From e79dadc6daad44934a2beb4792bfac8a551f234c Mon Sep 17 00:00:00 2001 From: Ben Hitz Date: Wed, 27 Jun 2018 13:30:08 -0700 Subject: [PATCH 1/5] add encode perspectives --- .gitignore | 2 + jupyter_notebooks/Fig1-take2.png | Bin 0 -> 51450 bytes jupyter_notebooks/Fig1-take3.png | Bin 0 -> 55608 bytes jupyter_notebooks/Fig1.png | Bin 0 -> 57363 bytes .../encode-perspectives-release-fig.ipynb | 8465 +++++++++++++++++ .../v64-duplicate vs. v65rc2-checkpoint.ipynb | 463 + jupyter_notebooks/timing-tests-sno-33.ipynb | 2526 +++++ 7 files changed, 11456 insertions(+) create mode 100644 jupyter_notebooks/Fig1-take2.png create mode 100644 jupyter_notebooks/Fig1-take3.png create mode 100644 jupyter_notebooks/Fig1.png create mode 100644 jupyter_notebooks/encode-perspectives-release-fig.ipynb create mode 100644 jupyter_notebooks/kath/.ipynb_checkpoints/v64-duplicate vs. v65rc2-checkpoint.ipynb create mode 100644 jupyter_notebooks/timing-tests-sno-33.ipynb diff --git a/.gitignore b/.gitignore index 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zW+1?woSm71_{y!xBeceSTvZfpEsEf zi?eyh(%3jb)S>#Ak$IClQ;tnRMT literal 0 HcmV?d00001 diff --git a/jupyter_notebooks/encode-perspectives-release-fig.ipynb b/jupyter_notebooks/encode-perspectives-release-fig.ipynb new file mode 100644 index 00000000..7b289978 --- /dev/null +++ b/jupyter_notebooks/encode-perspectives-release-fig.ipynb @@ -0,0 +1,8465 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "%matplotlib inline\n", + "%config InlineBackend.figure_format = 'retina'\n", + "import asyncio\n", + "import aiohttp\n", + "import json\n", + "import matplotlib as mpl\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib.patches as patches\n", + "import numpy as np\n", + "import os\n", + "import pandas as pd\n", + "import requests\n", + "import seaborn as sns\n", + "from ast import literal_eval\n", + "from collections import defaultdict\n", + "pd.options.display.max_rows = 200\n", + "pd.options.display.max_columns = 50\n", + "from IPython.core.display import display, HTML\n", + "display(HTML(\"\"))" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": true, + "scrolled": false + }, + "outputs": [], + "source": [ + "expts = pd.read_excel('/Users/hitz/encode-prod/Experiments_2017_11_30_perspectives_hacked.xls')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "expts['Date released'] = expts['Date released'].apply(lambda x: pd.to_datetime(x))" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "target.investigated_as object\n", + "Accession object\n", + "award.rfa object\n", + "award.pi.title object\n", + "Assay Type object\n", + "Assay Nickname object\n", + "Target label object\n", + "Target gene object\n", + "Biosample summary object\n", + "Biosample object\n", + "Lab object\n", + "Project object\n", + "Species object\n", + "Biosample type object\n", + "Date released datetime64[ns]\n", + "Assay type object\n", + "Month released object\n", + "dtype: object" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "expts.dtypes" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Distributions of metrics" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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2qE5B409LSxM86/K28kzDSpqVPxUlAOzatQtyuVy0vR+Ay+Pm5iYqu3fvniiI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fmI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+ "text/plain": [ + "" + ] + }, + "metadata": { + "image/png": { + "height": 501, + "width": 880 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "cols = expts['Assay type'].unique()\n", + "sns.set(style=\"darkgrid\", font=\"Arial\")\n", + "fig, ax = plt.subplots(figsize=(15,8))\n", + "(\n", + " expts.groupby(['Assay type', 'Date released'])\n", + " .count()\n", + " .unstack('Assay type')['Accession'][cols]\n", + " .resample('M').sum()\n", + " .cumsum()\n", + " .fillna(method='ffill')\n", + " .plot(colormap='Spectral',lw=3, ax=ax)\n", + ")\n", + "#fig.set_facecolor((0.4,0.4,0.4,1))\n", + "fig.patches.append(\n", + " patches.Rectangle(\n", + " (0,1),\n", + " 1,\n", + " 0.05,\n", + " color='black',#'#CCCCCC',\n", + " transform=ax.transAxes,\n", + " zorder=-1\n", + " )\n", + ")\n", + "fig.suptitle('ENCODE EXPERIMENTS THROUGH THE AGES',\n", + " size=16,\n", + " family='Arial',\n", + " fontweight='bold',\n", + " color='white',\n", + " y=0.902);" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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qiLrXhSGeQ4bUqlUr0faKFStw4cIFSbnk5GSMGDEC8fHxovwuXbqUaP/eVIsXL5Zcf02a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//ll18AcNxxw2qMO/74kRG3r1q1gi++WMjw4SMYMOAYli37hhkzprNx4wYmT361WhGrIbZv3wpA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\nLR/P5KhQmw8TkiALr1BjhhoAAIiubEi7xxbaPTalvF/UWNnedo0KNaD2jDH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REJ5Qo5Xg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FaPQA0AIqBYrujeF90je64ZWqstfV0hVxQO4+ec676hQ205autQ4ww1AADi4hfzR+TLVq17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\nZ7QpWz0GslgY0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+ "text/plain": [ + "" + ] + }, + "metadata": { + "image/png": { + "height": 501, + "width": 874 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "cols = expts['Assay type'].unique()\n", + "sns.set(style=\"darkgrid\", font=\"Arial\")\n", + "fig, ax = plt.subplots(figsize=(15,8))\n", + "(\n", + " expts.groupby(['Assay type', 'Date released'])\n", + " .count()\n", + " .unstack('Assay type')['Accession'][cols]\n", + " .resample('M').sum()\n", + " .cumsum()\n", + " .fillna(method='ffill')\n", + " .plot(colormap='Spectral',lw=3, ax=ax,logy=True)\n", + ")\n", + "#fig.set_facecolor((0.4,0.4,0.4,1))\n", + "fig.patches.append(\n", + " patches.Rectangle(\n", + " (0,1),\n", + " 1,\n", + " 0.05,\n", + " color='black',#'#CCCCCC',\n", + " transform=ax.transAxes,\n", + " zorder=-1\n", + " )\n", + ")\n", + "fig.suptitle('ENCODE EXPERIMENTS THROUGH THE AGES',\n", + " size=16,\n", + " family='Arial',\n", + " fontweight='bold',\n", + " color='white',\n", + " y=0.902);" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['3D chromatin structure', 'DNA accessibility', 'Histone ChIP-seq',\n", + " 'TF ChIP-seq', 'DNA methylation', 'Other', 'RNA binding',\n", + " 'Transcription', 'Knockdown RNA-seq'], dtype=object)" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "expts['Assay type'].unique()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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dKlLJyc3NxcKFC9G3b1/o6+vDzs4O+/fvF4rw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rwYNpsNy5cvR1hYGDp16oS1a9fi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\npEaNGpGXlxfduXOHiIi2b99OgwcPJlVVafny5ULG68VBRMaxY8e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+ "text/plain": [ + "" + ] + }, + "metadata": { + "image/png": { + "height": 563, + "width": 881 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "(\n", + " expts.groupby(['Assay type', 'Date released'])\n", + " .count()\n", + " .unstack('Assay type')['Accession'][cols]\n", + " .resample('M').sum()\n", + " .cumsum()\n", + " .plot.bar(stacked=True, figsize=(15,8), colormap='Spectral')\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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rwYNpsNy5cvR1hYGDp16oS1a9fi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\npEaNGpGXlxfduXOHiIi2b99OgwcPJlVVafny5ULG68VBRMaxY8e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+ "text/plain": [ + "" + ] + }, + "metadata": { + "image/png": { + "height": 563, + "width": 881 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "(\n", + " expts.groupby(['Assay type', 'Date released'])\n", + " .count()\n", + " .unstack('Assay type')['Accession'][cols]\n", + " .resample('M').sum()\n", + " .cumsum()\n", + " .plot.bar(stacked=True, figsize=(15,8), colormap='Spectral')\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "from pylab import *\n", + "\n", + "def rstyle(ax): \n", + " \"\"\"Styles an axes to appear like ggplot2\n", + " Must be called after all plot and axis manipulation operations have been carried out (needs to know final tick spacing)\n", + " \"\"\"\n", + " #set the style of the major and minor grid lines, filled blocks\n", + " ax.grid(True, 'major', color='w', linestyle='-', linewidth=1.4)\n", + " ax.grid(True, 'minor', color='0.92', linestyle='-', linewidth=0.7)\n", + " ax.patch.set_facecolor('0.85')\n", + " ax.set_axisbelow(True)\n", + " \n", + " #set minor tick spacing to 1/2 of the major ticks\n", + " ax.xaxis.set_minor_locator(MultipleLocator( (plt.xticks()[0][1]-plt.xticks()[0][0]) / 2.0 ))\n", + " ax.yaxis.set_minor_locator(MultipleLocator( (plt.yticks()[0][1]-plt.yticks()[0][0]) / 2.0 ))\n", + " \n", + " #remove axis border\n", + " for child in ax.get_children():\n", + " if isinstance(child, matplotlib.spines.Spine):\n", + " child.set_alpha(0)\n", + " \n", + " #restyle the tick lines\n", + " for line in ax.get_xticklines() + ax.get_yticklines():\n", + " line.set_markersize(5)\n", + " line.set_color(\"gray\")\n", + " line.set_markeredgewidth(1.4)\n", + " \n", + " #remove the minor tick lines \n", + " for line in ax.xaxis.get_ticklines(minor=True) + ax.yaxis.get_ticklines(minor=True):\n", + " line.set_markersize(0)\n", + " \n", + " #only show bottom left ticks, pointing out of axis\n", + " rcParams['xtick.direction'] = 'out'\n", + " rcParams['ytick.direction'] = 'out'\n", + " ax.xaxis.set_ticks_position('bottom')\n", + " ax.yaxis.set_ticks_position('left')\n", + " \n", + " \n", + " if ax.legend_ is None:\n", + " lg = ax.legend_\n", + " lg.get_frame().set_linewidth(0)\n", + " lg.get_frame().set_alpha(0.5)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "top_three = expts['Assay type'].value_counts().keys()[:3]\n" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "expts = pd.read_excel('/Users/hitz/encode-prod/Experiments_2017_11_30_perspectives_hacked_alt1.xls')" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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69Rly5coVWb8geZsHOTo64pNPPhGXVQURrly5gh9//FEMJCgUCvj4+GDr1q2I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\nge3V9LDNmpbm3l4A26ypYXs1PWyzpoXt1fg0rwEmRER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WvXToMGDVL//v3lcJSfH6xL28Phw4e1YMECrVq1SocOHVJOTo6SkpLU\npk0b9erVS8OHD1dKSkq5dWzfvl2vv/66Nm7cqGPHjqlRo0Zq1aqVBgwYoJtuuklJSUnlLu/1erVw\n4UItWrRIX3/9tQoLC9W8eXN17NhRgwcP1hVXXGHrc7z66qv67LPPdODAAdWrV08tWrRQnz59NGTI\nEJ111lmVWi/RbPXq1Xr33Xe1bds2HT16VIZhqHHjxurYsaMGDBhQ4TZOvKLDvn37NHDgQOXl5en+\n++/XAw88UGZZYhYe3333nY4cOWKr7HnnnafGjRuXeJ1jWGRs3bpVb7zxhjZu3KjMzEzFx8erRYsW\n6tatm+666y61adOmzGXpX+GxadMmFRUVVXq5hg0bqlOnTiGv0c/Ca9++fZo3b57WrVunAwcOqLi4\nWKmpqbrgggs0aNAg9evXT4ZhlFtHXYsZT2eoA3bu3KlRo0bp6NGjpc53uVx6+OGHdccdd4S5ZbEv\nPz9fvXv3Vm5urq0kwrvvvqsJEybI7XaXOr9JkyZ6/vnn1a1bt1LnFxUV6Q9/+IM++eSTMt+jV69e\nmj59uho1alTq/Lq0PSxdulQTJkxQXl5emWUaNWqk2bNn69JLLy11/pw5czRjxgz5fL5S57du3Vqz\nZs1S+/btS52fnZ2te+65R1u2bCmzDQMHDtRTTz2levXqlTp/9erV+t3vfqf8/PxS5ycmJurPf/6z\nrrvuujLfIxb4fD5NmDBBCxYsKLfcxRdfrL/97W9KTU0tMY94RQev16vhw4dr8+bNklRuEoGYhc/I\nkSO1evVqW2XnzJmjvn37hrzGMSz8TNPUtGnT9PLLL6usr+xxcXGaMWOGrr766hLz6F/hc9VVV+nA\ngQOVXq5bt26aN2+e9Tf9LLz+3//7f3rsscfKTQD16dNHzz//vBISEkqdXxdjRhKhljty5IgGDRqk\nzMxMSVLfvn113XXXqUGDBtq1a5fefPNNHTt2TJL017/+VTfccEMkmxtzJk2apDfeeEOSKkwirF27\nViNHjpTP51NcXJxuvfVWdevWTT6fTxs2bNCCBQvkdruVmJiod999t9SzCg899JDef/99SVKrVq10\n++23q02bNsrMzNQ777xjfWHv1auX/vGPf5TImtal7WHTpk2644475PF4ZBiG+vfvrz59+qhx48Y6\ncuSIFi9erPXr10uSGjRooPfee0+tW7cOqWPhwoV69NFHJUlJSUm67bbb1LlzZxUUFOjTTz/V4sWL\nZZqmmjdvrkWLFpX4Uevz+XTnnXdqw4YNkqT27dtryJAhOvPMM3Xw4EH985//1DfffCNJGjJkiJ56\n6qkSn+Obb77RrbfeqoKCAhmGoRtvvFG9e/dWfHy8tm7dqrfeekv5+flyOp2aO3euunbtWu3rMlxe\neOEFzZ49W5LUrFkzDR48WOedd54k/8HxrbfeUk5OjqSSX7ok4hVNZs2apZkzZ1p/l5VEIGbh1a9f\nP+3bt89W2VOTCBzDIiO4LzVv3lzDhg3Teeedp4KCAi1fvlxLliyR5D+OLVmyRGeccYa1LP0rvKqa\nROjdu7deeuklSfSzcNuwYYPuuusueb1eNWzYULfddpsuuOACeTwe7d69W/Pnz7c+a//+/fXCCy+U\nqKPOxsxErfbQQw+Z6enpZnp6uvnCCy+UmL93717zsssuM9PT080uXbqY2dnZEWhl7MjLyzN37Nhh\nvvnmm+awYcOsdZuenm4+/PDDZS7ndrvNfv36menp6WaHDh3MtWvXliizYsUKq67bbrutxPx169ZZ\n82+88UYzJycnZL7X6zUffPBBq8zbb79doo66tD0MGjTI+qxLliwptcz06dOtMvfee2/IvOPHj5td\nu3Y109PTzYsuusjctWtXieXnzZtnLT9u3LgS8xcsWGDNHzFihFlUVBQyv7CwMGQ7Km27uP322635\nCxcuLDH/yy+/NDt16mSmp6ebV111lel2u8tdL9EqKyvL+hw33HBDqdteVlaWecMNN1jr4/PPP7fm\nEa/osXXrVvP8888P2T+Wtr8hZuFVXFxsdujQwUxPTzdXrVpVqWU5hkXGt99+a8Vs4MCB5rFjx0qU\nefXVV6118uSTT1qv07+i2x//+EczPT3d7Nmzp3nw4EHTNOlnkRD4rtihQwfzq6++KjE/Ozvb/PnP\nf26tj40bN4bMr8sxY2DFWiwjI0OLFy+WJKWnp+u+++4rUaZVq1b6zW9+I0nKzc3V22+/HdY2xpJd\nu3bpkksu0aBBg/TEE09o06ZNtpddtmyZ9u7dK0m69dZbdfnll5co07dvX+usz8aNG7V9+/aQ+S+/\n/LI1PWnSJDVs2DBkvsPh0KOPPqq4uDhJ0quvvhoyvy5tD99++6127NghSbr22ms1YMCAUss9+OCD\nVkZ4xYoVVpZWkt5++22dOHFCkjR69OhSL/W8/fbbrfvLlixZooyMjJD5gZjFxcVp8uTJio+PD5lf\nr1496yyRVDJm27dv1xdffCFJuvLKK3XTTTeVaEOnTp106623SpL279+vjz/+uNTPGu0WL16s4uJi\nSdLDDz9c6uV6qampGjNmjPV3YN1IxCta5Ofna9y4cfJ4PLrsssvKLUvMwmvfvn3yer2SpLZt21Zq\nWY5hkTFnzhx5vV7FxcXphRdeKHWMijvuuENnn322JGn58uXW6/Sv6DV//nwtWrRILpdLM2bMsK4e\noZ+F16FDh6zviv369VPHjh1LlGnUqFHI945TbweryzEjiVCLLVu2TB6PR5J0yy23lDkYx/XXX29N\nl3cvTl1nnsadPx988IE1PXTo0DLLlRWLnJwcrV27VpLUoUMHXXjhhaUu37x5c+t+q++++07ff/+9\nNa8ubQ/BCZ7+/fuXWc7hcKhnz56S/PH98ssvrXmBmLlcLt18882lLm8YhrW+PB6PVq1aZc37+uuv\ntXv3bkn+SxVbtGhRah2dOnWyEhlr164NuWd06dKl1vSQIUPK/By1IWZff/21JP/6Lu0gHHDOOedY\n08ePH7emiVd0ePrpp/XDDz+oZcuWIT8uSkPMwuuHH36Q5P9B2LJly0otyzEs/E6ePKlly5ZJkn7x\ni1+oVatWpZZzOBwaNWqUBg0apB49eljfVehf0Wnbtm2aMmWKJOmBBx5Qly5drHn0s/A6fPiwNd2u\nXbsyywV/7ygsLAyZV5djRhKhFgvc7y2p3C/laWlp1qi427dvL9FB4Jeenq4vvvgi5N+cOXNsLfv5\n559L8p9JDdzjXZrgg0ngHkTJf8Y1sIMoL5aSdMkll4QsF1CXtofgQWVOHefgVA0aNLCmAwMwnjhx\nQjt37pTkvwe0tLM/AWXFzO76ln6Kmdvt1tatW0vU4XA4yj2re8EFF1hniILbEEvi4uLUrl07XXLJ\nJXI6nWWWCx5ZPnC1AvGKDh999JHeeecdORwOPfvssyF961TELPwCSYRWrVqV28dKwzEs/D7//HNr\noLef//zn5Za95ZZbNHXqVE2ZMkWGYdC/olRxcbHGjx8vt9utCy64QKNGjQqZTz8Lr+Az/gcPHiyz\nXOAkh6QSTxGpyzEjiVCL/fe//5Xk/3J+7rnnlls2kIHzer3WZTkI5XQ61bBhw5B/iYmJFS534MAB\nazC48nYwknTmmWdaX7yDs4y7du2ypiuqI/jxLcF11KXtoUuXLho7dqzGjh1b5tmbgMAXLcmf6ZX8\n6ztwNqdDhw7lLh+cva7OmHk8Hn333XeS/Aet8h7BFRcXZ50JOnLkSJkjYEezP/3pT1q8eHGJwRJP\n9eabb1rTPXr0kES8okFGRoYmTpwoSfrNb35T4eBoxCz8/ve//0mS9Tncbre+/vprffHFF9q1a1eZ\nXyg5hkVG8CXPwY//y8jI0JYtW7Rt2zZlZWWVuiz9KzrNmTNHe/bskdPp1KRJk0LOGNPPwu+cc86x\nbgVavHixNXhhsKysLD3//POS/OskeLDZuh4zkgi1lM/ns+5tS0tLq/C5omlpadb0oUOHarRtdU3w\nSL3BoyaXJRCL7Oxs60tdcB1nnnmmreWln2JZ17aHHj16aNSoURo1alSZj8KR/NnbNWvWSPJfkdC5\nc2dJlYtZSkqK6tevLyn00rj9+/db01WJWUZGhvWooMpsN6e2I5YFPn9ubq42btyoBx98UB9++KEk\n6YYbbrAy+8QrskzT1MMPP6zs7Gydf/75ZT7KMRgxC7/AF8bk5GQ98sgj6tatm2688UYNHz5cv/zl\nL3XppZfqgQceCDnrJnEMi5Q9e/ZIkhISEtSsWTOtWLFCv/zlL3XllVdq6NChuvXWW9WjRw8NGTJE\nn376aciy9K/os3v3busJDMOHDy+R3KGfhZ9hGPrzn/+sxMREFRcXa/jw4Ro/frzee+89LVu2TLNn\nz9aAAQOs9frAAw+ErNe6HjPXaS2NqJWdnW1dHlPej6iA4AzxyZMna6xddVHwmYKUlJQKy58ai/r1\n64fUUVE8S4sl20NJa9as0ZgxY6yzNSNGjLCecV3ZmDVo0ECFhYUh6yr4fv2K1nnwZd+BOk5nu6kt\nZ3GmT5+uV155JeQ1wzD029/+Vr/73e+s14hXZL366qtat26d6tevr2nTplmDP5WHmIVf4EqEwGPE\nTlVcXKxly5Zp5cqVeuKJJ3TLLbdI4hgWKYEfBklJSZo5c6ZmzZpVooxpmtq6datGjRqlO++80xqH\nhP4VfaZOnSq3260GDRro3nvvLTGffhYZXbt21YIFCzRmzBh98803evfdd/Xuu++WKPfEE09o2LBh\nIa/V9ZhxJUItFRjlXJL1w6g8wSPuBu7BQ/UIXp+njmxcmtJiEVxHRfEsbXm2h5/k5ubqySef1MiR\nI62Rq3v27Kl77rnHKlOZ9S39tL6ClzvdmJ3OdhMc79rGNE0tWrRIH330kfUa8YqcXbt2afr06ZKk\nsWPH6mc/+5mt5YhZeBUXF4ecderfv7/mz5+vjRs3atu2bfr3v/9tPTfc7XZrwoQJ1kj/HMMiI3B8\nysrK0qxZs5SUlKSHH35Yq1at0ldffaXPPvtMTz75pPXj5fXXX9frr78uif4VbTZu3KjPPvtMknTn\nnXcqNTW1RBn6WWScOHFCs2bN0jfffFNuuenTp5dILtT1mHElQi0VfDmLYRgVlg9ccibJuqwN1SN4\nAKvKxiKwQ6hMHcE7lEAs2R78l3wtXLhQ06dPD8n8Dh48WBMnTpTL9dPusLKDjgXWV/C6qsw6L219\nV8d2E+uGDBmiXr16KT8/X3v27NGyZcu0Y8cOHTx4UGPHjpVhGLruuuuIV4QUFRVp7Nixcrvd6tmz\np371q1/ZXpaYhdfhw4etwfXuvvtu/frXvw6Z37lzZ/31r39Vx44d9cwzz8jn82nSpEm68sorOYZF\nSGA9eL1eJSUl6a233gq5JzotLU1Dhw7Veeedp6FDh8o0Tc2ePVvDhg2jf0WZwD31iYmJuvvuu0st\nQz8Lv6KiIo0aNUpbtmyR5B+4cPTo0broootUr1497d27V++//75effVVnThxwhoUM/BI0roeM5II\ntVTwgH92Rt8MLlPeiNqovISEBGvaTtavtFgE11FRPIPfI7B8Xd8etm7dqqeeesp6HrDkH+hp4sSJ\n6t27d4nyVY1Z8Lo6dZ2Xtx5Li1l1bDexrk2bNtZgW5J0zz336JVXXrF+5PzlL3/RNddcQ7wi5Nln\nn9V3332nlJQUa1R4u4hZeLVu3doa/6U8I0aM0NKlS/Xll1/q0KFD+uKLLziGRUjwbUF33XVXSAIh\n2EUXXaQ+ffpo5cqVysnJ0ebNm+lfUWTz5s3WSPoDBw4MeSJAMPpZ+L399ttWAuGKK67Q//3f/4X8\nqD/33HM1duxYXX755Ro5cqR8Pp+effZZXXfddUpOTq7zMeN2hlqqQYMGVoYp+L62shw7dsyarmhg\nD1ROkyZNrOmyRlIOFohFkyZNrExl8OOZKqojMzPTmg4M9FJXtwev16tnnnlGw4YNsxIIiYmJGjNm\njJYuXVpqAkGqXMyKioqsR0MGD6xzujGr6nYjxXbMKjJixAh17NhRkn9Aop07dxKvCNi1a5feeOMN\nSf5nT+/evVtr164N+Rc80vW+ffus17/77jtiFsWuuuoqa/rbb7/lGBYhwfcuX3HFFeWWDT6W/fDD\nD/SvKDJ//nxrevjw4WWWo5+F33vvvWdNjx8/vswreHr06KGrr75akv+W2EBCtq7HjCRCLWUYhlq3\nbi3JPzhPRRmywL2ScXFxJZ6BitMTfCa1osepFBUVWR28bdu21uvB0/v27Su3juD7XgPL1cXtwePx\n6L777tMrr7win88nwzA0aNAgffzxx7r33nvLvVyyMjELfrZwdcasWbNm1pdIO4/hCbTjjDPOiLnL\nCjMyMvTaa6/ptdde07Zt2yosH/z4wAMHDhCvCAg81kryf0m+++67S/wbN26cVeb999+3Xv/HP/5B\nzKJY06ZNremioiKOYRHSrFkza7q0e+iDBX/GgoIC+leUOHbsmDV+z8UXX1zumDH0s/D74YcfJPkH\nRazo0YjB3zsC8anrMSOJUIsFHlfn9Xr11VdflVmuuLjYesZop06dat29aJGWkpJiPYd2165d5Q4Y\n9OWXX1pPCwg8vk6SLrzwQmu6oh9ZwfOD66hr28O0adO0cuVKSf5M78svv6ypU6eGfEEuS7t27axL\nxIKf1V2astZ3VWIWFxdnxSm4joyMDGuk7tIcOnRIR48eLdGGWHH8+HFNmTJFU6ZMCTkzUJbggYHi\n4+OJVwwiZuG1ceNGff755yG3dJUl+GxXs2bNOIZFSPAjALOzs8stm5uba02npqbSv6LE4sWLrXvQ\nBwwYUG5Z+ln4BWITPCZWWYITW4Fbjep6zEgi1GJXXnmlNf3BBx+UWW7NmjXWPTLBlzGi+gRicfLk\nyRLPcw4WGA1bCo1F586drUe3rFixoswdVXFxsTUC8DnnnBOS4axL28OhQ4c0d+5cSf6d/Pz589Wz\nZ0/by8fHx6t79+6S/JnqnTt3lll2xYoVkvyD2/Tp08d6vVevXtaANx9++GGZy2dlZVn35HXv3j3k\n/ja7MStru4kVZ599tnVQtnMlQuAgKPm3c+IVft27d9fXX39d7r/gz3n//fdbr0+dOpWYhdljjz2m\nO+64QyNGjJDX6y237KpVq6zpwBdVjmHhd+mll1rTq1evLrfs+vXrremLL76Y/hUlPvnkE2u6f//+\nFZann4VX4JaAzMxMHT58uNyygasWpNArEOpyzEgi1GJ9+vRRWlqaJGnhwoUhl8EEFBcXa+bMmZL8\nWbaBAweGtY11xa233moNOva3v/0tZHTUgP379+tf//qXJP8ZiIsuusia53K5dPPNN0vyXx4XfI9d\nsDfeeMPK5g8ZMiRkXl3aHj766CPri/Ljjz+uc845p9J1DB061JoOrJNTbd++XR9//LEkqW/fvtb6\nlfxXP1xzzTWS/BnqZcuWlVrH7NmzrcvPTn0G8S9/+Usr+/3qq69a960Gy8nJ0csvvyzJf9awX79+\ntj5fNElISNDll18uSdqxY4c2btxYZtn169db9yOee+651oGUeMUeYhY+gR+U2dnZeuedd8os98EH\nH1iJvG7dulmXyXIMC7/u3burVatWkqS5c+fqyJEjpZbbt2+fFi1aJMk/unwgZvSvyMrKytKmTZsk\n+Y9Vweu2LPSz8Aoea+TFF18ss9zx48f1/vvvS5IaNmyoyy67zJpXl2PmfOKJJ5447VoQlZxOpxo1\naqTly5fL7XZr7dq16tatmzWIx5EjRzRu3Dhr1Nj7778/JAuNih04cMB6bmyHDh3KPPg1adJE+/fv\n165du3T06FHt2bNHl112mTUq61dffaX77rtPR48elWEYev7550sMeNKhQwe9++67Kigo0Oeff660\ntDR16NBBhmHI7XbrzTff1F/+8hf5fD6de+65+vOf/xwySExd2h6ee+457d+/X/Xr19fNN9+s/fv3\na9++fRX+q1evnjVa7dlnn60NGzbowIED+v7775WTk6NLL73UOmO+Zs0ajRkzRvn5+apXr55efPFF\nK5sc0K5dO73zzjvyeDz6z3/+o/bt21sZ7IKCAs2aNUuvvPKKJKlnz576/e9/H7J8QkKCPB6PNmzY\noLy8PG3dulWXX365kpOTJUn/+9//9Lvf/U7fffedJOnJJ5+0Bh2MNWeeeabVlz777DO1bdtWZ599\ntnVwLi4u1sKFC/XII49YmfrJkydbSQTiFX1OnDhhXRHUrVs364dsADELn5YtW2rBggXy+XxavXq1\nkpOT1b59e+syXrfbrXfffVcTJ06Ux+ORy+XSX//6V7Vo0UISx7BIMAxDZ555ppYuXarCwkKtWrVK\nHTt2DBn8cMeOHbr//vt19OhRM5irqAAAFp9JREFUOZ1OTZ8+3ZpP/4qslStXWmeFr7nmGvXt27fC\nZehn4ZWenq5//etfcrvd2rFjh/Ly8nThhReG3Lqwdu1a/f73v9eBAwckSWPGjFG3bt2s+XU5ZoYZ\nuEEDtdb48eOtL+cOh0OtW7dWfHy89uzZI4/HI8k/su+sWbNC7jVGxT7//HPdcccdkqRBgwZp6tSp\nZZbNy8vTsGHD9M0330jyPyO2bdu2KigoCLlM6sEHH9To0aNLreM///mP7r33XivT2aRJE7Vo0UIH\nDhyw7plMTU3VK6+8ovPPP7/UOurC9nDNNdfYGsjpVFOmTNFNN91k/Z2RkaHBgwdb93ImJiaqTZs2\nys7OtgaBcjqdmjx5sgYNGlRqnQsWLNDjjz9u3QuXlpampk2b6n//+5/y8/MlSa1atdLrr7+uli1b\nllje6/Vq5MiRWrdunST/vXht2rSRaZravXu3Ve/gwYP19NNPV/ozR5Pnn39ef/vb36y/U1JS1LJl\nS5mmqe+//14FBQXWvDFjxujee+8NWZ54RZf9+/dbI1rff//9euCBB0qUIWbh889//lNPPPGE9XkS\nEhJ09tlny+l0hqwrwzD0pz/9qcRZZY5hkfHiiy9qxowZ1t8tWrRQ8+bNlZWVpf3790vyx+zxxx8v\nMfo//Stypk6dqldffVWS9Mwzz9g+80s/C69169Zp9OjROnnypCT/lQFt27ZVfHy89u3bpxMnTlhl\nb7jhBk2bNq3E44zrasy4EqEOuPrqqxUfH68vv/xSRUVFys7O1rFjx+Tz+ZSYmKhf/epXmjx5csgz\niWGP3SsRJP999jfeeKMyMjK0e/duud1uZWZmWqOcp6Wl6bHHHtOdd95ZZh1nn322evbsqa1btyor\nK0sFBQU6evSodY9T9+7dNXPmzDKfJy3Vje3hueeeK/WSsor069cvZDCrpKQk3XDDDdq9e7f27t0r\nt9uto0ePWoNYtW3bVlOmTNF1111XZp3nn3++/n979x0U1fX2AfzLwirSZOwIqFFhLRRFFEz4YRcV\ne4klMTJ2Y4kpmmDUGGOLo05QMdYZE9EELCAoBguIAhGMQOwRo2CJ4CqCwiosLu8fDOfdywIuKCDJ\n9zPDDPecW87u3RXPc895joODA5KSkvDs2TPk5uZCqVRCrVZDJpOhT58+2Lx5s3jiV5JMJoO3tzdU\nKhWuXbuG/Px8ZGZmiqWALC0tMXv2bEkm/NrK3d0dTZo0weXLl6FSqfDixQsolUoolUrxB7Bdu3ZY\nuXIlxowZo3M879fb5VUjEQDes+rk4OAAV1dXpKSkiO/Uo0ePxHsFFH2/1qxZA29vb53j+TesZnTt\n2hXt27fHpUuX8PTpU+Tk5CAjI0N0blq0aIFVq1aV2knl96vm+Pv7i2Hln3/++StX2CjG71n1srW1\nhbe3Nx4+fIjU1FQUFBQgMzMTSqVSTNNp0KAB5s+fj4ULF+oEEID/7j3jSIT/EJVKhbi4OBG5trGx\nQdeuXXWGr1HVy8jIQEJCAtLT02FqaoqWLVuiW7duFfpiJycn48aNG8jKykKTJk3QoUOHcv9xKYmf\nh4q5c+cOEhMT8fDhQ1haWuKdd96Bq6trqX9QSqPRaJCQkIBbt24hNzcXVlZWcHZ2FnNe9ZGdnY24\nuDg8ePAAcrkctra2cHNzE8Pm/i0KCgpw8eJF/PXXX8jOzoZcLkfDhg3h6OhY7hJZ2ni/ah/es+qT\nkpKC5ORkPH78GHXq1EGDBg3QqVMnScKw8vBvWPXTaDRITEzE9evXkZubi/r166NDhw5wdHTU6zvC\n71ftw+9Z9crMzERiYiLu3buH58+fw8LCAnZ2dujUqZPeT+7/S/eMQQQiIiIiIiIi0gtXZyAiIiIi\nIiIivTCIQERERERERER6YRCBiIiIiIiIiPTCIAIRERERERER6YVBBCIiIiIiIiLSC4MIRERERERE\nRKQXBhGIiIiIiIiISC8MIhARERERERGRXhhEICIiIiIiIiK9MIhARERERERERHphEIGIiIiIiIiI\n9MIgAhER0WuKj4+HQqEQP0OGDMHLly9L3ferr74S+02cOLGaW6q/kq/p3r17Nd2kKpWTk4Nly5ah\nb9++cHJygkKhwC+//FLh82g0Gnh6ekreu7Vr11ZBi4mIiGoGgwhERERv2I0bNxAUFFTTzaAKWLp0\nKX755RfcvXsXeXl5AFBmIKg88fHxyMjIkJQdPXoUGo3mjbSTiIiopjGIQEREVAX8/Pzw9OnTmm4G\n6ens2bPidxMTEzg4OKBBgwYVPs/hw4d1ytLT0xEfH/9a7SMiInpbMIhARERUBZ48eQJ/f/+abgbp\nSTvgs2DBAhw8eBCDBg2q0DmeP3+OiIiIUutCQ0Nfq31ERERvCwYRiIiIqsjevXtx69YtvfYtmYPg\njz/+kNTfu3dPUq/9ZFs7z8LXX3+N9PR0+Pr6wtPTE05OTvDy8sKOHTtQWFgItVqNrVu3wtvbG05O\nTnjvvfewdOlSPHny5JVt3L9/P4YPHw5nZ2d069YNU6ZMQVxcXJn7nzt3DnPnzoWHhwccHBzg4eGB\nmTNnIjIystzX37lzZ2g0GuzevVu089q1a3q9j/n5+QgICMDEiRPh7u4OBwcHuLu7Y+LEiQgICEB+\nfr5k/969e0OhUEjKvv32WygUCmzatEmvaxY7efIkVCqV2Pb09BS/Hz9+XEyTKE1eXh527tyJ0aNH\nw8XFBU5OTujXrx9mzJiBkydPljm1Ijw8HJMnT4abmxscHBzQo0cPTJgwAXv37kVOTk6pxyQnJ+Pz\nzz9H79694eTkBBcXFwwYMACLFi3CuXPnJPuOHTtW3BcPDw8UFhZK6l++fImuXbuKfVatWvXa7SMi\norebUU03gIiI6N/Gy8sLERERUKvVWLNmDbZv315t187MzMT48ePxzz//iLLU1FSsW7cOeXl5uHjx\nIqKjo0VdXl4eAgMDkZSUhP3798PY2LjU865du1bylP3FixeIiYlBTEwMFi9erJMkctWqVfjpp58k\nZUqlElFRUYiKisKoUaOwcuVKGBgYlHq9xYsX4+DBgxV67UqlEpMnT8aNGzck5U+ePEFCQgISEhIQ\nFBSEXbt2oXHjxhU6tz60pzK0a9cOPj4+OHPmDICixI2nTp0qdXRDdnY2Jk2apBMouXPnDu7cuYPT\np0/Dw8MD27Ztg5HR///XzdfXF4cOHZIck56ejvT0dFy4cAG7du3C3r17YWVlJer379+PJUuWSIIB\neXl5uH37Nm7fvo2DBw/Cx8cHvr6+AABvb28kJycDKHp/L1++DEdHR3FscnKyZBTH4MGDX6t9RET0\n9uNIBCIiojfs448/RqNGjQAA0dHRoiNZHSIjI/HPP//A2tpap6O8adMmREdHw9zcHG3btoWhoaGo\nu3HjRrmd9oiICBgaGsLe3h7NmzeX1K1Zs0bSAf75558lAQQzMzMoFApYWFiIsoMHD5YZXFGpVKIt\nLVq0gKOjI+rWrVvu63758iXmzp0rCSDUq1cPdnZ2qFevnij766+/MG/ePJHosH379nB2dpacy9bW\nFs7OzmjWrFm519SmVColozL69euHbt26wdzcXJSVNaVh3bp1kvfPysoKCoUCJiYmoiwmJgaBgYFi\nOywsTNJBr1+/Ptq3by/J43D//n2sXr1abGdnZ2P16tUigGBkZIS2bdvCzs5O8lnYvXs30tLSAACD\nBg2S1GkHoIrbVaxFixZwcnKqdPuIiKh2YBCBiIjoDTMzM8Onn34qttesWYOCgoJqubaBgQF27NiB\nyMhIxMTE6IwQcHR0RHR0NI4ePYqgoCBJB/HChQtlntfa2hrh4eEICwtDVFQUvv/+e1FXUFCAnTt3\nAih6qr1lyxZRN2DAAMTExCA0NBSxsbEYP368qNu+fTuePXtW6vUaN26M4OBgnDhxAgcOHEDr1q3L\nfd3Hjh1DUlKS2B47diwSEhJw5MgRnD9/HuPGjRN1iYmJOHbsGADA399fZyWNjz/+GEFBQRgzZky5\n19R29OhRyZQDLy8vyOVy9OjRQ5TFxMSUOm3k+PHj4vdJkybh9OnTCA0NxZkzZ+Di4iLqfvvtt1KP\ncXZ2RkxMDEJCQhAbGyu555GRkWIKR3JyMnJzcwEAcrkcQUFBOHr0KI4cOaITQLp69SoAoFGjRnBz\ncxPlp0+fluynnZBSe5RFZdpHRES1A4MIREREVWDUqFFwcHAAAPz999/Yt29ftVzXzs5OMhd/5MiR\nkvoPP/wQpqamAAAHBwe0adNG1GVnZ5d53k8++QStWrUS28OHD0fPnj3FdvET6cTERNFRlslkWLJk\niRgJUKdOHSxcuBAyWdF/P3JycvD777+Xer1Zs2ahQ4cOr3q5gvZUAhsbGyxduhR16tQBUNRhXrx4\nMWxsbMQ+ISEhep+7otdv1aoV7OzsAAB9+vQR5Wq1GuHh4eWeJyUlBdevX0dhYSHMzc2xYsUK+Pn5\nwc/PD1OnTi31mIcPH+LChQtQq9WQyWSYPXu2OGbdunUiuNG6dWts2LABGzZsgL+/Pzp27FhmO54/\nfy5+156icPnyZTx69AhA0TSRK1eulLpfZdpHRES1A3MiEBERVQEDAwN8/fXX4sn75s2bMWTIkCq/\nrqWlpWRbezg9AJ0h+tr7l9eZc3d31ylzc3MTT6azsrKQnZ2NmzdvinqNRoP33nuv3PZeuXIF/fv3\n1ykvOcXgVS5duiR+7969uyR3AFAUSHB3d8eBAwcAFHWG35SUlBTx5B6A5PV4enpCLpdDrVYDKBrm\n/8EHH0iO9/T0FFMd4uLiMGzYMFhaWqJz585wcXFB3759dUZieHp6iqf9Dx48gI+PD4yNjeHo6IhO\nnTqhV69e6Ny5swjYAEXTNGxtbfH06VOcPXsW69evR1paGtLS0nTySGjr378/li1bhvz8fBQWFuLM\nmTMYOXIk4uLixLQQe3t7ETipbPuIiKh24L/cREREVcTFxUU8nc3OzsbGjRurvQ0lExeWlcjwVerX\nr69Tpp3jAChKtljRjPtZWVl6X6882tMiivNRlKRdXtY0isrQHoUAFOVDKGZmZiaZDpCUlIS7d+9K\n9l+yZAm8vLwk9yYrKwtRUVFYv349Bg4ciJkzZyIjI0PUjxkzBrNmzZIkwnzx4gXOnz+PHTt2YMKE\nCRg6dKhIilhsy5Yt8PDwwGeffYbt27cjIiICqampktErJZmbm0umZRQHjrTzIXh7e0uOqWz7iIjo\n7ceRCERERFVo4cKFiIyMhEqlQmBgINq3b1/qfq/q3GsPL68JSqUStra2krLHjx9Lti0sLCTJAOVy\n+SunJJSVvLCiwQ4zMzMRkCgebl+SdrmZmVmFzl8WjUaDsLAwSdmrcikcPnwYc+bMEdsWFhbYuHEj\n7t69i6ioKMTHx+PChQuS/AlRUVHIzMxEYGCgeG/mz5+PyZMnIzIyEvHx8Th//rwkQJGSkoLp06cj\nLCwMTZs2xaFDh+Dn5wegaGrJvHnz4OnpiTZt2sDAwKDce+Xt7Y0TJ04AAGJjY5Gfny/Jh1AyiFCZ\n9hERUe3AIAIREVEVatq0KaZNmwY/Pz+8fPmyzGH0xfP3i2kvmwcUdbhq0pkzZ3SG4Ws/iba1tUW9\nevXQsmVLUSaXy7F3717I5fIqb1/Hjh0RGxsLoGhKgFqtllxXrVZL8i+Ulw+gIuLj45Genl6hY8LC\nwkQQIT09XfKZGDduHD766CMUFhbi6tWr2Llzp8ij8OeffyItLQ1WVlaSDnz37t0xfPhwAEUrHoSE\nhIhRL9nZ2YiOjsb7778vWS1h9OjRmDZtmth+1eerV69eMDU1RW5uLnJycrBv3z4olUoARVNPtANM\neXl5lWofERHVDpzOQEREVMWmTJkCa2vrcvcp+SQ2ODhYLMWXlZWFrVu3Vln79PHjjz9K8h3s27cP\nCQkJYrt3794AAFdXVzEaQaVSYdOmTWLePACEh4ejX79+4qesxIoVpZ1v4v79+/juu+9E1n+1Wo0V\nK1bg/v37pe7/Okou22hiYlLqj3ZAIzU1FRcvXgRQ1HmfPXu2+CleQtHAwAAdO3bEpEmTJOdXqVTQ\naDSYN2+eOGbHjh2i3traGtOmTRPJM4uPASA6/QBw584dcV8yMjKwfPnycl+nsbEx+vbtK7a1V+Ao\nOQqhsu0jIqLagSMRiIiIqljdunXx5ZdfYt68eWXuY2VlBWtra9HRPX78OHr16gUbGxtcvXpVLM1X\nU5RKJYYMGYI2bdogKytL0iE1NjYWnV0zMzNMnz4dP/zwA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+ "text/plain": [ + "" + ] + }, + "metadata": { + "image/png": { + "height": 647, + "width": 520 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.set(font='Helvetica')\n", + "df = (expts.groupby(['Assay type', 'Date released'])\n", + " .count()\n", + " .unstack('Assay type')['Accession']\n", + " .resample('A').sum()\n", + " .cumsum()\n", + " .fillna(method='ffill')\n", + " .sort_index(ascending=False))\n", + "y_labels = [x.strftime('%Y') for x in df.index]\n", + "with sns.plotting_context(\"notebook\", font_scale=1.5):\n", + " fig, ax = plt.subplots(figsize=(8, 10))\n", + " (\n", + " df.plot(\n", + " colormap='Spectral',\n", + " alpha=0.7,\n", + " ax=ax,\n", + " linewidth=0.8,\n", + " edgecolor='black',\n", + " width=0.8,\n", + " kind='barh',\n", + " stacked=True\n", + " )\n", + " )\n", + " fig.patches.append(\n", + " patches.Rectangle(\n", + " (0, 1),\n", + " 1,\n", + " 0.10,\n", + " color='black',#'#CCCCCC',\n", + " transform=ax.transAxes,\n", + " zorder=-1\n", + " )\n", + " )\n", + " ax.text(\n", + " 0.5,\n", + " 1.0035,\n", + " 'Cumulative Number of ENCODE Assays\\n (human and mouse)',\n", + " ha='center',\n", + " va='bottom',\n", + " color='white',\n", + " transform=ax.transAxes,\n", + " family='Helvetica',\n", + " size=18\n", + " )\n", + " ax.set_yticklabels(y_labels)\n", + " ax.set_ylabel('Year', weight='bold', size=12, family='Helvetica')\n", + " ax.set_xlabel('Number of Assays', weight='bold', size=12, family='Helvetica')\n", + " rstyle(ax)\n", + " savefig('Fig1.png',bbox_inches='tight')" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/hitz/pyvenvs/jupyter/lib/python3.5/site-packages/matplotlib/font_manager.py:1316: UserWarning: findfont: Font family ['Quicksand'] not found. Falling back to DejaVu Sans\n", + " (prop.get_family(), self.defaultFamily[fontext]))\n" + ] + }, + { + "data": { + "image/png": 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LIccvv/xS5FgF6dWrl5o0aWIe265C8XfUu3dvc/9///ufpb/82y7Na5VhGNq3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8+ePYiOjkZmZiaam5vR0NCA69ev4/r16zh+/DgcHR3x+uuvK9wDyd6byC4f3V7aXse2kB2+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\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/zeJMbm4uL730Utcn18TZs2eZNWtWj8QSERERERERuddcppBSW1tLQkICx44dAyA4OJjY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DVTGtZLeVgzZWG9lEEVjRSz2Sxf+/r6dju+85h79+45NFI8jdVfzGYz1q5di+bmZgDAK6+8Ip+4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\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i06ZNWCwWre9KayNGjOCtt95iwoQJXd5n8+bNne4AVFtb2+79ufPOO9sVUlo0NjZy8OBB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5k/fz47duwgIiLCZZ1vv/02mzZtAiAyMpJHH32UsWPHYrFYKCws5PDhw9y4cYOcnBy2bdvG\n6NGjndZz+84HYWFhjBw5kjNnznjV5+zsbB566CG3ZcaMGePVNYQQQgghhBBCCF8KmUTK9u3b9SRK\neno6H3/8MbGxsfr3n3jiCXJycjh06BA//vgja9asITc312ld33zzjZ5EGTx4MFu3bm03g2XevHks\nXbqUXbt2UVlZyfLly/nggw+87sO4ceNYuHAhkyZN0reIavXoo4+yYMEC5s+fT2VlJefOnWPDhg0s\nXrzYaV1nzpzhww8/BBzbJm7ZsqXdzJnZs2eTl5fH6tWrsVgsvPzyy+zcuRNFUTrUFRcXx6xZs0hP\nTyc9PZ1Ro0ZhMpkYNWqUV/298847ycrK8qoOIYQQQgghhBCiJ4XEYrNWq5V169YBjhX7V65c2S6J\nAhAeHs6qVav0NU22bNlCTY3zLRxXr16tH7/22msdHgNSVZVXX31V//rXX39NWVmZV32YN28e27dv\nZ8qUKR2SKK1GjBjBsmXL9Neff/65y/rWrFmjP87z7LPPOn386JlnnmHs2LEAnDp1iqKiIqd1jRs3\njmXLljF79mwyMjIwmUwe90sIIYQQQgghhAglIZFIKS4uprq6GoB7772XkSNHOi0XHx9PdnY24HgU\naN++fR3KlJeXc/bsWQBSUlKYPHmy07r69OnDzJkz9dd79+71qg+3J35cmTRpkp4MunbtGg0NDR3K\nNDQ08O233wIQHR3tcrFWRVF44okn9Nets3CEEEIIIYQQQgjhXEgkUg4fPqwfZ2Zmui3b9vsHDx7s\n8P1Dhw7px/fff79XdfmDwWCgT58++uvGxsYOZUpKSmhubgbgnnvucbuOSiD6IIQQQgghhBBCBKuQ\nWCOl7WM16enpbsvefffd+vH58+e9qmv06NEYDAZsNhsXLlxA0zSna4z4UlVVlT77JiIiwunOPW37\n1Vkf4uLiSEpK4urVq1RXV1NVVUV8fLxvG+1CYWEhhYWFXLlyBZvNRr9+/Rg9ejSTJ09m+vTp7RJG\nQgghhBBCCCFEbxASM1LKy8v146SkJLdlExIS9DVILl261G5b4K7WZTQaGTRoEAAWi4Vff/21C63u\nnh07dujHmZmZqGrHEP7000/6cWd9ANqtAdP2XH8rKyujrKwMi8VCU1MTFRUVHDhwgNdee42srKwO\n21gLIYQQQgghhBCBFhIzUsxms37cr18/t2WNRiPR0dHU1dVhtVqxWCxERUV1qy5wbI187do1AOrr\n60lISOhq8z32888/s379esCxvslTTz3ltFx3+uDsXH9RFIWMjAwmTJjA8OHDiYqKwmw2c+rUKQoK\nCjCbzVRWVrJgwQLWr1/Pfffd57KuI0eO8N1333V6zRarFUVRUBQVVVXdPu4UCKqqoqhKt9plNHZ/\nGKuq0ivfD0VRHP1Suvee9GYKYLgtZqoS+DioavfHhqIoGA2dx8vxOXd/DVVVuj0W/EFBwWB0vgB4\nMPt9jOHxe62oKorS++4Xt3M2xoJdIO6JRqORmJgYkpOT/X4tRVGIjo72+3V6ksFgICYmBlVVe+Q9\n7EkSr+AjMQsuEq/gEBI/aVgsFv04PDy80/Jty9y8ebNdIsXbuvzFYrHw9NNPc+vWLQDmzp2r77jj\nrKyz9rnSU30AGD58OF999RUpKSkdvjdz5kyWLFnC888/T1FREVarleeee459+/a5vJk0Nzc7XXD3\ndkajEau1BdDQNA2bzeplT3xLQwNNw2rt2XZpmuPath6+rnAmsJ9LTfP/2NA0x+fc3TUcZcBmtfmt\nHaKbNE3uF38gmt1OS0uLR//HCiGEEL1BTy4NERKJlFBns9lYsmQJ586dAxzrnuTm5ga4Vd0zcOBA\nt9+PjY0lLy+Pxx57jLKyMmpra9m2bRsLFy50Wt5kMnmUsbVarRiNYYCCoigYDL3ro6+gQOtfHHvy\nukrrX9x72fuhKI4sj6J0ePwu2CmA8x4F9nPpmLHVvTZ4Gi9FcXzO3V3D0Q56zSwQBcWR6AwxjpgB\nCp6PMUXplfeL27keY8ErEPdERVUJCwvrkb+KKiF4rzcYDNjtdlRVxWYLrcSwxCv4SMyCi8QrOPTu\nn4Y8FBkZSV1dHQBNTU2d/jLa1NSkH7edjdJal7NyXa2rurqa77//3uV5iYmJnS4EC2C323nhhRfY\nv38/4JjRsWHDBrczTXzVh0AJDw9n0aJFPPfccwAUFRW5TKRMnDiRiRMndlrnwQ+2/fYXdzt2u12f\n2dNb2O12NLvWpXa1TvW2Wq3dvtna7VqvfD8iIiKwWa0YjMZe1zZvKIpCmNFIy20xs2uBj4Pd3v2x\nERERgc1mxWBwHy/H59z9Nex2DaWLY8FfHPEKo8XaEnI/0DjGmA2D0eDxe63Z7Wha77tftOVqjAW7\nQNwTrVYrZrOZy5cv+/U6BoOB2NhY6urqQuaHa4Dk5GQaGhqIjo72+3vYkyRewUdiFlwkXt5JS0vz\nW923C4lESkxMjJ5IqampcZsMsFqt+jTVsLCwdkmH1rpa1dTUdHrt2tpa/fiOO+7Qj8+fP8/TTz/t\n8rzp06ezYsUKt3VrmsYrr7zC7t27AccHMD8/v9NddbzpQ9tzA2n8+PH68cWLFwPYEiGEEEIIIYQQ\n4nchsWtP2/U2rl696rZsRUWFnt1LTk7usF1xV+qyWq36Tj2RkZH6Dj6+8sYbb7Bz507AsftOfn6+\nR9cYPny4ftxZHwB9sdzbzw2knl4AVwghhBBCCCGE8ERIzEhJS0vj0KFDAJSWljJhwgSXZU+fPq0f\njxw50mldrUpLS5kxY4bLus6ePasnZVJTU9slZSZMmKCvadIdb775Jtu2bQMcWzbn5+e326bYnbb9\nKi0tdVu2urpaT7bExcV1Otulp/TGWTJCCCGEEEIIIURIzEi5//779ePWhIorBw8e1I8zMzP9Wld3\nrVy5ks2bNwMwYMAA8vPzGTp0qMfnjx8/HpPJBEBJSQmNjY0uy/qrD94qKSnRj53t8COEEEIIIYQQ\nQgRCSCRSJkyYQFxcHABHjhzh/PnzTstVVVVRUFAAOBY0nTp1aocyKSkpjBkzBoDy8nKKioqc1tXU\n1KQ/dgMwbdo0r/rQ6t1332Xjxo0A9O/fn/z8/C4nEqKiopg8eTIADQ0N7Nq1y2k5TdPYunWr/jo7\nO7t7jfax5uZm1q1bp79u7YsQQgghhBBCCBFoIZFIMRqNLFq0CHAkB3Jzc/XFZ1s1NTWRm5uLxWIB\nYN68efTr189pfW0XiX399dfbrSECjp0n2n79gQce8MkKwWvXrtUTCHFxcWzatInU1NRu1ZWTk6M/\navTOO+/www8/dCizZs0aTpw4AUBGRgZ/+ctfutdwD126dImPPvpIX+zXmbq6Op555hn9sajY2Fjm\nzp3r13YJIYQQQgghhBCeCok1UgDmzJlDYWEhR48epbS0lIcffpjHH3+cYcOGUVFRwaeffsqFCxcA\nGDFiBDk5OS7rysrKIjs7m4KCAq5evcr06dOZPXs2aWlp1NbW8sUXX3Dy5EnA8ejNiy++6HX7d+zY\nwfvvv6+/njdvHpcuXeLSpUtuzxs3bpw+G6etMWPG8OSTT7JhwwbMZjNz5szhscceY+zYsVgsFgoL\nC/VHlyIjI1m2bJnb62zcuLFDcqpVfX097777bruvDRkyhJkzZ7b7msViYdWqVbz//vtMnDiRjIwM\nkpKSiIiIoL6+nlOnTlFQUKAvLms0Gnnrrbfa7YYkhBBCCCGEEEIEUsgkUkwmE2vXrmXx4sUUFxfz\nyy+/8N5773Uol56ezurVqztdwHTlypUoisKePXuora1t96hJq+TkZPLy8khMTPS6/ceOHWv3Oi8v\nz6PzNm/e7HJx3SVLltDc3MzmzZuxWCz6uittxcfH8/bbbzN69Gi319myZYvLHYDMZnOH92f8+PEd\nEimtmpqaOHDgAAcOHHB5vcGDB7NixQq3CwcLIYQQQgghhBA9LWQSKeB4DGTTpk3s3buXL7/8kjNn\nzlBTU0NsbCwjRozgoYceYsaMGRiNnXfbZDLxzjvv8Mgjj/DZZ59x4sQJqqqqiIqKIiUlhQcffJBZ\ns2YRGRnZAz3rHkVReOmll5g2bRqffPIJJSUlXL9+nfDwcIYOHcrUqVOZM2eO0xkt/pCamsqHH37I\n8ePHOX78ONeuXaOmpgaz2UyfPn2Ij4/n7rvvZsqUKTzwwAP6grlCCCGEEEIIIURvoWiapgW6EUL4\n232D0hgYGUvxr+e5s28UI30wi8iXDly8QGpiFKOSPdviGgAFVEXFrtmhm6P46+M/Mnz4AEaN8HxX\nqJ5gNBrRNDuKomK1WgPdHJ9RFAVVVbDbNdreer8uOknKyGHcddedAWvbV18dZtCQvoxIS+nyuZ7G\nq+ib/0PEoIEMHeH6Gie/LYGYRBKGBe69aKW0GWOh9j+l0WhEs9tRVM/HWPn339HXEMfgwSn+bZwX\nFNqMse7eGHuh7sTLW/X1N/jXP49k6dKlfr2OwWAgNjaWuro6bDabX6/Vk5KTk2loaCA6OprLly8H\nujk+I/EKPhKz4CLx8o4v1i31VEjNSBHClbsfmUJYWBhJxRpNgJaeHugmtTNAgXrAMsj9I1ZtqaqK\nyWSiubkZu93erevGDbFT1wI31aRune8vMVExtLS0EBYWxs3f1swJBa5i1m9gLXV1Gg0NfQLWtn79\nEmi+CUpzfJfPjQz/LV7GMMwW1/EaEJ8EVhhs6OuyTM1ARzIxfUDgZ/v5Yoz1VjExv48xs4djLGxI\nAgBpY5wv1N4bhGrMuhMv7/UjISGhh64lhBBCBBdJpIg/hDfffFMy1kFE/soQXCRewUdiFlxCNV5C\nCCFEsJJEivjDsNlsGAyGQDfDZ1RVbfdvKGn9BUhiFhwkXsFHYhZcQjVeIDELNhKv4CMxCy4Sr+Ah\na6SIP4QbN24EuglCCCGEEEIIIfykf//+PXYtmZEi/jAiIiKoqKgIdDN8RlVVYmJiMJvNIbUWAEBC\nQgK3bt2SmAUJiVfwkZgFl1CNF0jMgo3EK/hIzIKLxMs7kkgRwg8MBkNIPTPfym63h1y/Wqf8ScyC\ng8Qr+EjMgkuoxwskZsFG4hV8JGbBReLV+0kiRfwhLF26lLCwMIqLiwFI72W79rQqLS0FPGufL3en\n6Mp1e0JgdqjwP3cx6y0x6E47uhovT67RG96PUN0BBro/xnpDXNwJ1ZgF+p6YkJDAggULevy6Qggh\nRG8liRTxh3D6iwMMjIzl6q8/cmffKJReujJQ5cULpCZGEfmrBwtMKaAqKqpmBy/7U33lIsOHDyDK\nftW7inxEvWnEpNlRmlWi7NZAN8dnFE1BbVIw2jVuX56q5vplUkYOIzq6MUCt+60dNRUMGtIXzVTl\n8TkWWx2aYqfFpqKZOo9XZdVVIgYN5Jqt1mWZn69fg5hEWiotHrfD15TfxphdsxNqq4kZa5rR7HYU\nVcVq9XyMlV+poK8hjjKlxo+t6z4FBVVVsNs1NG9vjL2I0WjuVrx8ob7+Bv/65x69pBBCCNHrSSJF\n/CEM6BPDojFZnLhRzoCICP73v00NdJOc+p+ff2bQHZEs/49/77SsoigYjUasVmuHX8q76vDZywzq\nH8PKF2d7VY+vREREYLNaMRiN3Lp1K9DN8RlFUQgzGmlxErNDR8sYNCiOlSv/K0Ct+60dh47Rf2Bf\nXlz2vzw+JyIiApvNisHgWbxKvislpn9f5v73Qpdlzh09jRIbR+b8//S4Hb7miFcYLdYWr8dYb+MY\nYzYMRkOXxti1M8eJCutLdtZTfmxd97kbY8EskPfEgm829Oj1hBBCiGAQWvsqCSGEEEIIIYQQQvhR\nyM1I0TSNvXv38uWXX3L27Fmqq6vp27cvqamp/PWvf2X69OkYjZ53+9tvv2XXrl2cOHGCGzduEB0d\nzbBhw3jwwQeZNWsWkZGRPmt7Y2MjR44cobi4mFOnTlFeXo7ZbMZkMjFo0CD+9Kc/8be//Y177723\nS/UeO3aMTz75hJKSEiorKwkPD2fIkCFkZWUxe/Zs4uLiOq3j+vXrnD59mtLSUv3fyspKAJKSkti/\nf79HbfnnP//J3//+d4/bvnz5cmbMmOFxeSGEEEIIIYQQwp9CKpFSV1fH4sWL9QVFW1VWVlJZWUlx\ncTHbt29n9erVDB482G1dzc3NvPDCC+zZs6fd16urq6murubYsWNs3bqVvLw87rrrLq/bvnv3bl59\n9VUslo7rAbS0tHDx4kUuXrzIrl27yMzMZNWqVZ0mQDRNY8WKFeTn57eb4tzY2EhdXR2lpaVs3bqV\nt956y21yZv/+/fzjH//ofueEEEIIIYQQQogQETKJlObmZnJycjh69CgAiYmJzJo1i2HDhlFRUcFn\nn33GhQsXKC0t5amnnmLHjh1ER0e7rC83N5eCggIA+vbty+OPP05aWho1NTXs3r2bkydPcvnyZZ58\n8kl27txJYmKiV+2/cuWKnkQZMGAA9913HxkZGcTFxXHr1i2OHj3Knj17aGpq4uDBg8yfP58dO3YQ\nERHhss63336bTZs2ARAZGcmjjz7K2LFjsVgsFBYWcvjwYW7cuEFOTg7btm1j9OjRTuu5feeDsLAw\nRo4cyZkzZ7zqc3Z2Ng899JDbMmPGjPHqGkIIIYQQQgghhC+FTCJl+/btehIlPT2djz/+mNjYWP37\nTzzxBDk5ORw6dIgff/yRNWvWkJub67Sub775Rk+iDB48mK1bt7abwTJv3jyWLl3Krl27qKysZPny\n5XzwwQde92HcuHEsXLiQSZMm6Xttt3r00UdZsGAB8+fPp7KyknPnzrFhwwYWL17stK4zZ87w4Ycf\nAo5tE7ds2dJu5szs2bPJy8tj9erVWCwWXn75ZXbu3ImiKB3qiouLY9asWaSnp5Oens6oUaMwmUyM\nGjXKq/7eeeedZGVleVWHEEIIIYQQQgjRk0JisVmr1cq6desAx4r9K1eubJdEAQgPD2fVqlX6miZb\ntmyhpsb59o2rV6/Wj1977bUOjwGpqsqrr76qf/3rr7+mrKzMqz7MmzeP7du3M2XKlA5JlFYjRoxg\n2bJl+uvPP//cZX1r1qzRH+d59tlnnT5+9MwzzzB27FgATp06RVFRkdO6xo0bx7Jly5g9ezYZGRmY\nTCaP+yWEEEIIIYQQQoSSkEikFBcXU11dDcC9997LyJEjnZaLj48nOzsbcDwKtG/fvg5lysvLOXv2\nLAApKSlMnjzZaV19+vRh5syZ+uu9e/d61YfbEz+uTJo0SU8GXbt2jYaGhg5lGhoa+PbbbwGIjo52\nuViroig88cQT+uvWWThCCCGEEEIIIYRwLiQSKYcPH9aPMzMz3ZZt+/2DBw92+P6hQ4f04/vvv9+r\nuvzBYDDQp08f/XVjY2OHMiUlJTQ3NwNwzz33uF1HJRB9EEIIIYQQQgghglVIrJHS9rGa9PR0t2Xv\nvvtu/fj8+fNe1TV69GgMBgM2m40LFy6gaZrTNUZ8qaqqSp99ExER4XTnnrb96qwPcXFxJCUlcfXq\nVaqrq6mqqiI+Pt63jXahsLCQwsJCrly5gs1mo1+/fowePZrJkyczffr0dgkjIYQQQgghhBCiNwiJ\nGSnl5eX6cVJSktuyCQkJ+hokly5darctcFfrMhqNDBo0CACLxcKvv/7ahVZ3z44dO/TjzMxMVLVj\nCH/66Sf9uLM+AO3WgGl7rr+VlZVRVlaGxWKhqamJiooKDhw4wGuvvUZWVlaHbayFEEIIIYQQQohA\nC4kZKWazWT/u16+f27JGo5Ho6Gjq6uqwWq1YLBaioqK6VRc4tka+du0aAPX19SQkJHS1+R77+eef\nWb9+PeBY3+Spp55yWq47fXB2rr8oikJGRgYTJkxg+PDhREVFYTabOXXqFAUFBZjNZiorK1mwYAHr\n16/nvvvuc1nXkSNH+O677zq9ZovViqIoKIqKqqpuH3cKJFVVUVSlS+0zGr0fxqqq9Kr3RVEUR7+U\nrr0XwUABDE5ipiq9Iwaq2vUxoigKRoPn8XJ8zt1fQ1WVLo8Ff1BQMBidLwAezH4fY3Qt1qqKogT+\nc+qOqzEWzAJ5TzQajcTExJCcnOy3ayiKQnR0tN/qDwSDwUBMTAyqqvr1vQsEiVfwkZgFF4lXcAiJ\nnzQsFot+HB4e3mn5tmVu3rzZLpHibV3+YrFYePrpp7l16xYAc+fO1XfccVbWWftc6ak+AAwfPpyv\nvvqKlJSUDt+bOXMmS5Ys4fnnn6eoqAir1cpzzz3Hvn37XN5MmpubnS64ezuj0YjV2gJoaJqGzWb1\nsif+oaGBpmG19mz7NM1xbVsPX1fcLvCfTU3z/xjRNMfn3N01HGXAZrX5rR2iGzRN7hV/MJrdTktL\ni0f/1wohhBCB1JNLQ4REIiXU2Ww2lixZwrlz5wDHuie5ubkBblX3DBw40O33Y2NjycvL47HHHqOs\nrIza2lq2bdvGwoULnZY3mUweZWytVitGYxigoCgKBkPv/OgrKND6l8eevK7S+pf33vG+KIriyO4o\nSofH74KdArjuUeA/m46ZW11rR1fjpSiOz7m7azjaQcBngygojgRniHHEDFDo2hhTlF51r3DG/RgL\nToG8JyqqSlhYmF//OqqE4L3eYDBgt9tRVRWbLbQSwhKv4CMxCy4Sr+DQe38S6oLIyEjq6uoAaGpq\n6vSX0KamJv247WyU1rqcletqXdXV1Xz//fcuz0tMTOx0IVgAu93OCy+8wP79+wHHjI4NGza4nWni\nqz4ESnh4OIsWLeK5554DoKioyGUiZeLEiUycOLHTOg9+sO23v7Tbsdvt+sye3sZut6PZNY/a1zrV\n22q1en2ztdu1XvW+REREYLNaMRiNvaZNvqAoCmFGIy1OYmbXekcM7Pauj5GIiAhsNisGg2fxcnzO\n3V/DbtdQPBwL/uKIVxgt1paQ+4HGMcZsGIyGLr3Hmt2OpgX+c+qKuzEWzAJ5T7RarZjNZi5fvuyX\n+g0GA7GxsdTV1YXMD9cAycnJNDQ0EB0d7bf3LhAkXsFHYhZcJF7eSUtL81vdtwuJREpMTIyeSKmp\nqXGbDLBarfr01LCwsHZJh9a6WtXU1HR67draWv34jjvu0I/Pnz/P008/7fK86dOns2LFCrd1a5rG\nK6+8wu7duwHHBzA/P7/TXXW86UPbcwNp/Pjx+vHFixcD2BIhhBBCCCGEEOJ3IbFrT9v1Nq5eveq2\nbEVFhZ7dS05O7rBdcVfqslqt+k49kZGR+g4+vvLGG2+wc+dOwLH7Tn5+vkfXGD58uH7cWR8AfbHc\n288NpJ5eAFcIIYQQQgghhPBESMxISUtL49ChQwCUlpYyYcIEl2VPnz6tH48cOdJpXa1KS0uZMWOG\ny7rOnj2rJ2VSU1PbJWUmTJigr2nSHW+++Sbbtm0DHFs25+fnt9um2J22/SotLXVbtrq6Wk+2xMXF\ndTrbpaf0xlkyQgghhBBCCCFESMxIuf/++/Xj1oSKKwcPHtSPMzMz/VpXd61cuZLNmzcDMGDAAPLz\n8xk6dKjH548fPx6TyQRASUkJjY2NLsv6qw/eKikp0Y+d7fAjhBBCCCGEEEIEQkgkUiZMmEBcXBwA\nR44c4fz5807LVVVVUVBQADgWNJ06dWqHMikpKYwZMwaA8vJyioqKnNbV1NSkP3YDMG3aNK/60Ord\nd99l48aNAPTv35/8/PwuJxKioqKYPHkyAA0NDezatctpOU3T2Lp1q/46Ozu7e432sebmZtatW6e/\nbu2LEEIIIYQQQggRaCGRSDEajSxatAhwJAdyc3P1xWdbNTU1kZubi8ViAWDevHn069fPaX1tF4l9\n/fXX260hAo4dJ9p+/YEHHvDJCsFr167VEwhxcXFs2rSJ1NTUbtWVk5OjP2r0zjvv8MMPP3Qos2bN\nGk6cOAFARkYGf/nLX7rXcA9dunSJjz76SF/s15m6ujqeeeYZ/bGo2NhY5s6d69d2CSGEEEIIIYQQ\nngqJNVIA5syZQ2FhIUePHqW0tJSHH36Yxx9/nGHDhlFRUcGnn37KhQsXABgxYgQ5OTku68qyCQdP\nAAAgAElEQVTKyiI7O5uCggKuXr3K9OnTmT17NmlpadTW1vLFF19w8uRJwPHozYsvvuh1+3fs2MH7\n77+vv543bx6XLl3i0qVLbs8bN26cPhunrTFjxvDkk0+yYcMGzGYzc+bM4bHHHmPs2LFYLBYKCwv1\nR5ciIyNZtmyZ2+ts3LixQ3KqVX19Pe+++267rw0ZMoSZM2e2+5rFYmHVqlW8//77TJw4kYyMDJKS\nkoiIiKC+vp5Tp05RUFCgLy5rNBp566232u2GJIQQQgghhBBCBFLIJFJMJhNr165l8eLFFBcX88sv\nv/Dee+91KJeens7q1as7XcB05cqVKIrCnj17qK2tbfeoSavk5GTy8vJITEz0uv3Hjh1r9zovL8+j\n8zZv3uxycd0lS5bQ3NzM5s2bsVgs+rorbcXHx/P2228zevRot9fZsmWLyx2AzGZzh/dn/PjxHRIp\nrZqamjhw4AAHDhxweb3BgwezYsUKtwsHCyGEEEIIIYQQPS1kEingeAxk06ZN7N27ly+//JIzZ85Q\nU1NDbGwsI0aM4KGHHmLGjBkYjZ1322Qy8c477/DII4/w2WefceLECaqqqoiKiiIlJYUHH3yQWbNm\nERkZ2QM96x5FUXjppZeYNm0an3zyCSUlJVy/fp3w8HCGDh3K1KlTmTNnjtMZLf6QmprKhx9+yPHj\nxzl+/DjXrl2jpqYGs9lMnz59iI+P5+6772bKlCk88MAD+oK5vlDZaGbdmW+4ZWuh8tYt/u/9+3xW\nty/dbGnm13oLL/4//1/nhRVQFRW7ZgfNu+s2NDXz6w0zucv/X+8q8hGj0Yim2VEUFavVGujm+Iyi\nKKiqgt2uoWntg3bzZiO//lpNbm7HBHBPamiwcON6Lctf3ujxOV2Nl+VmI9qNWratWu+yTJPlFhiq\nObjJs6SyPyhtxpjm5RjrbYxGI5rdjqJ2bYw1N97iZkstBd9s8GPruk+hzRjz9sbYi3Q3Xr5QX38D\ncP4otBBCCPFHFVKJFHD8opKdne2zhVMnTZrEpEmTfFKXOytWrGDFihV+qftf/uVf+Jd/+Rev6ti/\nf7/X7TCZTGRmZgZkd6C7H5lCWFgYScUaTYCWnt7jbfDEAAXqAcsg9zOEAFRVxWQy0dzcjN1u9+q6\ncUPs1LXATTXJq3p8JSYqhpaWFsLCwrj526NeocBdzPoNrKWuTqOhoU+AWvdbO/ol0HwTlGbPt0KP\nDP8tXsYwzJbO4zUgPgmsMNjQ12WZmoGO7d7TBwQuWe3LMdbbxMT8PsbMXRhjYUMSAEgb0zt/sQ7V\nmHU3Xr7Rj4SEhB6+phBCCNG7hVwiRQhn3nzzTaKjo7l8+XKgm+IzBoOB2NhY6urqsNlsgW6OTyUn\nJ9PQ0CAxCxISr+AjMQsuoRovIYQQIliFxK49QgghhBBCCCGEED1BZqSIPwybzYbBYAh0M3xGVdV2\n/4aS1r8kS8yCg8Qr+EjMgkuoxgskZsFG4hV8JGbBReIVPBTt9hUPhQhBN27cCHQThBBCCCGEEEL4\nSf/+/XvsWjIjRfxhREREUFFREehm+IyqqsTExGA2m0NqUUWAhIQEbt26JTELEhKv4CMxCy6hGi+Q\nmAUbiVfwkZgFF4mXdySRIoSPLV26lLCwMIqLiwFI76W79gCUlpYCnbfR17tTeHrdnhDYHSr8x5OY\n9YY4dLUN3Y2XJ9cJ5PsRqjvAQM+MsUDELlRjFkz3xISEBBYsWNDl8+x2e0gtENw6dd1gMIRUv1pJ\nvIKPxCy4SLx6P0mkiD+E018cYGBkLFd//ZE7+0ah9OIH2iovXiA1MYrIXzt5NlIBVVFRNTv4oD/V\nVy4yfPgAouxXva/MS+pNIybNjtKsEmW3Bro5PqNoCmqTgtGu4eqpyprrl0kZOYzo6MYebl2bNtRU\nMGhIXzRTlUflLbY6NMVOi01FM3ker8qqq0QMGsg1W63LMj9fvwYxibRUWjyu11eU38aYXbMTag/B\nGmua0ex2FFXFavXPGCu/UkFfQxxlSo1f6ndGQUFVFex2Dc0XN8Zewmg0+z1evlBff4N//XOgWyGE\nEEL4nyRSxB/CgD4xLBqTxYkb5QyIiOB//9vUQDfJpf/5+WcG3RHJ8v/4d7flFEXBaDRitVpd/lLe\nFYfPXmZQ/xhWvjjb67q8FRERgc1qxWA0cuvWrUA3x2cURSHMaKTFTcwOHS1j0KA4Vq78rx5uXZs2\nHDpG/4F9eXHZ//KofEREBDabFYOha/Eq+a6UmP59mfvfC12WOXf0NEpsHJnz/9Pjen3FEa8wWqwt\nPhljvYljjNkwGA1+G2PXzhwnKqwv2VlP+aV+ZzwZY8EoWO6JBd9sCHQThBBCiB4RWssBCyGEEEII\nIYQQQvhRyM1I0TSNvXv38uWXX3L27Fmqq6vp27cvqamp/PWvf2X69OkYjZ53+9tvv2XXrl2cOHGC\nGzduEB0dzbBhw3jwwQeZNWsWkZGRPmt7Y2MjR44cobi4mFOnTlFeXo7ZbMZkMjFo0CD+9Kc/8be/\n/Y177723S/UeO3aMTz75hJKSEiorKwkPD2fIkCFkZWUxe/Zs4uLiOq3j+vXrnD59mtLSUv3fyspK\nAJKSkti/f79HbfnnP//J3//+d4/bvnz5cmbMmOFxeSGEEEIIIYQQwp9CKpFSV1fH4sWL9QVFW1VW\nVlJZWUlxcTHbt29n9erVDB482G1dzc3NvPDCC+zZs6fd16urq6murubYsWNs3bqVvLw87rrrLq/b\nvnv3bl599VUslo7rALS0tHDx4kUuXrzIrl27yMzMZNWqVZ0mQDRNY8WKFeTn57eb4tzY2EhdXR2l\npaVs3bqVt956y21yZv/+/fzjH//ofueEEEIIIYQQQogQETKJlObmZnJycjh69CgAiYmJzJo1i2HD\nhlFRUcFnn33GhQsXKC0t5amnnmLHjh1ER0e7rC83N5eCggIA+vbty+OPP05aWho1NTXs3r2bkydP\ncvnyZZ588kl27txJYmKiV+2/cuWKnkQZMGAA9913HxkZGcTFxXHr1i2OHj3Knj17aGpq4uDBg8yf\nP58dO3YQERHhss63336bTZs2ARAZGcmjjz7K2LFjsVgsFBYWcvjwYW7cuEFOTg7btm1j9OjRTuu5\nfeeDsLAwRo4cyZkzZ7zqc3Z2Ng899JDbMmPGjPHqGkIIIYQQQgghhC+FTCJl+/btehIlPT2djz/+\nmNjYWP37TzzxBDk5ORw6dIgff/yRNWvWkJub67Sub775Rk+iDB48mK1bt7abwTJv3jyWLl3Krl27\nqKysZPny5XzwwQde92HcuHEsXLiQSZMm6VtEtXr00UdZsGAB8+fPp7KyknPnzrFhwwYWL17stK4z\nZ87w4YcfAo5tE7ds2dJu5szs2bPJy8tj9erVWCwWXn75ZXbu3ImiKB3qiouLY9asWaSnp5Oens6o\nUaMwmUyMGjXKq/7eeeedZGVleVWHEEIIIYQQQgjRk0JisVmr1cq6desAx4r9K1eubJdEAQgPD2fV\nqlX6miZbtmyhpsb5loyrV6/Wj1977bUOjwGpqsqrr76qf/3rr7+mrKzMqz7MmzeP7du3M2XKlA5J\nlFYjRoxg2bJl+uvPP//cZX1r1qzRH+d59tlnnT5+9MwzzzB27FgATp06RVFRkdO6xo0bx7Jly5g9\nezYZGRmYTCaP+yWEEEIIIYQQQoSSkEikFBcXU11dDcC9997LyJEjnZaLj48nOzsbcDwKtG/fvg5l\nysvLOXv2LAApKSlMnjzZaV19+vRh5syZ+uu9e/d61YfbEz+uTJo0SU8GXbt2jYaGhg5lGhoa+Pbb\nbwGIjo52uViroig88cQT+uvWWThCCCGEEEIIIYRwLiQSKYcPH9aPMzMz3ZZt+/2DBw92+P6hQ4f0\n4/vvv9+ruvzBYDDQp08f/XVjY2OHMiUlJTQ3NwNwzz33uF1HJRB9EEIIIYQQQgghglVIrJHS9rGa\n9PR0t2Xvvvtu/fj8+fNe1TV69GgMBgM2m40LFy6gaZrTNUZ8qaqqSp99ExER4XTnnrb96qwPcXFx\nJCUlcfXqVaqrq6mqqiI+Pt63jXahsLCQwsJCrly5gs1mo1+/fowePZrJkyczffr0dgkjIYQQQggh\nhBCiNwiJGSnl5eX6cVJSktuyCQkJ+hokly5darctcFfrMhqNDBo0CACLxcKvv/7ahVZ3z44dO/Tj\nzMxMVLVjCH/66Sf9uLM+AO3WgGl7rr+VlZVRVlaGxWKhqamJiooKDhw4wGuvvUZWVlaHbayFEEII\nIYQQQohAC4kZKWazWT/u16+f27JGo5Ho6Gjq6uqwWq1YLBaioqK6VRc4tka+du0aAPX19SQkJHS1\n+R77+eefWb9+PeBY3+Spp55yWq47fXB2rr8oikJGRgYTJkxg+PDhREVFYTabOXXqFAUFBZjNZior\nK1mwYAHr16/nvvvuc1nXkSNH+O677zq9ZovViqIoKIqKqqpuH3cKNFVVUVTF4zYajb4Zxqqq9Jr3\nRlEUR78Uz9+HYKEABjcxU5XAx0FVuzZOFEXBaOh6vByfdffXUVWlS+PB1xQUDEbnC4AHs9/HGH57\nbxVVRVF6/rPc2RgLRsFyTzQajcTExJCcnNyl8xRFITo62k+tCgyDwUBMTAyqqnb5/ejtJF7BR2IW\nXCRewSEkftKwWCz6cXh4eKfl25a5efNmu0SKt3X5i8Vi4emnn+bWrVsAzJ07V99xx1lZZ+1zpaf6\nADB8+HC++uorUlJSOnxv5syZLFmyhOeff56ioiKsVivPPfcc+/btc3kzaW5udrrg7u2MRiNWawug\noWkaNpvVy574j4YGmobV2rNt1DTHtW09fF3hTGA/o5rWM+NE0xyfdXfXcZQBm9Xm17YIP9A0uaf8\nwWh2Oy0tLR79vyyEEEL4Wk8uDRESiZRQZ7PZWLJkCefOnQMc657k5uYGuFXdM3DgQLffj42NJS8v\nj8cee4yysjJqa2vZtm0bCxcudFreZDJ5lLG1Wq0YjWGAgqIoGAy996OvoEDrXx978rpK61/fA//e\nKIriyOwoSofH74KdAnTeo8B+Rh2ztzxvQ3fjpSiOz7q76zjaQsBmhSgojuRmiHHEDFDw3xhTlIDc\nUzwbY8ElWO6JiqoSFhbW5b+kKr28X91hMBiw2+2oqorNFlqJYIlX8JGYBReJV3AI/G9MPhAZGUld\nXR0ATU1Nnf4C2tTUpB+3nY3SWpezcl2tq7q6mu+//97leYmJiZ0uBAtgt9t54YUX2L9/P+CY0bFh\nwwa3M0181YdACQ8PZ9GiRTz33HMAFBUVuUykTJw4kYkTJ3Za58EPtv32V3Y7drtdn9nTG9ntdjS7\n1mkbW6d6W61Wn9xs7Xat17w3ERER2KxWDEZjr2iPryiKQpjRSIubmNm1wMfBbu/aOImIiMBms2Iw\ndC1ejs+6++vY7RqKB+PBHxzxCqPF2hJyP9A4xpgNg9Hgt/dWs9vRtJ79LHsyxoJRsNwTrVYrZrOZ\ny5cve3yOwWAgNjaWurq6kPnhGiA5OZmGhgaio6O79H70dhKv4CMxCy4SL++kpaX5re7bhUQiJSYm\nRk+k1NTUuE0GWK1WfcppWFhYu6RDa12tampqOr12bW2tfnzHHXfox+fPn+fpp592ed706dNZsWKF\n27o1TeOVV15h9+7dgOMDmJ+f3+muOt70oe25gTR+/Hj9+OLFiwFsiRBCCCGEEEII8buQ2LWn7Xob\nV69edVu2oqJCz+4lJyd32K64K3VZrVZ9p57IyEh9Bx9feeONN9i5cyfg2H0nPz/fo2sMHz5cP+6s\nD4C+WO7t5wZSTy+AK4QQQgghhBBCeCIkZqSkpaVx6NAhAEpLS5kwYYLLsqdPn9aPR44c6bSuVqWl\npcyYMcNlXWfPntWTMqmpqe2SMhMmTNDXNOmON998k23btgGOLZvz8/PbbVPsTtt+lZaWui1bXV2t\nJ1vi4uI6ne3SU3rjLBkhhBBCCCGEECIkZqTcf//9+nFrQsWVgwcP6seZmZl+rau7Vq5cyebNmwEY\nMGAA+fn5DB061OPzx48fj8lkAqCkpITGxkaXZf3VB2+VlJTox852+BFCCCGEEEIIIQIhJBIpEyZM\nIC4uDoAjR45w/vx5p+WqqqooKCgAHAuaTp06tUOZlJQUxowZA0B5eTlFRUVO62pqatIfuwGYNm2a\nV31o9e6777Jx40YA+vfvT35+fpcTCVFRUUyePBmAhoYGdu3a5bScpmls3bpVf52dnd29RvtYc3Mz\n69at01+39kUIIYQQQgghhAi0kEikGI1GFi1aBDiSA7m5ufris62amprIzc3FYrEAMG/ePPr16+e0\nvraLxL7++uvt1hABx04Tbb/+wAMP+GSF4LVr1+oJhLi4ODZt2kRqamq36srJydEfNXrnnXf44Ycf\nOpRZs2YNJ06cACAjI4O//OUv3Wu4hy5dusRHH32kL/brTF1dHc8884z+WFRsbCxz5871a7uEEEII\nIYQQQghPhcQaKQBz5syhsLCQo0ePUlpaysMPP8zjjz/OsGHDqKio4NNPP+XChQsAjBgxgpycHJd1\nZWVlkZ2dTUFBAVevXmX69OnMnj2btLQ0amtr+eKLLzh58iTgePTmxRdf9Lr9O3bs4P3339dfz5s3\nj0uXLnHp0iW3540bN06fjdPWmDFjePLJJ9mwYQNms5k5c+bw2GOPMXbsWCwWC4WFhfqjS5GRkSxb\ntsztdTZu3NghOdWqvr6ed999t93XhgwZwsyZM9t9zWKxsGrVKt5//30mTpxIRkYGSUlJREREUF9f\nz6lTpygoKNAXlzUajbz11lvtdkMSQgghhBBCCCECKWQSKSaTibVr17J48WKKi4v55ZdfeO+99zqU\nS09PZ/Xq1Z0uYLpy5UoURWHPnj3U1ta2e9SkVXJyMnl5eSQmJnrd/mPHjrV7nZeX59F5mzdvdrm4\n7pIlS2hubmbz5s1YLBZ93ZW24uPjefvttxk9erTb62zZssXlDkBms7nD+zN+/PgOiZRWTU1NHDhw\ngAMHDri83uDBg1mxYoXbhYOFEEIIIYQQQoieFjKJFHA8BrJp0yb27t3Ll19+yZkzZ6ipqSE2NpYR\nI0bw0EMPMWPGDIzGzrttMpl45513eOSRR/jss884ceIEVVVVREVFkZKSwoMPPsisWbOIjIzsgZ51\nj6IovPTSS0ybNo1PPvmEkpISrl+/Tnh4OEOHDmXq1KnMmTPH6YwWf0hNTeXDDz/k+PHjHD9+nGvX\nrlFTU4PZbKZPnz7Ex8dz9913M2XKFB544AF9wVwhhBBCCCGEEKK3UDRN0wLdCCH87b5BaQyMjKX4\n1/Pc2TeKkT6YReQvBy5eIDUxilHJnWx3rYCqqNg1O/hgFH99/EeGDx/AqBGe7xDlL0ajEU2zoygq\nVqs10M3xGUVRUFUFu13D1a3366KTpIwcxl133dnDrfvdV18dZtCQvoxIS/GofHfjVfTN/yFi0ECG\njnB9nZPflkBMIgnDev79UNqMsVD7n9JoNKLZ7Siq/8ZY+fff0dcQx+DBKX6p3xmFNmPMFzfGXqIn\n4uUL9fU3+Nc/j2Tp0qUen2MwGIiNjaWurg6bzebH1vWs5ORkGhoaiI6O5vLly4Fujs9IvIKPxCy4\nSLy844t1Sz0VUjNShHDl7kemEBYWRlKxRhOgpacHukkuDVCgHrAMcv+4laqqmEwmmpubsdvtXl83\nboiduha4qSZ5XZe3YqJiaGlpISwsjJu/rZkTCjyJWb+BtdTVaTQ09Onh1rVpQ78Emm+C0hzvUfnI\n8N/iZQzDbPE8XgPik8AKgw19XZapGehIKKYP6PnZf74eY71JTMzvY8zspzEWNiQBgLQxzhd294dQ\njVlPxMs3+pGQkBDoRgghhBB+J4kU8Yfw5ptvSsY6iMhfGYKLxCv4SMyCS6jGSwghhAhWkkgRfxg2\nmw2DwRDoZviMqqrt/g0lrb8AScyCg8Qr+EjMgkuoxgskZsFG4hV8JGbBReIVPGSNFPGHcOPGjUA3\nQQghhBBCCCGEn/Tv37/HriUzUsQfRkREBBUVFYFuhs+oqkpMTAxmszmk1gIASEhI4NatWxKzICHx\nCj4Ss+ASqvECiVmwkXgFH4lZcJF4eUcSKUL42NKlSwkLC6O4uBiA9F682Gyr0tJSwHVb/bGoYmfX\n7CnBs7Bi1/gyZr0hVq1t+POf/+zXeHnTV2/ODdWFSyG4xlhXYhiqMQumeHWVq5glJCSwYMGCALbM\nO61T1w0GQ0it19PKbreHVL9CPV4gMQs2Eq/eTxIp4g/h9BcHGBgZy9Vff+TOvlEoQfBAW+Vv2yBH\n/uriGcnftmZVfbT9MUD1lYsMHz6AKPtV31TYTepNIybNjtKsEmXvvVt9dpWiKahNCkY32x97qub6\nZVJGDiM6utFHretGG2oqGDSkLxbbFTTFTotNRTP5Pl6VVVeJGDSQa7baLp/78/VrEJNIS6Wly+eG\n9PbHNc1BsZ0uQPmVCvoa4ihTajotG7rbH5uDJl5d5Sxmjm2UA9wwIYQQwg1JpIg/hAF9Ylg0JosT\nN8oZEBHB//63qYFuUqf+5+efGXRHJMv/49+dfl9RFIxGI1ar1etfylsdPnuZQf1jWPnibJ/U110R\nERHYrFYMRiO3bt0KaFt8SVEUwoxGWnwQs0NHyxg0KI6VK//LR63rRhsOHaP/wL68suL/wmazYjD4\nJ14l35US078vc/97YZfPPXf0NEpsHJnz/7PL5zriFUaLtcVnY6y3cIwxGwajodePsWtnjhMV1pfs\nrKc6LevLMdabhOo9EZzHrOCbDQFulRBCCOFeaC0HLIQQQgghhBBCCOFHITcjRdM09u7dy5dffsnZ\ns2eprq6mb9++pKam8te//pXp06djNHre7W+//ZZdu3Zx4sQJbty4QXR0NMOGDePBBx9k1qxZREZG\n+qztjY2NHDlyhOLiYk6dOkV5eTlmsxmTycSgQYP405/+xN/+9jfuvffeLtV77NgxPvnkE0pKSqis\nrCQ8PJwhQ4aQlZXF7NmziYuL67SO69evc/r0aUpLS/V/KysrAUhKSmL//v0eteWf//wnf//73z1u\n+/Lly5kxY4bH5YUQQgghhBBCCH8KqURKXV0dixcv1hcUbVVZWUllZSXFxcVs376d1atXM3jwYLd1\nNTc388ILL7Bnz552X6+urqa6uppjx46xdetW8vLyuOuuu7xu++7du3n11VexWDo+x9/S0sLFixe5\nePEiu3btIjMzk1WrVnWaANE0jRUrVpCfn99uinNjYyN1dXWUlpaydetW3nrrLbfJmf379/OPf/yj\n+50TQgghhBBCCCFCRMgkUpqbm8nJyeHo0aMAJCYmMmvWLIYNG0ZFRQWfffYZFy5coLS0lKeeeood\nO3YQHR3tsr7c3FwKCgoA6Nu3L48//jhpaWnU1NSwe/duTp48yeXLl3nyySfZuXMniYmJXrX/ypUr\nehJlwIAB3HfffWRkZBAXF8etW7c4evQoe/bsoampiYMHDzJ//nx27NhBRESEyzrffvttNm3aBEBk\nZCSPPvooY8eOxWKxUFhYyOHDh7lx4wY5OTls27aN0aNHO63n9p0PwsLCGDlyJGfOnPGqz9nZ2Tz0\n0ENuy4wZM8arawghhBBCCCGEEL4UMomU7du360mU9PR0Pv74Y2JjY/XvP/HEE+Tk5HDo0CF+/PFH\n1qxZQ25urtO6vvnmGz2JMnjwYLZu3dpuBsu8efNYunQpu3btorKykuXLl/PBBx943Ydx48axcOFC\nJk2apG8R1erRRx9lwYIFzJ8/n8rKSs6dO8eGDRtYvHix07rOnDnDhx9+CDi2TdyyZUu7mTOzZ88m\nLy+P1atXY7FYePnll9m5cyeKonSoKy4ujlmzZpGenk56ejqjRo3CZDIxatQor/p75513kpWV5VUd\nQgghhBBCCCFETwqJxWatVivr1q0DHKu/r1y5sl0SBSA8PJxVq1bpa5ps2bKFmhrnWymuXr1aP37t\ntdc6PAakqiqvvvqq/vWvv/6asrIyr/owb948tm/fzpQpUzokUVqNGDGCZcuW6a8///xzl/WtWbNG\nf5zn2Wefdfr40TPPPMPYsWMBOHXqFEVFRU7rGjduHMuWLWP27NlkZGRgMpk87pcQQgghhBBCCBFK\nQiKRUlxcTHV1NQD33nsvI0eOdFouPj6e7OxswPEo0L59+zqUKS8v5+zZswCkpKQwefJkp3X16dOH\nmTNn6q/37t3rVR9uT/y4MmnSJD0ZdO3aNRoaGjqUaWho4NtvvwUgOjra5WKtiqLwxBNP6K9bZ+EI\nIYQQQgghhBDCuZBIpBw+fFg/zszMdFu27fcPHjzY4fuHDh3Sj++//36v6vIHg8FAnz599NeNjY0d\nypSUlNDc3AzAPffc43YdlUD0QQghhBBCCCGECFYhsUZK28dq0tPT3Za9++679ePz5897Vdfo0aMx\nGAzYbDYuXLiApmlO1xjxpaqqKn32TUREhNOde9r2q7M+xMXFkZSUxNWrV6murqaqqor4+HjfNtqF\nwsJCCgsLuXLlCjabjX79+jF69GgmT57M9OnT2yWMhBBCCCGEEEKI3iAkZqSUl5frx0lJSW7LJiQk\n6GuQXLp0qd22wF2ty2g0MmjQIAAsFgu//vprF1rdPTt27NCPMzMzUdWOIfzpp5/04876ALRbA6bt\nuf5WVlZGWVkZFouFpqYmKioqOHDgAK+99hpZWVkdtrEWQgghhBBCCCECLSRmpJjNZv24X79+bssa\njUaio6Opq6vDarVisViIiorqVl3g2Br52rVrANTX15OQkNDV5nvs559/Zv369YBjfZOnnnrKabnu\n9MHZuf6iKAoZGRlMmDCB4cOHExUVhdls5tSpUxQUFGA2m6msrGTBggWsX7+e++67z2VdR44c4bvv\nvuv0mi1WK4qioCgqqqq6fdypt1BVFUVVOm2r0ei7YayqSq94fxRFcfRL6bz/wUYBDPTqXmsAACAA\nSURBVD6ImaoEPlaq6hhPiqJgNPgvXo6x0L2+qqri0ThyRUHBYHS+AHgw+32M0evHmKKqKIrn8ffV\nGOtNQvmeCB1jZjQaiYmJITk5OXCN8pLBYCAmJgZVVYO6H84oikJ0dHSgm+FToRwvkJgFG4lXcAiJ\nnzQsFot+HB4e3mn5tmVu3rzZLpHibV3+YrFYePrpp7l16xYAc+fO1XfccVbWWftc6ak+AAwfPpyv\nvvqKlJSUDt+bOXMmS5Ys4fnnn6eoqAir1cpzzz3Hvn37XN5MmpubnS64ezuj0YjV2gJoaJqGzWb1\nsif+p6GBpmG19lxbNc1xXVsPXlN4I7CfZU1zjCfH2PLvdejmuHWcCzarzQ8tEz1C0+S+9Aej2e20\ntLR49P+7EEII0aonl4YIiURKqLPZbCxZsoRz584BjnVPcnNzA9yq7hk4cKDb78fGxpKXl8djjz1G\nWVkZtbW1bNu2jYULFzotbzKZPMrYWq1WjMYwQEFRFAyG3v/RV1Cg9a+QPXVNpfUv8IF9fxRFcWR1\nFKXD43fBTgF816PAfpYds7wUx9jyY7wUxTEWutNXRxvp9qwSBcWR1AwxjjEGKPT+MaYoXbov+XaM\n9Q6hfE+EjjFTVJWwsLCg/ouswWDAbrejqio2W2glcpUQ/ByGcrxAYhZsJF7Boff/NumByMhI6urq\nAGhqaur0F8+mpib9uO1slNa6nJXral3V1dV8//33Ls9LTEzsdCFYALvdzgsvvMD+/fsBx4yODRs2\nuJ1p4qs+BEp4eDiLFi3iueeeA6CoqMhlImXixIlMnDix0zoPfrDtt7+e27Hb7frMnt7Mbrej2TWX\nbW2d6m21Wn12s7XbtV7x/kRERGCzWjEYjQFviy8pikKY0UiLD2Jm1wIfK7vdMZ5aZ3kZDP6Jl2Ms\ndK+vdruG4mYcueOIVxgt1paQ+4HGMcZsGIyGXj/GNLsdTfMs/r4cY71JqN4TwXnMrFYrZrOZy5cv\nB7h13ZecnExDQwPR0dFB3Y/bGQwGYmNjqaurC5lfhiB04wUSs2Aj8fJOWlqa3+q+XUgkUmJiYvRE\nSk1NjdtkgNVq1aeKhoWFtUs6tNbVqqamptNr19bW6sd33HGHfnz+/Hmefvppl+dNnz6dFStWuK1b\n0zReeeUVdu/eDTg+gPn5+Z3uquNNH9qeG0jjx4/Xjy9evBjAlgghhBBCCCGEEL8LiV172q63cfXq\nVbdlKyoq9OxecnJyh+2Ku1KX1WrVd+qJjIzUd/DxlTfeeIOdO3cCjt138vPzPbrG8OHD9ePO+gDo\ni+Xefm4g9fQCuEIIIYQQQgghhCdCYkZKWloahw4dAqC0tJQJEya4LHv69Gn9eOTIkU7ralVaWsqM\nGTNc1nX27Fk9KZOamtouKTNhwgR9TZPuePPNN9m2bRvg2LI5Pz+/3TbF7rTtV2lpqduy1dXVerIl\nLi6u09kuPaU3zpIRQgghhBBCCCFCYkbK/fffrx+3JlRcOXjwoH6cmZnp17q6a+XKlWzevBmAAQMG\nkJ+fz9ChQz0+f/z48ZhMJgBKSkpobGx0WdZfffBWSUmJfuxshx8hhBBCCCGEECIQQiKRMmHCBOLi\n4gA4cuQI58+fd1quqqqKgoICwLGg6dSpUzuUSUlJYcyYMQCUl5dTVFTktK6mpib9sRuAadOmedWH\nVu+++y4bN24EoH///uTn53c5kRAVFcXkyZMBaGhoYNeuXU7LaZrG1q1b9dfZ2dnda7SPNTc3s27d\nOv11a1+EEEIIIYQQQohAC4lEitFoZNGiRYAjOZCbm6svPtuqqamJ3NxcLBYLAPPmzaNfv35O62u7\nSOzrr7/ebg0RcOwg0fbrDzzwgE9WCF67dq2eQIiLi2PTpk2kpqZ2q66cnBz9UaN33nmHH374oUOZ\nNWvWcOLECQAyMjL4y1/+0r2Ge+jSpUt89NFH+mK/ztTV1fHMM8/oj0XFxsYyd+5cv7ZLCCGEEEII\nIYTwVEiskQIwZ84cCgsLOXr0KKWlpTz88MM8/vjjDBs2jIqKCj799FMuXLgAwIgRI8jJyXFZV1ZW\nFtnZ2RQUFHD16lWmT5/O7NmzSUtLo7a2li+++IKTJ08CjkdvXnzxRa/bv2PHDt5//3399bx587h0\n6RKXLl1ye964ceP02ThtjRkzhieffJINGzZgNpuZM2cOjz32GGPHjsVisVBYWKg/uhQZGcmyZcvc\nXmfjxo0dklOt6uvreffdd9t9bciQIcycObPd1ywWC6tWreL9999n4sSJZGRkkJSUREREBPX19Zw6\ndYqCggJ9cVmj0chbb73VbjckIYQQQgghhBAikEImkWIymVi7di2LFy+muLiYX375hffee69DufT0\ndFavXt3pAqYrV65EURT27NlDbW1tu0dNWiUnJ5OXl0diYqLX7T927Fi713l5eR6dt3nzZpeL6y5Z\nsoTm5mY2b96MxWLR111pKz4+nrfffpvRo0e7vc6WLVtc7gBkNps7vD/jx4/vkEhp1dTUxIEDBzhw\n4IDL6w0ePJgVK1a4XThYCCGEEEIIIYToaSGTSAHHYyCbNm1i7969fPnll5w5c4aamhpiY2MZMWIE\nDz30EDNmzMBo7LzbJpOJd955h0ceeYTPPvuMEydOUFVVRVRUFCkpKTz44IPMmjWLyMjIHuhZ9yiK\nwksvvcS0adP45JNPKCkp4fr164SHhzN06FCmTp3KnDlznM5o8YfU1FQ+/PBDjh8/zvH/n717D4vq\nyhO9/91VRck1YCECYhCj4AV1euyOJiZqZ0J3jOmnE02HYHTOOMfomyYZezI+ZzBt0knH+ER9YtIJ\nmCcTM2mxRV+1Q6t9xI5vNI93TvDEeEHbCwYv2ETuggUUVbXfPyrsBiluRZVFbX+ff9xFrb32Wvxq\nbeHH2mt98w3Xr1+npqaG+vp6goODiY6OZty4cTzyyCM89thj2oK5QgghhBBCCCFEf6Goqqr6uxFC\n+NpDsSkMDo2k8LsL3BcVRrIXZhH52peXShgRH8aoxE62vVbAoBhwqk7w0ij+/JuLDB8ew6iRPd8l\nyhdMJhOq6kRRDNjtdr+2xZsURcFgUHA6Vfp66/18/0mSkocxevR9Xmpd7/3lL4eJHRrF6LEjfRqv\n/V/8X0JiB3PvyKRen3vyQBFExBM3rPffJ6XNGNPb/5QmkwnV6UQx9P8xVvr1UaKMFoYMSeq2rEKb\nMeatG2M/EEjx6i13Mbt5s5IfPZDMsmXL/Nw6zyUmJtLQ0EB4eDhXrlzxd3O8xmg0EhkZSV1dHQ6H\nw9/N8Rq9xgskZoFG4tU33li3tKd0NSNFiM6Me+oRgoKCSChUaQbU1FR/N6lbMQrcBKyx7h+7MhgM\nmM1mbDYbTqfTK9e0DHVS1wK3DAleqc9TEWERtLS0EBQUxK3v18zRA2/GbODgWurqVBoagr3UOg/a\nMDAO2y0INQ51xcsURL3V+/GKiU4AOwwxRvX63JrBrkRkakzvZw/6Yoz1FxERfx9j9f18jAUNjQMg\nZaz7BeLb0mvMAileveU+ZgOJi4vza7uEEEKIrkgiRdwVVqxYIRnrACJ/ZQgsEq/AIzELLHqNF+g3\nZkIIIfRNEiniruFwODAajf5uhtcYDIZ2/+pJ6w/TErPAIPEKPBKzwKLXeIHELNBIvAKPxCywSLwC\nh6yRIu4KlZWV/m6CEEIIIYQQQggfGTRo0B27lsxIEXeNkJAQysvL/d0MrzEYDERERFBfX6+rtQAA\n4uLiaGxslJgFCIlX4JGYBRa9xgskZoFG4hV4JGaBReLVN5JIEcLLli1bRlBQEIWFhQCkBsBis8XF\nxUDnbfXFoordXfNO0evCit6MWX+IVWsbHnjgAZ/Gq6999fR8vS5cCoE5xnoSR73GLBDj1VNdxSwu\nLo4FCxb4qWV90zp13Wg06nLtF6fTqat+6T1eIDELNBKv/k8SKeKucHr7lwwOjaTsu4vcFxWGEgAP\ntFV8v/1x6HedPCP5/dasBi9uf1x97RLDh8cQ5izzToUeMtwyYVadKDYDYU79bPWpqAqGZgWTF7Y/\nrrlxhaTkYYSHN3mpdR60oaac2KFRWB3XUBUnLQ4Dqtn78aqoKiMkdjDXHbUenX/1xnWIiKelwtqr\n83S9/XGNLeC20y29Vk6U0cJ5pabTMvrd/rg+4OLVU53FzLUFsh8bJoQQQnRBEinirhATHMELY9M4\nUVlKTEgIr/7To/5uUre+unqV2HtCefuff+L2fUVRMJlM2O32Pv9S3urw2SvEDopg1SsZXqnPUyEh\nITjsdowmE42NjX5tizcpikKQyUSLF2J26Nh5YmMtrFr1715qnQdtOHScQYOj+M3K/weHw47R6Jt4\nFR0tJmJQFM/95yKPzj937DRKpIWp8/+tV+e54hVEi73Fa2Osv3CNMQdGkzFgxtj1M98QFhTFzLSF\nnZbx5hjrT/R6T4TOY1bwxTo/tkoIIYTomr6WAxZCCCGEEEIIIYTwId3NSFFVld27d7Njxw7Onj1L\ndXU1UVFRjBgxgp/97GfMmjULk6nn3T5w4AD5+fmcOHGCyspKwsPDGTZsGDNmzCA9PZ3Q0FCvtb2p\nqYkjR45QWFjIqVOnKC0tpb6+HrPZTGxsLD/4wQ/4+c9/zoMPPtireo8fP87WrVspKiqioqKCAQMG\nMHToUNLS0sjIyMBisXRbx40bNzh9+jTFxcXavxUVFQAkJCSwb9++HrXl//yf/8P/+B//o8dtf/vt\nt5k9e3aPywshhBBCCCGEEL6kq0RKXV0dixcv1hYUbVVRUUFFRQWFhYVs3ryZnJwchgwZ0mVdNpuN\npUuXsmvXrnZfr66uprq6muPHj5OXl0d2djajR4/uc9t37tzJ66+/jtXa8Rn+lpYWLl26xKVLl8jP\nz2fq1KmsXr262wSIqqqsXLmS3NzcdtNlm5qaqKuro7i4mLy8PN55550ukzP79u3jl7/8peedE0II\nIYQQQgghdEI3iRSbzUZmZibHjh0DID4+nvT0dIYNG0Z5eTmfffYZJSUlFBcXs3DhQrZs2UJ4eHin\n9WVlZVFQUABAVFQUzz77LCkpKdTU1LBz505OnjzJlStXeP7559m2bRvx8fF9av+1a9e0JEpMTAwP\nPfQQ48ePx2Kx0NjYyLFjx9i1axfNzc0cPHiQ+fPns2XLFkJCQjqtc82aNaxfvx6A0NBQnn76aSZM\nmIDVamXPnj0cPnyYyspKMjMz2bRpE2PGjHFbz+2r6AcFBZGcnMyZM2f61OeZM2fyxBNPdFlm7Nix\nfbqGEEIIIYQQQgjhTbpJpGzevFlLoqSmpvL73/+eyMhI7f158+aRmZnJoUOHuHjxImvXriUrK8tt\nXV988YWWRBkyZAh5eXntZrDMnTuXZcuWkZ+fT0VFBW+//TYffPBBn/swceJEFi1axLRp07Qtolo9\n/fTTLFiwgPnz51NRUcG5c+dYt24dixcvdlvXmTNn+OSTTwDXtokbN25sN3MmIyOD7OxscnJysFqt\nvPbaa2zbtg1FUTrUZbFYSE9PJzU1ldTUVEaNGoXZbGbUqFF96u99991HWlpan+oQQgghhBBCCCHu\nJF0sNmu32/noo48A1+rvq1atapdEARgwYACrV6/W1jTZuHEjNTXut1DMycnRjt94440OjwEZDAZe\nf/117euff/4558+f71Mf5s6dy+bNm3nkkUc6JFFajRw5kuXLl2uv//SnP3Va39q1a7XHeV5++WW3\njx+99NJLTJgwAYBTp06xf/9+t3VNnDiR5cuXk5GRwfjx4zGbzT3ulxBCCCGEEEIIoSe6SKQUFhZS\nXV0NwIMPPkhycrLbctHR0cycORNwPQq0d+/eDmVKS0s5e/YsAElJSUyfPt1tXcHBwTzzzDPa6927\nd/epD7cnfjozbdo0LRl0/fp1GhoaOpRpaGjgwIEDAISHh3e6WKuiKMybN0973ToLRwghhBBCCCGE\nEO7pIpFy+PBh7Xjq1Kldlm37/sGDBzu8f+jQIe344Ycf7lNdvmA0GgkODtZeNzU1dShTVFSEzWYD\n4P777+9yHRV/9EEIIYQQQgghhAhUulgjpe1jNampqV2WHTdunHZ84cKFPtU1ZswYjEYjDoeDkpIS\nVFV1u8aIN1VVVWmzb0JCQtzu3NO2X931wWKxkJCQQFlZGdXV1VRVVREdHe3dRndiz5497Nmzh2vX\nruFwOBg4cCBjxoxh+vTpzJo1q13CSAghhBBCCCGE6A90MSOltLRUO05ISOiybFxcnLYGyeXLl9tt\nC9zbukwmE7GxsQBYrVa+++67XrTaM1u2bNGOp06disHQMYTffvutdtxdH4B2a8C0PdfXzp8/z/nz\n57FarTQ3N1NeXs6XX37JG2+8QVpaWodtrIUQQgghhBBCCH/TxYyU+vp67XjgwIFdljWZTISHh1NX\nV4fdbsdqtRIWFuZRXeDaGvn69esA3Lx5k7i4uN42v8euXr3Kxx9/DLjWN1m4cKHbcp70wd25vqIo\nCuPHj2fy5MkMHz6csLAw6uvrOXXqFAUFBdTX11NRUcGCBQv4+OOPeeihhzqt68iRIxw9erTba7bY\n7SiKgqIYMBgMXT7u1F8YDAYUg9JtW00m7w1jg0HpF98fRVFc/VK673+gUQCjF2JmUPwfK4PBNZ4U\nRcFk9F28XGPB874aDEqPxpI7CgpGk/sFwAPZ38cYATPGFIMBRen+c+CtMdaf6PmeCO5jZjKZiIiI\nIDEx0T+N6iOj0UhERAQGgyFg+9AZRVEIDw/3dzO8Ss/xAolZoJF4BQZd/KRhtVq14wEDBnRbvm2Z\nW7dutUuk9LUuX7Farbz44os0NjYC8Nxzz2k77rgr6659nblTfQAYPnw4f/nLX0hKSurw3jPPPMOS\nJUv4X//rf7F//37sdjv/8R//wd69ezu9mdhsNrcL7t7OZDJht7cAKqqq4nDY+9gT31NRQVWx2+9c\nW1XVdV3HHbym6Av/fpZV1TWeXGPLt9ehD+PWdT447A4vt0zcUaoq96e7iOp00tLS0qP/44UQQgjg\nji4NoYtEit45HA6WLFnCuXPnANe6J1lZWX5ulWcGDx7c5fuRkZFkZ2fzi1/8gvPnz1NbW8umTZtY\ntGiR2/Jms7lHGVu73Y7JFAQoKIqC0dj/P/oKCrT+FfJOXVNp/Qu8f78/iqK4sjqK0uHxu0CnAN7r\nkX8/y65ZXoprbPkwXoriGgue9tXVTjyaWaKguJKaOuMaY4BC4IwxRenR/cm7Y6x/0PM9EdzHTDEY\nCAoKCti/yhqNRpxOJwaDAYdDX0lcRYefQz3HCyRmgUbiFRj6/2+TPRAaGkpdXR0Azc3N3f7i2dzc\nrB23nY3SWpe7cr2tq7q6mq+//rrT8+Lj47tdCBbA6XSydOlS9u3bB7hmdKxbt67LmSbe6oO/DBgw\ngBdeeIH/+I//AGD//v2dJlKmTJnClClTuq3z4Aebvv/ruROn06nN7OnPnE4nqlPttK2tU73tdrvX\nbrZOp9ovvj8hISE47HaMJpPf2+JNiqIQZDLR4oWYOVX/x8rpdI2n1lleRqNv4uUaC5731elUUboY\nS51xxSuIFnuL7n6gcY0xB0aTMWDGmOp0oqpdfw68Ocb6E73eE6HzmNntdurr67ly5YofW+e5xMRE\nGhoaCA8PD9g+uGM0GomMjKSurk43vwyBfuMFErNAI/Hqm5SUFJ/VfTtdJFIiIiK0REpNTU2XyQC7\n3a5NEw0KCmqXdGitq1VNTU23166trdWO77nnHu34woULvPjii52eN2vWLFauXNll3aqq8pvf/Iad\nO3cCrg9gbm5ut7vq9KUPbc/1p0mTJmnHly5d8mNLhBBCCCGEEEKIv9PFrj1t19soKyvrsmx5ebmW\n3UtMTOywXXFv6rLb7dpOPaGhodoOPt7y5ptvsm3bNsC1+05ubm6PrjF8+HDtuLs+ANpiubef6093\negFcIYQQQgghhBCiJ3QxIyUlJYVDhw4BUFxczOTJkzste/r0ae04OTnZbV2tiouLmT17dqd1nT17\nVkvKjBgxol1SZvLkydqaJp5YsWIFmzZtAlxbNufm5rbbprgrbftVXFzcZdnq6mot2WKxWLqd7XKn\n9MdZMkIIIYQQQgghhC5mpDz88MPacWtCpTMHDx7UjqdOnerTujy1atUqNmzYAEBMTAy5ubnce++9\nPT5/0qRJmM1mAIqKimhqauq0rK/60FdFRUXasbsdfoQQQgghhBBCCH/QRSJl8uTJWCwWAI4cOcKF\nCxfclquqqqKgoABwLWj66KOPdiiTlJTE2LFjASgtLWX//v1u62pubtYeuwF4/PHH+9SHVu+99x6f\nfvopAIMGDSI3N7fXiYSwsDCmT58OQENDA/n5+W7LqapKXl6e9nrmzJmeNdrLbDYbH330kfa6tS9C\nCCGEEEIIIYS/6SKRYjKZeOGFFwBXciArK0tbfLZVc3MzWVlZWK1WAObOncvAgQPd1td2kdjf/va3\n7dYQAdcOEm2//thjj3llheAPP/xQSyBYLBbWr1/PiBEjPKorMzNTe9To3Xff5a9//WuHMmvXruXE\niRMAjB8/nh//+MeeNbyHLl++zH//939ri/26U1dXx0svvaQ9FhUZGclzzz3n03YJIYQQQgghhBA9\npYs1UgDmzJnDnj17OHbsGMXFxTz55JM8++yzDBs2jPLycv74xz9SUlICwMiRI8nMzOy0rrS0NGbO\nnElBQQFlZWXMmjWLjIwMUlJSqK2tZfv27Zw8eRJwPXrzyiuv9Ln9W7Zs4f3339dez507l8uXL3P5\n8uUuz5s4caI2G6etsWPH8vzzz7Nu3Trq6+uZM2cOv/jFL5gwYQJWq5U9e/Zojy6FhoayfPnyLq/z\n6aefdkhOtbp58ybvvfdeu68NHTqUZ555pt3XrFYrq1ev5v3332fKlCmMHz+ehIQEQkJCuHnzJqdO\nnaKgoEBbXNZkMvHOO++02w1JCCGEEEIIIYTwJ90kUsxmMx9++CGLFy+msLCQv/3tb/zud7/rUC41\nNZWcnJxuFzBdtWoViqKwa9cuamtr2z1q0ioxMZHs7Gzi4+P73P7jx4+3e52dnd2j8zZs2NDp4rpL\nlizBZrOxYcMGrFartu5KW9HR0axZs4YxY8Z0eZ2NGzd2ugNQfX19h+/PpEmTOiRSWjU3N/Pll1/y\n5Zdfdnq9IUOGsHLlyi4XDhZCCCGEEEIIIe403SRSwPUYyPr169m9ezc7duzgzJkz1NTUEBkZyciR\nI3niiSeYPXs2JlP33Tabzbz77rs89dRTfPbZZ5w4cYKqqirCwsJISkpixowZpKenExoaegd65hlF\nUfj1r3/N448/ztatWykqKuLGjRsMGDCAe++9l0cffZQ5c+a4ndHiCyNGjOCTTz7hm2++4ZtvvuH6\n9evU1NRQX19PcHAw0dHRjBs3jkceeYTHHntMWzBXCCGEEEIIIYToLxRVVVV/N0IIX3soNoXBoZEU\nfneB+6LCSPbCLCJf+/JSCSPiwxiV2Mm21woYFANO1QleGsWff3OR4cNjGDWy57tE+YLJZEJVnSiK\nAbvd7te2eJOiKBgMCk6nSl9vvZ/vP0lS8jBGj77PS63rvb/85TCxQ6MYPXakT+O1/4v/S0jsYO4d\nmeTR+ScPFEFEPHHDeve9UtqMMb39T2kymVCdThRD4Iyx0q+PEmW0MGRIUqdlFNqMMW/dGPuBQIxX\nT3UWs5s3K/nRA8ksW7bMj63zXGJiIg0NDYSHh3PlyhV/N8drjEYjkZGR1NXV4XA4/N0cr9FrvEBi\nFmgkXn3jjXVLe0pXM1KE6My4px4hKCiIhEKVZkBNTfV3k7oVo8BNwBrr/rErg8GA2WzGZrPhdDq9\nck3LUCd1LXDLkOCV+jwVERZBS0sLQUFB3Pp+zRw98GbMBg6upa5OpaEh2Eut86ANA+Ow3YJQ41BX\nvExB1Fu9H6+Y6ASwwxBjlEfn1wx2JSNTY3o3g9AXY6y/iIj4+xirD5AxFjQ0DoCUse4Xigf9xiwQ\n49VTncdsIHFxcX5rlxBCCNEVSaSIu8KKFSskYx1A5K8MgUXiFXgkZoFFr/EC/cZMCCGEvkkiRdw1\nHA4HRqPR383wGoPB0O5fPWn9YVpiFhgkXoFHYhZY9BovkJgFGolX4JGYBRaJV+CQNVLEXaGystLf\nTRBCCCGEEEII4SODBg26Y9eSGSnirhESEkJ5ebm/m+E1BoOBiIgI6uvrdbUWAEBcXByNjY0SswAh\n8Qo8ErPAotd4gcQs0Ei8Ao/ELLBIvPpGEilCeNmyZcsICgqisLAQgNQAWGy2uLgY6LytvlhUsbtr\n3il6XVjRmzHrL7ECV7yOHTuG0Whk5MiRPrtOX/vc2/P1unAp6GeM3R5TvcZML/Fyx9OYxcXFsWDB\nAh+2rG9ap64bjUZdrv3idDp11S+9xwskZoFG4tX/SSJF3BVOb/+SwaGRlH13kfuiwlAC4IG2iu+3\nPw79rpNnJL/fmtXgxe2Pq69dYvjwGMKcZd6p0EOGWybMqhPFZiDMqZ+tPhVVwdCsYPLC9sc1N66Q\nlDyM8PAmL7XOc0ajnYqKMuISB6Kaq3x2nYqqMkJiB3PdUevR+VdvXIeIeFoqrD0qr+vtj2tsuthO\nt/RaOVFGC+eVGkDP2x/X6yJe7ngSM9fWyD5umBBCCNEFSaSIu0JMcAQvjE3jRGUpMSEhvPpPj/q7\nSd366upVYu8J5e1//onb9xVFwWQyYbfb+/xLeavDZ68QOyiCVa9keKU+T4WEhOCw2zGaTDQ2Nvq1\nLd6kKApBJhMtXojZoWPniY21sGrVv3updZ4LCQlh//5jxAyO4pXl/9Nn1yk6WkzEoCie+89FHp1/\n7thplEgLU+f/W4/Ku+IVRIu9xWtjrL9wjTEHRpMxoMfY9TPfEBYUxcy0hYB3x1h/otd7IngWs4Iv\n1vm4VUIIIUTX9LUcsBBCCCGEEEIIIYQP6W5Giqqq7N69mx07dnD27Fmqq6uJBKAr7wAAIABJREFU\niopixIgR/OxnP2PWrFmYTD3v9oEDB8jPz+fEiRNUVlYSHh7OsGHDmDFjBunp6YSGhnqt7U1NTRw5\ncoTCwkJOnTpFaWkp9fX1mM1mYmNj+cEPfsDPf/5zHnzwwV7Ve/z4cbZu3UpRUREVFRUMGDCAoUOH\nkpaWRkZGBhaLpds6bty4wenTpykuLtb+raioACAhIYF9+/Z51Of6+np27tzJ3r17uXTpElVVVYSG\nhhIdHc3o0aN54IEH+OlPf0pUVJRH9QshhBBCCCGEEN6kq0RKXV0dixcv1hYUbVVRUUFFRQWFhYVs\n3ryZnJwchgwZ0mVdNpuNpUuXsmvXrnZfr66uprq6muPHj5OXl0d2djajR4/uc9t37tzJ66+/jtXa\n8dn9lpYWLl26xKVLl8jPz2fq1KmsXr262wSIqqqsXLmS3NzcdtNlm5qaqKuro7i4mLy8PN55550u\nkzP79u3jl7/8peed60RBQQErVqzosDWxzWajtraWkpISdu3ahcViIS0tzevXF0IIIYQQQggheks3\niRSbzUZmZibHjh0DID4+nvT0dIYNG0Z5eTmfffYZJSUlFBcXs3DhQrZs2UJ4eHin9WVlZVFQUABA\nVFQUzz77LCkpKdTU1LBz505OnjzJlStXeP7559m2bRvx8fF9av+1a9e0JEpMTAwPPfQQ48ePx2Kx\n0NjYyLFjx9i1axfNzc0cPHiQ+fPns2XLFkJCQjqtc82aNaxfvx6A0NBQnn76aSZMmIDVamXPnj0c\nPnyYyspKMjMz2bRpE2PGjHFbz+2r6AcFBZGcnMyZM2c87u8f/vAH3nrrLa2+tLQ0fvjDHxIdHY3D\n4aCsrIyvv/6ao0ePenwNIYQQQgghhBDC23STSNm8ebOWRElNTeX3v/89kZGR2vvz5s0jMzOTQ4cO\ncfHiRdauXUtWVpbbur744gstiTJkyBDy8vLazWCZO3cuy5YtIz8/n4qKCt5++20++OCDPvdh4sSJ\nLFq0iGnTpmlbRLV6+umnWbBgAfPnz6eiooJz586xbt06Fi9e7LauM2fO8MknnwCubRM3btzYbuZM\nRkYG2dnZ5OTkYLVaee2119i2bRuKonSoy2KxkJ6eTmpqKqmpqYwaNQqz2cyoUaM86ueRI0e0JMq4\nceN4//33GTp0qNuyt27d0t0OBUIIIYQQQgghApcuFpu12+189NFHgGv191WrVrVLogAMGDCA1atX\na2uabNy4kZqaGrf15eTkaMdvvPFGh8eADAYDr7/+uvb1zz//nPPnz/epD3PnzmXz5s088sgjHZIo\nrUaOHMny5cu113/60586rW/t2rXa4zwvv/yy28ePXnrpJSZMmADAqVOn2L9/v9u6Jk6cyPLly8nI\nyGD8+PGYzeYe9+t2NpuNV199FXAlqXJzcztNogCEhYV1iKUQQgghhBBCCOEvukikFBYWUl1dDcCD\nDz5IcnKy23LR0dHMnDkTcP1Cv3fv3g5lSktLOXv2LABJSUlMnz7dbV3BwcE888wz2uvdu3f3qQ89\nTRZMmzZNSwZdv36dhoaGDmUaGho4cOAAAOHh4cyePdttXYqiMG/ePO116ywcXyooKKCsrAyAX/3q\nV10+XiWEEEIIIYQQQvQ3ukikHD58WDueOnVql2Xbvn/w4MEO7x86dEg7fvjhh/tUly8YjUaCg4O1\n101NTR3KFBUVYbPZALj//vu7XEflTvchPz8fALPZzIwZM3x+PSGEEEIIIYQQwpt0sUZK28dqUlNT\nuyw7btw47fjChQt9qmvMmDEYjUYcDgclJSWoqup2jRFvqqqq0mbfhISEuN25p22/uuuDxWIhISGB\nsrIyqqurqaqqIjo62ruN/l5LSwsnTpwAIDk5meDgYL799ls2bNjAoUOHKC8vJzQ0lMTERKZPn868\nefNk22MhhBBCCCGEEP2KLmaklJaWascJCQldlo2Li9PWILl8+XK7bYF7W5fJZCI2NhYAq9XKd999\n14tWe2bLli3a8dSpUzEYOobw22+/1Y676wPQbg2Ytud628WLF7UZNPHx8Wzfvp2nnnqKTZs2ceXK\nFW3b45MnT5Kdnc1PfvKTdjOEhBBCCCGEEEIIf9PFjJT6+nrteODAgV2WNZlMhIeHU1dXh91ux2q1\nEhYW5lFd4Noa+fr16wDcvHmTuLi43ja/x65evcrHH38MuNY3WbhwodtynvTB3bneVlFRoR2fP3+e\nL7/8EofDwaRJk5gxYwYDBw6krKyMHTt2cOHCBW7evMkLL7xAXl4e//AP/+C2ziNHjvRoi+QWux1F\nUVAUAwaDocvHnfoLg8GAYlC6bavJ5L1hbDAo/eL7oyiKq19K9/0PNApg9ELMDEr/iBWAoqDNxvNl\ne1xjwvM+GwxKj8ZUWwoKRpP7BcAD2d/HmG9j5muKwYCitP9MeGuM9Sd6vidC72NmMpmIiIggMTHR\nd43qI6PRSEREBAaDoV+30xOKouhujTs9xwskZoFG4hUYdPGThtVq1Y4HDBjQbfm2ZW7dutUukdLX\nunzFarXy4osv0tjYCMBzzz2n7bjjrqy79nXmTvWhbZLmypUrACxZsoRFixa1K/ev//qvLF26lD//\n+c+0tLTwyiuvsGvXLrePTdlsNrcL7t7OZDJht7cAKqqq4nD0/y2VVVRQ1Tu6/bOquq7rkC2nA0T/\n+Syrqu/Hlqq6xoSn13CdDw67w8stE36jqnLPugupTictLS09+v9fCCHE3aPtWqK+potEit45HA6W\nLFnCuXPnANe6J1lZWX5uVe85nc52r6dMmdIhiQKupMdbb71FUVER5eXllJSUcPjwYbeL/5rN5h5l\nbO12OyZTEKCgKApGY///6Cso0PpXyDt1TaX1L/D+/f4oiuLK6ihKh8fvAp0CeK9H/eOz3Dojxddj\nS3FdyONruNpIr2aYKCiupKbOuMYYoBDYY0xROtyzvDvG+gc93xOh9zFTDAaCgoL69V9sjUYjTqcT\ng8GAw6Gv5K2iw8+hnuMFErNAI/EKDP7/CdwLQkNDqaurA6C5ubnbXzybm5u147azUVrrcleut3VV\nV1fz9ddfd3pefHx8twvBgiv5sHTpUvbt2wfA8OHDWbduXZczTbzVB2+7ve709PROywYHB/Pkk0/y\nX//1XwAcPXrUbSJlypQpTJkypdtrH/xg0/d/MXfidDq1mT39mdPpRHWqnba1daq33W732s3W6VT7\nxfcnJCQEh92O0WTye1u8SVEUgkwmWrwQM6faP2IFrni19seX7XGNCc/77HSqKF2Mqdu54hVEi71F\ndz/QuMaYA6PJ2C8+Q55SnU5U9e+fCW+Osf5Er/dE8Cxmdrud+vp6bXZrf5SYmEhDQwPh4eH9up29\nZTQaiYyMpK6uTje/DIF+4wUSs0Aj8eqblJQUn9V9O10kUiIiIrRESk1NTZfJALvdrk0FDQoKapd0\naK2rVU1NTbfXrq2t1Y7vuece7fjChQu8+OKLnZ43a9YsVq5c2WXdqqrym9/8hp07dwKuD2Bubm63\nu+r0pQ9tz/W2tt8faL+DkjttE01Xr171SZuEEEIIIYQQQoje0MWuPUlJSdpxWVlZl2XLy8u17F5i\nYmKHdTd6U5fdbtd26gkNDdV28PGWN998k23btgGu3Xdyc3N7dI3hw4drx931AdAWy739XG+7ve7u\npuS2Ter4chFcIYQQQgghhBCip3QxIyUlJUXbJre4uJjJkyd3Wvb06dPacXJystu6WhUXFzN79uxO\n6zp79qyWlBkxYkS7pMzkyZO1NU08sWLFCjZt2gS4tmzOzc1tt01xV9r2q7i4uMuy1dXVWrLFYrF0\nO9ulL6Kjoxk0aBCVlZUANDQ0dLmrUNvkiS9nygghhBBCCCGEED2lixkpbdfOaE2odObgwYPa8dSp\nU31al6dWrVrFhg0bAIiJiSE3N5d77723x+dPmjQJs9kMQFFREU1NTZ2W9VUfOjNt2jTtuG1Sy522\nSaC2M4WEEEIIIYQQQgh/0UUiZfLkyVgsFgCOHDnChQsX3JarqqqioKAAcG35++ijj3Yok5SUxNix\nYwEoLS1l//79butqbm7WHrsBePzxx/vUh1bvvfcen376KQCDBg0iNze310mEsLAwpk+fDrhmfeTn\n57stp6oqeXl52uuZM2d61uheeOKJJ7TjrVu3dlquqamJHTt2aK/vRJJHCCGEEEIIIYToji4SKSaT\niRdeeAFwJQeysrK0xWdbNTc3k5WVhdVqBWDu3LmdPlbSdpHY3/72t+3WEAHXzhFtv/7YY495ZYXg\nDz/8kI8++ghwPWazfv16RowY4VFdmZmZ2qNG7777Ln/96187lFm7di0nTpwAYPz48fz4xz/2rOG9\n8PDDD/OjH/0IcCW9Pv744w5lHA4Hr732GuXl5QBMmDCB+++/3+dtE0IIIYQQQgghuqOLNVIA5syZ\nw549ezh27BjFxcU8+eSTPPvsswwbNozy8nL++Mc/UlJSAsDIkSPJzMzstK60tDRmzpxJQUEBZWVl\nzJo1i4yMDFJSUqitrWX79u2cPHkScD1688orr/S5/Vu2bOH999/XXs+dO5fLly9z+fLlLs+bOHGi\nNhunrbFjx/L888+zbt066uvrmTNnDr/4xS+YMGECVquVPXv2aI8uhYaGsnz58i6v8+mnn3ZITrW6\nefMm7733XruvDR06lGeeecZt+TfffJPnnnuO2tpa1qxZw8GDB5kxYwYWi4Xr16+zfft2zp8/D7hm\n13S3u5EQQgghhBBCCHGn6CaRYjab+fDDD1m8eDGFhYX87W9/43e/+12HcqmpqeTk5HS7eOmqVatQ\nFIVdu3ZRW1urzRRpKzExkezsbOLj4/vc/uPHj7d7nZ2d3aPzNmzY0OniukuWLMFms7FhwwasVqu2\n7kpb0dHRrFmzhjFjxnR5nY0bN3a6A1B9fX2H78+kSZM6TaSMGDGCdevW8fLLL3Pt2jW++uorvvrq\nqw7l4uPjycnJ8XhWjhBCCCGEEEII4W26SaQAREZGsn79enbv3s2OHTs4c+YMNTU1REZGMnLkSJ54\n4glmz56NydR9t81mM++++y5PPfUUn332GSdOnKCqqoqwsDCSkpKYMWMG6enphIaG3oGeeUZRFH79\n61/z+OOPs3XrVoqKirhx4wYDBgzg3nvv5dFHH2XOnDluZ7T42oQJE/jzn//Mtm3b2LNnD6WlpdTV\n1REeHk5KSgppaWmkp6cTHBx8x9smhBBCCCGEEEJ0RlFVVfV3I4TwtYdiUxgcGknhdxe4LyqMZC/M\nIvK1Ly+VMCI+jFGJnWx7rYBBMeBUneClUfz5NxcZPjyGUSN7vkuUL5hMJlTViaIYsNvtfm2LNymK\ngsGg4HSq9PXW+/n+kyQlD2P06Pu81DrPmUwm/vf/PkBc4kBGjEz02XX2f/F/CYkdzL0jkzw6/+SB\nIoiIJ25Yz75nSpsxprf/KU0mE6rTiWII7DFW+vVRoowWhgxJAkChzRjz1o2xH9BLvNzxJGY3b1by\noweSWbZsmY9b57nExEQaGhoIDw/nypUr/m6O1xiNRiIjI6mrq8PhcPi7OV6j13iBxCzQSLz6xhvr\nlvaUrmakCNGZcU89QlBQEAmFKs2Amprq7yZ1K0aBm4A11v1jVwaDAbPZjM1mw+l0euWalqFO6lrg\nliHBK/V5KiIsgpaWFoKCgrhVX+/XtniTN2M2cHAtdXUqDQ3+n7UVERFBTEwC2IwotmifXScmOgHs\nMMQY5dH5NYNdScnUmJ7NJPTFGOsvIiL+PsbqA3iMBQ2NAyBlrGvxeL3GTC/xcsezmA0kLi7Op+0S\nQgghuiKJFHFXWLFihWSsA4j8lSGwSLwCj8QssOg1XqDfmAkhhNA3SaSIu4bD4cBoNPq7GV5jMBja\n/asnrT9MS8wCg8Qr8EjMAote4wUSs0Aj8Qo8ErPAIvEKHLJGirgrVFZW+rsJQgghhBBCCCF8ZNCg\nQXfsWjIjRdw1QkJCKC8v93czvMZgMBAREUF9fb2u1gIAiIuLo7GxUWIWICRegUdiFlj0Gi+QmAUa\niVfgkZgFFolX30giRQgfMBqNunz+2ul06q5frVP+JGaBQeIVeCRmgUXv8QKJWaCReAUeiVlgkXj1\nf5JIEXeFZcuWERQURGFhIQCpAbBrT3FxMdB5W32xO0V317xT9LpDhS93FPFn7LqK151qV1+u09m5\net0BBmSMtdVf7ntd0Wu8wP/jLC4ujgULFtzx6wohhAhskkgRd4XT279kcGgkZd9d5L6oMJQAWBmo\n4lIJI+LDCP2uk8WmFDAoBgyqE7zUn+prlxg+PIYwZ5l3KvSQ4ZYJs+pEsRkIc9r92hZvUlQFQ7OC\nyani7eWpam5cISl5GOHhTV6ttyeMRjuK4sRgMBAe3j5eNTXlxA6NQjVX+bQNFVVlhMQO5rqjttfn\nXr1xHSLiaamwtvu68v0Yc6pO9LaamKnGhup0ohgM2O06GmMexKz0WjlRRgvnlRrfNq4PTKZ6XcYL\nQEHBYFBwOlVUb/1n1kM3b1byowfu6CWFEELohCRSxF0hJjiCF8amcaKylJiQEF79p0f93aRufXX1\nKrH3hPL2P//E7fuKomAymbDb7V77pfzw2SvEDopg1SsZXqnPUyEhITjsdowmE42NjX5tizcpikKQ\nyUSLF2PW6tCx88TGWli16t+9Wm9PhISE4HDYMRo7xuvQoeMMGhzFK8v/p0/bUHS0mIhBUTz3n4t6\nfe65Y6dRIi1Mnf9v7b7uilcQLfYWr8fL31xjzIHRZNThGOtdzK6f+YawoChmpi30ces8p9d7Ivj2\nvtidgi/W3dHrCSGE0A997askhBBCCCGEEEII4UO6m5Giqiq7d+9mx44dnD17lurqaqKiohgxYgQ/\n+9nPmDVrFiZTz7t94MAB8vPzOXHiBJWVlYSHhzNs2DBmzJhBeno6oaGhXmt7U1MTR44cobCwkFOn\nTlFaWkp9fT1ms5nY2Fh+8IMf8POf/5wHH3ywV/UeP36crVu3UlRUREVFBQMGDGDo0KGkpaWRkZGB\nxWLpto4bN25w+vRpiouLtX8rKioASEhIYN++fR71ub6+np07d7J3714uXbpEVVUVoaGhR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Kl2tGme/HrqK4xlzTebrSJ1db6ZOzIpq4xhigoMMxpriS0H2NonT5mqrnayL0peui93iK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VFRNDQ04Ha7A90cv0lMTKSpqYmIiAjKy8sD3Ry/kXj1jz/WLe0pQ81IEaIzkx5/EIvFQmNjo/7c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\ntSHYTL9H2e12Y7lZs2YNlncvc/HixTodKU2tK1TsdjuPPvooly5dAuDHP/6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i9+7drFmz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+ "text/plain": [ + "" + ] + }, + "metadata": { + "image/png": { + "height": 1764, + "width": 553 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.set(font='Quicksand')\n", + "df = (expts.groupby(['Assay type', 'Date released'])\n", + " .count()\n", + " .unstack('Assay type')['Accession']\n", + " .resample('M').sum()\n", + " .cumsum()\n", + " .fillna(method='ffill')\n", + " .sort_index(ascending=False))\n", + "y_labels = [x.strftime('%M-%Y') for x in df.index]\n", + "with sns.plotting_context(\"notebook\", font_scale=1.5):\n", + " fig, ax = plt.subplots(figsize=(8, 30))\n", + " (\n", + " df.plot(\n", + " colormap='Spectral',\n", + " alpha=0.7,\n", + " ax=ax,\n", + " linewidth=0.8,\n", + " edgecolor='black',\n", + " width=0.8,\n", + " kind='barh',\n", + " stacked=True\n", + " )\n", + " )\n", + " fig.patches.append(\n", + " patches.Rectangle(\n", + " (0, 1),\n", + " 1,\n", + " 0.05,\n", + " color='black',#'#CCCCCC',\n", + " transform=ax.transAxes,\n", + " zorder=-1\n", + " )\n", + " )\n", + " ax.text(\n", + " 0.5,\n", + " 1.0035,\n", + " 'ENCODE assays by Month',\n", + " ha='center',\n", + " va='bottom',\n", + " color='white',\n", + " transform=ax.transAxes,\n", + " family='Quicksand',\n", + " size=18\n", + " )\n", + " ax.set_yticklabels(y_labels)\n", + " ax.set_ylabel('Month', weight='bold', size=12, family='Quicksand')\n", + " ax.set_xlabel('Total Count', weight='bold', size=12, family='Quicksand')\n", + " rstyle(ax)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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/vlim5ORkoUKFCgIAwczMTNb/xZw5c3TKz8TERFi9erX6D9L/k5KSIkyaNKnQ8wEg1KlT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\nkMOXF8XHhxcfr17dwsP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oV/fRs+6i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\nItLL/wOezFJ8lDh3/QAAAABJRU5ErkJggg==\n", + "text/plain": [ + "" + ] + }, + "metadata": { + "image/png": { + "height": 647, + "width": 520 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.set(font='Helvetica')\n", + "df = (expts.groupby(['Assay type', 'Date released'])\n", + " .count()\n", + " .unstack('Assay type')['Accession']\n", + " .resample('2A').sum()\n", + " .cumsum()\n", + " .fillna(method='ffill')\n", + " .sort_index(ascending=False))\n", + "y_labels = [x.strftime('%Y') for x in df.index]\n", + "with sns.plotting_context(\"notebook\", font_scale=1.5):\n", + " fig, ax = plt.subplots(figsize=(8, 10))\n", + " (\n", + " df.plot(\n", + " colormap='Spectral',\n", + " alpha=0.7,\n", + " ax=ax,\n", + " linewidth=0.8,\n", + " edgecolor='black',\n", + " width=0.8,\n", + " kind='barh',\n", + " stacked=True\n", + " )\n", + " )\n", + " fig.patches.append(\n", + " patches.Rectangle(\n", + " (0, 1),\n", + " 1,\n", + " 0.10,\n", + " color='black',#'#CCCCCC',\n", + " transform=ax.transAxes,\n", + " zorder=-1\n", + " )\n", + " )\n", + " ax.text(\n", + " 0.5,\n", + " 1.0035,\n", + " 'Cumulative Number of ENCODE Assays\\n (human and mouse)',\n", + " ha='center',\n", + " va='bottom',\n", + " color='white',\n", + " transform=ax.transAxes,\n", + " family='Helvetica',\n", + " size=18\n", + " )\n", + " ax.set_yticklabels(y_labels)\n", + " ax.set_ylabel('Year', weight='bold', size=12, family='Helvetica')\n", + " ax.set_xlabel('Number of Assays', weight='bold', size=12, family='Helvetica')\n", + " rstyle(ax)\n", + " savefig('Fig1-take2.png',bbox_inches='tight')" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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/vlim5ORkoUKFCgIAwczMTNb/xZw5c3TKz8TERFi9erX6D9L/k5KSIkyaNKnQ8wEg1KlT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\n5uaK2/bs2YOioiIAwN/+9jeDwxWef/55+Pn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0bS7927t9sTAVxxnHnenDlzjATC3/72N/373/92u6ivW7euRo0apVtv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\ns8/kdDpls9k0ffp09ezZU02bNlX79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+ "text/plain": [ + "" + ] + }, + "metadata": { + "image/png": { + "height": 647, + "width": 520 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.set(font='Helvetica')\n", + "df = (expts.groupby(['Assay type', 'Date released'])\n", + " .count()\n", + " .unstack('Assay type')['Accession']\n", + " .resample('A').sum()\n", + " .cumsum()\n", + " .fillna(method='ffill')\n", + " .sort_index(ascending=False))\n", + "\n", + "ddf = df.drop(index=datetime.datetime.strptime('2012-12-31','%Y-%m-%d'))\n", + "y_labels = [x.strftime('%Y') for x in df.index]\n", + "with sns.plotting_context(\"notebook\", font_scale=1.5):\n", + " fig, ax = plt.subplots(figsize=(8, 10))\n", + " (\n", + " ddf.plot(\n", + " colormap='Spectral',\n", + " alpha=0.7,\n", + " ax=ax,\n", + " linewidth=0.8,\n", + " edgecolor='black',\n", + " width=0.8,\n", + " kind='barh',\n", + " stacked=True\n", + " )\n", + " )\n", + " fig.patches.append(\n", + " patches.Rectangle(\n", + " (0, 1),\n", + " 1,\n", + " 0.10,\n", + " color='black',#'#CCCCCC',\n", + " transform=ax.transAxes,\n", + " zorder=-1\n", + " )\n", + " )\n", + " ax.text(\n", + " 0.5,\n", + " 1.0035,\n", + " 'Cumulative Number of ENCODE Assays\\n (human and mouse)',\n", + " ha='center',\n", + " va='bottom',\n", + " color='white',\n", + " transform=ax.transAxes,\n", + " family='Helvetica',\n", + " size=18\n", + " )\n", + " ax.set_yticklabels(y_labels)\n", + " ax.set_ylabel('Year', weight='bold', size=12, family='Helvetica')\n", + " ax.set_xlabel('Number of Assays', weight='bold', size=12, family='Helvetica')\n", + " rstyle(ax)\n", + " savefig('Fig1-take3.png',bbox_inches='tight')" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "hier = pd.read_csv('/Users/hitz/encode-prod/Experiments_2017_11_30_hierarchical.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "hier['Date released'] = hier['Date released'].apply(lambda x: pd.to_datetime(x))" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Accession object\n", + "award.rfa object\n", + "award.pi.title object\n", + "Unnamed: 3 float64\n", + "Target label object\n", + "Target gene object\n", + "Biosample summary object\n", + "Biosample object\n", + "Lab object\n", + "Project object\n", + "Species object\n", + "Biosample type object\n", + "Date released datetime64[ns]\n", + "Month released object\n", + "Assay category object\n", + "Assay Type object\n", + "Assay name object\n", + "Assay sub-class object\n", + "dtype: object" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "hier.dtypes\n" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Accessionaward.rfaaward.pi.titleUnnamed: 3Target labelTarget geneBiosample summaryBiosampleLabProjectSpeciesBiosample typeDate releasedMonth releasedAssay categoryAssay TypeAssay nameAssay sub-class
0ENCSR618GKPENCODE3Richard MyersNaNNaNNaNC57BL/6 limb embryo (12.5 days)limbAli Mortazavi, UCIENCODEMus musculustissue2017-08-15August, 2017TranscriptionRNA-seqmicroRNA-seqmicroRNA-seq
1ENCSR000EANENCODE2Michael SnyderNaNRELARELAGM12892 treated with tumor necrosis factorGM12892Michael Snyder, StanfordENCODEHomo sapiensimmortalized cell line2011-10-29October, 2011DNA bindingChIP-seqChIP-seqTF ChIP-seq
2ENCSR668MJXENCODE3Brenton GraveleyNaNGRSF1GRSF1HepG2HepG2Gene Yeo, UCSDENCODEHomo sapiensimmortalized cell line2016-04-26April, 2016RNA bindingeCLIPeCLIPRNA binding protein
3ENCSR000ARYENCODE2Bradley BernsteinNaNH3K9acHIST2H3CDND-41DND-41Bradley Bernstein, BroadENCODEHomo sapiensimmortalized cell line2012-03-06March, 2012DNA bindingChIP-seqChIP-seqHistone ChIP-seq
4ENCSR290RXIENCODE3Thomas GingerasNaNNaNNaNmyometrial cell female adult (34 years)myometrial cellThomas Gingeras, CSHLENCODEHomo sapiensprimary cell2015-08-18August, 2015TranscriptionRNA-seqRAMPAGERAMPAGE
5ENCSR000EJHENCODE2Gregory CrawfordNaNNaNNaNGM13977GM13977Gregory Crawford, DukeENCODEHomo sapiensimmortalized cell line2012-08-28August, 2012DNA accessibilityDNase-seqDNase-seqDNase-seq
6ENCSR861GYEENCODE3Brenton GraveleyNaNLIN28BLIN28BHepG2HepG2Gene Yeo, UCSDENCODEHomo sapiensimmortalized cell line2015-11-09November, 2015RNA bindingeCLIPeCLIPRNA binding protein
7ENCSR000CGKENCODE2-MouseBing RenNaNH3K4me3Hist2h3c1B10.H-2aH-4bp/Wts CH12.LXCH12.LXBing Ren, UCSDENCODEMus musculusimmortalized cell line2012-09-05September, 2012DNA bindingChIP-seqChIP-seqHistone ChIP-seq
8ENCSR082DIFENCODE3David GilbertNaNNaNNaNprimitive gut cell originated from CyT49primitive gut cellDavid Gilbert, FSUENCODEHomo sapiensin vitro differentiated cells2015-07-21July, 2015Replication timingRepli-chipRepli-chipRepli-chip
9ENCSR000APLENCODE2Bradley BernsteinNaNH3K9me3HIST2H3CosteoblastosteoblastBradley Bernstein, BroadENCODEHomo sapiensprimary cell2011-02-10February, 2011DNA bindingChIP-seqChIP-seqHistone ChIP-seq
10ENCSR000FALENCODE2Michael SnyderNaNPOLR2APOLR2ANB4NB4Sherman Weissman, YaleENCODEHomo sapiensimmortalized cell line2011-10-29October, 2011DNA bindingChIP-seqChIP-seqTF ChIP-seq
11ENCSR963HARENCODE3Bradley BernsteinNaNH3K27me3HIST2H3CKarpas-422Karpas-422Bradley Bernstein, BroadENCODEHomo sapiensimmortalized cell line2014-07-11July, 2014DNA bindingChIP-seqChIP-seqHistone ChIP-seq
12ENCSR000ESYENCODE2-MouseMichael SnyderNaNMAFKMafkDBA/2 MEL cell line treated with dimethyl sulf...MEL cell lineMichael Snyder, StanfordENCODEMus musculusimmortalized cell line2012-06-15June, 2012DNA bindingChIP-seqChIP-seqTF ChIP-seq
13ENCSR000CLUENCODE2-MouseJohn StamatoyannopoulosNaNNaNNaNB6D2F1/J 416B416BJohn Stamatoyannopoulos, UWENCODEMus musculusimmortalized cell line2012-07-10July, 2012TranscriptionRNA-seqpolyA mRNA RNA-seqpolyA mRNA RNA-seq
14ENCSR900AQLENCODE3Michael SnyderNaNKHSRPKHSRPK562 genetically modified using CRISPRK562Michael Snyder, StanfordENCODEHomo sapiensimmortalized cell line2017-11-18November, 2017TranscriptionKnockdown RNAseqCRISPRi RNA-seqRNA binding protein
15ENCSR046FQXENCODE3Michael SnyderNaNLDB1LDB1K562 genetically modified using CRISPRK562Michael Snyder, StanfordENCODEHomo sapiensimmortalized cell line2017-11-18November, 2017TranscriptionKnockdown RNAseqCRISPRi RNA-seqtranscription factor
16ENCSR171RTNENCODE3Michael SnyderNaNCTBP1CTBP1K562 genetically modified using CRISPRK562Michael Snyder, StanfordENCODEHomo sapiensimmortalized cell line2017-11-18November, 2017TranscriptionKnockdown RNAseqCRISPRi RNA-seqtranscription factor
17ENCSR000ADPENCODE2-MouseMichael SnyderNaNH3K27me3Hist2h3c1DBA/2 MEL cell lineMEL cell lineMichael Snyder, StanfordENCODEMus musculusimmortalized cell line2012-08-20August, 2012DNA bindingChIP-seqChIP-seqHistone ChIP-seq
18ENCSR000EJUENCODE2Gregory CrawfordNaNNaNNaNhepatocytehepatocyteGregory Crawford, DukeENCODEHomo sapiensprimary cell2011-04-19April, 2011DNA accessibilityDNase-seqDNase-seqDNase-seq
19ENCSR000ADRENCODE2-MouseMichael SnyderNaNH3K4me3Hist2h3c1DBA/2 MEL cell lineMEL cell lineMichael Snyder, StanfordENCODEMus musculusimmortalized cell line2012-08-20August, 2012DNA bindingChIP-seqChIP-seqHistone ChIP-seq
20ENCSR288LNFENCODE3Bing RenNaNH3K4me2Hist2h3c1C57BL/6 stomach postnatal (0 days)stomachBing Ren, UCSDENCODEMus musculustissue2014-06-30June, 2014DNA bindingChIP-seqChIP-seqHistone ChIP-seq
21ENCSR000ELNENCODE2Gregory CrawfordNaNNaNNaNHGPS cellHGPS cellGregory Crawford, DukeENCODEHomo sapiensimmortalized cell line2011-04-19April, 2011DNA accessibilityDNase-seqDNase-seqDNase-seq
22ENCSR450BNZENCODE3Thomas GingerasNaNNaNNaNPeyer's patch female adult (51 year)Peyer's patchThomas Gingeras, CSHLENCODEHomo sapienstissue2016-05-03May, 2016TranscriptionRNA-seqtotal RNA-seqtotal RNA-seq
23ENCSR471RUKENCODE3Thomas GingerasNaNNaNNaNstomach male adult (37 years)stomachThomas Gingeras, CSHLENCODEHomo sapienstissue2016-08-04August, 2016TranscriptionRNA-seqtotal RNA-seqtotal RNA-seq
24ENCSR464UVOENCODE3Thomas GingerasNaNNaNNaNheart left ventricle female adult (53 years)heart left ventricleThomas Gingeras, CSHLENCODEHomo sapienstissue2016-08-05August, 2016TranscriptionRNA-seqRAMPAGERAMPAGE
25ENCSR779BVZENCODE3Thomas GingerasNaNNaNNaNesophagus squamous epithelium female adult (51...esophagus squamous epitheliumThomas Gingeras, CSHLENCODEHomo sapienstissue2016-06-13June, 2016TranscriptionRNA-seqsmall RNA-seqsmall RNA-seq
26ENCSR634VLAENCODE3Thomas GingerasNaNNaNNaNright lobe of liver female adult (53 years)right lobe of liverThomas Gingeras, CSHLENCODEHomo sapienstissue2016-08-05August, 2016TranscriptionRNA-seqsmall RNA-seqsmall RNA-seq
27ENCSR000EMJENCODE2John StamatoyannopoulosNaNNaNNaNB cell female adult (43 years)B cellJohn Stamatoyannopoulos, UWENCODEHomo sapiensprimary cell2011-10-19October, 2011DNA accessibilityDNase-seqDNase-seqDNase-seq
28ENCSR882ZTSENCODE3Michael SnyderNaNeGFP-ZBTB11ZBTB11HEK293 genetically modified using site-specifi...HEK293Michael Snyder, StanfordENCODEHomo sapiensimmortalized cell line2016-10-07October, 2016DNA bindingChIP-seqChIP-seqTF ChIP-seq
29ENCSR000CHOENCODE2-MouseBing RenNaNNaNNaNC57BL/6 bone marrow macrophage male adult (8 w...bone marrow macrophageBing Ren, UCSDENCODEMus musculusprimary cell2012-05-04May, 2012TranscriptionRNA-seqpolyA mRNA RNA-seqpolyA mRNA RNA-seq
30ENCSR000CPPENCODE2Thomas GingerasNaNNaNNaNHeLa-S3 cytosolic fractionHeLa-S3Thomas Gingeras, CSHLENCODEHomo sapiensimmortalized cell line2011-10-17October, 2011TranscriptionRNA-seqpolyA mRNA RNA-seqpolyA mRNA RNA-seq
31ENCSR966RAGENCODE3Bing RenNaNH3K9acNaNC57BL/6 liver postnatal (0 days)liverBing Ren, UCSDENCODEMus musculustissue2014-06-30June, 2014DNA bindingChIP-seqChIP-seqHistone ChIP-seq
32ENCSR000DAVENCODE2John StamatoyannopoulosNaNNaNNaNfibroblast of pedal digit skin female adult (2...fibroblast of pedal digit skinJohn Stamatoyannopoulos, UWENCODEHomo sapiensprimary cell2011-04-01April, 2011Transcriptiontranscription profiling by array assayRNA microarrayRNA microarray
33ENCSR168XPOENCODE3Thomas GingerasNaNNaNNaNtransverse colon male adult (54 years)transverse colonThomas Gingeras, CSHLENCODEHomo sapienstissue2016-05-23May, 2016TranscriptionRNA-seqsmall RNA-seqsmall RNA-seq
34ENCSR965JWFENCODE3Bing RenNaNH3K9me3Hist2h3c1C57BL/6 heart postnatal (0 days)heartBing Ren, UCSDENCODEMus musculustissue2016-02-17February, 2016DNA bindingChIP-seqChIP-seqHistone ChIP-seq
35ENCSR085AJXENCODE3Richard MyersNaNNaNNaNC57BL/6 hematopoietic stem cellhematopoietic stem cellRoss Hardison, PennStateENCODEMus musculusstem cell2017-01-04January, 2017TranscriptionRNA-seqtotal RNA-seqtotal RNA-seq
36ENCSR941SAZENCODE3Thomas GingerasNaNNaNNaNright lobe of liver female adult (53 years)right lobe of liverThomas Gingeras, CSHLENCODEHomo sapienstissue2016-08-05August, 2016TranscriptionRNA-seqRAMPAGERAMPAGE
37ENCSR000EQEENCODE2John StamatoyannopoulosNaNNaNNaNT-helper 1 cell male adult (33 years)T-helper 1 cellJohn Stamatoyannopoulos, UWENCODEHomo sapiensprimary cell2012-07-23July, 2012DNA accessibilityDNase-seqDNase-seqDNase-seq
38ENCSR973UGSENCODE3Bing RenNaNH3K27me3Hist2h3c1C57BL/6 liver postnatal (0 days)liverBing Ren, UCSDENCODEMus musculustissue2014-06-30June, 2014DNA bindingChIP-seqChIP-seqHistone ChIP-seq
39ENCSR000DTUENCODE2John StamatoyannopoulosNaNH3K4me3HIST2H3CHEK293HEK293John Stamatoyannopoulos, UWENCODEHomo sapiensimmortalized cell line2011-02-11February, 2011DNA bindingChIP-seqChIP-seqHistone ChIP-seq
40ENCSR365CUPENCODE3Bing RenNaNH3K9me3Hist2h3c1C57BL/6 hindbrain postnatal (0 days)hindbrainBing Ren, UCSDENCODEMus musculustissue2016-02-17February, 2016DNA bindingChIP-seqChIP-seqHistone ChIP-seq
41ENCSR000DDXENCODE2Richard MyersNaNNaNNaNhepatocytehepatocyteRichard Myers, HAIBENCODEHomo sapiensprimary cell2011-09-30September, 2011DNA methylationRRBSRRBSRRBS
42ENCSR000CWJENCODE2Michael SnyderNaNNaNNaNK562 treated with interferon alphaK562Sherman Weissman, YaleENCODEHomo sapiensimmortalized cell line2011-09-08September, 2011TranscriptionRNA-seqpolyA mRNA RNA-seqpolyA mRNA RNA-seq
43ENCSR401TBQENCODE3John StamatoyannopoulosNaNNaNNaNCaki2Caki2Job Dekker, UMassENCODEHomo sapiensimmortalized cell line2016-05-13May, 20163D chromatin structureHiCHi-CHi-C
44ENCSR440CTRENCODE3John StamatoyannopoulosNaNNaNNaNPanc1Panc1Job Dekker, UMassENCODEHomo sapiensimmortalized cell line2016-05-13May, 20163D chromatin structureHiCHi-CHi-C
45ENCSR444WCZENCODE3John StamatoyannopoulosNaNNaNNaNA549A549Job Dekker, UMassENCODEHomo sapiensimmortalized cell line2016-05-13May, 20163D chromatin structureHiCHi-CHi-C
46ENCSR000CBRENCODE2-MouseBing RenNaNPOLR2APolr2aC57BL/6 liver male adult (8 weeks)liverBing Ren, UCSDENCODEMus musculustissue2011-07-22July, 2011DNA bindingChIP-seqChIP-seqTF ChIP-seq
47ENCSR000BCOENCODE2Thomas GingerasNaNNaNNaNprostate gland maleprostate glandYijun Ruan, JAXENCODEHomo sapienstissue2011-10-17October, 2011TranscriptionRNA-PETRNA-PETRNA-PET
48ENCSR977IMDENCODE3Bradley BernsteinNaNDNMT1DNMT1GM12878GM12878John Rinn, BroadENCODEHomo sapiensimmortalized cell line2016-05-04May, 2016RNA bindingRIP-seqRIP-seqRNA binding protein
49ENCSR323LAMENCODE3Bradley BernsteinNaNCHD4CHD4GM12878GM12878John Rinn, BroadENCODEHomo sapiensimmortalized cell line2016-05-04May, 2016RNA bindingRIP-seqRIP-seqRNA binding protein
50ENCSR910LIEENCODE2Michael SnyderNaNH3K36me3HIST2H3CHEK293HEK293Peggy Farnham, USCENCODEHomo sapiensimmortalized cell line2017-06-01June, 2017DNA bindingChIP-seqChIP-seqHistone ChIP-seq
51ENCSR000EAGENCODE2Michael SnyderNaNRELARELAGM12878 treated with tumor necrosis factorGM12878Michael Snyder, StanfordENCODEHomo sapiensimmortalized cell line2012-05-14May, 2012DNA bindingChIP-seqChIP-seqTF ChIP-seq
52ENCSR998KYQENCODE3John StamatoyannopoulosNaNNaNNaNC57BL/6 adipocyteadipocyteJohn Stamatoyannopoulos, UWENCODEMus musculusin vitro differentiated cells2016-11-02November, 2016DNA accessibilityDNase-seqDNase-seqDNase-seq
53ENCSR690VOHENCODE3Bing RenNaNNaNNaNC57BL/6 neural tube embryo (12.5 days)neural tubeBing Ren, UCSDENCODEMus musculustissue2017-10-10October, 2017DNA accessibilityATAC-seqATAC-seqATAC-seq
54ENCSR700QBRENCODE3Bing RenNaNNaNNaNC57BL/6 neural tube embryo (14.5 days)neural tubeBing Ren, UCSDENCODEMus musculustissue2017-10-10October, 2017DNA accessibilityATAC-seqATAC-seqATAC-seq
55ENCSR945GURENCODE3Brenton GraveleyNaNNAA15NAA15K562 genetically modified using RNAiK562Brenton Graveley, UConnENCODEHomo sapiensimmortalized cell line2016-06-30June, 2016TranscriptionKnockdown RNAseqshRNA RNA-seqRNA binding protein
56ENCSR456JJQENCODE3Brenton GraveleyNaNRBM22RBM22HepG2HepG2Gene Yeo, UCSDENCODEHomo sapiensimmortalized cell line2016-04-26April, 2016RNA bindingeCLIPeCLIPRNA binding protein
57ENCSR766FACENCODE3Brenton GraveleyNaNRPS3RPS3HepG2HepG2Gene Yeo, UCSDENCODEHomo sapiensimmortalized cell line2017-08-15August, 2017RNA bindingeCLIPeCLIPRNA binding protein
58ENCSR000DUKENCODE2John StamatoyannopoulosNaNH3K4me3HIST2H3CHFF-Myc male newborn originated from foreskin ...HFF-MycJohn Stamatoyannopoulos, UWENCODEHomo sapiensprimary cell2011-11-17November, 2011DNA bindingChIP-seqChIP-seqHistone ChIP-seq
59ENCSR785DJDENCODE3Bradley BernsteinNaNH3K4me3HIST2H3Cgastrocnemius medialis female adult (53 years)gastrocnemius medialisBradley Bernstein, BroadENCODEHomo sapienstissue2017-01-27January, 2017DNA bindingChIP-seqChIP-seqHistone ChIP-seq
60ENCSR000DSYENCODE2John StamatoyannopoulosNaNH3K4me3HIST2H3Castrocyte of the cerebellumastrocyte of the cerebellumJohn Stamatoyannopoulos, UWENCODEHomo sapiensprimary cell2011-11-17November, 2011DNA bindingChIP-seqChIP-seqHistone ChIP-seq
61ENCSR000ADWENCODE2-MouseMichael SnyderNaNH3K27me3Hist2h3c1DBA/2 MEL cell line treated with dimethyl sulf...MEL cell lineMichael Snyder, StanfordENCODEMus musculusimmortalized cell line2012-08-20August, 2012DNA bindingChIP-seqChIP-seqHistone ChIP-seq
62ENCSR000AHLENCODE2-MouseRoss HardisonNaNH3K36me3Hist2h3c1C3H C2C12C2C12Barbara Wold, CaltechENCODEMus musculusimmortalized cell line2011-11-28November, 2011DNA bindingChIP-seqChIP-seqHistone ChIP-seq
63ENCSR081JYHENCODE3Brenton GraveleyNaNNSUN2NSUN2K562K562Gene Yeo, UCSDENCODEHomo sapiensimmortalized cell line2016-09-21September, 2016RNA bindingeCLIPeCLIPRNA binding protein
64ENCSR000DIFENCODE2-MouseRoss HardisonNaNPOLR2AphosphoS5Polr2a129 G1E-ER4 treated with 17β-estradiolG1E-ER4Ross Hardison, PennStateENCODEMus musculusstem cell2012-02-13February, 2012DNA bindingChIP-seqChIP-seqTF ChIP-seq
65ENCSR557JTZENCODE3Michael SnyderNaNGTF2F1GTF2F1MCF-7MCF-7Michael Snyder, StanfordENCODEHomo sapiensimmortalized cell line2014-07-07July, 2014DNA bindingChIP-seqChIP-seqTF ChIP-seq
66ENCSR000AHUENCODE2-MouseRoss HardisonNaNH3acHist1h3bC3H myocyte originated from C2C12myocyteBarbara Wold, CaltechENCODEMus musculusin vitro differentiated cells2011-11-28November, 2011DNA bindingChIP-seqChIP-seqHistone ChIP-seq
67ENCSR494TDUENCODE3Michael SnyderNaNNRF1NRF1K562K562Michael Snyder, StanfordENCODEHomo sapiensimmortalized cell line2014-07-07July, 2014DNA bindingChIP-seqChIP-seqTF ChIP-seq
68ENCSR096BPXENCODE3Michael SnyderNaNNaNNaNesophagus squamous epithelium female adult (51...esophagus squamous epitheliumMichael Snyder, StanfordENCODEHomo sapienstissue2017-06-21June, 2017DNA accessibilityATAC-seqATAC-seqATAC-seq
69ENCSR838SMCENCODE3Brenton GraveleyNaNRPS5RPS5HepG2 genetically modified using RNAiHepG2Brenton Graveley, UConnENCODEHomo sapiensimmortalized cell line2014-12-17December, 2014TranscriptionKnockdown RNAseqshRNA RNA-seqRNA binding protein
70ENCSR704IJMENCODE3Richard MyersNaNEP300EP300transverse colon female adult (51 year)transverse colonRichard Myers, HAIBENCODEHomo sapienstissue2017-06-15June, 2017DNA bindingChIP-seqChIP-seqTF ChIP-seq
71ENCSR977DCOENCODE3Bing RenNaNH3K4me1Hist2h3c1C57BL/6 neural tube embryo (14.5 days)neural tubeBing Ren, UCSDENCODEMus musculustissue2014-06-30June, 2014DNA bindingChIP-seqChIP-seqHistone ChIP-seq
72ENCSR000EHDENCODE2Michael SnyderNaNCHD2CHD2K562K562Michael Snyder, StanfordENCODEHomo sapiensimmortalized cell line2011-10-29October, 2011DNA bindingChIP-seqChIP-seqTF ChIP-seq
73ENCSR000CHXENCODE2-MouseRoss HardisonNaNNaNNaN129 G1E-ER4 treated with 17β-estradiolG1E-ER4Ross Hardison, PennStateENCODEMus musculusstem cell2012-08-13August, 2012TranscriptionRNA-seqpolyA mRNA RNA-seqpolyA mRNA RNA-seq
74ENCSR000EFQENCODE2Michael SnyderNaNZMIZ1ZMIZ1K562K562Michael Snyder, StanfordENCODEHomo sapiensimmortalized cell line2012-08-20August, 2012DNA bindingChIP-seqChIP-seqTF ChIP-seq
75ENCSR000CIAENCODE2-MouseRoss HardisonNaNNaNNaN129 G1E-ER4 treated with 17β-estradiolG1E-ER4Ross Hardison, PennStateENCODEMus musculusstem cell2012-08-13August, 2012TranscriptionRNA-seqpolyA mRNA RNA-seqpolyA mRNA RNA-seq
76ENCSR000CHHENCODE2-MouseBing RenNaNNaNNaNC57BL/6 testis male adult (8 weeks)testisBing Ren, UCSDENCODEMus musculustissue2012-05-04May, 2012TranscriptionRNA-seqpolyA mRNA RNA-seqpolyA mRNA RNA-seq
77ENCSR000DJBENCODE2-MouseRoss HardisonNaNH3K4me1Hist2h3c1129 G1EG1ERoss Hardison, PennStateENCODEMus musculusstem cell2012-08-06August, 2012DNA bindingChIP-seqChIP-seqHistone ChIP-seq
78ENCSR000EHLENCODE2Michael SnyderNaNPOLR2APOLR2AK562K562Michael Snyder, StanfordENCODEHomo sapiensimmortalized cell line2011-10-29October, 2011DNA bindingChIP-seqChIP-seqTF ChIP-seq
79ENCSR314UMJENCODE3Brenton GraveleyNaNTRA2ATRA2AHepG2HepG2Gene Yeo, UCSDENCODEHomo sapiensimmortalized cell line2015-07-15July, 2015RNA bindingeCLIPeCLIPRNA binding protein
80ENCSR000BCEENCODE2Thomas GingerasNaNNaNNaNHepG2 cytosolic fractionHepG2Yijun Ruan, JAXENCODEHomo sapiensimmortalized cell line2011-10-17October, 2011TranscriptionRNA-PETRNA-PETRNA-PET
81ENCSR000BDQENCODE2Gregory CrawfordNaNNaNNaNmammary epithelial cell femalemammary epithelial cellGregory Crawford, DukeENCODEHomo sapiensprimary cell2011-06-14June, 2011Transcriptiontranscription profiling by array assayRNA microarrayRNA microarray
82ENCSR000ETCENCODE2-MouseMichael SnyderNaNSIN3ASin3aDBA/2 MEL cell lineMEL cell lineMichael Snyder, StanfordENCODEMus musculusimmortalized cell line2012-06-15June, 2012DNA bindingChIP-seqChIP-seqTF ChIP-seq
83ENCSR057BKHENCODE3Bing RenNaNH3K4me3Hist2h3c1C57BL/6 embryonic facial prominence embryo (13...embryonic facial prominenceBing Ren, UCSDENCODEMus musculustissue2015-06-23June, 2015DNA bindingChIP-seqChIP-seqHistone ChIP-seq
84ENCSR895AWRENCODE3Bradley BernsteinNaNKDM6AKDM6AH1-hESCH1-hESCBradley Bernstein, BroadENCODEHomo sapiensstem cell2016-12-06December, 2016DNA bindingChIP-seqChIP-seqTF ChIP-seq
85ENCSR000DYFENCODE2Michael SnyderNaNPOLR2AphosphoS2POLR2AA549A549Michael Snyder, StanfordENCODEHomo sapiensimmortalized cell line2012-05-14May, 2012DNA bindingChIP-seqChIP-seqTF ChIP-seq
86ENCSR400TGEENCODE3Bing RenNaNH3K9acNaNC57BL/6 forebrain embryo (11.5 days)forebrainBing Ren, UCSDENCODEMus musculustissue2014-06-30June, 2014DNA bindingChIP-seqChIP-seqHistone ChIP-seq
87ENCSR670REKENCODE3Michael SnyderNaNNaNNaNgastroesophageal sphincter female adult (53 ye...gastroesophageal sphincterMichael Snyder, StanfordENCODEHomo sapienstissue2016-06-15June, 2016DNA accessibilityATAC-seqATAC-seqATAC-seq
88ENCSR857MYSENCODE2-MouseRoss HardisonNaNH3K9me3Hist2h3c1129 E14TG2a.4E14TG2a.4Ross Hardison, PennStateENCODEMus musculusstem cell2014-02-10February, 2014DNA bindingChIP-seqChIP-seqHistone ChIP-seq
89ENCSR668VCTENCODE3Michael SnyderNaNNaNNaNtransverse colon male adult (37 years)transverse colonMichael Snyder, StanfordENCODEHomo sapienstissue2016-06-15June, 2016DNA accessibilityATAC-seqATAC-seqATAC-seq
90ENCSR000CBLENCODE2-MouseBing RenNaNCTCFCtcfC57BL/6 bone marrow male adult (8 weeks)bone marrowBing Ren, UCSDENCODEMus musculustissue2011-07-22July, 2011DNA bindingChIP-seqChIP-seqTF ChIP-seq
91ENCSR000EAJENCODE2Michael SnyderNaNPOLR2APOLR2AGM12891GM12891Michael Snyder, StanfordENCODEHomo sapiensimmortalized cell line2011-10-29October, 2011DNA bindingChIP-seqChIP-seqTF ChIP-seq
92ENCSR479BMIENCODE3Thomas GingerasNaNNaNNaNSK-N-DZ nuclear fractionSK-N-DZThomas Gingeras, CSHLENCODEHomo sapiensimmortalized cell line2015-04-14April, 2015TranscriptionRNA-seqRAMPAGERAMPAGE
93ENCSR165YNQENCODE3Richard MyersNaNNaNNaNfibroblast of arm male adult (53 years)fibroblast of armRichard Myers, HAIBENCODEHomo sapiensprimary cell2016-08-05August, 2016Genotypingcomparative genomic hybridization by arraygenotyping arraygenotyping array
94ENCSR027YNXENCODE3Richard MyersNaNNaNNaNHeLa-S3HeLa-S3Richard Myers, HAIBENCODEHomo sapiensimmortalized cell line2016-08-05August, 2016Genotypingcomparative genomic hybridization by arraygenotyping arraygenotyping array
95ENCSR804MDHENCODE3Bradley BernsteinNaNH3K4me2HIST2H3CSU-DHL-6SU-DHL-6Bradley Bernstein, BroadENCODEHomo sapiensimmortalized cell line2014-07-11July, 2014DNA bindingChIP-seqChIP-seqHistone ChIP-seq
96ENCSR850QKNENCODE3Bradley BernsteinNaNH3K4me2HIST2H3COCI-LY7OCI-LY7Bradley Bernstein, BroadENCODEHomo sapiensimmortalized cell line2014-07-11July, 2014DNA bindingChIP-seqChIP-seqHistone ChIP-seq
97ENCSR475NLRENCODE3Bradley BernsteinNaNH3K27me3HIST2H3CACC112ACC112Bradley Bernstein, BroadENCODEHomo sapiensimmortalized cell line2014-09-04September, 2014DNA bindingChIP-seqChIP-seqHistone ChIP-seq
98ENCSR875KOJENCODE3Bradley BernsteinNaNH3K4me2HIST2H3CMCF-7MCF-7Bradley Bernstein, BroadENCODEHomo sapiensimmortalized cell line2014-07-11July, 2014DNA bindingChIP-seqChIP-seqHistone ChIP-seq
99ENCSR767VHRENCODE3Richard MyersNaNNaNNaNC57BL/6 common myeloid progenitor male adult (...common myeloid progenitorRoss Hardison, PennStateENCODEMus musculusprimary cell2014-09-29September, 2014TranscriptionRNA-seqtotal RNA-seqtotal RNA-seq
.........................................................
7735ENCSR000BPZENCODE2Richard MyersNaNZBTB33ZBTB33A549 treated with ethanolA549Richard Myers, HAIBENCODEHomo sapiensimmortalized cell line2012-02-29February, 2012DNA bindingChIP-seqChIP-seqTF ChIP-seq
7736ENCSR000EFYENCODE2Michael SnyderNaNARID3AARID3AK562K562Michael Snyder, StanfordENCODEHomo sapiensimmortalized cell line2012-05-14May, 2012DNA bindingChIP-seqChIP-seqTF ChIP-seq
7737ENCSR000AJHENCODE3Richard MyersNaNNaNNaNGM12878GM12878Barbara Wold, CaltechENCODEHomo sapiensimmortalized cell line2014-06-30June, 2014TranscriptionRNA-seqsingle cell RNA-seqsingle cell RNA-seq
7738ENCSR617FKVENCODE3Richard MyersNaNNaNNaNH1-hESCH1-hESCRichard Myers, HAIBENCODEHomo sapiensstem cell2015-10-13October, 2015DNA methylationwhole-genome shotgun bisulfite sequencingWGBSWGBS
7739ENCSR000APZENCODE2Bradley BernsteinNaNH3K9me3HIST2H3CH1-hESCH1-hESCBradley Bernstein, BroadENCODEHomo sapiensstem cell2012-03-06March, 2012DNA bindingChIP-seqChIP-seqHistone ChIP-seq
7740ENCSR000AMGENCODE2Bradley BernsteinNaNH3K4me3HIST2H3CH1-hESCH1-hESCBradley Bernstein, BroadENCODEHomo sapiensstem cell2011-02-10February, 2011DNA bindingChIP-seqChIP-seqHistone ChIP-seq
7741ENCSR000APXENCODE2Bradley BernsteinNaNH2AFZH2AFZH1-hESCH1-hESCBradley Bernstein, BroadENCODEHomo sapiensstem cell2012-03-06March, 2012DNA bindingChIP-seqChIP-seqHistone ChIP-seq
7742ENCSR000CRJENCODE2Thomas GingerasNaNNaNNaNH1-hESCH1-hESCThomas Gingeras, CSHLENCODEHomo sapiensstem cell2012-02-22February, 2012TranscriptionRNA-seqsmall RNA-seqsmall RNA-seq
7743ENCSR828LSCENCODE3Thomas GingerasNaNNaNNaNneural progenitor cell originated from H9neural progenitor cellThomas Gingeras, CSHLENCODEHomo sapiensin vitro differentiated cells2015-01-08January, 2015TranscriptionRNA-seqsmall RNA-seqsmall RNA-seq
7744ENCSR139PIAENCODE3Bradley BernsteinNaNH3K27me3HIST2H3Cneural progenitor cell originated from H9neural progenitor cellBradley Bernstein, BroadENCODEHomo sapiensin vitro differentiated cells2016-06-14June, 2016DNA bindingChIP-seqChIP-seqHistone ChIP-seq
7745ENCSR227VCKENCODE3Richard MyersNaNNaNNaNprostate gland male adult (54 years)prostate glandAli Mortazavi, UCIENCODEHomo sapienstissue2016-08-01August, 2016TranscriptionmicroRNA countsmicroRNA countsmicroRNA counts
7746ENCSR301SLOENCODE3Richard MyersNaNNaNNaNlower leg skin male adult (37 years)lower leg skinRichard Myers, HAIBENCODEHomo sapienstissue2017-06-15June, 2017DNA methylationDNA methylation profiling by array assayDNAme arrayDNAme array
7747ENCSR157ZVPENCODE3Bradley BernsteinNaNH3K36me3HIST2H3Ctibial nerve female adult (53 years)tibial nerveBradley Bernstein, BroadENCODEHomo sapienstissue2017-01-27January, 2017DNA bindingChIP-seqChIP-seqHistone ChIP-seq
7748ENCSR684NJDENCODE3Richard MyersNaNEP300EP300stomach male adult (54 years)stomachRichard Myers, HAIBENCODEHomo sapienstissue2017-06-15June, 2017DNA bindingChIP-seqChIP-seqTF ChIP-seq
7749ENCSR025ZZAENCODE3Michael SnyderNaNPOLR2APOLR2Asuprapubic skin female adult (51 year)suprapubic skinMichael Snyder, StanfordENCODEHomo sapienstissue2017-04-04April, 2017DNA bindingChIP-seqChIP-seqTF ChIP-seq
7750ENCSR329YVAENCODE3Thomas GingerasNaNNaNNaNspleen male adult (37 years)spleenThomas Gingeras, CSHLENCODEHomo sapienstissue2016-08-05August, 2016TranscriptionRNA-seqRAMPAGERAMPAGE
7751ENCSR887SSWENCODE3Thomas GingerasNaNNaNNaNspleen female adult (51 year)spleenThomas Gingeras, CSHLENCODEHomo sapienstissue2016-08-05August, 2016TranscriptionRNA-seqRAMPAGERAMPAGE
7752ENCSR373CTAENCODE3Richard MyersNaNNaNNaNprostate gland male adult (54 years)prostate glandAli Mortazavi, UCIENCODEHomo sapienstissue2016-07-29July, 2016TranscriptionRNA-seqmicroRNA-seqmicroRNA-seq
7753ENCSR479GPUENCODE3Bradley BernsteinNaNH3K9me3HIST2H3Ctibial nerve female adult (53 years)tibial nerveBradley Bernstein, BroadENCODEHomo sapienstissue2017-01-27January, 2017DNA bindingChIP-seqChIP-seqHistone ChIP-seq
7754ENCSR442CIFENCODE3Richard MyersNaNPOLR2AphosphoS5POLR2Aprostate gland male adult (54 years)prostate glandRichard Myers, HAIBENCODEHomo sapienstissue2017-10-31October, 2017DNA bindingChIP-seqChIP-seqTF ChIP-seq
7755ENCSR000EQFENCODE2John StamatoyannopoulosNaNNaNNaNT-helper 17 cellT-helper 17 cellJohn Stamatoyannopoulos, UWENCODEHomo sapiensprimary cell2012-07-23July, 2012DNA accessibilityDNase-seqDNase-seqDNase-seq
7756ENCSR158VATENCODE3John StamatoyannopoulosNaNNaNNaNthyroid gland male adult (37 years)thyroid glandJohn Stamatoyannopoulos, UWENCODEHomo sapienstissue2016-05-09May, 2016DNA accessibilityDNase-seqDNase-seqDNase-seq
7757ENCSR295GRBENCODE3Michael SnyderNaNeGFP-ZNF213ZNF213HEK293 genetically modified using site-specifi...HEK293Michael Snyder, StanfordENCODEHomo sapiensimmortalized cell line2017-11-30November, 2017DNA bindingChIP-seqChIP-seqTF ChIP-seq
7758ENCSR619OUCENCODE3Michael SnyderNaNeGFP-ZBTB6ZBTB6HEK293 genetically modified using site-specifi...HEK293Michael Snyder, StanfordENCODEHomo sapiensimmortalized cell line2017-11-30November, 2017DNA bindingChIP-seqChIP-seqTF ChIP-seq
7759ENCSR000DNTENCODE2Michael SnyderNaNZZZ3ZZZ3HeLa-S3HeLa-S3Kevin Struhl, HMSENCODEHomo sapiensimmortalized cell line2011-10-29October, 2011DNA bindingChIP-seqChIP-seqTF ChIP-seq
7760ENCSR953LFIENCODE3Bing RenNaNH3K27me3Hist2h3c1C57BL/6 hindbrain embryo (14.5 days)hindbrainBing Ren, UCSDENCODEMus musculustissue2014-06-30June, 2014DNA bindingChIP-seqChIP-seqHistone ChIP-seq
7761ENCSR254AHAENCODE3Bing RenNaNH3K27acHist2h3c1C57BL/6 midbrain embryo (14.5 days)midbrainBing Ren, UCSDENCODEMus musculustissue2014-06-30June, 2014DNA bindingChIP-seqChIP-seqHistone ChIP-seq
7762ENCSR000CEHENCODE2-MouseBing RenNaNCTCFCtcfC57BL/6 brain embryo (14.5 days)brainBing Ren, UCSDENCODEMus musculustissue2012-04-13April, 2012DNA bindingChIP-seqChIP-seqTF ChIP-seq
7763ENCSR929GXPENCODE3Bing RenNaNH3K27me3Hist2h3c1C57BL/6 midbrain embryo (14.5 days)midbrainBing Ren, UCSDENCODEMus musculustissue2014-06-30June, 2014DNA bindingChIP-seqChIP-seqHistone ChIP-seq
7764ENCSR689NXEENCODE3Bing RenNaNH3K9me3Hist2h3c1C57BL/6 hindbrain embryo (14.5 days)hindbrainBing Ren, UCSDENCODEMus musculustissue2016-02-18February, 2016DNA bindingChIP-seqChIP-seqHistone ChIP-seq
7765ENCSR522LDJENCODE3Michael SnyderNaNHDGFHDGFHEK293THEK293TMichael Snyder, StanfordENCODEHomo sapiensimmortalized cell line2017-04-14April, 2017DNA bindingChIP-seqChIP-seqTF ChIP-seq
7766ENCSR624LFPENCODE3Richard MyersNaNNaNNaNneural progenitor cell originated from H9neural progenitor cellAli Mortazavi, UCIENCODEHomo sapiensin vitro differentiated cells2016-01-19January, 2016TranscriptionmicroRNA countsmicroRNA countsmicroRNA counts
7767ENCSR511YYUENCODE3Richard MyersNaNNaNNaNneural progenitor cell originated from H9neural progenitor cellAli Mortazavi, UCIENCODEHomo sapiensin vitro differentiated cells2016-02-02February, 2016TranscriptionRNA-seqmicroRNA-seqmicroRNA-seq
7768ENCSR303GFIENCODE3Michael SnyderNaNCTCFCTCFRWPE1RWPE1Michael Snyder, StanfordENCODEHomo sapiensimmortalized cell line2017-07-21July, 2017DNA bindingChIP-seqChIP-seqTF ChIP-seq
7769ENCSR000EZFENCODE2Michael SnyderNaNMAXMAXHeLa-S3HeLa-S3Sherman Weissman, YaleENCODEHomo sapiensimmortalized cell line2011-10-29October, 2011DNA bindingChIP-seqChIP-seqTF ChIP-seq
7770ENCSR000ANIENCODE2Bradley BernsteinNaNH3K4me1HIST2H3Cskeletal muscle myoblast male adult (22 years)skeletal muscle myoblastBradley Bernstein, BroadENCODEHomo sapiensprimary cell2011-02-10February, 2011DNA bindingChIP-seqChIP-seqHistone ChIP-seq
7771ENCSR000EVKENCODE2Michael SnyderNaNE2F6E2F6HeLa-S3HeLa-S3Peggy Farnham, USCENCODEHomo sapiensimmortalized cell line2011-10-29October, 2011DNA bindingChIP-seqChIP-seqTF ChIP-seq
7772ENCSR702JYVENCODE3Bing RenNaNH3K36me3Hist2h3c1C57BL/6 midbrain embryo (14.5 days)midbrainBing Ren, UCSDENCODEMus musculustissue2014-06-30June, 2014DNA bindingChIP-seqChIP-seqHistone ChIP-seq
7773ENCSR227UTYENCODE3Bing RenNaNH3K36me3Hist2h3c1C57BL/6 forebrain embryo (14.5 days)forebrainBing Ren, UCSDENCODEMus musculustissue2014-06-30June, 2014DNA bindingChIP-seqChIP-seqHistone ChIP-seq
7774ENCSR203KIBENCODE3Bing RenNaNH3K4me3Hist2h3c1C57BL/6 midbrain embryo (14.5 days)midbrainBing Ren, UCSDENCODEMus musculustissue2014-06-30June, 2014DNA bindingChIP-seqChIP-seqHistone ChIP-seq
7775ENCSR000BZJENCODE2Thomas GingerasNaNNaNNaNC57BL/6 brain embryo (14.5 days)brainThomas Gingeras, CSHLENCODEMus musculustissue2012-09-05September, 2012TranscriptionRNA-seqpolyA mRNA RNA-seqpolyA mRNA RNA-seq
7776ENCSR197ALXENCODE3Michael SnyderNaNHDGFHDGFK562K562Michael Snyder, StanfordENCODEHomo sapiensimmortalized cell line2016-08-05August, 2016DNA bindingChIP-seqChIP-seqTF ChIP-seq
7777ENCSR396SKIENCODE3Michael SnyderNaNeGFP-ZNF331ZNF331HEK293 genetically modified using site-specifi...HEK293Michael Snyder, StanfordENCODEHomo sapiensimmortalized cell line2017-11-30November, 2017DNA bindingChIP-seqChIP-seqTF ChIP-seq
7778ENCSR000ANFENCODE2Bradley BernsteinNaNH3K27acHIST2H3Cskeletal muscle myoblast male adult (22 years)skeletal muscle myoblastBradley Bernstein, BroadENCODEHomo sapiensprimary cell2011-02-10February, 2011DNA bindingChIP-seqChIP-seqHistone ChIP-seq
7779ENCSR000DNXENCODE2Michael SnyderNaNBDP1BDP1HeLa-S3HeLa-S3Kevin Struhl, HMSENCODEHomo sapiensimmortalized cell line2011-10-29October, 2011DNA bindingChIP-seqChIP-seqTF ChIP-seq
7780ENCSR691CPMENCODE3Michael SnyderNaNPOLR2APOLR2Aspleen female adult (51 year)spleenMichael Snyder, StanfordENCODEHomo sapienstissue2017-03-14March, 2017DNA bindingChIP-seqChIP-seqTF ChIP-seq
7781ENCSR497BYBENCODE3Thomas GingerasNaNNaNNaNstomach female adult (51 year)stomachThomas Gingeras, CSHLENCODEHomo sapienstissue2016-08-05August, 2016TranscriptionRNA-seqRAMPAGERAMPAGE
7782ENCSR543DUCENCODE3Michael SnyderNaNPOLR2APOLR2Alower leg skin female adult (51 year)lower leg skinMichael Snyder, StanfordENCODEHomo sapienstissue2017-03-20March, 2017DNA bindingChIP-seqChIP-seqTF ChIP-seq
7783ENCSR080HYXENCODE3Richard MyersNaNNaNNaNprostate gland male adult (54 years)prostate glandRichard Myers, HAIBENCODEHomo sapienstissue2017-06-15June, 2017DNA methylationDNA methylation profiling by array assayDNAme arrayDNAme array
7784ENCSR021JTMENCODE3Richard MyersNaNNaNNaNlower leg skin male adult (37 years)lower leg skinAli Mortazavi, UCIENCODEHomo sapienstissue2016-07-29July, 2016TranscriptionmicroRNA countsmicroRNA countsmicroRNA counts
7785ENCSR626GVPENCODE3Thomas GingerasNaNNaNNaNtestis male adult (54 years)testisThomas Gingeras, CSHLENCODEHomo sapienstissue2016-05-23May, 2016TranscriptionRNA-seqsmall RNA-seqsmall RNA-seq
7786ENCSR344MQKENCODE3Thomas GingerasNaNNaNNaNtestis male adult (54 years)testisThomas Gingeras, CSHLENCODEHomo sapienstissue2016-08-04August, 2016TranscriptionRNA-seqtotal RNA-seqtotal RNA-seq
7787ENCSR265AREENCODE3Michael SnyderNaNCTCFCTCFVCaPVCaPMichael Snyder, StanfordENCODEHomo sapiensimmortalized cell line2017-07-21July, 2017DNA bindingChIP-seqChIP-seqTF ChIP-seq
7788ENCSR000ANKENCODE2Bradley BernsteinNaNH3K4me3HIST2H3Cskeletal muscle myoblast male adult (22 years)skeletal muscle myoblastBradley Bernstein, BroadENCODEHomo sapiensprimary cell2011-02-10February, 2011DNA bindingChIP-seqChIP-seqHistone ChIP-seq
7789ENCSR000APAENCODE2Bradley BernsteinNaNH2AFZH2AFZskeletal muscle myoblast male adult (22 years)skeletal muscle myoblastBradley Bernstein, BroadENCODEHomo sapiensprimary cell2011-02-10February, 2011DNA bindingChIP-seqChIP-seqHistone ChIP-seq
7790ENCSR000DNVENCODE2Michael SnyderNaNBRF2BRF2HeLa-S3HeLa-S3Kevin Struhl, HMSENCODEHomo sapiensimmortalized cell line2011-10-29October, 2011DNA bindingChIP-seqChIP-seqTF ChIP-seq
7791ENCSR000EVJENCODE2Michael SnyderNaNE2F1E2F1HeLa-S3HeLa-S3Peggy Farnham, USCENCODEHomo sapiensimmortalized cell line2011-10-29October, 2011DNA bindingChIP-seqChIP-seqTF ChIP-seq
7792ENCSR089DTYENCODE3Michael SnyderNaNCTCFCTCFomental fat pad male adult (37 years)omental fat padMichael Snyder, StanfordENCODEHomo sapienstissue2017-06-23June, 2017DNA bindingChIP-seqChIP-seqTF ChIP-seq
7793ENCSR494FISENCODE3Richard MyersNaNNaNNaNtestis male adult (54 years)testisAli Mortazavi, UCIENCODEHomo sapienstissue2016-07-29July, 2016TranscriptionmicroRNA countsmicroRNA countsmicroRNA counts
7794ENCSR727HMEENCODE3Michael SnyderNaNCTCFCTCFlower leg skin female adult (51 year)lower leg skinMichael Snyder, StanfordENCODEHomo sapienstissue2016-11-07November, 2016DNA bindingChIP-seqChIP-seqTF ChIP-seq
7795ENCSR858QELENCODE3Thomas GingerasNaNNaNNaNtibial nerve female adult (53 years)tibial nerveThomas Gingeras, CSHLENCODEHomo sapienstissue2016-02-18February, 2016TranscriptionRNA-seqtotal RNA-seqtotal RNA-seq
7796ENCSR611YUJENCODE3Bradley BernsteinNaNH3K27me3HIST2H3Ctibial nerve female adult (53 years)tibial nerveBradley Bernstein, BroadENCODEHomo sapienstissue2017-01-27January, 2017DNA bindingChIP-seqChIP-seqHistone ChIP-seq
7797ENCSR000DNYENCODE2Michael SnyderNaNGTF3C2GTF3C2HeLa-S3HeLa-S3Kevin Struhl, HMSENCODEHomo sapiensimmortalized cell line2011-10-29October, 2011DNA bindingChIP-seqChIP-seqTF ChIP-seq
7798ENCSR000DNUENCODE2Michael SnyderNaNPOLR3APOLR3AHeLa-S3HeLa-S3Kevin Struhl, HMSENCODEHomo sapiensimmortalized cell line2011-10-29October, 2011DNA bindingChIP-seqChIP-seqTF ChIP-seq
7799ENCSR729GXEENCODE3Michael SnyderNaNPOLR2APOLR2Aspleen male adult (37 years)spleenMichael Snyder, StanfordENCODEHomo sapienstissue2017-03-14March, 2017DNA bindingChIP-seqChIP-seqTF ChIP-seq
7800ENCSR000EZDENCODE2Michael SnyderNaNMYCMYCHeLa-S3HeLa-S3Sherman Weissman, YaleENCODEHomo sapiensimmortalized cell line2011-10-29October, 2011DNA bindingChIP-seqChIP-seqTF ChIP-seq
7801ENCSR469POZENCODE3Michael SnyderNaNCTCFCTCFtibial nerve female adult (53 years)tibial nerveMichael Snyder, StanfordENCODEHomo sapienstissue2016-12-08December, 2016DNA bindingChIP-seqChIP-seqTF ChIP-seq
7802ENCSR950CUQENCODE3Richard MyersNaNPOLR2AphosphoS5POLR2Aspleen male adult (37 years)spleenRichard Myers, HAIBENCODEHomo sapienstissue2017-10-31October, 2017DNA bindingChIP-seqChIP-seqTF ChIP-seq
7803ENCSR194HVUENCODE3Thomas GingerasNaNNaNNaNspleen female adult (51 year)spleenThomas Gingeras, CSHLENCODEHomo sapienstissue2016-05-03May, 2016TranscriptionRNA-seqtotal RNA-seqtotal RNA-seq
7804ENCSR229WIWENCODE3Thomas GingerasNaNNaNNaNtestis male adult (37 years)testisThomas Gingeras, CSHLENCODEHomo sapienstissue2016-05-23May, 2016TranscriptionRNA-seqsmall RNA-seqsmall RNA-seq
7805ENCSR000EZLENCODE2Michael SnyderNaNPOLR2APOLR2AHeLa-S3HeLa-S3Sherman Weissman, YaleENCODEHomo sapiensimmortalized cell line2011-10-29October, 2011DNA bindingChIP-seqChIP-seqTF ChIP-seq
7806ENCSR851SBYENCODE3Michael SnyderNaNNaNNaNstomach male adult (54 years)stomachMichael Snyder, StanfordENCODEHomo sapienstissue2016-06-15June, 2016DNA accessibilityATAC-seqATAC-seqATAC-seq
7807ENCSR771YJTENCODE3Bradley BernsteinNaNH3K27acHIST2H3Ctibial nerve female adult (53 years)tibial nerveBradley Bernstein, BroadENCODEHomo sapienstissue2017-01-27January, 2017DNA bindingChIP-seqChIP-seqHistone ChIP-seq
7808ENCSR315NACENCODE3Michael SnyderNaNCTCFCTCFLNCAPLNCAPMichael Snyder, StanfordENCODEHomo sapiensimmortalized cell line2017-06-29June, 2017DNA bindingChIP-seqChIP-seqTF ChIP-seq
7809ENCSR899UFGENCODE3Richard MyersNaNNaNNaNstomach male adult (54 years)stomachRichard Myers, HAIBENCODEHomo sapienstissue2017-06-15June, 2017DNA methylationDNA methylation profiling by array assayDNAme arrayDNAme array
7810ENCSR584HJLENCODE3Richard MyersNaNNaNNaNspleen male adult (37 years)spleenRichard Myers, HAIBENCODEHomo sapienstissue2017-06-15June, 2017DNA methylationDNA methylation profiling by array assayDNAme arrayDNAme array
7811ENCSR088SDZENCODE3Richard MyersNaNNaNNaNtestis male adult (54 years)testisAli Mortazavi, UCIENCODEHomo sapienstissue2016-07-29July, 2016TranscriptionRNA-seqmicroRNA-seqmicroRNA-seq
7812ENCSR210NKBENCODE3Michael SnyderNaNNaNNaNtestis male adult (37 years)testisMichael Snyder, StanfordENCODEHomo sapienstissue2017-06-21June, 2017DNA accessibilityATAC-seqATAC-seqATAC-seq
7813ENCSR175BVDENCODE3Michael SnyderNaNPOLR2APOLR2Alower leg skin male adult (37 years)lower leg skinMichael Snyder, StanfordENCODEHomo sapienstissue2017-03-14March, 2017DNA bindingChIP-seqChIP-seqTF ChIP-seq
7814ENCSR978QUTENCODE3John StamatoyannopoulosNaNNaNNaNtestis male adult (54 years)testisJohn Stamatoyannopoulos, UWENCODEHomo sapienstissue2017-11-01November, 2017DNA accessibilityDNase-seqDNase-seqDNase-seq
7815ENCSR648OSRENCODE3Thomas GingerasNaNNaNNaNtibial nerve male adult (54 years)tibial nerveThomas Gingeras, CSHLENCODEHomo sapienstissue2016-02-18February, 2016TranscriptionRNA-seqtotal RNA-seqtotal RNA-seq
7816ENCSR917CQJENCODE3Thomas GingerasNaNNaNNaNspleen male adult (37 years)spleenThomas Gingeras, CSHLENCODEHomo sapienstissue2016-05-03May, 2016TranscriptionRNA-seqsmall RNA-seqsmall RNA-seq
7817ENCSR946ZLIENCODE3Michael SnyderNaNeGFP-KLF13KLF13HEK293 genetically modified using site-specifi...HEK293Michael Snyder, StanfordENCODEHomo sapiensimmortalized cell line2017-11-30November, 2017DNA bindingChIP-seqChIP-seqTF ChIP-seq
7818ENCSR575WOHENCODE3Richard MyersNaNNaNNaNsuprapubic skin female adult (51 year)suprapubic skinRichard Myers, HAIBENCODEHomo sapienstissue2017-06-15June, 2017DNA methylationDNA methylation profiling by array assayDNAme arrayDNAme array
7819ENCSR234HEMENCODE3Michael SnyderNaNCTCFCTCFspleen male adult (37 years)spleenMichael Snyder, StanfordENCODEHomo sapienstissue2016-07-11July, 2016DNA bindingChIP-seqChIP-seqTF ChIP-seq
