FFT.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import numpy.fft as fft\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import math\n",
    "import random\n",
    "\n",
    "% matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "random.seed(42)\n",
    "data = np.random.random((128, 128))*65535"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def plotImage(img, cmap='gray', vmin=0, vmax=65535):\n",
    "    fig, ax = plt.subplots()\n",
    "\n",
    "    params = {'axes.labelsize': 20,'axes.titlesize':20, 'font.size': 20, 'legend.fontsize': 20, \n",
    "              'xtick.labelsize': 20, 'ytick.labelsize': 20}\n",
    "    matplotlib.rcParams.update(params)\n",
    "    majorLocator = matplotlib.ticker.MultipleLocator(20)\n",
    "    ax.xaxis.set_major_locator(majorLocator)\n",
    "    ax.yaxis.set_major_locator(majorLocator)\n",
    "    plt.rcParams[\"figure.figsize\"] = [10, 10]\n",
    "\n",
    "    fig = plt.imshow(img, cmap=cmap, vmin=vmin, vmax=vmax)\n",
    "    \n",
    "def plotSpectrum(fftData, cmap='gray'):\n",
    "    fftData2 = np.fft.fftshift(fftData)\n",
    "    #img = np.arctan(fftData2.imag / (fftData2.real + 10e-20))\n",
    "    img = freq = np.fft.fftfreq(fftData, n=1)\n",
    "    #img -= img.min()\n",
    "    #img /= img.max()\n",
    "    #img.real += 10e-20\n",
    "    img = np.log(1 + (img + 10e20))\n",
    "\n",
    "    img -= img.min()\n",
    "    img /= img.max()\n",
    "    plotImage(img, cmap=cmap, vmin=img.min(), vmax=img.max())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Standard distribution equation\n",
    "$$ Y = (\\frac{1}{\\sigma \\sqrt(2\\pi)}) e^{-\\frac{(x - \\mu)^2}{2\\sigma^2}}$$\n",
    "With $\\mu$ the mean and $\\sigma$ the standard deviation\n",
    "\n",
    "FWHM: Full Width at Half Maximum\n",
    "\n",
    "$$FWHM = 2\\sqrt{2 ln(2)} \\sigma $$\n",
    "\n",
    "$$FWHM \\simeq 2.355 \\sigma $$\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Standard distribution equation\n",
    "def stdDist(x, mu, sigma):\n",
    "    '''\n",
    "    Equation of the standard distribution\n",
    "    \n",
    "    Paramaters:\n",
    "    - x: a number\n",
    "    - mu: the mean of the function\n",
    "    - sigma: the standard deviation of the function\n",
    "    '''\n",
    "    equation =lambda x, mu, sigma: 1 / (sigma * math.sqrt(2 * math.pi)) * math.exp(-((x - mu)**2) / (2 * sigma**2))\n",
    "    max = equation(mu, mu, sigma)\n",
    "    return equation(x, mu, sigma) * (1 / max)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0xadcb8d0>]"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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0tHdSdeVFaggWuS4lo2rLi7SmslhH+whmQC4imAHwpKO9E9rdUiFjcqPx/1K7WiqXVgwB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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x9f0b250>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.arange(0, 100., 1)\n",
    "y = np.array([stdDist(p, 50, 10) for p in x])\n",
    "\n",
    "plt.plot(x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "frame = np.zeros((128,128))\n",
    "\n",
    "def drawStar(frame, x, y, sigma):\n",
    "    for horizontal in range(frame.shape[0]):\n",
    "        for vertical in range(frame.shape[1]):\n",
    "            frame[horizontal][vertical] += stdDist(horizontal, x, sigma) * stdDist(vertical, y, sigma) * 65535 / (1.7/sigma)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for i in range(50):\n",
    "    x = random.randint(0, frame.shape[1])\n",
    "    y = random.randint(0, frame.shape[0])\n",
    "    sigma = random.randint(3, 10) / 5\n",
    "    drawStar(frame, x, y, sigma)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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xxgsAACATJl4AAACZMPECAADIhIxXGyELAKBRPvM1Y8aMurenrqta8DvVHLXT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\nOgEAFgj+1OxKU8wAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xace0430>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotImage(frame)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "97223.046395204059"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "completeFrame = frame + data/3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ypPa4444L22B/04vifmXnlOOO6xr3M1vH6MFxzPG7IfPI2C/0kjn3s1Ba9j+/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w9v8kfoMdALkWr9NbohfBbsar7RL6KzQneIz/2lwb4RvQZmUEk1V4UOBp/rL1mypGyDHsOcOXOa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\n3PFFNM51B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y4wlMVU+TydXpArYkrfhD4BHR8XTvfOd76zadNroCviQmnpKdAbo2vmisvS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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xacc89b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotImage(completeFrame)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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VdVbU319VfZjX2YtoJwDAKI5Z0HkfkuQlST6d5PwkH0/yfyX5mSQvT3K/qnpI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\nh/TbXH15elYJbfrsG33zpST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      "text/plain": [
