bachelorThesis/figure_9/figure_9.ipynb

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{
"cells": [
{
"cell_type": "code",
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"execution_count": 1,
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"id": "3f392515",
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"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import sys\n",
"import glob\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"import matplotlib as mpl\n",
"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
"import itertools"
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]
},
{
"cell_type": "code",
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"execution_count": 2,
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"id": "c6d18e78",
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"metadata": {},
"outputs": [],
"source": [
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"DIR = \"/home/claudio/hdd/git/bachelorThesis/figure_9/\""
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]
},
{
"cell_type": "code",
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"execution_count": 3,
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"id": "8330c5bd",
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"metadata": {},
"outputs": [],
"source": [
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"LABELS = {\"task_count\": \"Number of tasks\", \n",
" \"interval\": \"Job execution time\",\n",
" \"machine_locality\": \"Machine locality\"}\n",
"\n",
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"def categorical_plot(df, key, title, sorted_xs = None):\n",
" if sorted_xs == None:\n",
" xs = set()\n",
" lines = []\n",
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" for t in [4,5,6,7]:\n",
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" xs = xs.union(np.array(df[df.term == t][key]).reshape(-1))\n",
" xs = [str(x) for x in sorted(xs)]\n",
" else:\n",
" xs = sorted_xs\n",
" \n",
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" plt.figure(figsize=(4,3))\n",
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" ax = plt.gca()\n",
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" plt.xlabel(LABELS[key])\n",
" plt.ylabel(\"Event rate [%]\")\n",
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" lines = []\n",
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" for t in [4,5,6,7]:\n",
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" ys = []\n",
" for x in xs:\n",
" partsum = df[(df.term != -1) & (df[key] == x)][\"count\"].sum().astype(int)\n",
" y = df[(df.term == t) & (df[key] == x)][\"count\"]\n",
" ys.append((y.values.astype(int)[0] / partsum if partsum > 0 else y.values.astype(int)[0]) if y.any() else 0)\n",
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" ys[-1] *= 100\n",
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" lines.append(ax.plot(xs,ys, marker='.')[0])\n",
"\n",
" plt.xticks(xs)\n",
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" plt.yticks([0,20,40,60,80,100])\n",
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" lgd = plt.legend(lines, [\"EVICT\", \"FAIL\", \"FINISH\", \"KILL\"],\n",
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" bbox_to_anchor=(1,1))\n",
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" 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",
" plt.savefig('../report/figures/figure_9/%s-%s.pgf' % \n",
" (key.replace(\"_\", \"\"), cluster), bbox_extra_artists=(lgd,), bbox_inches='tight')\n",