7820ENCSR532VUBENCODE3Brenton GraveleyNaNCPSF6CPSF6K562K562Gene Yeo, UCSDENCODEHomo sapiensimmortalized cell line2015-07-15July, 2015RNA bindingeCLIPeCLIPRNA binding protein
7821ENCSR811FAMENCODE3Richard MyersNaNNaNNaNspleen female adult (51 year)spleenRichard Myers, HAIBENCODEHomo sapienstissue2017-06-15June, 2017DNA methylationDNA methylation profiling by array assayDNAme arrayDNAme array
7822ENCSR300KULENCODE3Richard MyersNaNEP300EP300suprapubic skin female adult (51 year)suprapubic skinRichard Myers, HAIBENCODEHomo sapienstissue2017-06-15June, 2017DNA bindingChIP-seqChIP-seqTF ChIP-seq
7823ENCSR706VZWENCODE3Thomas GingerasNaNNaNNaNtibial nerve female adult (53 years)tibial nerveThomas Gingeras, CSHLENCODEHomo sapienstissue2016-08-05August, 2016TranscriptionRNA-seqRAMPAGERAMPAGE
7824ENCSR078EBDENCODE3Michael SnyderNaNNaNNaNspleen female adult (51 year)spleenMichael Snyder, StanfordENCODEHomo sapienstissue2016-06-15June, 2016DNA accessibilityATAC-seqATAC-seqATAC-seq
7825ENCSR000EZEENCODE2Michael SnyderNaNFOSFOSHeLa-S3HeLa-S3Sherman Weissman, YaleENCODEHomo sapiensimmortalized cell line2011-10-29October, 2011DNA bindingChIP-seqChIP-seqTF ChIP-seq
7826ENCSR915GVHENCODE3Richard MyersNaNNaNNaNtestis male adult (37 years)testisAli Mortazavi, UCIENCODEHomo sapienstissue2016-07-29July, 2016TranscriptionRNA-seqmicroRNA-seqmicroRNA-seq
7827ENCSR122EYEENCODE3Michael SnyderNaNPOLR2APOLR2Astomach male adult (54 years)stomachMichael Snyder, StanfordENCODEHomo sapienstissue2016-07-06July, 2016DNA bindingChIP-seqChIP-seqTF ChIP-seq
7828ENCSR829HTOENCODE3Michael SnyderNaNCTCFCTCFprostate gland male adult (54 years)prostate glandMichael Snyder, StanfordENCODEHomo sapienstissue2016-11-29November, 2016DNA bindingChIP-seqChIP-seqTF ChIP-seq
7829ENCSR593MVWENCODE3Thomas GingerasNaNNaNNaNspleen female adult (51 year)spleenThomas Gingeras, CSHLENCODEHomo sapienstissue2016-05-03May, 2016TranscriptionRNA-seqsmall RNA-seqsmall RNA-seq
7830ENCSR029KNZENCODE3Thomas GingerasNaNNaNNaNtestis male adult (37 years)testisThomas Gingeras, CSHLENCODEHomo sapienstissue2016-08-04August, 2016TranscriptionRNA-seqtotal RNA-seqtotal RNA-seq
7831ENCSR841EQJENCODE3Thomas GingerasNaNNaNNaNtestis male adult (37 years)testisThomas Gingeras, CSHLENCODEHomo sapienstissue2016-08-05August, 2016TranscriptionRNA-seqRAMPAGERAMPAGE
7832ENCSR314SPWENCODE3Bradley BernsteinNaNH3K4me3HIST2H3Ctibial nerve female adult (53 years)tibial nerveBradley Bernstein, BroadENCODEHomo sapienstissue2017-01-27January, 2017DNA bindingChIP-seqChIP-seqHistone ChIP-seq
7833ENCSR303OQDENCODE3Brenton GraveleyNaNMETAP2METAP2K562K562Gene Yeo, UCSDENCODEHomo sapiensimmortalized cell line2016-04-26April, 2016RNA bindingeCLIPeCLIPRNA binding protein
7834ENCSR647CLFENCODE3Brenton GraveleyNaNGPKOWGPKOWK562K562Gene Yeo, UCSDENCODEHomo sapiensimmortalized cell line2016-10-31October, 2016RNA bindingeCLIPeCLIPRNA binding protein
\n", + "

7835 rows × 18 columns

\n", + "
" + ], + "text/plain": [ + " Accession award.rfa award.pi.title Unnamed: 3 \\\n", + "0 ENCSR618GKP ENCODE3 Richard Myers NaN \n", + "1 ENCSR000EAN ENCODE2 Michael Snyder NaN \n", + "2 ENCSR668MJX ENCODE3 Brenton Graveley NaN \n", + "3 ENCSR000ARY ENCODE2 Bradley Bernstein NaN \n", + "4 ENCSR290RXI ENCODE3 Thomas Gingeras NaN \n", + "5 ENCSR000EJH ENCODE2 Gregory Crawford NaN \n", + "6 ENCSR861GYE ENCODE3 Brenton Graveley NaN \n", + "7 ENCSR000CGK ENCODE2-Mouse Bing Ren NaN \n", + "8 ENCSR082DIF ENCODE3 David Gilbert NaN \n", + "9 ENCSR000APL ENCODE2 Bradley Bernstein NaN \n", + "10 ENCSR000FAL ENCODE2 Michael Snyder NaN \n", + "11 ENCSR963HAR ENCODE3 Bradley Bernstein NaN \n", + "12 ENCSR000ESY ENCODE2-Mouse Michael Snyder NaN \n", + "13 ENCSR000CLU ENCODE2-Mouse John Stamatoyannopoulos NaN \n", + "14 ENCSR900AQL ENCODE3 Michael Snyder NaN \n", + "15 ENCSR046FQX ENCODE3 Michael Snyder NaN \n", + "16 ENCSR171RTN ENCODE3 Michael Snyder NaN \n", + "17 ENCSR000ADP ENCODE2-Mouse Michael Snyder NaN \n", + "18 ENCSR000EJU ENCODE2 Gregory Crawford NaN \n", + "19 ENCSR000ADR ENCODE2-Mouse Michael Snyder NaN \n", + "20 ENCSR288LNF ENCODE3 Bing Ren NaN \n", + "21 ENCSR000ELN ENCODE2 Gregory Crawford NaN \n", + "22 ENCSR450BNZ ENCODE3 Thomas Gingeras NaN \n", + "23 ENCSR471RUK ENCODE3 Thomas Gingeras NaN \n", + "24 ENCSR464UVO ENCODE3 Thomas Gingeras NaN \n", + "25 ENCSR779BVZ ENCODE3 Thomas Gingeras NaN \n", + "26 ENCSR634VLA ENCODE3 Thomas Gingeras NaN \n", + "27 ENCSR000EMJ ENCODE2 John Stamatoyannopoulos NaN \n", + "28 ENCSR882ZTS ENCODE3 Michael Snyder NaN \n", + "29 ENCSR000CHO ENCODE2-Mouse Bing Ren NaN \n", + "30 ENCSR000CPP ENCODE2 Thomas Gingeras NaN \n", + "31 ENCSR966RAG ENCODE3 Bing Ren NaN \n", + "32 ENCSR000DAV ENCODE2 John Stamatoyannopoulos NaN \n", + "33 ENCSR168XPO ENCODE3 Thomas Gingeras NaN \n", + "34 ENCSR965JWF ENCODE3 Bing Ren NaN \n", + "35 ENCSR085AJX ENCODE3 Richard Myers NaN \n", + "36 ENCSR941SAZ ENCODE3 Thomas Gingeras NaN \n", + "37 ENCSR000EQE ENCODE2 John Stamatoyannopoulos NaN \n", + "38 ENCSR973UGS ENCODE3 Bing Ren NaN \n", + "39 ENCSR000DTU ENCODE2 John Stamatoyannopoulos NaN \n", + "40 ENCSR365CUP ENCODE3 Bing Ren NaN \n", + "41 ENCSR000DDX ENCODE2 Richard Myers NaN \n", + "42 ENCSR000CWJ ENCODE2 Michael Snyder NaN \n", + "43 ENCSR401TBQ ENCODE3 John Stamatoyannopoulos NaN \n", + "44 ENCSR440CTR ENCODE3 John Stamatoyannopoulos NaN \n", + "45 ENCSR444WCZ ENCODE3 John Stamatoyannopoulos NaN \n", + "46 ENCSR000CBR ENCODE2-Mouse Bing Ren NaN \n", + "47 ENCSR000BCO ENCODE2 Thomas Gingeras NaN \n", + "48 ENCSR977IMD ENCODE3 Bradley Bernstein NaN \n", + "49 ENCSR323LAM ENCODE3 Bradley Bernstein NaN \n", + "50 ENCSR910LIE ENCODE2 Michael Snyder NaN \n", + "51 ENCSR000EAG ENCODE2 Michael Snyder NaN \n", + "52 ENCSR998KYQ ENCODE3 John Stamatoyannopoulos NaN \n", + "53 ENCSR690VOH ENCODE3 Bing Ren NaN \n", + "54 ENCSR700QBR ENCODE3 Bing Ren NaN \n", + "55 ENCSR945GUR ENCODE3 Brenton Graveley NaN \n", + "56 ENCSR456JJQ ENCODE3 Brenton Graveley NaN \n", + "57 ENCSR766FAC ENCODE3 Brenton Graveley NaN \n", + "58 ENCSR000DUK ENCODE2 John Stamatoyannopoulos NaN \n", + "59 ENCSR785DJD ENCODE3 Bradley Bernstein NaN \n", + "60 ENCSR000DSY ENCODE2 John Stamatoyannopoulos NaN \n", + "61 ENCSR000ADW ENCODE2-Mouse Michael Snyder NaN \n", + "62 ENCSR000AHL ENCODE2-Mouse Ross Hardison NaN \n", + "63 ENCSR081JYH ENCODE3 Brenton Graveley NaN \n", + "64 ENCSR000DIF ENCODE2-Mouse Ross Hardison NaN \n", + "65 ENCSR557JTZ ENCODE3 Michael Snyder NaN \n", + "66 ENCSR000AHU ENCODE2-Mouse Ross Hardison NaN \n", + "67 ENCSR494TDU ENCODE3 Michael Snyder NaN \n", + "68 ENCSR096BPX ENCODE3 Michael Snyder NaN \n", + "69 ENCSR838SMC ENCODE3 Brenton Graveley NaN \n", + "70 ENCSR704IJM ENCODE3 Richard Myers NaN \n", + "71 ENCSR977DCO ENCODE3 Bing Ren NaN \n", + "72 ENCSR000EHD ENCODE2 Michael Snyder NaN \n", + "73 ENCSR000CHX ENCODE2-Mouse Ross Hardison NaN \n", + "74 ENCSR000EFQ ENCODE2 Michael Snyder NaN \n", + "75 ENCSR000CIA ENCODE2-Mouse Ross Hardison NaN \n", + "76 ENCSR000CHH ENCODE2-Mouse Bing Ren NaN \n", + "77 ENCSR000DJB ENCODE2-Mouse Ross Hardison NaN \n", + "78 ENCSR000EHL ENCODE2 Michael Snyder NaN \n", + "79 ENCSR314UMJ ENCODE3 Brenton Graveley NaN \n", + "80 ENCSR000BCE ENCODE2 Thomas Gingeras NaN \n", + "81 ENCSR000BDQ ENCODE2 Gregory Crawford NaN \n", + "82 ENCSR000ETC ENCODE2-Mouse Michael Snyder NaN \n", + "83 ENCSR057BKH ENCODE3 Bing Ren NaN \n", + "84 ENCSR895AWR ENCODE3 Bradley Bernstein NaN \n", + "85 ENCSR000DYF ENCODE2 Michael Snyder NaN \n", + "86 ENCSR400TGE ENCODE3 Bing Ren NaN \n", + "87 ENCSR670REK ENCODE3 Michael Snyder NaN \n", + "88 ENCSR857MYS ENCODE2-Mouse Ross Hardison NaN \n", + "89 ENCSR668VCT ENCODE3 Michael Snyder NaN \n", + "90 ENCSR000CBL ENCODE2-Mouse Bing Ren NaN \n", + "91 ENCSR000EAJ ENCODE2 Michael Snyder NaN \n", + "92 ENCSR479BMI ENCODE3 Thomas Gingeras NaN \n", + "93 ENCSR165YNQ ENCODE3 Richard Myers NaN \n", + "94 ENCSR027YNX ENCODE3 Richard Myers NaN \n", + "95 ENCSR804MDH ENCODE3 Bradley Bernstein NaN \n", + "96 ENCSR850QKN ENCODE3 Bradley Bernstein NaN \n", + "97 ENCSR475NLR ENCODE3 Bradley Bernstein NaN \n", + "98 ENCSR875KOJ ENCODE3 Bradley Bernstein NaN \n", + "99 ENCSR767VHR ENCODE3 Richard Myers NaN \n", + "... ... ... ... ... \n", + "7735 ENCSR000BPZ ENCODE2 Richard Myers NaN \n", + "7736 ENCSR000EFY ENCODE2 Michael Snyder NaN \n", + "7737 ENCSR000AJH ENCODE3 Richard Myers NaN \n", + "7738 ENCSR617FKV ENCODE3 Richard Myers NaN \n", + "7739 ENCSR000APZ ENCODE2 Bradley Bernstein NaN \n", + "7740 ENCSR000AMG ENCODE2 Bradley Bernstein NaN \n", + "7741 ENCSR000APX ENCODE2 Bradley Bernstein NaN \n", + "7742 ENCSR000CRJ ENCODE2 Thomas Gingeras NaN \n", + "7743 ENCSR828LSC ENCODE3 Thomas Gingeras NaN \n", + "7744 ENCSR139PIA ENCODE3 Bradley Bernstein NaN \n", + "7745 ENCSR227VCK ENCODE3 Richard Myers NaN \n", + "7746 ENCSR301SLO ENCODE3 Richard Myers NaN \n", + "7747 ENCSR157ZVP ENCODE3 Bradley Bernstein NaN \n", + "7748 ENCSR684NJD ENCODE3 Richard Myers NaN \n", + "7749 ENCSR025ZZA ENCODE3 Michael Snyder NaN \n", + "7750 ENCSR329YVA ENCODE3 Thomas Gingeras NaN \n", + "7751 ENCSR887SSW ENCODE3 Thomas Gingeras NaN \n", + "7752 ENCSR373CTA ENCODE3 Richard Myers NaN \n", + "7753 ENCSR479GPU ENCODE3 Bradley Bernstein NaN \n", + "7754 ENCSR442CIF ENCODE3 Richard Myers NaN \n", + "7755 ENCSR000EQF ENCODE2 John Stamatoyannopoulos NaN \n", + "7756 ENCSR158VAT ENCODE3 John Stamatoyannopoulos NaN \n", + "7757 ENCSR295GRB ENCODE3 Michael Snyder NaN \n", + "7758 ENCSR619OUC ENCODE3 Michael Snyder NaN \n", + "7759 ENCSR000DNT ENCODE2 Michael Snyder NaN \n", + "7760 ENCSR953LFI ENCODE3 Bing Ren NaN \n", + "7761 ENCSR254AHA ENCODE3 Bing Ren NaN \n", + "7762 ENCSR000CEH ENCODE2-Mouse Bing Ren NaN \n", + "7763 ENCSR929GXP ENCODE3 Bing Ren NaN \n", + "7764 ENCSR689NXE ENCODE3 Bing Ren NaN \n", + "7765 ENCSR522LDJ ENCODE3 Michael Snyder NaN \n", + "7766 ENCSR624LFP ENCODE3 Richard Myers NaN \n", + "7767 ENCSR511YYU ENCODE3 Richard Myers NaN \n", + "7768 ENCSR303GFI ENCODE3 Michael Snyder NaN \n", + "7769 ENCSR000EZF ENCODE2 Michael Snyder NaN \n", + "7770 ENCSR000ANI ENCODE2 Bradley Bernstein NaN \n", + "7771 ENCSR000EVK ENCODE2 Michael Snyder NaN \n", + "7772 ENCSR702JYV ENCODE3 Bing Ren NaN \n", + "7773 ENCSR227UTY ENCODE3 Bing Ren NaN \n", + "7774 ENCSR203KIB ENCODE3 Bing Ren NaN \n", + "7775 ENCSR000BZJ ENCODE2 Thomas Gingeras NaN \n", + "7776 ENCSR197ALX ENCODE3 Michael Snyder NaN \n", + "7777 ENCSR396SKI ENCODE3 Michael Snyder NaN \n", + "7778 ENCSR000ANF ENCODE2 Bradley Bernstein NaN \n", + "7779 ENCSR000DNX ENCODE2 Michael Snyder NaN \n", + "7780 ENCSR691CPM ENCODE3 Michael Snyder NaN \n", + "7781 ENCSR497BYB ENCODE3 Thomas Gingeras NaN \n", + "7782 ENCSR543DUC ENCODE3 Michael Snyder NaN \n", + "7783 ENCSR080HYX ENCODE3 Richard Myers NaN \n", + "7784 ENCSR021JTM ENCODE3 Richard Myers NaN \n", + "7785 ENCSR626GVP ENCODE3 Thomas Gingeras NaN \n", + "7786 ENCSR344MQK ENCODE3 Thomas Gingeras NaN \n", + "7787 ENCSR265ARE ENCODE3 Michael Snyder NaN \n", + "7788 ENCSR000ANK ENCODE2 Bradley Bernstein NaN \n", + "7789 ENCSR000APA ENCODE2 Bradley Bernstein NaN \n", + "7790 ENCSR000DNV ENCODE2 Michael Snyder NaN \n", + "7791 ENCSR000EVJ ENCODE2 Michael Snyder NaN \n", + "7792 ENCSR089DTY ENCODE3 Michael Snyder NaN \n", + "7793 ENCSR494FIS ENCODE3 Richard Myers NaN \n", + "7794 ENCSR727HME ENCODE3 Michael Snyder NaN \n", + "7795 ENCSR858QEL ENCODE3 Thomas Gingeras NaN \n", + "7796 ENCSR611YUJ ENCODE3 Bradley Bernstein NaN \n", + "7797 ENCSR000DNY ENCODE2 Michael Snyder NaN \n", + "7798 ENCSR000DNU ENCODE2 Michael Snyder NaN \n", + "7799 ENCSR729GXE ENCODE3 Michael Snyder NaN \n", + "7800 ENCSR000EZD ENCODE2 Michael Snyder NaN \n", + "7801 ENCSR469POZ ENCODE3 Michael Snyder NaN \n", + "7802 ENCSR950CUQ ENCODE3 Richard Myers NaN \n", + "7803 ENCSR194HVU ENCODE3 Thomas Gingeras NaN \n", + "7804 ENCSR229WIW ENCODE3 Thomas Gingeras NaN \n", + "7805 ENCSR000EZL ENCODE2 Michael Snyder NaN \n", + "7806 ENCSR851SBY ENCODE3 Michael Snyder NaN \n", + "7807 ENCSR771YJT ENCODE3 Bradley Bernstein NaN \n", + "7808 ENCSR315NAC ENCODE3 Michael Snyder NaN \n", + "7809 ENCSR899UFG ENCODE3 Richard Myers NaN \n", + "7810 ENCSR584HJL ENCODE3 Richard Myers NaN \n", + "7811 ENCSR088SDZ ENCODE3 Richard Myers NaN \n", + "7812 ENCSR210NKB ENCODE3 Michael Snyder NaN \n", + "7813 ENCSR175BVD ENCODE3 Michael Snyder NaN \n", + "7814 ENCSR978QUT ENCODE3 John Stamatoyannopoulos NaN \n", + "7815 ENCSR648OSR ENCODE3 Thomas Gingeras NaN \n", + "7816 ENCSR917CQJ ENCODE3 Thomas Gingeras NaN \n", + "7817 ENCSR946ZLI ENCODE3 Michael Snyder NaN \n", + "7818 ENCSR575WOH ENCODE3 Richard Myers NaN \n", + "7819 ENCSR234HEM ENCODE3 Michael Snyder NaN \n", + "7820 ENCSR532VUB ENCODE3 Brenton Graveley NaN \n", + "7821 ENCSR811FAM ENCODE3 Richard Myers NaN \n", + "7822 ENCSR300KUL ENCODE3 Richard Myers NaN \n", + "7823 ENCSR706VZW ENCODE3 Thomas Gingeras NaN \n", + "7824 ENCSR078EBD ENCODE3 Michael Snyder NaN \n", + "7825 ENCSR000EZE ENCODE2 Michael Snyder NaN \n", + "7826 ENCSR915GVH ENCODE3 Richard Myers NaN \n", + "7827 ENCSR122EYE ENCODE3 Michael Snyder NaN \n", + "7828 ENCSR829HTO ENCODE3 Michael Snyder NaN \n", + "7829 ENCSR593MVW ENCODE3 Thomas Gingeras NaN \n", + "7830 ENCSR029KNZ ENCODE3 Thomas Gingeras NaN \n", + "7831 ENCSR841EQJ ENCODE3 Thomas Gingeras NaN \n", + "7832 ENCSR314SPW ENCODE3 Bradley Bernstein NaN \n", + "7833 ENCSR303OQD ENCODE3 Brenton Graveley NaN \n", + "7834 ENCSR647CLF ENCODE3 Brenton Graveley NaN \n", + "\n", + " Target label Target gene \\\n", + "0 NaN NaN \n", + "1 RELA RELA \n", + "2 GRSF1 GRSF1 \n", + "3 H3K9ac HIST2H3C \n", + "4 NaN NaN \n", + "5 NaN NaN \n", + "6 LIN28B LIN28B \n", + "7 H3K4me3 Hist2h3c1 \n", + "8 NaN NaN \n", + "9 H3K9me3 HIST2H3C \n", + "10 POLR2A POLR2A \n", + "11 H3K27me3 HIST2H3C \n", + "12 MAFK Mafk \n", + "13 NaN NaN \n", + "14 KHSRP KHSRP \n", + "15 LDB1 LDB1 \n", + "16 CTBP1 CTBP1 \n", + "17 H3K27me3 Hist2h3c1 \n", + "18 NaN NaN \n", + "19 H3K4me3 Hist2h3c1 \n", + "20 H3K4me2 Hist2h3c1 \n", + "21 NaN NaN \n", + "22 NaN NaN \n", + "23 NaN NaN \n", + "24 NaN NaN \n", + "25 NaN NaN \n", + "26 NaN NaN \n", + "27 NaN NaN \n", + "28 eGFP-ZBTB11 ZBTB11 \n", + "29 NaN NaN \n", + "30 NaN NaN \n", + "31 H3K9ac NaN \n", + "32 NaN NaN \n", + "33 NaN NaN \n", + "34 H3K9me3 Hist2h3c1 \n", + "35 NaN NaN \n", + "36 NaN NaN \n", + "37 NaN NaN \n", + "38 H3K27me3 Hist2h3c1 \n", + "39 H3K4me3 HIST2H3C \n", + "40 H3K9me3 Hist2h3c1 \n", + "41 NaN NaN \n", + "42 NaN NaN \n", + "43 NaN NaN \n", + "44 NaN NaN \n", + "45 NaN NaN \n", + "46 POLR2A Polr2a \n", + "47 NaN NaN \n", + "48 DNMT1 DNMT1 \n", + "49 CHD4 CHD4 \n", + "50 H3K36me3 HIST2H3C \n", + "51 RELA RELA \n", + "52 NaN NaN \n", + "53 NaN NaN \n", + "54 NaN NaN \n", + "55 NAA15 NAA15 \n", + "56 RBM22 RBM22 \n", + "57 RPS3 RPS3 \n", + "58 H3K4me3 HIST2H3C \n", + "59 H3K4me3 HIST2H3C \n", + "60 H3K4me3 HIST2H3C \n", + "61 H3K27me3 Hist2h3c1 \n", + "62 H3K36me3 Hist2h3c1 \n", + "63 NSUN2 NSUN2 \n", + "64 POLR2AphosphoS5 Polr2a \n", + "65 GTF2F1 GTF2F1 \n", + "66 H3ac Hist1h3b \n", + "67 NRF1 NRF1 \n", + "68 NaN NaN \n", + "69 RPS5 RPS5 \n", + "70 EP300 EP300 \n", + "71 H3K4me1 Hist2h3c1 \n", + "72 CHD2 CHD2 \n", + "73 NaN NaN \n", + "74 ZMIZ1 ZMIZ1 \n", + "75 NaN NaN \n", + "76 NaN NaN \n", + "77 H3K4me1 Hist2h3c1 \n", + "78 POLR2A POLR2A \n", + "79 TRA2A TRA2A \n", + "80 NaN NaN \n", + "81 NaN NaN \n", + "82 SIN3A Sin3a \n", + "83 H3K4me3 Hist2h3c1 \n", + "84 KDM6A KDM6A \n", + "85 POLR2AphosphoS2 POLR2A \n", + "86 H3K9ac NaN \n", + "87 NaN NaN \n", + "88 H3K9me3 Hist2h3c1 \n", + "89 NaN NaN \n", + "90 CTCF Ctcf \n", + "91 POLR2A POLR2A \n", + "92 NaN NaN \n", + "93 NaN NaN \n", + "94 NaN NaN \n", + "95 H3K4me2 HIST2H3C \n", + "96 H3K4me2 HIST2H3C \n", + "97 H3K27me3 HIST2H3C \n", + "98 H3K4me2 HIST2H3C \n", + "99 NaN NaN \n", + "... ... ... \n", + "7735 ZBTB33 ZBTB33 \n", + "7736 ARID3A ARID3A \n", + "7737 NaN NaN \n", + "7738 NaN NaN \n", + "7739 H3K9me3 HIST2H3C \n", + "7740 H3K4me3 HIST2H3C \n", + "7741 H2AFZ H2AFZ \n", + "7742 NaN NaN \n", + "7743 NaN NaN \n", + "7744 H3K27me3 HIST2H3C \n", + "7745 NaN NaN \n", + "7746 NaN NaN \n", + "7747 H3K36me3 HIST2H3C \n", + "7748 EP300 EP300 \n", + "7749 POLR2A POLR2A \n", + "7750 NaN NaN \n", + "7751 NaN NaN \n", + "7752 NaN NaN \n", + "7753 H3K9me3 HIST2H3C \n", + "7754 POLR2AphosphoS5 POLR2A \n", + "7755 NaN NaN \n", + "7756 NaN NaN \n", + "7757 eGFP-ZNF213 ZNF213 \n", + "7758 eGFP-ZBTB6 ZBTB6 \n", + "7759 ZZZ3 ZZZ3 \n", + "7760 H3K27me3 Hist2h3c1 \n", + "7761 H3K27ac Hist2h3c1 \n", + "7762 CTCF Ctcf \n", + "7763 H3K27me3 Hist2h3c1 \n", + "7764 H3K9me3 Hist2h3c1 \n", + "7765 HDGF HDGF \n", + "7766 NaN NaN \n", + "7767 NaN NaN \n", + "7768 CTCF CTCF \n", + "7769 MAX MAX \n", + "7770 H3K4me1 HIST2H3C \n", + "7771 E2F6 E2F6 \n", + "7772 H3K36me3 Hist2h3c1 \n", + "7773 H3K36me3 Hist2h3c1 \n", + "7774 H3K4me3 Hist2h3c1 \n", + "7775 NaN NaN \n", + "7776 HDGF HDGF \n", + "7777 eGFP-ZNF331 ZNF331 \n", + "7778 H3K27ac HIST2H3C \n", + "7779 BDP1 BDP1 \n", + "7780 POLR2A POLR2A \n", + "7781 NaN NaN \n", + "7782 POLR2A POLR2A \n", + "7783 NaN NaN \n", + "7784 NaN NaN \n", + "7785 NaN NaN \n", + "7786 NaN NaN \n", + "7787 CTCF CTCF \n", + "7788 H3K4me3 HIST2H3C \n", + "7789 H2AFZ H2AFZ \n", + "7790 BRF2 BRF2 \n", + "7791 E2F1 E2F1 \n", + "7792 CTCF CTCF \n", + "7793 NaN NaN \n", + "7794 CTCF CTCF \n", + "7795 NaN NaN \n", + "7796 H3K27me3 HIST2H3C \n", + "7797 GTF3C2 GTF3C2 \n", + "7798 POLR3A POLR3A \n", + "7799 POLR2A POLR2A \n", + "7800 MYC MYC \n", + "7801 CTCF CTCF \n", + "7802 POLR2AphosphoS5 POLR2A \n", + "7803 NaN NaN \n", + "7804 NaN NaN \n", + "7805 POLR2A POLR2A \n", + "7806 NaN NaN \n", + "7807 H3K27ac HIST2H3C \n", + "7808 CTCF CTCF \n", + "7809 NaN NaN \n", + "7810 NaN NaN \n", + "7811 NaN NaN \n", + "7812 NaN NaN \n", + "7813 POLR2A POLR2A \n", + "7814 NaN NaN \n", + "7815 NaN NaN \n", + "7816 NaN NaN \n", + "7817 eGFP-KLF13 KLF13 \n", + "7818 NaN NaN \n", + "7819 CTCF CTCF \n", + "7820 CPSF6 CPSF6 \n", + "7821 NaN NaN \n", + "7822 EP300 EP300 \n", + "7823 NaN NaN \n", + "7824 NaN NaN \n", + "7825 FOS FOS \n", + "7826 NaN NaN \n", + "7827 POLR2A POLR2A \n", + "7828 CTCF CTCF \n", + "7829 NaN NaN \n", + "7830 NaN NaN \n", + "7831 NaN NaN \n", + "7832 H3K4me3 HIST2H3C \n", + "7833 METAP2 METAP2 \n", + "7834 GPKOW GPKOW \n", + "\n", + " Biosample summary \\\n", + "0 C57BL/6 limb embryo (12.5 days) \n", + "1 GM12892 treated with tumor necrosis factor \n", + "2 HepG2 \n", + "3 DND-41 \n", + "4 myometrial cell female adult (34 years) \n", + "5 GM13977 \n", + "6 HepG2 \n", + "7 B10.H-2aH-4bp/Wts CH12.LX \n", + "8 primitive gut cell originated from CyT49 \n", + "9 osteoblast \n", + "10 NB4 \n", + "11 Karpas-422 \n", + "12 DBA/2 MEL cell line treated with dimethyl sulf... \n", + "13 B6D2F1/J 416B \n", + "14 K562 genetically modified using CRISPR \n", + "15 K562 genetically modified using CRISPR \n", + "16 K562 genetically modified using CRISPR \n", + "17 DBA/2 MEL cell line \n", + "18 hepatocyte \n", + "19 DBA/2 MEL cell line \n", + "20 C57BL/6 stomach postnatal (0 days) \n", + "21 HGPS cell \n", + "22 Peyer's patch female adult (51 year) \n", + "23 stomach male adult (37 years) \n", + "24 heart left ventricle female adult (53 years) \n", + "25 esophagus squamous epithelium female adult (51... \n", + "26 right lobe of liver female adult (53 years) \n", + "27 B cell female adult (43 years) \n", + "28 HEK293 genetically modified using site-specifi... \n", + "29 C57BL/6 bone marrow macrophage male adult (8 w... \n", + "30 HeLa-S3 cytosolic fraction \n", + "31 C57BL/6 liver postnatal (0 days) \n", + "32 fibroblast of pedal digit skin female adult (2... \n", + "33 transverse colon male adult (54 years) \n", + "34 C57BL/6 heart postnatal (0 days) \n", + "35 C57BL/6 hematopoietic stem cell \n", + "36 right lobe of liver female adult (53 years) \n", + "37 T-helper 1 cell male adult (33 years) \n", + "38 C57BL/6 liver postnatal (0 days) \n", + "39 HEK293 \n", + "40 C57BL/6 hindbrain postnatal (0 days) \n", + "41 hepatocyte \n", + "42 K562 treated with interferon alpha \n", + "43 Caki2 \n", + "44 Panc1 \n", + "45 A549 \n", + "46 C57BL/6 liver male adult (8 weeks) \n", + "47 prostate gland male \n", + "48 GM12878 \n", + "49 GM12878 \n", + "50 HEK293 \n", + "51 GM12878 treated with tumor necrosis factor \n", + "52 C57BL/6 adipocyte \n", + "53 C57BL/6 neural tube embryo (12.5 days) \n", + "54 C57BL/6 neural tube embryo (14.5 days) \n", + "55 K562 genetically modified using RNAi \n", + "56 HepG2 \n", + "57 HepG2 \n", + "58 HFF-Myc male newborn originated from foreskin ... \n", + "59 gastrocnemius medialis female adult (53 years) \n", + "60 astrocyte of the cerebellum \n", + "61 DBA/2 MEL cell line treated with dimethyl sulf... \n", + "62 C3H C2C12 \n", + "63 K562 \n", + "64 129 G1E-ER4 treated with 17β-estradiol \n", + "65 MCF-7 \n", + "66 C3H myocyte originated from C2C12 \n", + "67 K562 \n", + "68 esophagus squamous epithelium female adult (51... \n", + "69 HepG2 genetically modified using RNAi \n", + "70 transverse colon female adult (51 year) \n", + "71 C57BL/6 neural tube embryo (14.5 days) \n", + "72 K562 \n", + "73 129 G1E-ER4 treated with 17β-estradiol \n", + "74 K562 \n", + "75 129 G1E-ER4 treated with 17β-estradiol \n", + "76 C57BL/6 testis male adult (8 weeks) \n", + "77 129 G1E \n", + "78 K562 \n", + "79 HepG2 \n", + "80 HepG2 cytosolic fraction \n", + "81 mammary epithelial cell female \n", + "82 DBA/2 MEL cell line \n", + "83 C57BL/6 embryonic facial prominence embryo (13... \n", + "84 H1-hESC \n", + "85 A549 \n", + "86 C57BL/6 forebrain embryo (11.5 days) \n", + "87 gastroesophageal sphincter female adult (53 ye... \n", + "88 129 E14TG2a.4 \n", + "89 transverse colon male adult (37 years) \n", + "90 C57BL/6 bone marrow male adult (8 weeks) \n", + "91 GM12891 \n", + "92 SK-N-DZ nuclear fraction \n", + "93 fibroblast of arm male adult (53 years) \n", + "94 HeLa-S3 \n", + "95 SU-DHL-6 \n", + "96 OCI-LY7 \n", + "97 ACC112 \n", + "98 MCF-7 \n", + "99 C57BL/6 common myeloid progenitor male adult (... \n", + "... ... \n", + "7735 A549 treated with ethanol \n", + "7736 K562 \n", + "7737 GM12878 \n", + "7738 H1-hESC \n", + "7739 H1-hESC \n", + "7740 H1-hESC \n", + "7741 H1-hESC \n", + "7742 H1-hESC \n", + "7743 neural progenitor cell originated from H9 \n", + "7744 neural progenitor cell originated from H9 \n", + "7745 prostate gland male adult (54 years) \n", + "7746 lower leg skin male adult (37 years) \n", + "7747 tibial nerve female adult (53 years) \n", + "7748 stomach male adult (54 years) \n", + "7749 suprapubic skin female adult (51 year) \n", + "7750 spleen male adult (37 years) \n", + "7751 spleen female adult (51 year) \n", + "7752 prostate gland male adult (54 years) \n", + "7753 tibial nerve female adult (53 years) \n", + "7754 prostate gland male adult (54 years) \n", + "7755 T-helper 17 cell \n", + "7756 thyroid gland male adult (37 years) \n", + "7757 HEK293 genetically modified using site-specifi... \n", + "7758 HEK293 genetically modified using site-specifi... \n", + "7759 HeLa-S3 \n", + "7760 C57BL/6 hindbrain embryo (14.5 days) \n", + "7761 C57BL/6 midbrain embryo (14.5 days) \n", + "7762 C57BL/6 brain embryo (14.5 days) \n", + "7763 C57BL/6 midbrain embryo (14.5 days) \n", + "7764 C57BL/6 hindbrain embryo (14.5 days) \n", + "7765 HEK293T \n", + "7766 neural progenitor cell originated from H9 \n", + "7767 neural progenitor cell originated from H9 \n", + "7768 RWPE1 \n", + "7769 HeLa-S3 \n", + "7770 skeletal muscle myoblast male adult (22 years) \n", + "7771 HeLa-S3 \n", + "7772 C57BL/6 midbrain embryo (14.5 days) \n", + "7773 C57BL/6 forebrain embryo (14.5 days) \n", + "7774 C57BL/6 midbrain embryo (14.5 days) \n", + "7775 C57BL/6 brain embryo (14.5 days) \n", + "7776 K562 \n", + "7777 HEK293 genetically modified using site-specifi... \n", + "7778 skeletal muscle myoblast male adult (22 years) \n", + "7779 HeLa-S3 \n", + "7780 spleen female adult (51 year) \n", + "7781 stomach female adult (51 year) \n", + "7782 lower leg skin female adult (51 year) \n", + "7783 prostate gland male adult (54 years) \n", + "7784 lower leg skin male adult (37 years) \n", + "7785 testis male adult (54 years) \n", + "7786 testis male adult (54 years) \n", + "7787 VCaP \n", + "7788 skeletal muscle myoblast male adult (22 years) \n", + "7789 skeletal muscle myoblast male adult (22 years) \n", + "7790 HeLa-S3 \n", + "7791 HeLa-S3 \n", + "7792 omental fat pad male adult (37 years) \n", + "7793 testis male adult (54 years) \n", + "7794 lower leg skin female adult (51 year) \n", + "7795 tibial nerve female adult (53 years) \n", + "7796 tibial nerve female adult (53 years) \n", + "7797 HeLa-S3 \n", + "7798 HeLa-S3 \n", + "7799 spleen male adult (37 years) \n", + "7800 HeLa-S3 \n", + "7801 tibial nerve female adult (53 years) \n", + "7802 spleen male adult (37 years) \n", + "7803 spleen female adult (51 year) \n", + "7804 testis male adult (37 years) \n", + "7805 HeLa-S3 \n", + "7806 stomach male adult (54 years) \n", + "7807 tibial nerve female adult (53 years) \n", + "7808 LNCAP \n", + "7809 stomach male adult (54 years) \n", + "7810 spleen male adult (37 years) \n", + "7811 testis male adult (54 years) \n", + "7812 testis male adult (37 years) \n", + "7813 lower leg skin male adult (37 years) \n", + "7814 testis male adult (54 years) \n", + "7815 tibial nerve male adult (54 years) \n", + "7816 spleen male adult (37 years) \n", + "7817 HEK293 genetically modified using site-specifi... \n", + "7818 suprapubic skin female adult (51 year) \n", + "7819 spleen male adult (37 years) \n", + "7820 K562 \n", + "7821 spleen female adult (51 year) \n", + "7822 suprapubic skin female adult (51 year) \n", + "7823 tibial nerve female adult (53 years) \n", + "7824 spleen female adult (51 year) \n", + "7825 HeLa-S3 \n", + "7826 testis male adult (37 years) \n", + "7827 stomach male adult (54 years) \n", + "7828 prostate gland male adult (54 years) \n", + "7829 spleen female adult (51 year) \n", + "7830 testis male adult (37 years) \n", + "7831 testis male adult (37 years) \n", + "7832 tibial nerve female adult (53 years) \n", + "7833 K562 \n", + "7834 K562 \n", + "\n", + " Biosample Lab Project \\\n", + "0 limb Ali Mortazavi, UCI ENCODE \n", + "1 GM12892 Michael Snyder, Stanford ENCODE \n", + "2 HepG2 Gene Yeo, UCSD ENCODE \n", + "3 DND-41 Bradley Bernstein, Broad ENCODE \n", + "4 myometrial cell Thomas Gingeras, CSHL ENCODE \n", + "5 GM13977 Gregory Crawford, Duke ENCODE \n", + "6 HepG2 Gene Yeo, UCSD ENCODE \n", + "7 CH12.LX Bing Ren, UCSD ENCODE \n", + "8 primitive gut cell David Gilbert, FSU ENCODE \n", + "9 osteoblast Bradley Bernstein, Broad ENCODE \n", + "10 NB4 Sherman Weissman, Yale ENCODE \n", + "11 Karpas-422 Bradley Bernstein, Broad ENCODE \n", + "12 MEL cell line Michael Snyder, Stanford ENCODE \n", + "13 416B John Stamatoyannopoulos, UW ENCODE \n", + "14 K562 Michael Snyder, Stanford ENCODE \n", + "15 K562 Michael Snyder, Stanford ENCODE \n", + "16 K562 Michael Snyder, Stanford ENCODE \n", + "17 MEL cell line Michael Snyder, Stanford ENCODE \n", + "18 hepatocyte Gregory Crawford, Duke ENCODE \n", + "19 MEL cell line Michael Snyder, Stanford ENCODE \n", + "20 stomach Bing Ren, UCSD ENCODE \n", + "21 HGPS cell Gregory Crawford, Duke ENCODE \n", + "22 Peyer's patch Thomas Gingeras, CSHL ENCODE \n", + "23 stomach Thomas Gingeras, CSHL ENCODE \n", + "24 heart left ventricle Thomas Gingeras, CSHL ENCODE \n", + "25 esophagus squamous epithelium Thomas Gingeras, CSHL ENCODE \n", + "26 right lobe of liver Thomas Gingeras, CSHL ENCODE \n", + "27 B cell John Stamatoyannopoulos, UW ENCODE \n", + "28 HEK293 Michael Snyder, Stanford ENCODE \n", + "29 bone marrow macrophage Bing Ren, UCSD ENCODE \n", + "30 HeLa-S3 Thomas Gingeras, CSHL ENCODE \n", + "31 liver Bing Ren, UCSD ENCODE \n", + "32 fibroblast of pedal digit skin John Stamatoyannopoulos, UW ENCODE \n", + "33 transverse colon Thomas Gingeras, CSHL ENCODE \n", + "34 heart Bing Ren, UCSD ENCODE \n", + "35 hematopoietic stem cell Ross Hardison, PennState ENCODE \n", + "36 right lobe of liver Thomas Gingeras, CSHL ENCODE \n", + "37 T-helper 1 cell John Stamatoyannopoulos, UW ENCODE \n", + "38 liver Bing Ren, UCSD ENCODE \n", + "39 HEK293 John Stamatoyannopoulos, UW ENCODE \n", + "40 hindbrain Bing Ren, UCSD ENCODE \n", + "41 hepatocyte Richard Myers, HAIB ENCODE \n", + "42 K562 Sherman Weissman, Yale ENCODE \n", + "43 Caki2 Job Dekker, UMass ENCODE \n", + "44 Panc1 Job Dekker, UMass ENCODE \n", + "45 A549 Job Dekker, UMass ENCODE \n", + "46 liver Bing Ren, UCSD ENCODE \n", + "47 prostate gland Yijun Ruan, JAX ENCODE \n", + "48 GM12878 John Rinn, Broad ENCODE \n", + "49 GM12878 John Rinn, Broad ENCODE \n", + "50 HEK293 Peggy Farnham, USC ENCODE \n", + "51 GM12878 Michael Snyder, Stanford ENCODE \n", + "52 adipocyte John Stamatoyannopoulos, UW ENCODE \n", + "53 neural tube Bing Ren, UCSD ENCODE \n", + "54 neural tube Bing Ren, UCSD ENCODE \n", + "55 K562 Brenton Graveley, UConn ENCODE \n", + "56 HepG2 Gene Yeo, UCSD ENCODE \n", + "57 HepG2 Gene Yeo, UCSD ENCODE \n", + "58 HFF-Myc John Stamatoyannopoulos, UW ENCODE \n", + "59 gastrocnemius medialis Bradley Bernstein, Broad ENCODE \n", + "60 astrocyte of the cerebellum John Stamatoyannopoulos, UW ENCODE \n", + "61 MEL cell line Michael Snyder, Stanford ENCODE \n", + "62 C2C12 Barbara Wold, Caltech ENCODE \n", + "63 K562 Gene Yeo, UCSD ENCODE \n", + "64 G1E-ER4 Ross Hardison, PennState ENCODE \n", + "65 MCF-7 Michael Snyder, Stanford ENCODE \n", + "66 myocyte Barbara Wold, Caltech ENCODE \n", + "67 K562 Michael Snyder, Stanford ENCODE \n", + "68 esophagus squamous epithelium Michael Snyder, Stanford ENCODE \n", + "69 HepG2 Brenton Graveley, UConn ENCODE \n", + "70 transverse colon Richard Myers, HAIB ENCODE \n", + "71 neural tube Bing Ren, UCSD ENCODE \n", + "72 K562 Michael Snyder, Stanford ENCODE \n", + "73 G1E-ER4 Ross Hardison, PennState ENCODE \n", + "74 K562 Michael Snyder, Stanford ENCODE \n", + "75 G1E-ER4 Ross Hardison, PennState ENCODE \n", + "76 testis Bing Ren, UCSD ENCODE \n", + "77 G1E Ross Hardison, PennState ENCODE \n", + "78 K562 Michael Snyder, Stanford ENCODE \n", + "79 HepG2 Gene Yeo, UCSD ENCODE \n", + "80 HepG2 Yijun Ruan, JAX ENCODE \n", + "81 mammary epithelial cell Gregory Crawford, Duke ENCODE \n", + "82 MEL cell line Michael Snyder, Stanford ENCODE \n", + "83 embryonic facial prominence Bing Ren, UCSD ENCODE \n", + "84 H1-hESC Bradley Bernstein, Broad ENCODE \n", + "85 A549 Michael Snyder, Stanford ENCODE \n", + "86 forebrain Bing Ren, UCSD ENCODE \n", + "87 gastroesophageal sphincter Michael Snyder, Stanford ENCODE \n", + "88 E14TG2a.4 Ross Hardison, PennState ENCODE \n", + "89 transverse colon Michael Snyder, Stanford ENCODE \n", + "90 bone marrow Bing Ren, UCSD ENCODE \n", + "91 GM12891 Michael Snyder, Stanford ENCODE \n", + "92 SK-N-DZ Thomas Gingeras, CSHL ENCODE \n", + "93 fibroblast of arm Richard Myers, HAIB ENCODE \n", + "94 HeLa-S3 Richard Myers, HAIB ENCODE \n", + "95 SU-DHL-6 Bradley Bernstein, Broad ENCODE \n", + "96 OCI-LY7 Bradley Bernstein, Broad ENCODE \n", + "97 ACC112 Bradley Bernstein, Broad ENCODE \n", + "98 MCF-7 Bradley Bernstein, Broad ENCODE \n", + "99 common myeloid progenitor Ross Hardison, PennState ENCODE \n", + "... ... ... ... \n", + "7735 A549 Richard Myers, HAIB ENCODE \n", + "7736 K562 Michael Snyder, Stanford ENCODE \n", + "7737 GM12878 Barbara Wold, Caltech ENCODE \n", + "7738 H1-hESC Richard Myers, HAIB ENCODE \n", + "7739 H1-hESC Bradley Bernstein, Broad ENCODE \n", + "7740 H1-hESC Bradley Bernstein, Broad ENCODE \n", + "7741 H1-hESC Bradley Bernstein, Broad ENCODE \n", + "7742 H1-hESC Thomas Gingeras, CSHL ENCODE \n", + "7743 neural progenitor cell Thomas Gingeras, CSHL ENCODE \n", + "7744 neural progenitor cell Bradley Bernstein, Broad ENCODE \n", + "7745 prostate gland Ali Mortazavi, UCI ENCODE \n", + "7746 lower leg skin Richard Myers, HAIB ENCODE \n", + "7747 tibial nerve Bradley Bernstein, Broad ENCODE \n", + "7748 stomach Richard Myers, HAIB ENCODE \n", + "7749 suprapubic skin Michael Snyder, Stanford ENCODE \n", + "7750 spleen Thomas Gingeras, CSHL ENCODE \n", + "7751 spleen Thomas Gingeras, CSHL ENCODE \n", + "7752 prostate gland Ali Mortazavi, UCI ENCODE \n", + "7753 tibial nerve Bradley Bernstein, Broad ENCODE \n", + "7754 prostate gland Richard Myers, HAIB ENCODE \n", + "7755 T-helper 17 cell John Stamatoyannopoulos, UW ENCODE \n", + "7756 thyroid gland John Stamatoyannopoulos, UW ENCODE \n", + "7757 HEK293 Michael Snyder, Stanford ENCODE \n", + "7758 HEK293 Michael Snyder, Stanford ENCODE \n", + "7759 HeLa-S3 Kevin Struhl, HMS ENCODE \n", + "7760 hindbrain Bing Ren, UCSD ENCODE \n", + "7761 midbrain Bing Ren, UCSD ENCODE \n", + "7762 brain Bing Ren, UCSD ENCODE \n", + "7763 midbrain Bing Ren, UCSD ENCODE \n", + "7764 hindbrain Bing Ren, UCSD ENCODE \n", + "7765 HEK293T Michael Snyder, Stanford ENCODE \n", + "7766 neural progenitor cell Ali Mortazavi, UCI ENCODE \n", + "7767 neural progenitor cell Ali Mortazavi, UCI ENCODE \n", + "7768 RWPE1 Michael Snyder, Stanford ENCODE \n", + "7769 HeLa-S3 Sherman Weissman, Yale ENCODE \n", + "7770 skeletal muscle myoblast Bradley Bernstein, Broad ENCODE \n", + "7771 HeLa-S3 Peggy Farnham, USC ENCODE \n", + "7772 midbrain Bing Ren, UCSD ENCODE \n", + "7773 forebrain Bing Ren, UCSD ENCODE \n", + "7774 midbrain Bing Ren, UCSD ENCODE \n", + "7775 brain Thomas Gingeras, CSHL ENCODE \n", + "7776 K562 Michael Snyder, Stanford ENCODE \n", + "7777 HEK293 Michael Snyder, Stanford ENCODE \n", + "7778 skeletal muscle myoblast Bradley Bernstein, Broad ENCODE \n", + "7779 HeLa-S3 Kevin Struhl, HMS ENCODE \n", + "7780 spleen Michael Snyder, Stanford ENCODE \n", + "7781 stomach Thomas Gingeras, CSHL ENCODE \n", + "7782 lower leg skin Michael Snyder, Stanford ENCODE \n", + "7783 prostate gland Richard Myers, HAIB ENCODE \n", + "7784 lower leg skin Ali Mortazavi, UCI ENCODE \n", + "7785 testis Thomas Gingeras, CSHL ENCODE \n", + "7786 testis Thomas Gingeras, CSHL ENCODE \n", + "7787 VCaP Michael Snyder, Stanford ENCODE \n", + "7788 skeletal muscle myoblast Bradley Bernstein, Broad ENCODE \n", + "7789 skeletal muscle myoblast Bradley Bernstein, Broad ENCODE \n", + "7790 HeLa-S3 Kevin Struhl, HMS ENCODE \n", + "7791 HeLa-S3 Peggy Farnham, USC ENCODE \n", + "7792 omental fat pad Michael Snyder, Stanford ENCODE \n", + "7793 testis Ali Mortazavi, UCI ENCODE \n", + "7794 lower leg skin Michael Snyder, Stanford ENCODE \n", + "7795 tibial nerve Thomas Gingeras, CSHL ENCODE \n", + "7796 tibial nerve Bradley Bernstein, Broad ENCODE \n", + "7797 HeLa-S3 Kevin Struhl, HMS ENCODE \n", + "7798 HeLa-S3 Kevin Struhl, HMS ENCODE \n", + "7799 spleen Michael Snyder, Stanford ENCODE \n", + "7800 HeLa-S3 Sherman Weissman, Yale ENCODE \n", + "7801 tibial nerve Michael Snyder, Stanford ENCODE \n", + "7802 spleen Richard Myers, HAIB ENCODE \n", + "7803 spleen Thomas Gingeras, CSHL ENCODE \n", + "7804 testis Thomas Gingeras, CSHL ENCODE \n", + "7805 HeLa-S3 Sherman Weissman, Yale ENCODE \n", + "7806 stomach Michael Snyder, Stanford ENCODE \n", + "7807 tibial nerve Bradley Bernstein, Broad ENCODE \n", + "7808 LNCAP Michael Snyder, Stanford ENCODE \n", + "7809 stomach Richard Myers, HAIB ENCODE \n", + "7810 spleen Richard Myers, HAIB ENCODE \n", + "7811 testis Ali Mortazavi, UCI ENCODE \n", + "7812 testis Michael Snyder, Stanford ENCODE \n", + "7813 lower leg skin Michael Snyder, Stanford ENCODE \n", + "7814 testis John Stamatoyannopoulos, UW ENCODE \n", + "7815 tibial nerve Thomas Gingeras, CSHL ENCODE \n", + "7816 spleen Thomas Gingeras, CSHL ENCODE \n", + "7817 HEK293 Michael Snyder, Stanford ENCODE \n", + "7818 suprapubic skin Richard Myers, HAIB ENCODE \n", + "7819 spleen Michael Snyder, Stanford ENCODE \n", + "7820 K562 Gene Yeo, UCSD ENCODE \n", + "7821 spleen Richard Myers, HAIB ENCODE \n", + "7822 suprapubic skin Richard Myers, HAIB ENCODE \n", + "7823 tibial nerve Thomas Gingeras, CSHL ENCODE \n", + "7824 spleen Michael Snyder, Stanford ENCODE \n", + "7825 HeLa-S3 Sherman Weissman, Yale ENCODE \n", + "7826 testis Ali Mortazavi, UCI ENCODE \n", + "7827 stomach Michael Snyder, Stanford ENCODE \n", + "7828 prostate gland Michael Snyder, Stanford ENCODE \n", + "7829 spleen Thomas Gingeras, CSHL ENCODE \n", + "7830 testis Thomas Gingeras, CSHL ENCODE \n", + "7831 testis Thomas Gingeras, CSHL ENCODE \n", + "7832 tibial nerve Bradley Bernstein, Broad ENCODE \n", + "7833 K562 Gene Yeo, UCSD ENCODE \n", + "7834 K562 Gene Yeo, UCSD ENCODE \n", + "\n", + " Species Biosample type Date released \\\n", + "0 Mus musculus tissue 2017-08-15 \n", + "1 Homo sapiens immortalized cell line 2011-10-29 \n", + "2 Homo sapiens immortalized cell line 2016-04-26 \n", + "3 Homo sapiens immortalized cell line 2012-03-06 \n", + "4 Homo sapiens primary cell 2015-08-18 \n", + "5 Homo sapiens immortalized cell line 2012-08-28 \n", + "6 Homo sapiens immortalized cell line 2015-11-09 \n", + "7 Mus musculus immortalized cell line 2012-09-05 \n", + "8 Homo sapiens in vitro differentiated cells 2015-07-21 \n", + "9 Homo sapiens primary cell 2011-02-10 \n", + "10 Homo sapiens immortalized cell line 2011-10-29 \n", + "11 Homo sapiens immortalized cell line 2014-07-11 \n", + "12 Mus musculus immortalized cell line 2012-06-15 \n", + "13 Mus musculus immortalized cell line 2012-07-10 \n", + "14 Homo sapiens immortalized cell line 2017-11-18 \n", + "15 Homo sapiens immortalized cell line 2017-11-18 \n", + "16 Homo sapiens immortalized cell line 2017-11-18 \n", + "17 Mus musculus immortalized cell line 2012-08-20 \n", + "18 Homo sapiens primary cell 2011-04-19 \n", + "19 Mus musculus immortalized cell line 2012-08-20 \n", + "20 Mus musculus tissue 2014-06-30 \n", + "21 Homo sapiens immortalized cell line 2011-04-19 \n", + "22 Homo sapiens tissue 2016-05-03 \n", + "23 Homo sapiens tissue 2016-08-04 \n", + "24 Homo sapiens tissue 2016-08-05 \n", + "25 Homo sapiens tissue 2016-06-13 \n", + "26 Homo sapiens tissue 2016-08-05 \n", + "27 Homo sapiens primary cell 2011-10-19 \n", + "28 Homo sapiens immortalized cell line 2016-10-07 \n", + "29 Mus musculus primary cell 2012-05-04 \n", + "30 Homo sapiens immortalized cell line 2011-10-17 \n", + "31 Mus musculus tissue 2014-06-30 \n", + "32 Homo sapiens primary cell 2011-04-01 \n", + "33 Homo sapiens tissue 2016-05-23 \n", + "34 Mus musculus tissue 2016-02-17 \n", + "35 Mus musculus stem cell 2017-01-04 \n", + "36 Homo sapiens tissue 2016-08-05 \n", + "37 Homo sapiens primary cell 2012-07-23 \n", + "38 Mus musculus tissue 2014-06-30 \n", + "39 Homo sapiens immortalized cell line 2011-02-11 \n", + "40 Mus musculus tissue 2016-02-17 \n", + "41 Homo sapiens primary cell 2011-09-30 \n", + "42 Homo sapiens immortalized cell line 2011-09-08 \n", + "43 Homo sapiens immortalized cell line 2016-05-13 \n", + "44 Homo sapiens immortalized cell line 2016-05-13 \n", + "45 Homo sapiens immortalized cell line 2016-05-13 \n", + "46 Mus musculus tissue 2011-07-22 \n", + "47 Homo sapiens tissue 2011-10-17 \n", + "48 Homo sapiens immortalized cell line 2016-05-04 \n", + "49 Homo sapiens immortalized cell line 2016-05-04 \n", + "50 Homo sapiens immortalized cell line 2017-06-01 \n", + "51 Homo sapiens immortalized cell line 2012-05-14 \n", + "52 Mus musculus in vitro differentiated cells 2016-11-02 \n", + "53 Mus musculus tissue 2017-10-10 \n", + "54 Mus musculus tissue 2017-10-10 \n", + "55 Homo sapiens immortalized cell line 2016-06-30 \n", + "56 Homo sapiens immortalized cell line 2016-04-26 \n", + "57 Homo sapiens immortalized cell line 2017-08-15 \n", + "58 Homo sapiens primary cell 2011-11-17 \n", + "59 Homo sapiens tissue 2017-01-27 \n", + "60 Homo sapiens primary cell 2011-11-17 \n", + "61 Mus musculus immortalized cell line 2012-08-20 \n", + "62 Mus musculus immortalized cell line 2011-11-28 \n", + "63 Homo sapiens immortalized cell line 2016-09-21 \n", + "64 Mus musculus stem cell 2012-02-13 \n", + "65 Homo sapiens immortalized cell line 2014-07-07 \n", + "66 Mus musculus in vitro differentiated cells 2011-11-28 \n", + "67 Homo sapiens immortalized cell line 2014-07-07 \n", + "68 Homo sapiens tissue 2017-06-21 \n", + "69 Homo sapiens immortalized cell line 2014-12-17 \n", + "70 Homo sapiens tissue 2017-06-15 \n", + "71 Mus musculus tissue 2014-06-30 \n", + "72 Homo sapiens immortalized cell line 2011-10-29 \n", + "73 Mus musculus stem cell 2012-08-13 \n", + "74 Homo sapiens immortalized cell line 2012-08-20 \n", + "75 Mus musculus stem cell 2012-08-13 \n", + "76 Mus musculus tissue 2012-05-04 \n", + "77 Mus musculus stem cell 2012-08-06 \n", + "78 Homo sapiens immortalized cell line 2011-10-29 \n", + "79 Homo sapiens immortalized cell line 2015-07-15 \n", + "80 Homo sapiens immortalized cell line 2011-10-17 \n", + "81 Homo sapiens primary cell 2011-06-14 \n", + "82 Mus musculus immortalized cell line 2012-06-15 \n", + "83 Mus musculus tissue 2015-06-23 \n", + "84 Homo sapiens stem cell 2016-12-06 \n", + "85 Homo sapiens immortalized cell line 2012-05-14 \n", + "86 Mus musculus tissue 2014-06-30 \n", + "87 Homo sapiens tissue 2016-06-15 \n", + "88 Mus musculus stem cell 2014-02-10 \n", + "89 Homo sapiens tissue 2016-06-15 \n", + "90 Mus musculus tissue 2011-07-22 \n", + "91 Homo sapiens immortalized cell line 2011-10-29 \n", + "92 Homo sapiens immortalized cell line 2015-04-14 \n", + "93 Homo sapiens primary cell 2016-08-05 \n", + "94 Homo sapiens immortalized cell line 2016-08-05 \n", + "95 Homo sapiens immortalized cell line 2014-07-11 \n", + "96 Homo sapiens immortalized cell line 2014-07-11 \n", + "97 Homo sapiens immortalized cell line 2014-09-04 \n", + "98 Homo sapiens immortalized cell line 2014-07-11 \n", + "99 Mus musculus primary cell 2014-09-29 \n", + "... ... ... ... \n", + "7735 Homo sapiens immortalized cell line 2012-02-29 \n", + "7736 Homo sapiens immortalized cell line 2012-05-14 \n", + "7737 Homo sapiens immortalized cell line 2014-06-30 \n", + "7738 Homo sapiens stem cell 2015-10-13 \n", + "7739 Homo sapiens stem cell 2012-03-06 \n", + "7740 Homo sapiens stem cell 2011-02-10 \n", + "7741 Homo sapiens stem cell 2012-03-06 \n", + "7742 Homo sapiens stem cell 2012-02-22 \n", + "7743 Homo sapiens in vitro differentiated cells 2015-01-08 \n", + "7744 Homo sapiens in vitro differentiated cells 2016-06-14 \n", + "7745 Homo sapiens tissue 2016-08-01 \n", + "7746 Homo sapiens tissue 2017-06-15 \n", + "7747 Homo sapiens tissue 2017-01-27 \n", + "7748 Homo sapiens tissue 2017-06-15 \n", + "7749 Homo sapiens tissue 2017-04-04 \n", + "7750 Homo sapiens tissue 2016-08-05 \n", + "7751 Homo sapiens tissue 2016-08-05 \n", + "7752 Homo sapiens tissue 2016-07-29 \n", + "7753 Homo sapiens tissue 2017-01-27 \n", + "7754 Homo sapiens tissue 2017-10-31 \n", + "7755 Homo sapiens primary cell 2012-07-23 \n", + "7756 Homo sapiens tissue 2016-05-09 \n", + "7757 Homo sapiens immortalized cell line 2017-11-30 \n", + "7758 Homo sapiens immortalized cell line 2017-11-30 \n", + "7759 Homo sapiens immortalized cell line 2011-10-29 \n", + "7760 Mus musculus tissue 2014-06-30 \n", + "7761 Mus musculus tissue 2014-06-30 \n", + "7762 Mus musculus tissue 2012-04-13 \n", + "7763 Mus musculus tissue 2014-06-30 \n", + "7764 Mus musculus tissue 2016-02-18 \n", + "7765 Homo sapiens immortalized cell line 2017-04-14 \n", + "7766 Homo sapiens in vitro differentiated cells 2016-01-19 \n", + "7767 Homo sapiens in vitro differentiated cells 2016-02-02 \n", + "7768 Homo sapiens immortalized cell line 2017-07-21 \n", + "7769 Homo sapiens immortalized cell line 2011-10-29 \n", + "7770 Homo sapiens primary cell 2011-02-10 \n", + "7771 Homo sapiens immortalized cell line 2011-10-29 \n", + "7772 Mus musculus tissue 2014-06-30 \n", + "7773 Mus musculus tissue 2014-06-30 \n", + "7774 Mus musculus tissue 2014-06-30 \n", + "7775 Mus musculus tissue 2012-09-05 \n", + "7776 Homo sapiens immortalized cell line 2016-08-05 \n", + "7777 Homo sapiens immortalized cell line 2017-11-30 \n", + "7778 Homo sapiens primary cell 2011-02-10 \n", + "7779 Homo sapiens immortalized cell line 2011-10-29 \n", + "7780 Homo sapiens tissue 2017-03-14 \n", + "7781 Homo sapiens tissue 2016-08-05 \n", + "7782 Homo sapiens tissue 2017-03-20 \n", + "7783 Homo sapiens tissue 2017-06-15 \n", + "7784 Homo sapiens tissue 2016-07-29 \n", + "7785 Homo sapiens tissue 2016-05-23 \n", + "7786 Homo sapiens tissue 2016-08-04 \n", + "7787 Homo sapiens immortalized cell line 2017-07-21 \n", + "7788 Homo sapiens primary cell 2011-02-10 \n", + "7789 Homo sapiens primary cell 2011-02-10 \n", + "7790 Homo sapiens immortalized cell line 2011-10-29 \n", + "7791 Homo sapiens immortalized cell line 2011-10-29 \n", + "7792 Homo sapiens tissue 2017-06-23 \n", + "7793 Homo sapiens tissue 2016-07-29 \n", + "7794 Homo sapiens tissue 2016-11-07 \n", + "7795 Homo sapiens tissue 2016-02-18 \n", + "7796 Homo sapiens tissue 2017-01-27 \n", + "7797 Homo sapiens immortalized cell line 2011-10-29 \n", + "7798 Homo sapiens immortalized cell line 2011-10-29 \n", + "7799 Homo sapiens tissue 2017-03-14 \n", + "7800 Homo sapiens immortalized cell line 2011-10-29 \n", + "7801 Homo sapiens tissue 2016-12-08 \n", + "7802 Homo sapiens tissue 2017-10-31 \n", + "7803 Homo sapiens tissue 2016-05-03 \n", + "7804 Homo sapiens tissue 2016-05-23 \n", + "7805 Homo sapiens immortalized cell line 2011-10-29 \n", + "7806 Homo sapiens tissue 2016-06-15 \n", + "7807 Homo sapiens tissue 2017-01-27 \n", + "7808 Homo sapiens immortalized cell line 2017-06-29 \n", + "7809 Homo sapiens tissue 2017-06-15 \n", + "7810 Homo sapiens tissue 2017-06-15 \n", + "7811 Homo sapiens tissue 2016-07-29 \n", + "7812 Homo sapiens tissue 2017-06-21 \n", + "7813 Homo sapiens tissue 2017-03-14 \n", + "7814 Homo sapiens tissue 2017-11-01 \n", + "7815 Homo sapiens tissue 2016-02-18 \n", + "7816 Homo sapiens tissue 2016-05-03 \n", + "7817 Homo sapiens immortalized cell line 2017-11-30 \n", + "7818 Homo sapiens tissue 2017-06-15 \n", + "7819 Homo sapiens tissue 2016-07-11 \n", + "7820 Homo sapiens immortalized cell line 2015-07-15 \n", + "7821 Homo sapiens tissue 2017-06-15 \n", + "7822 Homo sapiens tissue 2017-06-15 \n", + "7823 Homo sapiens tissue 2016-08-05 \n", + "7824 Homo sapiens tissue 2016-06-15 \n", + "7825 Homo sapiens immortalized cell line 2011-10-29 \n", + "7826 Homo sapiens tissue 2016-07-29 \n", + "7827 Homo sapiens tissue 2016-07-06 \n", + "7828 Homo sapiens tissue 2016-11-29 \n", + "7829 Homo sapiens tissue 2016-05-03 \n", + "7830 Homo sapiens tissue 2016-08-04 \n", + "7831 Homo sapiens tissue 2016-08-05 \n", + "7832 Homo sapiens tissue 2017-01-27 \n", + "7833 Homo sapiens immortalized cell line 2016-04-26 \n", + "7834 Homo sapiens immortalized cell line 2016-10-31 \n", + "\n", + " Month released Assay category \\\n", + "0 August, 2017 Transcription \n", + "1 October, 2011 DNA binding \n", + "2 April, 2016 RNA binding \n", + "3 March, 2012 DNA binding \n", + "4 August, 2015 Transcription \n", + "5 August, 2012 DNA accessibility \n", + "6 November, 2015 RNA binding \n", + "7 September, 2012 DNA binding \n", + "8 July, 2015 Replication timing \n", + "9 February, 2011 DNA binding \n", + "10 October, 2011 DNA binding \n", + "11 July, 2014 DNA binding \n", + "12 June, 2012 DNA binding \n", + "13 July, 2012 Transcription \n", + "14 November, 2017 Transcription \n", + "15 November, 2017 Transcription \n", + "16 November, 2017 Transcription \n", + "17 August, 2012 DNA binding \n", + "18 April, 2011 DNA accessibility \n", + "19 August, 2012 DNA binding \n", + "20 June, 2014 DNA binding \n", + "21 April, 2011 DNA accessibility \n", + "22 May, 2016 Transcription \n", + "23 August, 2016 Transcription \n", + "24 August, 2016 Transcription \n", + "25 June, 2016 Transcription \n", + "26 August, 2016 Transcription \n", + "27 October, 2011 DNA accessibility \n", + "28 October, 2016 DNA binding \n", + "29 May, 2012 Transcription \n", + "30 October, 2011 Transcription \n", + "31 June, 2014 DNA binding \n", + "32 April, 2011 Transcription \n", + "33 May, 2016 Transcription \n", + "34 February, 2016 DNA binding \n", + "35 January, 2017 Transcription \n", + "36 August, 2016 Transcription \n", + "37 July, 2012 DNA accessibility \n", + "38 June, 2014 DNA binding \n", + "39 February, 2011 DNA binding \n", + "40 February, 2016 DNA binding \n", + "41 September, 2011 DNA methylation \n", + "42 September, 2011 Transcription \n", + "43 May, 2016 3D chromatin structure \n", + "44 May, 2016 3D chromatin structure \n", + "45 May, 2016 3D chromatin structure \n", + "46 July, 2011 DNA binding \n", + "47 October, 2011 Transcription \n", + "48 May, 2016 RNA binding \n", + "49 May, 2016 RNA binding \n", + "50 June, 2017 DNA binding \n", + "51 May, 2012 DNA binding \n", + "52 November, 2016 DNA accessibility \n", + "53 October, 2017 DNA accessibility \n", + "54 October, 2017 DNA accessibility \n", + "55 June, 2016 Transcription \n", + "56 April, 2016 RNA binding \n", + "57 August, 2017 RNA binding \n", + "58 November, 2011 DNA binding \n", + "59 January, 2017 DNA binding \n", + "60 November, 2011 DNA binding \n", + "61 August, 2012 DNA binding \n", + "62 November, 2011 DNA binding \n", + "63 September, 2016 RNA binding \n", + "64 February, 2012 DNA binding \n", + "65 July, 2014 DNA binding \n", + "66 November, 2011 DNA binding \n", + "67 July, 2014 DNA binding \n", + "68 June, 2017 DNA accessibility \n", + "69 December, 2014 Transcription \n", + "70 June, 2017 DNA binding \n", + "71 June, 2014 DNA binding \n", + "72 October, 2011 DNA binding \n", + "73 August, 2012 Transcription \n", + "74 August, 2012 DNA binding \n", + "75 August, 2012 Transcription \n", + "76 May, 2012 Transcription \n", + "77 August, 2012 DNA binding \n", + "78 October, 2011 DNA binding \n", + "79 July, 2015 RNA binding \n", + "80 October, 2011 Transcription \n", + "81 June, 2011 Transcription \n", + "82 June, 2012 DNA binding \n", + "83 June, 2015 DNA binding \n", + "84 December, 2016 DNA binding \n", + "85 May, 2012 DNA binding \n", + "86 June, 2014 DNA binding \n", + "87 June, 2016 DNA accessibility \n", + "88 February, 2014 DNA binding \n", + "89 June, 2016 DNA accessibility \n", + "90 July, 2011 DNA binding \n", + "91 October, 2011 DNA binding \n", + "92 April, 2015 Transcription \n", + "93 August, 2016 Genotyping \n", + "94 August, 2016 Genotyping \n", + "95 July, 2014 DNA binding \n", + "96 July, 2014 DNA binding \n", + "97 September, 2014 DNA binding \n", + "98 July, 2014 DNA binding \n", + "99 September, 2014 Transcription \n", + "... ... ... \n", + "7735 February, 2012 DNA binding \n", + "7736 May, 2012 DNA binding \n", + "7737 June, 2014 Transcription \n", + "7738 October, 2015 DNA methylation \n", + "7739 March, 2012 DNA binding \n", + "7740 February, 2011 DNA binding \n", + "7741 March, 2012 DNA binding \n", + "7742 February, 2012 Transcription \n", + "7743 January, 2015 Transcription \n", + "7744 June, 2016 DNA binding \n", + "7745 August, 2016 Transcription \n", + "7746 June, 2017 DNA methylation \n", + "7747 January, 2017 DNA binding \n", + "7748 June, 2017 DNA binding \n", + "7749 April, 2017 DNA binding \n", + "7750 August, 2016 Transcription \n", + "7751 August, 2016 Transcription \n", + "7752 July, 2016 Transcription \n", + "7753 January, 2017 DNA binding \n", + "7754 October, 2017 DNA binding \n", + "7755 July, 2012 DNA accessibility \n", + "7756 May, 2016 DNA accessibility \n", + "7757 November, 2017 DNA binding \n", + "7758 November, 2017 DNA binding \n", + "7759 October, 2011 DNA binding \n", + "7760 June, 2014 DNA binding \n", + "7761 June, 2014 DNA binding \n", + "7762 April, 2012 DNA binding \n", + "7763 June, 2014 DNA binding \n", + "7764 February, 2016 DNA binding \n", + "7765 April, 2017 DNA binding \n", + "7766 January, 2016 Transcription \n", + "7767 February, 2016 Transcription \n", + "7768 July, 2017 DNA binding \n", + "7769 October, 2011 DNA binding \n", + "7770 February, 2011 DNA binding \n", + "7771 October, 2011 DNA binding \n", + "7772 June, 2014 DNA binding \n", + "7773 June, 2014 DNA binding \n", + "7774 June, 2014 DNA binding \n", + "7775 September, 2012 Transcription \n", + "7776 August, 2016 DNA binding \n", + "7777 November, 2017 DNA binding \n", + "7778 February, 2011 DNA binding \n", + "7779 October, 2011 DNA binding \n", + "7780 March, 2017 DNA binding \n", + "7781 August, 2016 Transcription \n", + "7782 March, 2017 DNA binding \n", + "7783 June, 2017 DNA methylation \n", + "7784 July, 2016 Transcription \n", + "7785 May, 2016 Transcription \n", + "7786 August, 2016 Transcription \n", + "7787 July, 2017 DNA binding \n", + "7788 February, 2011 DNA binding \n", + "7789 February, 2011 DNA binding \n", + "7790 October, 2011 DNA binding \n", + "7791 October, 2011 DNA binding \n", + "7792 June, 2017 DNA binding \n", + "7793 July, 2016 Transcription \n", + "7794 November, 2016 DNA binding \n", + "7795 February, 2016 Transcription \n", + "7796 January, 2017 DNA binding \n", + "7797 October, 2011 DNA binding \n", + "7798 October, 2011 DNA binding \n", + "7799 March, 2017 DNA binding \n", + "7800 October, 2011 DNA binding \n", + "7801 December, 2016 DNA binding \n", + "7802 October, 2017 DNA binding \n", + "7803 May, 2016 Transcription \n", + "7804 May, 2016 Transcription \n", + "7805 October, 2011 DNA binding \n", + "7806 June, 2016 DNA accessibility \n", + "7807 January, 2017 DNA binding \n", + "7808 June, 2017 DNA binding \n", + "7809 June, 2017 DNA methylation \n", + "7810 June, 2017 DNA methylation \n", + "7811 July, 2016 Transcription \n", + "7812 June, 2017 DNA accessibility \n", + "7813 March, 2017 DNA binding \n", + "7814 November, 2017 DNA accessibility \n", + "7815 February, 2016 Transcription \n", + "7816 May, 2016 Transcription \n", + "7817 November, 2017 DNA binding \n", + "7818 June, 2017 DNA methylation \n", + "7819 July, 2016 DNA binding \n", + "7820 July, 2015 RNA binding \n", + "7821 June, 2017 DNA methylation \n", + "7822 June, 2017 DNA binding \n", + "7823 August, 2016 Transcription \n", + "7824 June, 2016 DNA accessibility \n", + "7825 October, 2011 DNA binding \n", + "7826 July, 2016 Transcription \n", + "7827 July, 2016 DNA binding \n", + "7828 November, 2016 DNA binding \n", + "7829 May, 2016 Transcription \n", + "7830 August, 2016 Transcription \n", + "7831 August, 2016 Transcription \n", + "7832 January, 2017 DNA binding \n", + "7833 April, 2016 RNA binding \n", + "7834 October, 2016 RNA binding \n", + "\n", + " Assay Type Assay name \\\n", + "0 RNA-seq microRNA-seq \n", + "1 ChIP-seq ChIP-seq \n", + "2 eCLIP eCLIP \n", + "3 ChIP-seq ChIP-seq \n", + "4 RNA-seq RAMPAGE \n", + "5 DNase-seq DNase-seq \n", + "6 eCLIP eCLIP \n", + "7 ChIP-seq ChIP-seq \n", + "8 Repli-chip Repli-chip \n", + "9 ChIP-seq ChIP-seq \n", + "10 ChIP-seq ChIP-seq \n", + "11 ChIP-seq ChIP-seq \n", + "12 ChIP-seq ChIP-seq \n", + "13 RNA-seq polyA mRNA RNA-seq \n", + "14 Knockdown RNAseq CRISPRi RNA-seq \n", + "15 Knockdown RNAseq CRISPRi RNA-seq \n", + "16 Knockdown RNAseq CRISPRi RNA-seq \n", + "17 ChIP-seq ChIP-seq \n", + "18 DNase-seq DNase-seq \n", + "19 ChIP-seq ChIP-seq \n", + "20 ChIP-seq ChIP-seq \n", + "21 DNase-seq DNase-seq \n", + "22 RNA-seq total RNA-seq \n", + "23 RNA-seq total RNA-seq \n", + "24 RNA-seq RAMPAGE \n", + "25 RNA-seq small RNA-seq \n", + "26 RNA-seq small RNA-seq \n", + "27 DNase-seq DNase-seq \n", + "28 ChIP-seq ChIP-seq \n", + "29 RNA-seq polyA mRNA RNA-seq \n", + "30 RNA-seq polyA mRNA RNA-seq \n", + "31 ChIP-seq ChIP-seq \n", + "32 transcription profiling by array assay RNA microarray \n", + "33 RNA-seq small RNA-seq \n", + "34 ChIP-seq ChIP-seq \n", + "35 RNA-seq total RNA-seq \n", + "36 RNA-seq RAMPAGE \n", + "37 DNase-seq DNase-seq \n", + "38 ChIP-seq ChIP-seq \n", + "39 ChIP-seq ChIP-seq \n", + "40 ChIP-seq ChIP-seq \n", + "41 RRBS RRBS \n", + "42 RNA-seq polyA mRNA RNA-seq \n", + "43 HiC Hi-C \n", + "44 HiC Hi-C \n", + "45 HiC Hi-C \n", + "46 ChIP-seq ChIP-seq \n", + "47 RNA-PET RNA-PET \n", + "48 RIP-seq RIP-seq \n", + "49 RIP-seq RIP-seq \n", + "50 ChIP-seq ChIP-seq \n", + "51 ChIP-seq ChIP-seq \n", + "52 DNase-seq DNase-seq \n", + "53 ATAC-seq ATAC-seq \n", + "54 ATAC-seq ATAC-seq \n", + "55 Knockdown RNAseq shRNA RNA-seq \n", + "56 eCLIP eCLIP \n", + "57 eCLIP eCLIP \n", + "58 ChIP-seq ChIP-seq \n", + "59 ChIP-seq ChIP-seq \n", + "60 ChIP-seq ChIP-seq \n", + "61 ChIP-seq ChIP-seq \n", + "62 ChIP-seq ChIP-seq \n", + "63 eCLIP eCLIP \n", + "64 ChIP-seq ChIP-seq \n", + "65 ChIP-seq