       "<matplotlib.figure.Figure at 0xafba9f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "bins  =  np.linspace(0, 65535, 255)\n",
    "plt.hist(completeFrame.flatten(), bins)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def sigmaClipping(data, sigma=2, iteration=1):     \n",
    "    shape = data.shape\n",
    "    res = data\n",
    "    for i in range(iteration):\n",
    "        referenceValue = res.mean()\n",
    "        stdDev = res.std()\n",
    "        #print(referenceValue - sigma * stdDev)\n",
    "        #np.putmask(res, res<(referenceValue - sigma * stdDev), referenceValue - sigma * stdDev)\n",
    "        #np.putmask(res, res>(referenceValue + sigma * stdDev), referenceValue + sigma * stdDev)\n",
    "        \n",
    "        res[res<(referenceValue - sigma * stdDev)] = referenceValue - sigma * stdDev\n",
    "        res[res>(referenceValue + sigma * stdDev)] = referenceValue + sigma * stdDev\n",
    "        \n",
    "        #res = [cut(e, referenceValue - sigma * stdDev, referenceValue + sigma * stdDev) for l in res for e in l]\n",
    "        #res = np.reshape(res, shape)\n",
    "    return res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "clippedImage = sigmaClipping(completeFrame, sigma=1, iteration=4)\n",
    "#clippedImage -= clippedImage.min()\n",
    "#clippedImage = (clippedImage / clippedImage.max()) * 65535"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11879.120674045398"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "completeFrame.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3707.151466600747"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "completeFrame.std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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5KleE2Wms3SfVtTuJyzZq8QIXcfOU7hiPhWN94sSJ0T7ozVVZYG7dsp5jlQ/U\nsl4qz9T5ai4PaxGO/dWr4/89zT6qfBye96RxvU933l7EeWJcD9W8dU4tx4FOF8/rrtYrXVSuD+Y1\nOiqHqXK+pHlqDvP7x811OqGVa8hzlttHxab6g/PyySeffLzv+3O7vPwVNiXX78ysA5L++i6veUxb\nF2eSpL7vf7Hruq+V9Le1VVLoiKQnJX2PpL/XctEVQgghhLCX2ciFV9/3PyjpBye878OSvmnd7Qkh\nhBBC2Ask9CqEEEIIYSZy4RVCCCGEMBN3okj2HcUFhlIypWRJKZWBd9JYUj54cNi1DBV0IjSF2Urs\ndIGh/JyqEGyLCE6BkPt0xVXZpxRuKTYyNE/yYYSLVEWRpdWLmHLcpLFgzbY/99xzg20ng1YyfcsD\nHByrKQWLKaU6KfnVQlmYorQ0FmpXlWWl1UMTWwoHk0oUd3De8gEWt14qEZy4dnANvfnNb166D9cO\ntrU6P7h5ynOsC+JcxK0XnnO4BvkZbi2sWj7O9QfVYq5jPhTBbdc2ro8pD8lURbPvFC2FpasHNHg+\nbXngh3Ctu4czqoezpgRjP/nkk03tyy9eIYQQQggzkQuvEEIIIYSZyIVXCCGEEMJM7DvH6+bNm4N7\ns7wH6+6FM8CP/gndKhY5lcY+QRUQ6fZR3bdnu5y/RHeIRWzpW7jAP3oK9CnoojmvwTlbi7B/nHtH\nl4r33Pm5U4reMsyQBXylscdCF6ClUCoLrFZhjm6e0oWpjtc5Liw4y+NtcUU476r3OH+Lx8J9uPlA\nWsIaF3HuzNGjRwfbXJdcc+5Y6ag888xuldF23wfbRq+F7pULPmYR+Qp6U64dFey/FlrmOv/GOdTi\npnKuVyGsrj/oAVVhuNevXx/tg+uQ7WIwcuXESf6cuxdxfidhwCwd65aC8QxHrkKMpfEam+KSTfFs\npfziFUIIIYQwG7nwCiGEEEKYiVx4hRBCCCHMxL5zvAjv6zPnShq7EVXRTgfv20/xjSqYb8JC1C2f\ny8LCLBIsjb2fqsC1K+hMV4b3+unwVP6FVLtErsgtM5XowDFTh06HNL73TyeDzpsrCk2n6dq1a6PX\nLPsM1w7C/nGFpTm2nLeVKyGNHa9Vs9KksRtBv5GwndLYnWF2nFsfhPOSc5t+nxs3rsvKV2vJNqpw\nRbJXpWUfdJaqtSDVx1L5jdJ4vOm08bzlPEKex+lFcZ8tRZPptPH80VJSmH3G7yRXeJwuKs+XLfOH\n83COotnxBUhjAAAgAElEQVTO9aXfy3HitvMIefx0aElLUfkKd+1w4cKFlfaxQ37xCiGEEEKYiVx4\nhRBCCCHMRC68QgghhBBmYt85XocPHx7c727JjKm8KOa7uBpozCLh59BhafEreE+ePsrUDJFFpmQ9\n8X66y67h8bN/mHXk6ug5v2gReh0uh6clA2aRFjePfVb5SdLYLXM5TIs4n+vkyZOD7SrHzM11jgNx\nzl8F5wOP1bkk9CtYI5Nj6+bpqh6l6w/WXa1cGTef2KdsV0suE7kTPo40nlN0Qjku7jzGXEQ6tFUW\nljQe78qTc3lRdIOq9TGlNl/Lezj+dEC5T3ceq9pBp9bVE6Znuo45Vc1TV/uW82NKn9Ir5jxlu5yf\nVXnGnJdTzo27kV+8QgghhBBmIhdeIYQQQggzkQuvEEIIIYSZyIVXCCGEEMJM7Du5nkwR98iJEycG\n266QciXXt8j0FFcpQ1Kmd4VSVw2FawkvJBRZXaFtQlmWBY6d/EjZsSqc7IJvOQ7cJ/vYHTvHuxLU\nnejLor6uSHoFx5vtqMJAp+D2wQchqocgXKhk1TaOgwsu5fFSKJ4S9MvPqYq9S+OHbbhOuc+WsMu5\nZPrqcxnCyz534ZZ8uKI6P/BcIK0+d93DKjyfrnpulMYBuhxbCtcMIJbG4jfHnyGs7uGt6lzIfa4a\nyDuVluDrV4ubHwyh5TbP6+58y7nOAO6WtT+lSLyUX7xCCCGEEGYjF14hhBBCCDORC68QQgghhJnY\nd45X3/cDX8gFuBH6V7wnTyrHR2oLsyS8L819MEDTFWOmx8IC1wz7dMGU1b1tFiN2XhSdLXo+vL/O\nwqlTcI4X+5DFZtk/Le4Vx7IqeC2NfRNX0HuRFieQYzeluDu9KIahTgkcJnRYHPTGWNzcHRvDTNkf\ndOLc2E4JTCXVWuexuMBdhma6UNE5YD+zADqLyLu5QC+Ka5//7hweemL0s+haOSeuOp+2rDEX7LyI\nC48mPF/y2Fqo/FbOKTql0ritPG/TxaPbLI2/Tysf2PnQlb/Y4mVzDnGdtrhnVQB1C1wPn/jEJ5re\nl1+8QgghhBBmIhdeIYQQQggzkQuvEEIIIYSZ2HeOlzR0Cuiw0JOSxgWb6VfQe3HFMl1+yyK8f8x7\nw9LYz+K9cLZzin/De+POnakcthbHjffY6QJUHp1rGz0pHv/Vq1dH+6gcHr7HeQ30z+js0FFpyX/h\na+gnMZdGqn2Tyu9z+6gKCbtC7OxTvoY+jvOV2GdcD8yPqo5dGs9LzvUWp2cTsH+czzjFCd0E7DPO\nS7qbLhuNc7dydtzY0oPi2NGJc+e9KtuK72nJ8OPY8Tznxo1zmW4u9+ncXbKOfEpS5fG5z6FHx7F0\nLis9Me6TOWZujnH8q3xGzmvJn9sWqfw1qc0hd+QXrxBCCCGEmciFVwghhBDCTOTCK4QQQghhJjpX\nR+21zKFDh/pl96qd91L1QYtvwZwVOjzMEHKeBzNzmLvC+9QuQ4bHwrbTeXN1BUmVf+NyiVZ1EJx/\nQ7eObW/5jGrs6Aa4+pf0CeiF0U9yDpzLs1mE3qDzoioPqCWnyI3VIpWzIbXlci3ixoB9xPXiHMi9\ngKspymOpMoTulL81BZ63KiewhSnrluc1zkHn3XINVevD1XukX8R98Nzw3HPPjfbBPqNHSj/YrTmO\nA1/Dtrc4onSIWzLJqjwx4uY6x5LfyWy7c2ZPnz492K4yDV12Gr9vCX1wOtaOixcvPt73/bnqdfnF\nK4QQQghhJnLhFUIIIYQwE7nwCiGEEEKYiVx4hRBCCCHMxL6T648dO9Z/+Zd/+SvbFOic7MfioC1h\nlqQSZik1Uxx3f6PIS7m+RWxdNUBUGsufPH4XaEcov25ink2RlNlnp06dGmy78EJKuCyK3RIoSyrB\n2BUv5wMZVXjfZz7zmdHf+J5KMN0UlPg5P9inUx7g2ITEPuUBDgbuOkn3ThyLC5Bk+G11jmk5n/Jh\nJ45t9eCJNBawKYq7QtsUsCu53onx9913X9m2Rdy65fmCBay5rl2fnz17drDNtlK+dw+Yca2zsLR7\n8IwwDJbfDXwoxhWmrx7Q4JxyY7uJIvJVO9yDBXyQJnJ9CCGEEMIeIxdeIYQQQggzkQuvEEIIIYSZ\n2HeO19GjR/sv+7Ive2Wb95h5319a3adgkKc0vrdNl6YKAHSwHVXRaPceHtuUUDi6Zwyjaykuy9fQ\nFXDHsiotRcOnjC1DEuloOJeKMKyQvgA/w3l0DBJkAVp+RguVw+OK3PJzqmBb50jSL6p8HDdudFYq\nn9O5eM7JWdaOKbAdDMyUxv3M8wcDMt26pTfHffCcQ29IGnul7DO2o8W1YR9y/nA9SWPfiOcc9qk7\nf/B8uY5zEH0szm3nSa1anN2F9F64cGGwXZ3H3Fyna8Z20aWa4lFxrFuCbat9ONbhPPJzGCbO85o7\nV3AuP/HEE3G8QgghhBD2ErnwCiGEEEKYiVx4hRBCCCHMxPIgoNcgBw8eXPmeOuG9froCzo2oMlCY\nD+XuUdP7qQpau33QN2JmCotAtzhe9G/Onz8/2G7J4aHH0eJTVAVoOQ50Nhy8r899uNwZ/o39zj53\nDkNVXJbHxiw1aTz+zLZipoxzvtgOZsPRE3Lwcyvfwvlq7DM6KS2FlOns0PFif7gx4D6YuVUVmZf8\nnFmEbWdWljQeK7adDpjzgOh0cZzceYvw+KYUVubx8dxIT8plyfFv/FzOF5dpt2q+Gs830nhd0pOi\n/9qS+0XXjuv6yJEj5T54ruN7nI9Er5JziN9zDvaRO08t4nxGrrmW749Xi8sCIy7XbhHnMk91QPOL\nVwghhBDCTOTCK4QQQghhJnLhFUIIIYQwE/vO8bp58+bgvivv87v7uHQfKv/IZXDRjeE+WnJH6Cnw\nHnxLthHzxKbkNLGGFzlz5sxg29XRYz/TleD9cpeFxYwcunt0R1rciGocWmrPVdl3ziego1LVZ5uS\nZcPjd/O4cnT4Hjc/6OvR0Xjzm9882Hb+I/PkmNPEvCgHPRa+h31MN9FR1VSljyON5y7b0TIunNtc\nHy21PNl2jh1dNPqf0vh4uW7p67n6hu58sMiUuV0dv/M7eQ7isfGc3dIunhu5ntaRQUWPrOU9Ld8N\nbCv7sMWrXEeNxOr82dIO/o2uKsfaeYRcyzwHsd6lc0RbMvoc+cUrhBBCCGEmcuEVQgghhDATufAK\nIYQQQpiJXHiFEEIIIczEvpPrDx48OJBKpwScUXKnhOnkx0qmb2kHJX+G1VFadcFzrjjqMiqRXhqH\nKlLSPXXq1Og9DCekPMywPoqM7nN5/JXEK40Fa7aLAi5f79pG2b5lrClmrlq8272HQjEFU25L47lc\nFZp2oYp8gIMyeRUmLI2Deynt8gEFF+y66trmQyHSWIynlEsxnmPv2sbjbxHj+Rr3UMMibp1XwdF8\nKKKl/9hWPvDiQiWrwuM8f7L4uyRdvXp1sM3+4PnWic8Mcq0Cqh2rSu0OhtBO2QfP09V7XH/wb/x+\n4cNcTqR34b+LtJwLXdjtMlw7uC45L1vCYLmP6vvGzYUEqIYQQggh7HFy4RVCCCGEMBO58AohhBBC\nmImuCjN7rXHo0KF+0clpcWdIdd/WeQ28P05vgV6U8yAYKsmAw5b7ybwHT++D7ZjLc6hwgZn0rXiv\nn86CKwq9attcIeFLly4Nth988MGl+3CfWQXs0gtqKWhM6CvRxWqhKuYt1W4ZfQsXXsj3MLyQPhJD\nWaVxkDHnC30st27ZVgaEtvhZ9K3oPNIlafFP2D88TzuPjs4nP5fro8XvbFljpFpz9OhOnz5d7qNa\nP45Vz/0uhPXy5cuD7Soc14XSVi5qS9Fo9js9qcpnc69hoDALXtPDlKa5y4R9yONnKK/rv+p7rioi\nLtVt52e48HX2x2OPPfZ43/fnlu5Y+cUrhBBCCGE2cuEVQgghhDATufAKIYQQQpiJfZfjdfjw4aX3\n9lvuSVcFjelJSeN7+1Welvt3+lb0PKZkPdGVodPSAl0A7rOlXfRa6Gi44sNVwVE6TGyXNHalWBSa\neUHOnWGmFPuYzoLzYOhL3HfffYNtelDOa6DHUM3lKY4X297iI9E3YW4R/S1p7OzQn6AzSc9OGntf\nbEdLph1dEDpenD8tGWVcx25uE3pPVc6b84Don1V9PMXPmeLM8vz56U9/+lV/Dv/dzVOubTpMVaFl\n9zmV88acQGl8/HQxq9wzaXwOcnmDi9BNk/z31iLr8Pe4D5ct53yrRehWuewwtoNzmxll7jM5tvxu\n5Jp0jldyvEIIIYQQ9ji58AohhBBCmIlceIUQQgghzMS+z/EirgYa70vT0aicL6l2MlruBa8jL4sZ\nQnQS6CC4vBceL++Pu3vdZFWvw43LqvXJXE00Ol0VLfW46C3QQXDZaPQrmAVW+WyubWwX+7zF2VgH\ndKnorKzDq5wCPbELFy6MXkOPgz4ax8nNJ3pinMv0wlytuqqP6JA6b4yeID+XHlTLeYxU/eVg23n8\nzjtd9fzZsm7p79H5avH3CF1M5zRVrhlx/h7fQ0eWa875jTw/ci635InRnaq8uRaqsZ7iNk9xEdln\n/K503i3X0Ec/+tHkeIUQQggh7CVy4RVCCCGEMBO58AohhBBCmIlceIUQQgghzMSscn3XdX9R0j/e\n3vyOvu//vnnN2yV9v6S3SToq6ZOSflrS+/q+LxMRX//61/df+ZVf+co2BVsXxlaF4lHccxLmmTNn\nBtss4MswQxfWtypOZGQhaQbvUfxlMW9pLCZSHmb/sI+lcYAfxcXqM6SxDExxlTKxK8ZcSadsh9sH\nw06vXbu2dJuvl+pCuS1wznBOVZL7uliHyLqOfVRQQHZiPM9/6ygCXEFBWRpLyly3XNfuYQw+BENp\n/eTJk4NtVwSZ54eqkLZ70IbyPOdtS8As5zJDRzmWU+R69s+UOchzlJtjDDKuCq87Mb6al3wIhPPF\ntZXjwvOYe/CqClSuilc7+Ll8GMM9mLVq0XT3IEn1wBfbUQXQStLFixf3llzfdd2Dkn5c0jja9w9f\n882SPiTpnZJ+Yfv1hyT9qKRHZ2hmCCGEEMLGmOXCq9v6iehnJH1W0k/u8pp7JP2UpJclvavv+7/c\n9/33SfpqSb8u6T1d1z08R3tDCCGEEDbBXL94fbekr5f0lyTt9lvleyQ9IOnRvu8/vvPHvu9vaOvW\noyR95yYbGUIIIYSwSTZeJLvruq+Q9MOSfqzv+w91Xff1u7x05++/bP7tQ5KuS3p713WH+74f33ze\n5tatW0vv9/J+sjQOjpsShlo5XWwTCytL04pPE97rZ1vpdLnQ0aqgNe+XO6+hJYxvEVfUtTp++lgt\n/VUVCma73WvouNFRcXOsmg8tgaH8XHpxdA835XgROiksaM1Q3xbY5yxWLY3XHMeffe7W7arhjS37\nYPAix8Wdn5577rml+yR0wKSxO8bxp9PEIuPSOGSWjteVK1cG2674cOWvcr04b6hydnisbs0R55Eu\n4tyqag3xWN2xV54g+5Dz1u2D3hjnT0vINefYqoHVbh90Jl04Ll276nPpWknj+cF98nvNhUlXa7ul\nuH1LwXfHRn/x6rruoLZk+guS/lbx8rdu//cT/Ie+71+S9JS2LhTXb+GGEEIIIczApn/x+i8k/TFJ\n/3bf99UjATuPQ+x2qb7z99FjNl3XPSLpEWm+/5UfQgghhLAqG/vFq+u6P6GtX7n+277vf31TnyNJ\nfd+/v+/7c33fn3O38EIIIYQQ9gIb+cVr+xbjP9LWbcMfaHzbzi9a46Ct4d/rm/mLb2rIFanuZbf4\nJrzHTgejxRXhPeUphWGZd8N73csKiO8GnQPm9LjcqlX71MHisu5zKuiPcD4wg8xlkvFXVDpLdI2c\nT1A5K1V2nKPy6DaRjSWNnaXK33OZQtUv0y3rZVU3s2Xt8z1cT65Pme/DOUSv0u2DjtKU/DDObTqj\ndCJd0fAK+pxTzifsH+dFsY+4fjin3LrlftkfLPjdkuHHedtSJJvwx4EWt6paDzx/8NikcUHzdWTU\n8fzKbDj3XVl9Lr8HmfvmYOYYj9/ND87/qo+da0Y398knnyzbKm3uF6+7Jb1F0ldIutF1Xb/zf5L+\ny+3X/NT23967vf3E9n/fwp1tX8idlfSSpPUnGoYQQgghzMCmHK+bkv7BLv/2x7Xlff2ati62dm5D\nflDSX5D0jZL+Kd7zTknHJH1o2RONIYQQQgh7mY1ceG2L9P+J+7eu635QWxde/xAlgz4g6UckPdx1\n3ft2sry6rjsi6Ye2X/MTm2hvCCGEEMIcbDzHq5W+75/ruu47tHUB9i+7rntU0rOS3q2tqIkPSPq5\naj+HDx8euB+8J+/uL9ODosfAzBg6Pe5zmAlDL8b5Srw/ToeFLknLPfoW54BU3sKUfBdmO9E3cDlW\n9Bacg1G1i44B7/Xz2FwuCx0MN/6LuBpnhD4Os59aYL0+9rnLR6oyluhruQwuZvVw7jOXyPltVbYX\nx9K9nm1d1fmSxnO9mtvMT5LGPgldkKreoTSeM+vw86p6hs7No8+5ah1bB9cgnR1mDzo4l+mZuvPc\nqucxN8eYL1i5uw6e29iHLWt/1Xw51x/8nqPzxna4dtHp47G4XMhVacmzZD4YXUyOvavRTNiHPJaW\nddzKnnoEsO/7X5T0tdoKTP02Sd8l6Zak75H0cD9nRe8QQgghhDUz+y9efd//oKQfXPLvH5b0TXO1\nJ4QQQghhLvbUL14hhBBCCPuZXHiFEEIIIcxEt9+0qUOHDvXLQv2cXEyhlKIeRT4n+1HapvxJnJRK\niZ+hrMQFut1///2D7aqIZ4scyrayuK47Vr6HRUx5rK6dbNuqfSyNhXxu86EHtx7YDhYK5nxzY0sB\nnbInQzYdFGYpkBJXbLcKciUcJ2ksGDMQkp/rxrZ6AIF97o6VYi8fTiFOjOdar9rh+s/1852gKqTM\nNdiyD0Lh2IXjVhJ7Szhu1XaOm3uQ5MyZM4NtziGeT9w+Tp48Odi+++67B9ssRu0kbkrqnKfsLye1\nc71wzfFYW5gSoFqd+7lPF5TMPuXDFpxTriD8qrjvOa5ljj+DXN33LXnsscce7/v+XPW6/OIVQggh\nhDATufAKIYQQQpiJXHiFEEIIIczEnglQXReHDx8e3M/lPecTJ06U+6BfwLBPBwtu0vugW9YS1lfB\nQFVp7NMwvJDhn+7+OYM5SVVc1EFPjn08ZR904Oi3SWOnq/JLXDv4GgZmtrgSDNSlK8JwPje2dAzo\nrDCUtwpLlcahoyxM7tYLHTfO9ZbishUt48I+5bHQL+H8ca/hPlpoaescVI4oPamWYsykZa5zHXKf\n9KLcuqXDxW2eP52/x8+hF3Xjxo3Btgv/pI/FddsS1El3iA4Tz1H8DGkcwspxYED16dOnR/tgW6vQ\nb+d3ss/onnFc3Hcazwfc5ji5drCfqzBlzgVpPO94HuM+GQwtjfujlfziFUIIIYQwE7nwCiGEEEKY\niVx4hRBCCCHMxL5zvF566aWRp7KIy/rhPXfmqvA+dosbUXkfzCByr6Hnw3vwzs9yxbcX4X19l8NT\nwXvwrj+YgcK8F3oNLmOoeg9pcfHOnz8/2G4p+kt/pMp+aoHHxkwhl+tFJ2FKTlNLhlJFS27ZIs5X\no09T7dN9BjOF6HE4r+PVQr9P2js5XvTxXL8v4ty7lmLLiziPkMW5mZfUMgfZNh4L3SHXTnpAPI/z\nfOLyH6si6i0+Hx0vrlt6QjzPu3Zw/bDP3T7YR1WOmetTOsI8/pbMyypvriXTkGPL453i7hLObZcb\nSZeM3y+7kV+8QgghhBBmIhdeIYQQQggzkQuvEEIIIYSZ2HeO18svvzzIr5lSi9DlqCzC+n5uHy2Z\nOYRtZQ0r3td29+Cre9vMWXG156r6hawL1uJoVMfv+nzVGm9uH8wyun379mCb+TiOqu1sl3PvmK9G\nD5HtbHESqvyslrnP11S1PVtfU7Wjcrg4LnRYXDvo6NDxcuuF7gz3SS/oTmV0TaHKT3O5VXSpeM5h\nfznvhWO1au1GaewKcRxazkFsO33OFjePTp/LlFpkmV+8A/OgeN5iTqJUZ9Yxc8rVSFzV56TPJdVz\niv5ri6/F+cJjc+1e9Zzccs7id7bL/SNTa13nF68QQgghhJnIhVcIIYQQwkzkwiuEEEIIYSZy4RVC\nCCGEMBP7Tq4/cODAQJJjSB7laqkOgSMnT54c/a0qSMyQuCnCYIssXO2TgqmTAymuUn5kQdYWKjHe\nBbmuGva5qvTtcHIsHzZgcCdxc4x9Sjh/Wh5YmFqgdRkUfV0gIPujEs5d0XWKzxSOOZYuHHbVgtYU\nw6V6jlVjLY3XkHv45k4wJRyXwcekCpt2n8s+duNAGNJMWbxlnKoHnnied+G4LDZNeZyhtU4+53xg\n0LNbHxU8T7GP+TCCND4+rjm23RWFvnLlymC7Oo+7B434UAPb1fLwBb+DqvDse++9d/Q3PljGAFni\nHsRyx9dCfvEKIYQQQpiJXHiFEEIIIcxELrxCCCGEEGZi3zlefd8PwuZainYS3sdvec/zzz8/2K5C\nWJ0LUBW1pefAIqeOKYGP7LN1FIWu9tFSeLwKmHX99+CDDw626VOwXe4+P50+hhXy3r8bF7p1fA29\nsJbQUQZgtoQG0tugN9ji46zq3jk3gm1jO9jnzgHkODBkku10YcHub4u4MEuyV0NVN9Euric6P1M+\nt8XN5Oe2QE+Mni3Xglv71fygZ+leTxfRhZsu4vqPbePncP24dUvXjNsMcb7vvvtG++BapgPKcWrx\nDLm2Vw3fdu9hf1UOtnsNzyfrcIh3yC9eIYQQQggzkQuvEEIIIYSZyIVXCCGEEMJMdFOLPO5Vjh8/\n3j/00EOvbPP+sLtvzZwqZrPQHXKZIKtm5kwp3s37627s6GfRa7h27dpge65jYR/SUXD5Qc8888xg\nm/4APQZXSLlyQyqHQxq7IHQhWrJcmFtFJ6MFOisuL2wRemXS2C9xfbaIy2nisVS4nKLKvWvpU5en\ntwjnj4MZQsxt4lpw2WGVszMXnMscO1fQehNMcf4Ic5mYwcUcJ5c5xfM4faQqW8/BPq4K1UvjtvOc\nzLnuCktXnzPF56uy0Jy/x3HhsfDc6Ma6yuDisfA7S/LfW8to+U7j51ZenXvPY4899njf9+eqz8ov\nXiGEEEIIM5ELrxBCCCGEmciFVwghhBDCTOy7HK9bt24N7iHTi3GOF+s50o3hdkvmFOF7puRWMfvJ\nORv8G2t60Xtw7VjVJWqBLg336Xwkvof32Okatdz3r9wI1x/0K+gx8N9d3TDOMX4uM6mcN1TVI+Pc\n5mc6psyxp556arBN15D7bMlgoufCjLI3vvGN5T4qj6PFV+M++O9uXOjrcS7TP2LmnzSurcf+aDl+\nzsM7RXUubMkJ5D7oG3EcXE5TNR/Y5y05Tatm2Enj46VXyble1Qx0tLiIPOfSz2I7Xc1R/o1j1/Jd\nuSrOeePfptQCrjxSzqlV3dZl5BevEEIIIYSZyIVXCCGEEMJM5MIrhBBCCGEmcuEVQgghhDAT+y5A\n9ciRI/2izMsANyf7UQikyEqRc4owePbs2cE2BWUHA+0oOk9pB0Mnq2Le0jjwjiGTrig020phlH3q\nAhCrALuW0EAWOqXYys91YZ+kEjlbClzzNS0iPOV5ziE+jEB5uIWWItl8iIGS6uXLl5fuUxo/TEAZ\nmOPG10vjOcR9tBQOJjxfUDjmwylSHf5Kqd9Jupwf99xzz2Cb/eFE+upBmrng+YLw/OFeXz1IwuNv\nCULmeb5lfXBOcR5SwGZQtPtchkWz7e47meetKvjXUa2H6lil8fqoHkhwa5+BqE6er/bB7wb2O//d\nfc/xe2vKwylcl7/2a7+WANUQQgghhL1ELrxCCCGEEGYiF14hhBBCCDOx7wJUu64b3FOnO+ECEBlg\nx3vbvMfswvrIlPvF/Bw6PPTEXDuq8D0WDnaFhNl23sdmn7rwU7pTfE2LB1QVcGbRW+dGrOowtnhj\nVRhqC+xDBhO6dtPx4nyYUgiWtLgRFy5cWNoO4gJDOafonzDE11GFAbf4aqsGYro1R9+G7eLntgQx\n0j+qnEmpzUebA/pG1Rp0fhLnB+fDjRs3ynbwXM8+5djzM6XaV2sJO2VwKT+nZR/VPOW2+/6pgrBb\nir1XThfDkl3/cbwZbsqxnRJqTXh+kerzA9/j+rTlWsCRX7xCCCGEEGYiF14hhBBCCDORC68QQggh\nhJnYd47Xyy+/PLjfS7eIOSTS+B4y79sy76Plnjz3yc91rg3vKdOdYV6QKz5c3aemj9JS0Jn5Ljw2\nl4fTkp9W/Tv7iEVdW+BY0ZVhpkzLPtg/rvA6qYpitxT8rnJ4WnylyhtkppDr8+PHjw+2K9/GeYRs\nKz+3ZY254sqLrKNAL3n66adHf6MbwzXF3CbnmlU+En0t1w5+zhw4L8rlPy0yJYOLWWgtbg379NSp\nU0tfzxw0aXx8XA/0F12OF8eSfitpyQGckvHIPmtxIFeFrqobpylrnTArj7l3XC8ssi6Nz1ucYzzf\nunk6xe+V8otXCCGEEMJs5MIrhBBCCGEmcuEVQgghhDAT+87xIry/7u5903viPWc6G3SepDoDpaWe\nHz0ftoP3tV0+Eu9Ts130k1wGE+9909ngZ6zDDWjJPav60N2DZx/SOWjxCzg/3Pgv4twjZixxrOlN\ntfhJVTsczNCp/EZ3LPfff/9gmy5ES21CujCV9+MyiJxPs4wWr7KiJeuI65T+TUumEMeFLuKZM2dG\n++A6pWfJdqwD1x+cQxzbKe4d284sOdcOnreZC9hy3qIXRj+La9CtF/pGPBbnyZFqfvD84eZ6lcfI\ncWrJ3yN0vFwN2sqLYrucQ8v6jtwnvWzWX5bqupvEOYJTPdL84hVCCCGEMBO58AohhBBCmIlceIUQ\nQgghzEQuvEIIIYQQZmLfy/VkSmFpiotO5GyR5xdx4iIFbHLy5MnBtitgTCghUlR0QjolVAqTVXCn\no1hHmb4AACAASURBVJKnWwIRKbLywQkncfNBAY412+6KujKEl/ug6FyNozQWrLnNPpfGD0Kw+HAV\n2iuNC9KSKQ85VGPn5hjlV7a1GifXDhZSZrvcmqsE61WLaE99D1/TEqhL+BAIBXTu89ixY6N9HD16\ndLDNUNGqMLk0rXg7YR9WBYvdHOO6PXLkyMrtcHL4IhS0p0jtxO2D5xS+hsWrWwpLE64Xt6653+ph\nLkd1/NUDYQ4ePwNV+R0ujecD5zYLb0+ZP7uRX7xCCCGEEGYiF14hhBBCCDORC68QQgghhJno6Im8\n1jl+/Hj/0EMPvbLd4hdUvgC9KBeASM+ncr5cu+i58L41i2K74sP0viofy40/CymTKSGk9C3oZ7kC\nv/RNquLU6yiK7DyxKlSUgZnOreJYEjpdPHZp7N4ROjtslzT2gDj+PH7nQLFt9I+qIsnuc+iK0AGj\nr+T2wWBK/ntLwC7XBx3BqsCxVAfMuhBK+ovsQ7p5PBdIYz+Rn9MS1El4bqQz6uYYWTUwswWuF3f+\n4FjRPeO4OI+ObeM+qnOlNA7epCvENca1II3nIfdRhaFK9Xm7pVg5z21cp/SzWtYL4XxxBa55LmTR\n8JaAXa65VfvYcfHixcf7vj9XvS6/eIUQQgghzEQuvEIIIYQQZiIXXiGEEEIIM7Hvcrxu3rw5uBfb\nkvdS3dumS0RPxuEcjEVa8l6YRULPg/8ujfNKqgwU5yg88MADg236FPTI3L3vymljnz799NNL2ymN\n7+NXOU7S+D4+j5fH5vw9FmiuvBbnc1UOEz+38rkcLATbktHmiqQvwkLD7m9sO30KV8ybfUTPhft0\n64XHV+XatWQMMeuLHqVrB4+FHhTdGvqOrm1VjpfLiuOccoXFV