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     "text": [
      "DataModule v2.3.6\n",
      "SIGGEN v1.5.2\n",
      "Pulse library v2.0.1\n",
      "Sensor reader v2.0.0\n"
     ]
    }
   ],
   "source": [
    "from DIGSIGD import Digsigd\n",
    "from AWGSIGD import Awgsigd\n",
    "from SIGGEN import Siggen\n",
    "from IPLIST import IPList\n",
    "from IQCALIBRATION import *\n",
    "from PULSE import Pulse\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from QUBEXP import Qubexp\n",
    "from UtilitiesLib import check_shared_gen,initialize_shared_gen\n",
    "import DataModule as dm\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# initialize some parameters/instruments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "exp = Qubexp('Freezer')\n",
    "\n",
    "exp.dig = Digsigd(8)\n",
    "exp.awg = Awgsigd(7)\n",
    "exp.sgLO = IPList['Fanta4']\n",
    "exp.sgLOch = 1\n",
    "exp.sgro = IPList['MXG']\n",
    "exp.sgIQLO = IPList['EXG3']\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load HVI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "HVI = exp.dig.sigd.SD_HVI()\n",
    "tmp= HVI.open('/home/oscar/personal-repo/HVIs/awg+dig-chassis2.HVI')\n",
    "if tmp<0:\n",
    "    print('ERROR in opening the HVI: {}\\n'.format(tmp))\n",
    "    raise Exception('HVIERR')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# readout setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "31.25"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "500.0/16"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "exp.readout_setup(HVI,1,channel_amplitude=0.3,LOpwr=12,delay_fix=150,down_freq=31.25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# peak scan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "121"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ro_pulse = Pulse(8.802,Duration=1e3,Delay=0) #Note: AWG pulse seems slow, 300 ns are needed for sync\n",
    "ro_pulse.par['sigpow'] = -5\n",
    "ro_pulse.par['instdelay'] = 180\n",
    "exp.averages= 1\n",
    "sweep = np.arange(8.804,8.81,0.05e-3)\n",
    "len(sweep)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "exp.awg.clear_waves()\n",
    "exp.awg.set_channel()\n",
    "exp.generate_readout_pulse(ro_pulse)\n",
    "initialize_shared_gen(exp.sgIQLO,output=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def IQ_to_amplitude_and_phase(I,Q):\n",
    "    c = (np.sum(I,0)/len(I) + 1j*np.sum(Q,0)/len(Q) )\n",
    "    return np.abs(c),np.angle(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ftqPrPJyVgG6uH02g4UTEWwoZnF6oo66byKWjb/myw8/3ZO1NO5tikUCy79t0OtP60es8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\nTZTrBs7bWvC0tuC9y13bCvj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jwOHSFQJ85Y+ucTvb9ufT6Mun3EZ581XdjYYA4NavPQ7q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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1427883a90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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ftqPrPJyVgG6uH02g4UTEWwoZnF6oo66byKWjb/myw8/3ZO1NO5tikUCy79t0OtP60es8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\nTZTrBs7bWvC0tuC9y13bCvj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jwOHSFQJ85Y+ucTvb9ufT6Mun3EZ581XdjYYA4NavPQ7q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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1427883a90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ro = ro_pulse.copy()\n",
    "measurement_amp = np.ndarray(len(sweep))\n",
    "measurement_ph = np.ndarray(len(sweep))\n",
    "ave=10\n",
    "\n",
    "for i,f in enumerate( sweep):\n",
    "    ro.frequency(np.round(f,12))\n",
    "    exp.generate_readout_pulse(ro)\n",
    "    time.sleep(0.01)\n",
    "    \n",
    "    I,Q = exp.readout_IQ(ro_pulse)\n",
    "    for count in range(ave-1):\n",
    "        tmp1,tmp2 = exp.readout_IQ(ro_pulse)\n",
    "        I += tmp1\n",
    "        Q += tmp2\n",
    "    I /= ave\n",
    "    Q /=ave\n",
    "    \n",
    "\n",
    "    measurement_amp[i],measurement_ph[i] = IQ_to_amplitude_and_phase(I,Q)\n",
    "    \n",
    "    progressive_plot_2d(sweep[:i],measurement_amp[:i],'-o')\n",
    "    \n",
    "    \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot(sweep,measurement_ph,'-o')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ro_pulse.frequency(8.809)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
423
    "data_e = dm.data_table([sweep[:-1],measurement_ph[:-1]])"
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   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
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qALYuKyZmu/z7C82sX1xITUnORb+G09WlKl1KS3E9jd0P2GZJCeYSNXUovncf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\nP0pPgo0PJM7xAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1427a8e128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_g.plot(engine='p')\n",
