1061 lines
259 KiB
Plaintext
1061 lines
259 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import json\n",
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"import sys\n",
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"import glob\n",
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"import pandas as pd\n",
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"import seaborn as sns\n",
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"import matplotlib as mpl\n",
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"import os\n",
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"from IPython.display import display, Markdown"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"DIR = os.environ[\"HOME\"] + \"/Git/bachelorThesis/table_iii/\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"NAMES = {-1: \"No termination\", 0: \"SUBMIT\", 1: \"QUEUE\", 2: \"ENABLE\", \n",
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" 3: \"SCHEDULE\", 4: \"EVICT\", 5: \"FAIL\", 6: \"FINISH\",\n",
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" 7: \"KILL\", 8: \"LOST\", 9: \"UPDATE_PENDING\", 10: \"UPDATE_RUNNING\"}\n",
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"\n",
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"def rename(df, new, old):\n",
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" df.rename(columns={old: new}, inplace=True)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/markdown": [
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"# Table III"
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],
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"text/plain": [
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"<IPython.core.display.Markdown object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\\tableIII{A}{\n",
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"\\begin{tabular}{llrrrr}\n",
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"\\toprule\n",
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" EVICT & 103.228 (719) & 73.694 & 0.769 & 0.000 & 28.766 \\\\\n",
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" FAIL & 11.819 (26) & 0.288 & 11.062 & 0.002 & 0.468 \\\\\n",
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" FINISH & 2.185 (1) & 0.019 & 0.004 & 2.153 & 0.008 \\\\\n",
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" KILL & 5.963 (11) & 2.350 & 0.214 & 0.003 & 3.396 \\\\\n",
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"\\bottomrule\n",
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"\\end{tabular}\n",
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"}\n",
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"\\tableIII{B}{\n",
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"\\begin{tabular}{llrrrr}\n",
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"\\toprule\n",
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" EVICT & 83.018 (394) & 64.817 & 0.240 & 0.000 & 17.962 \\\\\n",
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" FAIL & 20.851 (62) & 0.518 & 19.657 & 0.001 & 0.675 \\\\\n",
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" FINISH & 2.995 (4) & 0.020 & 0.021 & 2.943 & 0.012 \\\\\n",
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" KILL & 9.173 (12) & 3.351 & 0.276 & 0.004 & 5.541 \\\\\n",
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"\\bottomrule\n",
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"\\end{tabular}\n",
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"}\n",
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"\\tableIII{C}{\n",
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"\\begin{tabular}{llrrrr}\n",
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"\\toprule\n",
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" EVICT & 98.437 (444) & 73.716 & 1.813 & 0.000 & 22.908 \\\\\n",
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" FAIL & 52.010 (30) & 0.773 & 48.446 & 2.035 & 0.756 \\\\\n",
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" FINISH & 2.507 (2) & 0.018 & 0.013 & 2.471 & 0.006 \\\\\n",
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" KILL & 5.452 (6) & 1.533 & 0.116 & 0.004 & 3.799 \\\\\n",
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"\\bottomrule\n",
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"\\end{tabular}\n",
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"}\n",
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"\\tableIII{D}{\n",
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"\\begin{tabular}{llrrrr}\n",
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"\\toprule\n",
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" EVICT & 76.759 (366) & 62.001 & 0.700 & 0.000 & 14.058 \\\\\n",
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" FAIL & 62.314 (62) & 0.496 & 58.968 & 0.810 & 2.040 \\\\\n",
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" FINISH & 3.877 (2) & 0.059 & 0.019 & 3.789 & 0.010 \\\\\n",
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" KILL & 6.795 (6) & 1.960 & 0.151 & 0.002 & 4.682 \\\\\n",
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"\\bottomrule\n",
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"\\end{tabular}\n",
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"}\n",
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"\\tableIII{E}{\n",
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"\\begin{tabular}{llrrrr}\n",
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"\\toprule\n",
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" EVICT & 17.678 (72) & 11.781 & 0.106 & 0.000 & 5.791 \\\\\n",
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" FAIL & 112.384 (28) & 0.458 & 111.471 & 0.000 & 0.456 \\\\\n",
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" FINISH & 2.029 (2) & 0.014 & 0.008 & 1.999 & 0.008 \\\\\n",
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" KILL & 13.505 (64) & 1.288 & 0.057 & 0.000 & 12.160 \\\\\n",
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"\\bottomrule\n",
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"\\end{tabular}\n",
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"}\n",
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"\\tableIII{F}{\n",
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"\\begin{tabular}{llrrrr}\n",
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"\\toprule\n",
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" EVICT & 70.146 (114) & 23.974 & 0.192 & 0.000 & 45.980 \\\\\n",
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" FAIL & 41.087 (54) & 0.279 & 39.257 & 0.000 & 1.550 \\\\\n",
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" FINISH & 3.129 (4) & 0.019 & 0.004 & 3.008 & 0.098 \\\\\n",
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" KILL & 10.288 (38) & 0.384 & 0.098 & 0.001 & 9.804 \\\\\n",
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"\\bottomrule\n",
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"\\end{tabular}\n",
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"}\n",
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"\\tableIII{G}{\n",
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"\\begin{tabular}{llrrrr}\n",
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"\\toprule\n",
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" EVICT & 136.032 (490) & 77.429 & 0.303 & 0.000 & 58.299 \\\\\n",
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" FAIL & 8.948 (8) & 0.016 & 8.593 & 0.000 & 0.339 \\\\\n",
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" FINISH & 14.176 (2) & 0.015 & 0.002 & 14.154 & 0.005 \\\\\n",