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" plt.show()"
]
},
{
"cell_type": "code",
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"execution_count": 4,
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"id": "35d8f9f0-5233-4437-ab97-061d720f6f0a",
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"metadata": {},
"outputs": [
{
"data": {
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"image/png": "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"text/plain": [
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"<Figure size 288x216 with 1 Axes>"
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]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"image/png": "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"text/plain": [
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"<Figure size 288x216 with 1 Axes>"
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]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
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"<Figure size 288x216 with 1 Axes>"
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]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"image/png": "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"text/plain": [
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"<Figure size 288x216 with 1 Axes>"
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]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
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"<Figure size 288x216 with 1 Axes>"
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]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"image/png": "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"text/plain": [
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"<Figure size 288x216 with 1 Axes>"
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]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
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"<Figure size 288x216 with 1 Axes>"
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]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
2021-05-22 14:31:35 +00:00
"image/png": "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"text/plain": [
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"<Figure size 288x216 with 1 Axes>"
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]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"image/png": "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"text/plain": [
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"<Figure size 288x216 with 1 Axes>"
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]
},
"metadata": {
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},
"output_type": "display_data"
},
{
"data": {
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"image/png": "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"text/plain": [
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"<Figure size 288x216 with 1 Axes>"
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]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
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"<Figure size 288x216 with 1 Axes>"
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]
},
"metadata": {
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},
"output_type": "display_data"
},
{
"data": {
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"image/png": "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"text/plain": [
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"<Figure size 288x216 with 1 Axes>"
