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network.tcp.sendbuffer.ipynb
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"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
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"language_info": {
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"name": "ipython",
"version": 2
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"file_extension": ".py",
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"name": "python",
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"cells": [
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"input": [
"import os \n",
"import json\n",
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib\n",
"import matplotlib.pyplot as plt\n",
"from datetime import datetime\n",
"from IPython.display import display, display_markdown\n",
"\n",
"#\n",
"# Hide the plotbox if case miss any one data source\n",
"#\n",
"HIDE_MISSING_CASE = False\n",
"\n",
"DATA_LIST = 'time_list'\n",
"DATA_NAME = 'run_time'\n",
"DELETE_KEY = \"video-recording-fps\"\n",
"\n",
"#\n",
"# Input data source\n",
"#\n",
"input_json_fp = os.getenv(\"input_json_fp\")\n",
"#input_json_fp = \"output/javascript.options.baselinejit.threshold.json\"\n",
"with open(input_json_fp) as read_fh:\n",
" data_dict = json.load(read_fh)\n",
" for item in data_dict:\n",
" if DELETE_KEY in data_dict[item]:\n",
" data_dict[item].pop(DELETE_KEY)\n",
"\n",
"\n",
"#\n",
"# Definde layout and figure size\n",
"#\n",
"layout_row = 1\n",
"layout_column = 1\n",
"fig_size_w = 10\n",
"fig_size_h = 5\n",
"matplotlib.rcParams.update({'figure.max_open_warning': 0})\n",
"\n",
"#\n",
"# generate merged data\n",
"#\n",
"casename_list = list(set([casename for lable, data in data_dict.items() for casename in data.keys()]))\n",
"\n",
"case_result = []\n",
"for casename in casename_list:\n",
" result = {\n",
" \"casename\": casename,\n",
" \"result\": {}\n",
" }\n",
" for lable, data in data_dict.items():\n",
" result[\"result\"][lable] = {}\n",
" \n",
" for lable, data in data_dict.items():\n",
" if data.get(casename):\n",
" result[\"result\"][lable][DATA_LIST] = data.get(casename).get(DATA_LIST)\n",
" else:\n",
" result[\"result\"][lable][DATA_LIST] = []\n",
" case_result.append(result)\n",
"\n",
"nightly_better_list = []\n",
"for case in sorted(case_result):\n",
" casename = case.get('casename')\n",
" result = case.get('result')\n",
" d = pd.DataFrame(result)\n",
" \n",
" # drop empty 'DATA_LIST'\n",
" for c in d:\n",
" if (d[c][DATA_LIST] == []) :\n",
" d.drop(c, axis=1, inplace=True)\n",
"\n",
" # Retrive the value of 'DATA_NAME' from each run\n",
" value = pd.DataFrame([pd.DataFrame(d[c][DATA_LIST])[DATA_NAME] for c in d]).T\n",
" value.columns = d.columns\n",
" \n",
" # Plot input latency boxplot\n",
" value_min = min(value.min())\n",
" value_max = max(value.max())\n",
" value_median = pd.DataFrame([pd.DataFrame(d[c][DATA_LIST])[DATA_NAME].median() for c in d]).T\n",
" value_median.columns = d.columns\n",
" \n",
" # When HIDE_MISSING_CASE is enabled, skip the case if the case data less then input data amount.\n",
" if HIDE_MISSING_CASE and len(INPUT_SOURCE) > len(value.T):\n",