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" KILL & 32.320 (164) & 6.909 & 0.135 & 0.000 & 25.276 \\\\\n",
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"\\bottomrule\n",
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"\\end{tabular}\n",
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"}\n",
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"\\tableIII{H}{\n",
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"\\begin{tabular}{llrrrr}\n",
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"\\toprule\n",
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" EVICT & 14.734 (40) & 6.733 & 0.837 & 0.000 & 7.165 \\\\\n",
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" FAIL & 41.067 (120) & 0.600 & 37.600 & 0.000 & 2.867 \\\\\n",
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" FINISH & 3.681 (2) & 0.024 & 0.014 & 3.633 & 0.011 \\\\\n",
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" KILL & 17.976 (98) & 0.633 & 0.170 & 0.000 & 17.173 \\\\\n",
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"\\bottomrule\n",
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"\\end{tabular}\n",
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"}\n",
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"\\tableIII{ALL}{\n",
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"\\begin{tabular}{llrrrr}\n",
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"\\toprule\n",
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" EVICT & 78.710 (342) & 52.242 & 0.673 & 0.000 & 25.795 \\\\\n",
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" FAIL & 24.962 (26) & 0.290 & 23.635 & 0.348 & 0.691 \\\\\n",
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" FINISH & 2.962 (2) & 0.022 & 0.012 & 2.915 & 0.013 \\\\\n",
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" KILL & 8.763 (16) & 1.876 & 0.143 & 0.003 & 6.741 \\\\\n",
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"\\bottomrule\n",
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"\\end{tabular}\n",
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"}\n"
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]
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}
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],
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"source": [
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"display(Markdown(\"# Table III\"))\n",
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"for cluster in list(\"abcdefgh\") + [\"all\"]:\n",
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" df = pd.read_csv(glob.glob(DIR + \"/table-iii-\" + cluster + \".csv/part-00000-*\")[0])\n",
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" df = df[df[\"task_term\"].isin(range(4,8))]\n",
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" df = df.sort_values(\"task_term\")\n",
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" df[\"mean\"] = df[\"mean\"].round(3).apply(lambda x: \"%.03f\" % x) + \" (\" + df[\"%95\"].apply(lambda x: \"%d\" % x) + \")\"\n",
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" rename(df, \"# Evts. mean (95-th percentile)\", \"mean\")\n",
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" del df[\"%95\"]\n",
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" \n",
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" for i in [4,5,6,7]:\n",
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" df.loc[df.task_term == i, \"task_term\"] = NAMES[i]\n",
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" df[\"avg_count_%d\" % i] = df[\"avg_count_%d\" % i].round(3)\n",
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" rename(df, \"mean # \" + NAMES[i] + \" evts.\", \"avg_count_\" + str(i))\n",
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" for i in [0,1,2,3,8,9,10]:\n",
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" del df[\"avg_count_\" + str(i)]\n",
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" rename(df, \"Task termination\", \"task_term\")\n",
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" print((\"\\\\tableIII{\" + cluster.upper() + \"}{\"))\n",
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" print(df.to_latex(index=False, header=False), end=\"}\\n\")\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/markdown": [
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"# Table IV"
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],
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"text/plain": [
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"<IPython.core.display.Markdown object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\\tableIV{A}{\n",
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" EVICT & 0.000 (0) & NaN & NaN & NaN & NaN \\\\\n",
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" FAIL & 90.793 (499) & 0.695 & 0.684 & 0.086 & 1.850 \\\\\n",
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" FINISH & 1.187 (1) & 0.005 & 0.001 & 1.073 & 0.024 \\\\\n",
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" KILL & 16.533 (10) & 1.045 & 0.074 & 0.461 & 1.189 \\\\\n",
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"}\n",
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"\\tableIV{B}{\n",
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" EVICT & 1.000 (1) & 1.000 & 0.000 & 0.000 & 0.000 \\\\\n",
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" FAIL & 74.368 (374) & 2.003 & 1.994 & 0.267 & 4.944 \\\\\n",
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" FINISH & 6.304 (10) & 0.022 & 0.008 & 2.349 & 0.013 \\\\\n",
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" KILL & 69.853 (234) & 1.696 & 0.158 & 0.614 & 3.009 \\\\\n",
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"}\n",
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"\\tableIV{C}{\n",
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" EVICT & 1.000 (1) & 1.001 & 0.000 & 0.000 & 0.000 \\\\\n",
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" FAIL & 41.982 (200) & 3.484 & 0.998 & 0.376 & 3.998 \\\\\n",
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" FINISH & 1.991 (1) & 0.022 & 0.017 & 1.565 & 0.017 \\\\\n",
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" KILL & 110.681 (652) & 0.627 & 0.059 & 0.656 & 2.267 \\\\\n",
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"}\n",
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"\\tableIV{D}{\n",
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" EVICT & 1.000 (1) & 1.000 & 0.000 & 0.000 & 0.000 \\\\\n",
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" FAIL & 43.356 (250) & 6.112 & 0.949 & 0.531 & 6.498 \\\\\n",
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" FINISH & 2.109 (2) & 0.268 & 0.013 & 1.723 & 0.019 \\\\\n",
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" KILL & 89.648 (283) & 1.013 & 0.054 & 0.283 & 3.256 \\\\\n",
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"}\n",
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"\\tableIV{E}{\n",
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" EVICT & 1.000 (1) & 1.000 & 0.000 & 0.000 & 0.000 \\\\\n",
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" FAIL & 23.081 (25) & 0.247 & 0.666 & 0.717 & 1.588 \\\\\n",
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" FINISH & 7.776 (2) & 0.019 & 0.029 & 1.934 & 0.021 \\\\\n",
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" KILL & 88.790 (309) & 0.706 & 0.029 & 0.461 & 7.572 \\\\\n",
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"}\n",
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"\\tableIV{F}{\n",
