGzYMNzc3Vq5cmatMD+u/fPlyPD098fX1Zdu2bepyjUbDvHnzaN26NW+99RbTpk3j/v37euuuWLGCFi1aMGnSpFzbf/hjr2nTpnh6ejJ27Nh8P4u7d+8ydOhQmjdvjoeHB0OHDiUhIQGAyMhIjhw5wowZM3Bzc2PGjBl5th49eoWSX96Pe7idjRs34uXlhZeXF6tWrVKX5+TksGLFCtq0aYOnpydjxowhJSVFb91NmzbRunVr+vfvn2ceT3Pt2jX69euHp6cnnp6evPvuu6SmpqrL8zp28js/HpXfMfCk47Zv375ERkbSu3dv3njjDa5fv673Hejm5saiRYu4du0avXv3pkmTJowZM0b9PsnrnFq1ahWdO3emadOmjB07lqysLACDP3PQb6lIS0vj/fffp3nz5vj4+LB06VJycnKA/79anDdvHh4eHvj6+nLgwIECfyaXLl0iPDycY8eO4ebmhru7O8ePH+ett97S+37bs2ePuu+f51zOl/IEBw4cUOrXr69otdp80yxevFh59913FUVRlMOHDyve3t56y318fJT//ve/iqIoSs+ePZXvvvtOURRFuXfvnnL06FFFURTl+vXrSt26dfXy+c9//qO0adNGuXjxoqLVapVPP/1U6dWrl7q8bt26yoABA5S//vpLyczMzLNsmzZtUtLS0pSsrCxl5syZSpcuXdRlEyZMUBYuXJhnucPDw5Xw8PB861y3bl3lypUriqIoysWLF5UWLVooa9asURRFUU6dOqU0b95cOXbsmJKdna1s2bJF8fHxUbKysnLtjxMnTihHjx5VtFqtcv36dSUgIEDdzuP5PF7OuLg4pXHjxkpaWpqiKIqSnZ2ttGjRQt2nI0aMUD744AMlPT1duX37ttKtWzdlw4YNedbn0c/woZCQECU8PFy5f/++cvr0acXT01P5+eef803/448/KlevXlVycnKU2NhYpXHjxsrJkyfz3L9P2p95pffx8VF69Oih3Lp1S0lISFCaN2+uBAUFKadOnVLu37+v9O3bV4mKilIURVESEhKUZs2aKfv371d0Op1y6NAhpVmzZsqdO3dy5Xvp0iWlZcuWSkJCgqIoD47Dq1evqnVs0KCBsnPnTkWj0Siff/654uPjo2g0GkWn0ynBwcFKVFSUkpWVpVy7dk3x9fVVfvrpJ3XdRo0aKfv371eys7OVBQsWKD169NCrz8NjIC+HDx9W6tevr8yePVvJyspSYmNjlTfeeEO5dOmSoiiKMmvWLGXo0KHKX3/9paSlpSlDhw5VFixYoLfuRx99pGRlZeV5bowbN05ZunSpotPplPv37yu//fZbvp9FcnKysmvXLiUjI0NJS0tTRo8erQwfPlxdHhoaqnzzzTfqdF7n8qNpnpT3ox5uZ9y4cUp6erpy9uxZxdPTU91vX3zxhdKjRw8lPj5eycrKUj744ANl3Lhxeuu+9957Snp6er7fD3l5tKxXrlxRDh06pGRlZSl37txRQkJClJkzZyqK8vRj5/Hz43GPHwNPO25DQ0OVVq1aKefPn1e0Wq2i0WiUunXrKsOGDVPS0tKU8+fPKw0bNlT69eunXLt2TUlNTVXat2+vbNmyRVGUvM+pbt26KQkJCcpff/2lBAQEKP/+978VRTH8M1cU/ePmvffeU8t1/fp1pV27dmr6zZs3Kw0aNFA2btyoZGdnK+vXr1datGih5OTkFPgz2rx5s9K7d2+9ee3bt1f279+vTo8YMUJZtWqVoijPdy7n54lXnCkpKVSsWLHQmjksLS25du0aycnJlCtXDldX13zTfv311wwZMoQ6depgaWnJsGHDOHPmjN5V55AhQ6hQoQJlypTJcxvdu3fHzs4Oa2trRo8ezdmzZ0lLS3tqOSMiIoiIiHhimuDgYFxdXenQoQPNmjUjJCQEgI0bN9KrVy/eeOMNLCwsCA4OxsrKimPHjuXaRqNGjXB1dcXS0hIXFxd69erFb7/99tTyAVSvXp0GDRqwd+9eAA4fPkyZMmVwdXXl9u3bHDhwgMmTJ2Nra0vlypUZMGAA33//fYG2HR8fz++//8748eOxsbGhfv369OjRg+jo6HzXad26NTVr1sTMzIxmzZrRokWLQr0PHhoaSpUqVXB0dMTd3Z3GjRvToEEDbGxsaNu2LadPnwYeNKG3bNmSVq1aYW5uTosWLWjUqFGev2otLCzQaDRcunQJrVaLi4sLNWvWVJc3bNiQgIAArKysGDhwIBqNhj/++IMTJ06QnJzMqFGjsLa2pkaNGvTs2ZMdO3ao6zZt2pRWrVphYWFBYGBgvq0OTzJmzBisra1p1qwZrVq1YufOnSiKwjfffMPkyZOpUKECdnZ2DB06VO+zNTc3JywsDGtr6zzPDUtLS27evElSUhI2NjZPvOVSsWJF/P39KVu2LHZ2dgwfPrzAx2heDMkbYOTIkdja2lKvXj26du1KTEwM8OD7Ydy4cVSrVg1ra2tGjRrF7t279a50R48eja2tbb7fD09Tq1YtWrRogbW1NZUqVWLgwIFq3Z927BiqIMdtcHAwr776KpaWllhZWQEwaNAg7OzsePXVV6lbty4tWrSgRo0alC9fnpYtW6rnRV769u2Lo6MjFSpUwMfHR201e57PXKfTsWPHDt59913s7Ox
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
2021-02-23 15:33:21 +00:00
"dft = None\n",
"tts = None\n",
"\n",
2021-02-23 15:33:21 +00:00
"for cluster in \"abcdefgh\":\n",
" df, totals = create_df(cluster)\n",
" graph_1(df, cluster)\n",
" plt.figure()\n",
" graph_2(df, cluster, totals)\n",
" \n",
" if dft is None:\n",
" dft = df\n",
" tts = totals\n",
" else:\n",
" dft.loc[:, \"time_ms\"] = dft[\"time_ms\"].add(df[\"time_ms\"], fill_value=0)\n",
" for key in totals:\n",