" # display summary\n",
" display_markdown('### {}\\nskip draw plot box'.format(casename), raw=True)\n",
" display(value.describe())\n",
" else:\n",
" \n",
" fig, ax = plt.subplots()\n",
" ax.plot(list(range(1,len(list(value_median.median()))+1)), list(value_median.median()), \"r:\")\n",
" \n",
" value.plot.box(layout=(layout_row, layout_column),\n",
" sharey=True, sharex=True, figsize=(fig_size_w, fig_size_h),\n",
" ylim=(0, value_max*1.1), ax=ax)\n",
" plt.title(casename)\n",
" if \"Nightly\" in value_median and \"ESR52\" in value_median:\n",
" if value_median['Nightly'][0] < value_median['ESR52'][0]:\n",
" nightly_better_list.append(casename)\n",
" # display summary\n",
" display(casename)\n",
" display(value.describe().T)"
],
"language": "python",
"metadata": {
"scrolled": false
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"outputs": [
{
"output_type": "display_data",
"text": [
"u'test_firefox_amazon_ail_hover_related_product_thumbnail'"
]
},
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" <th></th>\n",
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" <th>mean</th>\n",
" <th>std</th>\n",
" <th>min</th>\n",
" <th>25%</th>\n",
" <th>50%</th>\n",
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" <td>431.111111</td>\n",
" <td>33.044012</td>\n",
" <td>400.000000</td>\n",
" <td>405.555556</td>\n",
" <td>422.222222</td>\n",
" <td>433.333333</td>\n",
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" count mean std min 25% 50% \\\n",
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"default 10.0 431.111111 33.044012 400.000000 405.555556 422.222222 \n",
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"65536 461.111111 488.888889 \n",
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"output_type": "display_data",
"text": [
"u'test_firefox_amazon_ail_select_search_suggestion'"
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" <td>5.555556</td>\n",
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" <td>5.555556</td>\n",
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" count mean std min 25% 50% 75% \\\n",
"65536 10.0 12.222222 8.606630 5.555556 5.555556 5.555556 22.222222 \n",
"default 10.0 7.222222 5.270463 5.555556 5.555556 5.555556 5.555556 \n",
"\n",
" max \n",
"65536 22.222222 \n",
"default 22.222222 "
]
},
{
"output_type": "display_data",
"text": [
"u'test_firefox_amazon_ail_type_in_search_field'"
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" <td>22.222222</td>\n",
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" <td>22.222222</td>\n",
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" <td>6.953698</td>\n",
" <td>5.555556</td>\n",
" <td>6.944444</td>\n",
" <td>11.111111</td>\n",
" <td>19.444444</td>\n",
" <td>22.222222</td>\n",
" </tr>\n",
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"output_type": "display_data",
"text": [
" count mean std min 25% 50% \\\n",
"65536 10.0 18.888889 5.367177 11.111111 13.888889 22.222222 \n",
"default 10.0 12.777778 6.953698 5.555556 6.944444 11.111111 \n",
"\n",
" 75% max \n",
"65536 22.222222 22.222222 \n",
"default 19.444444 22.222222 "
]
},
{
"output_type": "display_data",
"text": [