ChIP-seq \n", + "66 ChIP-seq ChIP-seq \n", + "67 ChIP-seq ChIP-seq \n", + "68 ATAC-seq ATAC-seq \n", + "69 Knockdown RNAseq shRNA RNA-seq \n", + "70 ChIP-seq ChIP-seq \n", + "71 ChIP-seq ChIP-seq \n", + "72 ChIP-seq ChIP-seq \n", + "73 RNA-seq polyA mRNA RNA-seq \n", + "74 ChIP-seq ChIP-seq \n", + "75 RNA-seq polyA mRNA RNA-seq \n", + "76 RNA-seq polyA mRNA RNA-seq \n", + "77 ChIP-seq ChIP-seq \n", + "78 ChIP-seq ChIP-seq \n", + "79 eCLIP eCLIP \n", + "80 RNA-PET RNA-PET \n", + "81 transcription profiling by array assay RNA microarray \n", + "82 ChIP-seq ChIP-seq \n", + "83 ChIP-seq ChIP-seq \n", + "84 ChIP-seq ChIP-seq \n", + "85 ChIP-seq ChIP-seq \n", + "86 ChIP-seq ChIP-seq \n", + "87 ATAC-seq ATAC-seq \n", + "88 ChIP-seq ChIP-seq \n", + "89 ATAC-seq ATAC-seq \n", + "90 ChIP-seq ChIP-seq \n", + "91 ChIP-seq ChIP-seq \n", + "92 RNA-seq RAMPAGE \n", + "93 comparative genomic hybridization by array genotyping array \n", + "94 comparative genomic hybridization by array genotyping array \n", + "95 ChIP-seq ChIP-seq \n", + "96 ChIP-seq ChIP-seq \n", + "97 ChIP-seq ChIP-seq \n", + "98 ChIP-seq ChIP-seq \n", + "99 RNA-seq total RNA-seq \n", + "... ... ... \n", + "7735 ChIP-seq ChIP-seq \n", + "7736 ChIP-seq ChIP-seq \n", + "7737 RNA-seq single cell RNA-seq \n", + "7738 whole-genome shotgun bisulfite sequencing WGBS \n", + "7739 ChIP-seq ChIP-seq \n", + "7740 ChIP-seq ChIP-seq \n", + "7741 ChIP-seq ChIP-seq \n", + "7742 RNA-seq small RNA-seq \n", + "7743 RNA-seq small RNA-seq \n", + "7744 ChIP-seq ChIP-seq \n", + "7745 microRNA counts microRNA counts \n", + "7746 DNA methylation profiling by array assay DNAme array \n", + "7747 ChIP-seq ChIP-seq \n", + "7748 ChIP-seq ChIP-seq \n", + "7749 ChIP-seq ChIP-seq \n", + "7750 RNA-seq RAMPAGE \n", + "7751 RNA-seq RAMPAGE \n", + "7752 RNA-seq microRNA-seq \n", + "7753 ChIP-seq ChIP-seq \n", + "7754 ChIP-seq ChIP-seq \n", + "7755 DNase-seq DNase-seq \n", + "7756 DNase-seq DNase-seq \n", + "7757 ChIP-seq ChIP-seq \n", + "7758 ChIP-seq ChIP-seq \n", + "7759 ChIP-seq ChIP-seq \n", + "7760 ChIP-seq ChIP-seq \n", + "7761 ChIP-seq ChIP-seq \n", + "7762 ChIP-seq ChIP-seq \n", + "7763 ChIP-seq ChIP-seq \n", + "7764 ChIP-seq ChIP-seq \n", + "7765 ChIP-seq ChIP-seq \n", + "7766 microRNA counts microRNA counts \n", + "7767 RNA-seq microRNA-seq \n", + "7768 ChIP-seq ChIP-seq \n", + "7769 ChIP-seq ChIP-seq \n", + "7770 ChIP-seq ChIP-seq \n", + "7771 ChIP-seq ChIP-seq \n", + "7772 ChIP-seq ChIP-seq \n", + "7773 ChIP-seq ChIP-seq \n", + "7774 ChIP-seq ChIP-seq \n", + "7775 RNA-seq polyA mRNA RNA-seq \n", + "7776 ChIP-seq ChIP-seq \n", + "7777 ChIP-seq ChIP-seq \n", + "7778 ChIP-seq ChIP-seq \n", + "7779 ChIP-seq ChIP-seq \n", + "7780 ChIP-seq ChIP-seq \n", + "7781 RNA-seq RAMPAGE \n", + "7782 ChIP-seq ChIP-seq \n", + "7783 DNA methylation profiling by array assay DNAme array \n", + "7784 microRNA counts microRNA counts \n", + "7785 RNA-seq small RNA-seq \n", + "7786 RNA-seq total RNA-seq \n", + "7787 ChIP-seq ChIP-seq \n", + "7788 ChIP-seq ChIP-seq \n", + "7789 ChIP-seq ChIP-seq \n", + "7790 ChIP-seq ChIP-seq \n", + "7791 ChIP-seq ChIP-seq \n", + "7792 ChIP-seq ChIP-seq \n", + "7793 microRNA counts microRNA counts \n", + "7794 ChIP-seq ChIP-seq \n", + "7795 RNA-seq total RNA-seq \n", + "7796 ChIP-seq ChIP-seq \n", + "7797 ChIP-seq ChIP-seq \n", + "7798 ChIP-seq ChIP-seq \n", + "7799 ChIP-seq ChIP-seq \n", + "7800 ChIP-seq ChIP-seq \n", + "7801 ChIP-seq ChIP-seq \n", + "7802 ChIP-seq ChIP-seq \n", + "7803 RNA-seq total RNA-seq \n", + "7804 RNA-seq small RNA-seq \n", + "7805 ChIP-seq ChIP-seq \n", + "7806 ATAC-seq ATAC-seq \n", + "7807 ChIP-seq ChIP-seq \n", + "7808 ChIP-seq ChIP-seq \n", + "7809 DNA methylation profiling by array assay DNAme array \n", + "7810 DNA methylation profiling by array assay DNAme array \n", + "7811 RNA-seq microRNA-seq \n", + "7812 ATAC-seq ATAC-seq \n", + "7813 ChIP-seq ChIP-seq \n", + "7814 DNase-seq DNase-seq \n", + "7815 RNA-seq total RNA-seq \n", + "7816 RNA-seq small RNA-seq \n", + "7817 ChIP-seq ChIP-seq \n", + "7818 DNA methylation profiling by array assay DNAme array \n", + "7819 ChIP-seq ChIP-seq \n", + "7820 eCLIP eCLIP \n", + "7821 DNA methylation profiling by array assay DNAme array \n", + "7822 ChIP-seq ChIP-seq \n", + "7823 RNA-seq RAMPAGE \n", + "7824 ATAC-seq ATAC-seq \n", + "7825 ChIP-seq ChIP-seq \n", + "7826 RNA-seq microRNA-seq \n", + "7827 ChIP-seq ChIP-seq \n", + "7828 ChIP-seq ChIP-seq \n", + "7829 RNA-seq small RNA-seq \n", + "7830 RNA-seq total RNA-seq \n", + "7831 RNA-seq RAMPAGE \n", + "7832 ChIP-seq ChIP-seq \n", + "7833 eCLIP eCLIP \n", + "7834 eCLIP eCLIP \n", + "\n", + " Assay sub-class \n", + "0 microRNA-seq \n", + "1 TF ChIP-seq \n", + "2 RNA binding protein \n", + "3 Histone ChIP-seq \n", + "4 RAMPAGE \n", + "5 DNase-seq \n", + "6 RNA binding protein \n", + "7 Histone ChIP-seq \n", + "8 Repli-chip \n", + "9 Histone ChIP-seq \n", + "10 TF ChIP-seq \n", + "11 Histone ChIP-seq \n", + "12 TF ChIP-seq \n", + "13 polyA mRNA RNA-seq \n", + "14 RNA binding protein \n", + "15 transcription factor \n", + "16 transcription factor \n", + "17 Histone ChIP-seq \n", + "18 DNase-seq \n", + "19 Histone ChIP-seq \n", + "20 Histone ChIP-seq \n", + "21 DNase-seq \n", + "22 total RNA-seq \n", + "23 total RNA-seq \n", + "24 RAMPAGE \n", + "25 small RNA-seq \n", + "26 small RNA-seq \n", + "27 DNase-seq \n", + "28 TF ChIP-seq \n", + "29 polyA mRNA RNA-seq \n", + "30 polyA mRNA RNA-seq \n", + "31 Histone ChIP-seq \n", + "32 RNA microarray \n", + "33 small RNA-seq \n", + "34 Histone ChIP-seq \n", + "35 total RNA-seq \n", + "36 RAMPAGE \n", + "37 DNase-seq \n", + "38 Histone ChIP-seq \n", + "39 Histone ChIP-seq \n", + "40 Histone ChIP-seq \n", + "41 RRBS \n", + "42 polyA mRNA RNA-seq \n", + "43 Hi-C \n", + "44 Hi-C \n", + "45 Hi-C \n", + "46 TF ChIP-seq \n", + "47 RNA-PET \n", + "48 RNA binding protein \n", + "49 RNA binding protein \n", + "50 Histone ChIP-seq \n", + "51 TF ChIP-seq \n", + "52 DNase-seq \n", + "53 ATAC-seq \n", + "54 ATAC-seq \n", + "55 RNA binding protein \n", + "56 RNA binding protein \n", + "57 RNA binding protein \n", + "58 Histone ChIP-seq \n", + "59 Histone ChIP-seq \n", + "60 Histone ChIP-seq \n", + "61 Histone ChIP-seq \n", + "62 Histone ChIP-seq \n", + "63 RNA binding protein \n", + "64 TF ChIP-seq \n", + "65 TF ChIP-seq \n", + "66 Histone ChIP-seq \n", + "67 TF ChIP-seq \n", + "68 ATAC-seq \n", + "69 RNA binding protein \n", + "70 TF ChIP-seq \n", + "71 Histone ChIP-seq \n", + "72 TF ChIP-seq \n", + "73 polyA mRNA RNA-seq \n", + "74 TF ChIP-seq \n", + "75 polyA mRNA RNA-seq \n", + "76 polyA mRNA RNA-seq \n", + "77 Histone ChIP-seq \n", + "78 TF ChIP-seq \n", + "79 RNA binding protein \n", + "80 RNA-PET \n", + "81 RNA microarray \n", + "82 TF ChIP-seq \n", + "83 Histone ChIP-seq \n", + "84 TF ChIP-seq \n", + "85 TF ChIP-seq \n", + "86 Histone ChIP-seq \n", + "87 ATAC-seq \n", + "88 Histone ChIP-seq \n", + "89 ATAC-seq \n", + "90 TF ChIP-seq \n", + "91 TF ChIP-seq \n", + "92 RAMPAGE \n", + "93 genotyping array \n", + "94 genotyping array \n", + "95 Histone ChIP-seq \n", + "96 Histone ChIP-seq \n", + "97 Histone ChIP-seq \n", + "98 Histone ChIP-seq \n", + "99 total RNA-seq \n", + "... ... \n", + "7735 TF ChIP-seq \n", + "7736 TF ChIP-seq \n", + "7737 single cell RNA-seq \n", + "7738 WGBS \n", + "7739 Histone ChIP-seq \n", + "7740 Histone ChIP-seq \n", + "7741 Histone ChIP-seq \n", + "7742 small RNA-seq \n", + "7743 small RNA-seq \n", + "7744 Histone ChIP-seq \n", + "7745 microRNA counts \n", + "7746 DNAme array \n", + "7747 Histone ChIP-seq \n", + "7748 TF ChIP-seq \n", + "7749 TF ChIP-seq \n", + "7750 RAMPAGE \n", + "7751 RAMPAGE \n", + "7752 microRNA-seq \n", + "7753 Histone ChIP-seq \n", + "7754 TF ChIP-seq \n", + "7755 DNase-seq \n", + "7756 DNase-seq \n", + "7757 TF ChIP-seq \n", + "7758 TF ChIP-seq \n", + "7759 TF ChIP-seq \n", + "7760 Histone ChIP-seq \n", + "7761 Histone ChIP-seq \n", + "7762 TF ChIP-seq \n", + "7763 Histone ChIP-seq \n", + "7764 Histone ChIP-seq \n", + "7765 TF ChIP-seq \n", + "7766 microRNA counts \n", + "7767 microRNA-seq \n", + "7768 TF ChIP-seq \n", + "7769 TF ChIP-seq \n", + "7770 Histone ChIP-seq \n", + "7771 TF ChIP-seq \n", + "7772 Histone ChIP-seq \n", + "7773 Histone ChIP-seq \n", + "7774 Histone ChIP-seq \n", + "7775 polyA mRNA RNA-seq \n", + "7776 TF ChIP-seq \n", + "7777 TF ChIP-seq \n", + "7778 Histone ChIP-seq \n", + "7779 TF ChIP-seq \n", + "7780 TF ChIP-seq \n", + "7781 RAMPAGE \n", + "7782 TF ChIP-seq \n", + "7783 DNAme array \n", + "7784 microRNA counts \n", + "7785 small RNA-seq \n", + "7786 total RNA-seq \n", + "7787 TF ChIP-seq \n", + "7788 Histone ChIP-seq \n", + "7789 Histone ChIP-seq \n", + "7790 TF ChIP-seq \n", + "7791 TF ChIP-seq \n", + "7792 TF ChIP-seq \n", + "7793 microRNA counts \n", + "7794 TF ChIP-seq \n", + "7795 total RNA-seq \n", + "7796 Histone ChIP-seq \n", + "7797 TF ChIP-seq \n", + "7798 TF ChIP-seq \n", + "7799 TF ChIP-seq \n", + "7800 TF ChIP-seq \n", + "7801 TF ChIP-seq \n", + "7802 TF ChIP-seq \n", + "7803 total RNA-seq \n", + "7804 small RNA-seq \n", + "7805 TF ChIP-seq \n", + "7806 ATAC-seq \n", + "7807 Histone ChIP-seq \n", + "7808 TF ChIP-seq \n", + "7809 DNAme array \n", + "7810 DNAme array \n", + "7811 microRNA-seq \n", + "7812 ATAC-seq \n", + "7813 TF ChIP-seq \n", + "7814 DNase-seq \n", + "7815 total RNA-seq \n", + "7816 small RNA-seq \n", + "7817 TF ChIP-seq \n", + "7818 DNAme array \n", + "7819 TF ChIP-seq \n", + "7820 RNA binding protein \n", + "7821 DNAme array \n", + "7822 TF ChIP-seq \n", + "7823 RAMPAGE \n", + "7824 ATAC-seq \n", + "7825 TF ChIP-seq \n", + "7826 microRNA-seq \n", + "7827 TF ChIP-seq \n", + "7828 TF ChIP-seq \n", + "7829 small RNA-seq \n", + "7830 total RNA-seq \n", + "7831 RAMPAGE \n", + "7832 Histone ChIP-seq \n", + "7833 RNA binding protein \n", + "7834 RNA binding protein \n", + "\n", + "[7835 rows x 18 columns]" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "hier" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "data = ( \n", + " hier.groupby(['Assay category','Assay Type', 'Assay name', 'Assay sub-class'])\n", + " .count()\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Accessionaward.rfaaward.pi.titleUnnamed: 3Target labelTarget geneBiosample summaryBiosampleLabProjectSpeciesBiosample typeDate releasedMonth released
Assay categoryAssay TypeAssay nameAssay sub-class
3D chromatin structure5C5C5C1313130001313131313131313
ChIA-PETChIA-PETChIA-PET393939039393939393939393939
HiCHi-CHi-C3030300003030303030303030
DNA accessibilityATAC-seqATAC-seqATAC-seq129129129000129129129129129129129129
DNase-seqDNase-seqDNase-seq472472472000472472472472472472472472
FAIRE-seqFAIRE-seqFAIRE-seq3737370003737373737373737
MNase-seqMNase-seqMNase-seq22200022222222
genetic modification followed by DNase-seqgenetic modification DNase-seqgenetic modification DNase-seq4040400004040404040404040
DNA bindingChIP-seqChIP-seqHistone ChIP-seq15881588158801588151615881588158815881588158815881588
RNA binding protein222222022222222222222222222
TF ChIP-seq22432243224302243224322432243224322432243224322432243
DNA methylationDNA methylation profiling by array assayDNAme arrayDNAme array259259259000259259259259259259259259
MRE-seqMRE-seqMRE-seq44400044444444
MeDIP-seqMeDIP-seqMeDIP-seq44404044444444
RRBSRRBSRRBS103103103000103103103103103103103103
whole-genome shotgun bisulfite sequencingWGBSWGBS8181810008181818181818181
GenotypingDNA-PETDNA-PETDNA-PET66600066666666
comparative genomic hybridization by arraygenotyping arraygenotyping array123123123000123123123123123123123123
genotyping by high throughput sequencing assaygenotyping HTSgenotyping HTS99900099999999
Proteomicsprotein sequencing by tandem mass spectrometry assayMS-MSMS-MS1414140001414141414141414
RNA bindingRIP-chipRIP-chipRNA binding protein181818018181818181818181818
RIP-seqRIP-seqRNA binding protein373737037373737373737373737
RNA Bind-n-SeqRNA Bind-n-SeqRNA binding protein777777077770077770777777
transcription factor11101100110111
SwitchgearSwitchgearRNA binding protein22202222222222
eCLIPeCLIPRNA binding protein1701701700170170170170170170170170170170
iCLIPiCLIPRNA binding protein55505555555555
Replication timingRepli-chipRepli-chipRepli-chip6363360006363636363636363
Repli-seqRepli-seqRepli-seq104104104000104104104104104104104104
TranscriptionKnockdown RNAseqCRISPR RNA-seqRNA binding protein191919019191919191919191919
CRISPRi RNA-seqRNA binding protein88808888888888
transcription factor636363063636363636363636363
shRNA RNA-seqRNA binding protein4724724720472472472472472472472472472472
siRNA RNA-seqRNA binding protein66606666666666
transcription factor303030030293030303030303030
RNA-PETRNA-PETRNA-PET3131310003131313131313131
RNA-seqCAGECAGE7777770007777777777777777
RAMPAGERAMPAGE155155155000155155155155155155155155
microRNA-seqmicroRNA-seq114114114000114114114114114114114114
polyA depleted RNA-seqpolyA depleted RNA-seq3232320003232323232323232
polyA mRNA RNA-seqpolyA mRNA RNA-seq286286286000286286286286286286286286
single cell RNA-seqsingle cell RNA-seq9191910009191919191919191
small RNA-seqsmall RNA-seq171171171000171171171171171171171171
total RNA-seqtotal RNA-seq300300300000300300300300300300300300
microRNA countsmicroRNA countsmicroRNA counts115115115000115115115115115115115115
transcription profiling by array assayRNA microarrayRNA microarray170170170000170170170170170170170170
\n", + "
" + ], + "text/plain": [ + " Accession \\\n", + "Assay category Assay Type Assay name Assay sub-class \n", + "3D chromatin structure 5C 5C 5C 13 \n", + " ChIA-PET ChIA-PET ChIA-PET 39 \n", + " HiC Hi-C Hi-C 30 \n", + "DNA accessibility ATAC-seq ATAC-seq ATAC-seq 129 \n", + " DNase-seq DNase-seq DNase-seq 472 \n", + " FAIRE-seq FAIRE-seq FAIRE-seq 37 \n", + " MNase-seq MNase-seq MNase-seq 2 \n", + " genetic modification followed by DNase-seq genetic modification DNase-seq genetic modification DNase-seq 40 \n", + "DNA binding ChIP-seq ChIP-seq Histone ChIP-seq 1588 \n", + " RNA binding protein 22 \n", + " TF ChIP-seq 2243 \n", + "DNA methylation DNA methylation profiling by array assay DNAme array DNAme array 259 \n", + " MRE-seq MRE-seq MRE-seq 4 \n", + " MeDIP-seq MeDIP-seq MeDIP-seq 4 \n", + " RRBS RRBS RRBS 103 \n", + " whole-genome shotgun bisulfite sequencing WGBS WGBS 81 \n", + "Genotyping DNA-PET DNA-PET DNA-PET 6 \n", + " comparative genomic hybridization by array genotyping array genotyping array 123 \n", + " genotyping by high throughput sequencing assay genotyping HTS genotyping HTS 9 \n", + "Proteomics protein sequencing by tandem mass spectrometry ... MS-MS MS-MS 14 \n", + "RNA binding RIP-chip RIP-chip RNA binding protein 18 \n", + " RIP-seq RIP-seq RNA binding protein 37 \n", + " RNA Bind-n-Seq RNA Bind-n-Seq RNA binding protein 77 \n", + " transcription factor 1 \n", + " Switchgear Switchgear RNA binding protein 2 \n", + " eCLIP eCLIP RNA binding protein 170 \n", + " iCLIP iCLIP RNA binding protein 5 \n", + "Replication timing Repli-chip Repli-chip Repli-chip 63 \n", + " Repli-seq Repli-seq Repli-seq 104 \n", + "Transcription Knockdown RNAseq CRISPR RNA-seq RNA binding protein 19 \n", + " CRISPRi RNA-seq RNA binding protein 8 \n", + " transcription factor 63 \n", + " shRNA RNA-seq RNA binding protein 472 \n", + " siRNA RNA-seq RNA binding protein 6 \n", + " transcription factor 30 \n", + " RNA-PET RNA-PET RNA-PET 31 \n", + " RNA-seq CAGE CAGE 77 \n", + " RAMPAGE RAMPAGE 155 \n", + " microRNA-seq microRNA-seq 114 \n", + " polyA depleted RNA-seq polyA depleted RNA-seq 32 \n", + " polyA mRNA RNA-seq polyA mRNA RNA-seq 286 \n", + " single cell RNA-seq single cell RNA-seq 91 \n", + " small RNA-seq small RNA-seq 171 \n", + " total RNA-seq total RNA-seq 300 \n", + " microRNA counts microRNA counts microRNA counts 115 \n", + " transcription profiling by array assay RNA microarray RNA microarray 170 \n", + "\n", + " award.rfa \\\n", + "Assay category Assay Type Assay name Assay sub-class \n", + "3D chromatin structure 5C 5C 5C 13 \n", + " ChIA-PET ChIA-PET ChIA-PET 39 \n", + " HiC Hi-C Hi-C 30 \n", + "DNA accessibility ATAC-seq ATAC-seq ATAC-seq 129 \n", + " DNase-seq DNase-seq DNase-seq 472 \n", + " FAIRE-seq FAIRE-seq FAIRE-seq 37 \n", + " MNase-seq MNase-seq MNase-seq 2 \n", + " genetic modification followed by DNase-seq genetic modification DNase-seq genetic modification DNase-seq 40 \n", + "DNA binding ChIP-seq ChIP-seq Histone ChIP-seq 1588 \n", + " RNA binding protein 22 \n", + " TF ChIP-seq 2243 \n", + "DNA methylation DNA methylation profiling by array assay DNAme array DNAme array 259 \n", + " MRE-seq MRE-seq MRE-seq 4 \n", + " MeDIP-seq MeDIP-seq MeDIP-seq 4 \n", + " RRBS RRBS RRBS 103 \n", + " whole-genome shotgun bisulfite sequencing WGBS WGBS 81 \n", + "Genotyping DNA-PET DNA-PET DNA-PET 6 \n", + " comparative genomic hybridization by array genotyping array genotyping array 123 \n", + " genotyping by high throughput sequencing assay genotyping HTS genotyping HTS 9 \n", + "Proteomics protein sequencing by tandem mass spectrometry ... MS-MS MS-MS 14 \n", + "RNA binding RIP-chip RIP-chip RNA binding protein 18 \n", + " RIP-seq RIP-seq RNA binding protein 37 \n", + " RNA Bind-n-Seq RNA Bind-n-Seq RNA binding protein 77 \n", + " transcription factor 1 \n", + " Switchgear Switchgear RNA binding protein 2 \n", + " eCLIP eCLIP RNA binding protein 170 \n", + " iCLIP iCLIP RNA binding protein 5 \n", + "Replication timing Repli-chip Repli-chip Repli-chip 63 \n", + " Repli-seq Repli-seq Repli-seq 104 \n", + "Transcription Knockdown RNAseq CRISPR RNA-seq RNA binding protein 19 \n", + " CRISPRi RNA-seq RNA binding protein 8 \n", + " transcription factor 63 \n", + " shRNA RNA-seq RNA binding protein 472 \n", + " siRNA RNA-seq RNA binding protein 6 \n", + " transcription factor 30 \n", + " RNA-PET RNA-PET RNA-PET 31 \n", + " RNA-seq CAGE CAGE 77 \n", + " RAMPAGE RAMPAGE 155 \n", + " microRNA-seq microRNA-seq 114 \n", + " polyA depleted RNA-seq polyA depleted RNA-seq 32 \n", + " polyA mRNA RNA-seq polyA mRNA RNA-seq 286 \n", + " single cell RNA-seq single cell RNA-seq 91 \n", + " small RNA-seq small RNA-seq 171 \n", + " total RNA-seq total RNA-seq 300 \n", + " microRNA counts microRNA counts microRNA counts 115 \n", + " transcription profiling by array assay RNA microarray RNA microarray 170 \n", + "\n", + " award.pi.title \\\n", + "Assay category Assay Type Assay name Assay sub-class \n", + "3D chromatin structure 5C 5C 5C 13 \n", + " ChIA-PET ChIA-PET ChIA-PET 39 \n", + " HiC Hi-C Hi-C 30 \n", + "DNA accessibility ATAC-seq ATAC-seq ATAC-seq 129 \n", + " DNase-seq DNase-seq DNase-seq 472 \n", + " FAIRE-seq FAIRE-seq FAIRE-seq 37 \n", + " MNase-seq MNase-seq MNase-seq 2 \n", + " genetic modification followed by DNase-seq genetic modification DNase-seq genetic modification DNase-seq 40 \n", + "DNA binding ChIP-seq ChIP-seq Histone ChIP-seq 1588 \n", + " RNA binding protein 22 \n", + " TF ChIP-seq 2243 \n", + "DNA methylation DNA methylation profiling by array assay DNAme array DNAme array 259 \n", + " MRE-seq MRE-seq MRE-seq 4 \n", + " MeDIP-seq MeDIP-seq MeDIP-seq 4 \n", + " RRBS RRBS RRBS 103 \n", + " whole-genome shotgun bisulfite sequencing WGBS WGBS 81 \n", + "Genotyping DNA-PET DNA-PET DNA-PET 6 \n", + " comparative genomic hybridization by array genotyping array genotyping array 123 \n", + " genotyping by high throughput sequencing assay genotyping HTS genotyping HTS 9 \n", + "Proteomics protein sequencing by tandem mass spectrometry ... MS-MS MS-MS 14 \n", + "RNA binding RIP-chip RIP-chip RNA binding protein 18 \n", + " RIP-seq RIP-seq RNA binding protein 37 \n", + " RNA Bind-n-Seq RNA Bind-n-Seq RNA binding protein 77 \n", + " transcription factor 1 \n", + " Switchgear Switchgear RNA binding protein 2 \n", + " eCLIP eCLIP RNA binding protein 170 \n", + " iCLIP iCLIP RNA binding protein 5 \n", + "Replication timing Repli-chip Repli-chip Repli-chip 36 \n", + " Repli-seq Repli-seq Repli-seq 104 \n", + "Transcription Knockdown RNAseq CRISPR RNA-seq RNA binding protein 19 \n", + " CRISPRi RNA-seq RNA binding protein 8 \n", + " transcription factor 63 \n", + " shRNA RNA-seq RNA binding protein 472 \n", + " siRNA RNA-seq RNA binding protein 6 \n", + " transcription factor 30 \n", + " RNA-PET RNA-PET RNA-PET 31 \n", + " RNA-seq CAGE CAGE 77 \n", + " RAMPAGE RAMPAGE 155 \n", + " microRNA-seq microRNA-seq 114 \n", + " polyA depleted RNA-seq polyA depleted RNA-seq 32 \n", + " polyA mRNA RNA-seq polyA mRNA RNA-seq 286 \n", + " single cell RNA-seq single cell RNA-seq 91 \n", + " small RNA-seq small RNA-seq 171 \n", + " total RNA-seq total RNA-seq 300 \n", + " microRNA counts microRNA counts microRNA counts 115 \n", + " transcription profiling by array assay RNA microarray RNA microarray 170 \n", + "\n", + " Unnamed: 3 \\\n", + "Assay category Assay Type Assay name Assay sub-class \n", + "3D chromatin structure 5C 5C 5C 0 \n", + " ChIA-PET ChIA-PET ChIA-PET 0 \n", + " HiC Hi-C Hi-C 0 \n", + "DNA accessibility ATAC-seq ATAC-seq ATAC-seq 0 \n", + " DNase-seq DNase-seq DNase-seq 0 \n", + " FAIRE-seq FAIRE-seq FAIRE-seq 0 \n", + " MNase-seq MNase-seq MNase-seq 0 \n", + " genetic modification followed by DNase-seq genetic modification DNase-seq genetic modification DNase-seq 0 \n", + "DNA binding ChIP-seq ChIP-seq Histone ChIP-seq 0 \n", + " RNA binding protein 0 \n", + " TF ChIP-seq 0 \n", + "DNA methylation DNA methylation profiling by array assay DNAme array DNAme array 0 \n", + " MRE-seq MRE-seq MRE-seq 0 \n", + " MeDIP-seq MeDIP-seq MeDIP-seq 0 \n", + " RRBS RRBS RRBS 0 \n", + " whole-genome shotgun bisulfite sequencing WGBS WGBS 0 \n", + "Genotyping DNA-PET DNA-PET DNA-PET 0 \n", + " comparative genomic hybridization by array genotyping array genotyping array 0 \n", + " genotyping by high throughput sequencing assay genotyping HTS genotyping HTS 0 \n", + "Proteomics protein sequencing by tandem mass spectrometry ... MS-MS MS-MS 0 \n", + "RNA binding RIP-chip RIP-chip RNA binding protein 0 \n", + " RIP-seq RIP-seq RNA binding protein 0 \n", + " RNA Bind-n-Seq RNA Bind-n-Seq RNA binding protein 0 \n", + " transcription factor 0 \n", + " Switchgear Switchgear RNA binding protein 0 \n", + " eCLIP eCLIP RNA binding protein 0 \n", + " iCLIP iCLIP RNA binding protein 0 \n", + "Replication timing Repli-chip Repli-chip Repli-chip 0 \n", + " Repli-seq Repli-seq Repli-seq 0 \n", + "Transcription Knockdown RNAseq CRISPR RNA-seq RNA binding protein 0 \n", + " CRISPRi RNA-seq RNA binding protein 0 \n", + " transcription factor 0 \n", + " shRNA RNA-seq RNA binding protein 0 \n", + " siRNA RNA-seq RNA binding protein 0 \n", + " transcription factor 0 \n", + " RNA-PET RNA-PET RNA-PET 0 \n", + " RNA-seq CAGE CAGE 0 \n", + " RAMPAGE RAMPAGE 0 \n", + " microRNA-seq microRNA-seq 0 \n", + " polyA depleted RNA-seq polyA depleted RNA-seq 0 \n", + " polyA mRNA RNA-seq polyA mRNA RNA-seq 0 \n", + " single cell RNA-seq single cell RNA-seq 0 \n", + " small RNA-seq small RNA-seq 0 \n", + " total RNA-seq total RNA-seq 0 \n", + " microRNA counts microRNA counts microRNA counts 0 \n", + " transcription profiling by array assay RNA microarray RNA microarray 0 \n", + "\n", + " Target label \\\n", + "Assay category Assay Type Assay name Assay sub-class \n", + "3D chromatin structure 5C 5C 5C 0 \n", + " ChIA-PET ChIA-PET ChIA-PET 39 \n", + " HiC Hi-C Hi-C 0 \n", + "DNA accessibility ATAC-seq ATAC-seq ATAC-seq 0 \n", + " DNase-seq DNase-seq DNase-seq 0 \n", + " FAIRE-seq FAIRE-seq FAIRE-seq 0 \n", + " MNase-seq MNase-seq MNase-seq 0 \n", + " genetic modification followed by DNase-seq genetic modification DNase-seq genetic modification DNase-seq 0 \n", + "DNA binding ChIP-seq ChIP-seq Histone ChIP-seq 1588 \n", + " RNA binding protein 22 \n", + " TF ChIP-seq 2243 \n", + "DNA methylation DNA methylation profiling by array assay DNAme array DNAme array 0 \n", + " MRE-seq MRE-seq MRE-seq 0 \n", + " MeDIP-seq MeDIP-seq MeDIP-seq 4 \n", + " RRBS RRBS RRBS 0 \n", + " whole-genome shotgun bisulfite sequencing WGBS WGBS 0 \n", + "Genotyping DNA-PET DNA-PET DNA-PET 0 \n", + " comparative genomic hybridization by array genotyping array genotyping array 0 \n", + " genotyping by high throughput sequencing assay genotyping HTS genotyping HTS 0 \n", + "Proteomics protein sequencing by tandem mass spectrometry ... MS-MS MS-MS 0 \n", + "RNA binding RIP-chip RIP-chip RNA binding protein 18 \n", + " RIP-seq RIP-seq RNA binding protein 37 \n", + " RNA Bind-n-Seq RNA Bind-n-Seq RNA binding protein 77 \n", + " transcription factor 1 \n", + " Switchgear Switchgear RNA binding protein 2 \n", + " eCLIP eCLIP RNA binding protein 170 \n", + " iCLIP iCLIP RNA binding protein 5 \n", + "Replication timing Repli-chip Repli-chip Repli-chip 0 \n", + " Repli-seq Repli-seq Repli-seq 0 \n", + "Transcription Knockdown RNAseq CRISPR RNA-seq RNA binding protein 19 \n", + " CRISPRi RNA-seq RNA binding protein 8 \n", + " transcription factor 63 \n", + " shRNA RNA-seq RNA binding protein 472 \n", + " siRNA RNA-seq RNA binding protein 6 \n", + " transcription factor 30 \n", + " RNA-PET RNA-PET RNA-PET 0 \n", + " RNA-seq CAGE CAGE 0 \n", + " RAMPAGE RAMPAGE 0 \n", + " microRNA-seq microRNA-seq 0 \n", + " polyA depleted RNA-seq polyA depleted RNA-seq 0 \n", + " polyA mRNA RNA-seq polyA mRNA RNA-seq 0 \n", + " single cell RNA-seq single cell RNA-seq 0 \n", + " small RNA-seq small RNA-seq 0 \n", + " total RNA-seq total RNA-seq 0 \n", + " microRNA counts microRNA counts microRNA counts 0 \n", + " transcription profiling by array assay RNA microarray RNA microarray 0 \n", + "\n", + " Target gene \\\n", + "Assay category Assay Type Assay name Assay sub-class \n", + "3D chromatin structure 5C 5C 5C 0 \n", + " ChIA-PET ChIA-PET ChIA-PET 39 \n", + " HiC Hi-C Hi-C 0 \n", + "DNA accessibility ATAC-seq ATAC-seq ATAC-seq 0 \n", + " DNase-seq DNase-seq DNase-seq 0 \n", + " FAIRE-seq FAIRE-seq FAIRE-seq 0 \n", + " MNase-seq MNase-seq MNase-seq 0 \n", + " genetic modification followed by DNase-seq genetic modification DNase-seq genetic modification DNase-seq 0 \n", + "DNA binding ChIP-seq ChIP-seq Histone ChIP-seq 1516 \n", + " RNA binding protein 22 \n", + " TF ChIP-seq 2243 \n", + "DNA methylation DNA methylation profiling by array assay DNAme array DNAme array 0 \n", + " MRE-seq MRE-seq MRE-seq 0 \n", + " MeDIP-seq MeDIP-seq MeDIP-seq 0 \n", + " RRBS RRBS RRBS 0 \n", + " whole-genome shotgun bisulfite sequencing WGBS WGBS 0 \n", + "Genotyping DNA-PET DNA-PET DNA-PET 0 \n", + " comparative genomic hybridization by array genotyping array genotyping array 0 \n", + " genotyping by high throughput sequencing assay genotyping HTS genotyping HTS 0 \n", + "Proteomics protein sequencing by tandem mass spectrometry ... MS-MS MS-MS 0 \n", + "RNA binding RIP-chip RIP-chip RNA binding protein 18 \n", + " RIP-seq RIP-seq RNA binding protein 37 \n", + " RNA Bind-n-Seq RNA Bind-n-Seq RNA binding protein 77 \n", + " transcription factor 1 \n", + " Switchgear Switchgear RNA binding protein 2 \n", + " eCLIP eCLIP RNA binding protein 170 \n", + " iCLIP iCLIP RNA binding protein 5 \n", + "Replication timing Repli-chip Repli-chip Repli-chip 0 \n", + " Repli-seq Repli-seq Repli-seq 0 \n", + "Transcription Knockdown RNAseq CRISPR RNA-seq RNA binding protein 19 \n", + " CRISPRi RNA-seq RNA binding protein 8 \n", + " transcription factor 63 \n", + " shRNA RNA-seq RNA binding protein 472 \n", + " siRNA RNA-seq RNA binding protein 6 \n", + " transcription factor 29 \n", + " RNA-PET RNA-PET RNA-PET 0 \n", + " RNA-seq CAGE CAGE 0 \n", + " RAMPAGE RAMPAGE 0 \n", + " microRNA-seq microRNA-seq 0 \n", + " polyA depleted RNA-seq polyA depleted RNA-seq 0 \n", + " polyA mRNA RNA-seq polyA mRNA RNA-seq 0 \n", + " single cell RNA-seq single cell RNA-seq 0 \n", + " small RNA-seq small RNA-seq 0 \n", + " total RNA-seq total RNA-seq 0 \n", + " microRNA counts microRNA counts microRNA counts 0 \n", + " transcription profiling by array assay RNA microarray RNA microarray 0 \n", + "\n", + " Biosample summary \\\n", + "Assay category Assay Type Assay name Assay sub-class \n", + "3D chromatin structure 5C 5C 5C 13 \n", + " ChIA-PET ChIA-PET ChIA-PET 39 \n", + " HiC Hi-C Hi-C 30 \n", + "DNA accessibility ATAC-seq ATAC-seq ATAC-seq 129 \n", + " DNase-seq DNase-seq DNase-seq 472 \n", + " FAIRE-seq FAIRE-seq FAIRE-seq 37 \n", + " MNase-seq MNase-seq MNase-seq 2 \n", + " genetic modification followed by DNase-seq genetic modification DNase-seq genetic modification DNase-seq 40 \n", + "DNA binding ChIP-seq ChIP-seq Histone ChIP-seq 1588 \n", + " RNA binding protein 22 \n", + " TF ChIP-seq 2243 \n", + "DNA methylation DNA methylation profiling by array assay DNAme array DNAme array 259 \n", + " MRE-seq MRE-seq MRE-seq 4 \n", + " MeDIP-seq MeDIP-seq MeDIP-seq 4 \n", + " RRBS RRBS RRBS 103 \n", + " whole-genome shotgun bisulfite sequencing WGBS WGBS 81 \n", + "Genotyping DNA-PET DNA-PET DNA-PET 6 \n", + " comparative genomic hybridization by array genotyping array genotyping array 123 \n", + " genotyping by high throughput sequencing assay genotyping HTS genotyping HTS 9 \n", + "Proteomics protein sequencing by tandem mass spectrometry ... MS-MS MS-MS 14 \n", + "RNA binding RIP-chip RIP-chip RNA binding protein 18 \n", + " RIP-seq RIP-seq RNA binding protein 37 \n", + " RNA Bind-n-Seq RNA Bind-n-Seq RNA binding protein 0 \n", + " transcription factor 0 \n", + " Switchgear Switchgear RNA binding protein 2 \n", + " eCLIP eCLIP RNA binding protein 170 \n", + " iCLIP iCLIP RNA binding protein 5 \n", + "Replication timing Repli-chip Repli-chip Repli-chip 63 \n", + " Repli-seq Repli-seq Repli-seq 104 \n", + "Transcription Knockdown RNAseq CRISPR RNA-seq RNA binding protein 19 \n", + " CRISPRi RNA-seq RNA binding protein 8 \n", + " transcription factor 63 \n", + " shRNA RNA-seq RNA binding protein 472 \n", + " siRNA RNA-seq RNA binding protein 6 \n", + " transcription factor 30 \n", + " RNA-PET RNA-PET RNA-PET 31 \n", + " RNA-seq CAGE CAGE 77 \n", + " RAMPAGE RAMPAGE 155 \n", + " microRNA-seq microRNA-seq 114 \n", + " polyA depleted RNA-seq polyA depleted RNA-seq 32 \n", + " polyA mRNA RNA-seq polyA mRNA RNA-seq 286 \n", + " single cell RNA-seq single cell RNA-seq 91 \n", + " small RNA-seq small RNA-seq 171 \n", + " total RNA-seq total RNA-seq 300 \n", + " microRNA counts microRNA counts microRNA counts 115 \n", + " transcription profiling by array assay RNA microarray RNA microarray 170 \n", + "\n", + " Biosample \\\n", + "Assay category Assay Type Assay name Assay sub-class \n", + "3D chromatin structure 5C 5C 5C 13 \n", + " ChIA-PET ChIA-PET ChIA-PET 39 \n", + " HiC Hi-C Hi-C 30 \n", + "DNA accessibility ATAC-seq ATAC-seq ATAC-seq 129 \n", + " DNase-seq DNase-seq DNase-seq 472 \n", + " FAIRE-seq FAIRE-seq FAIRE-seq 37 \n", + " MNase-seq MNase-seq MNase-seq 2 \n", + " genetic modification followed by DNase-seq genetic modification DNase-seq genetic modification DNase-seq 40 \n", + "DNA binding ChIP-seq ChIP-seq Histone ChIP-seq 1588 \n", + " RNA binding protein 22 \n", + " TF ChIP-seq 2243 \n", + "DNA methylation DNA methylation profiling by array assay DNAme array DNAme array 259 \n", + " MRE-seq MRE-seq MRE-seq 4 \n", + " MeDIP-seq MeDIP-seq MeDIP-seq 4 \n", + " RRBS RRBS RRBS 103 \n", + " whole-genome shotgun bisulfite sequencing WGBS WGBS 81 \n", + "Genotyping DNA-PET DNA-PET DNA-PET 6 \n", + " comparative genomic hybridization by array genotyping array genotyping array 123 \n", + " genotyping by high throughput sequencing assay genotyping HTS genotyping HTS 9 \n", + "Proteomics protein sequencing by tandem mass spectrometry ... MS-MS MS-MS 14 \n", + "RNA binding RIP-chip RIP-chip RNA binding protein 18 \n", + " RIP-seq RIP-seq RNA binding protein 37 \n", + " RNA Bind-n-Seq RNA Bind-n-Seq RNA binding protein 0 \n", + " transcription factor 0 \n", + " Switchgear Switchgear RNA binding protein 2 \n", + " eCLIP eCLIP RNA binding protein 170 \n", + " iCLIP iCLIP RNA binding protein 5 \n", + "Replication timing Repli-chip Repli-chip Repli-chip 63 \n", + " Repli-seq Repli-seq Repli-seq 104 \n", + "Transcription Knockdown RNAseq CRISPR RNA-seq RNA binding protein 19 \n", + " CRISPRi RNA-seq RNA binding protein 8 \n", + " transcription factor 63 \n", + " shRNA RNA-seq RNA binding protein 472 \n", + " siRNA RNA-seq RNA binding protein 6 \n", + " transcription factor 30 \n", + " RNA-PET RNA-PET RNA-PET 31 \n", + " RNA-seq CAGE CAGE 77 \n", + " RAMPAGE RAMPAGE 155 \n", + " microRNA-seq microRNA-seq 114 \n", + " polyA depleted RNA-seq polyA depleted RNA-seq 32 \n", + " polyA mRNA RNA-seq polyA mRNA RNA-seq 286 \n", + " single cell RNA-seq single cell RNA-seq 91 \n", + " small RNA-seq small RNA-seq 171 \n", + " total RNA-seq total RNA-seq 300 \n", + " microRNA counts microRNA counts microRNA counts 115 \n", + " transcription profiling by array assay RNA microarray RNA microarray 170 \n", + "\n", + " Lab \\\n", + "Assay category Assay Type Assay name Assay sub-class \n", + "3D chromatin structure 5C 5C 5C 13 \n", + " ChIA-PET ChIA-PET ChIA-PET 39 \n", + " HiC Hi-C Hi-C 30 \n", + "DNA accessibility ATAC-seq ATAC-seq ATAC-seq 129 \n", + " DNase-seq DNase-seq DNase-seq 472 \n", + " FAIRE-seq FAIRE-seq FAIRE-seq 37 \n", + " MNase-seq MNase-seq MNase-seq 2 \n", + " genetic modification followed by DNase-seq genetic modification DNase-seq genetic modification DNase-seq 40 \n", + "DNA binding ChIP-seq ChIP-seq Histone ChIP-seq 1588 \n", + " RNA binding protein 22 \n", + " TF ChIP-seq 2243 \n", + "DNA methylation DNA methylation profiling by array assay DNAme array DNAme array 259 \n", + " MRE-seq MRE-seq MRE-seq 4 \n", + " MeDIP-seq MeDIP-seq MeDIP-seq 4 \n", + " RRBS RRBS RRBS 103 \n", + " whole-genome shotgun bisulfite sequencing WGBS WGBS 81 \n", + "Genotyping DNA-PET DNA-PET DNA-PET 6 \n", + " comparative genomic hybridization by array genotyping array genotyping array 123 \n", + " genotyping by high throughput sequencing assay genotyping HTS genotyping HTS 9 \n", + "Proteomics protein sequencing by tandem mass spectrometry ... MS-MS MS-MS 14 \n", + "RNA binding RIP-chip RIP-chip RNA binding protein 18 \n", + " RIP-seq RIP-seq RNA binding protein 37 \n", + " RNA Bind-n-Seq RNA Bind-n-Seq RNA binding protein 77 \n", + " transcription factor 1 \n", + " Switchgear Switchgear RNA binding protein 2 \n", + " eCLIP eCLIP RNA binding protein 170 \n", + " iCLIP iCLIP RNA binding protein 5 \n", + "Replication timing Repli-chip Repli-chip Repli-chip 63 \n", + " Repli-seq Repli-seq Repli-seq 104 \n", + "Transcription Knockdown RNAseq CRISPR RNA-seq RNA binding protein 19 \n", + " CRISPRi RNA-seq RNA binding protein 8 \n", + " transcription factor 63 \n", + " shRNA RNA-seq RNA binding protein 472 \n", + " siRNA RNA-seq RNA binding protein 6 \n", + " transcription factor 30 \n", + " RNA-PET RNA-PET RNA-PET 31 \n", + " RNA-seq CAGE CAGE 77 \n", + " RAMPAGE RAMPAGE 155 \n", + " microRNA-seq microRNA-seq 114 \n", + " polyA depleted RNA-seq polyA depleted RNA-seq 32 \n", + " polyA mRNA RNA-seq polyA mRNA RNA-seq 286 \n", + " single cell RNA-seq single cell RNA-seq 91 \n", + " small RNA-seq small RNA-seq 171 \n", + " total RNA-seq total RNA-seq 300 \n", + " microRNA counts microRNA counts microRNA counts 115 \n", + " transcription profiling by array assay RNA microarray RNA microarray 170 \n", + "\n", + " Project \\\n", + "Assay category Assay Type Assay name Assay sub-class \n", + "3D chromatin structure 5C 5C 5C 13 \n", + " ChIA-PET ChIA-PET ChIA-PET 39 \n", + " HiC Hi-C Hi-C 30 \n", + "DNA accessibility ATAC-seq ATAC-seq ATAC-seq 129 \n", + " DNase-seq DNase-seq DNase-seq 472 \n", + " FAIRE-seq FAIRE-seq FAIRE-seq 37 \n", + " MNase-seq MNase-seq MNase-seq 2 \n", + " genetic modification followed by DNase-seq genetic modification DNase-seq genetic modification DNase-seq 40 \n", + "DNA binding ChIP-seq ChIP-seq Histone ChIP-seq 1588 \n", + " RNA binding protein 22 \n", + " TF ChIP-seq 2243 \n", + "DNA methylation DNA methylation profiling by array assay DNAme array DNAme array 259 \n", + " MRE-seq MRE-seq MRE-seq 4 \n", + " MeDIP-seq MeDIP-seq MeDIP-seq 4 \n", + " RRBS RRBS RRBS 103 \n", + " whole-genome shotgun bisulfite sequencing WGBS WGBS 81 \n", + "Genotyping DNA-PET DNA-PET DNA-PET 6 \n", + " comparative genomic hybridization by array genotyping array genotyping array 123 \n", + " genotyping by high throughput sequencing assay genotyping HTS genotyping HTS 9 \n", + "Proteomics protein sequencing by tandem mass spectrometry ... MS-MS MS-MS 14 \n", + "RNA binding RIP-chip RIP-chip RNA binding protein 18 \n", + " RIP-seq RIP-seq RNA binding protein 37 \n", + " RNA Bind-n-Seq RNA Bind-n-Seq RNA binding protein 77 \n", + " transcription factor 1 \n", + " Switchgear Switchgear RNA binding protein 2 \n", + " eCLIP eCLIP RNA binding protein 170 \n", + " iCLIP iCLIP RNA binding protein 5 \n", + "Replication timing Repli-chip Repli-chip Repli-chip 63 \n", + " Repli-seq Repli-seq Repli-seq 104 \n", + "Transcription Knockdown RNAseq CRISPR RNA-seq RNA binding protein 19 \n", + " CRISPRi RNA-seq RNA binding protein 8 \n", + " transcription factor 63 \n", + " shRNA RNA-seq RNA binding protein 472 \n", + " siRNA RNA-seq RNA binding protein 6 \n", + " transcription factor 30 \n", + " RNA-PET RNA-PET RNA-PET 31 \n", + " RNA-seq CAGE CAGE 77 \n", + " RAMPAGE RAMPAGE 155 \n", + " microRNA-seq microRNA-seq 114 \n", + " polyA depleted RNA-seq polyA depleted RNA-seq 32 \n", + " polyA mRNA RNA-seq polyA mRNA RNA-seq 286 \n", + " single cell RNA-seq single cell RNA-seq 91 \n", + " small RNA-seq small RNA-seq 171 \n", + " total RNA-seq total RNA-seq 300 \n", + " microRNA counts microRNA counts microRNA counts 115 \n", + " transcription profiling by array assay RNA microarray RNA microarray 170 \n", + "\n", + " Species \\\n", + "Assay category Assay Type Assay name Assay sub-class \n", + "3D chromatin structure 5C 5C 5C 13 \n", + " ChIA-PET ChIA-PET ChIA-PET 39 \n", + " HiC Hi-C Hi-C 30 \n", + "DNA accessibility ATAC-seq ATAC-seq ATAC-seq 129 \n", + " DNase-seq DNase-seq DNase-seq 472 \n", + " FAIRE-seq FAIRE-seq FAIRE-seq 37 \n", + " MNase-seq MNase-seq MNase-seq 2 \n", + " genetic modification followed by DNase-seq genetic modification DNase-seq genetic modification DNase-seq 40 \n", + "DNA binding ChIP-seq ChIP-seq Histone ChIP-seq 1588 \n", + " RNA binding protein 22 \n", + " TF ChIP-seq 2243 \n", + "DNA methylation DNA methylation profiling by array assay DNAme array DNAme array 259 \n", + " MRE-seq MRE-seq MRE-seq 4 \n", + " MeDIP-seq MeDIP-seq MeDIP-seq 4 \n", + " RRBS RRBS RRBS 103 \n", + " whole-genome shotgun bisulfite sequencing WGBS WGBS 81 \n", + "Genotyping DNA-PET DNA-PET DNA-PET 6 \n", + " comparative genomic hybridization by array genotyping array genotyping array 123 \n", + " genotyping by high throughput sequencing assay genotyping HTS genotyping HTS 9 \n", + "Proteomics protein sequencing by tandem mass spectrometry ... MS-MS MS-MS 14 \n", + "RNA binding RIP-chip RIP-chip RNA binding protein 18 \n", + " RIP-seq RIP-seq RNA binding protein 37 \n", + " RNA Bind-n-Seq RNA Bind-n-Seq RNA binding protein 0 \n", + " transcription factor 0 \n", + " Switchgear Switchgear RNA binding protein 2 \n", + " eCLIP eCLIP RNA binding protein 170 \n", + " iCLIP iCLIP RNA binding protein 5 \n", + "Replication timing Repli-chip Repli-chip Repli-chip 63 \n", + " Repli-seq Repli-seq Repli-seq 104 \n", + "Transcription Knockdown RNAseq CRISPR RNA-seq RNA binding protein 19 \n", + " CRISPRi RNA-seq RNA binding protein 8 \n", + " transcription factor 63 \n", + " shRNA RNA-seq RNA binding protein 472 \n", + " siRNA RNA-seq RNA binding protein 6 \n", + " transcription factor 30 \n", + " RNA-PET RNA-PET RNA-PET 31 \n", + " RNA-seq CAGE CAGE 77 \n", + " RAMPAGE RAMPAGE 155 \n", + " microRNA-seq microRNA-seq 114 \n", + " polyA depleted RNA-seq polyA depleted RNA-seq 32 \n", + " polyA mRNA RNA-seq polyA mRNA RNA-seq 286 \n", + " single cell RNA-seq single cell RNA-seq 91 \n", + " small RNA-seq small RNA-seq 171 \n", + " total RNA-seq total RNA-seq 300 \n", + " microRNA counts microRNA counts microRNA counts 115 \n", + " transcription profiling by array assay RNA microarray RNA microarray 170 \n", + "\n", + " Biosample type \\\n", + "Assay category Assay Type Assay name Assay sub-class \n", + "3D chromatin structure 5C 5C 5C 13 \n", + " ChIA-PET ChIA-PET ChIA-PET 39 \n", + " HiC Hi-C Hi-C 30 \n", + "DNA accessibility ATAC-seq ATAC-seq ATAC-seq 129 \n", + " DNase-seq DNase-seq DNase-seq 472 \n", + " FAIRE-seq FAIRE-seq FAIRE-seq 37 \n", + " MNase-seq MNase-seq MNase-seq 2 \n", + " genetic modification followed by DNase-seq genetic modification DNase-seq genetic modification DNase-seq 40 \n", + "DNA binding ChIP-seq ChIP-seq Histone ChIP-seq 1588 \n", + " RNA binding protein 22 \n", + " TF ChIP-seq 2243 \n", + "DNA methylation DNA methylation profiling by array assay DNAme array DNAme array 259 \n", + " MRE-seq MRE-seq MRE-seq 4 \n", + " MeDIP-seq MeDIP-seq MeDIP-seq 4 \n", + " RRBS RRBS RRBS 103 \n", + " whole-genome shotgun bisulfite sequencing WGBS WGBS 81 \n", + "Genotyping DNA-PET DNA-PET DNA-PET 6 \n", + " comparative genomic hybridization by array genotyping array genotyping array 123 \n", + " genotyping by high throughput sequencing assay genotyping HTS genotyping HTS 9 \n", + "Proteomics protein sequencing by tandem mass spectrometry ... MS-MS MS-MS 14 \n", + "RNA binding RIP-chip RIP-chip RNA binding protein 18 \n", + " RIP-seq RIP-seq RNA binding protein 37 \n", + " RNA Bind-n-Seq RNA Bind-n-Seq RNA binding protein 77 \n", + " transcription factor 1 \n", + " Switchgear Switchgear RNA binding protein 2 \n", + " eCLIP eCLIP RNA binding protein 170 \n", + " iCLIP iCLIP RNA binding protein 5 \n", + "Replication timing Repli-chip Repli-chip Repli-chip 63 \n", + " Repli-seq Repli-seq Repli-seq 104 \n", + "Transcription Knockdown RNAseq CRISPR RNA-seq RNA binding protein 19 \n", + " CRISPRi RNA-seq RNA binding protein 8 \n", + " transcription factor 63 \n", + " shRNA RNA-seq RNA binding protein 472 \n", + " siRNA RNA-seq RNA binding protein 6 \n", + " transcription factor 30 \n", + " RNA-PET RNA-PET RNA-PET 31 \n", + " RNA-seq CAGE CAGE 77 \n", + " RAMPAGE RAMPAGE 155 \n", + " microRNA-seq microRNA-seq 114 \n", + " polyA depleted RNA-seq polyA depleted RNA-seq 32 \n", + " polyA mRNA RNA-seq polyA mRNA RNA-seq 286 \n", + " single cell RNA-seq single cell RNA-seq 91 \n", + " small RNA-seq small RNA-seq 171 \n", + " total RNA-seq total RNA-seq 300 \n", + " microRNA counts microRNA counts microRNA counts 115 \n", + " transcription profiling by array assay RNA microarray RNA microarray 170 \n", + "\n", + " Date released \\\n", + "Assay category Assay Type Assay name Assay sub-class \n", + "3D chromatin structure 5C 5C 5C 13 \n", + " ChIA-PET ChIA-PET ChIA-PET 39 \n", + " HiC Hi-C Hi-C 30 \n", + "DNA accessibility ATAC-seq ATAC-seq ATAC-seq 129 \n", + " DNase-seq DNase-seq DNase-seq 472 \n", + " FAIRE-seq FAIRE-seq FAIRE-seq 37 \n", + " MNase-seq MNase-seq MNase-seq 2 \n", + " genetic modification followed by DNase-seq genetic modification DNase-seq genetic modification DNase-seq 40 \n", + "DNA binding ChIP-seq ChIP-seq Histone ChIP-seq 1588 \n", + " RNA binding protein 22 \n", + " TF ChIP-seq 2243 \n", + "DNA methylation DNA methylation profiling by array assay DNAme array DNAme array 259 \n", + " MRE-seq MRE-seq MRE-seq 4 \n", + " MeDIP-seq MeDIP-seq MeDIP-seq 4 \n", + " RRBS RRBS RRBS 103 \n", + " whole-genome shotgun bisulfite sequencing WGBS WGBS 81 \n", + "Genotyping DNA-PET DNA-PET DNA-PET 6 \n", + " comparative genomic hybridization by array genotyping array genotyping array 123 \n", + " genotyping by high throughput sequencing assay genotyping HTS genotyping HTS 9 \n", + "Proteomics protein sequencing by tandem mass spectrometry ... MS-MS MS-MS 14 \n", + "RNA binding RIP-chip RIP-chip RNA binding protein 18 \n", + " RIP-seq RIP-seq RNA binding protein 37 \n", + " RNA Bind-n-Seq RNA Bind-n-Seq RNA binding protein 77 \n", + " transcription factor 1 \n", + " Switchgear Switchgear RNA binding protein 2 \n", + " eCLIP eCLIP RNA binding protein 170 \n", + " iCLIP iCLIP RNA binding protein 5 \n", + "Replication timing Repli-chip Repli-chip Repli-chip 63 \n", + " Repli-seq Repli-seq Repli-seq 104 \n", + "Transcription Knockdown RNAseq CRISPR RNA-seq RNA binding protein 19 \n", + " CRISPRi RNA-seq RNA binding protein 8 \n", + " transcription factor 63 \n", + " shRNA RNA-seq RNA binding protein 472 \n", + " siRNA RNA-seq RNA binding protein 6 \n", + " transcription factor 30 \n", + " RNA-PET RNA-PET RNA-PET 31 \n", + " RNA-seq CAGE CAGE 77 \n", + " RAMPAGE RAMPAGE 155 \n", + " microRNA-seq microRNA-seq 114 \n", + " polyA depleted RNA-seq polyA depleted RNA-seq 32 \n", + " polyA mRNA RNA-seq polyA mRNA RNA-seq 286 \n", + " single cell RNA-seq single cell RNA-seq 91 \n", + " small RNA-seq small RNA-seq 171 \n", + " total RNA-seq total RNA-seq 300 \n", + " microRNA counts microRNA counts microRNA counts 115 \n", + " transcription profiling by array assay RNA microarray RNA microarray 170 \n", + "\n", + " Month released \n", + "Assay category Assay Type Assay name Assay sub-class \n", + "3D chromatin structure 5C 5C 5C 13 \n", + " ChIA-PET ChIA-PET ChIA-PET 39 \n", + " HiC Hi-C Hi-C 30 \n", + "DNA accessibility ATAC-seq ATAC-seq ATAC-seq 129 \n", + " DNase-seq DNase-seq DNase-seq 472 \n", + " FAIRE-seq FAIRE-seq FAIRE-seq 37 \n", + " MNase-seq MNase-seq MNase-seq 2 \n", + " genetic modification followed by DNase-seq genetic modification DNase-seq genetic modification DNase-seq 40 \n", + "DNA binding ChIP-seq ChIP-seq Histone ChIP-seq 1588 \n", + " RNA binding protein 22 \n", + " TF ChIP-seq 2243 \n", + "DNA methylation DNA methylation profiling by array assay DNAme array DNAme array 259 \n", + " MRE-seq MRE-seq MRE-seq 4 \n", + " MeDIP-seq MeDIP-seq MeDIP-seq 4 \n", + " RRBS RRBS RRBS 103 \n", + " whole-genome shotgun bisulfite sequencing WGBS WGBS 81 \n", + "Genotyping DNA-PET DNA-PET DNA-PET 6 \n", + " comparative genomic hybridization by array genotyping array genotyping array 123 \n", + " genotyping by high throughput sequencing assay genotyping HTS genotyping HTS 9 \n", + "Proteomics protein sequencing by tandem mass spectrometry ... MS-MS MS-MS 14 \n", + "RNA binding RIP-chip RIP-chip RNA binding protein 18 \n", + " RIP-seq RIP-seq RNA binding protein 37 \n", + " RNA Bind-n-Seq RNA Bind-n-Seq RNA binding protein 77 \n", + " transcription factor 1 \n", + " Switchgear Switchgear RNA binding protein 2 \n", + " eCLIP eCLIP RNA binding protein 170 \n", + " iCLIP iCLIP RNA binding protein 5 \n", + "Replication timing Repli-chip Repli-chip Repli-chip 63 \n", + " Repli-seq Repli-seq Repli-seq 104 \n", + "Transcription Knockdown RNAseq CRISPR RNA-seq RNA binding protein 19 \n", + " CRISPRi RNA-seq RNA binding protein 8 \n", + " transcription factor 63 \n", + " shRNA RNA-seq RNA binding protein 472 \n", + " siRNA RNA-seq RNA binding protein 6 \n", + " transcription factor 30 \n", + " RNA-PET RNA-PET RNA-PET 31 \n", + " RNA-seq CAGE CAGE 77 \n", + " RAMPAGE RAMPAGE 155 \n", + " microRNA-seq microRNA-seq 114 \n", + " polyA depleted RNA-seq polyA depleted RNA-seq 32 \n", + " polyA mRNA RNA-seq polyA mRNA RNA-seq 286 \n", + " single cell RNA-seq single cell RNA-seq 91 \n", + " small RNA-seq small RNA-seq 171 \n", + " total RNA-seq total RNA-seq 300 \n", + " microRNA counts microRNA counts microRNA counts 115 \n", + " transcription profiling by array assay RNA microarray RNA microarray 170 " + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "dd = data['Accession']" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Assay category Assay Type Assay name Assay sub-class \n", + "3D chromatin structure 5C 5C 5C 13\n", + " ChIA-PET ChIA-PET ChIA-PET 39\n", + " HiC Hi-C Hi-C 30\n", + "DNA accessibility ATAC-seq ATAC-seq ATAC-seq 129\n", + " DNase-seq DNase-seq DNase-seq 472\n", + " FAIRE-seq FAIRE-seq FAIRE-seq 37\n", + " MNase-seq MNase-seq MNase-seq 2\n", + " genetic modification followed by DNase-seq genetic modification DNase-seq genetic modification DNase-seq 40\n", + "DNA binding ChIP-seq ChIP-seq Histone ChIP-seq 1588\n", + " RNA binding protein 22\n", + " TF ChIP-seq 2243\n", + "DNA methylation DNA methylation profiling by array assay DNAme array DNAme array 259\n", + " MRE-seq MRE-seq MRE-seq 4\n", + " MeDIP-seq MeDIP-seq MeDIP-seq 4\n", + " RRBS RRBS RRBS 103\n", + " whole-genome shotgun bisulfite sequencing WGBS WGBS 81\n", + "Genotyping DNA-PET DNA-PET DNA-PET 6\n", + " comparative genomic hybridization by array genotyping array genotyping array 123\n", + " genotyping by high throughput sequencing assay genotyping HTS genotyping HTS 9\n", + "Proteomics protein sequencing by tandem mass spectrometry assay MS-MS MS-MS 14\n", + "RNA binding RIP-chip RIP-chip RNA binding protein 18\n", + " RIP-seq RIP-seq RNA binding protein 37\n", + " RNA Bind-n-Seq RNA Bind-n-Seq RNA binding protein 77\n", + " transcription factor 1\n", + " Switchgear Switchgear RNA binding protein 2\n", + " eCLIP eCLIP RNA binding protein 170\n", + " iCLIP iCLIP RNA binding protein 5\n", + "Replication timing Repli-chip Repli-chip Repli-chip 63\n", + " Repli-seq Repli-seq Repli-seq 104\n", + "Transcription Knockdown RNAseq CRISPR RNA-seq RNA binding protein 19\n", + " CRISPRi RNA-seq RNA binding protein 8\n", + " transcription factor 63\n", + " shRNA RNA-seq RNA binding protein 472\n", + " siRNA RNA-seq RNA binding protein 6\n", + " transcription factor 30\n", + " RNA-PET RNA-PET RNA-PET 31\n", + " RNA-seq CAGE CAGE 77\n", + " RAMPAGE RAMPAGE 155\n", + " microRNA-seq microRNA-seq 114\n", + " polyA depleted RNA-seq polyA depleted RNA-seq 32\n", + " polyA mRNA RNA-seq polyA mRNA RNA-seq 286\n", + " single cell RNA-seq single cell RNA-seq 91\n", + " small RNA-seq small RNA-seq 171\n", + " total RNA-seq total RNA-seq 300\n", + " microRNA counts microRNA counts microRNA counts 115\n", + " transcription profiling by array assay RNA microarray RNA microarray 170\n", + "Name: Accession, dtype: int64" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dd" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "anaconda-cloud": {}, + "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": "3.5.1" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/jupyter_notebooks/kath/.ipynb_checkpoints/v64-duplicate vs. v65rc2-checkpoint.ipynb b/jupyter_notebooks/kath/.ipynb_checkpoints/v64-duplicate vs. v65rc2-checkpoint.ipynb new file mode 100644 index 00000000..c269cc8a --- /dev/null +++ b/jupyter_notebooks/kath/.ipynb_checkpoints/v64-duplicate vs. v65rc2-checkpoint.ipynb @@ -0,0 +1,463 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "import sys\n", + "sys.path.append('../..')