    "data_e.plot(engine='p',color='r')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.05867681,  0.13100047,  0.47434809,  0.25884587,  0.3349008 ,\n",
       "        0.37331859,  0.05068808,  0.2078128 ,  0.18652742,  0.06579955,\n",
       "        0.23108727,  0.36655149,  0.21678218,  0.05120841,  0.26849868,\n",
       "        0.38783263,  0.23891928,  0.32523668,  0.2094726 ,  0.20757055,\n",
       "        0.35692857,  0.14165355,  0.42854291,  0.19061517,  0.71388717,\n",
       "        0.38383214,  0.42072403,  0.52528852,  0.45831899,  0.09106379,\n",
       "        0.1321099 ,  0.28909524,  0.21388836,  0.18888819,  0.1489761 ,\n",
       "        0.21225261,  0.43873524,  0.06674079,  0.53673795,  0.25097401,\n",
       "        0.47037214,  0.80254856,  0.18971179,  0.62827167,  0.16029798,\n",
       "        0.99436373,  0.0294345 ,  0.00375602,  0.77213866,  0.37836664,\n",
       "        0.10981937,  0.36287821,  0.3429589 ,  0.27497099,  1.71589279,\n",
       "        0.59922602,  0.59774947,  0.41716981,  0.51165314,  0.16681705,\n",
       "        0.62687455,  1.56919644,  0.55274685,  0.85816204,  0.05988168,\n",
       "        0.82472902,  0.1209473 ,  1.47670707,  1.17451923,  0.51940272,\n",
       "        1.28972072,  1.6010486 ,  0.85264411,  0.50594145,  0.13867164,\n",
       "        0.5119408 ,  0.33623679,  0.69735639,  0.02611529,  0.95895958,\n",
       "        0.65109784,  0.4435927 ,  0.88283573,  0.9419947 ,  0.93186209,\n",
       "        0.3408138 ,  0.67041377,  0.86858798,  1.07964665,  0.4610227 ,\n",
       "        1.11052212,  0.20911585,  1.03248826,  0.35389907,  1.21060766,\n",
       "        0.44429101,  1.5061231 ,  1.00081053,  0.86498239,  1.22160131,\n",
       "        0.56512484,  1.39600071,  1.32034757,  1.0441579 ,  1.48468858,\n",
       "        1.25302228,  1.39717278,  1.17124093,  0.8485038 ,  0.9374302 ,\n",
       "        0.04065379,  0.85593347,  2.72962914,  1.06300745,  1.5685232 ,\n",
       "        0.11009581,  2.10423512,  0.11092194,  1.50547721,  1.52161184])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.abs(data_e.y-data_g.y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# qubit-spec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for i in range(2):\n",
    "    exp.awg.amplitude(i,1) #1V to \"open\" the mixer\n",
    "    exp.awg.mode(i,'DC')\n",
    "exp.awg.set_channel('a')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Frequency: 0 MHz\n",
      "Amplitude: 0 V\n",
      "Offset: 0 V\n",
      "Phase: 0 deg\n",
      "Mode: OFF\n",
      "Amplitude Modulation: False\n",
      "Queue elements: 0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "exp.awg.get_channel_parameters(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ex_pulse = Pulse(8.,Duration=100e3)\n",
    "ex_pulse.par['sigpow'] = -50\n",
    "sweep = np.arange(6.44,6.46,0.4e-3)\n",
    "#filename = 'test'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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CJKKBuqW1zXp+vYw2GBqNS6rS5s5/Nn6fIBL0V7yRbtFKWW+msLZKalOTAoSVpr2a8FU/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\nOVBiAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7efc49d5c9b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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CJKKBuqW1zXp+vYw2GBqNS6rS5s5/Nn6fIBL0V7yRbtFKWW+msLZKalOTAoSVpr2a8FU/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\nOVBiAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7efc49d5c9b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "measurement_amp = np.ndarray(len(sweep))\n",
    "measurement_ph = np.ndarray(len(sweep))\n",
    "ave=100\n",
    "\n",
    "for i,f in enumerate( sweep):\n",
    "    ex_pulse.frequency(np.round(f,12))\n",
    "    exp.generate_readout_pulse(ro_pulse)\n",
    "    exp.generate_excitation_pulse(ex_pulse)\n",
    "    time.sleep(0.01)\n",
    "    \n",
    "    I,Q = exp.readout_IQ(ro_pulse)\n",
    "    for count in range(ave-1):\n",
    "        tmp1,tmp2 = exp.readout_IQ(ro_pulse)\n",
    "        I += tmp1\n",
    "        Q += tmp2\n",
    "    I /= ave\n",
    "    Q /=ave\n",
    "    \n",
    "\n",
    "    measurement_amp[i],measurement_ph[i] = IQ_to_amplitude_and_phase(I,Q)\n",
    "    \n",
    "    progressive_plot_2d(sweep[:i],measurement_amp[:i],'-o')\n",
    "    \n",