"u'test_firefox_facebook_ail_click_close_chat_tab'"
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},
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" <td>10.0</td>\n",
" <td>46.666667</td>\n",
" <td>18.739423</td>\n",
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" <td>50.000000</td>\n",
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" <td>66.666667</td>\n",
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" <tr>\n",
" <th>default</th>\n",
" <td>10.0</td>\n",
" <td>64.444444</td>\n",
" <td>16.396995</td>\n",
" <td>44.444444</td>\n",
" <td>50.000000</td>\n",
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" <td>88.888889</td>\n",
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"output_type": "display_data",
"text": [
" count mean std min 25% 50% \\\n",
"65536 10.0 46.666667 18.739423 22.222222 27.777778 50.000000 \n",
"default 10.0 64.444444 16.396995 44.444444 50.000000 66.666667 \n",
"\n",
" 75% max \n",
"65536 63.888889 66.666667 \n",
"default 66.666667 88.888889 "
]
},
{
"output_type": "display_data",
"text": [
"u'test_firefox_facebook_ail_click_open_chat_tab'"
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" <th>50%</th>\n",
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" <td>63.677859</td>\n",
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" <tr>\n",
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" <td>59.027324</td>\n",
" <td>111.111111</td>\n",
" <td>133.333333</td>\n",
" <td>144.444444</td>\n",
" <td>233.333333</td>\n",
" <td>266.666667</td>\n",
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" </tbody>\n",
"</table>\n",
"</div>"
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"output_type": "display_data",
"text": [
" count mean std min 25% 50% \\\n",
"65536 10.0 180.000000 63.677859 144.444444 144.444444 150.000000 \n",
"default 10.0 177.777778 59.027324 111.111111 133.333333 144.444444 \n",
"\n",
" 75% max \n",
"65536 163.888889 300.000000 \n",
"default 233.333333 266.666667 "
]
},
{
"output_type": "display_data",
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"text": [
" count mean std min 25% 50% \\\n",
"65536 10.0 61.111111 13.094570 44.444444 55.555556 61.111111 \n",
"default 10.0 85.555556 12.883353 66.666667 77.777778 83.333333 \n",
"\n",
" 75% max \n",
"65536 66.666667 88.888889 \n",
"default 88.888889 111.111111 "
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"text": [
" count mean std min 25% 50% 75% \\\n",
"65536 10.0 92.222222 9.147473 77.777778 88.888889 94.444444 100.0 \n",
"default 10.0 90.000000 9.728834 77.777778 80.555556 88.888889 100.0 \n",
"\n",
" max \n",
"65536 100.0 \n",
"default 100.0 "
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" <th>75%</th>\n",
" <th>max</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>65536</th>\n",
" <td>10.0</td>\n",
" <td>6.111111</td>\n",
" <td>1.756821</td>\n",
" <td>5.555556</td>\n",
" <td>5.555556</td>\n",
" <td>5.555556</td>\n",
" <td>5.555556</td>\n",
" <td>11.111111</td>\n",
" </tr>\n",
" <tr>\n",
" <th>default</th>\n",
" <td>10.0</td>\n",
" <td>10.555556</td>\n",
" <td>6.651217</td>\n",
" <td>5.555556</td>\n",
" <td>5.555556</td>\n",
" <td>8.333333</td>\n",
