Interacting_with_Airavata_using_ipython_Notebook/Admin-User/.ipynb_checkpoints/Admin User-checkpoint.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import ConfigParser\n",
    "import pandas as pd\n",
    "import datetime\n",
    "from datetime import datetime\n",
    "import calendar\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "conf = ConfigParser.RawConfigParser()\n",
    "conf.read('cli.properties')\n",
    "hostName = conf.get('AiravataServer', 'host')\n",
    "port = conf.get('AiravataServer', 'port')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.16.0\n",
      "0.16.0\n",
      "\n",
      "Welcome to Airavata CLI v0.0.1 - Wirtten in python\n",
      "\n",
      "\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "from airavata_cli import AiravataCLI\n",
    "airavata_cli = AiravataCLI(hostName, int(port))\n",
    "print(airavata_cli.printVersion())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Making Sure we are connected to the right Gateway"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Gateway(gatewayId='Ultrascan_Production', emailAddress=None, domain=None, gatewayName='Ultrascan_Production')]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "airavata_cli.get_gatewaylist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## List of Resources the Gateway uses"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('alamo.uthscsa.edu_4793b5cc-b991-4e43-b82d-17163b64ef29',\n",
       "  'alamo.uthscsa.edu'),\n",
       " ('Jureca_32098185-4396-4c11-afb7-26e991a03476', 'Jureca'),\n",
       " ('comet.sdsc.edu_f24b0bba-5230-498d-97e2-46a975ee035b', 'comet.sdsc.edu'),\n",
       " ('gordon.sdsc.edu_f9363997-4614-477f-847e-79d262ee8ef7', 'gordon.sdsc.edu'),\n",
       " ('ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aad1f8310ecf',\n",
       "  'ls5.tacc.utexas.edu'),\n",
       " ('stampede.tacc.xsede.org_bf7958ae-f9d4-468b-b146-a201fb89bf12',\n",
       "  'stampede.tacc.xsede.org')]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "airavata_cli.computer_resources().items()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>Name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>alamo.uthscsa.edu_4793b5cc-b991-4e43-b82d-1716...</td>\n",
       "      <td>alamo.uthscsa.edu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jureca_32098185-4396-4c11-afb7-26e991a03476</td>\n",
       "      <td>Jureca</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>comet.sdsc.edu_f24b0bba-5230-498d-97e2-46a975e...</td>\n",
       "      <td>comet.sdsc.edu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>gordon.sdsc.edu_f9363997-4614-477f-847e-79d262...</td>\n",
       "      <td>gordon.sdsc.edu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aa...</td>\n",
       "      <td>ls5.tacc.utexas.edu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>stampede.tacc.xsede.org_bf7958ae-f9d4-468b-b14...</td>\n",
       "      <td>stampede.tacc.xsede.org</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  Id                     Name\n",
       "0  alamo.uthscsa.edu_4793b5cc-b991-4e43-b82d-1716...        alamo.uthscsa.edu\n",
       "1        Jureca_32098185-4396-4c11-afb7-26e991a03476                   Jureca\n",
       "2  comet.sdsc.edu_f24b0bba-5230-498d-97e2-46a975e...           comet.sdsc.edu\n",
       "3  gordon.sdsc.edu_f9363997-4614-477f-847e-79d262...          gordon.sdsc.edu\n",
       "4  ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aa...      ls5.tacc.utexas.edu\n",
       "5  stampede.tacc.xsede.org_bf7958ae-f9d4-468b-b14...  stampede.tacc.xsede.org"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compute_resources = pd.DataFrame(list(airavata_cli.computer_resources().items()), columns=[\"Id\", \"Name\"])\n",
