src/plot_example.ipynb

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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# SARK-110 Plot example\n",
    "\n",
    "Simple Jupyter notebook example for interacting with the SARK-110 Antenna Analyzer.\n",
    "\n",
    "Please ensure that the analyzer is connected to the computer using the USB cable and in Computer Control mode."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from sark110 import *\n",
    "import math\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Enter frequency limits:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "fr_start = 12000000   # Frequency start in Hz\n",
    "fr_stop =  15000000   # Frequency stop in Hz\n",
    "points = 51           # Number of points"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Utility functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def z2vswr(rs: float, xs: float, z0=50 + 0j) -> float:\n",
    "    gamma = math.sqrt((rs - z0.real) ** 2 + xs ** 2) / math.sqrt((rs + z0.real) ** 2 + xs ** 2)\n",
    "    if gamma > 0.980197824:\n",
    "        return 99.999\n",
    "    swr = (1 + gamma) / (1 - gamma)\n",
    "    return swr\n",
    "\n",
    "\n",
    "def z2mag(r: float, x: float) -> float:\n",
    "    return math.sqrt(r ** 2 + x ** 2)\n",
    "\n",
    "\n",
    "def z2gamma(rs: float, xs: float, z0=50 + 0j) -> complex:\n",
    "    z = complex(rs, xs)\n",
    "    return (z - z0) / (z + z0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Connect to the device"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "Device connected\n"
    }
   ],
   "source": [
    "sark110 = Sark110()\n",
    "sark110.open()\n",
    "sark110.connect()\n",
    "if not sark110.is_connected:\n",
    "    print(\"Device not connected\")\n",
    "    exit(-1)\n",
    "else:\n",
    "    print(\"Device connected\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "2566 1.5\n"
    }
   ],
   "source": [
    "sark110.buzzer()\n",