\n", + "import qancode" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "#comparing to v65rc2 site\n", + "qa = qancode.QANCODE(rc_url=\"https://series5-test-master.demo.encodedcc.org/\", prod_url=\"https://v67rc1-master.demo.encodedcc.org/\")" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Checking response time\n", + "\n", + "*** item_type: /\n", + "------------------ https://v67rc1-master.demo.encodedcc.org// ------------------\n", + "\u001b[31mAverage es_time: 43.641 ± 5.736 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 1.228 ± 0.46 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 8.924 ± 2.705 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 63.508 ± 8.085 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 117.3 ± 14.63 ms (n=100)\u001b[0m\n", + "--------------- https://series5-test-master.demo.encodedcc.org// ---------------\n", + "\u001b[31mAverage es_time: 20.198 ± 2.972 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.458 ± 0.026 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 4.348 ± 1.255 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 28.376 ± 3.311 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 53.381 ± 6.612 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /search/?type=Experiment\n", + "------ https://v67rc1-master.demo.encodedcc.org//search/?type=Experiment -------\n", + "\u001b[31mAverage es_time: 30.541 ± 9.739 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 1.459 ± 0.73 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage render_time: 153.862 ± 16.943 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 214.367 ± 36.73 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 400.229 ± 51.638 ms (n=100)\u001b[0m\n", + "--------- https://series5-test-master.demo.encodedcc.org//search/?type=Experiment ---------\n", + "\u001b[31mAverage es_time: 19.734 ± 5.574 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.478 ± 0.014 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 117.199 ± 13.892 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 162.229 ± 91.072 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 299.64 ± 94.824 ms (n=100)\u001b[0m\n", + "\n" + ] + } + ], + "source": [ + "qa.check_response_time(item_types=[\"/\",\"/search/?type=Experiment\"], n=100)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Checking response time\n", + "\n", + "*** item_type: /search/?searchTerm=K562\n", + "------ https://v67rc1-master.demo.encodedcc.org//search/?searchTerm=K562 -------\n", + "\u001b[31mAverage es_time: 247.231 ± 30.918 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 1.578 ± 0.818 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 34.22 ± 8.142 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 300.096 ± 34.175 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 583.125 ± 67.757 ms (n=100)\u001b[0m\n", + "--------- https://series5-test-master.demo.encodedcc.org//search/?searchTerm=K562 ---------\n", + "\u001b[31mAverage es_time: 120.489 ± 8.79 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.474 ± 0.017 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 20.121 ± 7.004 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 147.443 ± 12.09 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 288.526 ± 24.21 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /search/?searchTerm=DNA+binding\n", + "--------- https://v67rc1-master.demo.encodedcc.org//search/?searchTerm=DNA+binding ---------\n", + "\u001b[31mAverage es_time: 340.179 ± 63.128 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 1.469 ± 0.64 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 35.093 ± 7.38 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 398.883 ± 67.904 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 775.624 ± 132.959 ms (n=100)\u001b[0m\n", + "--------- https://series5-test-master.demo.encodedcc.org//search/?searchTerm=DNA+binding ---------\n", + "\u001b[31mAverage es_time: 159.085 ± 12.011 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.47 ± 0.011 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 19.867 ± 4.934 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 187.435 ± 13.637 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 366.857 ± 27.199 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /search/?searchTerm=human\n", + "------ https://v67rc1-master.demo.encodedcc.org//search/?searchTerm=human ------\n", + "\u001b[31mAverage es_time: 243.735 ± 31.568 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 1.432 ± 0.65 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 35.856 ± 7.386 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 297.734 ± 34.868 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 578.757 ± 68.995 ms (n=100)\u001b[0m\n", + "--------- https://series5-test-master.demo.encodedcc.org//search/?searchTerm=human ---------\n", + "\u001b[31mAverage es_time: 121.703 ± 7.659 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.47 ± 0.014 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 18.827 ± 3.831 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 147.28 ± 8.454 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 288.28 ± 16.851 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /search/?searchTerm=H3K36me3\n", + "---- https://v67rc1-master.demo.encodedcc.org//search/?searchTerm=H3K36me3 -----\n", + "\u001b[31mAverage es_time: 247.82 ± 22.696 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 1.355 ± 0.572 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 36.565 ± 6.737 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 303.303 ± 24.603 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 589.044 ± 48.642 ms (n=100)\u001b[0m\n", + "--------- https://series5-test-master.demo.encodedcc.org//search/?searchTerm=H3K36me3 ---------\n", + "\u001b[31mAverage es_time: 121.9 ± 10.281 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.471 ± 0.013 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 19.539 ± 5.396 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 148.45 ± 12.007 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 290.36 ± 24.005 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /search/?searchTerm=CTCF\n", + "------ https://v67rc1-master.demo.encodedcc.org//search/?searchTerm=CTCF -------\n", + "\u001b[31mAverage es_time: 251.685 ± 30.658 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 1.401 ± 0.623 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 34.813 ± 6.195 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 304.38 ± 33.823 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 592.279 ± 67.151 ms (n=100)\u001b[0m\n", + "--------- https://series5-test-master.demo.encodedcc.org//search/?searchTerm=CTCF ---------\n", + "\u001b[31mAverage es_time: 119.805 ± 8.078 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.47 ± 0.014 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 18.566 ± 5.193 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 144.951 ± 9.561 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 283.792 ± 19.158 ms (n=100)\u001b[0m\n", + "\n" + ] + } + ], + "source": [ + "qa.check_response_time(item_types=[\"/search/?searchTerm=K562\", \"/search/?searchTerm=DNA+binding\", \"/search/?searchTerm=human\", \"/search/?searchTerm=H3K36me3\", \"/search/?searchTerm=CTCF\"], n=100)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Checking response time\n", + "\n", + "*** item_type: /ENCSR255XZG/\n", + "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR255XZG/ ------------\n", + "\u001b[31mAverage es_time: 55.435 ± 8.724 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 1.645 ± 0.848 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 127.78 ± 8.627 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 307.997 ± 131.595 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 492.857 ± 133.71 ms (n=100)\u001b[0m\n", + "--------- https://series5-test-master.demo.encodedcc.org//ENCSR255XZG/ ---------\n", + "\u001b[31mAverage es_time: 29.644 ± 6.814 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 1.342 ± 8.583 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 100.909 ± 5.225 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 219.994 ± 108.024 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 351.888 ± 112.01 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR749ILN/\n", + "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR749ILN/ ------------\n", + "\u001b[31mAverage es_time: 48.427 ± 4.362 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 1.583 ± 0.674 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 34.947 ± 6.31 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 111.486 ± 9.197 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 196.443 ± 17.044 ms (n=100)\u001b[0m\n", + "--------- https://series5-test-master.demo.encodedcc.org//ENCSR749ILN/ ---------\n", + "\u001b[31mAverage es_time: 23.69 ± 3.865 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.475 ± 0.009 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 20.834 ± 4.134 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 59.105 ± 5.936 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 104.103 ± 11.713 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR688GVV/\n", + "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR688GVV/ ------------\n", + "\u001b[31mAverage es_time: 55.845 ± 5.704 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 1.716 ± 0.834 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 70.328 ± 8.276 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 188.543 ± 75.737 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 316.432 ± 76.676 ms (n=100)\u001b[0m\n", + "--------- https://series5-test-master.demo.encodedcc.org//ENCSR688GVV/ ---------\n", + "\u001b[31mAverage es_time: 28.696 ± 3.626 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.481 ± 0.011 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 49.869 ± 4.111 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 113.044 ± 5.986 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 192.09 ± 11.714 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR301HAG/\n", + "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR301HAG/ ------------\n", + "\u001b[31mAverage es_time: 46.166 ± 4.401 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 1.672 ± 0.801 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 19.887 ± 35.706 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 82.21 ± 36.266 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 149.935 ± 72.54 ms (n=100)\u001b[0m\n", + "--------- https://series5-test-master.demo.encodedcc.org//ENCSR301HAG/ ---------\n", + "\u001b[31mAverage es_time: 21.248 ± 2.508 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.48 ± 0.011 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 7.292 ± 2.202 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 34.026 ± 3.386 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 63.046 ± 6.685 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR315NAC/\n", + "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR315NAC/ ------------\n", + "\u001b[31mAverage es_time: 53.566 ± 6.047 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 1.691 ± 1.269 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 58.099 ± 9.342 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 166.66 ± 90.6 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 280.016 ± 91.567 ms (n=100)\u001b[0m\n", + "--------- https://series5-test-master.demo.encodedcc.org//ENCSR315NAC/ ---------\n", + "\u001b[31mAverage es_time: 26.854 ± 2.471 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.477 ± 0.011 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 39.787 ± 4.783 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 101.165 ± 70.588 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 168.283 ± 71.092 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR856JJB/\n", + "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR856JJB/ ------------\n", + "\u001b[31mAverage es_time: 53.123 ± 5.009 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 1.647 ± 0.911 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 52.026 ± 7.765 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 146.999 ± 10.763 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 253.796 ± 19.724 ms (n=100)\u001b[0m\n", + "--------- https://series5-test-master.demo.encodedcc.org//ENCSR856JJB/ ---------\n", + "\u001b[31mAverage es_time: 26.584 ± 3.355 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.476 ± 0.012 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 34.315 ± 4.205 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 91.577 ± 68.751 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 152.954 ± 68.975 ms (n=100)\u001b[0m\n", + "\n" + ] + } + ], + "source": [ + "qa.check_response_time(item_types=['/ENCSR255XZG/', '/ENCSR749ILN/', '/ENCSR688GVV/', '/ENCSR301HAG/','/ENCSR315NAC/', '/ENCSR856JJB/'], n=100)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Checking response time\n", + "\n", + "*** item_type: /ENCSR480OHP/\n", + "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR480OHP/ ------------\n", + "\u001b[31mAverage es_time: 49.248 ± 7.209 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 1.59 ± 0.959 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 35.152 ± 5.85 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 113.677 ± 11.161 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 199.667 ± 20.251 ms (n=100)\u001b[0m\n", + "--------- https://series5-test-master.demo.encodedcc.org//ENCSR480OHP/ ---------\n", + "\u001b[31mAverage es_time: 23.853 ± 4.252 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.473 ± 0.011 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 20.966 ± 3.594 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 66.685 ± 66.256 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 111.976 ± 66.883 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR000EMB/\n", + "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR000EMB/ ------------\n", + "\u001b[31mAverage es_time: 48.658 ± 6.125 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 1.539 ± 0.753 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 53.329 ± 8.469 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 148.721 ± 76.744 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 252.247 ± 78.559 ms (n=100)\u001b[0m\n", + "--------- https://series5-test-master.demo.encodedcc.org//ENCSR000EMB/ ---------\n", + "\u001b[31mAverage es_time: 23.27 ± 2.562 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.474 ± 0.014 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 36.819 ± 4.667 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 85.352 ± 5.565 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 145.913 ± 11.049 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR323QIP/\n", + "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR323QIP/ ------------\n", + "\u001b[31mAverage es_time: 59.852 ± 5.207 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 1.699 ± 1.042 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 149.958 ± 7.728 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 378.194 ± 200.862 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 589.703 ± 201.571 ms (n=100)\u001b[0m\n", + "--------- https://series5-test-master.demo.encodedcc.org//ENCSR323QIP/ ---------\n", + "\u001b[31mAverage es_time: 32.175 ± 3.36 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.48 ± 0.01 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 122.909 ± 4.222 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 279.625 ± 129.661 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 435.189 ± 131.305 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR718AXQ/\n", + "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR718AXQ/ ------------\n", + "\u001b[31mAverage es_time: 49.831 ± 5.527 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 1.585 ± 0.908 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 25.462 ± 5.129 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 97.683 ± 8.911 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 174.561 ± 16.623 ms (n=100)\u001b[0m\n", + "--------- https://series5-test-master.demo.encodedcc.org//ENCSR718AXQ/ ---------\n", + "\u001b[31mAverage es_time: 24.651 ± 4.37 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.469 ± 0.015 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 13.743 ± 3.976 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 47.904 ± 5.918 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 86.766 ± 11.576 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR165BGV/\n", + "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR165BGV/ ------------\n", + "\u001b[31mAverage es_time: 46.408 ± 5.364 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 1.582 ± 0.76 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 28.021 ± 5.87 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 96.965 ± 8.251 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 172.976 ± 15.625 ms (n=100)\u001b[0m\n", + "--------- https://series5-test-master.demo.encodedcc.org//ENCSR165BGV/ ---------\n", + "\u001b[31mAverage es_time: 21.831 ± 4.543 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.477 ± 0.012 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 16.355 ± 3.76 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 48.902 ± 6.487 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 87.565 ± 12.923 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR384KAN/\n", + "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR384KAN/ ------------\n", + "\u001b[31mAverage es_time: 52.972 ± 5.834 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 1.706 ± 0.932 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 49.502 ± 7.612 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 144.096 ± 10.827 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 248.276 ± 21.148 ms (n=100)\u001b[0m\n", + "--------- https://series5-test-master.demo.encodedcc.org//ENCSR384KAN/ ---------\n", + "\u001b[31mAverage es_time: 26.172 ± 3.102 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.472 ± 0.01 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 32.696 ± 4.335 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 89.048 ± 65.064 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 148.388 ± 65.329 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR330FXL/\n", + "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR330FXL/ ------------\n", + "\u001b[31mAverage es_time: 47.005 ± 10.829 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 1.339 ± 0.644 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 31.984 ± 5.899 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 104.802 ± 14.101 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 185.131 ± 25.715 ms (n=100)\u001b[0m\n", + "--------- https://series5-test-master.demo.encodedcc.org//ENCSR330FXL/ ---------\n", + "\u001b[31mAverage es_time: 21.27 ± 3.32 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.46 ± 0.01 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 19.611 ± 3.139 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 57.237 ± 32.377 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 98.577 ± 33.33 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR825UNV/\n", + "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR825UNV/ ------------\n", + "\u001b[31mAverage es_time: 60.881 ± 6.646 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 1.917 ± 0.956 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage render_time: 176.879 ± 8.834 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage wsgi_time: 412.39 ± 165.104 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 652.068 ± 167.389 ms (n=100)\u001b[0m\n", + "--------- https://series5-test-master.demo.encodedcc.org//ENCSR825UNV/ ---------\n", + "\u001b[31mAverage es_time: 32.656 ± 4.562 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.485 ± 0.012 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 148.88 ± 3.654 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 362.182 ± 207.96 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 544.202 ± 208.411 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR089EOA/\n", + "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR089EOA/ ------------\n" + ] + } + ], + "source": [ + "qa.check_response_time(item_types=['/ENCSR480OHP/','/ENCSR000EMB/','/ENCSR323QIP/','/ENCSR718AXQ/','/ENCSR165BGV/','/ENCSR384KAN/','/ENCSR330FXL/','/ENCSR825UNV/','/ENCSR089EOA/'], n=100)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "qa.check_response_time(item_types=['/ENCAB830JLB/','/ENCAB000BKR/','/ENCAB284TTY/','/ENCAB294YUD/','/ENCAB000AOC/','/ENCAB301QZF/','/ENCAB000ANM/','/ENCAB000ANU/','/ENCAB445KMF/','/ENCAB000BAY/'], n=100)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "qa.check_response_time(item_types=['/ENCBS787TFV/','/ENCBS676QAV/','/ENCBS996IWU/','/ENCBS913XJP/','/ENCBS565NTN/','/ENCBS896YZO/','/ENCBS280NYD/'], n=100)" + ] + }, + { + "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": "3.4.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/jupyter_notebooks/timing-tests-sno-33.ipynb b/jupyter_notebooks/timing-tests-sno-33.ipynb new file mode 100644 index 00000000..7c080d82 --- /dev/null +++ b/jupyter_notebooks/timing-tests-sno-33.ipynb @@ -0,0 +1,2526 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "%load_ext autoreload" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "%autoreload\n", + "import sys\n", + "sys.path.append('..')\n", + "import qancode\n", + "import numpy as np\n", + "import pandas as pd" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "#compare any two encoded instances here\n", + "qa = qancode.QANCODE(rc_url=\"https://test.encodedcc.org\", prod_url='https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org/')" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Checking response time\n", + "\n", + "*** item_type: /\n", + "---------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org// ----------\n", + "\u001b[36mAverage es_time: 0.733 ± 0.051 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.37 ± 0.032 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 3.005 ± 0.283 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 7.108 ± 0.454 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 11.216 ± 0.764 ms (n=50)\u001b[0m\n", + "------------------------- https://test.encodedcc.org/ --------------------------\n", + "\u001b[31mAverage es_time: 13.38 ± 3.615 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.421 ± 0.017 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 3.946 ± 1.37 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 21.032 ± 4.176 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 38.779 ± 8.338 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /search/?type=Experiment\n", + "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//search/?type=Experiment ---------\n", + "\u001b[31mAverage es_time: 14.774 ± 1.608 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.473 ± 0.013 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 110.853 ± 10.258 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 140.347 ± 11.087 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 266.447 ± 21.867 ms (n=50)\u001b[0m\n", + "-------------- https://test.encodedcc.org/search/?type=Experiment --------------\n", + "\u001b[31mAverage es_time: 22.591 ± 6.109 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.473 ± 0.014 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 110.62 ± 15.968 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 148.084 ± 18.568 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 281.768 ± 37.016 ms (n=50)\u001b[0m\n", + "\n" + ] + } + ], + "source": [ + "res = qa.check_response_time(item_types=[\"/\",\"/search/?type=Experiment\"], n=50)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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https://es-frontend2.demo.encodedcc.org/https://es-frontend2.demo.encodedcc.org/search/?type=Experimenthttps://test.encodedcc.org/https://test.encodedcc.org/search/?type=Experiment
es_time_mean16.25625.66813.31324.365
es_time_std2.5876.9293.4757.398
es_time_N50.00050.00050.00050.000
queue_time_mean1.1191.0680.4350.478
queue_time_std0.2740.4280.0320.013
queue_time_N50.00050.00050.00050.000
render_time_mean10.741150.6304.018108.651
render_time_std3.37414.4791.52714.653
render_time_N50.00050.00050.00050.000
wsgi_time_mean37.187202.89920.967147.731
wsgi_time_std5.29817.4184.04716.097
wsgi_time_N50.00050.00050.00050.000
total_mean65.303380.26438.734281.225
total_std9.44734.5088.12632.119
total_N50.00050.00050.00050.000
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" + ], + "text/plain": [ + " https://es-frontend2.demo.encodedcc.org/ \\\n", + "es_time_mean 16.256 \n", + "es_time_std 2.587 \n", + "es_time_N 50.000 \n", + "queue_time_mean 1.119 \n", + "queue_time_std 0.274 \n", + "queue_time_N 50.000 \n", + "render_time_mean 10.741 \n", + "render_time_std 3.374 \n", + "render_time_N 50.000 \n", + "wsgi_time_mean 37.187 \n", + "wsgi_time_std 5.298 \n", + "wsgi_time_N 50.000 \n", + "total_mean 65.303 \n", + "total_std 9.447 \n", + "total_N 50.000 \n", + "\n", + " https://es-frontend2.demo.encodedcc.org/search/?type=Experiment \\\n", + "es_time_mean 25.668 \n", + "es_time_std 6.929 \n", + "es_time_N 50.000 \n", + "queue_time_mean 1.068 \n", + "queue_time_std 0.428 \n", + "queue_time_N 50.000 \n", + "render_time_mean 150.630 \n", + "render_time_std 14.479 \n", + "render_time_N 50.000 \n", + "wsgi_time_mean 202.899 \n", + "wsgi_time_std 17.418 \n", + "wsgi_time_N 50.000 \n", + "total_mean 380.264 \n", + "total_std 34.508 \n", + "total_N 50.000 \n", + "\n", + " https://test.encodedcc.org/ \\\n", + "es_time_mean 13.313 \n", + "es_time_std 3.475 \n", + "es_time_N 50.000 \n", + "queue_time_mean 0.435 \n", + "queue_time_std 0.032 \n", + "queue_time_N 50.000 \n", + "render_time_mean 4.018 \n", + "render_time_std 1.527 \n", + "render_time_N 50.000 \n", + "wsgi_time_mean 20.967 \n", + "wsgi_time_std 4.047 \n", + "wsgi_time_N 50.000 \n", + "total_mean 38.734 \n", + "total_std 8.126 \n", + "total_N 50.000 \n", + "\n", + " https://test.encodedcc.org/search/?type=Experiment \n", + "es_time_mean 24.365 \n", + "es_time_std 7.398 \n", + "es_time_N 50.000 \n", + "queue_time_mean 0.478 \n", + "queue_time_std 0.013 \n", + "queue_time_N 50.000 \n", + "render_time_mean 108.651 \n", + "render_time_std 14.653 \n", + "render_time_N 50.000 \n", + "wsgi_time_mean 147.731 \n", + "wsgi_time_std 16.097 \n", + "wsgi_time_N 50.000 \n", + "total_mean 281.225 \n", + "total_std 32.119 \n", + "total_N 50.000 " + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "res" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Checking response time\n", + "\n", + "*** item_type: /search/?searchTerm=K562\n", + "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//search/?searchTerm=K562 ---------\n", + "\u001b[31mAverage es_time: 157.582 ± 3.94 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.482 ± 0.009 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 19.609 ± 7.719 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 183.631 ± 9.635 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 361.305 ± 19.223 ms (n=50)\u001b[0m\n", + "-------------- https://test.encodedcc.org/search/?searchTerm=K562 --------------\n", + "\u001b[31mAverage es_time: 190.879 ± 12.549 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.466 ± 0.011 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 19.467 ± 7.491 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 216.898 ± 14.289 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage total time: 427.71 ± 28.647 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /search/?searchTerm=DNA+binding\n", + "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//search/?searchTerm=DNA+binding ---------\n", + "\u001b[31mAverage es_time: 263.99 ± 4.486 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.483 ± 0.009 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 21.016 ± 5.636 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 293.514 ± 7.857 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage total time: 579.003 ± 15.653 ms (n=50)\u001b[0m\n", + "---------- https://test.encodedcc.org/search/?searchTerm=DNA+binding -----------\n", + "\u001b[31mAverage es_time: 281.067 ± 12.781 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.474 ± 0.023 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 20.123 ± 5.02 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 309.671 ± 14.141 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage total time: 611.335 ± 28.274 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /search/?searchTerm=human\n", + "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//search/?searchTerm=human ---------\n", + "\u001b[31mAverage es_time: 156.92 ± 3.856 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.48 ± 0.008 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 19.892 ± 4.162 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 183.057 ± 5.94 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 360.349 ± 11.868 ms (n=50)\u001b[0m\n", + "------------- https://test.encodedcc.org/search/?searchTerm=human --------------\n", + "\u001b[31mAverage es_time: 192.853 ± 9.624 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.466 ± 0.009 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 22.357 ± 6.606 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 221.441 ± 11.136 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage total time: 437.116 ± 22.276 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /search/?searchTerm=H3K36me3\n", + "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//search/?searchTerm=H3K36me3 ---------\n", + "\u001b[31mAverage es_time: 159.429 ± 3.633 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.483 ± 0.007 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 22.086 ± 6.045 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 188.201 ± 7.418 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 370.199 ± 14.642 ms (n=50)\u001b[0m\n", + "------------ https://test.encodedcc.org/search/?searchTerm=H3K36me3 ------------\n", + "\u001b[31mAverage es_time: 190.384 ± 9.842 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.466 ± 0.015 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 20.169 ± 4.732 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 217.075 ± 11.681 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage total time: 428.094 ± 23.346 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /search/?searchTerm=CTCF\n", + "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//search/?searchTerm=CTCF ---------\n", + "\u001b[31mAverage es_time: 158.013 ± 3.384 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.487 ± 0.011 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 17.455 ± 3.967 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 181.733 ± 4.878 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 357.688 ± 9.764 ms (n=50)\u001b[0m\n", + "-------------- https://test.encodedcc.org/search/?searchTerm=CTCF --------------\n", + "\u001b[31mAverage es_time: 190.518 ± 10.276 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.48 ± 0.021 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 18.016 ± 4.338 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 214.748 ± 10.204 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage total time: 423.763 ± 20.429 ms (n=50)\u001b[0m\n", + "\n" + ] + }, + { + "data": { + "text/html": [ + "
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es_time_mean158.013263.990159.429157.582156.920190.518281.067190.384190.879192.853
es_time_std3.3844.4863.6333.9403.85610.27612.7819.84212.5499.624
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queue_time_mean0.4870.4830.4830.4820.4800.4800.4740.4660.4660.466
queue_time_std0.0110.0090.0070.0090.0080.0210.0230.0150.0110.009
queue_time_N50.00050.00050.00050.00050.00050.00050.00050.00050.00050.000
render_time_mean17.45521.01622.08619.60919.89218.01620.12320.16919.46722.357
render_time_std3.9675.6366.0457.7194.1624.3385.0204.7327.4916.606
render_time_N50.00050.00050.00050.00050.00050.00050.00050.00050.00050.000
wsgi_time_mean181.733293.514188.201183.631183.057214.748309.671217.075216.898221.441
wsgi_time_std4.8787.8577.4189.6355.94010.20414.14111.68114.28911.136
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total_mean357.688579.003370.199361.305360.349423.763611.335428.094427.710437.116
total_std9.76415.65314.64219.22311.86820.42928.27423.34628.64722.276
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\n", + "wsgi_time_std 11.681 \n", + "wsgi_time_N 50.000 \n", + "total_mean 428.094 \n", + "total_std 23.346 \n", + "total_N 50.000 \n", + "\n", + " https://test.encodedcc.org/search/?searchTerm=K562 \\\n", + "es_time_mean 190.879 \n", + "es_time_std 12.549 \n", + "es_time_N 50.000 \n", + "queue_time_mean 0.466 \n", + "queue_time_std 0.011 \n", + "queue_time_N 50.000 \n", + "render_time_mean 19.467 \n", + "render_time_std 7.491 \n", + "render_time_N 50.000 \n", + "wsgi_time_mean 216.898 \n", + "wsgi_time_std 14.289 \n", + "wsgi_time_N 50.000 \n", + "total_mean 427.710 \n", + "total_std 28.647 \n", + "total_N 50.000 \n", + "\n", + " https://test.encodedcc.org/search/?searchTerm=human \n", + "es_time_mean 192.853 \n", + "es_time_std 9.624 \n", + "es_time_N 50.000 \n", + "queue_time_mean 0.466 \n", + "queue_time_std 0.009 \n", + "queue_time_N 50.000 \n", + "render_time_mean 22.357 \n", + "render_time_std 6.606 \n", + "render_time_N 50.000 \n", + "wsgi_time_mean 221.441 \n", + "wsgi_time_std 11.136 \n", + "wsgi_time_N 50.000 \n", + "total_mean 437.116 \n", + "total_std 22.276 \n", + "total_N 50.000 " + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "qa.check_response_time(item_types=[\"/search/?searchTerm=K562\", \"/search/?searchTerm=DNA+binding\", \"/search/?searchTerm=human\", \"/search/?searchTerm=H3K36me3\", \"/search/?searchTerm=CTCF\"], n=50)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Checking response time\n", + "\n", + "*** item_type: /ENCSR255XZG/\n", + "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR255XZG/ ---------\n", + "\u001b[36mAverage es_time: 3.427 ± 0.14 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.473 ± 0.011 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 102.627 ± 6.713 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 229.562 ± 170.299 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 336.089 ± 169.153 ms (n=50)\u001b[0m\n", + "------------------- https://test.encodedcc.org/ENCSR255XZG/ --------------------\n", + "\u001b[31mAverage es_time: 22.524 ± 5.369 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.484 ± 0.012 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 101.847 ± 4.433 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 222.274 ± 123.298 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 347.13 ± 123.42 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR749ILN/\n", + "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR749ILN/ ---------\n", + "\u001b[36mAverage es_time: 1.969 ± 0.707 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.458 ± 0.012 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 21.579 ± 4.237 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 37.883 ± 4.18 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 61.889 ± 8.476 ms (n=50)\u001b[0m\n", + "------------------- https://test.encodedcc.org/ENCSR749ILN/ --------------------\n", + "\u001b[31mAverage es_time: 16.634 ± 2.976 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.482 ± 0.017 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 21.232 ± 4.268 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 52.689 ± 4.831 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 91.036 ± 9.701 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR688GVV/\n", + "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR688GVV/ ---------\n", + "\u001b[36mAverage es_time: 3.353 ± 0.049 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.472 ± 0.008 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 50.326 ± 4.796 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 87.704 ± 4.724 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 141.855 ± 9.481 ms (n=50)\u001b[0m\n", + "------------------- https://test.encodedcc.org/ENCSR688GVV/ --------------------\n", + "\u001b[31mAverage es_time: 20.651 ± 4.494 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.481 ± 0.014 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 50.141 ± 5.997 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 104.909 ± 7.084 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 176.182 ± 14.266 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR301HAG/\n", + "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR301HAG/ ---------\n", + "\u001b[36mAverage es_time: 1.188 ± 0.037 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.472 ± 0.011 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 9.058 ± 4.089 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 15.581 ± 4.08 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 26.298 ± 8.169 ms (n=50)\u001b[0m\n", + "------------------- https://test.encodedcc.org/ENCSR301HAG/ --------------------\n", + "\u001b[31mAverage es_time: 15.776 ± 4.047 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.476 ± 0.011 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 7.52 ± 1.928 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 28.649 ± 4.635 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 52.42 ± 9.221 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR315NAC/\n", + "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR315NAC/ ---------\n", + "\u001b[36mAverage es_time: 2.861 ± 0.073 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.469 ± 0.012 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 40.14 ± 5.249 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 98.165 ± 138.118 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 141.635 ± 138.012 ms (n=50)\u001b[0m\n", + "------------------- https://test.encodedcc.org/ENCSR315NAC/ --------------------\n", + "\u001b[31mAverage es_time: 20.143 ± 4.434 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.479 ± 0.014 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 40.894 ± 5.696 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 88.257 ± 6.484 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 149.773 ± 13.098 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR856JJB/\n", + "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR856JJB/ ---------\n", + "\u001b[36mAverage es_time: 2.748 ± 0.057 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.469 ± 0.01 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 35.655 ± 4.13 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 62.074 ± 4.346 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 100.947 ± 8.435 ms (n=50)\u001b[0m\n", + "------------------- https://test.encodedcc.org/ENCSR856JJB/ --------------------\n", + "\u001b[31mAverage es_time: 19.421 ± 3.729 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.481 ± 0.01 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 34.81 ± 4.648 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 77.726 ± 5.414 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 132.439 ± 10.807 ms (n=50)\u001b[0m\n", + "\n" + ] + }, + { + "data": { + "text/html": [ + "
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es_time_mean3.4271.1882.8613.3531.9692.74822.52415.77620.14320.65116.63419.421
es_time_std0.1400.0370.0730.0490.7070.0575.3694.0474.4344.4942.9763.729
es_time_N50.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.000
queue_time_mean0.4730.4720.4690.4720.4580.4690.4840.4760.4790.4810.4820.481
queue_time_std0.0110.0110.0120.0080.0120.0100.0120.0110.0140.0140.0170.010
queue_time_N50.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.000
render_time_mean102.6279.05840.14050.32621.57935.655101.8477.52040.89450.14121.23234.810
render_time_std6.7134.0895.2494.7964.2374.1304.4331.9285.6965.9974.2684.648
render_time_N50.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.000
wsgi_time_mean229.56215.58198.16587.70437.88362.074222.27428.64988.257104.90952.68977.726
wsgi_time_std170.2994.080138.1184.7244.1804.346123.2984.6356.4847.0844.8315.414
wsgi_time_N50.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.000
total_mean336.08926.298141.635141.85561.889100.947347.13052.420149.773176.18291.036132.439
total_std169.1538.169138.0129.4818.4768.435123.4209.22113.09814.2669.70110.807
total_N50.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.000
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https://test.encodedcc.org/ENCSR749ILN/ \\\n", + "es_time_mean 16.634 \n", + "es_time_std 2.976 \n", + "es_time_N 50.000 \n", + "queue_time_mean 0.482 \n", + "queue_time_std 0.017 \n", + "queue_time_N 50.000 \n", + "render_time_mean 21.232 \n", + "render_time_std 4.268 \n", + "render_time_N 50.000 \n", + "wsgi_time_mean 52.689 \n", + "wsgi_time_std 4.831 \n", + "wsgi_time_N 50.000 \n", + "total_mean 91.036 \n", + "total_std 9.701 \n", + "total_N 50.000 \n", + "\n", + " https://test.encodedcc.org/ENCSR856JJB/ \n", + "es_time_mean 19.421 \n", + "es_time_std 3.729 \n", + "es_time_N 50.000 \n", + "queue_time_mean 0.481 \n", + "queue_time_std 0.010 \n", + "queue_time_N 50.000 \n", + "render_time_mean 34.810 \n", + "render_time_std 4.648 \n", + "render_time_N 50.000 \n", + "wsgi_time_mean 77.726 \n", + "wsgi_time_std 5.414 \n", + "wsgi_time_N 50.000 \n", + "total_mean 132.439 \n", + "total_std 10.807 \n", + "total_N 50.000 " + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "qa.check_response_time(item_types=['/ENCSR255XZG/', '/ENCSR749ILN/', '/ENCSR688GVV/', '/ENCSR301HAG/','/ENCSR315NAC/', '/ENCSR856JJB/'], n=50)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Checking response time\n", + "\n", + "*** item_type: /experiments/ENCSR255XZG/\n", + "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//experiments/ENCSR255XZG/ ---------\n", + "\u001b[36mAverage es_time: 3.465 ± 0.14 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.469 ± 0.012 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 102.812 ± 2.761 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 204.397 ± 119.778 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 311.142 ± 120.439 ms (n=50)\u001b[0m\n", + "------------- https://test.encodedcc.org/experiments/ENCSR255XZG/ --------------\n", + "\u001b[31mAverage es_time: 21.519 ± 2.996 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.49 ± 0.02 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 104.027 ± 2.903 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 227.953 ± 136.849 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 353.989 ± 137.183 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /experiments/ENCSR749ILN/\n", + "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//experiments/ENCSR749ILN/ ---------\n", + "\u001b[36mAverage es_time: 1.812 ± 0.057 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.428 ± 0.014 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 20.299 ± 4.004 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 36.672 ± 4.513 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 59.211 ± 8.474 ms (n=50)\u001b[0m\n", + "------------- https://test.encodedcc.org/experiments/ENCSR749ILN/ --------------\n", + "\u001b[31mAverage es_time: 16.351 ± 3.407 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.492 ± 0.026 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 20.522 ± 3.501 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 51.948 ± 5.347 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 89.314 ± 9.98 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /experiments/ENCSR688GVV/\n", + "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//experiments/ENCSR688GVV/ ---------\n", + "\u001b[36mAverage es_time: 3.392 ± 0.15 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.458 ± 0.011 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 44.491 ± 4.214 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 95.576 ± 95.782 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 143.916 ± 97.697 ms (n=50)\u001b[0m\n", + "------------- https://test.encodedcc.org/experiments/ENCSR688GVV/ --------------\n", + "\u001b[31mAverage es_time: 20.404 ± 3.93 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.499 ± 0.021 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 46.417 ± 4.955 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 101.581 ± 6.566 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 168.9 ± 12.805 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /experiments/ENCSR301HAG/\n", + "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//experiments/ENCSR301HAG/ ---------\n", + "\u001b[36mAverage es_time: 1.191 ± 0.033 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.46 ± 0.015 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 9.183 ± 4.054 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 15.75 ± 4.066 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 26.584 ± 8.117 ms (n=50)\u001b[0m\n", + "------------- https://test.encodedcc.org/experiments/ENCSR301HAG/ --------------\n", + "\u001b[31mAverage es_time: 15.04 ± 6.581 ms (n=50)\u001b[0m\n", + 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0.464 ± 0.017 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 36.909 ± 4.456 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 83.347 ± 6.864 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 139.721 ± 12.583 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /experiments/ENCSR856JJB/\n", + "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//experiments/ENCSR856JJB/ ---------\n", + "\u001b[36mAverage es_time: 2.744 ± 0.066 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.439 ± 0.022 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 31.81 ± 5.409 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 58.038 ± 5.628 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 93.031 ± 11.021 ms (n=50)\u001b[0m\n", + "------------- https://test.encodedcc.org/experiments/ENCSR856JJB/ --------------\n", + "\u001b[31mAverage es_time: 19.184 ± 5.515 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.465 ± 0.025 ms 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es_time_std0.1400.0330.0880.1500.0570.0662.9966.5814.0623.9303.4075.515
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render_time_mean102.8129.18335.79944.49120.29931.810104.0276.68036.90946.41720.52230.939
render_time_std2.7614.0544.0844.2144.0045.4092.9031.5194.4564.9553.5014.881
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wsgi_time_mean204.39715.75080.27195.57636.67258.038227.95327.05883.347101.58151.94873.260
wsgi_time_std119.7784.066101.84295.7824.5135.628136.8496.5496.8646.5665.3477.695
wsgi_time_N50.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.000
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total_std120.4398.117101.66797.6978.47411.021137.18313.12212.58312.8059.98015.186
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\n", + "wsgi_time_std 5.628 \n", + "wsgi_time_N 50.000 \n", + "total_mean 93.031 \n", + "total_std 11.021 \n", + "total_N 50.000 \n", + "\n", + " https://test.encodedcc.org/experiments/ENCSR255XZG/ \\\n", + "es_time_mean 21.519 \n", + "es_time_std 2.996 \n", + "es_time_N 50.000 \n", + "queue_time_mean 0.490 \n", + "queue_time_std 0.020 \n", + "queue_time_N 50.000 \n", + "render_time_mean 104.027 \n", + "render_time_std 2.903 \n", + "render_time_N 50.000 \n", + "wsgi_time_mean 227.953 \n", + "wsgi_time_std 136.849 \n", + "wsgi_time_N 50.000 \n", + "total_mean 353.989 \n", + "total_std 137.183 \n", + "total_N 50.000 \n", + "\n", + " https://test.encodedcc.org/experiments/ENCSR301HAG/ \\\n", + "es_time_mean 15.040 \n", + "es_time_std 6.581 \n", + "es_time_N 50.000 \n", + "queue_time_mean 0.411 \n", + "queue_time_std 0.027 \n", + "queue_time_N 50.000 \n", + "render_time_mean 6.680 \n", + "render_time_std 1.519 \n", + "render_time_N 50.000 \n", + "wsgi_time_mean 27.058 \n", + "wsgi_time_std 6.549 \n", + "wsgi_time_N 50.000 \n", + "total_mean 49.189 \n", + "total_std 13.122 \n", + "total_N 50.000 \n", + "\n", + " https://test.encodedcc.org/experiments/ENCSR315NAC/ \\\n", + "es_time_mean 19.000 \n", + "es_time_std 4.062 \n", + "es_time_N 50.000 \n", + "queue_time_mean 0.464 \n", + "queue_time_std 0.017 \n", + "queue_time_N 50.000 \n", + "render_time_mean 36.909 \n", + "render_time_std 4.456 \n", + "render_time_N 50.000 \n", + "wsgi_time_mean 83.347 \n", + "wsgi_time_std 6.864 \n", + "wsgi_time_N 50.000 \n", + "total_mean 139.721 \n", + "total_std 12.583 \n", + "total_N 50.000 \n", + "\n", + " https://test.encodedcc.org/experiments/ENCSR688GVV/ \\\n", + "es_time_mean 20.404 \n", + "es_time_std 3.930 \n", + "es_time_N 50.000 \n", + "queue_time_mean 0.499 \n", + "queue_time_std 0.021 \n", + "queue_time_N 50.000 \n", + "render_time_mean 46.417 \n", + "render_time_std 4.955 \n", + "render_time_N 50.000 \n", + "wsgi_time_mean 101.581 \n", + "wsgi_time_std 6.566 \n", + "wsgi_time_N 50.000 \n", + "total_mean 168.900 \n", + "total_std 12.805 \n", + "total_N 50.000 \n", + "\n", + " https://test.encodedcc.org/experiments/ENCSR749ILN/ \\\n", + "es_time_mean 16.351 \n", + "es_time_std 3.407 \n", + "es_time_N 50.000 \n", + "queue_time_mean 0.492 \n", + "queue_time_std 0.026 \n", + "queue_time_N 50.000 \n", + "render_time_mean 20.522 \n", + "render_time_std 3.501 \n", + "render_time_N 50.000 \n", + "wsgi_time_mean 51.948 \n", + "wsgi_time_std 5.347 \n", + "wsgi_time_N 50.000 \n", + "total_mean 89.314 \n", + "total_std 9.980 \n", + "total_N 50.000 \n", + "\n", + " https://test.encodedcc.org/experiments/ENCSR856JJB/ \n", + "es_time_mean 19.184 \n", + "es_time_std 5.515 \n", + "es_time_N 50.000 \n", + "queue_time_mean 0.465 \n", + "queue_time_std 0.025 \n", + "queue_time_N 50.000 \n", + "render_time_mean 30.939 \n", + "render_time_std 4.881 \n", + "render_time_N 50.000 \n", + "wsgi_time_mean 73.260 \n", + "wsgi_time_std 7.695 \n", + "wsgi_time_N 50.000 \n", + "total_mean 123.848 \n", + "total_std 15.186 \n", + "total_N 50.000 " + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "qa.check_response_time(item_types=['/experiments/ENCSR255XZG/', '/experiments/ENCSR749ILN/', '/experiments/ENCSR688GVV/', '/experiments/ENCSR301HAG/','/experiments/ENCSR315NAC/', '/experiments/ENCSR856JJB/'], n=50)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Checking response time\n", + "\n", + "*** item_type: /ENCSR255XZG/\n", + "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR255XZG/ ---------\n", + "\u001b[36mAverage es_time: 3.548 ± 0.306 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.468 ± 0.013 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 102.824 ± 127.339 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 106.841 ± 127.372 ms (n=50)\u001b[0m\n", + "------------------- https://test.encodedcc.org/ENCSR255XZG/ --------------------\n", + "\u001b[31mAverage es_time: 22.733 ± 5.298 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.473 ± 0.017 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 96.062 ± 5.493 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 119.268 ± 10.715 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR749ILN/\n", + "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR749ILN/ ---------\n", + "\u001b[36mAverage es_time: 1.893 ± 0.242 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.46 ± 0.014 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 16.17 ± 0.901 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 18.523 ± 0.986 ms (n=50)\u001b[0m\n", + "------------------- https://test.encodedcc.org/ENCSR749ILN/ --------------------\n", + "\u001b[31mAverage es_time: 17.565 ± 5.914 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.481 ± 0.031 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 46.521 ± 98.772 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 64.567 ± 98.946 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR688GVV/\n", + "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR688GVV/ ---------\n", + "\u001b[36mAverage es_time: 3.36 ± 0.08 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.471 ± 0.011 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 62.86 ± 124.371 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 66.69 ± 124.415 ms (n=50)\u001b[0m\n", + "------------------- https://test.encodedcc.org/ENCSR688GVV/ --------------------\n", + "\u001b[31mAverage es_time: 20.534 ± 3.046 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.481 ± 0.012 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 54.658 ± 3.246 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 75.673 ± 6.239 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR301HAG/\n", + "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR301HAG/ ---------\n", + "\u001b[36mAverage es_time: 1.185 ± 0.039 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.467 ± 0.009 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 6.503 ± 0.385 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 8.155 ± 0.401 ms (n=50)\u001b[0m\n", + "------------------- https://test.encodedcc.org/ENCSR301HAG/ --------------------\n", + "\u001b[31mAverage es_time: 15.949 ± 3.715 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.48 ± 0.011 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 21.453 ± 3.775 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 37.882 ± 7.485 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR315NAC/\n", + "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR315NAC/ ---------\n", + "\u001b[36mAverage es_time: 2.85 ± 0.062 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.465 ± 0.01 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 43.198 ± 93.904 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 46.513 ± 93.931 ms (n=50)\u001b[0m\n", + "------------------- https://test.encodedcc.org/ENCSR315NAC/ --------------------\n", + "\u001b[31mAverage es_time: 34.573 ± 103.978 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.48 ± 0.011 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 61.732 ± 104.098 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 96.785 ± 208.075 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR856JJB/\n", + "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR856JJB/ ---------\n", + "\u001b[36mAverage es_time: 2.758 ± 0.045 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.466 ± 0.01 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 26.436 ± 1.023 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 29.66 ± 1.036 ms (n=50)\u001b[0m\n", + "------------------- https://test.encodedcc.org/ENCSR856JJB/ --------------------\n", + "\u001b[31mAverage es_time: 19.524 ± 4.852 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.47 ± 0.029 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 42.871 ± 5.054 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 62.865 ± 9.874 ms (n=50)\u001b[0m\n", + "\n" + ] + }, + { + "data": { + "text/html": [ + "
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wsgi_time_std127.3390.38593.904124.3710.9011.0235.4933.775104.0983.24698.7725.054