" tts[key] += totals[key]\n",
" \n",
"graph_1(dft, \"all\")\n",
"plt.figure()\n",
"graph_2(dft, \"all\", tts)"
]
},
{
"cell_type": "code",
2021-02-27 12:07:15 +00:00
"execution_count": 7,
"id": "pointed-bleeding",
"metadata": {},
"outputs": [
{
"data": {
2021-02-23 15:33:21 +00:00
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Last termination</th>\n",
" <th>time_type</th>\n",
" <th>time_ms</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>NO_TERM</td>\n",
" <td>queued</td>\n",
" <td>1699297448488984</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>NO_TERM</td>\n",
" <td>ended</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>NO_TERM</td>\n",
" <td>ready</td>\n",
" <td>125206711192446239</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>NO_TERM</td>\n",
" <td>running</td>\n",
" <td>38422265478853144</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>NO_TERM</td>\n",
" <td>evicted</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>NO_TERM</td>\n",
" <td>unknown</td>\n",
" <td>23419631884996</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>EVICT</td>\n",
" <td>queued</td>\n",
" <td>1435821272661726</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>EVICT</td>\n",
" <td>ended</td>\n",
" <td>47675802186</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>EVICT</td>\n",
" <td>ready</td>\n",
" <td>560627352043828</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>EVICT</td>\n",
" <td>running</td>\n",
" <td>250411263386366629</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>EVICT</td>\n",
" <td>evicted</td>\n",
" <td>22829884749530</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>EVICT</td>\n",
" <td>unknown</td>\n",
" <td>67267757697376575</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>FAIL</td>\n",
" <td>queued</td>\n",
" <td>1578510135252959</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>FAIL</td>\n",
" <td>ended</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>FAIL</td>\n",
" <td>ready</td>\n",
" <td>26139149330305</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>FAIL</td>\n",
" <td>running</td>\n",
" <td>48338511089399230</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>FAIL</td>\n",
" <td>evicted</td>\n",
" <td>557255</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>FAIL</td>\n",
" <td>unknown</td>\n",
" <td>16599969189378396</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>FINISH</td>\n",
" <td>queued</td>\n",
" <td>53576662501368320</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>FINISH</td>\n",
" <td>ended</td>\n",
" <td>85816274414</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>FINISH</td>\n",
" <td>ready</td>\n",
" <td>24400884339346191</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>FINISH</td>\n",
" <td>running</td>\n",
" <td>551150109458054816</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>FINISH</td>\n",
" <td>evicted</td>\n",
" <td>11507599</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>FINISH</td>\n",
" <td>unknown</td>\n",
" <td>505479685280501015</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>KILL</td>\n",
" <td>queued</td>\n",