    "compute_resources"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Some other custom functions which can be created"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[ApplicationInterfaceDescription(applicationName='Ultrascan', applicationInputs=[InputDataObjectType(userFriendlyDescription='Ultrascan HPC Input Tar File', name='Input_Tar_File', dataStaged=False, value='', applicationArgument='', isRequired=False, standardInput=False, requiredToAddedToCommandLine=True, type=3, inputOrder=1, metaData=''), InputDataObjectType(userFriendlyDescription='Batches for multi-wavelength data processing', name='Parallel_Group_Count', dataStaged=False, value='-mgroupcount=1', applicationArgument='', isRequired=False, standardInput=False, requiredToAddedToCommandLine=True, type=0, inputOrder=3, metaData=''), InputDataObjectType(userFriendlyDescription='Wall Clock Limit on the Compute Resource', name='Wall_Time', dataStaged=False, value='-walltime=60', applicationArgument='', isRequired=True, standardInput=False, requiredToAddedToCommandLine=True, type=0, inputOrder=2, metaData='')], applicationInterfaceId='Ultrascan_0ed937f6-26af-4c54-8064-3be082411e46', applicationDescription='Ultrascan Version 3 Interface', applicationOutputs=[OutputDataObjectType(dataMovement=True, name='output', value='output/analysis-results.tar', applicationArgument='', isRequired=True, searchQuery='', location='output', requiredToAddedToCommandLine=False, outputStreaming=False, type=3), OutputDataObjectType(dataMovement=True, name='Ultrascan-Standard-Error', value='', applicationArgument='', isRequired=True, searchQuery='', location='', requiredToAddedToCommandLine=False, outputStreaming=False, type=5), OutputDataObjectType(dataMovement=True, name='Ultrascan-Standard-Out', value='', applicationArgument='', isRequired=True, searchQuery='', location='', requiredToAddedToCommandLine=False, outputStreaming=False, type=4)], applicationModules=['Ultrascan_82282f1e-284f-4999-9beb-4620c485b03d']),\n",
       " ApplicationInterfaceDescription(applicationName='Ultrascan_Unicore', applicationInputs=[InputDataObjectType(userFriendlyDescription='', name='Input', dataStaged=False, value='', applicationArgument='', isRequired=True, standardInput=False, requiredToAddedToCommandLine=False, type=3, inputOrder=1, metaData=''), InputDataObjectType(userFriendlyDescription='', name='mgroupcount', dataStaged=False, value='-mgroupcount 1', applicationArgument='', isRequired=False, standardInput=False, requiredToAddedToCommandLine=True, type=0, inputOrder=2, metaData=''), InputDataObjectType(userFriendlyDescription='', name='US3INPUTARG', dataStaged=False, value='', applicationArgument='', isRequired=False, standardInput=False, requiredToAddedToCommandLine=True, type=0, inputOrder=4, metaData=''), InputDataObjectType(userFriendlyDescription='', name='walltime', dataStaged=False, value='-walltime 60', applicationArgument='', isRequired=False, standardInput=False, requiredToAddedToCommandLine=True, type=0, inputOrder=3, metaData='')], applicationInterfaceId='Ultrascan_Unicore_0e7f8522-6d75-41ba-8b09-0021e728679a', applicationDescription='Unicore Service', applicationOutputs=[OutputDataObjectType(dataMovement=True, name='Ultrascan-Unicore-Standard-Error', value='', applicationArgument='', isRequired=False, searchQuery='', location='', requiredToAddedToCommandLine=False, outputStreaming=False, type=5), OutputDataObjectType(dataMovement=True, name='Ultrascan-Unicore-Standard-Out', value='', applicationArgument='', isRequired=False, searchQuery='', location='', requiredToAddedToCommandLine=False, outputStreaming=False, type=4), OutputDataObjectType(dataMovement=True, name='US3OUT', value='analysis-results.tar', applicationArgument='', isRequired=True, searchQuery='', location='', requiredToAddedToCommandLine=False, outputStreaming=False, type=0)], applicationModules=['Ultrascan_Unicore_2471953d-5d87-4ffc-b0e6-b06c86c6206d'])]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "airavata_cli.list_of_applications('Ultrascan_Production')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[ApplicationModule(appModuleName='Ultrascan', appModuleVersion='Ultrascan Application', appModuleId='Ultrascan_82282f1e-284f-4999-9beb-4620c485b03d', appModuleDescription=''),\n",