" <td>11.111111</td>\n",
" <td>22.222222</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"output_type": "display_data",
"text": [
" count mean std min 25% 50% 75% \\\n",
"65536 10.0 6.111111 1.756821 5.555556 5.555556 5.555556 5.555556 \n",
"default 10.0 10.555556 6.651217 5.555556 5.555556 8.333333 11.111111 \n",
"\n",
" max \n",
"65536 11.111111 \n",
"default 22.222222 "
]
}
],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# show plot\n",
"plt.show()"
],
"language": "python",
"metadata": {
"scrolled": false
},
"outputs": [
{
"output_type": "display_data",
"png": 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eT/J3wEXA2sCXSyk3jfR8JEmSxrIm92SVUi4ALmjRtoSXmSW14bFFIyqllNHu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\nTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x10863e690>"
]
},
{
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x10c3a0210>"
]
},
{
"output_type": "display_data",
"png": 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pBMOUJElSCYYpSZKkEgxTkiRJJRimJEmSSjBMSZIklWCYkiRJKsEwJUmSVIJh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\nSZJUgmFKkiSpBMOUJElSCf8fSIJ+7I0KdoEAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x10c6edd10>"
]
},
{
"output_type": "display_data",
"png": 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ppW/ULboemFjdnwhc1/nVkyRJ6t4amWdqL+A44MGIuK967HPAZODKiDgBeBw4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\n",
"text": [
"<matplotlib.figure.Figure at 0x10c78bf90>"
]
},
{
"output_type": "display_data",
"png": 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h5MiRve2GJEnSgLKyIeuhjsuAzdd5zfzZwOZt641p5kmSJK1WVjZkXQRMbKYn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\nSZJUgSFLkiSpAkOWJElSBYYsSZKkCv4/ntLbfAJcjtMAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x10c7d7610>"
]
},
{
"output_type": "display_data",
"png": 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9XD755Mqo6FC5DU2T6nGpJElaBZsL1bvcey+cdVal/PnPw3bbVcr9++czUk2m\nTYNbbqmUDzgAdt65/HpKkno9Q5Z6nldeyWeoAK69Ft7/fnj55Vy+9FJobITnn8/liRPhhz+srP/d\n78K551b2tf76OXhJktTJagpZETE0Ii6KiAci4v6IeHdEDI+I6yLiweKnd5xV57nkElh7bXjwwVz+\n97/zAJ4LF+byZz4DCxbkQT4Bdt89z+vn/xOSpK4VtdxyICLOAW5OKZ0ZEWsAawHfBp5LKZ0YEccC\nw1JKx6xqPw0NDWn27Nkdroe6r7ed87Z6V6Hd7j787npXQZLUA0TEnJRSQ1vrdbjje0SsB+wGHAGQ\nUnoVeDUiDgB2L1Y7B7gRWGXIUu/1wv0ntu/ehXVWt3sXSpJ6rVraUDYDFgG/i4jbI+LMiFgb2CCl\nVAyBzVPABi1tHBFHRsTsiJi9aNGiGqohSZLU/dQSsgYAOwCnp5TeDvwbOLZ6hZTbIltsj0wpTUkp\nNaSUGkZWXzIvSZLUC9QSsuYD81NKs4ryReTQ9XREbAhQ/FxYWxUlSZJ6ng6HrJTSU8C8iCjudsue\nwH3AZcDhxbzDgUtrqqEkSVIPVOuI70cD04orCx8GPkkObhdERCPwGHBwjc8hSZLU49QUslJKdwAt\nXcK4Zy37lSRJ6ukcoVGSJKkEhixJkqQSGLIkSZJKYMiSJEkqQa1XF0pt6gm3rFlv8MB6V0GS1MsY\nslSqMu5bOObYK3vE/RAlSX2bzYWSJEklMGRJkiSVwJAlSZJUAkOWJElSCQxZkiRJJTBkSZIklcCQ\nJUmSVAJDliRJUgkMWZIkSSUwZEmSJJXAkCVJklQCQ5YkSVIJDFmSJEklMGRJkiSVwJAlSZJUAkOW\nJElSCQxZkiRJJTBkSZIklcCQJUmSVAJDliRJUgkMWZIkSSUwZEmSJJXAkCVJklSCAfWugAQQEau3\n/kntWy+l1IHaSJJUO0OWugXDkCSpt7G5UJIkqQSGLEmSpBIYsiRJkkpgyJIkSSpBzSErIvpHxO0R\ncUVR3iwiZkXE3Ig4PyLWqL2akiRJPUtnnMn6MnB/Vfkk4OcppS2AxUBjJzyHJElSj1JTyIqI0cAH\ngDOLcgB7ABcVq5wDTKjlOSRJknqiWs9k/QL4JvB6UV4fWJJSWlGU5wOjanwOSZKkHqfDISsiPggs\nTCnN6eD2R0bE7IiYvWjRoo5WQ5IkqVuq5UzWe4APRcSjwHnkZsJTgaER0TSS/GhgQUsbp5SmpJQa\nUkoNI0eOrKEakiRJ3U+HQ1ZK6VsppdEppTHAocANKaXDgBnAgcVqhwOX1lxLSZKkHqaMcbKOAb4a\nEXPJfbSmlvAckiRJ3Vqn3CANy52dAAAHpElEQVQ6pXQjcGMx/TCwY2fsV5IkqadyxHdJkqQSGLIk\nSZJKYMiSJEkqgSFLkiSpBIYsSZKkEhiyJEmSSmDIkiRJKoEhS5IkqQSGLEmSpBIYsiRJkkpgyJIk\nSSqBIUuSJKkEhixJkqQSGLIkSZJKYMiSJEkqgSFLkiSpBIYsSZKkEhiyJEmSSmDIkiRJKoEhS5Ik\nqQSGLEmSpBIYsiRJkkpgyJIkSSqBIUuSJKkEhixJkqQSGLIkSZJKYMiSJEkqgSFLkiSpBIYsSZKk\nEhiyJEmSSmDIkiRJKoEhS5IkqQSGLEmSpBIYsiRJkkpgyJIkSSqBIUuSJKkEHQ5ZEbFxRMyIiPsi\n4t6I+HIxf3hEXBcRDxY/h3VedSVJknqGWs5krQC+llLaGtgJ+EJEbA0cC1yfUtoSuL4oS5Ik9Skd\nDlkppSdTSrcV0y8A9wOjgAOAc4rVzgEm1FpJSZKknqZT+mRFxBjg7cAsYIOU0pPFoqeADVrZ5siI\nmB0RsxctWtQZ1ZAkSeo2ag5ZEbEO8CfgKyml56uXpZQSkFraLqU0JaXUkFJqGDlyZK3VkCRJ6lZq\nClkRMZAcsKallC4uZj8dERsWyzcEFtZWRUmSpJ6nlqsLA5gK3J9SOqVq0WXA4cX04cClHa+eJElS\nzzSghm3fA3wcuDsi7ijmfRs4EbggIhqBx4CDa6uiJElSz9PhkJVSmglEK4v37Oh+JUmSegNHfJck\nSSqBIUuSJKkEhixJkqQSGLIkSZJKYMiSJEkqgSFLkiSpBIYsSZKkEhiyJEmSSmDIkiRJKoEhS5Ik\nqQSGLEmSpBIYsiRJkkpgyJIkSSqBIUuSJKkEhixJkqQSGLIkSZJKYMiSJEkqgSFLkiSpBIYsSZKk\nEhiyJEmSSmDIkiRJKoEhS5IkqQSGLEmSpBIYsiRJkkpgyJIkSSqBIUuSJKkEhixJkqQSGLIkSZJK\nYMiSJEkqgSFLkiSpBIYsSZKkEhiyJEmSSmDIkiRJKoEhS5IkqQSGLEmSpBKUFrIiYt+I+GdEzI2I\nY8t6HkmSpO6olJAVEf2B/wH2A7YGJkbE1mU8lyRJUndU1pmsHYG5KaWHU0qvAucBB5T0XJIkSd1O\nWSFrFDCvqjy/mCdJktQnDKjXE0fEkcCRRfHFiPhnveqiHmcE8Ey9KyGp1/G7Re21aXtWKitkLQA2\nriqPLua9IaU0BZhS0vOrF4uI2SmlhnrXQ1Lv4neLOltZzYX/ALaMiM0iYg3gUOCykp5LkiSp2ynl\nTFZKaUVEfBG4BugPnJVSureM55IkSeqOSuuTlVK6CriqrP2rT7OZWVIZ/G5Rp4qUUr3rIEmS1Ot4\nWx1JkqQSGLJUNxExNCIuiogHIuL+iHh3RBwfEQsi4o7i8f5i3TERsaxq/hlV+7k6Iu6MiHsj4ozi\njgNNy44u9n9vRPykHscpqesV3yVfX8XykRExKyJuj4hdO7D/IyLitGJ6gnc1UUvqNk6WBJwKXJ1S\nOrC4CnUtYB/g5ymln7Ww/kMppe1bmH9wSun5iAjgIuAg4LyIGE++08B2KaVXIuJNJR2HpJ5nT+Du\nlNKnO2FfE4ArgPs6YV/qRTyTpbqIiPWA3YCpACmlV1NKSzqyr5TS88XkAGANoKmj4eeBE1NKrxTr\nLayp0pK6tYiYFBH/ioiZwFuLeZsXZ7vnRMTNEbFVRGwP/AQ4oDgzPjgiTo+I2cVZ7xOq9vloRIwo\nphsi4sZmz7kz8CHgp8W+Nu+q41X3Z8hSvWwGLAJ+V5yuPzMi1i6WfTEi7oqIsyJiWPU2xbo3NT+9\nHxHXAAuBF8hnswDeAuxaNAncFBHvLPmYJNVJRLyDPCbj9sD7gabf9ynA0SmldwBfB36dUroD+B5w\nfkpp+5TSMmBSMRDptsB7I2Lb9jxvSukW8jiQ3yj29VCnHph6NEOW6mUAsANwekrp7cC/gWOB04HN\nyV+UTwInF+s/CWxSrPtV4I8RsW7TzlJK+wAbAmsCe1Q9x3BgJ+AbwAVFk6Kk3mdX4JKU0kvF2e3L\ngEHAzsCFEXEH8Bvy90RLDo6I24DbgW0A+1ipZoYs1ct8YH5KaVZRvgjYIaX0dErptZTS68BvgR0B\nUkqvpJSeLabnAA+Rz1S9IaX0MnApuR9W03NcnLJbgdfJ9yaT1Df0A5YUZ5iaHmObrxQRm5HPcu2Z\nUtoWuJIc0ABWUPlbOaj5ttKqGLJUFymlp4B5EfHWYtaewH0RUf1f5oeBe+CNK4H6F9P/BWwJPBwR\n6zRtExEDgA8ADxTb/xkYXyx7C7m/ljd/lXqnvwITiv5VQ4D9gZeARyLiIIDItmth23XJZ9OXRsQG\nwH5Vyx4F3lFMf6SV534BGFL7Iai38epC1dPRwLTiysKHgU8Cvyw6pSbyl9tni3V3A74fEcvJZ6Q+\nl1J6rvhCvCwi1iT/0zADaBre4SzgrIi4B3gVODw5+q7UK6WUbouI84E7yf0z/1EsOgw4PSK+AwwE\nzivWqd72zoi4nfwP2jzg/6oWnwBMjYgfADe28vTnAb+NiC8BB9ovS00c8V2SJKkENhdKkiSVwJAl\nSZJUAkOWJElSCQxZkiRJJTBkSZIklcCQJUmSVAJDliRJUgkMWZIkSSX4/5O74GqwRczhAAAAAElF\nTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x10c8736d0>"
]
},
{
"output_type": "display_data",
"png": 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8EVgnIsY0y2wE3Nfdypl5cmZOzszJ48ePH0Q1JEmSRp4Bh6zMPCozN8rMScA7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\nCv4/X5YVWAJHe8cAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x10c929950>"