4V9TL/PrYVq7bvjr+D64XxpyVji\n2m9xAKtjaXF32Tb6rS2uGdvGNcXzaUsGF99TZYNJ47Hja/jd0ZK/NyX3jtDv5HeB+86uPofObMux\ntJJfvEIIIYQQZiIXXiGEEEIIM5ELrxBCCCGEmdh3jtcUeL+8yh5xNc5Wrb91/vz50WuYBcZ78C15\nL4T5Ni25O8ypon9C12zKffyWrKcq/6elRmQ1LnS8XK4ZvYVV/921o6pF546tyt3h2Losn2vXri39\nXHovLtesaivb2eIAEmbquCwf+kb0sehZsvaao8q6ch4QnZ3q2Jw7QyeHfUxPiGvUfS77nZ6L8/eq\nen306Dif3Odyfbj3VPA9PDc6quNtWXOrOjwuw49UmX4O+npsF89jbmxX3WfL9xz7jOvDtYN91PKd\nRPi5XIM8NpfzVkGPsuU8dvHixaZ95xevEEIIIYSZyIVXCCGEEMJM5MIrhBBCCGEmcuEVQgghhDAT\nG5fru677U5L+qqQ/Kek+SZ+V9JuSfqzv+1/Ca98u6fslvU3SUUmflPTTkt7X931ThdcDBw4MhGDK\noU6gXDV40BXs5X65T4p5LWGOFNBbZPpKfiQtgjphEOHJkyfL/VbtcsIpj5/iM+XZlv4hfKChBRZB\nJi1CLmXQKhxWGkvKlF8pdrqxpbTOfbKPXaBsJdNTsHWSfwUF3JZi7i6odRHXH5xjVeHtlmBKwrnN\nsZfGBa45tnxwwMF2VKGjDo4lx65lbldrmw89tEjLDILmtpPtOVZ8GIP903JslNj5kAMDeKXx3OU+\nGGLc0h/8fuE8dQ+BVIXYW4JMVw07dcGl7pyy7DNaittX3/MtY8s5xG33QMuUB0WkDV94dV33dyV9\nn6RLkv4XSVclPSDpIUnvkvRLC6/9Zkk/L+mGpJ+T9KykPyfpRyW9Q9K3b7KtIYQQQgibZmMXXl3X\nfYe2Lrr+oaRH+r5/Ef/+uoX//x5JPyXpZUnv6vv+49t//wFJH5T0nq7rHu77/tFNtTeEEEIIYdNs\nxPHquu6wpL8j6YLMRZck9X2/GN7xHm39EvbozkXX9mtuaOvWoyR95ybaGkIIIYQwF51zJ171Trvu\nz0r6Z5Leq61fvf49SX9EW7cRP9b3/a/j9f9E0l+Q9B/0ff9P8W8HJf2+pEOS7u77fixILHDo0KF+\nsVjwlHu9LD7dErzIe9mnT59+1Z974sSJlfdROSouEHMOpoS/klX9NfceunVVYKZUuzJ0J5y/V/lq\nxHlz9DroirT4SGwH28qgQRZ8lurAWLpXLeeYaixbfBO6Uy3FmFcNyHS+Gvv56tWrg22eP9zY0uGq\nCo1PLc5bwbZVbtmU8OQW5636HDpxPN+6dpDqXOlew89tCSollWvlzh88X3Cdsh0tPh9dO/qfx48f\nH72HfUrflQW+nRdFf5Hrh5/h2lGdg1qcao53FYTsztl0DX/rt37r8b7vzy1tnDZ3q/Hf2v7vDUm/\noa2Lrlfouu5Dkt7T9/3OqLx1+7+f4I76vn+p67q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zjcc6pbA0z7ctvhph/zz44INLX98C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yMtjhOdBGbEsD+iHC9C34L9EfUp3RjW5eS2tLgjhL5F5ipKuTfG/SgNa3NmuV6rTOafLaPW6xiX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\nMxH/HwAXWdPtaurJAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xacc83f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotImage(clippedImage)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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3Jrk0yVFVdUxrbf3UftYlOSHJN5I8vbX2/bH+zCRfSnJWVV3cWts0dfg3JDkkyYYkR7fW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\nXBQ+FwwvUwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x9bbca70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bins  =  np.linspace(0, 65535, 255)\n",
    "plt.hist(clippedImage.flatten(), bins)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "fourierTransform = fft.fft2(completeFrame)\n",
    "fourierTransform = np.fft.fftshift(fourierTransform)\n",
    "fourierTransform -= fourierTransform.min()\n",
    "fourierTransform /= fourierTransform.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "n should be an integer",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-236-2d583bc948aa>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mfourierTransform\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mfft\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfft2\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcompleteFrame\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mplotSpectrum\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfourierTransform\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m<ipython-input-235-f0b7138afb58>\u001b[0m in \u001b[0;36mplotSpectrum\u001b[0;34m(fftData, cmap)\u001b[0m\n\u001b[1;32m     15\u001b[0m     \u001b[0mfftData2\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfft\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfftshift\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfftData\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m     16\u001b[0m     \u001b[1;31m#img = np.arctan(fftData2.imag / (fftData2.real + 10e-20))\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m---> 17\u001b[0;31m     \u001b[0mimg\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mfreq\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfft\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfftfreq\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfftData\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     18\u001b[0m     \u001b[1;31m#img -= img.min()\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m     19\u001b[0m     \u001b[1;31m#img /= img.max()\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\numpy\\fft\\helper.py\u001b[0m in \u001b[0;36mfftfreq\u001b[0;34m(n, d)\u001b[0m\n\u001b[1;32m    162\u001b[0m     \"\"\"\n\u001b[1;32m    163\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0minteger_types\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m--> 164\u001b[0;31m         \u001b[1;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"n should be an integer\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    165\u001b[0m     \u001b[0mval\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m1.0\u001b[0m \u001b[1;33m/\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mn\u001b[0m \u001b[1;33m*\u001b[0m \u001b[0md\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    166\u001b[0m     \u001b[0mresults\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mempty\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mint\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: n should be an integer"