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+ "wsgi_time_N 50.000 \n", + "total_mean 18.523 \n", + "total_std 0.986 \n", + "total_N 50.000 \n", + "\n", + " https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR856JJB/ \\\n", + "es_time_mean 2.758 \n", + "es_time_std 0.045 \n", + "es_time_N 50.000 \n", + "queue_time_mean 0.466 \n", + "queue_time_std 0.010 \n", + "queue_time_N 50.000 \n", + "wsgi_time_mean 26.436 \n", + "wsgi_time_std 1.023 \n", + "wsgi_time_N 50.000 \n", + "total_mean 29.660 \n", + "total_std 1.036 \n", + "total_N 50.000 \n", + "\n", + " https://test.encodedcc.org/ENCSR255XZG/ \\\n", + "es_time_mean 22.733 \n", + "es_time_std 5.298 \n", + "es_time_N 50.000 \n", + "queue_time_mean 0.473 \n", + "queue_time_std 0.017 \n", + "queue_time_N 50.000 \n", + "wsgi_time_mean 96.062 \n", + "wsgi_time_std 5.493 \n", + "wsgi_time_N 50.000 \n", + "total_mean 119.268 \n", + "total_std 10.715 \n", + "total_N 50.000 \n", + "\n", + " https://test.encodedcc.org/ENCSR301HAG/ \\\n", + "es_time_mean 15.949 \n", + "es_time_std 3.715 \n", + "es_time_N 50.000 \n", + "queue_time_mean 0.480 \n", + "queue_time_std 0.011 \n", + "queue_time_N 50.000 \n", + "wsgi_time_mean 21.453 \n", + "wsgi_time_std 3.775 \n", + "wsgi_time_N 50.000 \n", + "total_mean 37.882 \n", + "total_std 7.485 \n", + "total_N 50.000 \n", + "\n", + " https://test.encodedcc.org/ENCSR315NAC/ \\\n", + "es_time_mean 34.573 \n", + "es_time_std 103.978 \n", + "es_time_N 50.000 \n", + "queue_time_mean 0.480 \n", + "queue_time_std 0.011 \n", + "queue_time_N 50.000 \n", + "wsgi_time_mean 61.732 \n", + "wsgi_time_std 104.098 \n", + "wsgi_time_N 50.000 \n", + "total_mean 96.785 \n", + "total_std 208.075 \n", + "total_N 50.000 \n", + "\n", + " https://test.encodedcc.org/ENCSR688GVV/ \\\n", + "es_time_mean 20.534 \n", + "es_time_std 3.046 \n", + "es_time_N 50.000 \n", + "queue_time_mean 0.481 \n", + "queue_time_std 0.012 \n", + "queue_time_N 50.000 \n", + "wsgi_time_mean 54.658 \n", + "wsgi_time_std 3.246 \n", + "wsgi_time_N 50.000 \n", + "total_mean 75.673 \n", + "total_std 6.239 \n", + "total_N 50.000 \n", + "\n", + " https://test.encodedcc.org/ENCSR749ILN/ \\\n", + "es_time_mean 17.565 \n", + "es_time_std 5.914 \n", + "es_time_N 50.000 \n", + "queue_time_mean 0.481 \n", + "queue_time_std 0.031 \n", + "queue_time_N 50.000 \n", + "wsgi_time_mean 46.521 \n", + "wsgi_time_std 98.772 \n", + "wsgi_time_N 50.000 \n", + "total_mean 64.567 \n", + "total_std 98.946 \n", + "total_N 50.000 \n", + "\n", + " https://test.encodedcc.org/ENCSR856JJB/ \n", + "es_time_mean 19.524 \n", + "es_time_std 4.852 \n", + "es_time_N 50.000 \n", + "queue_time_mean 0.470 \n", + "queue_time_std 0.029 \n", + "queue_time_N 50.000 \n", + "wsgi_time_mean 42.871 \n", + "wsgi_time_std 5.054 \n", + "wsgi_time_N 50.000 \n", + "total_mean 62.865 \n", + "total_std 9.874 \n", + "total_N 50.000 " + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "qa.check_response_time(json=True, item_types=['/ENCSR255XZG/', '/ENCSR749ILN/', '/ENCSR688GVV/', '/ENCSR301HAG/','/ENCSR315NAC/', '/ENCSR856JJB/'], n=50)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": false + }, + "outputs": [], + "source": [ + "qa.check_response_time(item_types=['/ENCSR480OHP/','/ENCSR000EMB/','/ENCSR323QIP/','/ENCSR718AXQ/','/ENCSR165BGV/','/ENCSR384KAN/','/ENCSR330FXL/','/ENCSR825UNV/'], n=50)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "qa.check_response_time(item_types=['/ENCAB830JLB/','/ENCAB000BKR/','/ENCAB284TTY/','/ENCAB294YUD/','/ENCAB000AOC/','/ENCAB301QZF/','/ENCAB000ANM/','/ENCAB000ANU/','/ENCAB445KMF/','/ENCAB000BAY/'], n=50)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "qa.check_response_time(item_types=['/ENCBS787TFV/','/ENCBS676QAV/','/ENCBS996IWU/','/ENCBS913XJP/','/ENCBS565NTN/','/ENCBS896YZO/','/ENCBS280NYD/'], n=50)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "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": "3.4.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From a5cd8229d87cec03713cc4e0f4c7c58ebf16d3a1 Mon Sep 17 00:00:00 2001 From: Ben Hitz Date: Wed, 27 Jun 2018 13:31:13 -0700 Subject: [PATCH 2/5] remove stray checkpoint --- .../v64-duplicate vs. v65rc2-checkpoint.ipynb | 463 ------------------ 1 file changed, 463 deletions(-) delete mode 100644 jupyter_notebooks/kath/.ipynb_checkpoints/v64-duplicate vs. v65rc2-checkpoint.ipynb diff --git a/jupyter_notebooks/kath/.ipynb_checkpoints/v64-duplicate vs. v65rc2-checkpoint.ipynb b/jupyter_notebooks/kath/.ipynb_checkpoints/v64-duplicate vs. v65rc2-checkpoint.ipynb deleted file mode 100644 index c269cc8a..00000000 --- a/jupyter_notebooks/kath/.ipynb_checkpoints/v64-duplicate vs. v65rc2-checkpoint.ipynb +++ /dev/null @@ -1,463 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "import sys\n", - "sys.path.append('../..')\n", - "import qancode" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "#comparing to v65rc2 site\n", - "qa = qancode.QANCODE(rc_url=\"https://series5-test-master.demo.encodedcc.org/\", prod_url=\"https://v67rc1-master.demo.encodedcc.org/\")" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Checking response time\n", - "\n", - "*** item_type: /\n", - "------------------ https://v67rc1-master.demo.encodedcc.org// ------------------\n", - "\u001b[31mAverage es_time: 43.641 ± 5.736 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 1.228 ± 0.46 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 8.924 ± 2.705 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 63.508 ± 8.085 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage total time: 117.3 ± 14.63 ms (n=100)\u001b[0m\n", - "--------------- https://series5-test-master.demo.encodedcc.org// ---------------\n", - "\u001b[31mAverage es_time: 20.198 ± 2.972 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.458 ± 0.026 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 4.348 ± 1.255 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 28.376 ± 3.311 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage total time: 53.381 ± 6.612 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /search/?type=Experiment\n", - "------ https://v67rc1-master.demo.encodedcc.org//search/?type=Experiment -------\n", - "\u001b[31mAverage es_time: 30.541 ± 9.739 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 1.459 ± 0.73 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage render_time: 153.862 ± 16.943 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 214.367 ± 36.73 ms (n=100)\u001b[0m\n", - "\u001b[31mAverage total time: 400.229 ± 51.638 ms (n=100)\u001b[0m\n", - "--------- https://series5-test-master.demo.encodedcc.org//search/?type=Experiment ---------\n", - "\u001b[31mAverage es_time: 19.734 ± 5.574 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.478 ± 0.014 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 117.199 ± 13.892 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 162.229 ± 91.072 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage total time: 299.64 ± 94.824 ms (n=100)\u001b[0m\n", - "\n" - ] - } - ], - "source": [ - "qa.check_response_time(item_types=[\"/\",\"/search/?type=Experiment\"], n=100)" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Checking response time\n", - "\n", - "*** item_type: /search/?searchTerm=K562\n", - "------ https://v67rc1-master.demo.encodedcc.org//search/?searchTerm=K562 -------\n", - "\u001b[31mAverage es_time: 247.231 ± 30.918 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 1.578 ± 0.818 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 34.22 ± 8.142 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 300.096 ± 34.175 ms (n=100)\u001b[0m\n", - "\u001b[31mAverage total time: 583.125 ± 67.757 ms (n=100)\u001b[0m\n", - "--------- https://series5-test-master.demo.encodedcc.org//search/?searchTerm=K562 ---------\n", - "\u001b[31mAverage es_time: 120.489 ± 8.79 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.474 ± 0.017 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 20.121 ± 7.004 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 147.443 ± 12.09 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage total time: 288.526 ± 24.21 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /search/?searchTerm=DNA+binding\n", - "--------- https://v67rc1-master.demo.encodedcc.org//search/?searchTerm=DNA+binding ---------\n", - "\u001b[31mAverage es_time: 340.179 ± 63.128 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 1.469 ± 0.64 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 35.093 ± 7.38 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 398.883 ± 67.904 ms (n=100)\u001b[0m\n", - "\u001b[31mAverage total time: 775.624 ± 132.959 ms (n=100)\u001b[0m\n", - "--------- https://series5-test-master.demo.encodedcc.org//search/?searchTerm=DNA+binding ---------\n", - "\u001b[31mAverage es_time: 159.085 ± 12.011 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.47 ± 0.011 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 19.867 ± 4.934 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 187.435 ± 13.637 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage total time: 366.857 ± 27.199 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /search/?searchTerm=human\n", - "------ https://v67rc1-master.demo.encodedcc.org//search/?searchTerm=human ------\n", - "\u001b[31mAverage es_time: 243.735 ± 31.568 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 1.432 ± 0.65 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 35.856 ± 7.386 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 297.734 ± 34.868 ms (n=100)\u001b[0m\n", - "\u001b[31mAverage total time: 578.757 ± 68.995 ms (n=100)\u001b[0m\n", - "--------- https://series5-test-master.demo.encodedcc.org//search/?searchTerm=human ---------\n", - "\u001b[31mAverage es_time: 121.703 ± 7.659 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.47 ± 0.014 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 18.827 ± 3.831 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 147.28 ± 8.454 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage total time: 288.28 ± 16.851 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /search/?searchTerm=H3K36me3\n", - "---- https://v67rc1-master.demo.encodedcc.org//search/?searchTerm=H3K36me3 -----\n", - "\u001b[31mAverage es_time: 247.82 ± 22.696 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 1.355 ± 0.572 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 36.565 ± 6.737 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 303.303 ± 24.603 ms (n=100)\u001b[0m\n", - "\u001b[31mAverage total time: 589.044 ± 48.642 ms (n=100)\u001b[0m\n", - "--------- https://series5-test-master.demo.encodedcc.org//search/?searchTerm=H3K36me3 ---------\n", - "\u001b[31mAverage es_time: 121.9 ± 10.281 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.471 ± 0.013 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 19.539 ± 5.396 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 148.45 ± 12.007 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage total time: 290.36 ± 24.005 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /search/?searchTerm=CTCF\n", - "------ https://v67rc1-master.demo.encodedcc.org//search/?searchTerm=CTCF -------\n", - "\u001b[31mAverage es_time: 251.685 ± 30.658 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 1.401 ± 0.623 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 34.813 ± 6.195 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 304.38 ± 33.823 ms (n=100)\u001b[0m\n", - "\u001b[31mAverage total time: 592.279 ± 67.151 ms (n=100)\u001b[0m\n", - "--------- https://series5-test-master.demo.encodedcc.org//search/?searchTerm=CTCF ---------\n", - "\u001b[31mAverage es_time: 119.805 ± 8.078 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.47 ± 0.014 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 18.566 ± 5.193 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 144.951 ± 9.561 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage total time: 283.792 ± 19.158 ms (n=100)\u001b[0m\n", - "\n" - ] - } - ], - "source": [ - "qa.check_response_time(item_types=[\"/search/?searchTerm=K562\", \"/search/?searchTerm=DNA+binding\", \"/search/?searchTerm=human\", \"/search/?searchTerm=H3K36me3\", \"/search/?searchTerm=CTCF\"], n=100)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Checking response time\n", - "\n", - "*** item_type: /ENCSR255XZG/\n", - "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR255XZG/ ------------\n", - "\u001b[31mAverage es_time: 55.435 ± 8.724 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 1.645 ± 0.848 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 127.78 ± 8.627 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 307.997 ± 131.595 ms (n=100)\u001b[0m\n", - "\u001b[31mAverage total time: 492.857 ± 133.71 ms (n=100)\u001b[0m\n", - "--------- https://series5-test-master.demo.encodedcc.org//ENCSR255XZG/ ---------\n", - "\u001b[31mAverage es_time: 29.644 ± 6.814 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 1.342 ± 8.583 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 100.909 ± 5.225 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 219.994 ± 108.024 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage total time: 351.888 ± 112.01 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /ENCSR749ILN/\n", - "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR749ILN/ ------------\n", - "\u001b[31mAverage es_time: 48.427 ± 4.362 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 1.583 ± 0.674 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 34.947 ± 6.31 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 111.486 ± 9.197 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage total time: 196.443 ± 17.044 ms (n=100)\u001b[0m\n", - "--------- https://series5-test-master.demo.encodedcc.org//ENCSR749ILN/ ---------\n", - "\u001b[31mAverage es_time: 23.69 ± 3.865 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.475 ± 0.009 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 20.834 ± 4.134 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 59.105 ± 5.936 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage total time: 104.103 ± 11.713 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /ENCSR688GVV/\n", - "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR688GVV/ ------------\n", - "\u001b[31mAverage es_time: 55.845 ± 5.704 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 1.716 ± 0.834 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 70.328 ± 8.276 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 188.543 ± 75.737 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage total time: 316.432 ± 76.676 ms (n=100)\u001b[0m\n", - "--------- https://series5-test-master.demo.encodedcc.org//ENCSR688GVV/ ---------\n", - "\u001b[31mAverage es_time: 28.696 ± 3.626 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.481 ± 0.011 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 49.869 ± 4.111 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 113.044 ± 5.986 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage total time: 192.09 ± 11.714 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /ENCSR301HAG/\n", - "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR301HAG/ ------------\n", - "\u001b[31mAverage es_time: 46.166 ± 4.401 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 1.672 ± 0.801 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 19.887 ± 35.706 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 82.21 ± 36.266 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage total time: 149.935 ± 72.54 ms (n=100)\u001b[0m\n", - "--------- https://series5-test-master.demo.encodedcc.org//ENCSR301HAG/ ---------\n", - "\u001b[31mAverage es_time: 21.248 ± 2.508 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.48 ± 0.011 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 7.292 ± 2.202 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 34.026 ± 3.386 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage total time: 63.046 ± 6.685 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /ENCSR315NAC/\n", - "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR315NAC/ ------------\n", - "\u001b[31mAverage es_time: 53.566 ± 6.047 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 1.691 ± 1.269 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 58.099 ± 9.342 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 166.66 ± 90.6 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage total time: 280.016 ± 91.567 ms (n=100)\u001b[0m\n", - "--------- https://series5-test-master.demo.encodedcc.org//ENCSR315NAC/ ---------\n", - "\u001b[31mAverage es_time: 26.854 ± 2.471 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.477 ± 0.011 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 39.787 ± 4.783 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 101.165 ± 70.588 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage total time: 168.283 ± 71.092 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /ENCSR856JJB/\n", - "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR856JJB/ ------------\n", - "\u001b[31mAverage es_time: 53.123 ± 5.009 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 1.647 ± 0.911 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 52.026 ± 7.765 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 146.999 ± 10.763 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage total time: 253.796 ± 19.724 ms (n=100)\u001b[0m\n", - "--------- https://series5-test-master.demo.encodedcc.org//ENCSR856JJB/ ---------\n", - "\u001b[31mAverage es_time: 26.584 ± 3.355 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.476 ± 0.012 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 34.315 ± 4.205 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 91.577 ± 68.751 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage total time: 152.954 ± 68.975 ms (n=100)\u001b[0m\n", - "\n" - ] - } - ], - "source": [ - "qa.check_response_time(item_types=['/ENCSR255XZG/', '/ENCSR749ILN/', '/ENCSR688GVV/', '/ENCSR301HAG/','/ENCSR315NAC/', '/ENCSR856JJB/'], n=100)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Checking response time\n", - "\n", - "*** item_type: /ENCSR480OHP/\n", - "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR480OHP/ ------------\n", - "\u001b[31mAverage es_time: 49.248 ± 7.209 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 1.59 ± 0.959 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 35.152 ± 5.85 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 113.677 ± 11.161 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage total time: 199.667 ± 20.251 ms (n=100)\u001b[0m\n", - "--------- https://series5-test-master.demo.encodedcc.org//ENCSR480OHP/ ---------\n", - "\u001b[31mAverage es_time: 23.853 ± 4.252 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.473 ± 0.011 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 20.966 ± 3.594 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 66.685 ± 66.256 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage total time: 111.976 ± 66.883 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /ENCSR000EMB/\n", - "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR000EMB/ ------------\n", - "\u001b[31mAverage es_time: 48.658 ± 6.125 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 1.539 ± 0.753 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 53.329 ± 8.469 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 148.721 ± 76.744 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage total time: 252.247 ± 78.559 ms (n=100)\u001b[0m\n", - "--------- https://series5-test-master.demo.encodedcc.org//ENCSR000EMB/ ---------\n", - "\u001b[31mAverage es_time: 23.27 ± 2.562 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.474 ± 0.014 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 36.819 ± 4.667 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 85.352 ± 5.565 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage total time: 145.913 ± 11.049 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /ENCSR323QIP/\n", - "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR323QIP/ ------------\n", - "\u001b[31mAverage es_time: 59.852 ± 5.207 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 1.699 ± 1.042 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 149.958 ± 7.728 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 378.194 ± 200.862 ms (n=100)\u001b[0m\n", - "\u001b[31mAverage total time: 589.703 ± 201.571 ms (n=100)\u001b[0m\n", - "--------- https://series5-test-master.demo.encodedcc.org//ENCSR323QIP/ ---------\n", - "\u001b[31mAverage es_time: 32.175 ± 3.36 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.48 ± 0.01 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 122.909 ± 4.222 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 279.625 ± 129.661 ms (n=100)\u001b[0m\n", - "\u001b[31mAverage total time: 435.189 ± 131.305 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /ENCSR718AXQ/\n", - "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR718AXQ/ ------------\n", - "\u001b[31mAverage es_time: 49.831 ± 5.527 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 1.585 ± 0.908 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 25.462 ± 5.129 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 97.683 ± 8.911 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage total time: 174.561 ± 16.623 ms (n=100)\u001b[0m\n", - "--------- https://series5-test-master.demo.encodedcc.org//ENCSR718AXQ/ ---------\n", - "\u001b[31mAverage es_time: 24.651 ± 4.37 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.469 ± 0.015 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 13.743 ± 3.976 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 47.904 ± 5.918 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage total time: 86.766 ± 11.576 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /ENCSR165BGV/\n", - "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR165BGV/ ------------\n", - "\u001b[31mAverage es_time: 46.408 ± 5.364 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 1.582 ± 0.76 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 28.021 ± 5.87 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 96.965 ± 8.251 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage total time: 172.976 ± 15.625 ms (n=100)\u001b[0m\n", - "--------- https://series5-test-master.demo.encodedcc.org//ENCSR165BGV/ ---------\n", - "\u001b[31mAverage es_time: 21.831 ± 4.543 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.477 ± 0.012 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 16.355 ± 3.76 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 48.902 ± 6.487 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage total time: 87.565 ± 12.923 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /ENCSR384KAN/\n", - "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR384KAN/ ------------\n", - "\u001b[31mAverage es_time: 52.972 ± 5.834 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 1.706 ± 0.932 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 49.502 ± 7.612 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 144.096 ± 10.827 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage total time: 248.276 ± 21.148 ms (n=100)\u001b[0m\n", - "--------- https://series5-test-master.demo.encodedcc.org//ENCSR384KAN/ ---------\n", - "\u001b[31mAverage es_time: 26.172 ± 3.102 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.472 ± 0.01 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 32.696 ± 4.335 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 89.048 ± 65.064 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage total time: 148.388 ± 65.329 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /ENCSR330FXL/\n", - "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR330FXL/ ------------\n", - "\u001b[31mAverage es_time: 47.005 ± 10.829 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 1.339 ± 0.644 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 31.984 ± 5.899 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 104.802 ± 14.101 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage total time: 185.131 ± 25.715 ms (n=100)\u001b[0m\n", - "--------- https://series5-test-master.demo.encodedcc.org//ENCSR330FXL/ ---------\n", - "\u001b[31mAverage es_time: 21.27 ± 3.32 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.46 ± 0.01 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 19.611 ± 3.139 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 57.237 ± 32.377 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage total time: 98.577 ± 33.33 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /ENCSR825UNV/\n", - "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR825UNV/ ------------\n", - "\u001b[31mAverage es_time: 60.881 ± 6.646 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 1.917 ± 0.956 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage render_time: 176.879 ± 8.834 ms (n=100)\u001b[0m\n", - "\u001b[31mAverage wsgi_time: 412.39 ± 165.104 ms (n=100)\u001b[0m\n", - "\u001b[31mAverage total time: 652.068 ± 167.389 ms (n=100)\u001b[0m\n", - "--------- https://series5-test-master.demo.encodedcc.org//ENCSR825UNV/ ---------\n", - "\u001b[31mAverage es_time: 32.656 ± 4.562 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.485 ± 0.012 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 148.88 ± 3.654 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 362.182 ± 207.96 ms (n=100)\u001b[0m\n", - "\u001b[31mAverage total time: 544.202 ± 208.411 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /ENCSR089EOA/\n", - "------------ https://v67rc1-master.demo.encodedcc.org//ENCSR089EOA/ ------------\n" - ] - } - ], - "source": [ - "qa.check_response_time(item_types=['/ENCSR480OHP/','/ENCSR000EMB/','/ENCSR323QIP/','/ENCSR718AXQ/','/ENCSR165BGV/','/ENCSR384KAN/','/ENCSR330FXL/','/ENCSR825UNV/','/ENCSR089EOA/'], n=100)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "qa.check_response_time(item_types=['/ENCAB830JLB/','/ENCAB000BKR/','/ENCAB284TTY/','/ENCAB294YUD/','/ENCAB000AOC/','/ENCAB301QZF/','/ENCAB000ANM/','/ENCAB000ANU/','/ENCAB445KMF/','/ENCAB000BAY/'], n=100)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "qa.check_response_time(item_types=['/ENCBS787TFV/','/ENCBS676QAV/','/ENCBS996IWU/','/ENCBS913XJP/','/ENCBS565NTN/','/ENCBS896YZO/','/ENCBS280NYD/'], n=100)" - ] - }, - { - "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": "3.4.3" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} From bd792296e06def35484715a5dd5fae0d0a6a8383 Mon Sep 17 00:00:00 2001 From: Ben Hitz Date: Wed, 12 Dec 2018 09:44:51 -0800 Subject: [PATCH 3/5] sno-33 --- jupyter_notebooks/timing-tests-sno-33.ipynb | 2676 +++---------------- 1 file changed, 407 insertions(+), 2269 deletions(-) diff --git a/jupyter_notebooks/timing-tests-sno-33.ipynb b/jupyter_notebooks/timing-tests-sno-33.ipynb index 7c080d82..ac219fe1 100644 --- a/jupyter_notebooks/timing-tests-sno-33.ipynb +++ b/jupyter_notebooks/timing-tests-sno-33.ipynb @@ -3,7 +3,9 @@ { "cell_type": "code", "execution_count": 1, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "%load_ext autoreload" @@ -12,7 +14,9 @@ { "cell_type": "code", "execution_count": 2, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "%autoreload\n", @@ -26,18 +30,20 @@ { "cell_type": "code", "execution_count": 3, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "#compare any two encoded instances here\n", - "qa = qancode.QANCODE(rc_url=\"https://test.encodedcc.org\", prod_url='https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org/')" + "qa = qancode.QANCODE(rc_url=\"https://test.encodedcc.org\", prod_url='https://sno68-on-dev.demo.encodedcc.org/')" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { - "scrolled": false + "scrolled": true }, "outputs": [ { @@ -47,33 +53,33 @@ "Checking response time\n", "\n", "*** item_type: /\n", - "---------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org// ----------\n", - "\u001b[36mAverage es_time: 0.733 ± 0.051 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.37 ± 0.032 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 3.005 ± 0.283 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 7.108 ± 0.454 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 11.216 ± 0.764 ms (n=50)\u001b[0m\n", + "------------------ https://sno68-on-dev.demo.encodedcc.org// -------------------\n", + "\u001b[36mAverage es_time: 1.437 ± 0.354 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.448 ± 0.041 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 25.741 ± 89.396 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 30.986 ± 89.729 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 58.612 ± 179.157 ms (n=50)\u001b[0m\n", "------------------------- https://test.encodedcc.org/ --------------------------\n", - "\u001b[31mAverage es_time: 13.38 ± 3.615 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.421 ± 0.017 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 3.946 ± 1.37 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 21.032 ± 4.176 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 38.779 ± 8.338 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage es_time: 2.303 ± 0.099 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.458 ± 0.041 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 5.768 ± 3.2 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 11.952 ± 3.236 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 20.48 ± 6.469 ms (n=50)\u001b[0m\n", "\n", "\n", "*** item_type: /search/?type=Experiment\n", - "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//search/?type=Experiment ---------\n", - "\u001b[31mAverage es_time: 14.774 ± 1.608 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.473 ± 0.013 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 110.853 ± 10.258 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 140.347 ± 11.087 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage total time: 266.447 ± 21.867 ms (n=50)\u001b[0m\n", + "------- https://sno68-on-dev.demo.encodedcc.org//search/?type=Experiment -------\n", + "\u001b[31mAverage es_time: 14.541 ± 5.102 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.502 ± 0.017 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 128.394 ± 23.567 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 159.202 ± 25.75 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 302.639 ± 51.557 ms (n=50)\u001b[0m\n", "-------------- https://test.encodedcc.org/search/?type=Experiment --------------\n", - "\u001b[31mAverage es_time: 22.591 ± 6.109 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.473 ± 0.014 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 110.62 ± 15.968 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 148.084 ± 18.568 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage total time: 281.768 ± 37.016 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage es_time: 27.5 ± 14.652 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.557 ± 0.036 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 125.738 ± 14.438 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 170.586 ± 23.562 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 324.382 ± 47.143 ms (n=50)\u001b[0m\n", "\n" ] } @@ -86,226 +92,14 @@ "cell_type": "code", "execution_count": 5, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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https://es-frontend2.demo.encodedcc.org/https://es-frontend2.demo.encodedcc.org/search/?type=Experimenthttps://test.encodedcc.org/https://test.encodedcc.org/search/?type=Experiment
es_time_mean16.25625.66813.31324.365
es_time_std2.5876.9293.4757.398
es_time_N50.00050.00050.00050.000
queue_time_mean1.1191.0680.4350.478
queue_time_std0.2740.4280.0320.013
queue_time_N50.00050.00050.00050.000
render_time_mean10.741150.6304.018108.651
render_time_std3.37414.4791.52714.653
render_time_N50.00050.00050.00050.000
wsgi_time_mean37.187202.89920.967147.731
wsgi_time_std5.29817.4184.04716.097
wsgi_time_N50.00050.00050.00050.000
total_mean65.303380.26438.734281.225
total_std9.44734.5088.12632.119
total_N50.00050.00050.00050.000
\n", - "
" - ], - "text/plain": [ - " https://es-frontend2.demo.encodedcc.org/ \\\n", - "es_time_mean 16.256 \n", - "es_time_std 2.587 \n", - "es_time_N 50.000 \n", - "queue_time_mean 1.119 \n", - "queue_time_std 0.274 \n", - "queue_time_N 50.000 \n", - "render_time_mean 10.741 \n", - "render_time_std 3.374 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 37.187 \n", - "wsgi_time_std 5.298 \n", - "wsgi_time_N 50.000 \n", - "total_mean 65.303 \n", - "total_std 9.447 \n", - "total_N 50.000 \n", - "\n", - " https://es-frontend2.demo.encodedcc.org/search/?type=Experiment \\\n", - "es_time_mean 25.668 \n", - "es_time_std 6.929 \n", - "es_time_N 50.000 \n", - "queue_time_mean 1.068 \n", - "queue_time_std 0.428 \n", - "queue_time_N 50.000 \n", - "render_time_mean 150.630 \n", - "render_time_std 14.479 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 202.899 \n", - "wsgi_time_std 17.418 \n", - "wsgi_time_N 50.000 \n", - "total_mean 380.264 \n", - "total_std 34.508 \n", - "total_N 50.000 \n", - "\n", - " https://test.encodedcc.org/ \\\n", - "es_time_mean 13.313 \n", - "es_time_std 3.475 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.435 \n", - "queue_time_std 0.032 \n", - "queue_time_N 50.000 \n", - "render_time_mean 4.018 \n", - "render_time_std 1.527 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 20.967 \n", - "wsgi_time_std 4.047 \n", - "wsgi_time_N 50.000 \n", - "total_mean 38.734 \n", - "total_std 8.126 \n", - "total_N 50.000 \n", - "\n", - " https://test.encodedcc.org/search/?type=Experiment \n", - "es_time_mean 24.365 \n", - "es_time_std 7.398 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.478 \n", - "queue_time_std 0.013 \n", - "queue_time_N 50.000 \n", - "render_time_mean 108.651 \n", - "render_time_std 14.653 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 147.731 \n", - "wsgi_time_std 16.097 \n", - "wsgi_time_N 50.000 \n", - "total_mean 281.225 \n", - "total_std 32.119 \n", - "total_N 50.000 " - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "res" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": { "scrolled": true }, @@ -317,489 +111,80 @@ "Checking response time\n", "\n", "*** item_type: /search/?searchTerm=K562\n", - "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//search/?searchTerm=K562 ---------\n", - "\u001b[31mAverage es_time: 157.582 ± 3.94 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.482 ± 0.009 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 19.609 ± 7.719 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 183.631 ± 9.635 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage total time: 361.305 ± 19.223 ms (n=50)\u001b[0m\n", + "------- https://sno68-on-dev.demo.encodedcc.org//search/?searchTerm=K562 -------\n", + "\u001b[31mAverage es_time: 155.442 ± 74.564 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.524 ± 0.028 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 22.779 ± 7.123 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 186.839 ± 80.049 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 365.584 ± 158.176 ms (n=50)\u001b[0m\n", "-------------- https://test.encodedcc.org/search/?searchTerm=K562 --------------\n", - "\u001b[31mAverage es_time: 190.879 ± 12.549 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.466 ± 0.011 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 19.467 ± 7.491 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 216.898 ± 14.289 ms (n=50)\u001b[0m\n", - "\u001b[31mAverage total time: 427.71 ± 28.647 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage es_time: 255.756 ± 77.864 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.513 ± 0.026 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 26.322 ± 8.186 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 290.326 ± 80.959 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage total time: 572.917 ± 161.66 ms (n=50)\u001b[0m\n", "\n", "\n", "*** item_type: /search/?searchTerm=DNA+binding\n", - "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//search/?searchTerm=DNA+binding ---------\n", - "\u001b[31mAverage es_time: 263.99 ± 4.486 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.483 ± 0.009 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 21.016 ± 5.636 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 293.514 ± 7.857 ms (n=50)\u001b[0m\n", - "\u001b[31mAverage total time: 579.003 ± 15.653 ms (n=50)\u001b[0m\n", + "--------- https://sno68-on-dev.demo.encodedcc.org//search/?searchTerm=DNA+binding ---------\n", + "\u001b[31mAverage es_time: 254.752 ± 75.15 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.526 ± 0.028 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 26.921 ± 7.768 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 294.292 ± 78.654 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage total time: 576.491 ± 156.045 ms (n=50)\u001b[0m\n", "---------- https://test.encodedcc.org/search/?searchTerm=DNA+binding -----------\n", - "\u001b[31mAverage es_time: 281.067 ± 12.781 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.474 ± 0.023 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 20.123 ± 5.02 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 309.671 ± 14.141 ms (n=50)\u001b[0m\n", - "\u001b[31mAverage total time: 611.335 ± 28.274 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage es_time: 367.404 ± 76.163 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.527 ± 0.021 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 29.935 ± 9.041 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage wsgi_time: 410.561 ± 79.709 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage total time: 808.427 ± 158.638 ms (n=50)\u001b[0m\n", "\n", "\n", "*** item_type: /search/?searchTerm=human\n", - "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//search/?searchTerm=human ---------\n", - "\u001b[31mAverage es_time: 156.92 ± 3.856 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.48 ± 0.008 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 19.892 ± 4.162 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 183.057 ± 5.94 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage total time: 360.349 ± 11.868 ms (n=50)\u001b[0m\n", + "------ https://sno68-on-dev.demo.encodedcc.org//search/?searchTerm=human -------\n", + "\u001b[31mAverage es_time: 148.868 ± 45.529 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.533 ± 0.032 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 23.33 ± 6.177 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 179.455 ± 46.863 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 352.186 ± 93.566 ms (n=50)\u001b[0m\n", "------------- https://test.encodedcc.org/search/?searchTerm=human --------------\n", - "\u001b[31mAverage es_time: 192.853 ± 9.624 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.466 ± 0.009 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 22.357 ± 6.606 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 221.441 ± 11.136 ms (n=50)\u001b[0m\n", - "\u001b[31mAverage total time: 437.116 ± 22.276 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage es_time: 257.445 ± 38.647 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.518 ± 0.022 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 27.964 ± 7.933 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 292.925 ± 39.979 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage total time: 578.852 ± 79.926 ms (n=50)\u001b[0m\n", "\n", "\n", "*** item_type: /search/?searchTerm=H3K36me3\n", - "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//search/?searchTerm=H3K36me3 ---------\n", - "\u001b[31mAverage es_time: 159.429 ± 3.633 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.483 ± 0.007 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 22.086 ± 6.045 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 188.201 ± 7.418 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage total time: 370.199 ± 14.642 ms (n=50)\u001b[0m\n", + "----- https://sno68-on-dev.demo.encodedcc.org//search/?searchTerm=H3K36me3 -----\n", + "\u001b[31mAverage es_time: 146.904 ± 24.684 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.523 ± 0.023 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 30.099 ± 7.767 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 185.015 ± 26.124 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 362.541 ± 52.151 ms (n=50)\u001b[0m\n", "------------ https://test.encodedcc.org/search/?searchTerm=H3K36me3 ------------\n", - "\u001b[31mAverage es_time: 190.384 ± 9.842 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.466 ± 0.015 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 20.169 ± 4.732 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 217.075 ± 11.681 ms (n=50)\u001b[0m\n", - "\u001b[31mAverage total time: 428.094 ± 23.346 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage es_time: 246.258 ± 32.593 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.525 ± 0.028 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 30.388 ± 8.277 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 285.043 ± 34.345 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage total time: 562.213 ± 68.457 ms (n=50)\u001b[0m\n", "\n", "\n", "*** item_type: /search/?searchTerm=CTCF\n", - "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//search/?searchTerm=CTCF ---------\n", - "\u001b[31mAverage es_time: 158.013 ± 3.384 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.487 ± 0.011 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 17.455 ± 3.967 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 181.733 ± 4.878 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage total time: 357.688 ± 9.764 ms (n=50)\u001b[0m\n", + "------- https://sno68-on-dev.demo.encodedcc.org//search/?searchTerm=CTCF -------\n", + "\u001b[31mAverage es_time: 144.103 ± 19.595 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.512 ± 0.007 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 20.148 ± 4.698 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 171.377 ± 19.931 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 336.14 ± 39.722 ms (n=50)\u001b[0m\n", "-------------- https://test.encodedcc.org/search/?searchTerm=CTCF --------------\n", - "\u001b[31mAverage es_time: 190.518 ± 10.276 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.48 ± 0.021 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 18.016 ± 4.338 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 214.748 ± 10.204 ms (n=50)\u001b[0m\n", - "\u001b[31mAverage total time: 423.763 ± 20.429 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage es_time: 252.529 ± 36.873 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.509 ± 0.023 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 23.091 ± 5.945 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 283.187 ± 37.499 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage total time: 559.317 ± 74.672 ms (n=50)\u001b[0m\n", "\n" ] - }, - { - "data": { - "text/html": [ - "
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https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//search/?searchTerm=CTCFhttps://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//search/?searchTerm=DNA+bindinghttps://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//search/?searchTerm=H3K36me3https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//search/?searchTerm=K562https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//search/?searchTerm=humanhttps://test.encodedcc.org/search/?searchTerm=CTCFhttps://test.encodedcc.org/search/?searchTerm=DNA+bindinghttps://test.encodedcc.org/search/?searchTerm=H3K36me3https://test.encodedcc.org/search/?searchTerm=K562https://test.encodedcc.org/search/?searchTerm=human
es_time_mean158.013263.990159.429157.582156.920190.518281.067190.384190.879192.853
es_time_std3.3844.4863.6333.9403.85610.27612.7819.84212.5499.624
es_time_N50.00050.00050.00050.00050.00050.00050.00050.00050.00050.000
queue_time_mean0.4870.4830.4830.4820.4800.4800.4740.4660.4660.466
queue_time_std0.0110.0090.0070.0090.0080.0210.0230.0150.0110.009
queue_time_N50.00050.00050.00050.00050.00050.00050.00050.00050.00050.000
render_time_mean17.45521.01622.08619.60919.89218.01620.12320.16919.46722.357
render_time_std3.9675.6366.0457.7194.1624.3385.0204.7327.4916.606
render_time_N50.00050.00050.00050.00050.00050.00050.00050.00050.00050.000
wsgi_time_mean181.733293.514188.201183.631183.057214.748309.671217.075216.898221.441
wsgi_time_std4.8787.8577.4189.6355.94010.20414.14111.68114.28911.136
wsgi_time_N50.00050.00050.00050.00050.00050.00050.00050.00050.00050.000
total_mean357.688579.003370.199361.305360.349423.763611.335428.094427.710437.116
total_std9.76415.65314.64219.22311.86820.42928.27423.34628.64722.276
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" - ], - "text/plain": [ - " https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//search/?searchTerm=CTCF \\\n", - "es_time_mean 158.013 \n", - "es_time_std 3.384 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.487 \n", - "queue_time_std 0.011 \n", - "queue_time_N 50.000 \n", - "render_time_mean 17.455 \n", - "render_time_std 3.967 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 181.733 \n", - "wsgi_time_std 4.878 \n", - "wsgi_time_N 50.000 \n", - "total_mean 357.688 \n", - "total_std 9.764 \n", - "total_N 50.000 \n", - "\n", - " https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//search/?searchTerm=DNA+binding \\\n", - "es_time_mean 263.990 \n", - "es_time_std 4.486 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.483 \n", - "queue_time_std 0.009 \n", - "queue_time_N 50.000 \n", - "render_time_mean 21.016 \n", - "render_time_std 5.636 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 293.514 \n", - "wsgi_time_std 7.857 \n", - "wsgi_time_N 50.000 \n", - "total_mean 579.003 \n", - "total_std 15.653 \n", - "total_N 50.000 \n", - "\n", - " https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//search/?searchTerm=H3K36me3 \\\n", - "es_time_mean 159.429 \n", - "es_time_std 3.633 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.483 \n", - "queue_time_std 0.007 \n", - "queue_time_N 50.000 \n", - "render_time_mean 22.086 \n", - "render_time_std 6.045 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 188.201 \n", - "wsgi_time_std 7.418 \n", - "wsgi_time_N 50.000 \n", - "total_mean 370.199 \n", - "total_std 14.642 \n", - "total_N 50.000 \n", - "\n", - " https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//search/?searchTerm=K562 \\\n", - "es_time_mean 157.582 \n", - "es_time_std 3.940 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.482 \n", - "queue_time_std 0.009 \n", - "queue_time_N 50.000 \n", - "render_time_mean 19.609 \n", - "render_time_std 7.719 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 183.631 \n", - "wsgi_time_std 9.635 \n", - "wsgi_time_N 50.000 \n", - "total_mean 361.305 \n", - "total_std 19.223 \n", - "total_N 50.000 \n", - "\n", - " https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//search/?searchTerm=human \\\n", - "es_time_mean 156.920 \n", - "es_time_std 3.856 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.480 \n", - "queue_time_std 0.008 \n", - "queue_time_N 50.000 \n", - "render_time_mean 19.892 \n", - "render_time_std 4.162 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 183.057 \n", - "wsgi_time_std 5.940 \n", - "wsgi_time_N 50.000 \n", - "total_mean 360.349 \n", - "total_std 11.868 \n", - "total_N 50.000 \n", - "\n", - " https://test.encodedcc.org/search/?searchTerm=CTCF \\\n", - "es_time_mean 190.518 \n", - "es_time_std 10.276 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.480 \n", - "queue_time_std 0.021 \n", - "queue_time_N 50.000 \n", - "render_time_mean 18.016 \n", - "render_time_std 4.338 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 214.748 \n", - "wsgi_time_std 10.204 \n", - "wsgi_time_N 50.000 \n", - "total_mean 423.763 \n", - "total_std 20.429 \n", - "total_N 50.000 \n", - "\n", - " https://test.encodedcc.org/search/?searchTerm=DNA+binding \\\n", - "es_time_mean 281.067 \n", - "es_time_std 12.781 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.474 \n", - "queue_time_std 0.023 \n", - "queue_time_N 50.000 \n", - "render_time_mean 20.123 \n", - "render_time_std 5.020 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 309.671 \n", - "wsgi_time_std 14.141 \n", - "wsgi_time_N 50.000 \n", - "total_mean 611.335 \n", - "total_std 28.274 \n", - "total_N 50.000 \n", - "\n", - " https://test.encodedcc.org/search/?searchTerm=H3K36me3 \\\n", - "es_time_mean 190.384 \n", - "es_time_std 9.842 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.466 \n", - "queue_time_std 0.015 \n", - "queue_time_N 50.000 \n", - "render_time_mean 20.169 \n", - "render_time_std 4.732 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 217.075 \n", - "wsgi_time_std 11.681 \n", - "wsgi_time_N 50.000 \n", - "total_mean 428.094 \n", - "total_std 23.346 \n", - "total_N 50.000 \n", - "\n", - " https://test.encodedcc.org/search/?searchTerm=K562 \\\n", - "es_time_mean 190.879 \n", - "es_time_std 12.549 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.466 \n", - "queue_time_std 0.011 \n", - "queue_time_N 50.000 \n", - "render_time_mean 19.467 \n", - "render_time_std 7.491 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 216.898 \n", - "wsgi_time_std 14.289 \n", - "wsgi_time_N 50.000 \n", - "total_mean 427.710 \n", - "total_std 28.647 \n", - "total_N 50.000 \n", - "\n", - " https://test.encodedcc.org/search/?searchTerm=human \n", - "es_time_mean 192.853 \n", - "es_time_std 9.624 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.466 \n", - "queue_time_std 0.009 \n", - "queue_time_N 50.000 \n", - "render_time_mean 22.357 \n", - "render_time_std 6.606 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 221.441 \n", - "wsgi_time_std 11.136 \n", - "wsgi_time_N 50.000 \n", - "total_mean 437.116 \n", - "total_std 22.276 \n", - "total_N 50.000 " - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" } ], "source": [ @@ -808,7 +193,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": { "scrolled": false }, @@ -820,570 +205,95 @@ "Checking response time\n", "\n", "*** item_type: /ENCSR255XZG/\n", - "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR255XZG/ ---------\n", - "\u001b[36mAverage es_time: 3.427 ± 0.14 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.473 ± 0.011 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 102.627 ± 6.713 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 229.562 ± 170.299 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage total time: 336.089 ± 169.153 ms (n=50)\u001b[0m\n", + "------------ https://sno68-on-dev.demo.encodedcc.org//ENCSR255XZG/ -------------\n", + "\u001b[36mAverage es_time: 4.903 ± 2.332 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.48 ± 0.01 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 110.471 ± 7.062 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 221.761 ± 137.386 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 337.615 ± 137.271 ms (n=50)\u001b[0m\n", "------------------- https://test.encodedcc.org/ENCSR255XZG/ --------------------\n", - "\u001b[31mAverage es_time: 22.524 ± 5.369 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.484 ± 0.012 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 101.847 ± 4.433 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 222.274 ± 123.298 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage total time: 347.13 ± 123.42 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage es_time: 13.03 ± 0.324 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.514 ± 0.042 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 112.099 ± 7.44 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 210.327 ± 58.171 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 335.971 ± 60.629 ms (n=50)\u001b[0m\n", "\n", "\n", "*** item_type: /ENCSR749ILN/\n", - "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR749ILN/ ---------\n", - "\u001b[36mAverage es_time: 1.969 ± 0.707 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.458 ± 0.012 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 21.579 ± 4.237 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 37.883 ± 4.18 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 61.889 ± 8.476 ms (n=50)\u001b[0m\n", + "------------ https://sno68-on-dev.demo.encodedcc.org//ENCSR749ILN/ -------------\n", + "\u001b[36mAverage es_time: 2.916 ± 1.82 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.471 ± 0.013 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 32.94 ± 5.569 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 54.267 ± 6.194 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 90.593 ± 12.348 ms (n=50)\u001b[0m\n", "------------------- https://test.encodedcc.org/ENCSR749ILN/ --------------------\n", - "\u001b[31mAverage es_time: 16.634 ± 2.976 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.482 ± 0.017 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 21.232 ± 4.268 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 52.689 ± 4.831 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 91.036 ± 9.701 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage es_time: 6.436 ± 1.997 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.494 ± 0.043 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 33.159 ± 5.633 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 58.507 ± 6.561 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 98.595 ± 12.807 ms (n=50)\u001b[0m\n", "\n", "\n", "*** item_type: /ENCSR688GVV/\n", - "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR688GVV/ ---------\n", - "\u001b[36mAverage es_time: 3.353 ± 0.049 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.472 ± 0.008 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 50.326 ± 4.796 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 87.704 ± 4.724 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 141.855 ± 9.481 ms (n=50)\u001b[0m\n", + "------------ https://sno68-on-dev.demo.encodedcc.org//ENCSR688GVV/ -------------\n", + "\u001b[36mAverage es_time: 4.76 ± 1.849 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.485 ± 0.012 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 67.924 ± 4.594 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 116.541 ± 5.01 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 189.71 ± 9.724 ms (n=50)\u001b[0m\n", "------------------- https://test.encodedcc.org/ENCSR688GVV/ --------------------\n", - "\u001b[31mAverage es_time: 20.651 ± 4.494 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.481 ± 0.014 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 50.141 ± 5.997 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 104.909 ± 7.084 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage total time: 176.182 ± 14.266 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage es_time: 11.618 ± 2.389 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.478 ± 0.036 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 65.276 ± 5.28 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 133.771 ± 92.157 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 211.144 ± 91.676 ms (n=50)\u001b[0m\n", "\n", "\n", "*** item_type: /ENCSR301HAG/\n", - "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR301HAG/ ---------\n", - "\u001b[36mAverage es_time: 1.188 ± 0.037 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.472 ± 0.011 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 9.058 ± 4.089 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 15.581 ± 4.08 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 26.298 ± 8.169 ms (n=50)\u001b[0m\n", + "------------ https://sno68-on-dev.demo.encodedcc.org//ENCSR301HAG/ -------------\n", + "\u001b[36mAverage es_time: 1.511 ± 0.058 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.482 ± 0.015 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 10.035 ± 3.754 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 17.406 ± 3.978 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 29.435 ± 7.687 ms (n=50)\u001b[0m\n", "------------------- https://test.encodedcc.org/ENCSR301HAG/ --------------------\n", - "\u001b[31mAverage es_time: 15.776 ± 4.047 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.476 ± 0.011 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 7.52 ± 1.928 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 28.649 ± 4.635 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 52.42 ± 9.221 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage es_time: 3.328 ± 0.766 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.514 ± 0.042 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 11.034 ± 5.567 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 20.235 ± 6.023 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 35.111 ± 11.654 ms (n=50)\u001b[0m\n", "\n", "\n", "*** item_type: /ENCSR315NAC/\n", - "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR315NAC/ ---------\n", - "\u001b[36mAverage es_time: 2.861 ± 0.073 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.469 ± 0.012 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 40.14 ± 5.249 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 98.165 ± 138.118 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 141.635 ± 138.012 ms (n=50)\u001b[0m\n", + "------------ https://sno68-on-dev.demo.encodedcc.org//ENCSR315NAC/ -------------\n", + "\u001b[36mAverage es_time: 3.931 ± 1.808 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.478 ± 0.011 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 51.032 ± 6.394 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 87.364 ± 5.965 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 142.805 ± 12.115 ms (n=50)\u001b[0m\n", "------------------- https://test.encodedcc.org/ENCSR315NAC/ --------------------\n", - "\u001b[31mAverage es_time: 20.143 ± 4.434 ms (n=50)\u001b[0m\n", - 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es_time_std0.1400.0370.0730.0490.7070.0575.3694.0474.4344.4942.9763.729
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queue_time_mean0.4730.4720.4690.4720.4580.4690.4840.4760.4790.4810.4820.481
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render_time_mean102.6279.05840.14050.32621.57935.655101.8477.52040.89450.14121.23234.810
render_time_std6.7134.0895.2494.7964.2374.1304.4331.9285.6965.9974.2684.648
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wsgi_time_mean229.56215.58198.16587.70437.88362.074222.27428.64988.257104.90952.68977.726
wsgi_time_std170.2994.080138.1184.7244.1804.346123.2984.6356.4847.0844.8315.414
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total_mean336.08926.298141.635141.85561.889100.947347.13052.420149.773176.18291.036132.439
total_std169.1538.169138.0129.4818.4768.435123.4209.22113.09814.2669.70110.807