    "print(sark110.fw_protocol, sark110.fw_version)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Acquire the data"
   ]
  },
  {
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   "execution_count": 6,
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   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "start: 12000000 stop: 15000000 points: 51\n"
    }
   ],
   "source": [
    "y = []\n",
    "y1 = []\n",
    "x = []\n",
    "rs = [0]\n",
    "xs = [0]\n",
    "print(\"start:\", fr_start, \"stop:\", fr_stop, \"points:\", points)\n",
    "for i in range(points):\n",
    "    fr = int(fr_start + i * (fr_stop - fr_start) / (points - 1))\n",
    "    sark110.measure(fr, rs, xs)\n",
    "    x.append(fr / 1e6)\n",
    "    y.append(z2vswr(rs[0][0], xs[0][0]))    # VSWR\n",
    "    y1.append(z2mag(rs[0][0], xs[0][0]))    # ZMAG"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot the data (single axis)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
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y7mJ4KK29ygcU8Caud6ALMuQKlFSpuC6FCMCZ68VQqbU0PMMTFPAmrk+QKwAg6cZdjishQnBUJoejtXn9cxaEWxTwJq6bryNsLCRIpIAnbaTR3lt7dUiIO8xp+gteoF4wceYSMaICXJCYRQFP2ib5dilKqlQYTsMzvEEBT9A3yBXXCxUoqqzluhRixI6myWEuEWGQAdcYIK1DAU/Qt8M/4/A36Sye6O6ITI4+Qa6wtzLnuhTyDwp4gi7eDrCzNKNhGqKzrCIFbhRV0d0zPEMBT2AmEaNXgDNdaCU6uz+52DCaPZJXWFvw45dffsGvv/4KAKitrYVMJsO5c+fg4ODAVgnkIfp2cMWJa0WQVyjh4UATRJHW+eNqAbr6OMLHyZrrUsgDWDuDf+qpp5CQkICEhASEh4dj2bJlFO480jfIDQDwF53Fk1bKL6/B5TtlGN3Fk+tSyL+wPkRz5coVZGZmYvLkyWwfmjxEmLcDHKxoHJ603sGrBQBAAc9DrA3R3Ldp0ybMnj272fdlMplO+1UqlTp/lm+4akuYuwVOp+dDJtPPXRDUJ/yk77b8cj4P7Z3MoSq+A1mx3nbbIkLpF0O1g9WAr6iowI0bN9CnT59mtwkNDdVp3zKZTOfP8g1XbRlebIn3D8jg5B0AL8e2j6VSn/CTPttSrKhFauENvDK0E0JDg/Wyz9YQSr+0tR1SqbTJ11kdorlw4QL69evH5iFJK9y/H56GaUhLHU6VQ8sAj9PwDC+xGvA3b96Er68vm4ckrRDq6QAnG3MKeNJif1zNR4CrDTp72nNdCmkCq0M0M2bMYPNwpJXEYhEeC3Sh++FJi5RX1yEx6y6mRwfS3O88RQ86kQb6Brkip7QGd0qquS6F8NxRmRxqLYPHu3hxXQppBgU8aaDPP+PwdD88eZQ/rhbA29EK3X0duS6FNIMCnjQQ3M4eLrYWNExDHkpRq8bp60UY1cWThmd4jAKeNCAWi9AnyAV/Zd0FwzBcl0N46kR6IVRqLQ3P8BwFPGmkb5Ar8sqVuE3j8KQZB68WwM3OApHtaWk+PqOAJ430pXF48hDKOg1OXCvEyHBPSMQ0PMNnFPCkkQ7udnCzs6T74UmTTmcUoVqloYebjAAFPGlEJLo3Dp94g8bhSWMHrxbA0docfYJcuS6FPAIFPGlS/45ukFfUIrNQwXUphEdUai2OyOQYEeYBcwnFB99RD5EmDfxn4eRTGUUcV0L45M+sYlQq1TQ8YyQo4EmTfJys0amdHQU8aeCPKwWwszRD/45uXJdCWoACnjRrULA7km6UoFql5roUwgO1ag3+uJqPkWEesDKXcF0OaQEKeNKsQSHuUGm0SLpRwnUphAfOZBSjQqlGTHdvrkshLUQBT5rVK8AF1uYSGqYhAIB9KXlwtjHHgE40PGMsKOBJs6zMJejbwZUCnqBapcaRNDke7+pFd88YEeop8lCDgt1xs7gK2XeruC6FcOiYrBA1dRrEdKPhGWPCasBv2rQJkydPxlNPPYVdu3axeWiio0F0uyTBveEZDwdL9A504boU0gqsBXxSUhIuXbqEHTt2ICEhAQUFBWwdmrRBgJst2rva4NQ1CnhTVV5Th1PXivBEV2+ae8bIsLZk39mzZxEcHIzZs2dDoVBg4cKFbB2atNGgYHfsupiDWrUGlmZ0e5ypOZRaAJVGi3E9aHjG2Dw04EtKSmBlZQUbG5v617Zv3464uLhWH6i0tBR5eXnYuHEjcnJy8PLLL+PgwYONFguQyWSt3jcAKJVKnT/LN3xrS5C1EjV1Guw+nYKeXtYt/hzf2tEWptyWHefy4WlnBovKPMhk+QasrPWE0i+GakezAb9p0yb8/PPP0Gg0WLlyJdq3b4+5c+fCzs5Op4B3cnJCUFAQLCwsEBQUBEtLS5SUlMDVteGERaGhoa1vBe79YdD1s3zDt7b4B6mx6tQR3FJaI64VdfGtHW1hqm0pqqxFSsENvDy4A8LCOhu4stYTSr+0tR1SqbTJ15sdgz9w4AAOHDiAHTt24PPPP8cLL7yAZ555Blu2bNGpgMjISJw5cwYMw0Aul6OmpgZOTk467Yuwy9bSDL0CnWkc3gT9cTUfWgYY192H61KIDpo9g3d0dISFhQU8PDwgl8uxbt06hIeH63ygIUOG4MKFC5g4cSIYhsHbb78NiYTGc43FoGB3rPo9HfnlNfBybPkwDTFu+y7nIcTDHiGe9lyXQnTQbMA/ODbu5eXVpnC/jy6sGq9Bwe2w6vd0nM4owuRe/lyXQ1iQW1aDi9mlmD8ymOtSiI6aDXi5XI6ffvoJDMOgsLAQP/30U/17kydPZqU4wh/BHnbwdLDCKQp4k/FbSh4A0NwzRqzZgI+JiUFRUVGjfxPTJBKJMCjYHb9fzYdao4UZPa4uePtS8tDd1xHtXW25LoXo6KFj8NHR0QgICGCxHMJng0Lc8dPFO7h8pwxRAfREo5BlFSmQmleBZU8Y/x0qpqzZgC8rK8Nbb72FkpIS9O7dG9HR0ejTp0+De+KJaenf0Q0SsQinMooo4AVuf0oeRCJgLM09Y9SaDfhXX30VAKBSqXDp0iVcuHAB3377LcRiMb777jvWCiT84Whtjp5+TjiVUYR5I0O4LocYCMMw+PVSLh4LdIGnoxXX5ZA2eOhAqkqlwl9//YUjR47g7NmzsLGxwdChQ9mqjfDQoGB3/J1TjqLKWq5LIQZyMbsU2XerMTHSj+tSSBs1ewY/a9Ys5Ofno1evXoiOjsb8+fNhZUV/zU3dsFAPfHwkA8fT5XQ3jUDtlubAxkJCC2sLQLNn8Gq1GtbW1rC1tYWdnR0sLCzYrIvwVKiXPXydrXE4Vc51KcQAlHUaHPg7H6O7eMLWkrW5CImBNNuDX3/9NZRKJRITE/Hbb7/Vz0czaNAgTJgwgc0aCY+IRCKMDPPEtqRsVNWqKQQE5lBqASpr1ZgY4ct1KUQPHjoGb2VlhSFDhiA2NhYTJ05EYWEhNmzYwFZthKdGhHlApdbiNC0CIji7k3Ph42SNPkGuj96Y8N5