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" EVICT & 1.000 (1) & 1.000 & 0.000 & 0.000 & 0.000 \\\\\n",
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" FAIL & 17.161 (8) & 0.621 & 0.546 & 0.426 & 7.559 \\\\\n",
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" FINISH & 2.941 (2) & 0.015 & 0.051 & 1.670 & 0.162 \\\\\n",
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" KILL & 103.889 (361) & 0.183 & 0.064 & 0.417 & 5.824 \\\\\n",
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"}\n",
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"\\tableIV{G}{\n",
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" EVICT & 1.000 (1) & 1.000 & 0.000 & 0.000 & 0.000 \\\\\n",
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" FAIL & 51.835 (250) & 0.556 & 3.335 & 0.608 & 20.352 \\\\\n",
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" FINISH & 8.519 (36) & 0.002 & 0.630 & 1.760 & 0.005 \\\\\n",
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" KILL & 37.055 (100) & 5.687 & 0.065 & 0.080 & 19.166 \\\\\n",
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"}\n",
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"\\tableIV{H}{\n",
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" EVICT & 1.000 (1) & 1.000 & 0.000 & 0.000 & 0.000 \\\\\n",
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" FAIL & 20.504 (1) & 0.114 & 2.300 & 0.981 & 12.833 \\\\\n",
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" FINISH & 4.278 (14) & 0.005 & 0.153 & 1.778 & 0.014 \\\\\n",
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" KILL & 11.023 (3) & 0.235 & 0.103 & 0.288 & 11.337 \\\\\n",
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"}\n",
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"\\tableIV{ALL}{\n",
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" EVICT & 0.989 (1) & 1.000 & 0.000 & 0.000 & 0.000 \\\\\n",
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" FAIL & 43.126 (200) & 0.114 & 2.300 & 0.981 & 12.833 \\\\\n",
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" FINISH & 3.074 (2) & 0.005 & 0.153 & 1.778 & 0.014 \\\\\n",
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" KILL & 53.919 (178) & 0.235 & 0.103 & 0.288 & 11.337 \\\\\n",
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"}\n"
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]
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}
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],
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"source": [
|
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"display(Markdown(\"# Table IV\"))\n",
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"for cluster in list(\"abcdefgh\") + [\"all\"]:\n",
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" df = pd.read_csv(glob.glob(DIR + \"/table-iv-evts-\" + cluster + \".csv/part-00000-*\")[0], header=None,\n",
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" names=[\"term\"] + [str(i) for i in range(0,11)])\n",
|
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" df2 = pd.read_csv(glob.glob(DIR + \"/table-iv-tasks-\" + cluster + \".csv/part-00000-*\")[0], header=None,\n",
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" names=[\"term\", \"mean\", \"%95\"])\n",
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" df[\"term\"] = df[\"term\"].astype(int)\n",
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" df2[\"term\"] = df2[\"term\"].astype(int)\n",
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" df.sort_values(by=\"term\", inplace=True)\n",
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" df2.sort_values(by=\"term\", inplace=True)\n",
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" \n",
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" df = df2.merge(df, on=\"term\", how=\"outer\")\n",
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" df = df[df[\"term\"].isin(range(4,8))]\n",
|
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" df.loc[df[\"mean\"] == -1, \"mean\"] = 0\n",
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" df.loc[df[\"%95\"] == -1, \"%95\"] = 0\n",
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" df[\"mean\"] = df[\"mean\"].round(3).apply(lambda x: \"%.03f\" % x) + \" (\" + df[\"%95\"].apply(lambda x: \"%d\" % x) + \")\"\n",
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" rename(df, \"# Tasks. mean (95-th p)\", \"mean\")\n",
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" del df[\"%95\"]\n",
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" \n",
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"\n",
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" rename(df, \"# Evts. mean\", \"mean\")\n",
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" rename(df, \"# Evts. 95% p.tile\", \"%95\")\n",
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" \n",
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" for i in [4,5,6,7]:\n",
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" df.loc[df.term == i, \"term\"] = NAMES[i]\n",
|
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" df[str(i)] = df[str(i)].round(3)\n",
|
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" rename(df, \"# \" + NAMES[i] + \" Evts. mean\", str(i))\n",
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" for i in [0,1,2,3,8,9,10]:\n",
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" del df[str(i)]\n",
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" rename(df, \"Job termination\", \"term\")\n",
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" print((\"\\\\tableIV{\" + cluster.upper() + \"}{\"))\n",
|
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" s = df.to_latex(index=False,header=False)\n",
|
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" s = s.split(\"\\\\toprule\\n\")[1]\n",
|
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" s = s.split(\"\\\\bottomrule\")[0]\n",
|
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" print(s, end=\"}\\n\")\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"max_count = 50"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Cluster a\n",
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" t4 t5 t7\n",
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"x \n",
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"0 47.362837 46.554701 97.884036\n",
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"1 16.332856 5.089623 0.888921\n",
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"2 6.524053 0.105539 0.129768\n",
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"3 3.214002 0.030579 0.043725\n",
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"4 1.922403 0.026895 0.050441\n",
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"5 1.338548 0.041612 0.028431\n",
|
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"6 1.018056 0.005256 0.013225\n",
|
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"7 0.722958 0.007037 0.006126\n",
|
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"8 0.558332 0.000000 0.002636\n",
|
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"9 0.370550 0.000000 0.001270\n",
|
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"10 0.292962 0.000000 0.000875\n",
|
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"11 0.224133 0.000000 0.000000\n",
|
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"12 0.178119 0.000000 0.005838\n",
|
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"13 0.149303 0.000000 0.001727\n",
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"14 0.123257 0.000000 0.000000\n",
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"15 0.139037 0.000000 0.000000\n",
