2021-04-17 09:37:58 +00:00
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{
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"cells": [
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{
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"cell_type": "code",
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2021-05-12 12:15:49 +00:00
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"execution_count": 14,
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2021-04-17 09:37:58 +00:00
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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"
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]
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},
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{
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"cell_type": "code",
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2021-05-12 12:15:49 +00:00
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"execution_count": 15,
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2021-04-17 09:37:58 +00:00
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"metadata": {},
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"outputs": [],
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"source": [
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2021-05-12 12:15:49 +00:00
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"DIR = \"/Users/maggicl/Git/bachelorThesis/figure_7/\""
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2021-04-17 09:37:58 +00:00
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]
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},
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{
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"cell_type": "code",
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2021-05-12 12:15:49 +00:00
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"execution_count": 24,
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2021-04-17 09:37:58 +00:00
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"metadata": {},
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"outputs": [],
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"source": [
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"def categorical_plot(df, key, title, sorted_xs = None):\n",
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" if sorted_xs == None:\n",
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" xs = set()\n",
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" lines = []\n",
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" for t in [4,5,6,7,8]:\n",
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2021-05-12 12:15:49 +00:00
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" xs = xs.union(np.array(df[df[\"term\"] == t][key]).reshape(-1))\n",
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2021-04-17 09:37:58 +00:00
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" xs = [str(x) for x in sorted(xs)]\n",
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" else:\n",
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" xs = sorted_xs\n",
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" \n",
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2021-04-18 20:15:26 +00:00
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" plt.figure(figsize=(10 if key != \"n_exec\" else 22,8))\n",
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2021-04-17 09:37:58 +00:00
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" ax = plt.gca()\n",
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" lines = []\n",
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" for t in [4,5,6,7,8]:\n",
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" ys = []\n",
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" for x in xs:\n",
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2021-05-12 12:15:49 +00:00
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" partsum = df[(df[\"term\"] != -1) & (df[key] == (int(x) if key == \"priority\" else x))][\"count\"].sum().astype(int)\n",
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" y = df[(df[\"term\"] == t) & (df[key] == (int(x) if key == \"priority\" else x))][\"count\"]\n",
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2021-04-17 09:37:58 +00:00
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" 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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" lines.append(ax.plot(xs,ys, marker='.')[0])\n",
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"\n",
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" plt.xticks(xs)\n",
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" plt.legend(lines, [\"EVICT\", \"FAIL\", \"FINISH\", \"KILL\", \"LOST\"],\n",
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" bbox_to_anchor=(1,1))\n",
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" plt.title(title)\n",
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" plt.show()"
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]
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},
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{
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"cell_type": "code",
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2021-05-12 12:15:49 +00:00
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"execution_count": 28,
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2021-04-17 09:37:58 +00:00
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"metadata": {},
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"outputs": [
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2021-04-17 10:50:40 +00:00
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{
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"data": {
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2021-05-12 12:15:49 +00:00
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"image/png": "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2021-04-17 10:50:40 +00:00
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"text/plain": [
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"<Figure size 720x576 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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2021-05-12 12:15:49 +00:00
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2021-04-17 10:50:40 +00:00
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"text/plain": [
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"<Figure size 720x576 with 1 Axes>"
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},
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"metadata": {
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},
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2021-04-18 20:15:26 +00:00
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{
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"data": {
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2021-05-12 12:15:49 +00:00
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"image/png": "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2021-04-18 20:15:26 +00:00
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"text/plain": [
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"<Figure size 1584x576 with 1 Axes>"
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]
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},
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"metadata": {
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},
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"output_type": "display_data"
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},
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2021-04-17 09:37:58 +00:00
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{
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"data": {
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2021-05-12 12:15:49 +00:00
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2021-04-17 09:37:58 +00:00
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},