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]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
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"<Figure size 288x216 with 1 Axes>"
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]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
2021-05-22 14:31:35 +00:00
"image/png": "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"text/plain": [
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"<Figure size 288x216 with 1 Axes>"
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]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
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"<Figure size 288x216 with 1 Axes>"
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]
},
"metadata": {
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},
"output_type": "display_data"
},
{
"data": {
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"image/png": "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"text/plain": [
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"<Figure size 288x216 with 1 Axes>"
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]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
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"<Figure size 288x216 with 1 Axes>"
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]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"image/png": "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"text/plain": [
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"<Figure size 288x216 with 1 Axes>"
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]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
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"<Figure size 288x216 with 1 Axes>"
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]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"image/png": "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"text/plain": [
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"<Figure size 288x216 with 1 Axes>"
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]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
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"<Figure size 288x216 with 1 Axes>"
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]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"image/png": "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"text/plain": [
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"<Figure size 288x216 with 1 Axes>"
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]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"image/png": "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"text/plain": [
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"<Figure size 288x216 with 1 Axes>"
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]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"image/png": "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"text/plain": [
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"<Figure size 288x216 with 1 Axes>"
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]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"def to_9a_bin(col):\n",
" # 1 [2,10] [11,50] [51,100] 101+\n",
" if col <= 0:\n",
" return \"None known\"\n",
" elif col == 1:\n",
" return \"1\"\n",
" elif col <= 10:\n",
" return \"2-10\"\n",
" elif col <= 50:\n",
" return \"11-50\"\n",
" elif col <= 100:\n",
" return \"51-100\"\n",
" else:\n",
" return \"101+\"\n",