]
},
{
"output_type": "display_data",
"png": 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FxLbAccCNmbklcGNVliRJWql0GqYyc3pm3lstzwEeAUYABwITqs0mAAe1qpKS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\nB6D61ORVK3AtAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x10c9350d0>"
]
},
{
"output_type": "display_data",
"png": 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7NCLu75j+dx3buSwivhMR10bE39U78I/NW1G3f21E/OVMHKekna++l7x5G/MX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\nlCRJUgPDlCRJUgPDlCRJUoP/D5Sx4MLPYZyHAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x10c9af810>"
]
},
{
"output_type": "display_data",
"png": 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+pS/VNyapi2vThfWI6BkRjwLzgNuBZ4EFKaUlxSKzgBG1CVGStFL694dbboFv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\nVML/B20DtPLNFFe+AAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x10caa7e50>"
]
},
{
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x10cab32d0>"
]
},
{
"output_type": "display_data",
"png": 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SDYYpSZKkGgxTkiRJNRimJEmSajBMSZIk1WCYkiRJqsEwJUmSVINhSpIkqQbD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\ngg==\n",
"text": [
"<matplotlib.figure.Figure at 0x10cb6d1d0>"
]
},
{
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x10cc41f50>"
]
},
{
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"text": [
"<matplotlib.figure.Figure at 0x10cc419d0>"
]
},
{
"output_type": "display_data",
"png": 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zZsxYwmZIkiT1TUsUsjLzycycl5mvAufQMST4GDC8reqwum5hxzg7M0dl5qjB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\n",
"text": [
"<matplotlib.figure.Figure at 0x10ccbfb10>"
]
},
{
"output_type": "display_data",
"png": 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C5/Z9Bvf9RpKv0/0HbRnwpYGb3wOcluSvgSvWcPhzgVOT/AXwh16XpRF+4rsk\nSVIDni6UJElqwJAlSZLUgCFLkiSpAUOWJElSA4YsSZKkBgxZkiRJDRiyJEmSGjBkSZIkNfD/AS16\nWaNRjBXdAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x10cd58cd0>"
]
},
{
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"text": [
"<matplotlib.figure.Figure at 0x10cdd4550>"
]
},
{
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QJUmSVIOWQ1ZEDIuIGyLisqq8fkRcHxF3RsR5EbFs69WUJEkaXPqiJetzwPRu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\nGhiyJEmSavD/Aeu1kEE+if4EAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x10ce993d0>"
]
},
{
"output_type": "display_data",
"png": 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9qWhJ01pE/FlEfDciLgWeV8ftVnuvr4yI/4iI3SNiIfCXwEG1p3vLiDgpIoZr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\nd2QAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x10ced7950>"
]
},
{
"output_type": "display_data",
"png": 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1NUlqEcOUJLUXDb1UvXrBZZfB8cfn9vTpebzVm29WV5uk5Wo2TEXEdRExMyKe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\nw4AAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x10cf75d50>"
]
},
{
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x10cf751d0>"
]
},
{
"output_type": "display_data",