       " ApplicationModule(appModuleName='Ultrascan_Unicore', appModuleVersion='', appModuleId='Ultrascan_Unicore_2471953d-5d87-4ffc-b0e6-b06c86c6206d', appModuleDescription='Ultrascan Unicore Application')]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "airavata_cli.module_descriptions('Ultrascan_Production')     "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "##Setting the time parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "start= datetime(2015,7,16,15,10)\n",
    "end= datetime(2016,7,17,11,59)\n",
    "fromTime = calendar.timegm(start.timetuple())\n",
    "toTime = calendar.timegm(end.timetuple())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Getting the list of Experiments executed during the above mentioned period"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "ds=airavata_cli.experiment_statistics(\"Ultrascan_Production\", fromTime*1000, toTime*1000)\n",
    "#ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>User Name</th>\n",
       "      <th>Name</th>\n",
       "      <th>Status Update</th>\n",
       "      <th>Resource Host ID</th>\n",
       "      <th>Project ID</th>\n",
       "      <th>Creation Time</th>\n",
       "      <th>Experiment ID</th>\n",
       "      <th>Execution ID</th>\n",
       "      <th>Gateway ID</th>\n",
       "      <th>Experiment Status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Daniel_Krzizike_550162c5-88f4-5624-cd19-114778...</td>\n",
       "      <td>US3-AIRA</td>\n",
       "      <td>None</td>\n",
       "      <td>ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aa...</td>\n",
       "      <td>Default_Project_4e1dede8-0925-47e6-b61c-966051...</td>\n",
       "      <td>1468618483000</td>\n",
       "      <td>US3-AIRA_36f4788f-240b-4119-aaed-18926be8165c</td>\n",
       "      <td>Ultrascan_0ed937f6-26af-4c54-8064-3be082411e46</td>\n",
       "      <td>Ultrascan_Production</td>\n",
       "      <td>COMPLETED</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Paul_Willard_098ba7b6-274c-9fb4-4915-f7ecc0c7cc1f</td>\n",
       "      <td>US3-AIRA</td>\n",
       "      <td>None</td>\n",
       "      <td>ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aa...</td>\n",
       "      <td>Default_Project_b884d629-32bf-4532-ae76-8366db...</td>\n",
       "      <td>1468616186000</td>\n",
       "      <td>US3-AIRA_408946e3-6104-48b3-a9dc-27ec03f45cb2</td>\n",
       "      <td>Ultrascan_0ed937f6-26af-4c54-8064-3be082411e46</td>\n",
       "      <td>Ultrascan_Production</td>\n",
       "      <td>COMPLETED</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Paul_Willard_098ba7b6-274c-9fb4-4915-f7ecc0c7cc1f</td>\n",
       "      <td>US3-AIRA</td>\n",
       "      <td>None</td>\n",
       "      <td>ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aa...</td>\n",
       "      <td>Default_Project_b884d629-32bf-4532-ae76-8366db...</td>\n",
       "      <td>1468615898000</td>\n",
       "      <td>US3-AIRA_270ed9fe-f0f9-4c00-936f-72c994cb2125</td>\n",
       "      <td>Ultrascan_0ed937f6-26af-4c54-8064-3be082411e46</td>\n",
       "      <td>Ultrascan_Production</td>\n",
       "      <td>COMPLETED</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Daniel_Krzizike_550162c5-88f4-5624-cd19-114778...</td>\n",
       "      <td>US3-AIRA</td>\n",
       "      <td>None</td>\n",
       "      <td>ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aa...</td>\n",
       "      <td>Default_Project_4e1dede8-0925-47e6-b61c-966051...</td>\n",
       "      <td>1468612459000</td>\n",
       "      <td>US3-AIRA_c23effff-bf70-4d77-968a-5982919eb3a0</td>\n",
       "      <td>Ultrascan_0ed937f6-26af-4c54-8064-3be082411e46</td>\n",
       "      <td>Ultrascan_Production</td>\n",
       "      <td>COMPLETED</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Daniel_Krzizike_550162c5-88f4-5624-cd19-114778...</td>\n",
       "      <td>US3-AIRA</td>\n",
       "      <td>None</td>\n",
       "      <td>ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aa...</td>\n",
       "      <td>Default_Project_4e1dede8-0925-47e6-b61c-966051...</td>\n",
       "      <td>1468612433000</td>\n",
       "      <td>US3-AIRA_2e65cd86-b4f2-4514-99c2-68c6cec880f4</td>\n",
       "      <td>Ultrascan_0ed937f6-26af-4c54-8064-3be082411e46</td>\n",
       "      <td>Ultrascan_Production</td>\n",