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"16 0.167366 0.000000 0.000000\n",
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"17 0.203744 0.000000 0.000000\n",
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"18 0.201785 0.000000 0.000000\n",
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"19 0.272658 0.000000 0.000000\n",
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"20 0.301028 0.000000 0.000000\n",
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"21 0.307559 0.000000 0.000000\n",
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"22 0.365285 0.000000 0.000000\n",
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"23 0.348940 0.000000 0.000000\n",
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"24 0.403881 0.000000 0.000000\n",
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"25 0.433774 0.000000 0.000000\n",
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"26 0.583566 0.000000 0.000000\n",
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"27 0.603533 0.000000 0.000000\n",
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"28 0.508347 0.000000 0.000000\n",
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"29 0.469310 0.000000 0.000000\n",
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"30 0.612706 0.000000 0.000000\n",
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"31 0.501672 0.000000 0.000000\n",
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"32 0.409605 0.000000 0.000000\n",
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"33 0.374111 0.000000 0.000000\n",
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"34 0.398718 0.000000 0.000000\n",
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"35 0.467942 0.000000 0.000000\n",
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"36 0.431704 0.000000 0.000000\n",
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"37 0.412002 0.000000 0.000000\n",
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"38 0.468911 0.000000 0.000000\n",
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"39 0.264317 0.000000 0.000000\n",
|
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"40 0.276155 0.000000 0.000000\n",
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"41 0.288184 0.000000 0.000000\n",
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"42 0.263883 0.000000 0.000000\n",
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"43 0.290839 0.000000 0.000000\n",
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"44 0.234163 0.000000 0.000000\n",
|
|
"45 0.285677 0.000000 0.000000\n",
|
|
"46 0.299973 0.000000 0.000000\n",
|
|
"47 0.200602 0.000000 0.000000\n",
|
|
"48 0.133968 0.000000 0.000000\n",
|
|
"49 0.231624 0.000000 0.000000\n",
|
|
"50 0.246427 0.000000 0.000000\n",
|
|
"Cluster b\n",
|
|
" t4 t5 t7\n",
|
|
"x \n",
|
|
"0 36.320530 34.309040 98.618346\n",
|
|
"1 26.594129 10.444409 1.171874\n",
|
|
"2 5.573492 27.567062 0.299673\n",
|
|
"3 19.855097 6.627517 6.087220\n",
|
|
"4 3.256016 1.578588 0.144134\n",
|
|
"5 14.672686 2.670623 3.251599\n",
|
|
"6 1.812073 0.068354 0.118964\n",
|
|
"7 7.969639 8.620690 0.127632\n",
|
|
"8 0.903039 0.143705 0.072289\n",
|
|
"9 6.896552 0.000000 0.000000\n",
|
|
"10 0.439832 0.283714 0.045550\n",
|
|
"11 6.060606 0.175747 0.000000\n",
|
|
"12 0.238994 0.303344 0.028309\n",
|
|
"13 8.695652 5.882353 0.000000\n",
|
|
"14 0.131841 0.136813 0.027090\n",
|
|
"15 11.363636 11.428571 0.000000\n",
|
|
"16 0.086630 0.170514 0.017097\n",
|
|
"17 19.354839 3.333333 0.000000\n",
|
|
"18 0.048183 0.229606 0.019054\n",
|
|
"19 12.500000 4.000000 0.000000\n",
|
|
"20 0.052340 0.177276 0.021857\n",
|
|
"21 25.000000 6.060606 0.000000\n",
|
|
"22 0.040403 0.088594 0.027238\n",
|
|
"23 5.555556 5.555556 0.000000\n",
|
|
"24 0.026294 0.095572 0.023853\n",
|
|
"25 20.000000 6.250000 0.000000\n",
|
|
"26 0.023747 0.206186 0.021003\n",
|
|
"27 14.285714 0.000000 0.000000\n",
|
|
"28 0.052672 0.078818 0.007426\n",
|
|
"29 0.000000 0.000000 0.000000\n",
|
|
"30 0.068830 0.098309 0.012387\n",
|
|
"31 0.000000 0.000000 0.000000\n",
|
|
"32 0.050386 0.137127 0.009484\n",
|
|
"33 7.692308 0.000000 0.000000\n",
|
|
"34 0.068846 0.000000 0.007023\n",
|
|
"35 0.000000 0.000000 0.000000\n",
|
|
"36 0.080070 0.053262 0.008368\n",
|
|
"37 66.666667 0.000000 0.000000\n",
|
|
"38 0.091681 0.000000 0.014958\n",
|
|
"39 0.000000 0.000000 0.000000\n",
|
|
"40 0.097831 0.000000 0.003045\n",
|
|
"41 0.000000 0.000000 0.000000\n",
|
|
"42 0.058265 0.000000 0.002896\n",
|
|
"43 0.000000 0.000000 0.000000\n",
|
|
"44 0.061367 0.025355 0.005606\n",
|
|
"45 9.090909 0.000000 0.000000\n",
|
|
"46 0.048591 0.050942 0.003122\n",
|
|
"47 0.000000 0.000000 0.000000\n",
|
|
"48 0.045963 0.192123 0.000000\n",
|
|
"49 0.000000 0.000000 0.000000\n",
|
|
"50 0.078819 0.136333 0.000000\n",
|
|
"Cluster c\n",
|
|
" t4 t5 t7\n",
|
|
"x \n",
|
|
"0 34.700920 34.244187 99.449071\n",
|
|
"1 32.133579 2.658985 5.362580\n",
|
|
"2 11.507749 13.749614 0.127211\n",
|
|
"3 31.860347 12.113402 1.082349\n",
|
|
"4 9.508958 2.728234 0.031753\n",
|
|
"5 29.913754 12.466368 1.580905\n",
|
|
"6 6.906893 3.103991 0.024434\n",
|
|
"7 31.560593 3.180862 3.205128\n",
|
|
"8 4.878342 1.776444 0.017919\n",
|
|
"9 32.667618 19.892473 0.186567\n",
|
|
"10 3.235434 2.721451 0.010076\n",
|
|
"11 31.178707 10.545455 0.234192\n",
|
|
"12 2.155569 5.704472 0.005586\n",
|
|
"13 36.528497 3.596288 0.000000\n",
|
|
"14 1.490700 5.219576 0.009520\n",
|
|
"15 32.363636 22.033898 2.448980\n",
|
|
"16 1.053054 8.133270 0.023441\n",
|
|
"17 36.199095 10.000000 4.750000\n",
|
|
"18 0.778531 11.835851 0.011607\n",
|
|
"19 38.636364 2.040816 0.495050\n",
|
|
"20 0.579882 13.535099 0.007809\n",
|
|
"21 42.675159 3.125000 0.000000\n",
|
|
"22 0.476852 19.568463 0.002137\n",
|
|
"23 39.436620 15.789474 0.529101\n",
|
|
"24 0.348962 18.518519 0.002317\n",
|
|
"25 41.964286 11.111111 0.877193\n",
|
|
"26 0.283916 15.388631 0.006934\n",
|
|
"27 41.758242 3.846154 0.000000\n",
|
|
"28 0.298426 15.383536 0.001477\n",
|
|
"29 42.222222 6.250000 0.000000\n",
|
|
"30 0.239024 21.026035 0.000000\n",
|
|
"31 40.000000 27.272727 0.000000\n",
|
|
"32 0.253931 18.458524 0.003032\n",
|
|
"33 41.818182 50.000000 1.562500\n",
|
|
"34 0.223272 15.286715 0.002772\n",
|
|
"35 50.000000 50.000000 2.525253\n",
|
|
"36 0.201950 12.893482 0.006265\n",
|
|
"37 38.461538 20.000000 0.680272\n",
|
|
"38 0.194737 12.593703 0.003507\n",
|
|
"39 47.368421 0.000000 0.000000\n",
|
|
"40 0.217931 9.067358 0.000000\n",
|
|
"41 50.847458 66.666667 0.000000\n",
|
|
"42 0.215771 3.875328 0.000000\n",
|
|
"43 45.652174 11.111111 0.000000\n",
|
|
"44 0.213527 1.301953 0.000000\n",
|
|
"45 38.636364 14.285714 0.000000\n",
|
|
"46 0.274613 0.265803 0.002078\n",
|
|
"47 33.333333 11.111111 0.000000\n",
|
|
"48 0.149810 0.102102 0.000000\n",
|
|
"49 36.111111 0.000000 0.000000\n",
|
|
"50 0.200553 0.045777 0.000000\n",
|
|
"Cluster d\n",
|
|
" t4 t5 t7\n",
|
|
"x \n",
|
|
"0 15.998574 15.744658 98.467699\n",
|
|
"1 39.241581 4.457610 0.407357\n",
|
|
"2 9.002476 6.888459 0.101781\n",
|
|
"3 46.903866 5.417925 0.599774\n",
|
|
"4 7.426166 4.110437 0.021777\n",
|
|
"5 46.852425 11.572700 0.386001\n",
|
|
"6 4.128459 5.157894 0.033838\n",
|
|
"7 48.850575 2.659574 0.145843\n",
|
|
"8 2.171374 3.593708 0.018238\n",
|
|
"9 45.427729 5.194805 0.065746\n",
|
|
"10 1.210312 9.673319 0.008470\n",
|
|
"11 32.017544 1.066790 0.000000\n",
|
|
"12 0.782879 7.090615 0.006522\n",
|
|
"13 28.089888 8.391608 0.000000\n",
|
|
"14 0.586503 2.948347 0.010075\n",
|
|
"15 29.133858 5.228758 0.000000\n",
|
|
"16 0.503178 3.976640 0.006712\n",
|
|
"17 26.923077 5.050505 0.000000\n",
|
|
"18 0.413075 6.716740 0.004206\n",
|
|