" \n",
"def to_9c_bin(col):\n",
" # 1 [2,10] [11,50] [51,100] 101+\n",
" if col <= 0:\n",
" return \"Unknown\"\n",
" elif col < 0.5:\n",
" return \"(0,0.5)\"\n",
" elif col < 0.9:\n",
" return \"[0.5,0.9)\"\n",
" elif col < 1.1:\n",
" return \"[0.9,1.1)\"\n",
" elif col < 1.5:\n",
" return \"[1.1,1.5)\"\n",
" else:\n",
" return \">=1.5\"\n",
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" \n",
"dfatot = None\n",
"dfbtot = None\n",
"dfctot = None\n",
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"\n",
"for cluster in \"abcdefgh\":\n",
" dfa = pd.read_csv(DIR + cluster + \"_term_task_count.csv\") \\\n",
" .sort_values([\"term\", \"task_count\"])\n",
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" dfa = dfa[dfa[\"task_count\"] > 0]\n",
" dfa = dfa[dfa[\"term\"].isin(range(4,8))]\n",
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" dfa[\"task_count\"] = dfa[\"task_count\"].apply(to_9a_bin)\n",
" dfa = dfa.groupby([\"term\", \"task_count\"]).sum().reset_index()\n",
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" if dfatot is None:\n",
" dfatot = dfa\n",
" else:\n",
" dfatot = dfatot.append(dfa)\n",
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" \n",
" categorical_plot(dfa, \"task_count\", \"# of tasks w.r.t. job rate (cluster \" + \n",
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" cluster + \")\", [to_9a_bin(x) for x in [1,10,50,100,101]])\n",
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" \n",
" # column should be called machine_count here, typo in analysis scripts\n",
" dfb = pd.read_csv(DIR + cluster + \"_priority_exectime/part-00000\", header=None,\n",
" names=[\"term\", \"priority\", \"interval\", \"count\"]).sort_values([\"term\", \"interval\"])\n",
" del dfb[\"priority\"]\n",
" dfb = dfb.groupby([\"term\", \"interval\"]).sum().reset_index()\n",
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" dfb = dfb[dfb[\"term\"].isin(range(4,8))]\n",
" if dfbtot is None:\n",
" dfbtot = dfb\n",
" else:\n",
" dfbtot = dfbtot.append(dfb)\n",
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" \n",
" xs = [\"<1\", \"1-2\", \"2-4\", \"4-10\", \"10-60\", \"60-1d\", \">=1d\"]\n",
" categorical_plot(dfb, \"interval\", \"Job execution time (in mins) w.r.t. job rate (cluster \" + \n",
" cluster + \")\", xs)\n",
" \n",
" dfc = pd.read_csv(DIR + cluster + \"_term_machine_locality.csv\") \\\n",
" .sort_values([\"term\", \"machine_locality\"])\n",
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" dfc= dfc[dfc[\"machine_locality\"] > 0]\n",
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" dfc[\"machine_locality\"] = dfc[\"machine_locality\"].apply(to_9c_bin)\n",
" dfc = dfc.groupby([\"term\", \"machine_locality\"]).sum().reset_index()\n",
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" dfc = dfc[dfc[\"term\"].isin(range(4,8))]\n",
" if dfctot is None:\n",
" dfctot = dfc\n",
" else:\n",
" dfctot = dfctot.append(dfc)\n",
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" \n",
" categorical_plot(dfc, \"machine_locality\", \"Machine locality w.r.t. job rate (cluster \" + \n",
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" cluster + \")\", [to_9c_bin(x) for x in [0.49,0.89,1.09,1.49,1.5]]) "
]
},
{
"cell_type": "code",
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"execution_count": 5,
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"id": "cc72331b-f5e6-4519-85ea-03c149b2abb9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" term task_count count\n",
"0 4 1 2686\n",
"1 5 1 375924\n",