" <td>616978559668414433</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>KILL</td>\n",
" <td>ended</td>\n",
" <td>760262369583642</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>KILL</td>\n",
" <td>ready</td>\n",
" <td>180362665151474149</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>KILL</td>\n",
" <td>running</td>\n",
" <td>3653008453309109098</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>KILL</td>\n",
" <td>evicted</td>\n",
" <td>391227515104446</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>KILL</td>\n",
" <td>unknown</td>\n",
" <td>2655091526754536598</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>LOST</td>\n",
" <td>queued</td>\n",
" <td>286647827559</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>LOST</td>\n",
" <td>ended</td>\n",
" <td>1830379457905173</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>LOST</td>\n",
" <td>ready</td>\n",
" <td>4515413933134</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>LOST</td>\n",
" <td>running</td>\n",
" <td>56717065233915</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>LOST</td>\n",
" <td>evicted</td>\n",
" <td>2014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td>LOST</td>\n",
" <td>unknown</td>\n",
" <td>11733560670807780</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
2021-02-23 15:33:21 +00:00
" Last termination time_type time_ms\n",
"0 NO_TERM queued 1699297448488984\n",
"1 NO_TERM ended 0\n",
"2 NO_TERM ready 125206711192446239\n",
"3 NO_TERM running 38422265478853144\n",
"4 NO_TERM evicted 0\n",
"5 NO_TERM unknown 23419631884996\n",
"6 EVICT queued 1435821272661726\n",
"7 EVICT ended 47675802186\n",
"8 EVICT ready 560627352043828\n",
"9 EVICT running 250411263386366629\n",
"10 EVICT evicted 22829884749530\n",
"11 EVICT unknown 67267757697376575\n",
"12 FAIL queued 1578510135252959\n",
"13 FAIL ended 0\n",
"14 FAIL ready 26139149330305\n",
"15 FAIL running 48338511089399230\n",
"16 FAIL evicted 557255\n",
"17 FAIL unknown 16599969189378396\n",
"18 FINISH queued 53576662501368320\n",
"19 FINISH ended 85816274414\n",
"20 FINISH ready 24400884339346191\n",
"21 FINISH running 551150109458054816\n",
"22 FINISH evicted 11507599\n",
"23 FINISH unknown 505479685280501015\n",
"24 KILL queued 616978559668414433\n",
"25 KILL ended 760262369583642\n",
"26 KILL ready 180362665151474149\n",
"27 KILL running 3653008453309109098\n",
"28 KILL evicted 391227515104446\n",
"29 KILL unknown 2655091526754536598\n",
"30 LOST queued 286647827559\n",
"31 LOST ended 1830379457905173\n",
"32 LOST ready 4515413933134\n",
"33 LOST running 56717065233915\n",
"34 LOST evicted 2014\n",
"35 LOST unknown 11733560670807780"
]
},
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"execution_count": 7,
"metadata": {},
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"output_type": "execute_result"
}
],
"source": [
2021-02-23 15:33:21 +00:00
"dft"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
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"name": "ipython",
"version": 3
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
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