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"es_time_mean 20.143 \n", - "es_time_std 4.434 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.479 \n", - "queue_time_std 0.014 \n", - "queue_time_N 50.000 \n", - "render_time_mean 40.894 \n", - "render_time_std 5.696 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 88.257 \n", - "wsgi_time_std 6.484 \n", - "wsgi_time_N 50.000 \n", - "total_mean 149.773 \n", - "total_std 13.098 \n", - "total_N 50.000 \n", - "\n", - " https://test.encodedcc.org/ENCSR688GVV/ \\\n", - "es_time_mean 20.651 \n", - "es_time_std 4.494 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.481 \n", - "queue_time_std 0.014 \n", - "queue_time_N 50.000 \n", - "render_time_mean 50.141 \n", - "render_time_std 5.997 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 104.909 \n", - "wsgi_time_std 7.084 \n", - "wsgi_time_N 50.000 \n", - "total_mean 176.182 \n", - "total_std 14.266 \n", - "total_N 50.000 \n", - "\n", - " https://test.encodedcc.org/ENCSR749ILN/ \\\n", - "es_time_mean 16.634 \n", - "es_time_std 2.976 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.482 \n", - "queue_time_std 0.017 \n", - "queue_time_N 50.000 \n", - "render_time_mean 21.232 \n", - "render_time_std 4.268 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 52.689 \n", - "wsgi_time_std 4.831 \n", - "wsgi_time_N 50.000 \n", - "total_mean 91.036 \n", - "total_std 9.701 \n", - "total_N 50.000 \n", - "\n", - " https://test.encodedcc.org/ENCSR856JJB/ \n", - "es_time_mean 19.421 \n", - "es_time_std 3.729 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.481 \n", - "queue_time_std 0.010 \n", - "queue_time_N 50.000 \n", - "render_time_mean 34.810 \n", - "render_time_std 4.648 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 77.726 \n", - "wsgi_time_std 5.414 \n", - "wsgi_time_N 50.000 \n", - "total_mean 132.439 \n", - "total_std 10.807 \n", - "total_N 50.000 " - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" } ], "source": [ @@ -1404,570 +314,95 @@ "Checking response time\n", "\n", "*** item_type: /experiments/ENCSR255XZG/\n", - "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//experiments/ENCSR255XZG/ ---------\n", - "\u001b[36mAverage es_time: 3.465 ± 0.14 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.469 ± 0.012 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 102.812 ± 2.761 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 204.397 ± 119.778 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage total time: 311.142 ± 120.439 ms (n=50)\u001b[0m\n", + "------ https://sno68-on-dev.demo.encodedcc.org//experiments/ENCSR255XZG/ -------\n", + "\u001b[36mAverage es_time: 4.022 ± 0.267 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.51 ± 0.02 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 109.33 ± 5.735 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 192.425 ± 5.473 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 306.286 ± 11.048 ms (n=50)\u001b[0m\n", "------------- https://test.encodedcc.org/experiments/ENCSR255XZG/ --------------\n", - "\u001b[31mAverage es_time: 21.519 ± 2.996 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.49 ± 0.02 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 104.027 ± 2.903 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 227.953 ± 136.849 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage total time: 353.989 ± 137.183 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage es_time: 13.514 ± 3.218 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.562 ± 0.021 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 109.987 ± 5.737 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 220.592 ± 88.486 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 344.655 ± 91.32 ms (n=50)\u001b[0m\n", "\n", "\n", "*** item_type: /experiments/ENCSR749ILN/\n", - "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//experiments/ENCSR749ILN/ ---------\n", - "\u001b[36mAverage es_time: 1.812 ± 0.057 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.428 ± 0.014 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 20.299 ± 4.004 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 36.672 ± 4.513 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 59.211 ± 8.474 ms (n=50)\u001b[0m\n", + "------ https://sno68-on-dev.demo.encodedcc.org//experiments/ENCSR749ILN/ -------\n", + "\u001b[36mAverage es_time: 2.493 ± 0.072 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.472 ± 0.021 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 29.516 ± 6.184 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 51.005 ± 6.574 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 83.487 ± 12.711 ms (n=50)\u001b[0m\n", "------------- https://test.encodedcc.org/experiments/ENCSR749ILN/ --------------\n", - "\u001b[31mAverage es_time: 16.351 ± 3.407 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.492 ± 0.026 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 20.522 ± 3.501 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 51.948 ± 5.347 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 89.314 ± 9.98 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage es_time: 6.395 ± 2.8 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.516 ± 0.029 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 28.675 ± 6.21 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 55.222 ± 6.933 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 90.809 ± 13.484 ms (n=50)\u001b[0m\n", "\n", "\n", "*** item_type: /experiments/ENCSR688GVV/\n", - "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//experiments/ENCSR688GVV/ ---------\n", - "\u001b[36mAverage es_time: 3.392 ± 0.15 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.458 ± 0.011 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 44.491 ± 4.214 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 95.576 ± 95.782 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 143.916 ± 97.697 ms (n=50)\u001b[0m\n", + "------ https://sno68-on-dev.demo.encodedcc.org//experiments/ENCSR688GVV/ -------\n", + "\u001b[36mAverage es_time: 4.425 ± 0.103 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.491 ± 0.02 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 61.885 ± 5.524 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 119.652 ± 61.652 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 186.454 ± 62.837 ms (n=50)\u001b[0m\n", "------------- https://test.encodedcc.org/experiments/ENCSR688GVV/ --------------\n", - "\u001b[31mAverage es_time: 20.404 ± 3.93 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.499 ± 0.021 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 46.417 ± 4.955 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 101.581 ± 6.566 ms (n=50)\u001b[0m\n", - "\u001b[33mAverage total time: 168.9 ± 12.805 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage es_time: 11.513 ± 0.2 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.553 ± 0.021 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 62.544 ± 5.625 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 128.16 ± 60.801 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 202.77 ± 62.738 ms (n=50)\u001b[0m\n", "\n", "\n", "*** item_type: /experiments/ENCSR301HAG/\n", - "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//experiments/ENCSR301HAG/ ---------\n", - "\u001b[36mAverage es_time: 1.191 ± 0.033 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.46 ± 0.015 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 9.183 ± 4.054 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 15.75 ± 4.066 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 26.584 ± 8.117 ms (n=50)\u001b[0m\n", + "------ https://sno68-on-dev.demo.encodedcc.org//experiments/ENCSR301HAG/ -------\n", + "\u001b[36mAverage es_time: 1.459 ± 0.052 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.471 ± 0.02 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 11.334 ± 5.182 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 18.492 ± 5.26 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 31.756 ± 10.421 ms (n=50)\u001b[0m\n", "------------- https://test.encodedcc.org/experiments/ENCSR301HAG/ --------------\n", - "\u001b[31mAverage es_time: 15.04 ± 6.581 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.411 ± 0.027 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 6.68 ± 1.519 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 27.058 ± 6.549 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 49.189 ± 13.122 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage es_time: 3.046 ± 0.104 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.47 ± 0.028 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 10.735 ± 4.49 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 19.373 ± 4.532 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 33.625 ± 9.036 ms (n=50)\u001b[0m\n", "\n", "\n", "*** item_type: /experiments/ENCSR315NAC/\n", - "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//experiments/ENCSR315NAC/ ---------\n", - "\u001b[36mAverage es_time: 2.872 ± 0.088 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.448 ± 0.012 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 35.799 ± 4.084 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 80.271 ± 101.842 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 119.391 ± 101.667 ms (n=50)\u001b[0m\n", + "------ https://sno68-on-dev.demo.encodedcc.org//experiments/ENCSR315NAC/ -------\n", + "\u001b[36mAverage es_time: 3.677 ± 0.1 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.487 ± 0.015 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 46.814 ± 5.759 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 93.227 ± 69.586 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 144.206 ± 69.243 ms (n=50)\u001b[0m\n", "------------- https://test.encodedcc.org/experiments/ENCSR315NAC/ --------------\n", - "\u001b[31mAverage es_time: 19.0 ± 4.062 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.464 ± 0.017 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 36.909 ± 4.456 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 83.347 ± 6.864 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 139.721 ± 12.583 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage es_time: 8.833 ± 0.248 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.528 ± 0.029 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 47.254 ± 5.473 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 89.393 ± 5.686 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 146.008 ± 11.104 ms (n=50)\u001b[0m\n", "\n", "\n", "*** item_type: /experiments/ENCSR856JJB/\n", - "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//experiments/ENCSR856JJB/ ---------\n", - "\u001b[36mAverage es_time: 2.744 ± 0.066 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.439 ± 0.022 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 31.81 ± 5.409 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 58.038 ± 5.628 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 93.031 ± 11.021 ms (n=50)\u001b[0m\n", + "------ https://sno68-on-dev.demo.encodedcc.org//experiments/ENCSR856JJB/ -------\n", + "\u001b[36mAverage es_time: 3.378 ± 0.077 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.483 ± 0.022 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 39.693 ± 5.439 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 71.004 ± 5.595 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 114.558 ± 11.007 ms (n=50)\u001b[0m\n", "------------- https://test.encodedcc.org/experiments/ENCSR856JJB/ --------------\n", - "\u001b[31mAverage es_time: 19.184 ± 5.515 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.465 ± 0.025 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage render_time: 30.939 ± 4.881 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 73.26 ± 7.695 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 123.848 ± 15.186 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage es_time: 7.527 ± 0.787 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.528 ± 0.021 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 41.415 ± 6.093 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 77.284 ± 6.558 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 126.754 ± 12.804 ms (n=50)\u001b[0m\n", "\n" ] - 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https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//experiments/ENCSR255XZG/https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//experiments/ENCSR301HAG/https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//experiments/ENCSR315NAC/https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//experiments/ENCSR688GVV/https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//experiments/ENCSR749ILN/https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//experiments/ENCSR856JJB/https://test.encodedcc.org/experiments/ENCSR255XZG/https://test.encodedcc.org/experiments/ENCSR301HAG/https://test.encodedcc.org/experiments/ENCSR315NAC/https://test.encodedcc.org/experiments/ENCSR688GVV/https://test.encodedcc.org/experiments/ENCSR749ILN/https://test.encodedcc.org/experiments/ENCSR856JJB/
es_time_mean3.4651.1912.8723.3921.8122.74421.51915.04019.00020.40416.35119.184
es_time_std0.1400.0330.0880.1500.0570.0662.9966.5814.0623.9303.4075.515
es_time_N50.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.000
queue_time_mean0.4690.4600.4480.4580.4280.4390.4900.4110.4640.4990.4920.465
queue_time_std0.0120.0150.0120.0110.0140.0220.0200.0270.0170.0210.0260.025
queue_time_N50.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.000
render_time_mean102.8129.18335.79944.49120.29931.810104.0276.68036.90946.41720.52230.939
render_time_std2.7614.0544.0844.2144.0045.4092.9031.5194.4564.9553.5014.881
render_time_N50.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.000
wsgi_time_mean204.39715.75080.27195.57636.67258.038227.95327.05883.347101.58151.94873.260
wsgi_time_std119.7784.066101.84295.7824.5135.628136.8496.5496.8646.5665.3477.695
wsgi_time_N50.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.000
total_mean311.14226.584119.391143.91659.21193.031353.98949.189139.721168.90089.314123.848
total_std120.4398.117101.66797.6978.47411.021137.18313.12212.58312.8059.98015.186
total_N50.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.000
\n", - "
" - ], - "text/plain": [ - " https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//experiments/ENCSR255XZG/ \\\n", - "es_time_mean 3.465 \n", - "es_time_std 0.140 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.469 \n", - "queue_time_std 0.012 \n", - "queue_time_N 50.000 \n", - "render_time_mean 102.812 \n", - "render_time_std 2.761 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 204.397 \n", - "wsgi_time_std 119.778 \n", - "wsgi_time_N 50.000 \n", - "total_mean 311.142 \n", - "total_std 120.439 \n", - "total_N 50.000 \n", - "\n", - " https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//experiments/ENCSR301HAG/ \\\n", - "es_time_mean 1.191 \n", - "es_time_std 0.033 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.460 \n", - "queue_time_std 0.015 \n", - "queue_time_N 50.000 \n", - "render_time_mean 9.183 \n", - "render_time_std 4.054 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 15.750 \n", - "wsgi_time_std 4.066 \n", - "wsgi_time_N 50.000 \n", - "total_mean 26.584 \n", - "total_std 8.117 \n", - "total_N 50.000 \n", - "\n", - " https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//experiments/ENCSR315NAC/ \\\n", - "es_time_mean 2.872 \n", - "es_time_std 0.088 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.448 \n", - "queue_time_std 0.012 \n", - "queue_time_N 50.000 \n", - "render_time_mean 35.799 \n", - "render_time_std 4.084 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 80.271 \n", - "wsgi_time_std 101.842 \n", - "wsgi_time_N 50.000 \n", - "total_mean 119.391 \n", - "total_std 101.667 \n", - "total_N 50.000 \n", - "\n", - " https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//experiments/ENCSR688GVV/ \\\n", - "es_time_mean 3.392 \n", - "es_time_std 0.150 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.458 \n", - "queue_time_std 0.011 \n", - "queue_time_N 50.000 \n", - "render_time_mean 44.491 \n", - "render_time_std 4.214 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 95.576 \n", - "wsgi_time_std 95.782 \n", - "wsgi_time_N 50.000 \n", - "total_mean 143.916 \n", - "total_std 97.697 \n", - "total_N 50.000 \n", - "\n", - " https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//experiments/ENCSR749ILN/ \\\n", - "es_time_mean 1.812 \n", - "es_time_std 0.057 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.428 \n", - "queue_time_std 0.014 \n", - "queue_time_N 50.000 \n", - "render_time_mean 20.299 \n", - "render_time_std 4.004 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 36.672 \n", - "wsgi_time_std 4.513 \n", - "wsgi_time_N 50.000 \n", - "total_mean 59.211 \n", - "total_std 8.474 \n", - "total_N 50.000 \n", - "\n", - " https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//experiments/ENCSR856JJB/ \\\n", - "es_time_mean 2.744 \n", - "es_time_std 0.066 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.439 \n", - "queue_time_std 0.022 \n", - "queue_time_N 50.000 \n", - "render_time_mean 31.810 \n", - "render_time_std 5.409 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 58.038 \n", - "wsgi_time_std 5.628 \n", - "wsgi_time_N 50.000 \n", - "total_mean 93.031 \n", - "total_std 11.021 \n", - "total_N 50.000 \n", - "\n", - " https://test.encodedcc.org/experiments/ENCSR255XZG/ \\\n", - "es_time_mean 21.519 \n", - "es_time_std 2.996 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.490 \n", - "queue_time_std 0.020 \n", - "queue_time_N 50.000 \n", - "render_time_mean 104.027 \n", - "render_time_std 2.903 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 227.953 \n", - "wsgi_time_std 136.849 \n", - "wsgi_time_N 50.000 \n", - "total_mean 353.989 \n", - "total_std 137.183 \n", - "total_N 50.000 \n", - "\n", - " https://test.encodedcc.org/experiments/ENCSR301HAG/ \\\n", - "es_time_mean 15.040 \n", - "es_time_std 6.581 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.411 \n", - "queue_time_std 0.027 \n", - "queue_time_N 50.000 \n", - "render_time_mean 6.680 \n", - "render_time_std 1.519 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 27.058 \n", - "wsgi_time_std 6.549 \n", - "wsgi_time_N 50.000 \n", - "total_mean 49.189 \n", - "total_std 13.122 \n", - "total_N 50.000 \n", - "\n", - " https://test.encodedcc.org/experiments/ENCSR315NAC/ \\\n", - "es_time_mean 19.000 \n", - "es_time_std 4.062 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.464 \n", - "queue_time_std 0.017 \n", - "queue_time_N 50.000 \n", - "render_time_mean 36.909 \n", - "render_time_std 4.456 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 83.347 \n", - "wsgi_time_std 6.864 \n", - "wsgi_time_N 50.000 \n", - "total_mean 139.721 \n", - "total_std 12.583 \n", - "total_N 50.000 \n", - "\n", - " https://test.encodedcc.org/experiments/ENCSR688GVV/ \\\n", - "es_time_mean 20.404 \n", - "es_time_std 3.930 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.499 \n", - "queue_time_std 0.021 \n", - "queue_time_N 50.000 \n", - "render_time_mean 46.417 \n", - "render_time_std 4.955 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 101.581 \n", - "wsgi_time_std 6.566 \n", - "wsgi_time_N 50.000 \n", - "total_mean 168.900 \n", - "total_std 12.805 \n", - "total_N 50.000 \n", - "\n", - " https://test.encodedcc.org/experiments/ENCSR749ILN/ \\\n", - "es_time_mean 16.351 \n", - "es_time_std 3.407 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.492 \n", - "queue_time_std 0.026 \n", - "queue_time_N 50.000 \n", - "render_time_mean 20.522 \n", - "render_time_std 3.501 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 51.948 \n", - "wsgi_time_std 5.347 \n", - "wsgi_time_N 50.000 \n", - "total_mean 89.314 \n", - "total_std 9.980 \n", - "total_N 50.000 \n", - "\n", - " https://test.encodedcc.org/experiments/ENCSR856JJB/ \n", - "es_time_mean 19.184 \n", - "es_time_std 5.515 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.465 \n", - "queue_time_std 0.025 \n", - "queue_time_N 50.000 \n", - "render_time_mean 30.939 \n", - "render_time_std 4.881 \n", - "render_time_N 50.000 \n", - "wsgi_time_mean 73.260 \n", - "wsgi_time_std 7.695 \n", - "wsgi_time_N 50.000 \n", - "total_mean 123.848 \n", - "total_std 15.186 \n", - "total_N 50.000 " - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" } ], "source": [ @@ -1976,489 +411,21 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "metadata": { "scrolled": false }, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Checking response time\n", - "\n", - "*** item_type: /ENCSR255XZG/\n", - "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR255XZG/ ---------\n", - "\u001b[36mAverage es_time: 3.548 ± 0.306 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.468 ± 0.013 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 102.824 ± 127.339 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 106.841 ± 127.372 ms (n=50)\u001b[0m\n", - "------------------- https://test.encodedcc.org/ENCSR255XZG/ --------------------\n", - "\u001b[31mAverage es_time: 22.733 ± 5.298 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.473 ± 0.017 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 96.062 ± 5.493 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 119.268 ± 10.715 ms (n=50)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /ENCSR749ILN/\n", - "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR749ILN/ ---------\n", - "\u001b[36mAverage es_time: 1.893 ± 0.242 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.46 ± 0.014 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 16.17 ± 0.901 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 18.523 ± 0.986 ms (n=50)\u001b[0m\n", - "------------------- https://test.encodedcc.org/ENCSR749ILN/ --------------------\n", - "\u001b[31mAverage es_time: 17.565 ± 5.914 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.481 ± 0.031 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 46.521 ± 98.772 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 64.567 ± 98.946 ms (n=50)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /ENCSR688GVV/\n", - "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR688GVV/ ---------\n", - "\u001b[36mAverage es_time: 3.36 ± 0.08 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.471 ± 0.011 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 62.86 ± 124.371 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 66.69 ± 124.415 ms (n=50)\u001b[0m\n", - "------------------- https://test.encodedcc.org/ENCSR688GVV/ --------------------\n", - "\u001b[31mAverage es_time: 20.534 ± 3.046 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.481 ± 0.012 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 54.658 ± 3.246 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 75.673 ± 6.239 ms (n=50)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /ENCSR301HAG/\n", - "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR301HAG/ ---------\n", - "\u001b[36mAverage es_time: 1.185 ± 0.039 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.467 ± 0.009 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 6.503 ± 0.385 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 8.155 ± 0.401 ms (n=50)\u001b[0m\n", - "------------------- https://test.encodedcc.org/ENCSR301HAG/ --------------------\n", - "\u001b[31mAverage es_time: 15.949 ± 3.715 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.48 ± 0.011 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 21.453 ± 3.775 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 37.882 ± 7.485 ms (n=50)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /ENCSR315NAC/\n", - "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR315NAC/ ---------\n", - "\u001b[36mAverage es_time: 2.85 ± 0.062 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.465 ± 0.01 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 43.198 ± 93.904 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 46.513 ± 93.931 ms (n=50)\u001b[0m\n", - "------------------- https://test.encodedcc.org/ENCSR315NAC/ --------------------\n", - "\u001b[31mAverage es_time: 34.573 ± 103.978 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.48 ± 0.011 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 61.732 ± 104.098 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 96.785 ± 208.075 ms (n=50)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /ENCSR856JJB/\n", - "--------- https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR856JJB/ ---------\n", - "\u001b[36mAverage es_time: 2.758 ± 0.045 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.466 ± 0.01 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 26.436 ± 1.023 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 29.66 ± 1.036 ms (n=50)\u001b[0m\n", - "------------------- https://test.encodedcc.org/ENCSR856JJB/ --------------------\n", - "\u001b[31mAverage es_time: 19.524 ± 4.852 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.47 ± 0.029 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 42.871 ± 5.054 ms (n=50)\u001b[0m\n", - "\u001b[36mAverage total time: 62.865 ± 9.874 ms (n=50)\u001b[0m\n", - "\n" + "ename": "TypeError", + "evalue": "check_response_time() got an unexpected keyword argument 'json'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mqa\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcheck_response_time\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mjson\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mitem_types\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'/ENCSR255XZG/'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'/ENCSR749ILN/'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'/ENCSR688GVV/'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'/ENCSR301HAG/'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'/ENCSR315NAC/'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'/ENCSR856JJB/'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m50\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;31mTypeError\u001b[0m: check_response_time() got an unexpected keyword argument 'json'" ] - 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https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR255XZG/https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR301HAG/https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR315NAC/https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR688GVV/https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR749ILN/https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR856JJB/https://test.encodedcc.org/ENCSR255XZG/https://test.encodedcc.org/ENCSR301HAG/https://test.encodedcc.org/ENCSR315NAC/https://test.encodedcc.org/ENCSR688GVV/https://test.encodedcc.org/ENCSR749ILN/https://test.encodedcc.org/ENCSR856JJB/
es_time_mean3.5481.1852.8503.3601.8932.75822.73315.94934.57320.53417.56519.524
es_time_std0.3060.0390.0620.0800.2420.0455.2983.715103.9783.0465.9144.852
es_time_N50.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.000
queue_time_mean0.4680.4670.4650.4710.4600.4660.4730.4800.4800.4810.4810.470
queue_time_std0.0130.0090.0100.0110.0140.0100.0170.0110.0110.0120.0310.029
queue_time_N50.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.000
wsgi_time_mean102.8246.50343.19862.86016.17026.43696.06221.45361.73254.65846.52142.871
wsgi_time_std127.3390.38593.904124.3710.9011.0235.4933.775104.0983.24698.7725.054
wsgi_time_N50.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.000
total_mean106.8418.15546.51366.69018.52329.660119.26837.88296.78575.67364.56762.865
total_std127.3720.40193.931124.4150.9861.03610.7157.485208.0756.23998.9469.874
total_N50.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.00050.000
\n", - "
" - ], - "text/plain": [ - " https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR255XZG/ \\\n", - "es_time_mean 3.548 \n", - "es_time_std 0.306 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.468 \n", - "queue_time_std 0.013 \n", - "queue_time_N 50.000 \n", - "wsgi_time_mean 102.824 \n", - "wsgi_time_std 127.339 \n", - "wsgi_time_N 50.000 \n", - "total_mean 106.841 \n", - "total_std 127.372 \n", - "total_N 50.000 \n", - "\n", - " https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR301HAG/ \\\n", - "es_time_mean 1.185 \n", - "es_time_std 0.039 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.467 \n", - "queue_time_std 0.009 \n", - "queue_time_N 50.000 \n", - "wsgi_time_mean 6.503 \n", - "wsgi_time_std 0.385 \n", - "wsgi_time_N 50.000 \n", - "total_mean 8.155 \n", - "total_std 0.401 \n", - "total_N 50.000 \n", - "\n", - " https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR315NAC/ \\\n", - "es_time_mean 2.850 \n", - "es_time_std 0.062 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.465 \n", - "queue_time_std 0.010 \n", - "queue_time_N 50.000 \n", - "wsgi_time_mean 43.198 \n", - "wsgi_time_std 93.904 \n", - "wsgi_time_N 50.000 \n", - "total_mean 46.513 \n", - "total_std 93.931 \n", - "total_N 50.000 \n", - "\n", - " https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR688GVV/ \\\n", - "es_time_mean 3.360 \n", - "es_time_std 0.080 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.471 \n", - "queue_time_std 0.011 \n", - "queue_time_N 50.000 \n", - "wsgi_time_mean 62.860 \n", - "wsgi_time_std 124.371 \n", - "wsgi_time_N 50.000 \n", - "total_mean 66.690 \n", - "total_std 124.415 \n", - "total_N 50.000 \n", - "\n", - " https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR749ILN/ \\\n", - "es_time_mean 1.893 \n", - "es_time_std 0.242 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.460 \n", - "queue_time_std 0.014 \n", - "queue_time_N 50.000 \n", - "wsgi_time_mean 16.170 \n", - "wsgi_time_std 0.901 \n", - "wsgi_time_N 50.000 \n", - "total_mean 18.523 \n", - "total_std 0.986 \n", - "total_N 50.000 \n", - "\n", - " https://sno-33-wrapper-f838d93b7-hitz.demo.encodedcc.org//ENCSR856JJB/ \\\n", - "es_time_mean 2.758 \n", - "es_time_std 0.045 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.466 \n", - "queue_time_std 0.010 \n", - "queue_time_N 50.000 \n", - "wsgi_time_mean 26.436 \n", - "wsgi_time_std 1.023 \n", - "wsgi_time_N 50.000 \n", - "total_mean 29.660 \n", - "total_std 1.036 \n", - "total_N 50.000 \n", - "\n", - " https://test.encodedcc.org/ENCSR255XZG/ \\\n", - "es_time_mean 22.733 \n", - "es_time_std 5.298 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.473 \n", - "queue_time_std 0.017 \n", - "queue_time_N 50.000 \n", - "wsgi_time_mean 96.062 \n", - "wsgi_time_std 5.493 \n", - "wsgi_time_N 50.000 \n", - "total_mean 119.268 \n", - "total_std 10.715 \n", - "total_N 50.000 \n", - "\n", - " https://test.encodedcc.org/ENCSR301HAG/ \\\n", - "es_time_mean 15.949 \n", - "es_time_std 3.715 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.480 \n", - "queue_time_std 0.011 \n", - "queue_time_N 50.000 \n", - "wsgi_time_mean 21.453 \n", - "wsgi_time_std 3.775 \n", - "wsgi_time_N 50.000 \n", - "total_mean 37.882 \n", - "total_std 7.485 \n", - "total_N 50.000 \n", - "\n", - " https://test.encodedcc.org/ENCSR315NAC/ \\\n", - "es_time_mean 34.573 \n", - "es_time_std 103.978 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.480 \n", - "queue_time_std 0.011 \n", - "queue_time_N 50.000 \n", - "wsgi_time_mean 61.732 \n", - "wsgi_time_std 104.098 \n", - "wsgi_time_N 50.000 \n", - "total_mean 96.785 \n", - "total_std 208.075 \n", - "total_N 50.000 \n", - "\n", - " https://test.encodedcc.org/ENCSR688GVV/ \\\n", - "es_time_mean 20.534 \n", - "es_time_std 3.046 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.481 \n", - "queue_time_std 0.012 \n", - "queue_time_N 50.000 \n", - "wsgi_time_mean 54.658 \n", - "wsgi_time_std 3.246 \n", - "wsgi_time_N 50.000 \n", - "total_mean 75.673 \n", - "total_std 6.239 \n", - "total_N 50.000 \n", - "\n", - " https://test.encodedcc.org/ENCSR749ILN/ \\\n", - "es_time_mean 17.565 \n", - "es_time_std 5.914 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.481 \n", - "queue_time_std 0.031 \n", - "queue_time_N 50.000 \n", - "wsgi_time_mean 46.521 \n", - "wsgi_time_std 98.772 \n", - "wsgi_time_N 50.000 \n", - "total_mean 64.567 \n", - "total_std 98.946 \n", - "total_N 50.000 \n", - "\n", - " https://test.encodedcc.org/ENCSR856JJB/ \n", - "es_time_mean 19.524 \n", - "es_time_std 4.852 \n", - "es_time_N 50.000 \n", - "queue_time_mean 0.470 \n", - "queue_time_std 0.029 \n", - "queue_time_N 50.000 \n", - "wsgi_time_mean 42.871 \n", - "wsgi_time_std 5.054 \n", - "wsgi_time_N 50.000 \n", - "total_mean 62.865 \n", - "total_std 9.874 \n", - "total_N 50.000 " - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" } ], "source": [ @@ -2471,7 +438,135 @@ "metadata": { "scrolled": false }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Checking response time\n", + "\n", + "*** item_type: /ENCSR480OHP/\n", + "------------ https://sno68-on-dev.demo.encodedcc.org//ENCSR480OHP/ -------------\n", + "\u001b[36mAverage es_time: 3.024 ± 1.973 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.476 ± 0.014 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 42.567 ± 4.129 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 92.21 ± 106.447 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 138.277 ± 107.694 ms (n=50)\u001b[0m\n", + "------------------- https://test.encodedcc.org/ENCSR480OHP/ --------------------\n", + "\u001b[36mAverage es_time: 6.934 ± 4.134 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.486 ± 0.043 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 43.671 ± 4.564 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 82.283 ± 5.793 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 133.373 ± 11.43 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR000EMB/\n", + "------------ https://sno68-on-dev.demo.encodedcc.org//ENCSR000EMB/ -------------\n", + "\u001b[36mAverage es_time: 3.539 ± 1.585 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.478 ± 0.011 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 46.913 ± 6.625 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 91.812 ± 97.01 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 142.743 ± 98.367 ms (n=50)\u001b[0m\n", + "------------------- https://test.encodedcc.org/ENCSR000EMB/ --------------------\n", + "\u001b[36mAverage es_time: 7.46 ± 0.897 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.495 ± 0.039 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 46.362 ± 7.316 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 104.983 ± 118.496 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 159.3 ± 120.608 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR323QIP/\n", + "------------ https://sno68-on-dev.demo.encodedcc.org//ENCSR323QIP/ -------------\n", + "\u001b[36mAverage es_time: 5.408 ± 0.751 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.483 ± 0.012 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 133.507 ± 5.343 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 256.008 ± 119.64 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage total time: 395.406 ± 119.941 ms (n=50)\u001b[0m\n", + "------------------- https://test.encodedcc.org/ENCSR323QIP/ --------------------\n", + "\u001b[31mAverage es_time: 17.838 ± 0.255 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.509 ± 0.039 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 133.907 ± 5.734 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 275.48 ± 126.165 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage total time: 427.734 ± 126.717 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR718AXQ/\n", + "------------ https://sno68-on-dev.demo.encodedcc.org//ENCSR718AXQ/ -------------\n", + "\u001b[36mAverage es_time: 2.845 ± 1.286 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.482 ± 0.012 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 19.758 ± 7.758 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 33.103 ± 7.805 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 56.188 ± 15.612 ms (n=50)\u001b[0m\n", + "------------------- https://test.encodedcc.org/ENCSR718AXQ/ --------------------\n", + "\u001b[36mAverage es_time: 5.281 ± 0.422 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.469 ± 0.025 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 17.789 ± 6.706 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 33.317 ± 6.879 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 56.855 ± 13.486 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR165BGV/\n", + "------------ https://sno68-on-dev.demo.encodedcc.org//ENCSR165BGV/ -------------\n", + "\u001b[36mAverage es_time: 1.523 ± 0.183 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.478 ± 0.014 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 19.061 ± 4.842 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 31.754 ± 4.894 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 52.817 ± 9.686 ms (n=50)\u001b[0m\n", + "------------------- https://test.encodedcc.org/ENCSR165BGV/ --------------------\n", + "\u001b[36mAverage es_time: 3.204 ± 0.412 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.497 ± 0.043 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 19.4 ± 5.446 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 33.894 ± 5.551 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 56.994 ± 11.006 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR384KAN/\n", + "------------ https://sno68-on-dev.demo.encodedcc.org//ENCSR384KAN/ -------------\n", + "\u001b[36mAverage es_time: 3.217 ± 0.336 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.475 ± 0.012 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 48.631 ± 6.211 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 86.01 ± 6.301 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 138.333 ± 12.447 ms (n=50)\u001b[0m\n", + "------------------- https://test.encodedcc.org/ENCSR384KAN/ --------------------\n", + "\u001b[36mAverage es_time: 7.753 ± 0.258 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.466 ± 0.019 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 48.559 ± 6.189 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 90.366 ± 6.371 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 147.143 ± 12.556 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR330FXL/\n", + "------------ https://sno68-on-dev.demo.encodedcc.org//ENCSR330FXL/ -------------\n", + "\u001b[36mAverage es_time: 1.833 ± 1.882 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.461 ± 0.017 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 23.601 ± 5.635 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 39.282 ± 6.39 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 65.177 ± 12.654 ms (n=50)\u001b[0m\n", + "------------------- https://test.encodedcc.org/ENCSR330FXL/ --------------------\n", + "\u001b[36mAverage es_time: 4.176 ± 4.315 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.447 ± 0.02 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 23.821 ± 6.008 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 41.621 ± 7.911 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 70.065 ± 15.61 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR825UNV/\n", + "------------ https://sno68-on-dev.demo.encodedcc.org//ENCSR825UNV/ -------------\n", + "\u001b[36mAverage es_time: 7.651 ± 0.795 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.496 ± 0.017 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage render_time: 214.359 ± 7.611 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage wsgi_time: 450.827 ± 223.591 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage total time: 673.333 ± 222.807 ms (n=50)\u001b[0m\n", + "------------------- https://test.encodedcc.org/ENCSR825UNV/ --------------------\n", + "\u001b[31mAverage es_time: 22.394 ± 5.35 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.489 ± 0.021 ms (n=50)\u001b[0m\n", + "\u001b[33mAverage render_time: 212.983 ± 7.953 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage wsgi_time: 514.785 ± 280.001 ms (n=50)\u001b[0m\n", + "\u001b[31mAverage total time: 750.652 ± 281.499 ms (n=50)\u001b[0m\n", + "\n" + ] + } + ], "source": [ "qa.check_response_time(item_types=['/ENCSR480OHP/','/ENCSR000EMB/','/ENCSR323QIP/','/ENCSR718AXQ/','/ENCSR165BGV/','/ENCSR384KAN/','/ENCSR330FXL/','/ENCSR825UNV/'], n=50)" ] @@ -2480,7 +575,48 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Checking response time\n", + "\n", + "*** item_type: /ENCAB830JLB/\n", + "------------ https://sno68-on-dev.demo.encodedcc.org//ENCAB830JLB/ -------------\n", + "\u001b[36mAverage es_time: 1.478 ± 0.355 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.456 ± 0.017 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 39.482 ± 6.56 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 66.734 ± 7.516 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 108.15 ± 14.101 ms (n=50)\u001b[0m\n", + "------------------- https://test.encodedcc.org/ENCAB830JLB/ --------------------\n", + "\u001b[36mAverage es_time: 3.655 ± 0.701 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.436 ± 0.026 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 38.509 ± 6.206 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 67.066 ± 6.822 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 109.667 ± 13.242 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCAB000BKR/\n", + "------------ https://sno68-on-dev.demo.encodedcc.org//ENCAB000BKR/ -------------\n", + "\u001b[36mAverage es_time: 1.272 ± 0.191 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.453 ± 0.017 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 19.947 ± 6.523 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 32.458 ± 6.693 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 54.13 ± 13.239 ms (n=50)\u001b[0m\n", + "------------------- https://test.encodedcc.org/ENCAB000BKR/ --------------------\n", + "\u001b[36mAverage es_time: 2.95 ± 0.839 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.46 ± 0.039 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage render_time: 19.6 ± 6.643 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 34.022 ± 6.833 ms (n=50)\u001b[0m\n", + "\u001b[36mAverage total time: 57.031 ± 13.672 ms (n=50)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCAB284TTY/\n", + "------------ https://sno68-on-dev.demo.encodedcc.org//ENCAB284TTY/ -------------\n" + ] + } + ], "source": [ "qa.check_response_time(item_types=['/ENCAB830JLB/','/ENCAB000BKR/','/ENCAB284TTY/','/ENCAB294YUD/','/ENCAB000AOC/','/ENCAB301QZF/','/ENCAB000ANM/','/ENCAB000ANU/','/ENCAB445KMF/','/ENCAB000BAY/'], n=50)" ] @@ -2488,7 +624,9 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "qa.check_response_time(item_types=['/ENCBS787TFV/','/ENCBS676QAV/','/ENCBS996IWU/','/ENCBS913XJP/','/ENCBS565NTN/','/ENCBS896YZO/','/ENCBS280NYD/'], n=50)" @@ -2518,7 +656,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.4.3" + "version": "3.5.1" } }, "nbformat": 4, From f47f35db5d97f97259dd82402636fa84d63cb242 Mon Sep 17 00:00:00 2001 From: Ben Hitz Date: Wed, 12 Dec 2018 17:13:27 -0800 Subject: [PATCH 4/5] move profiling notebooks around --- ...vs. Test + Production vs. v65rc1-es5.ipynb | 0 .../{ => profiling}/timing-tests-sno-33.ipynb | 0 .../profiling/timing-tests-sno-33.py | 68 +++++ .../v64-duplicate vs. v65rc2.ipynb | 0 .../profiling/v79rc1 vs v77-test.ipynb | 279 ++++++++++++++++++ 5 files changed, 347 insertions(+) rename jupyter_notebooks/{kath => profiling}/Production vs. Test + Production vs. v65rc1-es5.ipynb (100%) rename jupyter_notebooks/{ => profiling}/timing-tests-sno-33.ipynb (100%) create mode 100644 jupyter_notebooks/profiling/timing-tests-sno-33.py rename jupyter_notebooks/{kath => profiling}/v64-duplicate vs. v65rc2.ipynb (100%) create mode 100644 jupyter_notebooks/profiling/v79rc1 vs v77-test.ipynb diff --git a/jupyter_notebooks/kath/Production vs. Test + Production vs. v65rc1-es5.ipynb b/jupyter_notebooks/profiling/Production vs. Test + Production vs. v65rc1-es5.ipynb similarity index 100% rename from jupyter_notebooks/kath/Production vs. Test + Production vs. v65rc1-es5.ipynb rename to jupyter_notebooks/profiling/Production vs. Test + Production vs. v65rc1-es5.ipynb diff --git a/jupyter_notebooks/timing-tests-sno-33.ipynb b/jupyter_notebooks/profiling/timing-tests-sno-33.ipynb similarity index 100% rename from jupyter_notebooks/timing-tests-sno-33.ipynb rename to jupyter_notebooks/profiling/timing-tests-sno-33.ipynb diff --git a/jupyter_notebooks/profiling/timing-tests-sno-33.py b/jupyter_notebooks/profiling/timing-tests-sno-33.py new file mode 100644 index 00000000..791a233f --- /dev/null +++ b/jupyter_notebooks/profiling/timing-tests-sno-33.py @@ -0,0 +1,68 @@ + +# coding: utf-8 + +# In[1]: + + + +# In[2]: + +import sys +sys.path.append('..') +import qancode +import numpy as np +import pandas as pd + + +# In[3]: + +#compare any two encoded instances here +qa = qancode.QANCODE(rc_url="https://test.encodedcc.org", prod_url='https://sno68-on-dev.demo.encodedcc.org/') + + +# In[4]: + +res = qa.check_response_time(item_types=["/","/search/?type=Experiment"], n=50) + + +# In[5]: + +res + + +# In[6]: + +qa.check_response_time(item_types=["/search/?searchTerm=K562", "/search/?searchTerm=DNA+binding", "/search/?searchTerm=human", "/search/?searchTerm=H3K36me3", "/search/?searchTerm=CTCF"], n=50) + + +# In[7]: + +qa.check_response_time(item_types=['/ENCSR255XZG/', '/ENCSR749ILN/', '/ENCSR688GVV/', '/ENCSR301HAG/','/ENCSR315NAC/', '/ENCSR856JJB/'], n=50) + + +# In[8]: + +qa.check_response_time(item_types=['/experiments/ENCSR255XZG/', '/experiments/ENCSR749ILN/', '/experiments/ENCSR688GVV/', '/experiments/ENCSR301HAG/','/experiments/ENCSR315NAC/', '/experiments/ENCSR856JJB/'], n=50) + + +# In[10]: + +qa.check_response_time(json=True, item_types=['/ENCSR255XZG/', '/ENCSR749ILN/', '/ENCSR688GVV/', '/ENCSR301HAG/','/ENCSR315NAC/', '/ENCSR856JJB/'], n=50) + + +# In[ ]: + +qa.check_response_time(item_types=['/ENCSR480OHP/','/ENCSR000EMB/','/ENCSR323QIP/','/ENCSR718AXQ/','/ENCSR165BGV/','/ENCSR384KAN/','/ENCSR330FXL/','/ENCSR825UNV/'], n=50) + + +# In[ ]: + +qa.check_response_time(item_types=['/ENCAB830JLB/','/ENCAB000BKR/','/ENCAB284TTY/','/ENCAB294YUD/','/ENCAB000AOC/','/ENCAB301QZF/','/ENCAB000ANM/','/ENCAB000ANU/','/ENCAB445KMF/','/ENCAB000BAY/'], n=50) + + +# In[ ]: + +qa.check_response_time(item_types=['/ENCBS787TFV/','/ENCBS676QAV/','/ENCBS996IWU/','/ENCBS913XJP/','/ENCBS565NTN/','/ENCBS896YZO/','/ENCBS280NYD/'], n=50) + + +# ## diff --git a/jupyter_notebooks/kath/v64-duplicate vs. v65rc2.ipynb b/jupyter_notebooks/profiling/v64-duplicate vs. v65rc2.ipynb similarity index 100% rename from jupyter_notebooks/kath/v64-duplicate vs. v65rc2.ipynb rename to jupyter_notebooks/profiling/v64-duplicate vs. v65rc2.ipynb diff --git a/jupyter_notebooks/profiling/v79rc1 vs v77-test.ipynb b/jupyter_notebooks/profiling/v79rc1 vs v77-test.ipynb new file mode 100644 index 00000000..e3c8c071 --- /dev/null +++ b/jupyter_notebooks/profiling/v79rc1 vs v77-test.ipynb @@ -0,0 +1,279 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import sys\n", + "sys.path.append('../..')\n", + "import qancode" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "#comparing to v65rc2 site\n", + "qa = qancode.QANCODE(rc_url=\"https://v79rc1-master.demo.encodedcc.org/\", prod_url=\"https://test.encodedcc.org/\")" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Checking response time\n", + "\n", + "*** item_type: /\n", + "------------------------- https://test.encodedcc.org// -------------------------\n", + "\u001b[36mAverage es_time: 2.443 ± 1.396 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.509 ± 0.021 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 5.237 ± 1.01 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 11.828 ± 1.797 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 20.017 ± 3.473 ms (n=100)\u001b[0m\n", + "------------------ https://v79rc1-master.demo.encodedcc.org// ------------------\n", + "\u001b[36mAverage es_time: 2.038 ± 0.241 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.361 ± 0.032 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 3.991 ± 0.732 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 9.506 ± 0.798 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 15.895 ± 1.532 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /search/?type=Experiment\n", + "------------- https://test.encodedcc.org//search/?type=Experiment --------------\n", + "\u001b[31mAverage es_time: 24.699 ± 10.871 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.507 ± 0.023 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 140.946 ± 11.738 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 182.266 ± 17.143 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 348.418 ± 34.2 ms (n=100)\u001b[0m\n", + "------ https://v79rc1-master.demo.encodedcc.org//search/?type=Experiment -------\n", + "\u001b[31mAverage es_time: 22.949 ± 10.685 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.475 ± 0.019 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 123.067 ± 14.795 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 162.2 ± 20.174 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 308.692 ± 40.393 ms (n=100)\u001b[0m\n", + "\n" + ] + } + ], + "source": [ + "qa.check_response_time(item_types=[\"/\",\"/search/?type=Experiment\"], n=100)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Checking response time\n", + "\n", + "*** item_type: /search/?searchTerm=K562\n", + "------------- https://test.encodedcc.org//search/?searchTerm=K562 --------------\n", + "\u001b[31mAverage es_time: 250.489 ± 48.89 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.531 ± 0.02 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 33.264 ± 10.438 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 296.063 ± 52.472 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 580.347 ± 102.992 ms (n=100)\u001b[0m\n", + "------ https://v79rc1-master.demo.encodedcc.org//search/?searchTerm=K562 -------\n", + "\u001b[31mAverage es_time: 208.883 ± 35.957 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.437 ± 0.018 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 23.045 ± 6.471 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 239.354 ± 37.294 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 471.72 ± 74.319 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /search/?searchTerm=DNA+binding\n", + "---------- https://test.encodedcc.org//search/?searchTerm=DNA+binding ----------\n", + "\u001b[31mAverage es_time: 352.991 ± 54.339 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.531 ± 0.025 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 34.168 ± 10.722 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage wsgi_time: 401.306 ± 58.61 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 788.996 ± 115.49 ms (n=100)\u001b[0m\n", + "--------- https://v79rc1-master.demo.encodedcc.org//search/?searchTerm=DNA+binding ---------\n", + "\u001b[31mAverage es_time: 309.012 ± 50.516 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.442 ± 0.02 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 25.838 ± 6.634 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 345.825 ± 51.697 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 681.117 ± 102.851 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /search/?searchTerm=human\n", + "------------- https://test.encodedcc.org//search/?searchTerm=human -------------\n", + "\u001b[31mAverage es_time: 249.505 ± 31.124 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.525 ± 0.027 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 29.964 ± 8.021 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 287.351 ± 32.164 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 567.346 ± 64.18 ms (n=100)\u001b[0m\n", + "------ https://v79rc1-master.demo.encodedcc.org//search/?searchTerm=human ------\n", + "\u001b[31mAverage es_time: 212.92 ± 32.219 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.438 ± 0.023 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 24.804 ± 6.531 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 244.6 ± 35.275 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 482.762 ± 70.465 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /search/?searchTerm=H3K36me3\n", + "----------- https://test.encodedcc.org//search/?searchTerm=H3K36me3 ------------\n", + "\u001b[31mAverage es_time: 248.062 ± 24.424 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.539 ± 0.023 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 38.939 ± 10.035 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 295.371 ± 28.084 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 582.911 ± 56.039 ms (n=100)\u001b[0m\n", + "---- https://v79rc1-master.demo.encodedcc.org//search/?searchTerm=H3K36me3 -----\n", + "\u001b[31mAverage es_time: 212.122 ± 23.738 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.441 ± 0.021 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 27.224 ± 6.081 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 247.042 ± 25.751 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 486.828 ± 51.462 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /search/?searchTerm=CTCF\n", + "------------- https://test.encodedcc.org//search/?searchTerm=CTCF --------------\n", + "\u001b[31mAverage es_time: 254.143 ± 28.335 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.522 ± 0.02 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 27.405 ± 7.011 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 289.241 ± 30.306 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 571.311 ± 60.455 ms (n=100)\u001b[0m\n", + "------ https://v79rc1-master.demo.encodedcc.org//search/?searchTerm=CTCF -------\n", + "\u001b[31mAverage es_time: 212.717 ± 28.256 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.431 ± 0.023 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 22.226 ± 6.054 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 241.854 ± 29.208 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 477.229 ± 58.347 ms (n=100)\u001b[0m\n", + "\n" + ] + } + ], + "source": [ + "qa.check_response_time(item_types=[\"/search/?searchTerm=K562\", \"/search/?searchTerm=DNA+binding\", \"/search/?searchTerm=human\", \"/search/?searchTerm=H3K36me3\", \"/search/?searchTerm=CTCF\"], n=100)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Checking response time\n", + "\n", + "*** item_type: /ENCSR255XZG/\n", + "------------------- https://test.encodedcc.org//ENCSR255XZG/ -------------------\n", + "\u001b[31mAverage es_time: 13.068 ± 2.72 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.475 ± 0.031 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 114.842 ± 4.813 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 221.894 ± 103.95 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 350.278 ± 104.227 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCSR255XZG/ ------------\n", + "\u001b[31mAverage es_time: 13.003 ± 5.506 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.486 ± 0.043 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 135.871 ± 104.913 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 233.545 ± 126.217 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 382.906 ± 224.928 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR749ILN/\n", + "------------------- https://test.encodedcc.org//ENCSR749ILN/ -------------------\n", + "\u001b[36mAverage es_time: 6.697 ± 3.32 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.477 ± 0.047 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 35.722 ± 6.491 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 61.932 ± 9.362 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 104.827 ± 16.282 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCSR749ILN/ ------------\n", + "\u001b[36mAverage es_time: 6.561 ± 2.738 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.462 ± 0.025 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 31.747 ± 5.352 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 56.845 ± 6.371 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 95.615 ± 12.547 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR688GVV/\n", + "------------------- https://test.encodedcc.org//ENCSR688GVV/ -------------------\n" + ] + } + ], + "source": [ + "qa.check_response_time(item_types=['/ENCSR255XZG/', '/ENCSR749ILN/', '/ENCSR688GVV/', '/ENCSR301HAG/','/ENCSR315NAC/', '/ENCSR856JJB/'], n=100)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true, + "scrolled": true + }, + "outputs": [], + "source": [ + "qa.check_response_time(item_types=['/ENCSR480OHP/','/ENCSR000EMB/','/ENCSR323QIP/','/ENCSR718AXQ/','/ENCSR165BGV/','/ENCSR384KAN/','/ENCSR330FXL/','/ENCSR825UNV/','/ENCSR089EOA/'], n=100)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "qa.check_response_time(item_types=['/ENCAB830JLB/','/ENCAB000BKR/','/ENCAB284TTY/','/ENCAB294YUD/','/ENCAB000AOC/','/ENCAB301QZF/','/ENCAB000ANM/','/ENCAB000ANU/','/ENCAB445KMF/','/ENCAB000BAY/'], n=100)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "qa.check_response_time(item_types=['/ENCBS787TFV/','/ENCBS676QAV/','/ENCBS996IWU/','/ENCBS913XJP/','/ENCBS565NTN/','/ENCBS896YZO/','/ENCBS280NYD/'], n=100)" + ] + } + ], + "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": "3.5.1" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From c47a0580f53ad3cd52f284c4bcba9732baea9baf Mon Sep 17 00:00:00 2001 From: Ben Hitz Date: Fri, 14 Dec 2018 12:42:48 -0800 Subject: [PATCH 5/5] rnename latest --- .../profiling/v79rc1 vs v77-test.ipynb | 279 ------ .../profiling/v79rc1 vs v78-test.ipynb | 830 ++++++++++++++++++ 2 files changed, 830 insertions(+), 279 deletions(-) delete mode 100644 jupyter_notebooks/profiling/v79rc1 vs v77-test.ipynb create mode 100644 jupyter_notebooks/profiling/v79rc1 vs v78-test.ipynb diff --git a/jupyter_notebooks/profiling/v79rc1 vs v77-test.ipynb b/jupyter_notebooks/profiling/v79rc1 vs v77-test.ipynb deleted file mode 100644 index e3c8c071..00000000 --- a/jupyter_notebooks/profiling/v79rc1 vs v77-test.ipynb +++ /dev/null @@ -1,279 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "import sys\n", - "sys.path.append('../..')