"2 5 101+ 30652\n",
"3 5 11-50 25790\n",
"4 5 2-10 32493\n",
"5 5 51-100 5781\n",
"6 6 1 8746326\n",
"7 6 101+ 41178\n",
"8 6 11-50 121019\n",
"9 6 2-10 493786\n",
"10 6 51-100 45858\n",
"11 7 1 7004985\n",
"12 7 101+ 865662\n",
"13 7 11-50 677346\n",
"14 7 2-10 1824913\n",
"15 7 51-100 272201\n",
" term interval count\n",
"0 4 1-2 1272\n",
"1 4 10-60 3849\n",
"2 4 2-4 1012\n",
"3 4 4-10 1381\n",
"4 4 60-1d 670\n",
"5 4 <1 3401\n",
"6 4 >=1d 16\n",
"7 5 1-2 212983\n",
"8 5 10-60 556418\n",
"9 5 2-4 139020\n",
"10 5 4-10 156903\n",
"11 5 60-1d 678146\n",
"12 5 <1 303335\n",
"13 5 >=1d 36972\n",
"14 6 1-2 6186670\n",
"15 6 10-60 7480361\n",
"16 6 2-4 4988230\n",
"17 6 4-10 7181336\n",
"18 6 60-1d 1916021\n",
"19 6 <1 15420868\n",
"20 6 >=1d 168715\n",
"21 7 1-2 6915345\n",
"22 7 10-60 9405950\n",
"23 7 2-4 5424771\n",
"24 7 4-10 5125738\n",
"25 7 60-1d 3462416\n",
"26 7 <1 21817580\n",
"27 7 >=1d 522971\n",
" term machine_locality count\n",
"0 4 >=1.5 1\n",
"1 4 [0.9,1.1) 2685\n",
"2 5 (0,0.5) 3575\n",
"3 5 >=1.5 72202\n",
"4 5 [0.5,0.9) 3783\n",
"5 5 [0.9,1.1) 376132\n",
"6 5 [1.1,1.5) 13165\n",
"7 6 (0,0.5) 841\n",
"8 6 >=1.5 295788\n",
"9 6 [0.5,0.9) 5993\n",
"10 6 [0.9,1.1) 9118378\n",
"11 6 [1.1,1.5) 26942\n",
"12 7 (0,0.5) 35176\n",
"13 7 >=1.5 988339\n",
"14 7 [0.5,0.9) 110383\n",
"15 7 [0.9,1.1) 8649436\n",
"16 7 [1.1,1.5) 271514\n"
]
},
{
"data": {
2021-05-22 14:31:35 +00:00
"image/png": "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
2021-05-22 14:18:14 +00:00
"text/plain": [
"<Figure size 288x216 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
2021-05-22 14:31:35 +00:00
"image/png": "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
2021-05-22 14:18:14 +00:00
"text/plain": [
"<Figure size 288x216 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
2021-05-22 14:31:35 +00:00
"image/png": "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"text/plain": [
"<Figure size 288x216 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"cluster = \"all\"\n",
"\n",
"dfatot = dfatot.groupby([\"term\", \"task_count\"]).sum().reset_index()\n",
"dfbtot = dfbtot.groupby([\"term\", \"interval\"]).sum().reset_index()\n",
"dfctot = dfctot.groupby([\"term\", \"machine_locality\"]).sum().reset_index()\n",
"\n",
"print(dfatot)\n",
"print(dfbtot)\n",
"print(dfctot)\n",
"\n",
"categorical_plot(dfatot, \"task_count\", None, [to_9a_bin(x) for x in [1,10,50,100,101]])\n",
"\n",
"xs = [\"<1\", \"1-2\", \"2-4\", \"4-10\", \"10-60\", \"60-1d\", \">=1d\"]\n",
"categorical_plot(dfbtot, \"interval\", None, xs)\n",
"\n",
"categorical_plot(dfctot, \"machine_locality\", None, [to_9c_bin(x) for x in [0.49,0.89,1.09,1.49,1.5]]) "
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]
},
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{
"cell_type": "code",
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"execution_count": 6,
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"id": "68db43ac-04d1-4b0b-a6e1-39c7799cd074",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAV8AAADgCAYAAACkXmWVAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/Z1A+gAAAACXBIWXMAAAsTAAALEwEAmpwYAAA4eUlEQVR4nO3dd3yV1f3A8c/3jkwgEBKSsAwyRCABJFC02jpad10427qqOFFbceBqrVbFqnVbf6i4aq2KVhFR3HZYgTDDBlFUIIswM+/4/v54bkKAjAu5NzcJ3/frdV+5zzrP94Gbb849z3nOEVXFGGNM63LFOgBjjNkfWfI1xpgYsORrjDExYMnXGGNiwJKvMcbEgCVfY4yJAUu+ps0SkYtE5D+xjsOYaLDku58TkXgReU5E1onIdhFZKCIn7LbPMSKyQkQqROQzETmg3razReTL0LbPGyh/ioisFJGgiFwUxeu4U0T+Fq3yjYk0S77GA3wP/BRIAW4HXheRbAARSQPeAu4AUoF84LV6x5cBjwCTGyl/EXAVMD/yoRvTflny3c+parmq3qmq36pqUFVnAN8Ao0K7nAEsVdU3VLUKuBMYLiKDQ8d/rKqvAxsaKf9JVf0EqGouFhHpLiLTRWSbiMwB+u+2/VER+T60fZ6IHBFafzxwK3COiOwQkUWh9ReLyPJQjX6tiFy+9/9CxkSHJV+zCxHJAAYBS0OrhuLUXgEnWQNfh9ZH2pM4SToL+E3oVd9cYARODfzvwBsikqCqHwD3Aq+paidVHR7avxg4GegCXAw8LCKHRCFuY/aaJV9TR0S8wCvAi6q6IrS6E7B1t123Ap0jfG43MA74fag2vgR4sf4+qvo3Vd2kqn5VfQiIBw5qrExVfU9Vv1bHF8CHwBGRjNuYfWXJ1wAgIi7gZaAGmFBv0w6cmmN9XYDtEQ4hnZ3tz7XW7RbjDaFmhK0isgWnjTqtsQJF5AQR+UpEykL7n9jU/sa0Jku+BhER4DkgAxinqr56m5cCw+vtm4zTFruUyCoB/ECfeuv61jvvEcBNwNlAN1XtilMDl9AuuwzPJyLxwJvAg0BGaP+Z9fY3JqYs+RqAvwIHA79Q1crdtv0TGCYi40QkAfg9sLi2WUJE3KH1HsAlIgmh5gtC2+NC2wXwhrbv8blT1QBOr4o7RSRJRIYAF9bbpTNOci4BPCLye3atkRcB2fXKjsNpligB/KHuc8fuw7+NMVFhyXc/F+qzeznOjazCUG+BHSLyKwBVLcFpi70H2Az8CDi3XhHnA5U4CfyI0Ptn6m3/MLTuMGBK6P1PGglnAk4bcyHwAvB8vW2zgA+AVTjNEVXs2kTxRujnJhGZr6rbgWuB10Nx/xKY3ty/hzGtRWwwdWOMaX1W8zXGmBiw5GuMMTFgydcYY2LAkq8xxsRA1JKviEwVkWIRWVJvXaqIfCQiq0M/u4XWi4g8JiJrRGSxPQJqjOnootbbQUR+gvN01EuqOiy07s9AmapOFpFJOJ3lbxaRE4FrcJ5A+hHwqKr+qLlzpKWlaXZ2dlTiN8Y0bt68eaWqmh7rONozT7QKVtV/1Q5LWM+pwJGh9y8CnwM3h9a/pM5fgq9EpKuIZKnqxqbOkZ2dTX5+fkTjNsY0T0TWNb+XaUprt/lm1EuohTiPswL0YtcO8z+E1u1BRC4TkXwRyS8pKYlepMYYE0Uxu+EWquXudZuHqk5R1TxVzUtPt289xpj2qbWTb5GIZAGEfhaH1q9n1wFVeofWGWNMhxS1Nt9GTMcZLGVy6Oc79dZPEJF/4Nxw29pce68xJrIWFi8kvyifvIw8RvQYsdfHz5s3r4fH43kWGIZ1Yw0CS/x+/6WjRo0qbmiHqCVfEXkV5+Zamoj8APwBJ+m+LiKX4AyOcnZo95k4PR3WABU4sw4YYyJMVSn3lVNWVUZZVRmbqjZRVlXG0tKlvL3mbQIaIMGdwDPHPrPXCdjj8TybmZl5cHp6+maXy7VfDxoTDAalpKRkSGFh4bPAKQ3tE83eDuc1sumYBvZV4OpoxWJMR1YTqKlLpnWvyl2Ta/31NcGaJsvzBX3kF+XvS+13mCVeh8vl0vT09K2FhYXDGtuntZsdjDHNCGqQrdVbd62dVpbtmWBDyXS7r+FJRbwuL90Tu5OakEpqQioDug6ge0JoOTG1bn1qQio/bP+BKz++El/Qh9flJS8jb19Cd1ni3Sn0b9Fo84slX2NaIJx2UlWl0l+5sxa6WyLdpXZaWcaW6i0ENLBHOYLQLaFbXcI8OPXgnQk0lEzrkmtCKsneZJxJSpqXmZzJM8c+06I237bA7XaPGjhwYN2EAGeccUZZdXW1VFVVuZ588sm6m/hffvll4q9//esD165du7RXr145+fn5y7Oysvzfffed56qrruq7aNGipC5dugTS0tJ8kydPXn/xxRf3A9i4cWNcp06dAp07dw6kpqb6v/zyy1X7GqslX2P20cLihVz64aXUBGrwuDycNegsEjwJe3z1L6sqoypQ1WAZyd7kumTZu1NvctNynSRar8Za++oa3xW3yx216xnRY0S7Tbq14uPjgytWrFhWf93ixYvjTzzxxEH1k+/f/va31DPOOKOs/n7BYJBTTjllwC9/+ctNM2bMWAvwv//9L3Hr1q3u2jLHjRuXffLJJ2+9+OKLN7c0Vku+xoSp0l/J8k3LKSgtoKC0gC/Xf0l1oBpw2kn/vuLveFyeXWqg/VL67fE1v3Zbt4RuJHgSYnxVsfWfNaXJ/11T2vnHA9K2Hz4grTwa58jNza1OSUnxf/rpp8lHH310OcD06dNT33///V1qrTNmzOjs8Xj0pptuqnt669BDD919Wq2IseRrTAMCwQBrt65lSekSFpcuZknpElZvXl3XHNAzuSdDug9hXtE8ghrE4/Lw+DGPc2jWoWF/1e/Ibpy2qM+qwu1JTe1TXu13fV1anqQKT3/xNf3TkiuS4z3BxvYflNm54oEzh3/f2HaA6upq1+DBg4fULk+cOHHj+PHjN48bN67slVdeST366KPLP/nkk+SuXbv6c3Jyqusfu3jx4sThw4dXhHuNLWXJ1xigqLyorkZbUFrA0tKlVPid38PO3s4MSxvGJTmXkJOWw7C0YaQlOjPQt7Rv7P5sR7XfUzuul6qznBzvaborRjMaanYAuOCCC8oOP/zwgwOBwPevvPJK6rhx48oaOr41WfI1+51yXzlLS5fW1WgLSgoornT6wXtcHgZ3G8wp/U8hNz2XYWnDOKDLAbj2nHAZ6BjtpNHQXA0VnCaH37wwd5A/EHR53K7gg2ePWButpocBAwb4evfuXT1z5szOM2fO7Pbf//53+e775OTkVL799tvdonH+hljyNR2aL+hjzeY1dTXaJaVL+HrL12hoWJG+nfsyOms0OWk55KTlcFDqQcS742Mc9f7h8AFp5VMvGr0q2m2+tc4666yyG2+8sU+fPn2q+/fv79t9+y9+8Yvtd9xxhzz44INpN9xwQynA7NmzEzdv3uw+/vjjd0Q6Hku+psNQVTaUb6CgZGfzwfJNy+t6GnSL78awtGEcm32s03zQfRhdE7rGNuj93OED0sojmXR3b/M9+uijtz711FPrAS644ILNt912W5977723wVq5y+Vi+vTpX1911VV9Hn300cz4+Hjt3bt39eOPP95sLX5fWPI17dbW6q27Nh+UFlBW5TTlxbvjOTj1YM4cdGZd80HvTr3tZlgHFwgE5jW2LSsry+/3++fvvn79+vUFte+zs7N9M2fOXNtYGW+++ea3LQ4yxJKvaRdqAjWsLFu5S/PBt9u+BZyHD/ql9OOIXkc4zQfpOQzsNhCvyxvboI1pgiVf0+aoKt9t/47FJTtrtCvKVuALOs10aYlp5KTlcOqAUxmWNoyh3YfSOa5zjKM2Zu9Y8jUxUb+LVt8ufZ3+tPWS7baabQAkehIZ2n0ovx7y67qbYhlJGdZ8YNo9S76mVQWCAd5d+y5//PKP+NWPIHU9D1ziYmDXgfz8gJ/XtdP2T+kf1UdqjYkVS74mqvxBPyvLVjK3cC75RfnML5q/yyhcinJ4z8O5NPdSDk49mCRvkw9FGdN
"text/plain": [
