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 "cells": [
{
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Job Status: job has successfully run\n"
     ]
    }
   ],
   "source": [
    "#running\n",
    "from qiskit.tools.monitor import job_monitor\n",
    "qiskit.IBMQ.load_account()\n",
    "provider = qiskit.IBMQ.get_provider('ibm-q')\n",
    "backend = provider.get_backend('ibmq_5_yorktown')\n",
    "job = qiskit.execute(circuit,backend,shots=1024)\n",
    "job_monitor(job)\n",
    "result = job.result()\n",
    "noisy_measurements = result.get_counts()    #returns dictionary, with output string as keys \n",
    "                                            #and count as the respective value\n",
    "\n",
    "#get the result which occurred the most\n",
    "measurements = max(noisy_measurements, key=noisy_measurements.get)"
   ]
  },
  {
   "source": [
    "#Final Answer\n",
    "query_state = measurements[-1]\n",
    "print('Prediction:')\n",
    "if query_state == '1':\n",
    "    print('Balanced')\n",
    "else:   #constant query\n",
    "    aux_output = measurements[0]\n",
    "    if aux_output == '1':\n",
    "        print('Constantly One')\n",
    "    else:\n",
    "        print('Constantly Zero')\n",
    "\n",
    "print('Truth:')\n",
    "print(oracle_type)"
   ],
   "cell_type": "code",
   "metadata": {},
   "execution_count": 8,
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Prediction:\nConstantly Zero\nTruth:\nConstant0\n"
     ]
    },
    {
     "output_type": "execute_result",
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\n"
     },
     "metadata": {},
     "execution_count": 8
    }
   ]
  }
 ]
}