Dz+AvXryIrKwshIaGol+/fli9ejX8/Wnc1dT1CnCGk405Dv+zRicRhoJyJc5eL8LsIR0hpoU9BKHZgK+trcV//vMfdOnSBWIxPbVI/sdMIsawzh44KpOjTqOlRZgF4tdLudAywFM0PCMYzf5mzpgxA5cuXYJIJIJcLsecOXMwf/58mrKAAABGhnugvKYOF26WcF0K0QOGYbA7OQeR7Z0R6EZTEwhFswG/cuVK5OXlQavVYvny5ejcuTNGjRqF5cuXs1ge4auBndxhZS7G4TS6m0YI/s4pR2ahAk/T2bugNBvwubm5WLx4MdRqNaRSKWbOnIkRI0agpITO2AhgbSHBgI7uOJxaAIZhuC6HtNHu5BxYmonxRDe6piIkzQb8/fngk5OT0bVrV5ibmwO4NzZPCHBvmCavXInUvAquSyFtUKvWYF9KHkaGe8LR2pzrcogeNXuR1cbGBj/99BMOHjyImJgYaLVa7N69G15euv+FnzBhAuzt760M4+vri9WrV+u8L8K9YZ3bQSwCDqfJ0cXHketyiI5OpBeirLoOT0fQsnxC02zAd+/eHbdv38aIESPw1FNPITExEcePH8d7772n04Hun/knJCToVinhHVc7S0QFuOBwagHeGEGr/hirn6U5aGdviehO7lyXQvSs2SGagoICHDp0CBkZGZDJZOjbty++/PJLuLvr9kOQnp6OmpoaTJs2Dc8++ywuX76sc9GEP0aGeSC9oBK371ZzXQrRQbGiFievFeHJnj6Q0L3vgtNswC9duhR//PEH+vTpg7Vr12LKlCnYtWsXampqdDqQlZUVpk+fji1btuDdd9/F/PnzoVardS6c8MOIMA8AwOG0Ao4rIbrYezkPai2DpyPp7hkhEjEtvAWisLAQ33//PXbt2oWkpKRWH0ilUkGr1dbPSDlx4kSsX7++wZi+VCrVeUERpVIpmNkuja0tL+/LgZ2FGB+Nbrg4hLG142GE2BaGYTB7fy7MxCJ8NtY4x9+F0i9tbUd1dTUiIyMbvf7ImaJqa2tx5MgR7NmzB1VVVViwYIFOBfz888/IyMjA8uXLIZfLoVAomhzuCQ3VbYkwmUym82f5xtjaMu6OGJ+fyISHfwe42P5v1lFja8fDCLEtybdLcbP0JlY92RWhocY5BYlQ+qWt7ZBKpU2+3mzAJyUlYc+ePUhKSsKwYcOwcOFCBAfrfiFt4sSJWLx4MWJjYyESibBq1SqYmdFMhEIwIswTnx3PxDGZHM9E0SIRxmJ70m3YWkgwrgctyydUzSbs+vXrMXnyZLz77rt6mQvewsICH3/8cZv3Q/ini48DvBytcDiNAt5YlNfU4be/8/BkT1/Y0ZTPgtVsz27bto3NOogRuzdHvAd+vHAH1So1bCwoMPhuz6VcKOu0mPqYcQ7NkJahaQCJXowK90StWosT6TQZHd8xDIPtSbfRzdeRHlATOAp4ohePBbminb0l9lzO5boU8giyolpck1cirjedvQsdBTzRC4lYhJju3jh5rRBl1SquyyEP8UdGBewszRDTnS6uCh0FPNGbCT18UKdh8MdVeuiJr8qr63D6VhXG9/Cm9XRNAAU80ZsuPg4IcrPFnks0TMNXv1zKgUrDII4urpoECniiNyKRCON7+OD8rRLklek2pQUxnPsXV0PcLBHuTRdXTQEFPNGr8T28wTDA/pQ8rksh/yLNLsX1QgUeD7bnuhTCEgp4olcBbrbo7ueEvZcp4Plme9Jt2FuaYVCAHdelEJZQwBO9G9/dG2n5Fcguo7tp+KKsWoXfruRjQk8fWJnTr72poJ4meje2uxfEIuDkDQXXpZB/7E7OhUqtRSzd+25SKOCJ3rWzt0L/jm44eVNBC3LzgFbLYHtSNnr4OSHM24HrcgiLKOCJQYzv4YMChRrJt8u4LsXkncksRlZRFZ7vF8B1KYRlFPDEIEaFe8BCIsJemrqAc9+cvYl29pYY09Xr0RsTQaGAJwZhb2WOx3xtcODvfNRptFyXY7IyCytxKqMI8X3aw8KMft1NDfU4MZghQXa4W6XC2cxirksxWd+euwULMzE9uWqiKOCJwUT62MDBygz76J54TpRVq7A7OQdP9vCBq50l1+UQDrAe8Hfv3sWgQYOQlZXF9qEJyywkIjzRzQuHUgtQrVJzXY7J2XH+DpR1WrwwIIDrUghHWA34uro6vP3224JYBZ20zPgePqhWaXCQZphkVZ1Gi+8Tb6F/R1d09qRbI00VqwH/4YcfYsqUKWjXrh2bhyUc6h3gggBXG/x4/g7XpZiUg1cLkF+uxAv9ArkuhXCItQmhf/nlF7i4uCA6OhpfffVVs9vJZDKd9q9UKnX+LN8IpS1KpRLXrqVjSHsrfJtcgsN/pcDPse0LuHPB2Ppkw9FceNmbwQt3IZOVNHjP2NryMEJpi6HawVrA7969GyKRCImJiZDJZFi0aBG+/PJLuLu7N9guNDRUp/3LZDKdP8s3QmnL/Xb8x7cWCZeP4XyxOUb2Mc52GVOfJN8uRXrRDSyPCUN4WOMzeGNqy6MIpS1tbYdUKm3yddYC/ocffqj/d3x8PJYvX94o3IkwudtbYkSYB3Yn52DB6BBYmkm4LknQvj13C/aWZpgY5cd1KYRjdJskYUVsb3+UVtfhUKqc61IELb+8Br9fycfkXn6woyX5TB4nAZ+QkIAOHTpwcWjCkQEd3eDrbI0dSbe5LkXQEhKzwTAMnqN5ZwjoDJ6wRCwWYUovPyTeuIubxVVclyNIVbVq/JB0GyPCPODnYsN1OYQHKOAJa56J8oNELMKPF+gs3hB+SMpGeU0dZg2i/x2TeyjgCWs8HKwwrHM77JbmQKWmCcj0SVmnweYzN9G/oyt6+jtzXQ7hCQp4wqrY3v4oVqhwVEYXW/Vp18U7KKqsxezBHbkuhfAIBTxh1cBgd3g7WmHHeRqm0Zc6jRYbT91AT38n9O3gynU5hEco4AmrJGIRJvXyw5nrxbhTUs11OYKw93Iecstq8MqQjhCJRFyXQ3iEAp6wblKUH8Qi0MVWPdBoGXxxMhOdPe0xtDPN8UQaooAnrPN2ssaQkHbYdTGHVntqo0OpBbhRVIXZdPZOmkABT6IydecAABJPSURBVDgxpbc/CitrcTSNLrbqimEYbDiRiSA3W1pvlTSJAp5wYkiIO3ydrbHl7E2uSzFaJ68VITWvArMGd4BETGfvpDEKeMIJM4kY0wcE4mJ2KaTZpVyXY3QYhsHnJzLh42SNJ3v6cF0O4SkKeMKZSVF+cLQ2x+bTN7guxegk3SyBNLsULw0KgrmEfo1J0+gng3DG1tIM/9fHH4fSCnCL5qdplQ0nMuFmZ4lJNCUweQgKeMKp5/oGwFwsprH4Vjh/swRnrhdjZnQgrMxpbn3SPAp4wql2DlaY0NMbu6R3UFKl4roc3mMYBv89mI529pZ4tm8A1+UQnqOAJ5ybER0EZZ0W2/7K5roU3jsmK8TF7FK8NrwTrC3o7J08HGsBr9FosHjxYkyZMgVTp07F7dv0FCO5J9jDHkNC3PHdn7egrNNwXQ5vabQMPjp0DYFutjT2TlqEtYA/ceIEAODHH3/EnDlzsHr1arYOTYzAzIFBuFulwq+Xcrkuhbf2Xs7FNXkl5o0MpjtnSIuwtmjj8OHDMXjwYABAXl4e3Nzc2Do0MQJ9g1zRxccBm8/cwOQoP4jpwZ0GatUafHIkA118HDCmCz21SlpGxDAMw+YBFy1ahCNHjuCzzz7DgAEDGrwnlUphY6PbUmNKpRJWVlb6KJFzQmlLa9tx8oYCH54pxDtDPNDH39aAlbUe132yV1aOjefv4v3hnoj0adtyfFy3RZ+E0pa2tqO6uhqRkZGN32A4UFhYyAwePJipqqpq8PrFixd13mdaWlpby+INobSlte1QqTVMv9XHmGe+/NNAFemOyz6pVNYxEe8dZqZsSmS0Wm2b9yeUny+GEU5b2tqO5rKTtYG8PXv2YNOmTQAAa2triEQiSCR0FwD5H3OJGNMGBOL8rRJcuk3TF9y35cxN3K1SYeHoEJoxkrQKawE/