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2021-05-12 12:15:49 +00:00
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2021-04-17 09:37:58 +00:00
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"text/plain": [
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"<Figure size 720x576 with 1 Axes>"
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2021-04-20 07:15:19 +00:00
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{
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"data": {
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2021-05-12 12:15:49 +00:00
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2021-04-20 07:15:19 +00:00
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"text/plain": [
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"<Figure size 1584x576 with 1 Axes>"
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},
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"metadata": {
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2021-04-17 09:37:58 +00:00
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"data": {
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2021-05-12 12:15:49 +00:00
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2021-04-17 09:37:58 +00:00
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"text/plain": [
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"<Figure size 720x576 with 1 Axes>"
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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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"data": {
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2021-05-12 12:15:49 +00:00
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2021-04-17 09:37:58 +00:00
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"<Figure size 720x576 with 1 Axes>"
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},
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2021-04-20 07:15:19 +00:00
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{
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2021-05-12 12:15:49 +00:00
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2021-04-20 07:15:19 +00:00
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"text/plain": [
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"<Figure size 1584x576 with 1 Axes>"
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]
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},
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"metadata": {
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},
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"output_type": "display_data"
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},
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2021-04-17 09:37:58 +00:00
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{
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"data": {
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2021-05-12 12:15:49 +00:00
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2021-04-17 09:37:58 +00:00
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2021-05-12 12:15:49 +00:00
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2021-04-17 09:37:58 +00:00
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"text/plain": [
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"<Figure size 720x576 with 1 Axes>"
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]
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},
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},
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2021-04-20 07:15:19 +00:00
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{
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"data": {
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2021-05-12 12:15:49 +00:00
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2021-04-20 07:15:19 +00:00
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"text/plain": [
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"<Figure size 1584x576 with 1 Axes>"
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]
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},
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"metadata": {
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},
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2021-04-17 09:37:58 +00:00
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{
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"data": {
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2021-05-12 12:15:49 +00:00
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"image/png": "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2021-04-17 09:37:58 +00:00
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"text/plain": [
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"<Figure size 720x576 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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2021-05-12 12:15:49 +00:00
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2021-04-17 09:37:58 +00:00
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2021-04-20 07:15:19 +00:00
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2021-05-12 12:15:49 +00:00
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2021-04-20 07:15:19 +00:00
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"text/plain": [
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"<Figure size 1584x576 with 1 Axes>"
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]
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},
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"metadata": {
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2021-04-17 09:37:58 +00:00
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{
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"data": {
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2021-05-12 12:15:49 +00:00
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2021-04-17 09:37:58 +00:00
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2021-05-12 12:15:49 +00:00
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2021-04-17 09:37:58 +00:00
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"text/plain": [
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"<Figure size 720x576 with 1 Axes>"
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]
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},
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"metadata": {
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2021-04-20 07:15:19 +00:00
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{
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"data": {
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2021-05-12 12:15:49 +00:00
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2021-04-20 07:15:19 +00:00
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"text/plain": [
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"<Figure size 1584x576 with 1 Axes>"
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},
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2021-04-17 09:37:58 +00:00
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2021-05-12 12:15:49 +00:00
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2021-04-17 09:37:58 +00:00
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"text/plain": [
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"<Figure size 720x576 with 1 Axes>"
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]
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},
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"metadata": {
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{
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"data": {
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2021-05-12 12:15:49 +00:00
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2021-04-17 09:37:58 +00:00
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"text/plain": [
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"<Figure size 720x576 with 1 Axes>"
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]