       "      <td>COMPLETED</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           User Name      Name Status Update  \\\n",
       "0  Daniel_Krzizike_550162c5-88f4-5624-cd19-114778...  US3-AIRA          None   \n",
       "1  Paul_Willard_098ba7b6-274c-9fb4-4915-f7ecc0c7cc1f  US3-AIRA          None   \n",
       "2  Paul_Willard_098ba7b6-274c-9fb4-4915-f7ecc0c7cc1f  US3-AIRA          None   \n",
       "3  Daniel_Krzizike_550162c5-88f4-5624-cd19-114778...  US3-AIRA          None   \n",
       "4  Daniel_Krzizike_550162c5-88f4-5624-cd19-114778...  US3-AIRA          None   \n",
       "\n",
       "                                    Resource Host ID  \\\n",
       "0  ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aa...   \n",
       "1  ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aa...   \n",
       "2  ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aa...   \n",
       "3  ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aa...   \n",
       "4  ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aa...   \n",
       "\n",
       "                                          Project ID  Creation Time  \\\n",
       "0  Default_Project_4e1dede8-0925-47e6-b61c-966051...  1468618483000   \n",
       "1  Default_Project_b884d629-32bf-4532-ae76-8366db...  1468616186000   \n",
       "2  Default_Project_b884d629-32bf-4532-ae76-8366db...  1468615898000   \n",
       "3  Default_Project_4e1dede8-0925-47e6-b61c-966051...  1468612459000   \n",
       "4  Default_Project_4e1dede8-0925-47e6-b61c-966051...  1468612433000   \n",
       "\n",
       "                                   Experiment ID  \\\n",
       "0  US3-AIRA_36f4788f-240b-4119-aaed-18926be8165c   \n",
       "1  US3-AIRA_408946e3-6104-48b3-a9dc-27ec03f45cb2   \n",
       "2  US3-AIRA_270ed9fe-f0f9-4c00-936f-72c994cb2125   \n",
       "3  US3-AIRA_c23effff-bf70-4d77-968a-5982919eb3a0   \n",
       "4  US3-AIRA_2e65cd86-b4f2-4514-99c2-68c6cec880f4   \n",
       "\n",
       "                                     Execution ID            Gateway ID  \\\n",
       "0  Ultrascan_0ed937f6-26af-4c54-8064-3be082411e46  Ultrascan_Production   \n",
       "1  Ultrascan_0ed937f6-26af-4c54-8064-3be082411e46  Ultrascan_Production   \n",
       "2  Ultrascan_0ed937f6-26af-4c54-8064-3be082411e46  Ultrascan_Production   \n",
       "3  Ultrascan_0ed937f6-26af-4c54-8064-3be082411e46  Ultrascan_Production   \n",
       "4  Ultrascan_0ed937f6-26af-4c54-8064-3be082411e46  Ultrascan_Production   \n",
       "\n",
       "  Experiment Status  \n",
       "0         COMPLETED  \n",
       "1         COMPLETED  \n",
       "2         COMPLETED  \n",
       "3         COMPLETED  \n",
       "4         COMPLETED  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "All_Experiments = []\n",
    "for i in ds.allExperiments:\n",
    "    All_Experiments.append([i.userName, i.name, i.statusUpdateTime, i.resourceHostId, i.projectId, i.creationTime, \n",
    "                                i.experimentId, i.executionId, i.gatewayId, i.experimentStatus])\n",
    "labels = [\"User Name\", \"Name\", \"Status Update\", \"Resource Host ID\", \"Project ID\", \"Creation Time\", \"Experiment ID\", \n",
    "          \"Execution ID\", \"Gateway ID\", \"Experiment Status\"]\n",
    "df = pd.DataFrame(data=All_Experiments, columns=labels)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4124, 10)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Calculating percentage use of resources"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ls5_cn = sum([1 for x, row in df.iterrows() if row[3] == 'ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aad1f8310ecf' and row[9] == 'COMPLETED'])\n",
    "stampede_cn = sum([1 for x, row in df.iterrows() if row[3] == 'stampede.tacc.xsede.org_bf7958ae-f9d4-468b-b146-a201fb89bf12' and row[9] == 'COMPLETED'])\n",
    "comet_cn = sum([1 for x, row in df.iterrows() if row[3] == 'comet.sdsc.edu_f24b0bba-5230-498d-97e2-46a975ee035b' and row[9] == 'COMPLETED'])\n",
    "gordon_cn= sum([1 for x, row in df.iterrows() if row[3] == 'gordon.sdsc.edu_f9363997-4614-477f-847e-79d262ee8ef7' and row[9] == 'COMPLETED'])\n",