"19 15.957447 0.000000 0.000000\n",
|
|
"20 0.365594 4.436353 0.004179\n",
|
|
"21 18.571429 11.428571 0.000000\n",
|
|
"22 0.327552 1.143489 0.001154\n",
|
|
"23 14.814815 10.000000 0.000000\n",
|
|
"24 0.228291 0.517282 0.001413\n",
|
|
"25 14.035088 8.928571 0.000000\n",
|
|
"26 0.197619 0.297279 0.000000\n",
|
|
"27 14.893617 0.000000 0.000000\n",
|
|
"28 0.142954 0.040409 0.000000\n",
|
|
"29 11.764706 0.000000 0.000000\n",
|
|
"30 0.107823 0.070602 0.000000\n",
|
|
"31 21.428571 0.000000 0.000000\n",
|
|
"32 0.101385 0.016483 0.000000\n",
|
|
"33 17.948718 0.000000 0.000000\n",
|
|
"34 0.055946 0.020825 0.000000\n",
|
|
"35 8.888889 0.000000 0.000000\n",
|
|
"36 0.036581 0.000000 0.000000\n",
|
|
"37 15.384615 0.000000 0.000000\n",
|
|
"38 0.024701 0.000000 0.000000\n",
|
|
"39 0.000000 0.000000 0.000000\n",
|
|
"40 0.026115 0.000000 0.000000\n",
|
|
"41 5.882353 0.000000 0.000000\n",
|
|
"42 0.023865 0.000000 0.000000\n",
|
|
"43 0.000000 0.000000 0.000000\n",
|
|
"44 0.051188 0.000000 0.000000\n",
|
|
"45 2.380952 33.333333 0.000000\n",
|
|
"46 0.013461 0.000000 0.000000\n",
|
|
"47 3.125000 0.000000 0.000000\n",
|
|
"48 0.014197 0.000000 0.000000\n",
|
|
"49 5.555556 0.000000 0.000000\n",
|
|
"50 0.029987 0.000000 0.000000\n",
|
|
"Cluster e\n",
|
|
" t4 t5 t7\n",
|
|
"x \n",
|
|
"0 29.060181 27.568113 98.405342\n",
|
|
"1 42.092142 1.143201 0.331637\n",
|
|
"2 4.545281 0.862833 0.143521\n",
|
|
"3 42.342799 14.806867 1.183835\n",
|
|
"4 1.779696 1.917233 0.016046\n",
|
|
"5 39.553753 19.806763 0.792988\n",
|
|
"6 0.955921 4.733897 0.025259\n",
|
|
"7 17.818182 10.052910 0.288600\n",
|
|
"8 0.618527 7.872036 0.010712\n",
|
|
"9 8.474576 5.084746 0.184332\n",
|
|
"10 0.387358 26.811898 0.005487\n",
|
|
"11 2.816901 24.000000 0.080645\n",
|
|
"12 0.262131 21.145678 0.005748\n",
|
|
"13 3.092784 7.317073 0.000000\n",
|
|
"14 0.174203 6.922733 0.001833\n",
|
|
"15 0.000000 8.333333 0.000000\n",
|
|
"16 0.094376 9.696811 0.001886\n",
|
|
"17 0.990099 14.285714 0.000000\n",
|
|
"18 0.054997 13.310156 0.003360\n",
|
|
"19 0.000000 5.263158 0.000000\n",
|
|
"20 0.046538 8.521303 0.001230\n",
|
|
"21 0.000000 0.000000 0.000000\n",
|
|
"22 0.017076 3.672408 0.001389\n",
|
|
"23 0.000000 3.846154 0.000000\n",
|
|
"24 0.024240 9.278351 0.000000\n",
|
|
"25 0.000000 0.000000 0.000000\n",
|
|
"26 0.015338 2.069297 0.000000\n",
|
|
"27 0.000000 0.000000 0.000000\n",
|
|
"28 0.004213 1.397516 0.002578\n",
|
|
"29 0.000000 0.000000 0.000000\n",
|
|
"30 0.002302 0.338409 0.000000\n",
|
|
"31 0.000000 0.000000 0.000000\n",
|
|
"32 0.007490 0.000000 0.000971\n",
|
|
"33 0.000000 0.000000 0.000000\n",
|
|
"34 0.000000 0.139082 0.000000\n",
|
|
"35 0.000000 0.000000 0.000000\n",
|
|
"36 0.002919 0.115607 0.000000\n",
|
|
"37 0.000000 0.000000 0.000000\n",
|
|
"38 0.000000 0.000000 0.000000\n",
|
|
"39 0.000000 0.000000 0.000000\n",
|
|
"40 0.000000 0.089127 0.000000\n",
|
|
"41 0.000000 0.000000 0.000000\n",
|
|
"42 0.000000 0.000000 0.000000\n",
|
|
"43 0.000000 0.000000 0.000000\n",
|
|
"44 0.000000 0.000000 0.001411\n",
|
|
"45 0.000000 0.000000 0.373134\n",
|
|
"46 0.000000 0.000000 0.000000\n",
|
|
"47 0.000000 0.000000 0.000000\n",
|
|
"48 0.000000 0.000000 0.000000\n",
|
|
"49 0.000000 0.000000 0.000000\n",
|
|
"50 0.000000 0.281690 0.003120\n",
|
|
"Cluster f\n",
|
|
" t4 t5 t7\n",
|
|
"x \n",
|
|
"0 23.221217 22.949616 98.182529\n",
|
|
"1 28.964663 7.406842 0.602731\n",
|
|
"2 8.778786 2.814571 0.920639\n",
|
|
"3 5.952381 6.164384 1.419332\n",
|
|
"4 4.603357 0.210631 0.816905\n",
|
|
"5 2.777778 7.352941 0.488906\n",
|
|
"6 2.541858 0.163299 1.200103\n",
|
|
"7 3.546099 6.976744 0.353982\n",
|
|
"8 0.971659 0.056633 0.895532\n",
|
|
"9 1.739130 12.280702 0.068446\n",
|
|
"10 0.383972 0.064602 2.059272\n",
|
|
"11 1.111111 0.961538 0.160256\n",
|
|
"12 0.180200 0.129596 1.568797\n",
|
|
"13 1.388889 9.090909 0.000000\n",
|
|
"14 0.112934 0.143170 0.622607\n",
|
|
"15 0.000000 5.882353 0.000000\n",
|
|
"16 0.057648 0.406147 0.322456\n",
|
|
"17 0.000000 7.692308 0.000000\n",
|
|
"18 0.037331 0.178838 0.115619\n",
|
|
"19 0.000000 0.000000 0.143678\n",
|
|
"20 0.028396 0.100806 0.039895\n",
|
|
"21 3.448276 0.000000 0.000000\n",
|
|
"22 0.054437 0.074221 0.002923\n",
|
|
"23 2.173913 0.000000 0.000000\n",
|
|
"24 0.047396 0.154799 0.002537\n",
|
|
"25 0.000000 0.000000 0.000000\n",
|
|
"26 0.080215 0.074322 0.000803\n",
|
|
"27 3.846154 0.000000 0.000000\n",
|
|
"28 0.055064 0.097229 0.000000\n",
|
|
"29 0.000000 0.000000 0.000000\n",
|
|
"30 0.044152 0.000000 0.000000\n",
|
|
"31 0.000000 0.000000 0.000000\n",
|
|
"32 0.039355 0.245851 0.000000\n",
|
|
"33 0.000000 0.000000 0.000000\n",
|
|
"34 0.032819 0.247934 0.000000\n",
|
|
"35 0.000000 0.000000 0.000000\n",
|
|
"36 0.006266 0.401070 0.000000\n",
|
|
"37 0.000000 0.000000 0.000000\n",
|
|
"38 0.000000 0.318979 0.000000\n",
|
|
"39 0.000000 0.000000 0.000000\n",
|
|
"40 0.000000 0.907029 0.000000\n",
|
|
"41 0.000000 0.000000 0.000000\n",
|
|
"42 0.000000 0.271739 0.000000\n",
|
|
"43 0.000000 0.000000 0.000000\n",
|
|
"44 0.000000 0.000000 0.000000\n",
|
|
"45 0.000000 0.000000 0.000000\n",
|
|
"46 0.000000 0.000000 0.000000\n",
|
|
"47 0.000000 0.000000 0.000000\n",
|
|
"48 0.000000 0.420168 0.000000\n",
|
|
"49 0.000000 0.000000 0.000000\n",
|
|
"50 0.000000 0.500000 0.000000\n",
|
|
"Cluster g\n",
|
|
" t4 t5 t7\n",
|
|
"x \n",
|
|
"0 27.144219 23.955918 85.297571\n",
|
|
"1 37.458417 3.664392 0.336521\n",
|
|
"2 3.962138 1.156336 0.117015\n",
|
|
"3 39.669421 0.384044 6.434540\n",
|
|
"4 1.217580 0.389784 0.030781\n",
|
|
"5 43.333333 7.589286 1.724138\n",
|
|
"6 0.400887 0.111507 0.043164\n",
|
|
"7 24.637681 15.517241 0.663350\n",
|
|
"8 0.129372 0.001327 0.031519\n",
|
|
"9 3.125000 10.000000 0.569260\n",
|
|
"10 0.041683 0.166972 0.009957\n",
|
|
"11 0.000000 59.459459 0.000000\n",
|
|
"12 0.013887 0.282415 0.000674\n",
|
|
"13 3.846154 40.625000 0.000000\n",
|
|
"14 0.005518 0.024504 0.000000\n",
|
|
"15 0.000000 14.285714 0.000000\n",
|
|
"16 0.001399 0.090975 0.000000\n",
|
|
"17 4.761905 0.000000 0.000000\n",
|
|
"18 0.002394 0.026469 0.000000\n",
|
|
"19 0.000000 0.000000 0.000000\n",
|
|
"20 0.000000 0.081766 0.000000\n",
|
|
"21 10.526316 0.000000 0.000000\n",
|
|
"22 0.000000 0.000000 0.000000\n",
|
|
"23 0.000000 0.000000 0.000000\n",
|
|
"24 0.000000 0.000000 0.000000\n",
|
|
"25 0.000000 12.500000 0.000000\n",
|
|
"26 0.000000 0.000000 0.000000\n",
|
|
"27 0.000000 0.000000 0.000000\n",
|
|
"28 0.000000 0.000000 0.000000\n",
|
|
"29 0.000000 0.000000 0.000000\n",
|
|
"30 0.000000 0.000000 0.000000\n",
|
|
"31 3.448276 0.000000 0.000000\n",
|
|
"32 0.000000 0.000000 0.000000\n",
|
|
"33 0.000000 0.000000 0.000000\n",
|
|
"34 0.000000 0.000000 0.000000\n",
|
|
"35 0.000000 0.000000 0.000000\n",
|
|
"36 0.000000 0.000000 0.000000\n",
|
|
"37 0.000000 0.000000 0.000000\n",
|
|
"38 0.000000 0.000000 0.000000\n",
|
|
"39 0.000000 0.000000 0.000000\n",
|
|
"40 0.000000 0.000000 0.000000\n",
|
|
"41 0.000000 0.000000 0.000000\n",
|
|
"42 0.000000 0.000000 0.000000\n",
|
|
"43 0.000000 0.000000 0.000000\n",
|
|
"44 0.000000 0.000000 0.000000\n",
|
|
"45 0.000000 0.000000 0.000000\n",
|
|
"46 0.000000 0.000000 0.000000\n",
|
|
"47 0.000000 0.000000 0.000000\n",
|
|
"48 0.000000 0.000000 0.000000\n",
|
|
"49 0.000000 0.000000 0.000000\n",
|
|
"50 0.000000 0.000000 0.000000\n",
|
|
"Cluster h\n",
|
|
" t4 t5 t7\n",
|
|
"x \n",
|
|
"0 19.700148 18.546258 97.156117\n",
|
|
"1 15.942300 1.793886 0.020084\n",
|
|
"2 1.935968 14.486904 0.203083\n",
|
|
"3 1.666667 2.083333 0.443047\n",
|
|
"4 0.345462 2.401347 0.044810\n",
|
|
"5 0.000000 1.298701 0.167317\n",
|
|
"6 0.240148 0.446334 0.039865\n",
