{
 "metadata": {
  "name": "",
  "signature": "sha256:32aa2705fc2a411912d990d943f9130c01a0c08bf7a75a96a81adf27964bde7d"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import synapseclient"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#login to synapse\n",
      "syn = synapseclient.login()  #if you are logging for the first time you need to specify the username and password"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "Welcome, Abhishek Pratap!\n"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#### Provenence for creating training data for Adalimumab"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#get the current synapse entity and then add the entities that were used to produce it\n",
      "\n",
      "ada_training_data = syn.get('syn2754093', downloadFile=False)\n",
      "\n",
      "#adding the things used and executed to produce this\n",
      "ada_training_data = syn.store(ada_training_data,\n",
      "                              used = ['syn2343245', 'syn2343207'],\n",
      "                              executed = ['syn2775464'])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#### Provenence for creating training data for Etanercept"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#get the current synapse entity and then add the entities that were used to produce it\n",
      "\n",
      "etan_training_data = syn.get('syn2754073', downloadFile=False)\n",
      "\n",
      "#adding the things used and executed to produce this\n",
      "etan_training_data = syn.store(etan_training_data,\n",
      "                               used = ['syn2343245', 'syn2343207'],\n",
      "                               executed = ['syn2775464'])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#### Provenence for creating training data for Infliximab"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#get the current synapse entity and then add the entities that were used to produce it\n",
      "inflix_training_data = syn.get('syn2754077', downloadFile=False)\n",
      "\n",
      "#adding the things used and executed to produce this\n",
      "inflix_training_data = syn.store(inflix_training_data,\n",
      "                                 used = ['syn2343245', 'syn2343207'],\n",
      "                                 executed = ['syn2775464'])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#### 2. Now creating the provenance for the final prediction"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#get the final prediction\n",
      "final_prediction = syn.get('syn2484813', downloadFile=False)\n",
      "\n",
      "\n",
      "final_prediction = syn.store(final_prediction,\n",
      "                             used = [inflix_training_data, ada_training_data, etan_training_data],\n",
      "                             executed = ['syn2754070', 'syn2754071', 'syn2754072'])\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}