\n", - "import qancode" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "#comparing to v65rc2 site\n", - "qa = qancode.QANCODE(rc_url=\"https://v79rc1-master.demo.encodedcc.org/\", prod_url=\"https://test.encodedcc.org/\")" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Checking response time\n", - "\n", - "*** item_type: /\n", - "------------------------- https://test.encodedcc.org// -------------------------\n", - "\u001b[36mAverage es_time: 2.443 ± 1.396 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.509 ± 0.021 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 5.237 ± 1.01 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 11.828 ± 1.797 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage total time: 20.017 ± 3.473 ms (n=100)\u001b[0m\n", - "------------------ https://v79rc1-master.demo.encodedcc.org// ------------------\n", - "\u001b[36mAverage es_time: 2.038 ± 0.241 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.361 ± 0.032 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 3.991 ± 0.732 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 9.506 ± 0.798 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage total time: 15.895 ± 1.532 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /search/?type=Experiment\n", - "------------- https://test.encodedcc.org//search/?type=Experiment --------------\n", - "\u001b[31mAverage es_time: 24.699 ± 10.871 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.507 ± 0.023 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 140.946 ± 11.738 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 182.266 ± 17.143 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage total time: 348.418 ± 34.2 ms (n=100)\u001b[0m\n", - "------ https://v79rc1-master.demo.encodedcc.org//search/?type=Experiment -------\n", - "\u001b[31mAverage es_time: 22.949 ± 10.685 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.475 ± 0.019 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 123.067 ± 14.795 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 162.2 ± 20.174 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage total time: 308.692 ± 40.393 ms (n=100)\u001b[0m\n", - "\n" - ] - } - ], - "source": [ - "qa.check_response_time(item_types=[\"/\",\"/search/?type=Experiment\"], n=100)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Checking response time\n", - "\n", - "*** item_type: /search/?searchTerm=K562\n", - "------------- https://test.encodedcc.org//search/?searchTerm=K562 --------------\n", - "\u001b[31mAverage es_time: 250.489 ± 48.89 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.531 ± 0.02 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 33.264 ± 10.438 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 296.063 ± 52.472 ms (n=100)\u001b[0m\n", - "\u001b[31mAverage total time: 580.347 ± 102.992 ms (n=100)\u001b[0m\n", - "------ https://v79rc1-master.demo.encodedcc.org//search/?searchTerm=K562 -------\n", - "\u001b[31mAverage es_time: 208.883 ± 35.957 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.437 ± 0.018 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 23.045 ± 6.471 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 239.354 ± 37.294 ms (n=100)\u001b[0m\n", - "\u001b[31mAverage total time: 471.72 ± 74.319 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /search/?searchTerm=DNA+binding\n", - "---------- https://test.encodedcc.org//search/?searchTerm=DNA+binding ----------\n", - "\u001b[31mAverage es_time: 352.991 ± 54.339 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.531 ± 0.025 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 34.168 ± 10.722 ms (n=100)\u001b[0m\n", - "\u001b[31mAverage wsgi_time: 401.306 ± 58.61 ms (n=100)\u001b[0m\n", - "\u001b[31mAverage total time: 788.996 ± 115.49 ms (n=100)\u001b[0m\n", - "--------- https://v79rc1-master.demo.encodedcc.org//search/?searchTerm=DNA+binding ---------\n", - "\u001b[31mAverage es_time: 309.012 ± 50.516 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.442 ± 0.02 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 25.838 ± 6.634 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 345.825 ± 51.697 ms (n=100)\u001b[0m\n", - "\u001b[31mAverage total time: 681.117 ± 102.851 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /search/?searchTerm=human\n", - "------------- https://test.encodedcc.org//search/?searchTerm=human -------------\n", - "\u001b[31mAverage es_time: 249.505 ± 31.124 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.525 ± 0.027 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 29.964 ± 8.021 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 287.351 ± 32.164 ms (n=100)\u001b[0m\n", - "\u001b[31mAverage total time: 567.346 ± 64.18 ms (n=100)\u001b[0m\n", - "------ https://v79rc1-master.demo.encodedcc.org//search/?searchTerm=human ------\n", - "\u001b[31mAverage es_time: 212.92 ± 32.219 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.438 ± 0.023 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 24.804 ± 6.531 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 244.6 ± 35.275 ms (n=100)\u001b[0m\n", - "\u001b[31mAverage total time: 482.762 ± 70.465 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /search/?searchTerm=H3K36me3\n", - "----------- https://test.encodedcc.org//search/?searchTerm=H3K36me3 ------------\n", - "\u001b[31mAverage es_time: 248.062 ± 24.424 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.539 ± 0.023 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 38.939 ± 10.035 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 295.371 ± 28.084 ms (n=100)\u001b[0m\n", - "\u001b[31mAverage total time: 582.911 ± 56.039 ms (n=100)\u001b[0m\n", - "---- https://v79rc1-master.demo.encodedcc.org//search/?searchTerm=H3K36me3 -----\n", - "\u001b[31mAverage es_time: 212.122 ± 23.738 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.441 ± 0.021 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 27.224 ± 6.081 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 247.042 ± 25.751 ms (n=100)\u001b[0m\n", - "\u001b[31mAverage total time: 486.828 ± 51.462 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /search/?searchTerm=CTCF\n", - "------------- https://test.encodedcc.org//search/?searchTerm=CTCF --------------\n", - "\u001b[31mAverage es_time: 254.143 ± 28.335 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.522 ± 0.02 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 27.405 ± 7.011 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 289.241 ± 30.306 ms (n=100)\u001b[0m\n", - "\u001b[31mAverage total time: 571.311 ± 60.455 ms (n=100)\u001b[0m\n", - "------ https://v79rc1-master.demo.encodedcc.org//search/?searchTerm=CTCF -------\n", - "\u001b[31mAverage es_time: 212.717 ± 28.256 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.431 ± 0.023 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 22.226 ± 6.054 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 241.854 ± 29.208 ms (n=100)\u001b[0m\n", - "\u001b[31mAverage total time: 477.229 ± 58.347 ms (n=100)\u001b[0m\n", - "\n" - ] - } - ], - "source": [ - "qa.check_response_time(item_types=[\"/search/?searchTerm=K562\", \"/search/?searchTerm=DNA+binding\", \"/search/?searchTerm=human\", \"/search/?searchTerm=H3K36me3\", \"/search/?searchTerm=CTCF\"], n=100)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Checking response time\n", - "\n", - "*** item_type: /ENCSR255XZG/\n", - "------------------- https://test.encodedcc.org//ENCSR255XZG/ -------------------\n", - "\u001b[31mAverage es_time: 13.068 ± 2.72 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.475 ± 0.031 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 114.842 ± 4.813 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 221.894 ± 103.95 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage total time: 350.278 ± 104.227 ms (n=100)\u001b[0m\n", - "------------ https://v79rc1-master.demo.encodedcc.org//ENCSR255XZG/ ------------\n", - "\u001b[31mAverage es_time: 13.003 ± 5.506 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.486 ± 0.043 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 135.871 ± 104.913 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage wsgi_time: 233.545 ± 126.217 ms (n=100)\u001b[0m\n", - "\u001b[33mAverage total time: 382.906 ± 224.928 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /ENCSR749ILN/\n", - "------------------- https://test.encodedcc.org//ENCSR749ILN/ -------------------\n", - "\u001b[36mAverage es_time: 6.697 ± 3.32 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.477 ± 0.047 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 35.722 ± 6.491 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 61.932 ± 9.362 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage total time: 104.827 ± 16.282 ms (n=100)\u001b[0m\n", - "------------ https://v79rc1-master.demo.encodedcc.org//ENCSR749ILN/ ------------\n", - "\u001b[36mAverage es_time: 6.561 ± 2.738 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage queue_time: 0.462 ± 0.025 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage render_time: 31.747 ± 5.352 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage wsgi_time: 56.845 ± 6.371 ms (n=100)\u001b[0m\n", - "\u001b[36mAverage total time: 95.615 ± 12.547 ms (n=100)\u001b[0m\n", - "\n", - "\n", - "*** item_type: /ENCSR688GVV/\n", - "------------------- https://test.encodedcc.org//ENCSR688GVV/ -------------------\n" - ] - } - ], - "source": [ - "qa.check_response_time(item_types=['/ENCSR255XZG/', '/ENCSR749ILN/', '/ENCSR688GVV/', '/ENCSR301HAG/','/ENCSR315NAC/', '/ENCSR856JJB/'], n=100)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true, - "scrolled": true - }, - "outputs": [], - "source": [ - "qa.check_response_time(item_types=['/ENCSR480OHP/','/ENCSR000EMB/','/ENCSR323QIP/','/ENCSR718AXQ/','/ENCSR165BGV/','/ENCSR384KAN/','/ENCSR330FXL/','/ENCSR825UNV/','/ENCSR089EOA/'], n=100)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "qa.check_response_time(item_types=['/ENCAB830JLB/','/ENCAB000BKR/','/ENCAB284TTY/','/ENCAB294YUD/','/ENCAB000AOC/','/ENCAB301QZF/','/ENCAB000ANM/','/ENCAB000ANU/','/ENCAB445KMF/','/ENCAB000BAY/'], n=100)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "qa.check_response_time(item_types=['/ENCBS787TFV/','/ENCBS676QAV/','/ENCBS996IWU/','/ENCBS913XJP/','/ENCBS565NTN/','/ENCBS896YZO/','/ENCBS280NYD/'], n=100)" - ] - } - ], - "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": "3.5.1" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/jupyter_notebooks/profiling/v79rc1 vs v78-test.ipynb b/jupyter_notebooks/profiling/v79rc1 vs v78-test.ipynb new file mode 100644 index 00000000..40054725 --- /dev/null +++ b/jupyter_notebooks/profiling/v79rc1 vs v78-test.ipynb @@ -0,0 +1,830 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import sys\n", + "sys.path.append('../..')\n", + "import qancode" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "#comparing to v65rc2 site\n", + "qa = qancode.QANCODE(rc_url=\"https://v79rc1-master.demo.encodedcc.org/\", prod_url=\"https://test.encodedcc.org/\")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Checking response time\n", + "\n", + "*** item_type: /\n", + "------------------------- https://test.encodedcc.org// -------------------------\n", + "\u001b[36mAverage es_time: 2.404 ± 0.235 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.508 ± 0.021 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 5.502 ± 1.384 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 12.039 ± 1.406 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 20.454 ± 2.78 ms (n=100)\u001b[0m\n", + "------------------ https://v79rc1-master.demo.encodedcc.org// ------------------\n", + "\u001b[36mAverage es_time: 2.174 ± 0.228 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.362 ± 0.032 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 3.826 ± 0.929 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 9.435 ± 0.931 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 15.798 ± 1.837 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /search/?type=Experiment\n", + "------------- https://test.encodedcc.org//search/?type=Experiment --------------\n", + "\u001b[31mAverage es_time: 25.89 ± 11.699 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.561 ± 0.022 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 149.262 ± 6.897 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 200.628 ± 91.668 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 376.342 ± 98.67 ms (n=100)\u001b[0m\n", + "------ https://v79rc1-master.demo.encodedcc.org//search/?type=Experiment -------\n", + "\u001b[31mAverage es_time: 24.531 ± 10.934 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.487 ± 0.015 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 114.802 ± 11.71 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 155.372 ± 18.369 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 295.192 ± 36.709 ms (n=100)\u001b[0m\n", + "\n" + ] + } + ], + "source": [ + "qa.check_response_time(item_types=[\"/\",\"/search/?type=Experiment\"], n=100)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Checking response time\n", + "\n", + "*** item_type: /search/?searchTerm=K562\n", + "------------- https://test.encodedcc.org//search/?searchTerm=K562 --------------\n", + "\u001b[31mAverage es_time: 243.887 ± 13.728 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.53 ± 0.027 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 31.258 ± 8.252 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 283.582 ± 16.393 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 559.256 ± 32.844 ms (n=100)\u001b[0m\n", + "------ https://v79rc1-master.demo.encodedcc.org//search/?searchTerm=K562 -------\n", + "\u001b[31mAverage es_time: 229.142 ± 53.214 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.449 ± 0.019 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 23.096 ± 6.913 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 260.47 ± 57.134 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 513.156 ± 111.757 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /search/?searchTerm=DNA+binding\n", + "---------- https://test.encodedcc.org//search/?searchTerm=DNA+binding ----------\n", + "\u001b[31mAverage es_time: 347.761 ± 17.468 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.53 ± 0.025 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 30.999 ± 7.841 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 390.278 ± 20.23 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 769.568 ± 39.665 ms (n=100)\u001b[0m\n", + "--------- https://v79rc1-master.demo.encodedcc.org//search/?searchTerm=DNA+binding ---------\n", + "\u001b[31mAverage es_time: 335.342 ± 37.242 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.458 ± 0.013 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 25.927 ± 7.12 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 372.485 ± 38.966 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 734.211 ± 76.323 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /search/?searchTerm=human\n", + "------------- https://test.encodedcc.org//search/?searchTerm=human -------------\n", + "\u001b[31mAverage es_time: 258.99 ± 29.823 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.52 ± 0.035 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 33.276 ± 8.769 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 299.811 ± 29.008 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 592.597 ± 57.996 ms (n=100)\u001b[0m\n", + "------ https://v79rc1-master.demo.encodedcc.org//search/?searchTerm=human ------\n", + "\u001b[31mAverage es_time: 226.786 ± 25.529 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.448 ± 0.018 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 23.619 ± 5.863 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 257.346 ± 26.401 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 508.198 ± 52.588 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /search/?searchTerm=H3K36me3\n", + "----------- https://test.encodedcc.org//search/?searchTerm=H3K36me3 ------------\n", + "\u001b[31mAverage es_time: 257.811 ± 85.366 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.54 ± 0.029 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 36.654 ± 8.471 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 302.62 ± 86.173 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 597.625 ± 172.336 ms (n=100)\u001b[0m\n", + "---- https://v79rc1-master.demo.encodedcc.org//search/?searchTerm=H3K36me3 -----\n", + "\u001b[31mAverage es_time: 227.189 ± 19.983 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.452 ± 0.015 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 26.469 ± 6.945 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 261.334 ± 21.695 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 515.444 ± 43.258 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /search/?searchTerm=CTCF\n", + "------------- https://test.encodedcc.org//search/?searchTerm=CTCF --------------\n", + "\u001b[31mAverage es_time: 255.481 ± 16.197 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.525 ± 0.023 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 25.536 ± 6.221 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 288.336 ± 18.506 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 569.878 ± 36.892 ms (n=100)\u001b[0m\n", + "------ https://v79rc1-master.demo.encodedcc.org//search/?searchTerm=CTCF -------\n", + "\u001b[31mAverage es_time: 228.078 ± 19.633 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.446 ± 0.02 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 21.9 ± 5.966 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 256.862 ± 20.723 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 507.286 ± 41.297 ms (n=100)\u001b[0m\n", + "\n" + ] + } + ], + "source": [ + "qa.check_response_time(item_types=[\"/search/?searchTerm=K562\", \"/search/?searchTerm=DNA+binding\", \"/search/?searchTerm=human\", \"/search/?searchTerm=H3K36me3\", \"/search/?searchTerm=CTCF\"], n=100)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Checking response time\n", + "\n", + "*** item_type: /ENCSR255XZG/\n", + "------------------- https://test.encodedcc.org//ENCSR255XZG/ -------------------\n", + "\u001b[31mAverage es_time: 13.01 ± 1.976 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.48 ± 0.036 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 117.148 ± 6.335 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 225.437 ± 110.076 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 356.075 ± 111.526 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCSR255XZG/ ------------\n", + "\u001b[33mAverage es_time: 11.754 ± 4.162 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.473 ± 0.018 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 109.36 ± 6.365 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 205.708 ± 55.147 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 327.295 ± 56.641 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR749ILN/\n", + "------------------- https://test.encodedcc.org//ENCSR749ILN/ -------------------\n", + "\u001b[36mAverage es_time: 5.651 ± 0.31 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.47 ± 0.032 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 34.913 ± 4.789 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 59.295 ± 4.951 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 100.328 ± 9.668 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCSR749ILN/ ------------\n", + "\u001b[36mAverage es_time: 5.627 ± 0.605 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.459 ± 0.024 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 30.443 ± 4.97 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 69.345 ± 104.501 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 105.874 ± 104.757 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR688GVV/\n", + "------------------- https://test.encodedcc.org//ENCSR688GVV/ -------------------\n", + "\u001b[33mAverage es_time: 11.68 ± 2.061 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.483 ± 0.035 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 66.847 ± 5.011 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 122.691 ± 5.585 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 201.7 ± 10.929 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCSR688GVV/ ------------\n", + "\u001b[33mAverage es_time: 11.879 ± 5.102 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.474 ± 0.017 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 63.167 ± 5.46 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 129.356 ± 78.66 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 204.875 ± 79.259 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR301HAG/\n", + "------------------- https://test.encodedcc.org//ENCSR301HAG/ -------------------\n", + "\u001b[36mAverage es_time: 3.122 ± 0.149 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.465 ± 0.015 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 11.974 ± 5.726 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 20.819 ± 5.764 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 36.38 ± 11.508 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCSR301HAG/ ------------\n", + "\u001b[36mAverage es_time: 3.093 ± 0.078 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.474 ± 0.021 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 9.091 ± 2.555 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 17.899 ± 2.749 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 30.556 ± 5.273 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR315NAC/\n", + "------------------- https://test.encodedcc.org//ENCSR315NAC/ -------------------\n", + "\u001b[33mAverage es_time: 8.938 ± 2.33 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.46 ± 0.021 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 51.138 ± 6.462 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 97.203 ± 50.053 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 157.739 ± 51.741 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCSR315NAC/ ------------\n", + "\u001b[33mAverage es_time: 9.613 ± 5.057 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.466 ± 0.021 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 49.99 ± 5.765 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 96.104 ± 43.537 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 156.172 ± 46.008 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR856JJB/\n", + "------------------- https://test.encodedcc.org//ENCSR856JJB/ -------------------\n", + "\u001b[36mAverage es_time: 7.394 ± 0.798 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.461 ± 0.016 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 46.195 ± 6.454 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 80.896 ± 6.632 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 134.946 ± 13.233 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCSR856JJB/ ------------\n", + "\u001b[33mAverage es_time: 8.427 ± 0.161 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.465 ± 0.027 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 43.103 ± 6.219 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 78.958 ± 6.274 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 130.952 ± 12.44 ms (n=100)\u001b[0m\n", + "\n" + ] + } + ], + "source": [ + "qa.check_response_time(item_types=['/ENCSR255XZG/', '/ENCSR749ILN/', '/ENCSR688GVV/', '/ENCSR301HAG/','/ENCSR315NAC/', '/ENCSR856JJB/'], n=100)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Checking response time\n", + "\n", + "*** item_type: /ENCSR480OHP/\n", + "------------------- https://test.encodedcc.org//ENCSR480OHP/ -------------------\n", + "\u001b[36mAverage es_time: 5.873 ± 1.95 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.455 ± 0.014 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 46.45 ± 5.539 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 92.999 ± 90.626 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 145.777 ± 91.222 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCSR480OHP/ ------------\n", + "\u001b[36mAverage es_time: 6.912 ± 5.146 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.452 ± 0.021 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 42.995 ± 4.913 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 89.177 ± 81.967 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 139.536 ± 82.469 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR000EMB/\n", + "------------------- https://test.encodedcc.org//ENCSR000EMB/ -------------------\n", + "\u001b[36mAverage es_time: 7.942 ± 3.308 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.458 ± 0.018 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 48.343 ± 6.585 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 92.638 ± 86.933 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 149.382 ± 87.082 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCSR000EMB/ ------------\n", + "\u001b[33mAverage es_time: 8.96 ± 2.77 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.468 ± 0.022 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 44.549 ± 6.358 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 81.06 ± 6.881 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 135.037 ± 13.612 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR323QIP/\n", + "------------------- https://test.encodedcc.org//ENCSR323QIP/ -------------------\n", + "\u001b[31mAverage es_time: 18.097 ± 3.054 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.467 ± 0.017 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 136.435 ± 4.56 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 278.618 ± 146.403 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 433.617 ± 146.668 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCSR323QIP/ ------------\n" + ] + }, + { + "ename": "AssertionError", + "evalue": "", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mAssertionError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mqa\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcheck_response_time\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem_types\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'/ENCSR480OHP/'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'/ENCSR000EMB/'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'/ENCSR323QIP/'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'/ENCSR718AXQ/'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'/ENCSR165BGV/'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'/ENCSR384KAN/'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'/ENCSR330FXL/'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'/ENCSR825UNV/'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'/ENCSR089EOA/'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m100\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;32m/Users/hitz/Documents/workspace/pyencoded-tools/qancode/qancode.py\u001b[0m in \u001b[0;36mcheck_response_time\u001b[0;34m(self, urls, item_types, n)\u001b[0m\n\u001b[1;32m 492\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mitem\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 493\u001b[0m \u001b[0murl\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0murl\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mitem\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 494\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_average_time_for_get\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 495\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/Users/hitz/Documents/workspace/pyencoded-tools/qancode/qancode.py\u001b[0m in \u001b[0;36m_average_time_for_get\u001b[0;34m(self, url, n)\u001b[0m\n\u001b[1;32m 472\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_average_time_for_get\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 473\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_print_header\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 474\u001b[0;31m \u001b[0mtime_headers\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_time_headers\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 475\u001b[0m \u001b[0mparsed_headers\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_parse_header\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mh\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mh\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtime_headers\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 476\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;32min\u001b[0m \u001b[0msorted\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mparsed_headers\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/Users/hitz/Documents/workspace/pyencoded-tools/qancode/qancode.py\u001b[0m in \u001b[0;36m_get_time_headers\u001b[0;34m(url, n)\u001b[0m\n\u001b[1;32m 438\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 439\u001b[0m \u001b[0mr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrequests\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 440\u001b[0;31m \u001b[0;32massert\u001b[0m \u001b[0mr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstatus_code\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m200\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 441\u001b[0m \u001b[0mtime_headers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 442\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mtime_headers\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mAssertionError\u001b[0m: " + ] + } + ], + "source": [ + "qa.check_response_time(item_types=['/ENCSR480OHP/','/ENCSR000EMB/','/ENCSR323QIP/','/ENCSR718AXQ/','/ENCSR165BGV/','/ENCSR384KAN/','/ENCSR330FXL/','/ENCSR825UNV/','/ENCSR089EOA/'], n=100)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Checking response time\n", + "\n", + "*** item_type: /ENCAB830JLB/\n", + "------------------- https://test.encodedcc.org//ENCAB830JLB/ -------------------\n", + "\u001b[36mAverage es_time: 3.641 ± 0.588 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.445 ± 0.014 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 48.184 ± 5.886 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 77.284 ± 6.366 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 129.553 ± 12.186 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCAB830JLB/ ------------\n", + "\u001b[36mAverage es_time: 4.022 ± 0.147 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.439 ± 0.02 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 39.692 ± 6.411 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 68.649 ± 6.515 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 112.802 ± 12.918 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCAB000BKR/\n", + "------------------- https://test.encodedcc.org//ENCAB000BKR/ -------------------\n", + "\u001b[36mAverage es_time: 2.827 ± 0.484 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.442 ± 0.014 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 20.994 ± 7.188 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 35.146 ± 7.301 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 59.409 ± 14.493 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCAB000BKR/ ------------\n", + "\u001b[36mAverage es_time: 2.792 ± 0.386 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.442 ± 0.02 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 18.934 ± 5.421 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 32.854 ± 5.487 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 55.023 ± 10.885 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCAB284TTY/\n", + "------------------- https://test.encodedcc.org//ENCAB284TTY/ -------------------\n", + "\u001b[36mAverage es_time: 4.513 ± 0.964 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.444 ± 0.013 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 52.432 ± 4.794 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 91.504 ± 4.914 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 148.893 ± 9.585 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCAB284TTY/ ------------\n", + "\u001b[36mAverage es_time: 4.627 ± 1.038 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.435 ± 0.022 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 50.796 ± 4.824 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 90.083 ± 5.243 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 145.941 ± 10.108 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCAB294YUD/\n", + "------------------- https://test.encodedcc.org//ENCAB294YUD/ -------------------\n", + "\u001b[36mAverage es_time: 2.417 ± 1.598 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.465 ± 0.019 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 7.173 ± 2.18 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 12.826 ± 2.658 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 22.881 ± 5.302 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCAB294YUD/ ------------\n", + "\u001b[36mAverage es_time: 2.333 ± 1.92 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.376 ± 0.031 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 5.378 ± 1.252 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 10.653 ± 2.299 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 18.74 ± 4.538 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCAB000AOC/\n", + "------------------- https://test.encodedcc.org//ENCAB000AOC/ -------------------\n", + "\u001b[36mAverage es_time: 3.125 ± 0.571 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.443 ± 0.015 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 32.368 ± 6.97 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 57.044 ± 77.728 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 92.981 ± 79.576 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCAB000AOC/ ------------\n", + "\u001b[36mAverage es_time: 3.018 ± 0.407 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.427 ± 0.026 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 27.76 ± 5.575 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 44.384 ± 5.749 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 75.589 ± 11.395 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCAB301QZF/\n", + "------------------- https://test.encodedcc.org//ENCAB301QZF/ -------------------\n", + "\u001b[36mAverage es_time: 2.529 ± 0.557 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.435 ± 0.011 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 13.351 ± 4.587 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 21.135 ± 4.748 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 37.451 ± 9.516 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCAB301QZF/ ------------\n", + "\u001b[36mAverage es_time: 2.317 ± 0.199 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.412 ± 0.026 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 11.543 ± 3.061 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 18.933 ± 3.086 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 33.205 ± 6.145 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCAB000ANM/\n", + "------------------- https://test.encodedcc.org//ENCAB000ANM/ -------------------\n", + "\u001b[36mAverage es_time: 3.365 ± 0.543 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.449 ± 0.019 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 25.649 ± 6.054 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 41.631 ± 6.094 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 71.094 ± 12.164 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCAB000ANM/ ------------\n", + "\u001b[36mAverage es_time: 2.976 ± 0.374 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.433 ± 0.026 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 24.657 ± 5.193 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 40.138 ± 5.301 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 68.204 ± 10.516 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCAB000ANU/\n", + "------------------- https://test.encodedcc.org//ENCAB000ANU/ -------------------\n", + "\u001b[36mAverage es_time: 2.821 ± 0.68 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.443 ± 0.012 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 22.802 ± 8.603 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 35.033 ± 8.642 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 61.099 ± 17.157 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCAB000ANU/ ------------\n", + "\u001b[36mAverage es_time: 2.9 ± 0.094 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.427 ± 0.028 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 17.907 ± 5.177 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 30.139 ± 5.14 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 51.373 ± 10.3 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCAB445KMF/\n", + "------------------- https://test.encodedcc.org//ENCAB445KMF/ -------------------\n", + "\u001b[36mAverage es_time: 2.5 ± 0.377 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.439 ± 0.012 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 19.915 ± 7.131 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 30.476 ± 7.11 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 53.329 ± 14.249 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCAB445KMF/ ------------\n", + "\u001b[36mAverage es_time: 2.517 ± 0.333 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.414 ± 0.026 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 15.434 ± 3.951 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 25.738 ± 4.017 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 44.103 ± 8.02 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCAB000BAY/\n", + "------------------- https://test.encodedcc.org//ENCAB000BAY/ -------------------\n", + "\u001b[36mAverage es_time: 2.909 ± 0.624 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.437 ± 0.013 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 29.224 ± 6.951 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 44.764 ± 6.986 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 77.334 ± 13.869 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCAB000BAY/ ------------\n", + "\u001b[36mAverage es_time: 2.921 ± 0.525 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.426 ± 0.027 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 26.102 ± 5.384 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 41.435 ± 5.525 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 70.882 ± 10.943 ms (n=100)\u001b[0m\n", + "\n" + ] + } + ], + "source": [ + "qa.check_response_time(item_types=['/ENCAB830JLB/','/ENCAB000BKR/','/ENCAB284TTY/','/ENCAB294YUD/','/ENCAB000AOC/','/ENCAB301QZF/','/ENCAB000ANM/','/ENCAB000ANU/','/ENCAB445KMF/','/ENCAB000BAY/'], n=100)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Checking response time\n", + "\n", + "*** item_type: /ENCBS787TFV/\n", + "------------------- https://test.encodedcc.org//ENCBS787TFV/ -------------------\n", + "\u001b[36mAverage es_time: 2.403 ± 0.42 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.445 ± 0.02 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 7.142 ± 1.97 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 13.338 ± 2.337 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 23.328 ± 4.28 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCBS787TFV/ ------------\n", + "\u001b[36mAverage es_time: 2.538 ± 0.657 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.433 ± 0.025 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 6.216 ± 1.706 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 12.281 ± 2.349 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 21.467 ± 4.413 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCBS676QAV/\n", + "------------------- https://test.encodedcc.org//ENCBS676QAV/ -------------------\n", + "\u001b[36mAverage es_time: 5.192 ± 7.029 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.438 ± 0.019 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 7.877 ± 2.036 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 17.079 ± 8.361 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 30.587 ± 16.553 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCBS676QAV/ ------------\n", + "\u001b[36mAverage es_time: 2.942 ± 3.495 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.388 ± 0.029 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 6.245 ± 1.047 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 12.918 ± 4.359 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 22.492 ± 8.517 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCBS996IWU/\n", + "------------------- https://test.encodedcc.org//ENCBS996IWU/ -------------------\n", + "\u001b[36mAverage es_time: 2.267 ± 0.249 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.438 ± 0.013 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 8.137 ± 1.523 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 13.991 ± 1.669 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 24.833 ± 3.233 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCBS996IWU/ ------------\n", + "\u001b[36mAverage es_time: 3.038 ± 3.2 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.397 ± 0.026 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 7.34 ± 0.962 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 13.823 ± 3.716 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 24.598 ± 7.356 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCBS913XJP/\n", + "------------------- https://test.encodedcc.org//ENCBS913XJP/ -------------------\n", + "\u001b[36mAverage es_time: 2.319 ± 0.201 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.447 ± 0.018 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 5.89 ± 1.142 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 11.781 ± 1.193 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 20.438 ± 2.332 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCBS913XJP/ ------------\n", + "\u001b[36mAverage es_time: 2.47 ± 0.221 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.432 ± 0.026 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 5.988 ± 1.381 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 11.897 ± 1.491 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 20.787 ± 2.911 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCBS565NTN/\n", + "------------------- https://test.encodedcc.org//ENCBS565NTN/ -------------------\n", + "\u001b[36mAverage es_time: 2.216 ± 0.301 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.438 ± 0.014 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 6.133 ± 1.348 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 11.808 ± 1.464 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 20.594 ± 2.821 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCBS565NTN/ ------------\n" + ] + }, + { + "ename": "AssertionError", + "evalue": "", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mAssertionError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mqa\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcheck_response_time\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem_types\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'/ENCBS787TFV/'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'/ENCBS676QAV/'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'/ENCBS996IWU/'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'/ENCBS913XJP/'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'/ENCBS565NTN/'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'/ENCBS896YZO/'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'/ENCBS280NYD/'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m100\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;32m/Users/hitz/Documents/workspace/pyencoded-tools/qancode/qancode.py\u001b[0m in \u001b[0;36mcheck_response_time\u001b[0;34m(self, urls, item_types, n)\u001b[0m\n\u001b[1;32m 492\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mitem\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 493\u001b[0m \u001b[0murl\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0murl\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mitem\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 494\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_average_time_for_get\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 495\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/Users/hitz/Documents/workspace/pyencoded-tools/qancode/qancode.py\u001b[0m in \u001b[0;36m_average_time_for_get\u001b[0;34m(self, url, n)\u001b[0m\n\u001b[1;32m 472\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_average_time_for_get\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 473\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_print_header\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 474\u001b[0;31m \u001b[0mtime_headers\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_time_headers\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 475\u001b[0m \u001b[0mparsed_headers\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_parse_header\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mh\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mh\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtime_headers\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 476\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;32min\u001b[0m \u001b[0msorted\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mparsed_headers\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/Users/hitz/Documents/workspace/pyencoded-tools/qancode/qancode.py\u001b[0m in \u001b[0;36m_get_time_headers\u001b[0;34m(url, n)\u001b[0m\n\u001b[1;32m 438\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 439\u001b[0m \u001b[0mr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrequests\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 440\u001b[0;31m \u001b[0;32massert\u001b[0m \u001b[0mr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstatus_code\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m200\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 441\u001b[0m \u001b[0mtime_headers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 442\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mtime_headers\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mAssertionError\u001b[0m: " + ] + } + ], + "source": [ + "qa.check_response_time(item_types=['/ENCBS787TFV/','/ENCBS676QAV/','/ENCBS996IWU/','/ENCBS913XJP/','/ENCBS565NTN/','/ENCBS896YZO/','/ENCBS280NYD/'], n=100)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Checking response time\n", + "\n", + "*** item_type: /ENCBS565NTN/\n", + "------------------- https://test.encodedcc.org//ENCBS565NTN/ -------------------\n", + "\u001b[36mAverage es_time: 2.219 ± 0.136 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.442 ± 0.021 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 5.749 ± 1.163 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 20.038 ± 86.771 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 28.447 ± 86.733 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCBS565NTN/ ------------\n", + "\u001b[36mAverage es_time: 2.36 ± 0.089 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.425 ± 0.033 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 5.309 ± 0.394 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 10.975 ± 0.438 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 19.069 ± 0.789 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCBS896YZO/\n", + "------------------- https://test.encodedcc.org//ENCBS896YZO/ -------------------\n", + "\u001b[36mAverage es_time: 5.197 ± 6.644 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.437 ± 0.014 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 11.909 ± 3.419 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 21.76 ± 7.552 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 39.303 ± 14.927 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCBS896YZO/ ------------\n", + "\u001b[36mAverage es_time: 3.033 ± 3.455 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.403 ± 0.031 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 12.625 ± 3.998 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 19.969 ± 5.233 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 36.03 ± 10.391 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCBS280NYD/\n", + "------------------- https://test.encodedcc.org//ENCBS280NYD/ -------------------\n", + "\u001b[36mAverage es_time: 6.19 ± 9.361 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.428 ± 0.013 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 5.695 ± 1.007 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 15.325 ± 9.702 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 27.639 ± 19.246 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCBS280NYD/ ------------\n", + "\u001b[36mAverage es_time: 2.44 ± 2.423 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.377 ± 0.03 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 5.559 ± 1.28 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 11.122 ± 2.931 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 19.498 ± 5.765 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR323QIP/\n", + "------------------- https://test.encodedcc.org//ENCSR323QIP/ -------------------\n", + "\u001b[31mAverage es_time: 18.436 ± 3.353 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.502 ± 0.038 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 139.399 ± 5.342 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 269.148 ± 88.498 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 427.485 ± 89.72 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCSR323QIP/ ------------\n", + "\u001b[31mAverage es_time: 15.842 ± 3.518 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.473 ± 0.021 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 137.326 ± 5.019 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage wsgi_time: 276.052 ± 140.644 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 429.693 ± 142.372 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR718AXQ/\n", + "------------------- https://test.encodedcc.org//ENCSR718AXQ/ -------------------\n", + "\u001b[36mAverage es_time: 5.518 ± 0.471 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.483 ± 0.037 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 25.164 ± 7.685 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 41.21 ± 7.735 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 72.375 ± 15.422 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCSR718AXQ/ ------------\n", + "\u001b[36mAverage es_time: 6.655 ± 3.107 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.471 ± 0.021 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 17.897 ± 6.613 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 34.738 ± 7.684 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 59.761 ± 15.09 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR165BGV/\n", + "------------------- https://test.encodedcc.org//ENCSR165BGV/ -------------------\n", + "\u001b[36mAverage es_time: 3.497 ± 1.819 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.48 ± 0.035 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 21.242 ± 8.361 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 36.226 ± 8.561 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 61.445 ± 17.05 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCSR165BGV/ ------------\n", + "\u001b[36mAverage es_time: 3.543 ± 2.666 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.462 ± 0.021 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 18.487 ± 5.864 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 33.147 ± 6.39 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 55.638 ± 12.723 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR384KAN/\n", + "------------------- https://test.encodedcc.org//ENCSR384KAN/ -------------------\n", + "\u001b[33mAverage es_time: 8.253 ± 1.709 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.492 ± 0.037 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 50.718 ± 7.612 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 110.959 ± 119.528 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 170.421 ± 120.354 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCSR384KAN/ ------------\n", + "\u001b[33mAverage es_time: 8.045 ± 0.787 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.481 ± 0.038 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 49.812 ± 6.276 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 96.158 ± 39.425 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage total time: 154.496 ± 39.854 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR330FXL/\n", + "------------------- https://test.encodedcc.org//ENCSR330FXL/ -------------------\n", + "\u001b[36mAverage es_time: 6.449 ± 7.617 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.469 ± 0.031 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 28.098 ± 7.847 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 48.727 ± 12.311 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 83.743 ± 24.285 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCSR330FXL/ ------------\n", + "\u001b[36mAverage es_time: 4.021 ± 3.05 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.478 ± 0.036 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage render_time: 22.992 ± 4.531 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage wsgi_time: 41.206 ± 6.162 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage total time: 68.697 ± 12.029 ms (n=100)\u001b[0m\n", + "\n", + "\n", + "*** item_type: /ENCSR825UNV/\n", + "------------------- https://test.encodedcc.org//ENCSR825UNV/ -------------------\n" + ] + } + ], + "source": [ + "qa.check_response_time(item_types=['/ENCBS565NTN/','/ENCBS896YZO/','/ENCBS280NYD/','/ENCSR323QIP/','/ENCSR718AXQ/','/ENCSR165BGV/','/ENCSR384KAN/','/ENCSR330FXL/','/ENCSR825UNV/','/ENCSR089EOA/'], n=100)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Checking response time\n", + "\n", + "*** item_type: /ENCSR825UNV/\n", + "------------------- https://test.encodedcc.org//ENCSR825UNV/ -------------------\n", + "\u001b[31mAverage es_time: 22.765 ± 5.139 ms (n=100)\u001b[0m\n", + "\u001b[36mAverage queue_time: 0.464 ± 0.015 ms (n=100)\u001b[0m\n", + "\u001b[33mAverage render_time: 217.639 ± 8.502 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage wsgi_time: 430.781 ± 184.704 ms (n=100)\u001b[0m\n", + "\u001b[31mAverage total time: 671.648 ± 188.428 ms (n=100)\u001b[0m\n", + "------------ https://v79rc1-master.demo.encodedcc.org//ENCSR825UNV/ ------------\n" + ] + }, + { + "ename": "AssertionError", + "evalue": "", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mAssertionError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mqa\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcheck_response_time\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem_types\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'/ENCSR825UNV/'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'/ENCSR089EOA/'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m100\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;32m/Users/hitz/Documents/workspace/pyencoded-tools/qancode/qancode.py\u001b[0m in \u001b[0;36mcheck_response_time\u001b[0;34m(self, urls, item_types, n)\u001b[0m\n\u001b[1;32m 492\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mitem\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 493\u001b[0m \u001b[0murl\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0murl\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mitem\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 494\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_average_time_for_get\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 495\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/Users/hitz/Documents/workspace/pyencoded-tools/qancode/qancode.py\u001b[0m in \u001b[0;36m_average_time_for_get\u001b[0;34m(self, url, n)\u001b[0m\n\u001b[1;32m 472\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_average_time_for_get\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 473\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_print_header\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 474\u001b[0;31m \u001b[0mtime_headers\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_time_headers\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 475\u001b[0m \u001b[0mparsed_headers\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_parse_header\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mh\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mh\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtime_headers\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 476\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;32min\u001b[0m \u001b[0msorted\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mparsed_headers\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/Users/hitz/Documents/workspace/pyencoded-tools/qancode/qancode.py\u001b[0m in \u001b[0;36m_get_time_headers\u001b[0;34m(url, n)\u001b[0m\n\u001b[1;32m 438\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 439\u001b[0m \u001b[0mr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrequests\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 440\u001b[0;31m \u001b[0;32massert\u001b[0m \u001b[0mr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstatus_code\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m200\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 441\u001b[0m \u001b[0mtime_headers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 442\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mtime_headers\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mAssertionError\u001b[0m: " + ] + } + ], + "source": [ + "qa.check_response_time(item_types=['/ENCSR825UNV/','/ENCSR089EOA/'], n=100)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { 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