    "#jureca_cn = sum([1 for x, row in df.iterrows() if row[3] == 'Jureca_32098185-4396-4c11-afb7-26e991a03476' and row[9] == 'COMPLETED'])\n",
    "alamo_cn = sum([1 for x, row in df.iterrows() if row[3] == 'alamo.uthscsa.edu_4793b5cc-b991-4e43-b82d-17163b64ef29' and row[9] == 'COMPLETED'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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p1JN8hF/yz8mpT716dkehaWWmYGmmQKsZtXcvjoMHj5dmoqNjVJ06cZKY2NRx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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x946fba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "slices= [ls5_cn,stampede_cn,comet_cn,gordon_cn,alamo_cn]\n",
    "cols = ['c','m','r','w','y']\n",
    "Hosts= [\"lonestar\",\"stampede\",\"comet\",\"gordon\" , \"alamo\"]\n",
    "plt.pie(slices,\n",
    "        labels= Hosts,\n",
    "        colors=cols,\n",
    "        startangle=90,\n",
    "        shadow= False,\n",
    "        autopct='%1.1f%%')\n",
    "\n",
    "plt.title('Percentage Use by Resources')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "##Percentage failed by resources"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ls5_fn = sum([1 for x, row in df.iterrows() if row[3] == 'ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aad1f8310ecf' and row[9] == 'FAILED'])\n",
    "stampede_fn = sum([1 for x, row in df.iterrows() if row[3] == 'stampede.tacc.xsede.org_bf7958ae-f9d4-468b-b146-a201fb89bf12' and row[9] == 'FAILED'])\n",
    "comet_fn = sum([1 for x, row in df.iterrows() if row[3] == 'comet.sdsc.edu_f24b0bba-5230-498d-97e2-46a975ee035b' and row[9] == 'FAILED'])\n",
    "gordon_fn= sum([1 for x, row in df.iterrows() if row[3] == 'gordon.sdsc.edu_f9363997-4614-477f-847e-79d262ee8ef7' and row[9] == 'FAILED'])\n",
    "#jureca_fn = sum([1 for x, row in df.iterrows() if row[3] == 'Jureca_32098185-4396-4c11-afb7-26e991a03476' and row[9] == 'FAILED'])\n",
    "alamo_fn = sum([1 for x, row in df.iterrows() if row[3] == 'alamo.uthscsa.edu_4793b5cc-b991-4e43-b82d-17163b64ef29' and row[9] == 'FAILED'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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kpIj8KCKrRKSDiLwmIstE5PWw9s4RkR9EZJ6ITBSRVBHpjxWA87WIfHmkNset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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x97d1c88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "slices= [ls5_fn,stampede_fn,comet_fn,gordon_fn,alamo_fn]\n",
    "cols = ['c','m','r','w','y']\n",
    "Hosts= [\"lonestar\",\"stampede\",\"comet\",\"gordon\" , \"alamo\"]\n",
    "plt.pie(slices,\n",
    "        labels= Hosts,\n",
    "        colors=cols,\n",
    "        startangle=90,\n",
    "        shadow= False,\n",
    "        autopct='%1.1f%%')\n",
    "\n",
    "plt.title('Percentage failure by Resources')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Percentage cancelled by resources"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ls5_xn = sum([1 for x, row in df.iterrows() if row[3] == 'ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aad1f8310ecf' and row[9] == 'CANCELED'])\n",
    "stampede_xn = sum([1 for x, row in df.iterrows() if row[3] == 'stampede.tacc.xsede.org_bf7958ae-f9d4-468b-b146-a201fb89bf12' and row[9] == 'CANCELED'])\n",
    "comet_xn = sum([1 for x, row in df.iterrows() if row[3] == 'comet.sdsc.edu_f24b0bba-5230-498d-97e2-46a975ee035b' and row[9] == 'CANCELED'])\n",
    "gordon_xn= sum([1 for x, row in df.iterrows() if row[3] == 'gordon.sdsc.edu_f9363997-4614-477f-847e-79d262ee8ef7' and row[9] == 'CANCELED'])\n",
    "#jureca_xn = sum([1 for x, row in df.iterrows() if row[3] == 'Jureca_32098185-4396-4c11-afb7-26e991a03476' and row[9] == 'CANCELED'])\n",