     ]
    }
   ],
   "source": [
    "fourierTransform = fft.fft2(completeFrame)\n",
    "plotSpectrum(fourierTransform)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(194627513.1235598+0j)"
      ]
     },
     "execution_count": 229,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fourierTransform.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "oneStar = np.zeros((128,128))\n",
    "drawStar(oneStar, 128/2,128/2,3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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NYFbBa+66+5I8p7X2idba3a21Lyb5oQzfcnxaVZ26Fm/WWruwtXZya+3ktbgeAMAszOpW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\nasF7eovKAwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xacd66b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotImage(oneStar)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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PXOScAAA2y8LOeAEA8O2EFwDAIMILAGAQ4QUAMIjwAgAYRHgBAAwivAAABhFeAACDCC8A\ngEGEFwDAIMILAGAQ4QUAMIjwAgAYRHgBAAwivAAABhFeAACDCC8AgEGEFwDAIMILAGAQ4QUAMIjw\nAgAYRHgBAAwivAAABhFeAACDCC8AgEGEFwDAIMILAGAQ4QUAMIjwAgAYRHgBAAwivAAABhFeAACD\nCC8AgEGEFwDAIMILAGAQ4QUAMIjwAgAYRHgBAAwivAAABhFeAACDCC8AgEGEFwDAIMILAGAQ4QUA\nMIjwAgAYRHgBAAwivAAABhFeAACDCC8AgEGEFwDAIMILAGAQ4QUAMIjwAgAYRHgBAAwivAAABhFe\nAACDCC8AgEGEFwDAIMILAGAQ4QUAMIjwAgAYRHgBAAwivAAABhFeAACDCC8AgEGEFwDAIMILAGAQ\n4QUAMIjwAgAYRHgBAAyy0PCqqp+qqkur6vNVdUtVXVNV76iqx6wxfmdVXVxV18/jP1FVZ1TVIYuc\nJwDACAsLr6p6ZZL3JPnnSS5J8rokH0vy5CQfqqqnrRj/5CRXJDk2yUVJ3pDknklem+TCRc0TAGCU\nbYt40qp6YJIXJPn7JD/S3V9eduyEJJcl+dUkF8z77pvkvCR3JDm+u3fP+186jz2lqk7tbgEGAByw\nFnXG64fm5/5/lkdXknT3+5J8PcmRy3afMt+/cCm65rG3JnnJfPdZC5orAMAQiwqvzyT5ZpJHV9X9\nlx+oqmOT3CfJny3bfeK8vWSV57oiyZ4kO6vq0AXMFQBgiIWEV3dfn+RFSb4vyV9W1blV9etV9YdJ\nLk3yp0n+w7KHPGLeXrXKc92e5LOZXhZ96CLmCwAwwkLe45Uk3X1OVV2b5HeTnLbs0NVJzl/xEuT2\neXvjGk+3tP+I1Q5W1elJTp+e6Af3d8oAAAu1yJ9q/KUku5Kcn+RhSe6V5MeSXJPkbVX1qo36Wt19\nbnfv6O4dh3/bW8cAALaOhYRXVR2f5JVJ/qi7z+zua7p7T3d/LMnPJPm7JGdV1dJLh0tntLZ/57N9\n2/4bFjFfAIARFnXG60nz9n0rD3T3niQfmb/2o+bdn563R68cX1XbkhyV5PZMZ8sAAA5IiwqvpZ8+\nXOt1v6X935y3l83bx68y9tgkhye5srtv25jpAQCMt6jw+sC8Pb2qHrz8QFU9IckxSW5NcuW8e1eS\n65KcWlU7lo09LMnL57tvXNBcAQCGWNRPNe7KdJ2uf5XkU1V1UZIvJXlkppchK8l/7O6vJkl331RV\np82Pu7yqLkxyfZKTMl1qYleSty9orgAAQywkvLr7zqp6YpJnJzk10xvqD88UUxcn+a3uvnTFY95V\nVccleXGSpyQ5LNOlJ86cx/ci5goAMMoir+P1rSTnzLf1PuZDSZ64qDkBAGymhV3HCwCAbye8AAAG\nEV4AAIMILwCAQYQXAMAgwgsAYBDhBQAwiPACABhEeAEADCK8AAAGEV4AAIMILwCAQYQXAMAgwgsA\nYBDhBQAwiPACABhEeAEADCK8AAAGEV4AAIMILwCAQYQXAMAgwgsAYBDhBQAwiPACABhEeAEADCK8\nAAAGEV4AAIMILwCAQYQXAMAgwgsAYBDhBQAwiPACABhEeAEADCK8AAAGEV4AAIMILwCAQYQXAMAg\nwgsAYBDhBQAwiPACABhEeAEADCK8AAAGEV4AAIMILwCAQYQXAMAgwgsAYBDhBQAwiPACABhEeAEA\nDCK8AAAGEV4AAIMILwCAQYQXAMAgwgsAYBDhBQAwiPACABhEeAEADCK8AAAGEV4AAIMILwCAQYQX\nAMAgwgsAYBDhBQAwiPACABhEeAEADCK8AAAGEV4AAIMILwCAQYQXAMAgwgsAYJB1hVdVnVJVr6+q\nD1TVTVXVVXXBPh6zs6ourqrrq+qWqvpEVZ1RVYfs5TFPr6qPVNXNVXVjVV1eVU+6q98UAMBWtN4z\nXi9J8pwkP5rk7/Y1uKqenOSKJMcmuSjJG5LcM8lrk1y4xmNek+T8JA9Kcl6SC5L8syR/XFXPWec8\nAQC2rPWG1/OTHJ3kvkmetbeBVXXfTOF0R5Lju/vnu/uFmaLtw0lOqapTVzxmZ5Kzkvx1kh/p7ud3\n97OT/FiS65O8pqoest5vCgBgK1pXeHX3+7r7M93d6xh+SpIjk1zY3buXPcetmc6cJd8Zb78wb3+t\nu7+27DHXJvntJIcmecZ65goAsFUt4s31J87bS1Y5dkWSPUl2VtWh63zMn6wYAwBwQFpEeD1i3l61\n8kB3357ks0m2JXloklTVvZI8OMnN3f3FVZ7vM/P26I2fKgDAOIsIr+3z9sY1ji/tP2I/x3+Hqjq9\nqnZX1e49+cq6JwoAMNJBcR2v7j63u3d0947Dc+RmTwcAYFWLCK+lM1Tb1zi+tP+G/RwPAHBAWkR4\nfXrefsd7sqpqW5Kjktye5Jok6e5vZLo22L2r6kGrPN/D5+13vGcMAOBAsojwumzePn6VY8cmOTzJ\nld192zof84QVYwAADkiLCK9dSa5LcmpV7VjaWVWHJXn5fPeNKx7zpnn74qq637LHPCTJs5PcluQt\nC5grAMAw29YzqKpOTnLyfPeB8/YxVXX+/OvruvsFSdLdN1XVaZkC7PKqujDT1edPynSpiV1J3r78\n+bv7yqr6zSRnJvlEVe3K9BFDP5vke5I8d76YKgDAAWtd4ZXp436evmLfQ+dbknwuyQuWDnT3u6rq\nuCQvTvKUJIcluTpTWP3WalfA7+6zquqTmc5wnZ7kziQfS/Lq7n7Pur8jAIAtqtb3KUAHjn9SO/r0\n7N73QACADfKy1Ee7e8e+xh0U1/ECADgQCC8AgEGEFwDAIMILAGAQ4QUAMIjwAgAYRHgBAAwivAAA\nBhFeAACDCC8AgEGEFwDAIMILAGAQ4QUAMIjwAgAYRHgBAAwivAAABhFeAACDCC8AgEGEFwDAIMIL\nAGAQ4QUAMIjwAgAYRHgBAAwivAAABhFeAACDCC8AgEGEFwDAIMILAGAQ4QUAMIjwAgAYRHgBAAwi\nvAAABhFeAACDCC8AgEGEFwDAIMILAGAQ4QUAMIjwAgAYRHgBAAwivAAABhFeAACDCC8AgEGEFwDA\nIMILAGAQ4QUAMIjwAgAYRHgBAAwivAAABhFeAACDCC8AgEGEFwDAIMILAGAQ4QUAMIjwAgAYRHgB\nAAwivAAABhFeAACDCC8AgEGEFwDAIMILAGAQ4QUAMIjwAgAYRHgBAAwivAAABhFeAACDCC8AgEGE\nFwDAIMILAGAQ4QUAMIjwAgAYZF3hVVWnVNXrq+oDVXVTVXVVXbDG2IdX1Yuq6rKq+tuq+mZV/X1V\nvbuqTtjH13l6VX2kqm6uqhur6vKqetL+fGMAAFvNes94vSTJc5L8aJK/28fY/yPJK5J8X5KLk/xG\nkg8l+akkl1XV81Z7UFW9Jsn5SR6U5LwkFyT5Z0n+uKqes855AgBsWdvWOe75ST6f5OokxyV5317G\nXpLkld398eU7q+q4JH+a5NVV9Y7u/uKyYzuTnJXkr5P8eHd/bd7/6iQfTfKaqnpPd1+7zvkCAGw5\n6zrj1d3v6+7PdHevY+z5K6Nr3v/+JJcnuWeSnSsO/8K8/bWl6Jofc22S305yaJJnrGeuAABb1eg3\n139r3t6+Yv+J8/aSVR7zJyvGAAAckIaFV1X9UJLHJtmT5Ipl+++V5MFJbl7+8uMyn5m3Ry98kgAA\nC7Te93jdLVV1aJK3ZXrJ8JeWv5yYZPu8vXGNhy/tP2Ivz396ktOnJ/vBuzdZAIAFWfgZr6o6JMlb\nkxyT5O1JXrPRX6O7z+3uHd294/AcudFPDwCwIRYaXnN0XZDkqUn+MMnTVnmD/tIZre1Z3dL+GzZ+\nhgAA4ywsvKrqHkn+IMmpSf5Lkn