cuRIpKWlYerUqZg+fTqWLFkCS0tLtg5PjMTkXvemL/j06HWuS+GFu4pabD5zA6PDPWmtVdJqrF1ktbGxwbp169g6HDFSdpZm+M/gDlj9Rzr+unEXfYJMewm6L05moVqlxvxRwVyXQowQ3WtFeOe5fgHwcLDEfw+mg2H3HgBeuX23GgmJ2ZgY6YuO7ey5LocYIQp4wjtW5hK8PjwYybfLcFRWyHU5nHnvt1SYSUR4Y0QI16UQI0UBT3jpmUhfBLrZ4qND6dBoTe8s/ni6HEdlhXhtWCd4Ohr/bYCEGxTwhJfMJGLMGxmMDLkCe0zs6VZlnQbv7k9DB3dbvNA/kOtyiBGjgCe8NaaLF7r4OGDt0QzUqk1njprNp28g+2413h3XBRZm9CtKdEc/PYS3xGIRFo7qjJzSGuxIMo3J6XJKq7HhZCbGdPXEgE40nQdpGwp4wmvRndzQN8gV649nQlGr5rocg3v/NxlEEGHpE2Fcl0IEgAKe8JpIJMLC0SG4W6XCNwJf9el0RhEOphbglaEd4eNkzXU5RAAo4Anv9fR3xsgwD2w+fUOwqz6p1Fos35+KAFcbzIimC6tEPyjgiVGYPyoEVSo11h3N4LoUg9hy9iZuFFXhnXHhsDSjOZqIflDAE6MQ7GGPqY+1x/d/ZePvnDKuy9Gr3LIarD9+HSPCPDAkpB3X5RABoYAnRmPB6BC42Vliya9XoNZouS5HL7RaBgt2pUAE4O2xdGGV6BcFPDEaDlbmeHtsGK7mVuD7RGEs0P194i38mXUXy8aGwc+lbQt5EPJvFPDEqIzt5oWBwe74+PA15JfXcF1Om9woUuCDg+kYHOKOKb1oEW2ifxTwxKiIRCK8P74L1FoG7+5L47ocnak1WryxMwWWZhJ8+HQ3WsiDGAQFPDE6/q42mDOsEw6mFuCYTM51OTrZdPoGLt8pw3vjw+HhQJOJEcNgLeDr6uqwYMECxMXFYeLEiTh27BhbhyYCNDM6CJ3a2eHtvamoVhnXE65peRX49GgGnujqhXHdvbkuhwgYawG/b98+ODk5Yfv27di8eTNWrFjB1qGJAFmYibHyya7ILavBOiNa3q9WrcEbOy/D0doCKyZ0oaEZYlCsBfzo0aPx2muv1X9NC26Ttuod6IJJUb74+uxNyPIruC6nRdYdvY70gkp88FRXuNhacF0OETgRw/KaaAqFAi+//DImTZqEmJiYBu9JpVLY2Oh2q5hSqYSVlTDGMoXSFjbaUaHUYOaeO3CzNcPaMd6wkBjmnEUfbbkqr8GiQ/kY1sEOb/Tn7oEmofx8AcJpS1vbUV1djcjIyEavs7boNgDk5+dj9uzZiIuLaxTu94WGhuq0b5lMpvNn+UYobWGrHZ9YumPG9xfxSxaDd8cb5nhtbYu8QokPd59Fe1dbfPJ//WBvZa7H6lpHKD9fgHDa0tZ2SKXSJl9nbYimuLgY06ZNw4IFCzBx4kS2DktMwPAwD8wYEIjvErNx8Go+1+U0olJr8fI2KapVamz8v0hOw52YFtYCfuPGjaioqMAXX3yB+Ph4xMfHQ6lUsnV4InALR3dGd19HLPj5b9wpqea6nAbeP5CG5Ntl+O/EbgjxtOe6HGJCWBuiWbZsGZYtW8bW4YiJsTATY31sBJ747Axe2XEJu17qy4vl7nZLc/B9YjZmRgdibDe6JZKwi/vfAEL0xN/VBh883Q0pd8qw5vA1rsvB1dxyLPn1CvoEuWDR6M5cl0NMEAU8EZQnunnh//r446vTN3A8nbunXMuqVZi1TQoXWwt8HhcBMwPd3UPIw9BPHRGcZU+EobOnPebtTOFkQjKNlsGcHy+jsKIWX0yNgJudJes1EAJQwBMBsjKXYMPUCNSqtZi1LZnVqQwYhsG7+1NxOqMIy8eFo6e/M2vHJuTfKOCJIHVwt8PayT1wJacMs7YlQ6VmZ4GQT45k1F9Uje1NUwATblHAE8EaFe6JVU92xemMIiz4OQVarWEf2v7qdBbWH8/ElF5+WDImlOaZIZxj9UlWQtg2pbc/7lap8NGha3CxtcDbY8MMErw7zt/Gqt/T8UQ3L6x8siuFO+EFCngieP8Z3AF3FSp8c+4m3OwsMXtIR73uf39KHpb8egWDQ9yxdlIPSMQU7oQfKOCJ4IlEIix7IhQlVbX46NA1uNpaYEpvf73s+0R6Ieb+dBlR7Z3x5dRIXjxcRch9FPDEJIjFInz0THeU1dRhya9X4Ghtjse7erVpn6cyijBrmxQhnvbY8nwvWFvQFNiEX+h0g5gMc4kYX0yNQA8/J/xnezI2nMjU6cIrwzDYeCoLL3x7HoFutvh+Wm840ARihIco4IlJsbEww7YZjyGmmzc+OnQNs7ZJUamsa/Hnq1VqvLLjEj74Ix2Pd/HC7pf7wZUeZCI8RQFPTI6NhRnWTemBt8aG4Vh6IcZ/fg7X5ZWP/Fz23So89cWf+ONKPt58vDM+j+sJW0sa5ST8RQFPTJJIJML0AYH4YcZjqFDWYfyGc/j9SvNzyUtzqzHu83PIL1di6wu9MWtQB7oVkvAenX4Qk9YnyBW/vRqNl3+Q4j8/JGN4qAcszERQ1mmhrNOgpk4DZZ0W6fkVCPG0x1fxUfB31W1ZSULYRgFPTJ6noxV+fLEPPvgjHUdlcliaSWBtLoGVuRh2lmZwtZUgzEWEFZP7wMaCfmWI8WD9pzUlJQVr1qxBQkIC24cmpFmWZhK8ExOOd2LCm3xfJpNRuBOjw+pP7ObNm7Fv3z5YW1uzeVhCCDFJrF5k9ff3x/r169k8JCGEmCwRwzCGnWLvX3JycvDGG29g586djd6TSqVslkIIIYIRGRnZ6DVeDSo2VSAhhBDd0H3whBAiUBTwhBAiUKwHvK+vb5Pj74+SkpKC+Ph4APduWYuLi0N8fDymT5+O4uLiBttqtVq8/fbbmDx5MuLj45Gdna2X2vWlNW0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     },
     "metadata": {}
    }
   ],
   "source": [
    "plt.style.use('seaborn-whitegrid')\n",
    "plt.plot(x, y)\n",
    "plt.title('SARK-110')\n",
    "plt.xlabel('Freq MHz')\n",
    "plt.ylabel('VSWR')\n",
    "plt.ylim(1., 10.)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot the data (dual axis) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "plt.style.use('seaborn-whitegrid')\n",
    "fig, ax1 = plt.subplots()\n",
    "ax2 = ax1.twinx()\n",
    "ax1.plot(x, y, 'g-')\n",
    "ax2.plot(x, y1, 'b-')\n",
    "ax1.set_xlabel('Freq MHz')\n",
    "ax1.set_ylabel('VSWR', color='g')\n",
    "ax2.set_ylabel('|Zs|', color='b')\n",
    "fig.tight_layout() \n",
    "plt.title('SARK-110')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sark110.close()"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3.7.4 64-bit",
   "language": "python",
   "name": "python37464bit1448d8e03fd74e318aaf556afec8eee6"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4-final"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}