    "alamo_xn = sum([1 for x, row in df.iterrows() if row[3] == 'alamo.uthscsa.edu_4793b5cc-b991-4e43-b82d-17163b64ef29' and row[9] == 'CANCELED'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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UezhOHbAFqFPVA7n+CubEYOFuepyIBMi29L8B\nnEY4PIFweCQwhExmIOl0f9raisnLy1BYmKSkxKV/fxgwIJ+BA0MMGBCkpOTIxaCkpHNj9FWzI1IO\nH+4Y2hmamhI0NaU5dEhpbg7Q0hIkmQwTDMYJBpsJBA4i8l9c9yNisW3ATmAH8IGqOl3wrzLmK7Nw\nN72S19VTDAz2HoM+2w4GhxEODycQGIrq13DdfqjmdeqEeXktBAJNwH5SqUYcpxE44D0+6bB9UFXT\nnTqXMT3Awt0YY3zIJv42xhgfsnA3xhgfsnA3xhgfsnA3xhgfsnA3xhgfsnA3xhgfsnA3xhgfsnA3\nxhgfsnA3xhgfsnA3xhgfsnA3xhgfsnA3xhgfsnA3xhgfsnA3xhgfsnA3xhgfsnA3xhgfsnA3xhgf\nsnA3xhgfsnA3xhgfsnA3xhgfsnA3xhgfsnA3xhgfsnA3xhgfsnA3xhgfsnA3xhgfsnA3xhgfsnA3\nxhgfsnA3xhgf+h+TPoiKLnJ7WAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x97e6e48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "slices= [ls5_xn,stampede_xn,comet_xn,gordon_xn,alamo_xn]\n",
    "cols = ['c','m','r','w','y']\n",
    "Hosts= [\"lonestar\",\"stampede\",\"comet\",\"gordon\" , \"alamo\"]\n",
    "plt.pie(slices,\n",
    "        labels= Hosts,\n",
    "        colors=cols,\n",
    "        startangle=90,\n",
    "        shadow= False,\n",
    "        autopct='%1.1f%%')\n",
    "\n",
    "plt.title('Percentage canceled by Resources')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Number of Experiments Canceled by a user"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "number = sum([1 for x, row in df.iterrows() if row[0] == 'smarru' and row[9] == 'CANCELED'])\n",
    "number"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sorting users by the number of experiments cancelled/failed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Daniel_Krzizike_550162c5-88f4-5624-cd19-1147783ec5ed        44\n",
       "Victoria_Saenz_3963bfc5-9a55-d8f4-35f2-a98819ba7825         36\n",
       "Uma_Muthurajan_912a2d20-e858-a4b4-fdbf-6cdf8ec8e182         18\n",
       "Shaoxiong_Tian_f3c15677-e1d3-c894-7539-005f6df5e1b6         18\n",
       "Borries_Demeler_02d0c21b-1adf-9414-c175-d005bb256320         9\n",
       "Akash_Bhattacharya_65724131-4b32-bec4-5974-aa29b945deaf      9\n",
       "Ge_Yu_8d9a3ed0-135a-c974-69f5-44beb56d182f                   6\n",
       "Aysha Kinjo_Demeler_6804fe7e-35ce-f604-3905-bb73330ef346     4\n",
       "Todd_Stone_8aee0ad6-f820-8584-f18a-9a0fa325fd34              4\n",
       "Chris_Pierini_1c0bf9ca-2756-f454-355c-fbce45017f8b           4\n",
       "Gary_Gorbet_84f540d7-3276-8894-a544-fae60062b41c             3\n",
       "Borries_Demeler_0b30314f-70d9-74d4-7564-d9684b1a9a13         3\n",
       "William_Dean_e199fd03-1b9a-a214-ad3f-1d25202091c9            3\n",
       "Chris_Pierini_36b27c6b-f5ad-3794-6d81-0038d249d19b           2\n",
       "Aysha_Demeler_09d108a4-4a6c-f884-e971-5ea68f402fde           1\n",
       "Claudius_Mundoma_e1c6c320-ca98-f704-255c-b44fd6642c4d        1\n",
       "KYUNG_SU_ad389f57-0594-bd44-3986-2ea1ebe42274                1\n",
       "Daniel_Krzizike_84d7ac3a-a900-aad4-790e-1797c3e2110d         1\n",
       "Borries_Demeler_7db4a2d1-66dc-6b44-3935-40bceaa3a9a3         1\n",
       "Todd_Stone_1768d08e-c06c-7224-a58d-32bbd9d685fb              1\n",
       "Name: User Name, dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Experiment Status'] == 'CANCELED']['User Name'].value_counts().sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  Experiments Created by the hour of the day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df['hour_of_day'] = df['Creation Time'].apply(lambda time: datetime.utcfromtimestamp(time/1000).hour)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x9a0f710>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAEDCAYAAAAlRP8qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x971f9b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['hour_of_day'].value_counts().sort_index().plot('bar')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Experiments failed by the hour of the day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x971f7b8>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x9886160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df['Experiment Status'] == 'FAILED']['hour_of_day'].value_counts().sort_index().plot('bar')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Experiments canceled by the hour of the day"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}