/X3SvfVJ/u/kama4Pdu6oetMpTPXzeXrWouQIAjLCQ8KqqeyZ5\nR6YzXb+f5Oe6+469POSyefv4VY49YcUYAIAD0oaH1/xG+ouSPDnJ7yR5RnffuY+HvWnevriq7rfs\nuR6S5NlJbkvylo2eKwDASOv6qcaqOjnJyfPdB87bx1TV+fOvr+vuF8y/flOSJya5LtNLiL9SVSuf\n8vLuvnzpTndfWVW/meTMJJ+oql2ZLrT6s0m+J8lzXbUeADjQrfdyEj+a5Okr9j10viXJ55IshddR\n8/b+SX5lL895+fI73X1WVX0y0xmu05PcmeRjSV7d3e9Z5zwBALasWsenAB1Q/knt6NOze7OnAQB8\nF3lZ6qPdvWNf40Z/ZBAAwHct4QUAMIjwAgAYRHgBAAwivAAABhFeAACDCC8AgEGEFwDAIMILAGAQ\n4QUAMIjwAgAYRHgBAAwivAAABhFeAACDCC8AgEGEFwDAIMILAGAQ4QUAMIjwAgAYRHgBAAwivAAA\nBhFeAACDCC8AgEGquzd7Dhuqqr6S5HPz3fsnuW4Tp3MwsqYby3puPGu68azpxrOmG2+z1/SHuvvI\nfQ066MJruara3d07NnseBxNrurGs58azphvPmm48a7rxDpQ19VIjAMAgwgsAYJCDPbzO3ewJHISs\n6caynhvPmm48a7rxrOnGOyDW9KB+jxcAwFZysJ/xAgDYMoQXAMAgB114VdX3V9XvVtUXquq2qrq2\nqs6pqvtt9ty2oqr63qp6ZlVdVFVXV9UtVXVjVX2wqn6+qlb9PVJVO6vq4qq6fn7MJ6rqjKo6ZPT3\ncKCoqqdVVc+3Z64xxrruQ1U9dv79+qX5z/gXquq9VfXEVcZaz32oqp+qqkur6vPzGl1TVe+oqses\nMf67fk2r6pSqen1VfaCqbpr/TF+wj8fc5XWrqqdX1Ueq6ub57+XLq+pJG/8dbb67sqZV9fCqelFV\nXVZVf1tV36yqv6+qd1fVCfv4Opu/pt190NySPCzJ3yfpJO9K8ookl833/yrJ9272HLfaLckvzOvz\nhSRvS/LrSX43yQ3z/l2Z3wu47DFPTnJ7kpuT/E6SV8/r20nesdnf01a8JfmBeU2/Pq/TM1cZY133\nvY6vmtfjbzO9kfb/THJeko8leZX1vMvr+cp5Pa5L8ub578xdSb6Z5M4kT7Omq67bX8zf89eTfGr+\n9QV7GX+X1y3Ja5b9Xn9tkt9O8tV533M2ew02c02TXDgf//+S/F/zv1v/97zGneR5W3lNN32xN/g/\n3HvnBXzuiv2/Oe9/02bPcavdkpyY5KeT/KMV+x+Y5G/mdXvKsv33TfLlJLcl2bFs/2FJrpzHn7rZ\n39dWuiWpJH+W5K/nv3C/I7ys67rW8bR5Hc5Pcs9Vjt/Det6l9XxgkjuSfCnJA1YcO2Feo2us6apr\nd0KSh89/to/fRyTc5XVLsnPef3WS+y3b/5A5FG5N8pDNXodNXNP/NcmjVtl/XKb/abgtyYO26ppu\n+mJv4H+0h82L+tl8Z0TcJ9P/aXwjyb02e64Hyi3JL89r+vpl+/63ed/vrTL+xPnY+zd77lvpluQX\nM509ODbJ2Vk9vKzr3tfw0Pkfr89llehaZbz13Pca/cS8Du9e4/hNSb5uTfe5jvuKhLu8bkl+f97/\njFUe86vzsZdt9ve+WWu6j8demhUnDLbamh5M7/Fael330u6+c/mB7v56kg8lOTzJT46e2AHsW/P2\n9mX7Tpy3l6wy/ooke5LsrKpDFzmxA0VVPTLTyzev6+4r9jLUuu7dv05yZKaXE+6c35f0oqr6xTXe\ni2Q99+0zmc4OPLqq7r/8QFUdm+l/WP9s2W5run/2Z9329pg/WTGGb7fav1vJFlrTgym8HjFvr1rj\n+Gfm7dED5nLAq6ptSf79fHf5b9Q117m7b890xnFbkocudIIHgHkN35rpJdtf3sdw67p3Pz5vb03y\n8STvyRS05yS5sqreX1XLP5zWeu5Dd1+f5EVJvi/JX1bVuVX161X1h5nOGvxpkv+w7CHWdP/cpXWr\nqnsleXCSm7v7i6s8n3/L1lBVP5TksZli9opl+7fUmm4b8UUG2T5vb1zj+NL+IwbM5WDwiiQ/nOTi\n7n7vsv3Wef1+JcmjkvyL7r5lH2Ot6949YN6+MMlfJvmXmd6Me1SmN8w+Lsk7Mr1EkVjPdenuc6rq\n2kw/UHPaskNXJzm/u7+8bJ813T93dd2s836Yzxi+LdPbEn6pu7+27PCWWtOD6YwXG6SqnpfkrEw/\ndfNzmzxhm5dvAAAEPklEQVSdA1JV/USms1y/0d0f3uz5HASW/q66PclJ3f3B7r65uz+Z5GeSfD7J\ncWtdAoHVVdUvZfopxvMzvU/2Xkl+LMk1Sd5WVa/avNnB+syX5HhrkmOSvD3T/4xtWQdTeC0V6/Y1\nji/tv2HAXA5YVfWcJK/LdFbhhPnliOWs8z7MLzH+fqaXFl66zodZ171b+r4/3t3XLj/Q3Xsy/URz\nkjx63lrPfaiq4zNdTuKPuvvM7r6mu/d098cyxezfJTmrqpZeOrSm++eurpt1vgvm6LogyVOT/GGm\nS6D0imFbak0PpvD69Lxd6zXah8/btd4D9l2vqs5I8vok/z1TdH1plWFrrvMcHEdlOitxzaLmeQC4\nd6b1eWSSW5ddNLWT/Kd5zHnzvnPm+9Z175bWZ62/GJdeVvjHK8Zbz7UtXTTyfSsPzDH7kUz/Rjxq\n3m1N989dWrfu/kam6L13VT1olefzb9msqu6R5A+SnJrkvyT5d/P75r7NVlvTgym8lv7yeFytuNp6\nVd0n0ynIPUn+2+iJHQiq6kWZLij3F5mi68trDL1s3j5+lWPHZvrJ0Su7+7aNn+UB47ZMF0lc7fbx\necwH5/tLL0Na173780w/7v1PV/75nv3wvP3svLWe+7b0U3RHrnF8af8356013T/7s257e8wTVoz5\nrlRV98z0vs6nZnqF4ee6+469PGTrrOlmX69jI29xAdX9XbeXzuuzO8n37GPsfZN8JS6iuL9rfXbW\nvoCqdd372r17Xofnr9j/uEzXSftaku3Wc93r+W/ndfhSkgevOPaEeU1vyfyJH9Z0zXU8Pvu+gOpd\nWrdsoYt9btE1PTTJf53HvDkrrt25xmO2zJrW/IUPClX1sEy/kR+Q6S/pT2W6SOAJmU4h7uzur27e\nDLeeqnp6pjfW3pHpZcbVfurj2u4+f9ljTs70htxbM310w/VJTsr0Y9O7kvzbPph+Y22gqjo708uN\np3X3m1ccs657UVXfn+nP9w9kOgP28Uwv05yc//GP1zuXjbeeezGfOXxvkn+V6WNaLsoUYY/M9DJk\nJTmju1+37DHWNP+wDifPdx+Y5N9keqnwA/O+67r7BSvG36V1q6rfSHJmph8c2ZXknkl+Nsn3Zjq5\n8IaFfHOb5K6saVW9JdPV669L8p8z/flf6fLuvnzF19gaa7rZZbuAUv6BJG9J8sVMp8g/l+laP/fb\n7LltxVv+xxmYvd0uX+VxxyS5ONNZhluSfDLJ85Mcstnf01a+ZY0zXtZ13et3ZKb/Qfjc/Of7ukzB\n8GjruV/reY8kZ2R6C8ZNmd5r9OVM10l7nDVdc9329ffmtRuxbpni4v/N9KkrX0/y/iRP2uzvf7PX\nNMnl6/h36+ytuqYH1RkvAICt7GB6cz0AwJYmvAAABhFeAACDCC8AgEGEFwDAIMILAGAQ4QUAMIjw\nAgAYRHgBAAwivAAABvn/ASJB/NYBMvY0AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xe39c30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "oneStarFFT = fft.fft2(oneStar)\n",
    "plotSpectrum(oneStarFFT, cmap='rainbow')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-12.19182398+0.04908581j, -14.16094514+0.05701374j,\n",
       "        -14.23347153+0.05730574j, ...,  -3.01446859+0.01213663j,\n",
       "         -5.82547463+0.02345409j,  -9.11247164+0.03668795j],\n",
       "       [ -7.07249184+0.02847474j,  -9.61566534+0.03871387j,\n",
       "        -10.31303408+0.04152157j, ...,   3.58594786-0.01443748j,\n",
       "          0.37272162-0.00150062j,  -3.43818185+0.01384255j],\n",
       "       [ -1.19133592+0.00479647j,  -4.18456530+0.01684758j,\n",
       "         -5.52745814+0.02225424j, ...,   9.87771506-0.03976892j,\n",
       "          6.69341433-0.02694852j,   2.73387443-0.01100692j],\n",
       "       ..., \n",
       "       [-21.20637757+0.08537953j, -21.09537806+0.08493263j,\n",
       "        -20.02313856+0.08061566j, ..., -21.62332600+0.08705822j,\n",
       "        -21.14563172+0.08513496j, -21.03672247+0.08469648j],\n",
       "       [-19.31534652+0.077766j  , -19.89016241+0.08008028j,\n",
       "        -19.04302407+0.0766696j , ..., -16.11439472+0.06487857j,\n",