|
|
"7 0.000000 0.884956 0.000000\n",
|
|
"8 0.302454 0.041514 0.018718\n",
|
|
"9 0.000000 0.000000 0.000000\n",
|
|
"10 0.438648 0.009005 0.006319\n",
|
|
"11 0.000000 1.558074 0.121951\n",
|
|
"12 0.510128 0.059876 0.005273\n",
|
|
"13 0.000000 0.000000 0.000000\n",
|
|
"14 0.550489 0.088731 0.001569\n",
|
|
"15 0.000000 0.000000 0.300300\n",
|
|
"16 0.591507 0.009006 0.000884\n",
|
|
"17 0.000000 0.000000 0.000000\n",
|
|
"18 0.685781 0.000000 0.000472\n",
|
|
"19 0.000000 0.000000 0.416667\n",
|
|
"20 0.780825 0.000000 0.000000\n",
|
|
"21 0.000000 0.000000 0.000000\n",
|
|
"22 0.767510 0.000000 0.000000\n",
|
|
"23 0.000000 0.000000 0.000000\n",
|
|
"24 0.870496 0.000000 0.000000\n",
|
|
"25 0.000000 0.000000 0.000000\n",
|
|
"26 0.767858 0.000000 0.000000\n",
|
|
"27 0.000000 0.000000 0.751880\n",
|
|
"28 0.689920 0.000000 0.000000\n",
|
|
"29 0.000000 0.000000 0.000000\n",
|
|
"30 0.665122 0.000000 0.000000\n",
|
|
"31 0.000000 0.000000 0.000000\n",
|
|
"32 0.689776 0.000000 0.000000\n",
|
|
"33 0.000000 0.000000 0.000000\n",
|
|
"34 0.938967 0.000000 0.000000\n",
|
|
"35 0.000000 0.000000 0.000000\n",
|
|
"36 0.745282 0.000000 0.000000\n",
|
|
"37 0.000000 0.000000 0.000000\n",
|
|
"38 0.847693 0.000000 0.000000\n",
|
|
"39 0.000000 0.000000 0.000000\n",
|
|
"40 0.768979 0.000000 0.000000\n",
|
|
"41 0.000000 0.000000 0.000000\n",
|
|
"42 0.866218 0.000000 0.001087\n",
|
|
"43 0.000000 0.000000 0.000000\n",
|
|
"44 0.956106 0.000000 0.000000\n",
|
|
"45 0.000000 0.000000 0.000000\n",
|
|
"46 0.927086 0.000000 0.000000\n",
|
|
"47 0.000000 0.000000 0.000000\n",
|
|
"48 1.061634 0.000000 0.000000\n",
|
|
"49 0.000000 0.000000 0.000000\n",
|
|
"50 1.080351 0.000000 0.000000\n",
|
|
"Cluster all\n",
|
|
" t4 t5 t7\n",
|
|
"x \n",
|
|
"0 19.700148 18.546258 97.156117\n",
|
|
"1 15.942300 1.793886 0.020084\n",
|
|
"2 1.935968 14.486904 0.203083\n",
|
|
"3 1.666667 2.083333 0.443047\n",
|
|
"4 0.345462 2.401347 0.044810\n",
|
|
"5 0.000000 1.298701 0.167317\n",
|
|
"6 0.240148 0.446334 0.039865\n",
|
|
"7 0.000000 0.884956 0.000000\n",
|
|
"8 0.302454 0.041514 0.018718\n",
|
|
"9 0.000000 0.000000 0.000000\n",
|
|
"10 0.438648 0.009005 0.006319\n",
|
|
"11 0.000000 1.558074 0.121951\n",
|
|
"12 0.510128 0.059876 0.005273\n",
|
|
"13 0.000000 0.000000 0.000000\n",
|
|
"14 0.550489 0.088731 0.001569\n",
|
|
"15 0.000000 0.000000 0.300300\n",
|
|
"16 0.591507 0.009006 0.000884\n",
|
|
"17 0.000000 0.000000 0.000000\n",
|
|
"18 0.685781 0.000000 0.000472\n",
|
|
"19 0.000000 0.000000 0.416667\n",
|
|
"20 0.780825 0.000000 0.000000\n",
|
|
"21 0.000000 0.000000 0.000000\n",
|
|
"22 0.767510 0.000000 0.000000\n",
|
|
"23 0.000000 0.000000 0.000000\n",
|
|
"24 0.870496 0.000000 0.000000\n",
|
|
"25 0.000000 0.000000 0.000000\n",
|
|
"26 0.767858 0.000000 0.000000\n",
|
|
"27 0.000000 0.000000 0.751880\n",
|
|
"28 0.689920 0.000000 0.000000\n",
|
|
"29 0.000000 0.000000 0.000000\n",
|
|
"30 0.665122 0.000000 0.000000\n",
|
|
"31 0.000000 0.000000 0.000000\n",
|
|
"32 0.689776 0.000000 0.000000\n",
|
|
"33 0.000000 0.000000 0.000000\n",
|
|
"34 0.938967 0.000000 0.000000\n",
|
|
"35 0.000000 0.000000 0.000000\n",
|
|
"36 0.745282 0.000000 0.000000\n",
|
|
"37 0.000000 0.000000 0.000000\n",
|
|
"38 0.847693 0.000000 0.000000\n",
|
|
"39 0.000000 0.000000 0.000000\n",
|
|
"40 0.768979 0.000000 0.000000\n",
|
|
"41 0.000000 0.000000 0.000000\n",
|
|
"42 0.866218 0.000000 0.001087\n",
|
|
"43 0.000000 0.000000 0.000000\n",
|
|
"44 0.956106 0.000000 0.000000\n",
|
|
"45 0.000000 0.000000 0.000000\n",
|
|
"46 0.927086 0.000000 0.000000\n",
|
|
"47 0.000000 0.000000 0.000000\n",
|
|
"48 1.061634 0.000000 0.000000\n",
|
|
"49 0.000000 0.000000 0.000000\n",
|
|
"50 1.080351 0.000000 0.000000\n"
|
|
]
|
|
},
|
|
{
|
|
"data": {
|
|
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\n",
|
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"text/plain": [
|
|
"<Figure size 360x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
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"data": {
|
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"image/png": 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\n",
|
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"text/plain": [
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|
"<Figure size 360x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
},
|
|
{
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"data": {
|
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"image/png": 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\n",
|
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"text/plain": [
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"<Figure size 360x288 with 1 Axes>"
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]
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},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
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"output_type": "display_data"
|
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},
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{
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"data": {
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"image/png": 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\n",
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"text/plain": [
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"<Figure size 360x288 with 1 Axes>"
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]
|
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},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
},
|
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{
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"data": {
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"image/png": 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\n",
|
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"text/plain": [
|
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"<Figure size 360x288 with 1 Axes>"
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]
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},
|
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"metadata": {
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|
"needs_background": "light"
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},
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"output_type": "display_data"
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},
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{
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"data": {
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"image/png": 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\n",
|
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"text/plain": [
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|
"<Figure size 360x288 with 1 Axes>"
|
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]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
},
|
|
{
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"data": {
|
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"image/png": 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\n",
|
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"text/plain": [
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"<Figure size 360x288 with 1 Axes>"
|
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]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
},
|
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{
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"data": {