"<Figure size 288x216 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"image/png": "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"text/plain": [
"<Figure size 288x216 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
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"image/png": "iVBORw0KGgoAAAANSUhEUgAAAV8AAADgCAYAAACkXmWVAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/Z1A+gAAAACXBIWXMAAAsTAAALEwEAmpwYAABEMklEQVR4nO3dd3hU1dbA4d+aZNJpISSEGjrSS0CqBRURQVRsqBfEa/ssoGBBlG7h2rGiYkFFRREREbuodAkd6b1IIIFASAJps74/zgkETJ9JJmW/zzNPZk7ZZx0yrOzZs4uoKoZhGEbJcng7AMMwjIrIJF/DMAwvMMnXMAzDC0zyNQzD8AKTfA3DMLzAJF/DMAwvMMnXKLVE5DYRWeTtOAyjOJjkW8GJiL+IvCcie0TkhIisEZErzjnmEhHZLCIpIrJAROpn23eDiCyx9/2eQ/nviMgWEXGJyG3FeB/jReST4irfMDzNJF/DF9gHXAhUAZ4EvhCRKAARCQNmA2OAUCAGmJnt/KPAK8DkXMpfC9wLrPJ86IZRdpnkW8GparKqjlfV3arqUtV5wC6go33ItcDfqvqlqp4CxgNtRaS5ff4vqvoF8E8u5b+hqr8Cp/KLRUSqi8hcEUkUkb+ARufsnyIi++z9K0Wkp729DzAauFFEkkRkrb19qIhssmv0O0Xk7sL/CxlG8TDJ1ziLiEQATYG/7U0tsWqvgJWsgR32dk97AytJRwK324/sVgDtsGrgnwJfikiAqv4APAPMVNUQVW1rH38Y6AdUBoYCL4tIh2KI2zAKzSRf4zQRcQIzgOmqutneHAIcP+fQ40AlD1/bBxgIjLVr4xuA6dmPUdVPVPWIqmao6ouAP9AstzJV9TtV3aGWP4CfgJ6ejNswisokXwMAEXEAHwNpwP3ZdiVh1Ryzqwyc8HAINTjT/pxlzzkxPmw3IxwXkWNYbdRhuRUoIleIyDIROWof3zev4w2jJJnkayAiArwHRAADVTU92+6/gbbZjg3Gaov9G8+KAzKAutm21ct23Z7Ao8ANQDVVrYpVAxf7kLOm5xMRf+Ar4AUgwj5+frbjDcOrTPI1AN4CzgP6q+rJc/Z9DbQSkYEiEgCMBdZlNUuIiI+93RdwiEiA3XyBvd/P3i+A097/r/edqmZi9aoYLyJBItICGJLtkEpYyTkO8BWRsZxdIz8ERGUr2w+rWSIOyLC7z/Uuwr+NYRQLk3wrOLvP7t1YX2TF2r0FkkTkFgBVjcNqi30aSADOB27KVsR/gJNYCbyn/fzdbPt/srd1A96xn1+QSzj3Y7UxxwIfAh9k2/cj8AOwFas54hRnN1F8af88IiKrVPUEMAz4wo77ZmBufv8ehlFSxEymbhiGUfJMzdcwDMMLii35isj7InJYRDZk2xYqIj+LyDb7ZzV7u4jIqyKyXUTWmb6YhmGUd8VZ8/0Q6HPOtlHAr6raBPjVfg1wBdDEftyF1X5oGIZRbhVb8lXVP7HG/Wc3gDMd56cDV2fb/pHdGX4ZUFVEIosrNsMwDG8r6TbfCFU9aD+PxepXClCbs7+53m9vMwzDKJd8vXVhVVURKXRXCxG5C6tpguDg4I7Nmzf3eGyGYeRt5cqV8apaw9txlGUlnXwPiUikqh60mxUO29sPcPbIpjr2tn9R1Xew+osSHR2tMTExxRmvYRg5EJE9+R9l5KWkmx3mcmbU0hDgm2zbB9u9HroAx7M1TxiGYZQ7xVbzFZHPgIuAMBHZD4zDmnD7CxH5L9YopRvsw+djTXqyHUjBmv7PMAyj3Cq25Kuqg3LZdUkOxypwX3HFYhiGUdp47Qs3wzDKl5UrV4b7+vpOA1phRs+6gA0ZGRl3dOzY8XBOB5jkaxiGR/j6+k6rWbPmeTVq1EhwOBwVetIYl8slcXFxLWJjY6cBV+V0TEX/62QYhue0qlGjRmJFT7wADodDa9SocRzrU0DOx5RgPIZhlG8Ok3jPsP8tcs2xptnBMIxyw8fHp2OTJk1OLwhw7bXXHk1NTZVTp0453njjjdNjB5YsWRJ46623Nty5c+fftWvXbh0TE7MpMjIyY+/evb733ntvvbVr1wZVrlw5MywsLH3y5MkHhg4d2gDg4MGDfiEhIZmVKlXKDA0NzViyZMnWosZqkq9hGOWGv7+/a/PmzRuzb1u3bp1/3759m2ZPvp988knotddee9bcMy6Xi6uuuqrxzTfffGTevHk7AZYuXRp4/Phxn6wyBw4cGNWvX7/jQ4cOTXA3VpN8DcPwmkXb44MXb4+v1L1x2IkejcOSi+Mabdq0Sa1SpUrGb7/9FtyrV69kgLlz54Z+//33Z9Va582bV8nX11cfffTRuKxtXbt2PXdZLY8p98l39eHVrDy0kuiIaNqFt/N2OIZRITwya23drbEngvI6Jjk1w7EjPjlIFab+sYNGYcEpwf6+rtyOb1qzUsrz17Xdl9t+gNTUVEfz5s1bZL0eOXLkwTvvvDNh4MCBR2fMmBHaq1ev5F9//TW4atWqGa1bt07Nfu66desC27Ztm1LQe3RXuU6+aw6vYegPQ8nUTACCncEE+wbj5+OHv4//6Z/+Pv44fZz/2pb9OD/Hv885txw/H7+c9zv8sBYIdv9+Yg7FmD8kRrmQlJrhm7WKmar1OtjfN82dMnNqdgAYPHjw0R49epyXmZm5b8aMGaEDBw48d7rbEleuk2/MoRhcav0hFYRGVRrRpFoTUjNTSc1MJS0z7fTPpPQkUjNTSXeln7UvNTOVDFeG27FkJe+sJJ9b8s5K1ucm8aOnjvL1tq9xqQs/Hz/e7f2uScBGqZVfDRWsJofbP1zRNCPT5fD1cbheuKHdzuJqemjcuHF6nTp1UufPn19p/vz51RYvXrzp3GNat259cs6cOdWK4/o5KdfJNzoiGn8ff9Jd6TgdTh7p9EiRElamK5M0VxppmWlnJex/JXFXPvtzOt91Jvmnn0rP8ZzUzFSUMz140lxpxByKMcm3FFhzeA2/7f2NXvV6md9HIfVoHJb8/m2dthZ3m2+W66+//ugjjzxSt27duqmNGjVKP3d///79T4wZM0ZeeOGFsIcffjgeYPny5YEJCQk+ffr0SfJ0POU6+bYLb8e7vd91+6O6j8OHQEcggb6Bng2wgFSVlYdXcvdPd5PmSkMQoiOivRKLcUZWs1aGZjB943Se7v40/Rr183ZYZUqPxmHJnky657b59urV6/ibb755AGDw4MEJTzzxRN1nnnkmx1q5w+Fg7ty5O+699966U6ZMqenv76916tRJfe211/KtxRdFuU6+YCXgsl4jEbGS7XuXv8crq15h5aGVnMwoti9hjQL6cfePZKjVJOVSF6MXjWbFoRXc1+4+woPCvRxdxZSZmbkyt32RkZEZGRkZq87dfuDAgfVZz6OiotLnz5+/M7cyvvrqq91uB2kzI9zKkHbh7Zh66VTqV67PhKUTSEkvsS9mjXNkujJZ+s9SABziwN/Hn8ujLmfujrn0+7ofr69+neT0Yv0UbZRxJvmWMQG+AUzoNoEDSQd4bfVr3g6nwvp448fsOL6D+9rdxwPtH2Ba72k8f+HzzL16LhfWuZC3173NlbOv5IstX3jkC1uj/DHJtwzqGNGRG5vdyIxNM1hzeI23w6lwdh3fxetrXqdX3V7c3eZu7mh9x+mmrbqV6vL8hc/zad9PqV+5PpOWTeLaudeyYO8CVM20B8YZJvmWUQ91fIiI4AjGLRlHWqZbXSONQsh0ZTJ28Vj8ffwZ03VMrv23W9dozYd9PmTKxVNQVYYtGMbtP97OhvgNJRyxUVqZ5FtGBTuDGdd1HDuP7+TtdW97O5wK49PNn7Imbg2jOo8iLDAsz2NFhF71ejF7wGyePP9Jdh7fyaDvBvHon49yICnH9WGNCsQk3zKsR+0eXNXoKt5f/z5bjm7xdjjl3t7Evby66lUurHMh/RoWvEuZ0+HkxuY38t0133Fn6ztZsHcB/b/uzwsrXuB46vFijNgozUzyLeMeiX6Eyv6VGbN4jPlipxi51MXYJWNxOpyM6ZJ7c0NeQvxCGNZhGPOumUe/hv34aONH9J3dl+l/TzdNRx7i4+P
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"text/plain": [
"<Figure size 288x216 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"def malusa(l, r):\n",
" return [a for a in itertools.chain(*[[b for x in range(r)] for b in l])]\n",
"\n",
"dfa11 = {'term': [x for x in range(4,8)] * 5,\n",
" 'task_count': malusa([\"1\", \"2-10\", \"11-50\", \"51-100\", \"101+\"], 4),\n",
" 'count': [0,1,22,77,\n",
" 0,0,78,21,\n",
" 0,0,87,13,\n",
" 0,0,95,6,\n",
" 0,1,94,2]}\n",
"dfa11 = pd.DataFrame(data=dfa11, columns=dfa11.keys())\n",
"\n",
"dfc11 = {'term': [x for x in range(4,8)] * 5,\n",
" 'machine_locality': malusa([to_9c_bin(x) for x in [0.49,0.89,1.09,1.49,1.5]], 4),\n",
" 'count': [0,0,91,9,\n",
" 0,1,90,9,\n",
" 0,0,40,60,\n",
" 0,8,91,3,\n",
" 0,18,77,13]}\n",
"dfc11 = pd.DataFrame(data=dfc11, columns=dfc11.keys())\n",
"\n",
"dfb11 = {'term': [x for x in range(4,8)] * 7,\n",
" 'interval': malusa([\"<1\", \"1-2\", \"2-4\", \"4-10\", \"10-60\", \"60-1d\", \">=1d\"], 4),\n",
" 'count': [0,0,10,90,\n",
" 0,0,44,56,\n",
" 0,0,49,51,\n",
" 0,0,50,50,\n",
" 0,1,53,47,\n",
" 0,3,60,38,\n",
" 0,6,91,3]}\n",
"dfb11 = pd.DataFrame(data=dfb11, columns=dfb11.keys())\n",
"\n",
"cluster = \"2011\"\n",
"\n",
"categorical_plot(dfa11,\"task_count\", None, [to_9a_bin(x) for x in [1,10,50,100,101]])\n",
"\n",
"xs = [\"<1\", \"1-2\", \"2-4\", \"4-10\", \"10-60\", \"60-1d\", \">=1d\"]\n",
"categorical_plot(dfb11, \"interval\", None, xs)\n",
"\n",
"categorical_plot(dfc11, \"machine_locality\", None, [to_9c_bin(x) for x in [0.49,0.89,1.09,1.49,1.5]]) "
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a8d25894",
"metadata": {},
"outputs": [],
"source": []
},
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{
"cell_type": "code",
"execution_count": null,
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"id": "7a337122",
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"metadata": {},
"outputs": [],
"source": []
},
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{
"cell_type": "code",
"execution_count": null,
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"id": "11314301-be1c-43ce-a2c0-63798ea8ebe8",
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"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
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"display_name": "venv",
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"language": "python",
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"name": "venv"
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},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
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"version": "3.9.5"
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}
},
"nbformat": 4,
"nbformat_minor": 5
}