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},
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"metadata": {
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},
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2021-04-20 07:15:19 +00:00
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{
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"data": {
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2021-05-12 12:15:49 +00:00
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"image/png": "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2021-04-20 07:15:19 +00:00
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"text/plain": [
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"<Figure size 1584x576 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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2021-04-17 09:37:58 +00:00
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{
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"data": {
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2021-05-12 12:15:49 +00:00
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2021-04-17 09:37:58 +00:00
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2021-05-12 12:15:49 +00:00
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2021-04-17 09:37:58 +00:00
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"text/plain": [
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"<Figure size 720x576 with 1 Axes>"
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},
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"output_type": "display_data"
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2021-04-20 07:15:19 +00:00
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},
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{
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"data": {
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2021-05-12 12:15:49 +00:00
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"image/png": "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2021-04-20 07:15:19 +00:00
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"text/plain": [
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"<Figure size 1584x576 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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2021-04-17 09:37:58 +00:00
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}
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],
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"source": [
|
2021-04-17 10:50:40 +00:00
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|
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"for cluster in \"abcdefgh\":\n",
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2021-04-17 09:37:58 +00:00
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" # Processing figure 7a\n",
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" \n",
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" dfa = pd.read_csv(glob.glob(DIR + cluster + \"_priority/part-*\")[0], header=None,\n",
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" names=[\"term\", \"priority\", \"count\"])\n",
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" dfa = dfa.sort_values([\"term\", \"priority\"])\n",
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" \n",
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" categorical_plot(dfa, \"priority\", \"Figure 7a: Priorities w.r.t. event rate (cluster \" + cluster + \")\")\n",
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" \n",
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" # Processing figure 7b\n",
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" \n",
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" dfb = pd.read_csv(glob.glob(DIR + cluster + \"_exectime/part-*\")[0], header=None,\n",
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|
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" names=[\"term\", \"ignore\", \"exectime\", \"count\"])\n",
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" del dfb[\"ignore\"]\n",
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" dfb = dfb.sort_values([\"term\", \"exectime\"])\n",
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" \n",
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|
" xs = [\"<1\", \"1-2\", \"2-4\", \"4-10\", \"10-60\", \"60-1d\", \">=1d\"]\n",
|
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|
|
|
" categorical_plot(dfb, \"exectime\", \"Figure 7b: Execution times (mins) w.r.t. event rate (cluster \" + cluster + \")\", xs)\n",
|
2021-04-18 20:15:26 +00:00
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"\n",
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|
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" # Processing figure 7c\n",
|
2021-04-17 09:37:58 +00:00
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" \n",
|
2021-05-12 12:15:49 +00:00
|
|
|
" bins = [\"0\", \"1\", \"2-3\", \"4-5\", \"6-7\", \"8-9\", \"10-11\", \"12-13\", \">=14\"]\n",
|
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|
|
" bin_max = [1, 3, 5, 7, 9, 11, 13]\n",
|
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|
|
" def map_bins(value):\n",
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|
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|
" for i, m in enumerate(bin_max):\n",
|
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|
|
|
" if value < m:\n",
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|
" return bins[i-1]\n",
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|
|
" return bins[-1]\n",
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|
" \n",
|
2021-04-20 07:15:19 +00:00
|
|
|
" dfc = pd.read_csv(DIR + cluster + \"_figure7c.csv\", header=0)\n",
|
|
|
|
|
" dfc = dfc.sort_values([\"term\", \"n_exec\"])\n",
|
2021-05-12 12:15:49 +00:00
|
|
|
" dfc[\"n_exec\"] = dfc[\"n_exec\"].map(map_bins)\n",
|
|
|
|
|
" dfc = dfc.groupby([\"term\", \"n_exec\"]).sum().reset_index()\n",
|
2021-04-20 07:15:19 +00:00
|
|
|
" categorical_plot(dfc, \"n_exec\", \"Figure 7c: Priorities w.r.t. machine concurrency (cluster \" + cluster + \")\")\n",
|
2021-04-17 09:37:58 +00:00
|
|
|
" "
|
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|
|
|
]
|
|
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|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
"execution_count": null,
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [],
|
|
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|
"source": []
|
2021-04-18 20:15:26 +00:00
|
|
|
},
|
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|
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|
{
|
|
|
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|
"cell_type": "code",
|
|
|
|
|
"execution_count": null,
|
2021-05-12 12:15:49 +00:00
|
|
|
"metadata": {},
|
|
|
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|
"outputs": [],
|
|
|
|
|
"source": []
|
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|
|
|
},
|
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|
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|
{
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
"execution_count": null,
|
2021-04-18 20:15:26 +00:00
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [],
|
|
|
|
|
"source": []
|
2021-04-17 09:37:58 +00:00
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"metadata": {
|
|
|
|
|
"kernelspec": {
|
2021-05-12 12:15:49 +00:00
|
|
|
"display_name": "Python 3",
|
2021-04-17 09:37:58 +00:00
|
|
|
"language": "python",
|
2021-05-12 12:15:49 +00:00
|
|
|
"name": "python3"
|
2021-04-17 09:37:58 +00:00
|
|
|
},
|
|
|
|
|
"language_info": {
|
|
|
|
|
"codemirror_mode": {
|
|
|
|
|
"name": "ipython",
|
|
|
|
|
"version": 3
|
|
|
|
|
},
|
|
|
|
|
"file_extension": ".py",
|
|
|
|
|
"mimetype": "text/x-python",
|
|
|
|
|
"name": "python",
|
|
|
|
|
"nbconvert_exporter": "python",
|
|
|
|
|
"pygments_lexer": "ipython3",
|
2021-05-12 12:15:49 +00:00
|
|
|
"version": "3.8.3"
|
2021-04-17 09:37:58 +00:00
|
|
|
}
|
|
|
|
|
},
|
|
|
|
|
"nbformat": 4,
|
|
|
|
|
"nbformat_minor": 5
|
|
|
|
|
}
|