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"image/png": 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rkpZLOltSg6THJK0KH+tzvX6fafre5865CGQbNH8IHAhXbP8L4E2C/YJydRvwiJnNIdjZcjlwPfCEmR0LPBG+jowHTedcFLINmikzM+By4O/N7B+A6lwSlFQLvAe4E8DMOsLdLi8H7g5Pu5tge43IdG/j6wPcnXN5yDZo7pN0A8FQo19KigHJHNNsAbYBP5b0sqQ7JI0Hms1sU3jOZqC5rzdLulbSIkmLtm3blnWisbCmmfEedOdcHrINmlcB7QTjNTcDU4H/l2OaCeB04Idmdhqwn8Oa4mGt1vp6s5ndbmZzzWxuU1NT1ol689w5F4WsgmYYKO8HysND24EHc0xzPbDezJ4PX99HEES3SJoEED5uzfH6fVJZ2Dz3mqZzLg/ZTqP8DEFw++fw0BSCnSqHLAzA6yQdFx66EPg98BAwPzw2H/h5Ltfvj9c0nXNRyHac5nXAmcDzAGa2StJReaT7P4CfhbtcriYY8xkD7pF0DbAW+Gge1z+CB03nXBSyDZrtZtYhBTMnJSXo555jNsKdLOf28asLc73mYGJdg9u999w5l4dsO4J+LelrQKWki4F7gf8sXLai5zVN51wUsg2a1xMME3oN+CzwMMGsoFGja5ymDzlyzuUj2+Z5JfAjM/sXAEnx8NiBQmUsat01TW+eO+fykG1N8wmCINmlEng8+uwUTveMIG+eO+fykG3QrDCz1q4X4fNxhclSYfg9TedcFLINmvslnd71QtI7gYOFyVJhyHvPnXMRyPae5peAeyVtJFixfSLB1MpRo2vuuaW8I8g5l7usgqaZvShpDtA1i2eFmY2qKpu6F+wYVdl2zo0w2U6jvA4Yb2ZLzWwpUCXpzwubtWgpEYdYDOvwmqZzLnfZ3tP8TLjmJQBmtgv4TEFyVEBKJrwjyDmXl2yDZlxdcyjpHqc56jbaCXak9KDpnMtdth1BjwD/LqlrlaPPhsdGFSUT3nvunMtLtkHzqwSB8s/C148BdxQkRwUU85qmcy5P2faeZwg2V/thYbNTWEomfe65cy4vWQVNSW/Rx1JwZjYz8hwVkMqS3jx3zuUl2+Z577UvK4CPAA3RZ6ewlEz44HbnXF6y3SNoR6+fDWZ2K/CBwmYtet577pzLV7bN89N7vYwR1DyzraWOGN48d87lK9vAd3Ov5ylgDRHv4TMcYskk6bbWwU90zrl+ZNt7/geFzshw8Oa5cy5f2c49/6KkGgXukPSSpPcVOnNRUzJBxueeO+fykO00yk+b2V7gfcAE4BPAtwuWqwLxmqZzLl/ZBs2ueeeXAj8xs2W9jo0avmCHcy5f2QbNxZL+myBoPiqpGsgULluFoTKvaTrn8pNt7/k1wKnAajM7IGkC8KmC5apAgua539N0zuVuKHPPX+r1egewo1CZKhRfsMM5l69sm+djQtA8T2F2xDR655zLyoBBU1LLcGVkOPTsfe5NdOdcbgarad4HIOmJYchLwfne5865fA12TzMm6WvAbElfOfyXZnZLYbJVGD01TQ+azrncDFbTvBpIEwTX6j5+RpXumqYv2uGcy9GANU0zWwF8R9KrZvZfUSYcbs62CNhgZpeF908XEsw4Wgx8wsw6okwz5s1z51yesu09f0bSLZIWhT83S6rNM+0vAst7vf4O8D0zOwbYRTA2NFIqC4Kmb3nhnMtVtkHzR8A+guXgPgrsBX6ca6KSphIsYnxH+FrABYQdT8DdwBW5Xr/fdL2m6ZzLU7YzgmaZ2Yd6vf4bSUvySPdW4C/puS86AdhtZl1VwPXAlL7eKOla4FqAadOmDSlRH3LknMtXtjXNg5Le3fVC0rnAwVwSlHQZsNXMFufyfjO73czmmtncpqamoaVd5h1Bzrn8ZFvT/Bzwk173MXcB83NM81zgg5IuJdikrQa4DaiTlAhrm1OBDTlev1/ePHfO5SvbjdVeMbNTgJOBk83sNDN7NZcEzewGM5tqZjMIhjT9ysw+DjwJfDg8bT7w81yuPxDvPXfO5WtIc8/NbG+4GHEhfBX4iqQ3CO5x3hl1At33NL157pzLUVF3lDSzp4CnwuergTMLmV5X8zzjNU3nXI5Ka5Wj7ua5954753KTc9CUNDHKjAyH7t5zr2k653KUT00z8nuOhebjNJ1z+co5aJrZB6LMyHDwIUfOuXxl3REk6XTg3YABvzOzlwZ5y4gT88Htzrk8ZVXTlPRXBPPBJwCNwI8lfb2QGSuIeBwk7z13zuUs25rmx4FTzKwNQNK3gSXATQXKV0FICnek9KDpnMtNtvc0NxJMeexSTgGmOQ4HlSWwDu8Ics7lZsCapqQfENzD3AMsk/RY+Ppi4IXCZy96SnhN0zmXu8Ga54vCx8XAg72OP1WQ3AwDJRMeNJ1zORtsu4u7u55LKgNmhy9XmNmojDyxMq9pOudyl1VHkKTzCXrP1wACjpY038x+U7CcFYiSSTI+5Mg5l6Nse89vBt4XbrSGpNnAAuCdhcpYoSiZxFLeEeScy022vefJroAJYGYrgWRhslRYKkv64HbnXM6yrWkulnQH8NPw9cfp6SQaVYKOIK9pOudyM5TtLq4DvhC+fhr4x4LkqMCUTJLZf6DY2XDOjVKDBk1JceAVM5sD3FL4LBVWLJkk7b3nzrkcDXpP08zSwApJQ9svd4RSMuH3NJ1zOcu2eV5PMCPoBWB/10Ez+2BBclVASiZ9wQ7nXM6yDZr/p6C5GEYqS3pHkHMuZ4PNPa8g6AQ6BngNuDPcl3zUUtKHHDnncjfYPc27gbkEAfP9BIPcRzUlEz643TmXs8Ga58eb2UkAku5klK5s1Juvp+mcy8dgNc3u6DLam+VdYuGMIDMrdlacc6PQYDXNUyTtDZ8LqAxfCzAzqylo7gqge3O1VKr7uXPOZWuwpeHiw5WR4dKzI2UKPGg654Yon33PR6Xuvc+9B905l4MSDJq+97lzLnelFzTLwpqmB03nXA5KLmjGumqa3jx3zuVg2IOmpKMlPSnp95KWSfpieLxB0mOSVoWP9QVJv1fvuXPODVUxapop4C/M7HjgXcB1ko4HrgeeMLNjgSfC15FTWRA0fZ8g51wuhj1omtkmM3spfL4PWA5MAS4nmLZJ+HhFVGlmeg1k944g51w+inpPU9IM4DTgeaDZzDaFv9oMNPfznmslLZK0aNu2bYOm8cKanVx95/Ps3N8RvL9ryJGvdOScy0HRgqakKuB+4Etmtrf37yyY49jnPEczu93M5prZ3KampkHTaRhfxrpdB/jGI8sxM69pOufyUpSgKSlJEDB/ZmYPhIe3SJoU/n4SsDWKtGaV7eKfT13Di29s4qFXN/ngdudcXorRey7gTmC5mfXec+ghYH74fD7w80gSbN3Kifue5v3TjJufWMnWtgzgNU3nXG6KUdM8F/gEcIGkJeHPpcC3gYslrQIuCl/nr3oSAJ87bRwS3Pb0WwC+5YVzLifZbncRGTP7LcEqSX25MPIEq44CxahNb+erF5/D9+4LlgS1Du8Ics4N3ZifEaRYAsYfBfs28/4TJnLOcUGn/OadrUXOmXNuNBrzQROA6onQuglJfPF9xwPw6KvraetMFzljzrnRpkSC5iRo3YJl0tTVVAKwd99Bnlo1+DhP55zrrSSCpqomQSYFB7ajRHAbt9wyrNi8r8g5c86NNiURNLt60NkXNNFVlqSxPMbKrYfe17RNr2Bte4qQQefcaFEiQXNi8LgvmKWpRILGihgrt+7r3mDN2luxZ2/FVv5XsXLpnBsFSiJoqqwKymuwrqCZTNJQFmPXgU62twZz0tkdjN9k1+oi5dI5NxqURNAEws6gzUCwPFxduKfaiq3hfc1dYdDcvRbL+BhO51zfSidoVk3saZ4nE1SHJV8V3te0rqCZ7oC9G4uRQ+fcKFAyQVPVk6CjFWvfRyyZJGEZptRWsHJLV01zDTTMCp+/VbR8OudGtpIJmr07g1SWxDo6md1czYqtrdjBXdC2G009E8rGY35f0znXjxIKmuGwo9bNKJkk09nJ7KOqWLfzAB3b3gx+V98C9TO9pumc61fpBM1xjRBLYPs2oWQS6wxqmgbs3rgSFIPaaUHg3LMeS7UXO8fOuRGoZIKmFOvuDFIygXWmmH1UFQCZXW9BzRSUKEf1MwGD3WuLm2Hn3IhUMkETCJroXTXNjk4m1lRQXR6n5uB6qJsRnFPfEjz6fU3nXB9KL2ju34YScayzE0mcMzFDJW0oDJaqqIFxjdhOD5rOuSOVVNBU9UTAUCzdvd3Fu+qCPd0ydS09J9a3eGeQc65PJRU0qQp60EUHmXBjtTnlO2jPxFiXru8+TfUtcGA71ra3z8s450pXaQXNcKxmzDq69z2flNnMqvZ6Vm5v6zmvYWbw6LVN59xhSipoKlEBlQ1gbViqE7MMlfvX8Xp7Y8/MIIC66YB8kLtz7gglFTQBqJ6E0geCjdX2bULpdnYkJx+ytqYSFVAzxWuazrkjlGbQzBzAOjuxneF2vrUzWLn1sFXc61tg1+ru9Tadcw5KMGiqahIxpcAM27Ea4uXUN09je2sHO/b3zAJSw0zo2A/7fR8h51yPkguaVE9E8WDbddu2GupnMHtiDdCzTBwQzEEHH+TunDtECQbNSSgePM3sWgf1Mzj2qGqAQ/cMqpkM8bKedTadc45SDJoVdSgZLNtunSlU10JtZZKJNRWH9KArlgh60T1oOud6KbmgKQmNrwPA0tY91/zYo6qO2J2S+hbf/sI5d4iSC5oAqgpm/5gqYXwTAMcdVcWaHftp60z3nFc/07e/cM4dIlHsDBRDrGoCADZ+MlLQKTS7uZqMwZvb93PCpKBjiIZwPvr217F4Eg5shwM7sAM7UNl4mHYuKq8uRhGcc0VSkkFTNUHt0sZN7D42uzkIfv/89GpOnlJLU1U5TVVlnJEYT/zVBcCCXheIYZaBZfdjU9+FZl3QvUqSc25sK82gWT85eFI9vfvY5NoKzp01gaUb9/LM6h3dx98zfi4n17Qyp2UGpx93DMnqJqiog9bN2OpfwdrfYW//FqufiWb+AUw+HSXHDVtZrH0f9vsHYM86NPtSmHRad+3ZOdejI5UhY0ZFMp7XdUZU0JR0CXAbEAfuMLNvFyKdWFUjADZ+Us8xids+cioA7ak021s72NbazqY9J3D/y+v5+2f20Lx0O58+u4oPnlxPsmYKOvUT2Akfgrefwd58Alt8J7x0F9Z8Ipr8Tph8GioLVoe39r3BvdG9G7AD21HDLGg+CSXKcyqDWQZWPxUEzFQbVNZjz/0Amo6Hk69GtUfn9yHloTOdYfPeNqbUVRIbIIDva+tk8du7mVRbweyjqvoN9umMsXzzXto6M5wytZZkvO9b8R2pDM+v2cnrm/dyxvQGTp5a22/6+9tTvLJhDxNrymmZMB5JWCrNwddXEausoHzm9O787D7QQWfaaKoe+N8qnTF27u+gsapswP+4zIwNe9poGJdkXFn/f4JvbGvlkWWbaetMc/E7mjl5Sm2/192xv523tu/nHRNrGF/e/zXX7jzAM29uZ3JdJe9qaaA80XcA6fnM05wyta7fz7wz3fWZ7+OM6fWcNKXvz7wjleHpN7bz1KptTK2r5AMnTmRqfd+VizU79gflTmW4aM5RnDCp5ohymxmvbdzL/S+v55X1e3jvsU388WlTmN5w5DU37TnIA0s28vNXNvDJs2fwsTOm9fv5ZEMjZZqgpDiwErgYWA+8CMwzs9/39565c+faokWLhpzWgWUreOvPvsq073ydqjNOI93aSnpvK+k9+0jt3k1q5x5SO3eR2rWb1M7dxCor2FrdwKO7xfNtZWjSRD5w+jSm11cyeVycieVifLoddr2Ndi2HHa+RSO+CeJz9FZOp6NxNItWrZ14xsAwWS7K//h1sHHc8K2KzKK+oYmJNBRNrKmisLiMRi2FmbNnXzurt+3lzWyurt+9ncmodV+gpJqQ2c7DmWMpOuAqNa+TA2t9S/tYviafbeJ6T+Ne9p9PYMIE5zdXMmVjNcc3VVFckaW1PsXzTXpaFPyu27KVhfDknTyjnxLIUs2Id1B/ch8VibEqOZ3lnkpf2x1iyZT8d6QwnTa7h5Cl1nDyllhMm1VCejLFySysvrt3JC2t28vL63bR1Zmgsg/dWZTg9foCZbXuo3L2TA1U1rCqr4bn2cn69P8mBeDD8q7m6nHcf08h5sxqZO72eznSGZ9/ayW/f2M4zq3ew+2CwlN/4sjhnzmjgvGMaOWfmBGoqkjy/ZiePLd/Cb97YTmt7z0iHpqpyLjiuiYvnNHPy1Fo27D7I029s57dv7uDldbvoTBs17Qd4T+tGzt23gUlr3kAHDgCQqa9nY8uxPFc7lccSTbQly5jWMI4zp9dz5owG3jmtnuqKBG9sbWXR27tYtHYXL6/bzb72FE1V5bxzWh1zp9czd1o9U+oq2bqvnRfX7uKFNTt5Ye1Otrd2EI+JkybXcOaMBs6c3sCJk2vYeaCDR3+/hf9atpmVW1uJx0QiJtpTGabUVfL+45u55ISJHF0/jqUb9/DM6h08s3oHyzcHw+USMXHq1DrOmTWBc2ZOYFbjeN7ctp8nVmzlVyu38ua2/d2fz7iyOOfOmsCFxx3FuTMbSWUyPPfWTp7u5zN/96xGzp3V85k//voWfr3q0M/8qOpyLpjdxEVzmjlpSi1LN+7h4WWbeWz5Fva2paitSLC3LYUBp0yt5QMnTuKiOUfR3pnh0eVbeGTZZl7fso+YIB4TnWljWn0lf3j8RN5/wkQaxpfxyLLN3P/yBlZta2VcWZwTJ9WweN1u0hnjjOn1fOi0KbznmCYWvb2Le19az+/e3A7Au2c18omzpnHa0T3LQPZH0mIzm9vn70ZQ0DwbuNHM/jB8fQOAmX2rv/fkGjQPrlrN6mu+0r2Vb3/itdUk6mpJHzhIaltPk92AtniS8nTngMMP0vEYsaRIK0anYnQqToeSZGJxknQyjk4q1UkcwwwyhP+bSpiCxyDBnn8jAfFMhlQndHSIZDp9SJopxSApKsoMJcAkzMLH8ArCEASPApmROmBk2gf+LmhcnFhFLLgeFubmSDEJ0hnSew4bqjU+DgfTkOk5FK9OoLLgP4dMP8nHpCCfQMYg0893NiYRUzCsLGNGxoy+TlV4jjJGalf47z8uTmxaJfFplVhnhszag2TWH4QOgxgk6srI0Pf1gotCjCCfNkAee5fHCGpM/eUxKE/wGQ9WnpgUfD5ZXtMwMpmBP8vsPvOec7vO6+vUmEQsFnz7BipPtuU+/Lyuc9N9fIliMREPz2u49Gwm/OmX+izLodfvP2iOpOb5FGBdr9frgbMOP0nStcC1ANOm5VbNrmiZxoSPfhDLZIjXVBOvriJeU0W8uopEfR2JhjoS9bUo0fPxpA8cpGPdRjrWbaD97Q20721lvxLsIc7uTIztqRgHM1CjNDWkqbIU49KdlKU6SXek6OjopKO9k86OFKnOFOlEDMoSZMrijI+1U5HaC+lOUukMmXSadDpDJp1BCmoaiXiMRFzEYkLl40lPmEFGSXZmYmzvFAczRnO5aEoYdXEj3rqbzK6NYBnS6TSdqTSp8LqxeIxEPEEyEScWjwNifFU5idoKOsfHaSsXbUkjhjG+PUPFwTS2r53U7jbSB4NAaGZ0pjN0pjNkMkYyEaMsHiMWC76ciouyxnGUN40n01DBvsoE+9IZqpJxatvTaGcbHVv307FtP5lwmJdZ0NxrT2WQoDweJxnXkbHZIJUx2sN7VGWJGOXxWJ8x3AzaUxk6UxnicVGeiBGPdZ0oKs6qpmrOBJITq9h9MMWO/e3EJJreW0ZtWZz2dXtpfX07HTsOdKfdmTY6epU7GY9xROs1zGPwGRmJuCiLx0jEjiyPWdB87UhniElUJHvn8VCZDLR1pkmbkYzHKE/EUB+nZjJBuVPpDIm4KE/EifX1P7xBR9poT6WH9JmXJ+KUJYL/eo/8zK37M0/GY5Qn+85j1zXbOtNIoiIRIx4fvNwVyTjJPj7HnvIE36FkPEZF4tDvRaKuoc/rD8VICppZMbPbgdshqGnmcg0lEkz8/KeH9J74uEoqj5tF5XGzckmy5OX/VS28pvCntyRQVYS8uJFrJA1u3wD07r2YGh5zzrkRYyQFzReBYyW1SCoDrgYeKnKenHPuECOmeW5mKUmfBx4lGHL0IzNbVuRsOefcIUZM0AQws4eBh4udD+ec689Iap4759yI50HTOeeGwIOmc84NgQdN55wbghEzjTIXkrYBa7M4tRHYXuDseDqeznCl4ekUPp3pZnb4XAdglAfNbEla1N88Uk/H0xltaXg6xU3Hm+fOOTcEHjSdc24ISiVo3u7peDrDlM5YKoun04eSuKfpnHNRKZWapnPORcKDpnPODcGYD5qSLpG0QtIbkq4vYDprJL0maYmkoe/B0f91fyRpq6SlvY41SHpM0qrwcfBNT3JL50ZJG8IyLZF0aZ5pHC3pSUm/l7RM0hcLUZ4B0om6PBWSXpD0SpjO34THWyQ9H37n/j1c6rAQ6dwl6a1e5Tk1n3TCa8YlvSzpF4UoywDpFKIsR/xNRvJdC/YTGZs/BEvMvQnMBMqAV4DjC5TWGqCxANd9D3A6sLTXsb8Drg+fXw98p0Dp3Aj8zwjLMgk4PXxeTbCR3vFRl2eAdKIuj4Cq8HkSeB54F3APcHV4/J+APytQOncBH474+/YV4N+AX4SvIy3LAOkUoixH/E1G8V0b6zXNM4E3zGy1mXUAC4HLi5ynITGz3wA7Dzt8OXB3+Pxu4IoCpRMpM9tkZi+Fz/cBywn2hoq0PAOkEykLdG0zmgx/DLgAuC88HkV5+ksnUpKmAh8A7ghfi4jL0lc6wyzv79pYD5p9bdYW+R9PyID/lrQ43PytkJrNbFP4fDPQXMC0Pi/p1bD5nvdtgC6SZgCnEdSaClaew9KBiMsTNjOXAFuBxwhaNrvNrGsrzki+c4enY2Zd5flGWJ7vSRp4Y/bB3Qr8JT37hU6gAGXpI50uUZYF+v6bzPu7NtaD5nB6t5mdDrwfuE7Se4YjUQvaGYUaN/ZDYBZwKrAJuDmKi0qqAu4HvmRme3v/Lsry9JFO5OUxs7SZnUqwp9WZwJx8r5lNOpJOBG4I0zuDYO+6r+Z6fUmXAVvNbHEE2c0lncjK0suAf5O5ftfGetActs3azGxD+LgVeJDgD6hQtkiaBBA+bi1EIma2JfxjzQD/QgRlkpQkCGQ/M7MHwsORl6evdApRni5mtht4EjgbqJPUtStCpN+5XulcEt6GMDNrB35MfuU5F/igpDUEt7EuAG4j+rIckY6kn0ZcFqDfv8m8v2tjPWgOy2ZtksZLqu56DrwPWDrwu/LyEDA/fD4f+HkhEun6coWuJM8yhffI7gSWm9ktvX4VaXn6S6cA5WmSVBc+rwQuJrh/+iTw4fC0KMrTVzqv9/rjF8G9uZzLY2Y3mNlUM5tB8HfyKzP7OBGXpZ90/iTKsoTX6e9vMv/vWpS9VSPxB7iUoPf0TeB/FyiNmQQ9868Ay6JMB1hA0JTsJLindA3BvaYngFXA40BDgdL5V+A14NXwyzYpzzTeTdAcehVYEv5cGnV5Bkgn6vKcDLwcXm8p8Fe9vg8vAG8A9wLlBUrnV2F5lgI/Jexhj+C7cD49vdqRlmWAdCItS39/k1F813wapXPODcFYb54751ykPGg659wQeNB0zrkh8KDpnHND4EHTOeeGwIOmKwpJ6V4r2ixRxCtQSTpf0jlRXnMIac+Q9LFipO0KLzH4Kc4VxEELpgUWyvlAK/BMAdPozwzgYwSr+LgxxmuabsRQsPbpvb1en99rvcX3SXpW0kuS7g3nlXetmfg34fHXJM0JF+n4HPDlsBZ73mHpVEn6cXj+q5I+FB6fFx5bKuk7vc5v7fX8w5LuCp/fJen7kp6RtFpS18yZbwPnhWl/uRCflSseD5quWCoPa55fRTBD46xw2hvAVcBCSY3A14GLLFiAYRHBeoxdtofHf0iwXuYagrUfv2dmp5rZ04el/X+APWZ2kpmdDPxK0mTgOwRzrk8FzpB0RRblmEQwA+kygmAJwTqNT4dpfy/rT8SNCt48d8XSZ/Nc0iPAH0m6j2DNxb8E3kuwiPDvgqnJlAHP9npb18Ifi4E/ziLtiwjmPQNgZrvCFXCeMrNtYT5+RrAw838Mcq3/sGABkN9LKuQSfW6E8KDpRpqFwOcJFkReZGb7wkUcHjOzef28pz18TFOY73TvucYV/aQNwQrrbozz5rkbaX5NsO3GZwgCKMBzwLmSjoHuFWxmD3KdfQRbXfTlMeC6rhfhYsQvAO+V1CgpDswL8wLBcmLvkBQjWB1pMAOl7UY5D5quWA6/p/ltCBbbBX5BsHDsL8Jj24BPAgskvUrQNB9ssd//BK7sqyMIuAmoDzt8XgH+wILVvK8nWArtFWCxmXUtG3Z9mJdnCFaCGsyrQFrBRmjeETTG+CpHzjk3BF7TdM65IfCg6ZxzQ+BB0znnhsCDpnPODYEHTeecGwIPms45NwQeNJ1zbgj+P+OJdsWX/JGVAAAAAElFTkSuQmCC\n",
|
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"text/plain": [
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"<Figure size 360x288 with 1 Axes>"
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]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
},
|
|
{
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"data": {
|
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"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 360x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"def figure_5_plot(df, cluster):\n",
|
|
" dft = {}\n",
|
|
" _, ax = plt.subplots(figsize=(5,4))\n",
|
|
" colors = plt.cm.Spectral([0.9, 0.3, 0.8, 0.1])\n",
|
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" \n",
|
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" pds = {}\n",
|
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"\n",
|
|
" for i in [4,5,7]:\n",
|
|
" dft[i] = df[[\"count_\" + str(i), \"succ\", \"non\"]].copy()\n",
|
|
" dft[i] = dft[i].groupby(\"count_\" + str(i)).sum().reset_index()\n",
|
|
" \n",
|
|
" over = dft[i][dft[i][\"count_\" + str(i)] > max_count].sum()\n",
|
|
" if over[\"succ\"] == 0 and over[\"non\"] == 0:\n",
|
|
" percover = 0\n",
|
|
" else:\n",
|
|
" percover = over[\"succ\"] / (over[\"succ\"] + over[\"non\"])\n",
|
|
" \n",
|
|
" dft[i][\"perc\"] = dft[i][\"succ\"] / (dft[i][\"succ\"] + dft[i][\"non\"])\n",
|
|
" dfi = dft[i]\n",
|
|
" dft[i].loc[dfi[\"succ\"].eq(0) & dfi[\"non\"].eq(0), [\"perc\"]] = 0\n",
|
|
" \n",
|
|
" dft[i] = dft[i].drop(dft[i][dft[i][\"count_\" + str(i)] > max_count].index)\n",
|
|
" #dft[i][\"count_\" + str(i)] = dft[i][\"count_\" + str(i)].astype(str)\n",
|
|
" dft[i] = dft[i].append({\"count_\" + str(i): max_count + 1, \"perc\": percover}, ignore_index=True)\n",
|
|
"\n",
|
|
" del dft[i][\"succ\"]\n",
|
|
" del dft[i][\"non\"]\n",
|
|
" plt.xticks([0,5,10,15,20,25,30,35,40,45,50])\n",
|
|
" \n",
|
|
" ys = []\n",
|
|
" for j in range(0, max_count + 2):\n",
|
|
" a = dft[i][dft[i][\"count_\" + str(i)] == j]\n",
|
|
" ys.append(0 if a.empty else a[\"perc\"].squeeze() * 100)\n",
|
|
" \n",
|
|
" pds[\"t\" + str(i)] = ys[:-1]\n",
|
|
" \n",
|
|
" plt.plot([x for x in range(0,51)], ys[:-1], color=colors[i-4])\n",
|
|
" \n",
|
|
" if cluster == \"all\":\n",
|
|
" plt.title(\"2019 data\")\n",
|
|
" elif cluster == \"2011\":\n",
|
|
" plt.title(\"2011 data\")\n",
|
|
" else:\n",
|
|
" plt.title(\"Cluster \" + cluster.upper())\n",
|
|
" \n",
|
|
" print(\"Cluster \" + cluster)\n",
|
|
" \n",
|
|
" print(pd.DataFrame({\"x\": [x for x in range(0,51)], \"t4\": pds[\"t4\"], \"t5\": pds[\"t5\"], \"t7\": pds[\"t7\"]}).set_index(\"x\"))\n",
|
|
" \n",
|
|
" lgd = plt.legend([\"EVICT\", \"FAIL\", \"KILL\"])\n",
|
|
" plt.xlabel(\"Event count\")\n",
|
|
" plt.xlim([-2,52])\n",
|
|
" plt.ylim([-5,105])\n",
|
|
" plt.ylabel(\"Prob. of success [%]\")\n",
|
|
" plt.savefig('../report/figures/figure_5/figure-5-%s.pgf' % cluster, \n",
|
|
" bbox_extra_artists=(lgd,), bbox_inches='tight')\n",
|
|
"\n",
|
|
"dftot = None\n",
|
|
"for cluster in \"abcdefgh\":\n",
|
|
" df = pd.read_csv(glob.glob(DIR + \"fig-5-\" + cluster + \".csv/part-00000-*\")[0], \n",
|
|
" names=[\"count_4\", \"count_5\", \"count_7\", \"count_8\", \"succ\", \"non\"])\n",
|
|
" figure_5_plot(df, cluster)\n",
|
|
" if dftot is None:\n",
|
|
" dftot = df\n",
|
|
" else:\n",
|
|
" dftot = dftot.append(df)\n",
|
|
" \n",
|
|
"dftot = dftot.groupby([\"count_4\", \"count_5\", \"count_7\", \"count_8\"]).sum().reset_index()\n",
|
|
"figure_5_plot(df, \"all\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 44,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 360x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"EVICT2011 = [70,41,35,30,26,23,22,21,20,19,18,17,16,15,\n",
|
|
" 14,13,12,11,10,9,8,7,6,5,4,3,2,1,0,0]\n",
|
|
"KILL2011 = [70, 1,34,18,17,15,15,16,14,14,12, 8, 0, 0,\n",
|
|
" 0, 0, 0, 0, 0,0,0,0,0,0,0,0,0,0,0,0]\n",
|
|
"FAIL2011 = [70,17, 5, 2, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
|
|
" 0, 0, 0, 0, 0,0,0,0,0,0,0,0,0,0,0,0]\n",
|
|
"\n",
|
|
"dft = {}\n",
|
|
"_, ax = plt.subplots(figsize=(5,4))\n",
|
|
"colors = plt.cm.Spectral([0.9, 0.3, 0.8, 0.1])\n",
|
|
"for i,S in [(4,EVICT2011),(5,FAIL2011),(7,KILL2011)]:\n",
|
|
" plt.xticks([0,5,10,15,20,25,30,35,40,45,50])\n",
|
|
" plt.plot([x for x in range(0,len(S))], S, color=colors[i-4])\n",
|
|
" plt.title(\"2011 data\")\n",
|
|
"lgd = plt.legend([\"EVICT\", \"FAIL\", \"KILL\"])\n",
|
|
"plt.xlabel(\"Event count\")\n",
|
|
"plt.xlim([-2,52])\n",
|
|
"plt.ylim([-3,103])\n",
|
|
"plt.ylabel(\"Prob. of success [%]\")\n",
|
|
"plt.savefig('../report/figures/figure_5/figure-5-2011.pgf', \n",
|
|
" bbox_extra_artists=(lgd,), bbox_inches='tight')\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.8.3"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|