    "    \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7efc49e33be0>]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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9sRK3RzM8tRjWC3/hwgR7ttRQaeyF29Vaw4tvOLj3rQm9NODLADKbFJvrwot9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\nfKUIcWEgQaoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7efc49d389e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(sweep,measurement_ph,'-o')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Calibration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "awg_pulse = Pulse(6.433845,Duration=200,Shape='g')\n",
    "awg_pulse.par['upmix']=True\n",
    "awg_pulse.par['AM']=True\n",
    "awg_pulse.par"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## On the go"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "calib = IQCalAM(exp.awg,exp.sgIQLO,1,'RS',0.6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "calib.set_awg(awg_pulse.par['awg_freq'],awg_pulse.par['awg_chan1'],awg_pulse.par['awg_chan2'])\n",
    "calib.set_frequency(awg_pulse.frequency(),'R')\n",
    "calib.set_LO()\n",
    "calib.apply_corr()\n",
    "calib.measure_SB(True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "calib.calibrate_offset(0.2,max_num_steps=2)\n",
    "calib.calibrate_offset(0.002)\n",
    "calib.calibrate_amp_ratio_and_phase(0,0.2,2,max_num_steps=2)\n",
    "calib.calibrate_amp_ratio_and_phase(0,0.002,0.05)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "cal_file ='test-{}MHz-freq-{}GHz'.format(calib.calibration.awg_parameters()[0],calib.calibration.frequency()[0])\n",
    "calib.save_calibration(cal_file)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Or load stored calibration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "cal_file ='test-200.0MHz-freq-6.433845GHz.cal'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#the following is used for testing, it will also apply the correction to the AWG channels\n",
    "calib = IQCalAM(exp.awg,exp.sgIQLO,1,'RS',0.6,cal_file)\n",
    "calib.apply_corr()\n",
    "calib.set_LO()\n",
    "calib.measure_SB(True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "awg_pulse.par['calibration'] = cal_file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from SCOPE import Scope\n",
    "sc=Scope()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Rabi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ro_pulse.par['sigpow']=-5\n",
    "#ro_pulse.par['instdelay']= 180\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#exp.averages = 400\n",
    "amplitude_sweep = [0.6]#np.arange(0,1.1,0.05)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc.clear(),sc.run(1)\n",
    "data_rabi = exp.Rabi(amplitude_sweep,ro_pulse,awg_pulse,fit_attempt=False,clear_mem=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "check_shared_gen(exp.sgro)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = sc.read('ch2')\n",
    "a.select([500,1000])\n",
    "a.plot(engine='p')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pi-pulse set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pi_pulse = awg_pulse.copy()\n",
    "pi_pulse.par['sigpow']=0.4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# T1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "delay_sweep = [200]#np.arange(0,10e3,100)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc.clear(),sc.run(1)\n",
    "data_t1 = exp.T1(delay_sweep,ro_pulse,pi_pulse,clear_mem=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = sc.read('ch2')\n",
    "a.select([710,960])\n",
    "a.plot(engine='p')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# T2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "osc_period = 0\n",
    "delay_sweep = [400]#np.arange(0,10e3,20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "hpi_pulse = pi_pulse.copy()\n",
    "hpi_pulse.par['sigpow'] = pi_pulse.par['sigpow']/2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc.clear(),sc.run(1)\n",
    "data = exp.T2(delay_sweep,ro_pulse,hpi_pulse,osc_period,clear_mem=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = sc.read('ch2')\n",
    "#a.select([0,2000])\n",
    "a.plot(engine='p')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# TEcho"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "osc_period = 0\n",
    "delay_sweep = [400]\n",
    "amp_ratio = hpi_pulse.par['sigpow']/pi_pulse.par['sigpow']\n",
    "amp_ratio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc.clear(),sc.run(1)\n",
    "data = exp.TEcho(delay_sweep,ro_pulse,pi_pulse,amp_ratio,osc_period,clear_mem=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = sc.read('ch2')\n",
    "a.plot(engine='p')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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   "display_name": "Python 3",
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   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
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