       "        -16.90369343+0.06805639j, -18.07817156+0.07278498j],\n",
       "       [-16.29221636+0.0655945j , -17.58826300+0.07081255j,\n",
       "        -17.13245273+0.0689774j , ...,  -9.71056295+0.03909594j,\n",
       "        -11.66768917+0.04697558j, -14.03795589+0.05651857j]])"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oneStarFFT.imag *= -1\n",
    "result = fourierTransform * oneStarFFT\n",
    "resultImg = fft.ifft2(result)\n",
    "resultImg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#resultImg = resultImg.real**2 + resultImg.imag**2\n",
    "resultImg = resultImg.real"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "resultImg -= resultImg.min()\n",
    "resultImg /= resultImg.max()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "resultImg.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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RkWmWLTNmZq8DXlf+enj5+BIzu6T8933u/p7y3+cBR5nZVoqq/QDHAqeU/z7H3bemaFen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\nQgghxAT5/xJ+yP/NZmSNAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xb206530>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "params = {'axes.labelsize': 20,'axes.titlesize':20, 'font.size': 20, 'legend.fontsize': 20, \n",
    "          'xtick.labelsize': 20, 'ytick.labelsize': 20}\n",
    "matplotlib.rcParams.update(params)\n",
    "majorLocator = matplotlib.ticker.MultipleLocator(5)\n",
    "ax.xaxis.set_major_locator(majorLocator)\n",
    "ax.yaxis.set_major_locator(majorLocator)\n",
    "plt.rcParams[\"figure.figsize\"] = [10, 10]\n",
    "\n",
    "#fig = plt.imshow(fourierTransform.real, cmap='gray', vmin=0, vmax=65000)\n",
    "fig = plt.imshow(resultImg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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EgsxcWipeSZKkJpQ6KHw68GfAvXRJxAAy85mWy/lUK2ZLRxOxes4GqteWAB8u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\nSz6FtgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xb0184d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "oneStarFFT = np.fft.ifftshift(oneStarFFT)\n",
    "newOneStar = fft.ifft2(oneStarFFT).real\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "\n",
    "params = {'axes.labelsize': 20,'axes.titlesize':20, 'font.size': 20, 'legend.fontsize': 20, \n",
    "          'xtick.labelsize': 20, 'ytick.labelsize': 20}\n",
    "matplotlib.rcParams.update(params)\n",
    "majorLocator = matplotlib.ticker.MultipleLocator(5)\n",
    "ax.xaxis.set_major_locator(majorLocator)\n",
    "ax.yaxis.set_major_locator(majorLocator)\n",
    "plt.rcParams[\"figure.figsize\"] = [10, 10]\n",
    "\n",
    "#fig = plt.imshow(fourierTransform.real, cmap='gray', vmin=0, vmax=65000)\n",
    "fig = plt.imshow(newOneStar)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  2.47094761e-13,   1.92624954e-13,   1.20349224e-12, ...,\n",
       "          4.52733275e-13,   2.01443811e-12,  -1.11291372e-12],\n",
       "       [ -1.18383235e-12,   6.70875397e-13,  -1.78639872e-12, ...,\n",
       "          7.33066663e-15,  -2.55465322e-12,   1.99576058e-12],\n",
       "       [  1.83367899e-14,   3.80180345e-13,   7.98975957e-13, ...,\n",
       "          5.43147501e-13,   1.39828801e-12,  -9.06546884e-13],\n",
       "       ..., \n",
       "       [ -1.26324664e-12,   1.00304225e-12,  -2.16473822e-12, ...,\n",
       "         -3.83011917e-13,  -1.89227392e-12,   1.81591525e-12],\n",
       "       [  1.07667282e-12,  -7.50821131e-13,   2.08955950e-12, ...,\n",
       "          1.14798619e-13,   2.32236312e-12,  -1.78012012e-12],\n",
       "       [  7.91403587e-13,  -1.16089340e-12,  -4.77376342e-13, ...,\n",
       "         -6.09009802e-13,  -1.45518761e-12,   2.26563286e-13]])"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newOneStar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "testArray = np.array([[1,0,0,0,0,1],\n",
    "                     [0,0,0,0,0,0],\n",
    "                     [0,0,0,0,0,0],\n",
    "                     [0,0,0,0,0,0],\n",
    "                     [0,0,0,0,0,0],\n",
    "                     [1,0,0,0,0,1]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "testArray2 = np.roll(testArray, 6*6//2)\n",
    "testArray2 = [np.roll(testArray[i], 3) for i in testArray]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[array([[0, 0, 0, 0, 0, 0],\n",
       "        [0, 0, 0, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 0, 0, 0]]), array([[0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0]]), array([[0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0]]), array([[0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0]]), array([[0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0]]), array([[0, 0, 0, 0, 0, 0],\n",
       "        [0, 0, 0, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 1, 0, 0],\n",
       "        [0, 0, 1, 0, 0, 0]])]"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testArray2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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