"png": 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pzTZJkqTlxrBuHTgijgSObIpPRcQfu9UXDTnrAY92uxOSljn+btGS2nRJKtUI\nWQ8BG/cpb9Rsm09mng2cXeH4WsZFRG9m9nS7H5KWLf5u0UCrMV34W2CLiNgsIlYGDgGuqHAcSZKk\nQWvAR7Iy88WI+Ajwc2BF4NzMvGOgjyNJkjSYVVmTlZlXAVfVaFvCaWZJdfi7RQMqMrPbfZAkSVrm\n+LE6kiRJFRiy1BURsXZEXBoRf4iIaRHxpog4ISIeiohbmsd+Td3REfFsn+1n9WnnZxFxa0TcERFn\nNZ840Np3dNP+HRHx5W6cp6RXX/O75OOL2T8yIm6IiJsjYrelaP+wiPh/zetxfqqJFqVr98nScu80\n4GeZeWBzFerqwDuAUzPz3xdS/57M3H4h2w/OzCcjIoBLgYOAiyJiD8onDWyXmc9HxN9UOg9JQ89e\nwG2ZefgAtDUOuBK4cwDa0jLGkSy96iJiBLA7MAkgM1/IzCeWpq3MfLJ5OQxYGWgtMvxfwCmZ+XxT\nb1ZHnZY0qEXExIj4U0RMBd7QbHt9M9p9U0T8V0RsFRHbA18GDmhGxleLiDMjorcZ9f58nzbvj4j1\nmtc9EXHtAsd8M/Au4CtNW69/tc5XQ4MhS92wGTAb+HYzXH9ORAxv9n0kIn4fEedGxDp939PUvW7B\n4f2I+DkwC5hLGc0C2BLYrZkSuC4i3lj5nCR1SUTsRLkn4/bAfkDr3/vZwNGZuRPwceCbmXkL8Dng\n4szcPjOfBSY2NyH9W+DvI+Jvl+S4mflryn0gP9G0dc+AnpiGPEOWumEYsCNwZmbuADwNHAecCbye\n8otyBvDVpv4MYJOm7rHA9yJirVZjmfkOYH1gFWDPPsdYF9gF+ATw/WZKUdKyZzfgh5n5TDO6fQWw\nKvBm4JKIuAX4D8rviYU5OCJ+B9wMbAO4xkoDwpClbpgOTM/MG5rypcCOmflIZr6UmS8D3wJ2BsjM\n5zPzz83rm4B7KCNVf5GZzwGXU9ZhtY7xgyxuBF6mfC6ZpOXDCsATzQhT6zFmwUoRsRlllGuvzPxb\n4CeUgAbwIu2/k6su+F6pP4YsveoycybwYES8odm0F3BnRPT9X+a7gdvhL1cCrdi8fh2wBXBvRKzR\nek9EDAP2B/7QvP9HwB7Nvi0p67X84Fdp2XQ9MK5ZX7Um8E7gGeC+iDgIIIrtFvLetSij6XMiYhSw\nb5999wM7Na/fs4hjzwXW7PwUtCzy6kJ1y9HAhc2VhfcCHwRObxalJuWX2780dXcHvhAR8ygjUkdl\n5mPNL8QrImIVyn8YpgCt2zucC5wbEbcDLwDj0zvvSsukzPxdRFwM3EpZn/nbZtehwJkR8VlgJeCi\npk7f994aETdT/oP2IPCrPrsDd5NcAAAAVklEQVQ/D0yKiC8C1y7i8BcB34qIjwIHui5LfXnHd0mS\npAqcLpQkSarAkCVJklSBIUuSJKkCQ5YkSVIFhixJkqQKDFmSJEkVGLIkSZIqMGRJkiRV8P8BMIvY\nJJD86n0AAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x10d0a64d0>"
]
},
{
"output_type": "display_data",
"png": 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MWZIkSQ0YsiRJkhowZEmSJDVgyJIkSWrAkCVJktSAIUuSJKkBQ5YkSVIDhixJ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\nQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x10d1017d0>"
]
},
{
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x10cf91a50>"
]
},
{
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x10d250d50>"
]
},
{
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22qlZPuKIJbc/+eQlyz//OTzzTLP8la80hy0BDjusOcwJ8OSTS57vtNNKj9nb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\nqolBS5IkqSYGLUmSpJoYtCRJkmry/wFyrauPCOX3lgAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x10d2b81d0>"
]
},
{
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x10d37cad0>"
]
},
{
"output_type": "display_data",
"png": 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bkQNKkiQNJF0xZuoTmfl8F+xHkiSp33GeKUmSpBrqhqkE/hgRt0fEwV1RIUmS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\nUg2GKUmSpBoMU5IkSTUYpiRJkmr4/60Og/pvtX/RAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x10c747e50>"
]
}
],
"prompt_number": 2
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Case list which Nightly peform better than ESR52"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"nightly_better_list"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 3,
"text": [
"[]"
]
}
],
"prompt_number": 3
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 4
}
],
"metadata": {}
}
]
}
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